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+15
-1
@@ -211,10 +211,24 @@ COSYVOICE_CLONE_MODEL=voice-enrollment
|
||||
# 用于 AI 文案生成、智能剪辑等需要大模型能力的场景
|
||||
|
||||
DOUBAO_API_KEY=your-doubao-api-key
|
||||
DOUBAO_MODEL=doubao-seed-1-6-250615
|
||||
DOUBAO_MODEL=doubao-seed-2-1-pro-260915
|
||||
DOUBAO_FAST_MODEL=doubao-seed-2-1-lite-260915
|
||||
DOUBAO_BASE_URL=https://ark.cn-beijing.volces.com/api/v3
|
||||
DOUBAO_TIMEOUT=30
|
||||
DOUBAO_MAX_RETRIES=2
|
||||
# 视觉模型:pro 精度高,lite 速度快(viral-video 商品识别默认用 lite 提速)
|
||||
DOUBAO_VISION_MODEL=doubao-seed-2-1-pro-260915
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||||
DOUBAO_VISION_LITE_MODEL=doubao-seed-2-1-lite-260915
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||||
DOUBAO_VISION_USE_LITE=true
|
||||
# Embedding 向量化模型
|
||||
DOUBAO_EMBEDDING_MODEL=doubao-embedding-vision-251215
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||||
# 视频模型(Seedance 2.5,统一走方舟;真人参考图通过信任链自动 AI 化)
|
||||
DOUBAO_VIDEO_MODEL=doubao-seedance-2-5-260628
|
||||
DOUBAO_VIDEO_TIMEOUT=480
|
||||
DOUBAO_VIDEO_POLL_INTERVAL=10
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||||
# 图片模型(Seedream 5.0 Pro,用于信任链真人 AI 化 + 文生图)
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||||
DOUBAO_IMAGE_MODEL=doubao-seedream-5-0-pro-260628
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||||
DOUBAO_IMAGE_TIMEOUT=120
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||||
|
||||
# ==================== 积分/会员系统 (#1895) ====================
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# 积分系统总开关:默认 false(暂停积分系统)。
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|
||||
@@ -0,0 +1,25 @@
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"""viral video add image_analysis column
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Revision ID: 087_viral_video_image_analysis
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Revises: 086_add_viral_video_tables
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Create Date: 2026-09-30
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#2106 爆款视频 P0:持久化图片分析结果(image_analysis JSON),供 resume 阶段使用。
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||||
"""
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||||
|
||||
import sqlalchemy as sa
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||||
|
||||
from alembic import op
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||||
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||||
revision = "087_viral_video_image_analysis"
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||||
down_revision = "086_add_viral_video_tables"
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||||
branch_labels = None
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||||
depends_on = None
|
||||
|
||||
|
||||
def upgrade() -> None:
|
||||
op.add_column("viral_video_jobs", sa.Column("image_analysis", sa.JSON(), nullable=True))
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||||
|
||||
|
||||
def downgrade() -> None:
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||||
op.drop_column("viral_video_jobs", "image_analysis")
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||||
@@ -0,0 +1,51 @@
|
||||
"""viral video add copy_result + voice/video columns
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||||
|
||||
Revision ID: 088_viral_video_copy_result
|
||||
Revises: 087_viral_video_image_analysis
|
||||
Create Date: 2026-10-01
|
||||
|
||||
v1.6 爆款视频字段补齐:
|
||||
- copy_result JSON: 编导分镜脚本完整结构(overview/scene_and_lighting/shots/hard_constraints/negative_prompts/voiceover_script)
|
||||
- voice_id/voice_source: TTS 音色参数
|
||||
- video_ratio/video_model: Seedance 视频比例/模型
|
||||
注意:线上启动也有幂等 ADD COLUMN 补列逻辑 (_ensure_viral_video_columns),本 migration 提供标准 Alembic 路径,
|
||||
两套机制互不冲突(IF NOT EXISTS 等价行为)。
|
||||
"""
|
||||
|
||||
import sqlalchemy as sa
|
||||
|
||||
from alembic import op
|
||||
|
||||
revision = "088_viral_video_copy_result"
|
||||
down_revision = "087_viral_video_image_analysis"
|
||||
branch_labels = None
|
||||
depends_on = None
|
||||
|
||||
|
||||
def upgrade() -> None:
|
||||
# 幂等添加列(通过单独执行 + 异常忽略兼容已由 backfill 补上的环境)
|
||||
cols = [
|
||||
("voice_id", "VARCHAR(200) NOT NULL DEFAULT ''"),
|
||||
("voice_source", "VARCHAR(20) NOT NULL DEFAULT ''"),
|
||||
("video_ratio", "VARCHAR(10) NOT NULL DEFAULT '9:16'"),
|
||||
("video_model", "VARCHAR(100) NOT NULL DEFAULT ''"),
|
||||
("copy_result", "JSON"),
|
||||
]
|
||||
conn = op.get_bind()
|
||||
for name, ddl in cols:
|
||||
try:
|
||||
conn.execute(sa.text(f"ALTER TABLE viral_video_jobs ADD COLUMN IF NOT EXISTS {name} {ddl}"))
|
||||
except Exception:
|
||||
# 不支持 IF NOT EXISTS 的库(如老版本 SQLite)直接尝试 ADD COLUMN,失败则忽略
|
||||
try:
|
||||
conn.execute(sa.text(f"ALTER TABLE viral_video_jobs ADD COLUMN {name} {ddl}"))
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
|
||||
def downgrade() -> None:
|
||||
for name in ("copy_result", "video_model", "video_ratio", "voice_source", "voice_id"):
|
||||
try:
|
||||
op.drop_column("viral_video_jobs", name)
|
||||
except Exception:
|
||||
pass
|
||||
@@ -0,0 +1,62 @@
|
||||
"""viral video add storyboard + generated_copy_text (complement 088)
|
||||
|
||||
Revision ID: 089_viral_video_cols
|
||||
Revises: 088_viral_video_copy_result
|
||||
Create Date: 2026-10-01
|
||||
|
||||
#2129 兜底迁移:补齐 _VIRAL_VIDEO_BACKFILL_COLS 中所有列,覆盖
|
||||
# watchtower 自动部署未跑历史 migration、且 AUTO_CREATE_SCHEMA=false 时
|
||||
# _ensure_viral_video_columns 未执行的场景。
|
||||
# 幂等 ADD COLUMN IF NOT EXISTS,已存在则跳过。
|
||||
"""
|
||||
|
||||
import sqlalchemy as sa
|
||||
|
||||
from alembic import op
|
||||
|
||||
revision = "089_viral_video_cols"
|
||||
down_revision = "088_viral_video_copy_result"
|
||||
branch_labels = None
|
||||
depends_on = None
|
||||
|
||||
|
||||
def upgrade() -> None:
|
||||
# 扩展 alembic_version.version_num 字段长度(原来 VARCHAR(32) 装不下长 revision id)
|
||||
conn = op.get_bind()
|
||||
try:
|
||||
conn.execute(sa.text("ALTER TABLE alembic_version ALTER COLUMN version_num TYPE VARCHAR(256)"))
|
||||
except Exception:
|
||||
pass
|
||||
cols = [
|
||||
("storyboard", "JSON"),
|
||||
("generated_copy_text", "TEXT NOT NULL DEFAULT ''"),
|
||||
("voice_id", "VARCHAR(200) NOT NULL DEFAULT ''"),
|
||||
("voice_source", "VARCHAR(20) NOT NULL DEFAULT ''"),
|
||||
("video_ratio", "VARCHAR(10) NOT NULL DEFAULT '9:16'"),
|
||||
("video_model", "VARCHAR(100) NOT NULL DEFAULT ''"),
|
||||
("copy_result", "JSON"),
|
||||
]
|
||||
for name, ddl in cols:
|
||||
try:
|
||||
conn.execute(sa.text(f"ALTER TABLE viral_video_jobs ADD COLUMN IF NOT EXISTS {name} {ddl}"))
|
||||
except Exception:
|
||||
try:
|
||||
conn.execute(sa.text(f"ALTER TABLE viral_video_jobs ADD COLUMN {name} {ddl}"))
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
|
||||
def downgrade() -> None:
|
||||
for name in (
|
||||
"copy_result",
|
||||
"video_model",
|
||||
"video_ratio",
|
||||
"voice_source",
|
||||
"voice_id",
|
||||
"generated_copy_text",
|
||||
"storyboard",
|
||||
):
|
||||
try:
|
||||
op.drop_column("viral_video_jobs", name)
|
||||
except Exception:
|
||||
pass
|
||||
@@ -0,0 +1,35 @@
|
||||
"""viral video add phase_message column (#2134)
|
||||
|
||||
Revision ID: 090_viral_video_phase_msg
|
||||
Revises: 089_viral_video_cols
|
||||
Create Date: 2026-10-02
|
||||
|
||||
#2134 阶段细粒度提示:viral_video 表新增 phase_message 列(中文阶段提示文案)。
|
||||
current_stage 列已在之前版本存在,本迁移只补 phase_message。
|
||||
幂等 ADD COLUMN IF NOT EXISTS。
|
||||
"""
|
||||
|
||||
import sqlalchemy as sa
|
||||
|
||||
from alembic import op
|
||||
|
||||
revision = "090_viral_video_phase_msg"
|
||||
down_revision = "089_viral_video_cols"
|
||||
branch_labels = None
|
||||
depends_on = None
|
||||
|
||||
|
||||
def upgrade() -> None:
|
||||
# SQLite/PostgreSQL 兼容的幂等添加列
|
||||
conn = op.get_bind()
|
||||
inspector = sa.inspect(conn)
|
||||
cols = {c["name"] for c in inspector.get_columns("viral_video_jobs")}
|
||||
if "phase_message" not in cols:
|
||||
op.add_column(
|
||||
"viral_video_jobs",
|
||||
sa.Column("phase_message", sa.String(length=500), nullable=False, server_default=""),
|
||||
)
|
||||
|
||||
|
||||
def downgrade() -> None:
|
||||
op.drop_column("viral_video_jobs", "phase_message")
|
||||
@@ -0,0 +1,49 @@
|
||||
"""viral video add current_stage column (#2137 follow-up)
|
||||
|
||||
Revision ID: 091_viral_video_stage
|
||||
Revises: 090_viral_video_phase_msg
|
||||
Create Date: 2026-10-02
|
||||
|
||||
#2137 follow-up fix: 090 migration missed current_stage column on viral_video_jobs,
|
||||
causing UndefinedColumn errors and 500s on all authenticated viral-video endpoints.
|
||||
Idempotently add current_stage and double-check phase_message.
|
||||
"""
|
||||
|
||||
import sqlalchemy as sa
|
||||
|
||||
from alembic import op
|
||||
|
||||
revision = "091_viral_video_stage"
|
||||
down_revision = "090_viral_video_phase_msg"
|
||||
branch_labels = None
|
||||
depends_on = None
|
||||
|
||||
|
||||
def upgrade() -> None:
|
||||
conn = op.get_bind()
|
||||
inspector = sa.inspect(conn)
|
||||
cols = {c["name"] for c in inspector.get_columns("viral_video_jobs")}
|
||||
if "current_stage" not in cols:
|
||||
op.add_column(
|
||||
"viral_video_jobs",
|
||||
sa.Column(
|
||||
"current_stage",
|
||||
sa.String(length=200),
|
||||
nullable=False,
|
||||
server_default="",
|
||||
),
|
||||
)
|
||||
if "phase_message" not in cols:
|
||||
op.add_column(
|
||||
"viral_video_jobs",
|
||||
sa.Column(
|
||||
"phase_message",
|
||||
sa.String(length=500),
|
||||
nullable=False,
|
||||
server_default="",
|
||||
),
|
||||
)
|
||||
|
||||
|
||||
def downgrade() -> None:
|
||||
op.drop_column("viral_video_jobs", "current_stage")
|
||||
@@ -0,0 +1,42 @@
|
||||
"""viral_video_jobs 增加 heartbeat_at 列(worker 心跳,用于僵尸任务超时回收)
|
||||
|
||||
Revision ID: 092_viral_video_heartbeat
|
||||
Revises: 091_viral_video_stage
|
||||
Create Date: 2026-10-02
|
||||
"""
|
||||
|
||||
import sqlalchemy as sa
|
||||
|
||||
from alembic import op
|
||||
|
||||
revision = "092_viral_video_heartbeat"
|
||||
down_revision = "091_viral_video_stage"
|
||||
branch_labels = None
|
||||
depends_on = None
|
||||
|
||||
|
||||
def upgrade() -> None:
|
||||
conn = op.get_bind()
|
||||
inspector = sa.inspect(conn)
|
||||
cols = {c["name"] for c in inspector.get_columns("viral_video_jobs")}
|
||||
if "heartbeat_at" not in cols:
|
||||
op.add_column("viral_video_jobs", sa.Column("heartbeat_at", sa.DateTime(), nullable=True))
|
||||
op.execute(
|
||||
"UPDATE viral_video_jobs SET heartbeat_at = updated_at " "WHERE status = 'running' AND heartbeat_at IS NULL"
|
||||
)
|
||||
try:
|
||||
op.create_index("ix_viral_video_jobs_heartbeat_at", "viral_video_jobs", ["heartbeat_at"])
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
|
||||
def downgrade() -> None:
|
||||
conn = op.get_bind()
|
||||
inspector = sa.inspect(conn)
|
||||
cols = {c["name"] for c in inspector.get_columns("viral_video_jobs")}
|
||||
if "heartbeat_at" in cols:
|
||||
try:
|
||||
op.drop_index("ix_viral_video_jobs_heartbeat_at", table_name="viral_video_jobs")
|
||||
except Exception:
|
||||
pass
|
||||
op.drop_column("viral_video_jobs", "heartbeat_at")
|
||||
@@ -0,0 +1,87 @@
|
||||
"""viral_video 动态积分定价 + 积分字段从 Integer 改为 Float (#2151)
|
||||
|
||||
Revision ID: 093
|
||||
Revises: 092_viral_video_heartbeat
|
||||
Create Date: 2026-10-02
|
||||
"""
|
||||
|
||||
import sqlalchemy as sa
|
||||
|
||||
from alembic import op
|
||||
|
||||
revision = "093"
|
||||
down_revision = "092_viral_video_heartbeat"
|
||||
branch_labels = None
|
||||
depends_on = None
|
||||
|
||||
|
||||
def upgrade() -> None:
|
||||
conn = op.get_bind()
|
||||
inspector = sa.inspect(conn)
|
||||
|
||||
# 1) points_accounts 三列 Integer -> Float
|
||||
pa_cols = {c["name"]: c for c in inspector.get_columns("points_accounts")}
|
||||
for col in ("balance", "total_earned", "total_spent"):
|
||||
if col in pa_cols:
|
||||
op.alter_column(
|
||||
"points_accounts",
|
||||
col,
|
||||
existing_type=sa.Integer(),
|
||||
type_=sa.Float(),
|
||||
existing_nullable=False,
|
||||
)
|
||||
|
||||
# 2) points_transactions amount/balance_after Integer -> Float
|
||||
pt_cols = {c["name"]: c for c in inspector.get_columns("points_transactions")}
|
||||
for col in ("amount", "balance_after"):
|
||||
if col in pt_cols:
|
||||
op.alter_column(
|
||||
"points_transactions",
|
||||
col,
|
||||
existing_type=sa.Integer(),
|
||||
type_=sa.Float(),
|
||||
existing_nullable=False,
|
||||
)
|
||||
|
||||
# 3) users.points_balance Integer -> Float
|
||||
user_cols = {c["name"]: c for c in inspector.get_columns("users")}
|
||||
if "points_balance" in user_cols:
|
||||
op.alter_column(
|
||||
"users",
|
||||
"points_balance",
|
||||
existing_type=sa.Integer(),
|
||||
type_=sa.Float(),
|
||||
existing_nullable=False,
|
||||
)
|
||||
|
||||
# 4) viral_video_jobs.credits_cost Integer -> Float
|
||||
vv_cols = {c["name"]: c for c in inspector.get_columns("viral_video_jobs")}
|
||||
if "credits_cost" in vv_cols:
|
||||
op.alter_column(
|
||||
"viral_video_jobs",
|
||||
"credits_cost",
|
||||
existing_type=sa.Integer(),
|
||||
type_=sa.Float(),
|
||||
existing_nullable=False,
|
||||
)
|
||||
|
||||
# 5) viral_video_jobs 新增列
|
||||
if "video_resolution" not in vv_cols:
|
||||
op.add_column(
|
||||
"viral_video_jobs",
|
||||
sa.Column("video_resolution", sa.String(20), nullable=False, server_default="720p"),
|
||||
)
|
||||
if "credits_prepaid" not in vv_cols:
|
||||
op.add_column(
|
||||
"viral_video_jobs",
|
||||
sa.Column("credits_prepaid", sa.Float(), nullable=False, server_default="0"),
|
||||
)
|
||||
if "credits_transaction_id" not in vv_cols:
|
||||
op.add_column(
|
||||
"viral_video_jobs",
|
||||
sa.Column("credits_transaction_id", sa.String(36), nullable=False, server_default=""),
|
||||
)
|
||||
|
||||
|
||||
def downgrade() -> None:
|
||||
pass
|
||||
@@ -0,0 +1,31 @@
|
||||
"""viral_video_jobs 增加 pre_trusted_images 列(信任链Seedream预热结果)
|
||||
|
||||
Revision ID: 094_viral_video_pre_trusted
|
||||
Revises: 093_viral_video_pricing_points_float
|
||||
Create Date: 2026-10-04
|
||||
"""
|
||||
|
||||
import sqlalchemy as sa
|
||||
|
||||
from alembic import op
|
||||
|
||||
revision = "094_viral_video_pre_trusted"
|
||||
down_revision = "093"
|
||||
branch_labels = None
|
||||
depends_on = None
|
||||
|
||||
|
||||
def upgrade() -> None:
|
||||
conn = op.get_bind()
|
||||
inspector = sa.inspect(conn)
|
||||
cols = {c["name"] for c in inspector.get_columns("viral_video_jobs")}
|
||||
if "pre_trusted_images" not in cols:
|
||||
op.add_column("viral_video_jobs", sa.Column("pre_trusted_images", sa.Text(), nullable=True))
|
||||
|
||||
|
||||
def downgrade() -> None:
|
||||
conn = op.get_bind()
|
||||
inspector = sa.inspect(conn)
|
||||
cols = {c["name"] for c in inspector.get_columns("viral_video_jobs")}
|
||||
if "pre_trusted_images" in cols:
|
||||
op.drop_column("viral_video_jobs", "pre_trusted_images")
|
||||
@@ -29,8 +29,6 @@ from app.services.ai_avatar_render_service import (
|
||||
from fastapi import APIRouter, Depends, HTTPException, Query
|
||||
from sqlalchemy.orm import Session
|
||||
|
||||
from packages.middleware.points_gate import points_gate
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
router = APIRouter()
|
||||
@@ -44,7 +42,6 @@ def _get_service(db: Session = Depends(get_db_session)) -> AiAvatarRenderService
|
||||
|
||||
|
||||
@router.post("", response_model=AiAvatarRenderJobResponse, status_code=201)
|
||||
@points_gate("ai_digital_human", per_unit=15)
|
||||
def create_render_job(
|
||||
body: CreateAiAvatarRenderRequest,
|
||||
current_user: AuthenticatedUser = Depends(get_current_user),
|
||||
|
||||
@@ -27,7 +27,6 @@ from packages.adapters.sqlalchemy_impl.generation_task_repository import (
|
||||
)
|
||||
from packages.application import ListGeneratedVideosByTaskUseCase
|
||||
from packages.domain.config_schemas import normalize_plan_config
|
||||
from packages.middleware.points_gate import points_gate
|
||||
from packages.shared.storage import get_shared_storage_service
|
||||
|
||||
from .templates_editor.dependencies import get_draft_plan_id, get_editor_services
|
||||
@@ -346,7 +345,6 @@ def _is_trusted_media_url(url: str) -> bool:
|
||||
|
||||
|
||||
@router.post("/generate-cover", response_model=GenerateCoverResponse)
|
||||
@points_gate("ai_cover")
|
||||
def generate_cover(
|
||||
body: GenerateCoverRequest,
|
||||
template_id: str = Query(..., description="模板 ID"),
|
||||
|
||||
@@ -41,7 +41,6 @@ from packages.application import (
|
||||
GetGenerationTaskUseCase,
|
||||
ListGeneratedVideosByTaskUseCase,
|
||||
)
|
||||
from packages.middleware.points_gate import points_gate
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
@@ -270,7 +269,6 @@ def _variant_value(values: list[str], index: int, fallback: str = "") -> str:
|
||||
|
||||
|
||||
@router.post("/preview", response_model=BatchPreviewGenerationTaskResponse, status_code=201)
|
||||
@points_gate("ai_video", quantity_field="preview_count")
|
||||
def create_preview_generation_task(
|
||||
request: CreatePreviewGenerationTaskRequest,
|
||||
authenticated_user: AuthenticatedUser = Depends(get_current_user),
|
||||
|
||||
@@ -163,7 +163,6 @@ def _infer_expected_categories(script_tags: set[str] | None) -> set[str] | None:
|
||||
return matched or None
|
||||
|
||||
|
||||
from packages.middleware.points_gate import points_gate
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
@@ -465,7 +464,6 @@ def _resolve_project_and_library(
|
||||
|
||||
|
||||
@router.post("/tasks", response_model=BatchGenerationTaskResponse)
|
||||
@points_gate("ai_video", quantity_field="count")
|
||||
def create_generation_task(
|
||||
request: CreateGenerationTaskRequest,
|
||||
authenticated_user: AuthenticatedUser = Depends(get_current_user),
|
||||
|
||||
@@ -9,6 +9,11 @@ from fastapi.responses import JSONResponse
|
||||
router = APIRouter(tags=["Health"])
|
||||
|
||||
|
||||
|
||||
def _pg_url(url: str) -> str:
|
||||
"""Convert SQLAlchemy URL (postgresql+psycopg://...) to libpq connection string."""
|
||||
return url.replace("postgresql+psycopg://", "postgresql://", 1).replace("postgresql+psycopg2://", "postgresql://", 1)
|
||||
|
||||
@router.get("/health", status_code=status.HTTP_200_OK)
|
||||
async def health_check():
|
||||
return {
|
||||
@@ -49,7 +54,7 @@ async def _check_database() -> dict:
|
||||
"message": "Using in-memory database",
|
||||
}
|
||||
try:
|
||||
conn = psycopg.connect(settings.DATABASE_URL, connect_timeout=3)
|
||||
conn = psycopg.connect(_pg_url(settings.DATABASE_URL), connect_timeout=3)
|
||||
with conn.cursor() as cur:
|
||||
cur.execute("SELECT 1")
|
||||
cur.fetchone()
|
||||
@@ -124,7 +129,7 @@ async def _check_migrations() -> dict:
|
||||
"message": "Using in-memory database, no migrations needed",
|
||||
}
|
||||
try:
|
||||
conn = psycopg.connect(settings.DATABASE_URL, connect_timeout=3)
|
||||
conn = psycopg.connect(_pg_url(settings.DATABASE_URL), connect_timeout=3)
|
||||
with conn.cursor() as cur:
|
||||
cur.execute("""
|
||||
SELECT COUNT(*) FROM information_schema.tables
|
||||
@@ -137,3 +142,5 @@ async def _check_migrations() -> dict:
|
||||
return {"status": "unhealthy", "message": f"Missing tables, found {count}/5"}
|
||||
except Exception as error:
|
||||
return {"status": "unhealthy", "message": f"Migration check failed: {error}"}
|
||||
|
||||
|
||||
|
||||
@@ -12,11 +12,9 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import logging
|
||||
import math
|
||||
from datetime import UTC
|
||||
|
||||
from app.auth import AuthenticatedUser, get_current_user
|
||||
from app.config import settings
|
||||
from app.dependencies import (
|
||||
get_db_session,
|
||||
get_voice_clone_profile_repository,
|
||||
@@ -32,9 +30,6 @@ from app.services.mediakit_client import MediaKitError
|
||||
from fastapi import APIRouter, BackgroundTasks, Depends, HTTPException, Query
|
||||
from sqlalchemy.orm import Session
|
||||
|
||||
from packages.domain.points_rules import calculate_points_cost
|
||||
from packages.domain.points_service import PointsService
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
router = APIRouter()
|
||||
@@ -61,37 +56,6 @@ def create_lipsync_job(
|
||||
db: Session = Depends(get_db_session),
|
||||
svc: LipsyncService = Depends(_get_service),
|
||||
):
|
||||
user_id = current_user.user.id
|
||||
|
||||
# ── 积分扣点(#1895 P2) ──
|
||||
_points_deducted = 0
|
||||
_points_scene = "ai_digital_human"
|
||||
_points_svc = PointsService() if settings.points_enabled else None
|
||||
if _points_svc is not None:
|
||||
# 口型同步:TTS 模式按 script_text 估时长(240字/分钟);音频直传按 audio_duration(秒→分钟)
|
||||
if body.audio_url and body.audio_duration and body.audio_duration > 0:
|
||||
est_minutes = max(1.0, math.ceil(body.audio_duration / 60.0))
|
||||
elif body.script_text:
|
||||
est_minutes = max(1.0, math.ceil(len(body.script_text) / 240))
|
||||
else:
|
||||
est_minutes = 1.0
|
||||
_points_deducted = calculate_points_cost(
|
||||
_points_scene,
|
||||
is_member=getattr(current_user.user, "is_member", False),
|
||||
duration_minutes=est_minutes,
|
||||
member_type=getattr(current_user.user, "member_type", None),
|
||||
)
|
||||
_deduct_res = _points_svc.deduct_points(user_id, _points_deducted, _points_scene, db)
|
||||
if not _deduct_res["success"]:
|
||||
raise HTTPException(
|
||||
status_code=402,
|
||||
detail={
|
||||
"code": "INSUFFICIENT_POINTS",
|
||||
"message": f"积分不足,需要 {_points_deducted} 积分,当前余额 {_deduct_res['balance']}",
|
||||
"required": _points_deducted,
|
||||
"balance": _deduct_res["balance"],
|
||||
},
|
||||
)
|
||||
"""提交对口型任务.
|
||||
|
||||
三种模式:
|
||||
@@ -101,6 +65,8 @@ def create_lipsync_job(
|
||||
- 预合成音频(#1845 新主路径):传 {video_url, audio_url, audio_duration, sentence_timings},
|
||||
后端同步ffprobe+写入timings+直接提交MediaKit(~2-3s)。
|
||||
"""
|
||||
user_id = current_user.user.id
|
||||
|
||||
try:
|
||||
job = svc.create_job(
|
||||
user_id=user_id,
|
||||
@@ -118,18 +84,8 @@ def create_lipsync_job(
|
||||
project_id=body.project_id,
|
||||
)
|
||||
except ValueError as exc:
|
||||
if _points_deducted > 0 and _points_svc is not None:
|
||||
try:
|
||||
_points_svc.refund_points(user_id, _points_deducted, _points_scene, db)
|
||||
except Exception as refund_err:
|
||||
logger.warning(f"对口型 ValueError 退积分异常: err={refund_err}")
|
||||
raise HTTPException(status_code=400, detail=str(exc)) from exc
|
||||
except MediaKitError as exc:
|
||||
if _points_deducted > 0 and _points_svc is not None:
|
||||
try:
|
||||
_points_svc.refund_points(user_id, _points_deducted, _points_scene, db)
|
||||
except Exception as refund_err:
|
||||
logger.warning(f"对口型 MediaKitError 退积分异常: err={refund_err}")
|
||||
status_code = 502
|
||||
if exc.code in ("VoiceForbidden",):
|
||||
status_code = 403
|
||||
@@ -145,24 +101,11 @@ def create_lipsync_job(
|
||||
) from exc
|
||||
except Exception as exc:
|
||||
logger.error("创建对口型任务异常: %s", exc, exc_info=True)
|
||||
if _points_deducted > 0 and _points_svc is not None:
|
||||
try:
|
||||
_points_svc.refund_points(user_id, _points_deducted, _points_scene, db)
|
||||
except Exception as refund_err:
|
||||
logger.warning(f"对口型异常退积分异常: err={refund_err}")
|
||||
raise HTTPException(
|
||||
status_code=400,
|
||||
detail=f"创建对口型任务失败: {exc}",
|
||||
) from exc
|
||||
|
||||
# 创建成功但状态为 failed(同步路径失败已抛异常到上面 except;此处处理 Celery 调度失败等)
|
||||
# 若任务已创建且状态为 failed,退费
|
||||
if _points_deducted > 0 and _points_svc is not None and getattr(job, "status", None) == "failed":
|
||||
try:
|
||||
_points_svc.refund_points(user_id, _points_deducted, _points_scene, db, ref_id=job.id)
|
||||
except Exception as refund_err:
|
||||
logger.warning(f"对口型任务失败退积分异常: job_id={job.id}, err={refund_err}")
|
||||
|
||||
return job
|
||||
|
||||
|
||||
@@ -176,37 +119,14 @@ def preview_tts(
|
||||
db: Session = Depends(get_db_session),
|
||||
svc: LipsyncService = Depends(_get_service),
|
||||
):
|
||||
user_id = current_user.user.id
|
||||
|
||||
# ── 积分扣点(#1895 P2) ──
|
||||
_points_deducted = 0
|
||||
_points_scene = "ai_digital_human"
|
||||
_points_svc = PointsService() if settings.points_enabled else None
|
||||
if _points_svc is not None:
|
||||
est_minutes = max(1.0, math.ceil(len(body.script_text or "") / 240)) if body.script_text else 1.0
|
||||
_points_deducted = calculate_points_cost(
|
||||
_points_scene,
|
||||
is_member=getattr(current_user.user, "is_member", False),
|
||||
duration_minutes=est_minutes,
|
||||
member_type=getattr(current_user.user, "member_type", None),
|
||||
)
|
||||
_deduct_res = _points_svc.deduct_points(user_id, _points_deducted, _points_scene, db)
|
||||
if not _deduct_res["success"]:
|
||||
raise HTTPException(
|
||||
status_code=402,
|
||||
detail={
|
||||
"code": "INSUFFICIENT_POINTS",
|
||||
"message": f"积分不足,需要 {_points_deducted} 积分,当前余额 {_deduct_res['balance']}",
|
||||
"required": _points_deducted,
|
||||
"balance": _deduct_res["balance"],
|
||||
},
|
||||
)
|
||||
"""步骤1「生成配音」同步 TTS 预合成.
|
||||
|
||||
同步执行 TTS 合成 → 下载音频 → ffprobe 时长 → 句子时间戳计算,
|
||||
不创建 LipsyncJob、不转存 OSS,直接返回 CosyVoice 临时 URL(~24h 有效)。
|
||||
耗时约 2-3 秒。
|
||||
"""
|
||||
user_id = current_user.user.id
|
||||
|
||||
try:
|
||||
result = svc.preview_tts(
|
||||
user_id=user_id,
|
||||
@@ -218,11 +138,6 @@ def preview_tts(
|
||||
emotion=body.emotion,
|
||||
)
|
||||
except MediaKitError as exc:
|
||||
if _points_deducted > 0 and _points_svc is not None:
|
||||
try:
|
||||
_points_svc.refund_points(user_id, _points_deducted, _points_scene, db)
|
||||
except Exception as refund_err:
|
||||
logger.warning(f"TTS 预合成 MediaKitError 退积分异常: err={refund_err}")
|
||||
status_code = 400
|
||||
if exc.code in ("VoiceForbidden",):
|
||||
status_code = 403
|
||||
@@ -237,11 +152,6 @@ def preview_tts(
|
||||
) from exc
|
||||
except Exception as exc:
|
||||
logger.error("TTS 预合成异常: %s", exc, exc_info=True)
|
||||
if _points_deducted > 0 and _points_svc is not None:
|
||||
try:
|
||||
_points_svc.refund_points(user_id, _points_deducted, _points_scene, db)
|
||||
except Exception as refund_err:
|
||||
logger.warning(f"TTS 预合成异常退积分异常: err={refund_err}")
|
||||
raise HTTPException(
|
||||
status_code=400,
|
||||
detail=f"TTS 合成失败: {exc}",
|
||||
|
||||
@@ -145,19 +145,22 @@ def get_rules(
|
||||
def get_packages(
|
||||
current_user: AuthenticatedUser = Depends(get_current_user),
|
||||
):
|
||||
"""查询可购买的积分包列表。"""
|
||||
packages = []
|
||||
for code, pkg in POINTS_PACKAGES.items():
|
||||
unit_price = f"¥{pkg['price_cents'] / 100 / pkg['points']:.3f}/积分"
|
||||
packages.append(
|
||||
PointsPackageItem(
|
||||
code=code,
|
||||
name=pkg["name"],
|
||||
points=pkg["points"],
|
||||
price_cents=pkg["price_cents"],
|
||||
unit_price=unit_price,
|
||||
)
|
||||
"""查询可购买的积分包列表(读管理后台 credit_packages 表真实数据)。
|
||||
|
||||
仅返回 is_active=true;后台改价/启停后最多 30 秒生效。
|
||||
"""
|
||||
from packages.application.catalog.admin_catalog import get_points_packages
|
||||
|
||||
packages = [
|
||||
PointsPackageItem(
|
||||
code=row["code"],
|
||||
name=row["name"],
|
||||
points=row["points"],
|
||||
price_cents=row["price_cents"],
|
||||
unit_price=row["unit_price"],
|
||||
)
|
||||
for row in get_points_packages()
|
||||
]
|
||||
mt = _member_type(current_user)
|
||||
discount = MEMBER_DISCOUNT.get(mt) if mt else None
|
||||
return PointsPackagesResponse(packages=packages, user_discount=discount)
|
||||
@@ -169,17 +172,7 @@ def check_points(
|
||||
current_user: AuthenticatedUser = Depends(get_current_user),
|
||||
db: Session = Depends(get_db_session),
|
||||
):
|
||||
"""消费前检查余额是否足够。未知 scene_key 返回 400(而非 500)。"""
|
||||
if body.scene_key not in POINTS_SCENES:
|
||||
raise HTTPException(
|
||||
status_code=400,
|
||||
detail={
|
||||
"code": "UNKNOWN_SCENE",
|
||||
"message": f"未知场景: {body.scene_key}",
|
||||
"valid_scenes": sorted(POINTS_SCENES.keys()),
|
||||
},
|
||||
)
|
||||
|
||||
"""消费前检查余额是否足够。已下线/未知场景返回 cost=0(免费)。"""
|
||||
# 积分系统暂停(ENABLE_CREDIT_SYSTEM=false):所有场景直接放行,需 0 积分
|
||||
if not _credits_enabled():
|
||||
svc = _get_service()
|
||||
@@ -195,13 +188,6 @@ def check_points(
|
||||
is_mem = _is_member(current_user)
|
||||
mt = _member_type(current_user)
|
||||
|
||||
# 混剪场景先检查免费额度
|
||||
is_free_quota = False
|
||||
if body.scene_key == "ai_video" and not is_mem:
|
||||
svc = _get_service()
|
||||
if svc.check_daily_free_clip(current_user.user.id, db):
|
||||
is_free_quota = True
|
||||
|
||||
required = calculate_points_cost(
|
||||
body.scene_key,
|
||||
is_mem,
|
||||
@@ -215,11 +201,11 @@ def check_points(
|
||||
balance = account["balance"]
|
||||
|
||||
return PointsCheckResponse(
|
||||
allowed=is_free_quota or balance >= required,
|
||||
allowed=balance >= required,
|
||||
required_points=required,
|
||||
current_balance=balance,
|
||||
remaining_after=balance - required,
|
||||
is_free_quota=is_free_quota,
|
||||
is_free_quota=False,
|
||||
)
|
||||
|
||||
|
||||
|
||||
@@ -44,7 +44,6 @@ from app.services.script_asr_service import (
|
||||
from fastapi import APIRouter, Depends, HTTPException, status
|
||||
from sqlalchemy.orm import Session
|
||||
|
||||
from packages.middleware.points_gate import points_gate
|
||||
from packages.shared.ai_client import get_doubao_client
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
@@ -373,7 +372,6 @@ def douyin_diag():
|
||||
|
||||
|
||||
@router.post("/extract-from-douyin", response_model=ExtractFromDouyinResponse)
|
||||
@points_gate("douyin_extract")
|
||||
def extract_from_douyin(
|
||||
request: ExtractFromDouyinRequest,
|
||||
current_user: AuthenticatedUser = Depends(get_current_user),
|
||||
@@ -497,7 +495,6 @@ def extract_from_douyin(
|
||||
|
||||
|
||||
@router.post("/ai-rewrite", response_model=AiRewriteResponse)
|
||||
@points_gate("ai_rewrite")
|
||||
def ai_rewrite(
|
||||
request: AiRewriteRequest,
|
||||
current_user: AuthenticatedUser = Depends(get_current_user),
|
||||
@@ -537,7 +534,6 @@ def ai_rewrite(
|
||||
|
||||
|
||||
@router.post("/ai-generate-titles", response_model=AiGenerateTitlesResponse)
|
||||
@points_gate("ai_title")
|
||||
def ai_generate_titles(
|
||||
request: AiGenerateTitlesRequest,
|
||||
current_user: AuthenticatedUser = Depends(get_current_user),
|
||||
|
||||
@@ -86,33 +86,13 @@ async def get_current_subscription(
|
||||
def list_membership_plans(
|
||||
current_user: AuthenticatedUser = Depends(get_current_user),
|
||||
) -> dict[str, list[dict[str, Any]]]:
|
||||
"""查询所有会员档位(供前端会员购买页展示)。
|
||||
"""查询可购买的会员套餐(读管理后台 plans 表真实数据)。
|
||||
|
||||
返回 points 积分体系下的会员档位(月卡/季卡/年卡),含价格、时长、积分折扣等信息。
|
||||
仅返回 is_enabled=true 的套餐;后台启停/改价后最多 30 秒生效。
|
||||
"""
|
||||
from packages.domain.points_rules import MEMBER_DISCOUNT, MEMBERSHIP_PRICES
|
||||
from packages.application.catalog.admin_catalog import get_membership_plans
|
||||
|
||||
plans: list[dict[str, Any]] = []
|
||||
for plan_id, info in MEMBERSHIP_PRICES.items():
|
||||
days = info["duration_days"]
|
||||
monthly_cents = round(info["price_cents"] * 30 / days)
|
||||
features: dict[str, Any] = {"max_resolution": "1080p"}
|
||||
if plan_id == MembershipType.MONTHLY:
|
||||
features.update({"free_clips_daily": 2})
|
||||
elif plan_id == MembershipType.QUARTERLY:
|
||||
features.update({"free_clips_daily": 5})
|
||||
elif plan_id == MembershipType.YEARLY:
|
||||
features.update({"free_clips_daily": "unlimited"})
|
||||
plans.append({
|
||||
"plan_id": plan_id,
|
||||
"name": info["name"],
|
||||
"price_cents": info["price_cents"],
|
||||
"monthly_price_cents": monthly_cents,
|
||||
"duration_days": days,
|
||||
"points_discount": MEMBER_DISCOUNT.get(plan_id, 1.0),
|
||||
"features": features,
|
||||
})
|
||||
return {"plans": plans}
|
||||
return {"plans": get_membership_plans()}
|
||||
|
||||
|
||||
@router.get("/billing-records", response_model=list[BillingRecord])
|
||||
|
||||
@@ -4,14 +4,12 @@ from __future__ import annotations
|
||||
|
||||
import json
|
||||
import logging
|
||||
import math
|
||||
import subprocess
|
||||
import tempfile
|
||||
from pathlib import Path
|
||||
from typing import Any, Optional
|
||||
|
||||
from app.auth import AuthenticatedUser, get_current_user
|
||||
from app.config import settings
|
||||
from app.core.celery_app import celery_app
|
||||
from app.core.storage import get_storage_service
|
||||
from app.dependencies import (
|
||||
@@ -53,8 +51,6 @@ from packages.application.tts_job.use_cases import (
|
||||
)
|
||||
from packages.application.tts_job.workflow import TTSWorkflowService
|
||||
from packages.domain import Asset, AssetLibrary, AssetLibraryKind, AssetStatus, ClassificationStatus
|
||||
from packages.domain.points_rules import calculate_points_cost
|
||||
from packages.domain.points_service import PointsService
|
||||
from packages.domain.voice_presets import list_voices
|
||||
from packages.ports.asset_library_repository import AssetLibraryRepository
|
||||
from packages.ports.asset_repository import AssetRepository
|
||||
@@ -144,31 +140,6 @@ def synthesize(
|
||||
"""
|
||||
user_id = authenticated_user.user.id
|
||||
|
||||
# ── 积分扣点(#1895 P2) ──
|
||||
_points_deducted = 0
|
||||
_points_scene = "ai_voice"
|
||||
_points_svc = PointsService() if settings.points_enabled else None
|
||||
if _points_svc is not None:
|
||||
# 中文按 ~240 字/分钟粗估时长,至少按 1 分钟扣 1 分
|
||||
est_minutes = max(1.0, math.ceil(len(request.text) / 240))
|
||||
_points_deducted = calculate_points_cost(
|
||||
_points_scene,
|
||||
is_member=getattr(authenticated_user.user, "is_member", False),
|
||||
duration_minutes=est_minutes,
|
||||
member_type=getattr(authenticated_user.user, "member_type", None),
|
||||
)
|
||||
_deduct_res = _points_svc.deduct_points(user_id, _points_deducted, _points_scene, db)
|
||||
if not _deduct_res["success"]:
|
||||
raise HTTPException(
|
||||
status_code=402,
|
||||
detail={
|
||||
"code": "INSUFFICIENT_POINTS",
|
||||
"message": f"积分不足,需要 {_points_deducted} 积分,当前余额 {_deduct_res['balance']}",
|
||||
"required": _points_deducted,
|
||||
"balance": _deduct_res["balance"],
|
||||
},
|
||||
)
|
||||
|
||||
# 解析 voice_id:前端可能传克隆音色 profile UUID(而非 CosyVoice voice_id),
|
||||
# 与 /tts/preview 保持一致:命中 profile → 校验归属 → 取 CosyVoice voice_id
|
||||
actual_voice_id = request.voice_id
|
||||
@@ -231,7 +202,6 @@ def synthesize(
|
||||
cosyvoice_service=cosyvoice_service,
|
||||
)
|
||||
|
||||
synthesis_error: Exception | None = None
|
||||
try:
|
||||
job = workflow.start_synthesis(job.id)
|
||||
except Exception as e:
|
||||
@@ -239,18 +209,10 @@ def synthesize(
|
||||
# 但 DB 异常、网络异常等意外错误可能逃逸。
|
||||
# 与音色克隆接口保持一致:标记 failed,返回 201,不抛 500。
|
||||
logger.error(f"TTS 合成异常: job_id={job.id}, error={e}", exc_info=True)
|
||||
synthesis_error = e
|
||||
try:
|
||||
job = workflow.process_synthesis_failure(job.id, str(e))
|
||||
except Exception as inner_e:
|
||||
logger.error(f"标记 TTS job 失败时出错: job_id={job.id}, error={inner_e}")
|
||||
# 合成失败且已扣积分 → 退费
|
||||
if synthesis_error is not None and _points_deducted > 0 and _points_svc is not None:
|
||||
try:
|
||||
_points_svc.refund_points(user_id, _points_deducted, _points_scene, db, ref_id=job.id)
|
||||
except Exception as refund_err:
|
||||
logger.warning(f"TTS 合失败退积分异常: job_id={job.id}, err={refund_err}")
|
||||
|
||||
# 若任务处于 processing 状态(异步模式),触发 Celery 后台轮询
|
||||
if job.status.value == "processing":
|
||||
# 分段合成任务 vs 普通单段任务
|
||||
@@ -269,13 +231,6 @@ def synthesize(
|
||||
workflow.process_synthesis_failure(job.id, f"Celery 任务调度失败: {e}")
|
||||
except Exception as inner_e:
|
||||
logger.error(f"Celery 调度后标记失败时出错: job_id={job.id}, error={inner_e}")
|
||||
# 调度失败退费
|
||||
if _points_deducted > 0 and _points_svc is not None:
|
||||
try:
|
||||
_points_svc.refund_points(user_id, _points_deducted, _points_scene, db, ref_id=job.id)
|
||||
except Exception as refund_err:
|
||||
logger.warning(f"Celery 调度失败退积分异常: job_id={job.id}, err={refund_err}")
|
||||
|
||||
return TTSSynthesizeResponse(
|
||||
job_id=job.id,
|
||||
status=job.status,
|
||||
@@ -610,31 +565,6 @@ def preview_tts(
|
||||
用于前端预览配音效果,限制文本长度 200 字以内。
|
||||
支持预设音色和克隆音色:克隆音色传的是 profile UUID,需解析为 CosyVoice voice_id。
|
||||
"""
|
||||
user_id = authenticated_user.user.id
|
||||
# ── 积分扣点(#1895 P2) ──
|
||||
_points_deducted = 0
|
||||
_points_scene = "ai_voice"
|
||||
_points_svc = PointsService() if settings.points_enabled else None
|
||||
if _points_svc is not None:
|
||||
est_minutes = max(1.0, math.ceil(len(request.text) / 240))
|
||||
_points_deducted = calculate_points_cost(
|
||||
_points_scene,
|
||||
is_member=getattr(authenticated_user.user, "is_member", False),
|
||||
duration_minutes=est_minutes,
|
||||
member_type=getattr(authenticated_user.user, "member_type", None),
|
||||
)
|
||||
_deduct_res = _points_svc.deduct_points(user_id, _points_deducted, _points_scene, db)
|
||||
if not _deduct_res["success"]:
|
||||
raise HTTPException(
|
||||
status_code=402,
|
||||
detail={
|
||||
"code": "INSUFFICIENT_POINTS",
|
||||
"message": f"积分不足,需要 {_points_deducted} 积分,当前余额 {_deduct_res['balance']}",
|
||||
"required": _points_deducted,
|
||||
"balance": _deduct_res["balance"],
|
||||
},
|
||||
)
|
||||
|
||||
# 解析 voice_id:前端可能传 VoiceCloneProfile UUID 或预设音色 ID
|
||||
actual_voice_id = request.voice_id
|
||||
profile = voice_clone_repo.get(request.voice_id)
|
||||
@@ -664,12 +594,6 @@ def preview_tts(
|
||||
language=getattr(request, "language", "zh-CN"),
|
||||
)
|
||||
except (CosyVoiceError, ValueError) as e:
|
||||
# 合成失败退费
|
||||
if _points_deducted > 0 and _points_svc is not None:
|
||||
try:
|
||||
_points_svc.refund_points(user_id, _points_deducted, _points_scene, db)
|
||||
except Exception as refund_err:
|
||||
logger.warning(f"TTS 预览失败退积分异常: {refund_err}")
|
||||
if isinstance(e, CosyVoiceError):
|
||||
raise HTTPException(status_code=status.HTTP_502_BAD_GATEWAY, detail=f"TTS 合成失败: {e}") from e
|
||||
raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail=str(e)) from e
|
||||
|
||||
@@ -191,6 +191,23 @@ def _find_duplicate_asset(
|
||||
return None
|
||||
|
||||
|
||||
|
||||
def _get_existing_asset_url(existing: Any, storage_service: Any) -> str:
|
||||
"""安全获取已存在素材的公网 URL,兼容 domain Asset(无 file_url 字段)和 ORM model。"""
|
||||
# Domain Asset 只有 storage_key 字段;ORM model 有 file_url 但存的也是 storage_key
|
||||
key = ""
|
||||
for attr in ("storage_key", "file_url"):
|
||||
v = getattr(existing, attr, None)
|
||||
if v:
|
||||
key = v
|
||||
break
|
||||
if not key:
|
||||
return ""
|
||||
try:
|
||||
return storage_service.get_url(key) or ""
|
||||
except Exception:
|
||||
return ""
|
||||
|
||||
def _create_pending_asset(
|
||||
asset_repository,
|
||||
project_id,
|
||||
@@ -390,6 +407,7 @@ async def prepare_direct_upload(
|
||||
duplicated=True,
|
||||
skip_transfer=True,
|
||||
asset_id=existing.id,
|
||||
url=_get_existing_asset_url(existing, storage_service),
|
||||
)
|
||||
|
||||
file_id = uuid4().hex[:8]
|
||||
@@ -443,6 +461,7 @@ async def prepare_direct_upload(
|
||||
duplicated=False,
|
||||
skip_transfer=False,
|
||||
asset_id=pending_asset_id,
|
||||
url="",
|
||||
)
|
||||
|
||||
|
||||
|
||||
Executable → Regular
+712
-29
@@ -1,13 +1,21 @@
|
||||
"""爆款视频 API 路由。
|
||||
|
||||
端点:
|
||||
POST /api/v1/viral-video/generate 创建爆款视频任务
|
||||
GET /api/v1/viral-video/{job_id} 查询任务状态
|
||||
GET /api/v1/viral-video/history 历史记录
|
||||
POST /api/v1/viral-video/{job_id}/retry 重试失败任务
|
||||
POST /api/v1/viral-video/{job_id}/confirm-intent 确认意图文案
|
||||
POST /api/v1/viral-video/{job_id}/analyze-style 触发风格分析
|
||||
GET /api/v1/viral-video/style-templates 获取风格模板列表
|
||||
v1.6 三步分步流水线端点(单次 Seedance 出片版):
|
||||
POST /api/v1/viral-video/analyze-images 阶段1:创建任务 + 仅做图片/视频分析,暂停在 image_analyzed
|
||||
POST /api/v1/viral-video/{job_id}/generate-copy 阶段2:用户填完参数后跑意图+文案+分镜+审核,暂停在 copy_generated
|
||||
POST /api/v1/viral-video/{job_id}/confirm-copy 阶段3:用户确认/编辑文案后跑渲染,直到完成
|
||||
|
||||
旧端点(兼容保留,旧前端/一键生成模式):
|
||||
POST /api/v1/viral-video/generate 一键入队,前半段跑到 wait_user_confirm
|
||||
POST /api/v1/viral-video/{job_id}/confirm-intent 旧的意图确认后继续渲染
|
||||
|
||||
通用:
|
||||
GET /api/v1/viral-video/{job_id} 查询任务状态(含 image_analysis/copy_result 编导脚本)
|
||||
GET /api/v1/viral-video/history 历史记录
|
||||
POST /api/v1/viral-video/{job_id}/retry 重试失败任务
|
||||
POST /api/v1/viral-video/{job_id}/analyze-style 触发风格分析
|
||||
GET /api/v1/viral-video/style-templates 风格模板列表
|
||||
WS /api/v1/viral-video/ws/{job_id}?token= WebSocket 进度推送
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
@@ -15,25 +23,35 @@ from __future__ import annotations
|
||||
import logging
|
||||
|
||||
from app.auth import AuthenticatedUser, get_current_user
|
||||
from app.core.celery_app import celery_app
|
||||
from app.dependencies import get_db_session
|
||||
from app.schemas.viral_video import (
|
||||
AnalyzeImagesRequest,
|
||||
AnalyzeStyleRequest,
|
||||
AnalyzeStyleResponse,
|
||||
ConfirmCopyRequest,
|
||||
ConfirmIntentRequest,
|
||||
CreateViralVideoRequest,
|
||||
CreditsFormulaBreakdown,
|
||||
EstimateCreditsRequest,
|
||||
EstimateCreditsResponse,
|
||||
GenerateCopyRequest,
|
||||
RetryViralVideoRequest,
|
||||
StyleTemplateListResponse,
|
||||
StyleTemplateResponse,
|
||||
ViralVideoHistoryResponse,
|
||||
ViralVideoJobResponse,
|
||||
)
|
||||
from fastapi import APIRouter, Depends, HTTPException
|
||||
from fastapi import APIRouter, Depends, HTTPException, WebSocket, WebSocketDisconnect
|
||||
from sqlalchemy.orm import Session
|
||||
|
||||
from packages.adapters.sqlalchemy_impl.viral_video_repository import (
|
||||
SQLAlchemyViralVideoJobRepository,
|
||||
SQLAlchemyViralVideoStyleTemplateRepository,
|
||||
)
|
||||
from packages.domain.points_rules import list_viral_video_models
|
||||
from packages.domain.viral_video import ViralVideoStatus
|
||||
from packages.shared.dashscope_client import get_dashscope_client
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
@@ -43,6 +61,59 @@ router = APIRouter()
|
||||
# ── Helpers ──────────────────────────────────────────────────────────────
|
||||
|
||||
|
||||
def _build_copy_result(job) -> dict | None:
|
||||
"""v1.6: 返回编导分镜脚本 CopyResult 结构(给前端/Seedance 使用)。
|
||||
|
||||
- 若 job.copy_result 已持久化(v1.6 worker 生成),直接返回(补 final_copy 兜底)。
|
||||
- 否则从老字段(generated_copy_text=口播, storyboard=分镜列表, intent_result)拼装兼容结构。
|
||||
"""
|
||||
cr = getattr(job, "copy_result", None)
|
||||
if isinstance(cr, dict) and cr:
|
||||
out = dict(cr)
|
||||
# 向后兼容字段
|
||||
voiceover = out.get("voiceover_script", "") or ""
|
||||
out.setdefault("final_copy", voiceover)
|
||||
out.setdefault("suggested_copy", voiceover)
|
||||
out.setdefault("title", "")
|
||||
return out
|
||||
# 兼容 v1.5 老数据:storyboard 是老格式 [{order,type,description,text,duration,...}]
|
||||
copy_text = getattr(job, "generated_copy_text", "") or ""
|
||||
sb = getattr(job, "storyboard", None) or []
|
||||
intent = getattr(job, "intent_result", None) or {}
|
||||
if not copy_text and not sb:
|
||||
return None
|
||||
title = ""
|
||||
if isinstance(intent, dict):
|
||||
title = intent.get("suggested_title") or intent.get("intent", "") or ""
|
||||
shots = []
|
||||
for seg in sb:
|
||||
if isinstance(seg, dict):
|
||||
shots.append(
|
||||
{
|
||||
"time_range": "",
|
||||
"shot_type_angle_movement": seg.get("ken_burns", ""),
|
||||
"scene_and_dialogue": (seg.get("text") or "")
|
||||
+ (" " + seg.get("description", "") if seg.get("description") else ""),
|
||||
"action_details": "",
|
||||
"audio_bgm": "",
|
||||
"transition": seg.get("transition", "硬切"),
|
||||
"reference_image_index": None,
|
||||
}
|
||||
)
|
||||
ratio = getattr(job, "video_ratio", None) or "9:16"
|
||||
return {
|
||||
"overview": {"theme": title, "total_duration": getattr(job, "duration", 15), "aspect_ratio": ratio},
|
||||
"scene_and_lighting": "",
|
||||
"shots": shots,
|
||||
"hard_constraints": ["无字幕", "无水印", "人物一致性"],
|
||||
"negative_prompts": ["字幕", "水印", "错误文字", "五官崩坏"],
|
||||
"voiceover_script": copy_text,
|
||||
"final_copy": copy_text,
|
||||
"suggested_copy": copy_text,
|
||||
"title": title,
|
||||
}
|
||||
|
||||
|
||||
def _to_response(job) -> ViralVideoJobResponse:
|
||||
return ViralVideoJobResponse(
|
||||
id=job.id,
|
||||
@@ -54,7 +125,7 @@ def _to_response(job) -> ViralVideoJobResponse:
|
||||
viral_structure=job.viral_structure,
|
||||
marketing_purpose=job.marketing_purpose,
|
||||
bgm_preference=job.bgm_preference,
|
||||
duration=job.duration,
|
||||
duration=job.duration or 15,
|
||||
user_copy_text=job.user_copy_text,
|
||||
fusion_level=job.fusion_level,
|
||||
reference_audio_path=job.reference_audio_path,
|
||||
@@ -63,9 +134,21 @@ def _to_response(job) -> ViralVideoJobResponse:
|
||||
style_guide=job.style_guide,
|
||||
style_template_id=job.style_template_id,
|
||||
status=job.status,
|
||||
current_stage=getattr(job, "current_stage", "") or "",
|
||||
phase_message=getattr(job, "phase_message", "") or "",
|
||||
image_analysis=getattr(job, "image_analysis", None),
|
||||
storyboard=getattr(job, "storyboard", None),
|
||||
generated_copy_text=getattr(job, "generated_copy_text", "") or "",
|
||||
copy_result=_build_copy_result(job),
|
||||
voice_id=getattr(job, "voice_id", "") or "",
|
||||
voice_source=getattr(job, "voice_source", "") or "",
|
||||
video_ratio=getattr(job, "video_ratio", "9:16") or "9:16",
|
||||
video_model=getattr(job, "video_model", "") or "",
|
||||
intent_result=job.intent_result,
|
||||
result_video_url=job.result_video_url,
|
||||
credits_cost=job.credits_cost,
|
||||
video_resolution=getattr(job, "video_resolution", "720p") or "720p",
|
||||
credits_prepaid=float(getattr(job, "credits_prepaid", 0) or 0),
|
||||
credits_cost=float(getattr(job, "credits_cost", 0) or 0),
|
||||
error_msg=job.error_msg,
|
||||
retry_count=job.retry_count,
|
||||
started_at=job.started_at,
|
||||
@@ -107,13 +190,19 @@ def create_viral_video(
|
||||
viral_structure=request.viral_structure,
|
||||
marketing_purpose=request.marketing_purpose,
|
||||
bgm_preference=request.bgm_preference,
|
||||
duration=request.duration,
|
||||
duration=request.duration or 15,
|
||||
user_copy_text=request.user_copy_text,
|
||||
fusion_level=request.fusion_level,
|
||||
reference_audio_path=request.reference_audio_path,
|
||||
reference_video_url=request.reference_video_url,
|
||||
style_strength=request.style_strength,
|
||||
style_template_id=request.style_template_id,
|
||||
voice_id=getattr(request, "voice_id", "") or "",
|
||||
voice_source=getattr(request, "voice_source", "") or "",
|
||||
video_ratio=getattr(request, "video_ratio", "9:16") or "9:16",
|
||||
video_model=getattr(request, "video_model", "") or "",
|
||||
video_resolution=getattr(request, "video_resolution", "720p") or "720p",
|
||||
copy_result=None,
|
||||
)
|
||||
|
||||
# 持久化
|
||||
@@ -121,9 +210,7 @@ def create_viral_video(
|
||||
|
||||
# 入队 Celery 任务
|
||||
try:
|
||||
from worker_app.tasks.viral_video import run_viral_video_pipeline
|
||||
|
||||
run_viral_video_pipeline.delay(job.id)
|
||||
celery_app.send_task("worker.run_viral_video_pipeline", args=[job.id])
|
||||
logger.info("[爆款视频] 任务已入队: job_id=%s user_id=%s", job.id, job.user_id)
|
||||
except Exception as e:
|
||||
logger.error("[爆款视频] 入队失败: %s", e, exc_info=True)
|
||||
@@ -133,6 +220,208 @@ def create_viral_video(
|
||||
return _to_response(job)
|
||||
|
||||
|
||||
@router.post("/analyze-images", response_model=ViralVideoJobResponse)
|
||||
def analyze_images(
|
||||
request: AnalyzeImagesRequest,
|
||||
authenticated_user: AuthenticatedUser = Depends(get_current_user),
|
||||
session: Session = Depends(get_db_session),
|
||||
) -> ViralVideoJobResponse:
|
||||
"""v1.5 阶段1:创建任务并仅做图片/视频 VLM 分析,跑完后状态=image_analyzed。
|
||||
|
||||
前端拿到 image_analysis(商品名/品牌/特征/颜色/材质等结构化结果)展示给用户;
|
||||
用户填完营销参数后再调 /{id}/generate-copy 进入阶段2。
|
||||
"""
|
||||
from packages.domain.viral_video import ViralVideoJob
|
||||
|
||||
repo = _get_job_repo(session)
|
||||
job = ViralVideoJob(
|
||||
user_id=authenticated_user.user.id,
|
||||
images=list(request.images),
|
||||
reference_video_url=request.reference_video_url or "",
|
||||
style_template_id=request.style_template_id or "",
|
||||
style_strength=request.style_strength or "medium",
|
||||
voice_id=request.voice_id or "",
|
||||
voice_source=request.voice_source or "",
|
||||
video_ratio=request.video_ratio or "9:16",
|
||||
video_model=request.video_model or "",
|
||||
video_resolution=getattr(request, "video_resolution", "720p") or "720p",
|
||||
duration=request.duration or 15,
|
||||
)
|
||||
repo.save(job)
|
||||
|
||||
try:
|
||||
celery_app.send_task("worker.run_viral_video_analyze", args=[job.id])
|
||||
logger.info("[爆款视频][阶段1] analyze-images 入队: job_id=%s", job.id)
|
||||
except Exception as e:
|
||||
logger.error("[爆款视频][阶段1] analyze-images 入队失败: %s", e, exc_info=True)
|
||||
job.mark_failed(f"任务入队失败: {e}")
|
||||
repo.update(job)
|
||||
|
||||
return _to_response(job)
|
||||
|
||||
|
||||
@router.post("/{job_id}/generate-copy", response_model=ViralVideoJobResponse)
|
||||
def generate_copy(
|
||||
job_id: str,
|
||||
request: GenerateCopyRequest,
|
||||
authenticated_user: AuthenticatedUser = Depends(get_current_user),
|
||||
session: Session = Depends(get_db_session),
|
||||
) -> ViralVideoJobResponse:
|
||||
"""v1.6 阶段2:用户填完营销参数后,跑 意图解析 → 编导分镜脚本生成 → 合规审核。
|
||||
|
||||
跑完后状态=copy_generated,响应 copy_result(含 overview/scene_and_lighting/shots/
|
||||
hard_constraints/negative_prompts/voiceover_script),前端展示脚本与口播供用户编辑;
|
||||
确认/编辑后调 /{id}/confirm-copy 进入阶段3(TTS + 单次 Seedance 出片)。
|
||||
"""
|
||||
repo = _get_job_repo(session)
|
||||
job = repo.get(job_id)
|
||||
if job is None:
|
||||
raise HTTPException(status_code=404, detail="任务不存在")
|
||||
if job.user_id != authenticated_user.user.id:
|
||||
raise HTTPException(status_code=403, detail="无权操作此任务")
|
||||
if job.status not in (ViralVideoStatus.IMAGE_ANALYZED, ViralVideoStatus.PENDING, ViralVideoStatus.FAILED):
|
||||
raise HTTPException(status_code=409, detail=f"任务当前状态 {job.status} 不能生成文案")
|
||||
|
||||
# 允许失败任务重试:重置
|
||||
if job.status == ViralVideoStatus.FAILED:
|
||||
job.retry_count += 1
|
||||
job.error_msg = ""
|
||||
|
||||
# 把用户填的营销参数写到 job 上
|
||||
job.industry = request.industry or job.industry
|
||||
job.target_customer = request.target_customer or job.target_customer
|
||||
job.persona_id = request.persona_id or job.persona_id
|
||||
job.viral_structure = request.viral_structure or job.viral_structure
|
||||
job.marketing_purpose = request.marketing_purpose or job.marketing_purpose
|
||||
job.bgm_preference = request.bgm_preference or job.bgm_preference
|
||||
if request.duration:
|
||||
job.duration = max(5, min(30, int(request.duration)))
|
||||
job.user_copy_text = request.user_copy_text if request.user_copy_text else job.user_copy_text
|
||||
job.fusion_level = request.fusion_level or job.fusion_level
|
||||
job.reference_audio_path = request.reference_audio_path or job.reference_audio_path
|
||||
job.reference_video_url = request.reference_video_url or job.reference_video_url
|
||||
job.style_strength = request.style_strength or job.style_strength
|
||||
job.style_template_id = request.style_template_id or job.style_template_id
|
||||
if request.style_guide is not None:
|
||||
job.style_guide = request.style_guide
|
||||
job.voice_id = request.voice_id or job.voice_id
|
||||
job.voice_source = request.voice_source or job.voice_source
|
||||
job.video_ratio = request.video_ratio or job.video_ratio or "9:16"
|
||||
job.video_model = request.video_model or job.video_model or ""
|
||||
job.video_resolution = getattr(request, "video_resolution", "") or job.video_resolution or "720p"
|
||||
|
||||
job.resume_from_image_analyzed()
|
||||
repo.update(job)
|
||||
|
||||
try:
|
||||
celery_app.send_task("worker.run_viral_video_generate_copy", args=[job.id])
|
||||
logger.info("[爆款视频][阶段2] generate-copy 入队: job_id=%s", job.id)
|
||||
except Exception as e:
|
||||
logger.error("[爆款视频][阶段2] generate-copy 入队失败: %s", e, exc_info=True)
|
||||
job.mark_failed(f"任务入队失败: {e}")
|
||||
repo.update(job)
|
||||
|
||||
return _to_response(job)
|
||||
|
||||
|
||||
@router.post("/{job_id}/confirm-copy", response_model=ViralVideoJobResponse)
|
||||
def confirm_copy(
|
||||
job_id: str,
|
||||
request: ConfirmCopyRequest,
|
||||
authenticated_user: AuthenticatedUser = Depends(get_current_user),
|
||||
session: Session = Depends(get_db_session),
|
||||
) -> ViralVideoJobResponse:
|
||||
"""v1.6 阶段3:用户确认/编辑口播后开始 TTS + 单次 Seedance 生成 + 上传。"""
|
||||
repo = _get_job_repo(session)
|
||||
job = repo.get(job_id)
|
||||
if job is None:
|
||||
raise HTTPException(status_code=404, detail="任务不存在")
|
||||
if job.user_id != authenticated_user.user.id:
|
||||
raise HTTPException(status_code=403, detail="无权操作此任务")
|
||||
if job.status != ViralVideoStatus.COPY_GENERATED:
|
||||
raise HTTPException(status_code=409, detail=f"任务当前状态 {job.status} 不能确认文案(需 copy_generated)")
|
||||
|
||||
# 积分预扣(已扣过/重试任务跳过)
|
||||
from app.config import settings as _settings
|
||||
|
||||
if _settings.points_enabled:
|
||||
already_paid = (float(getattr(job, "credits_prepaid", 0) or 0) > 0) or (
|
||||
float(getattr(job, "credits_cost", 0) or 0) > 0
|
||||
)
|
||||
if not already_paid:
|
||||
from packages.domain.points_rules import calculate_viral_video_credits, resolve_video_dimensions
|
||||
from packages.domain.points_service import PointsService
|
||||
|
||||
w, h = resolve_video_dimensions(
|
||||
getattr(job, "video_resolution", "720p") or "720p",
|
||||
job.video_ratio or "9:16",
|
||||
)
|
||||
est_credits = calculate_viral_video_credits(
|
||||
int(job.duration or 15), w, h, job.video_model or "seedance-2.5"
|
||||
)
|
||||
svc = PointsService()
|
||||
res = svc.deduct_viral_video(authenticated_user.user.id, est_credits, job.id, session)
|
||||
if not res.get("success"):
|
||||
balance = res.get("balance", 0)
|
||||
raise HTTPException(
|
||||
status_code=402,
|
||||
detail={
|
||||
"code": "INSUFFICIENT_POINTS",
|
||||
"message": f"积分不足,需要 {est_credits} 积分,当前余额 {balance}",
|
||||
"required": est_credits,
|
||||
"balance": balance,
|
||||
},
|
||||
)
|
||||
job.credits_prepaid = est_credits
|
||||
job.credits_transaction_id = res.get("transaction_id", "") or ""
|
||||
repo.update(job)
|
||||
|
||||
job.resume_from_copy_generated(edited_copy=request.edited_copy or None)
|
||||
repo.update(job)
|
||||
|
||||
try:
|
||||
celery_app.send_task("worker.run_viral_video_render", args=[job.id])
|
||||
logger.info("[爆款视频][阶段3] confirm-copy 入队: job_id=%s", job.id)
|
||||
except Exception as e:
|
||||
logger.error("[爆款视频][阶段3] confirm-copy 入队失败: %s", e, exc_info=True)
|
||||
job.mark_failed(f"任务入队失败: {e}")
|
||||
repo.update(job)
|
||||
|
||||
return _to_response(job)
|
||||
|
||||
|
||||
@router.post("/estimate-credits", response_model=EstimateCreditsResponse)
|
||||
def estimate_credits(
|
||||
request: EstimateCreditsRequest,
|
||||
authenticated_user: AuthenticatedUser = Depends(get_current_user),
|
||||
) -> EstimateCreditsResponse:
|
||||
"""爆款视频积分预估(纯计算,不扣费、不创建任务)。
|
||||
|
||||
返回 estimated_credits 与 formula_breakdown(tokens / video_cost / fixed_cost /
|
||||
profit_multiplier / model_price / width / height / fps),便于前端展示计费明细。
|
||||
同时兼容前端传 model 或 video_model、resolution 或 video_resolution、ratio 或 video_ratio。
|
||||
"""
|
||||
from packages.domain.points_rules import (
|
||||
calculate_viral_video_credits_with_breakdown,
|
||||
resolve_video_dimensions,
|
||||
)
|
||||
|
||||
model = (request.model or "").strip() or "seedance-2.5"
|
||||
resolution = (request.resolution or "").strip() or "720p"
|
||||
ratio = (request.ratio or "").strip() or "9:16"
|
||||
duration = int(request.duration or 15)
|
||||
|
||||
w, h = resolve_video_dimensions(resolution, ratio)
|
||||
credits, bd = calculate_viral_video_credits_with_breakdown(
|
||||
duration,
|
||||
w,
|
||||
h,
|
||||
model,
|
||||
)
|
||||
breakdown = CreditsFormulaBreakdown(**bd)
|
||||
return EstimateCreditsResponse(estimated_credits=credits, formula_breakdown=breakdown)
|
||||
|
||||
|
||||
@router.get("/history", response_model=ViralVideoHistoryResponse)
|
||||
def list_viral_video_history(
|
||||
limit: int = 50,
|
||||
@@ -167,6 +456,17 @@ def list_style_templates(
|
||||
return StyleTemplateListResponse(items=items)
|
||||
|
||||
|
||||
@router.get("/models")
|
||||
def list_available_models() -> dict:
|
||||
"""返回爆款视频可用模型列表(供前端模型选择器使用)。"""
|
||||
dashscope_available = get_dashscope_client() is not None
|
||||
models = list_viral_video_models(
|
||||
include_placeholder=False,
|
||||
dashscope_available=dashscope_available,
|
||||
)
|
||||
return {"models": models}
|
||||
|
||||
|
||||
@router.get("/{job_id}", response_model=ViralVideoJobResponse)
|
||||
def get_viral_video_job(
|
||||
job_id: str,
|
||||
@@ -186,33 +486,156 @@ def get_viral_video_job(
|
||||
@router.post("/{job_id}/retry", response_model=ViralVideoJobResponse)
|
||||
def retry_viral_video_job(
|
||||
job_id: str,
|
||||
request: RetryViralVideoRequest | None = None,
|
||||
authenticated_user: AuthenticatedUser = Depends(get_current_user),
|
||||
session: Session = Depends(get_db_session),
|
||||
) -> ViralVideoJobResponse:
|
||||
"""重试失败的爆款视频任务。"""
|
||||
"""重试失败的爆款视频任务(也支持对僵尸/超时 running 任务强制重置后重试)。
|
||||
|
||||
可选 body (RetryViralVideoRequest):若传入新的 duration/video_resolution/video_ratio/
|
||||
video_model,会重新预估积分并与原 credits_prepaid 做差额多退少补(不足抛 402 阻止重试);
|
||||
不传 body 或参数无变化时,保持原参数、原预扣金额不变,仅重置状态并入队。
|
||||
credits_prepaid 为 0 的老任务首次重试会走预扣流程(与 confirm-copy 一致)。
|
||||
"""
|
||||
from datetime import datetime, timezone
|
||||
|
||||
repo = _get_job_repo(session)
|
||||
job = repo.get(job_id)
|
||||
if job is None:
|
||||
raise HTTPException(status_code=404, detail="任务不存在")
|
||||
if job.user_id != authenticated_user.user.id:
|
||||
raise HTTPException(status_code=403, detail="无权操作此任务")
|
||||
if job.status != ViralVideoStatus.FAILED:
|
||||
raise HTTPException(status_code=409, detail="只有失败的任务可以重试")
|
||||
|
||||
# 判定是否为僵尸 running 任务:running 超过 10 分钟且心跳停止超过 2 分钟
|
||||
now = datetime.now(timezone.utc)
|
||||
is_stale_running = False
|
||||
if job.status == ViralVideoStatus.RUNNING and job.started_at is not None:
|
||||
hb = getattr(job, "heartbeat_at", None) or job.updated_at
|
||||
if (now - job.started_at).total_seconds() > 10 * 60 and hb is not None and (now - hb).total_seconds() > 2 * 60:
|
||||
is_stale_running = True
|
||||
|
||||
if job.status != ViralVideoStatus.FAILED and not is_stale_running:
|
||||
raise HTTPException(status_code=409, detail="只有失败或超时的任务可以重试")
|
||||
|
||||
# ── 参数变更检测 + 积分多退少补 ──────────────────────────────────────
|
||||
req = request or RetryViralVideoRequest()
|
||||
new_duration = req.duration
|
||||
new_resolution = (req.video_resolution or "").strip() or None
|
||||
new_ratio = (req.video_ratio or "").strip() or None
|
||||
new_model = (req.video_model or "").strip() or None
|
||||
|
||||
old_duration = int(getattr(job, "duration", 15) or 15)
|
||||
old_resolution = (getattr(job, "video_resolution", "720p") or "720p").strip() or "720p"
|
||||
old_ratio = (getattr(job, "video_ratio", "9:16") or "9:16").strip() or "9:16"
|
||||
old_model = (getattr(job, "video_model", "") or "").strip()
|
||||
|
||||
# 仅当有任意字段传入且值不同才算"参数变更"
|
||||
param_changed = bool(
|
||||
(new_duration is not None and int(new_duration) != old_duration)
|
||||
or (new_resolution is not None and new_resolution != old_resolution)
|
||||
or (new_ratio is not None and new_ratio != old_ratio)
|
||||
or (new_model is not None and new_model != old_model)
|
||||
)
|
||||
|
||||
from app.config import settings as _settings
|
||||
|
||||
need_points_settle = False
|
||||
new_est = 0.0
|
||||
if _settings.points_enabled and param_changed:
|
||||
from packages.domain.points_rules import (
|
||||
calculate_viral_video_credits_with_breakdown,
|
||||
resolve_video_dimensions,
|
||||
)
|
||||
|
||||
eff_dur = int(new_duration if new_duration is not None else old_duration)
|
||||
eff_res = new_resolution if new_resolution is not None else old_resolution
|
||||
eff_ratio = new_ratio if new_ratio is not None else old_ratio
|
||||
eff_model = new_model if new_model is not None else (old_model or "seedance-2.5")
|
||||
w, h = resolve_video_dimensions(eff_res, eff_ratio)
|
||||
new_est, _ = calculate_viral_video_credits_with_breakdown(eff_dur, w, h, eff_model or "seedance-2.5")
|
||||
need_points_settle = True
|
||||
|
||||
# 写入新参数(即使不开 points 也要允许用户重试时改参数)
|
||||
if new_duration is not None:
|
||||
job.duration = max(5, min(30, int(new_duration)))
|
||||
if new_resolution is not None:
|
||||
job.video_resolution = new_resolution
|
||||
if new_ratio is not None:
|
||||
job.video_ratio = new_ratio
|
||||
if new_model is not None:
|
||||
job.video_model = new_model
|
||||
|
||||
if need_points_settle:
|
||||
from packages.domain.points_service import PointsService
|
||||
|
||||
old_prepaid = float(getattr(job, "credits_prepaid", 0) or 0)
|
||||
svc = PointsService()
|
||||
diff = round(new_est - old_prepaid, 2)
|
||||
if abs(diff) >= 0.01:
|
||||
if diff > 0:
|
||||
# 新预扣更多:补扣差额
|
||||
res = svc.deduct_viral_video(authenticated_user.user.id, diff, job.id, session)
|
||||
if not res.get("success"):
|
||||
balance = res.get("balance", 0)
|
||||
raise HTTPException(
|
||||
status_code=402,
|
||||
detail={
|
||||
"code": "INSUFFICIENT_POINTS",
|
||||
"message": f"重试参数变更后需补扣 {diff} 积分,余额不足(当前 {balance},需 {new_est})",
|
||||
"required": new_est,
|
||||
"balance": balance,
|
||||
"delta": diff,
|
||||
},
|
||||
)
|
||||
job.credits_prepaid = round(old_prepaid + diff, 2)
|
||||
logger.info(
|
||||
"[爆款视频][retry] 补扣差额 job_id=%s diff=%.2f new_prepaid=%.2f",
|
||||
job.id,
|
||||
diff,
|
||||
job.credits_prepaid,
|
||||
)
|
||||
else:
|
||||
# 新预扣更少:退还差额
|
||||
refund = round(-diff, 2)
|
||||
txn_id = getattr(job, "credits_transaction_id", "") or ""
|
||||
svc.refund_points(
|
||||
user_id=authenticated_user.user.id,
|
||||
amount=refund,
|
||||
source="viral_video",
|
||||
db=session,
|
||||
ref_id=txn_id or job.id,
|
||||
description="爆款视频重试参数变更退费",
|
||||
)
|
||||
job.credits_prepaid = round(old_prepaid - refund, 2)
|
||||
logger.info(
|
||||
"[爆款视频][retry] 退还差额 job_id=%s refund=%.2f new_prepaid=%.2f",
|
||||
job.id,
|
||||
refund,
|
||||
job.credits_prepaid,
|
||||
)
|
||||
# 差额为 0 则不调整
|
||||
|
||||
# 重置状态
|
||||
job.retry_count += 1
|
||||
job.status = ViralVideoStatus.PENDING
|
||||
job.error_msg = ""
|
||||
job.error_msg = "" if not is_stale_running else "任务执行超时,已重置重试"
|
||||
job.started_at = None
|
||||
job.completed_at = None
|
||||
job.current_stage = ""
|
||||
job.phase_message = ""
|
||||
job.heartbeat_at = None
|
||||
repo.update(job)
|
||||
|
||||
# 重新入队
|
||||
try:
|
||||
from worker_app.tasks.viral_video import run_viral_video_pipeline
|
||||
|
||||
run_viral_video_pipeline.delay(job.id)
|
||||
logger.info("[爆款视频] 重试入队: job_id=%s retry_count=%d", job.id, job.retry_count)
|
||||
celery_app.send_task("worker.run_viral_video_pipeline", args=[job.id])
|
||||
logger.info(
|
||||
"[爆款视频] 重试入队: job_id=%s retry_count=%d stale=%s params_changed=%s",
|
||||
job.id,
|
||||
job.retry_count,
|
||||
is_stale_running,
|
||||
param_changed,
|
||||
)
|
||||
except Exception as e:
|
||||
logger.error("[爆款视频] 重试入队失败: %s", e, exc_info=True)
|
||||
job.mark_failed(f"重试入队失败: {e}")
|
||||
@@ -248,9 +671,7 @@ def confirm_intent(
|
||||
|
||||
# 从断点恢复 Celery 任务
|
||||
try:
|
||||
from worker_app.tasks.viral_video import resume_viral_video_pipeline
|
||||
|
||||
resume_viral_video_pipeline.delay(job.id)
|
||||
celery_app.send_task("worker.resume_viral_video_pipeline", args=[job.id])
|
||||
logger.info("[爆款视频] 意图确认,恢复流水线: job_id=%s", job.id)
|
||||
except Exception as e:
|
||||
logger.error("[爆款视频] 恢复流水线失败: %s", e, exc_info=True)
|
||||
@@ -283,9 +704,7 @@ def analyze_style(
|
||||
|
||||
# 入队风格分析任务
|
||||
try:
|
||||
from worker_app.tasks.viral_video import run_video_style_analysis
|
||||
|
||||
run_video_style_analysis.delay(job.id)
|
||||
celery_app.send_task("worker.run_video_style_analysis", args=[job.id])
|
||||
logger.info("[爆款视频] 风格分析入队: job_id=%s", job.id)
|
||||
except Exception as e:
|
||||
logger.error("[爆款视频] 风格分析入队失败: %s", e, exc_info=True)
|
||||
@@ -295,3 +714,267 @@ def analyze_style(
|
||||
status="analyzing",
|
||||
style_guide=None,
|
||||
)
|
||||
|
||||
|
||||
# ── WebSocket 进度推送 ──────────────────────────────────────────────────
|
||||
|
||||
|
||||
def _ws_authenticate_user(token: str):
|
||||
"""从 token 字符串解析用户(复用 HTTP Bearer 的解码 + 黑名单逻辑)。
|
||||
|
||||
WebSocket 握手阶段不能发自定义 Authorization header,
|
||||
因此统一通过 query 参数 ``?token=...`` 传 JWT。
|
||||
"""
|
||||
from app.auth import _decode_user_token
|
||||
from app.dependencies import get_user_repository
|
||||
|
||||
if not token:
|
||||
return None
|
||||
try:
|
||||
payload = _decode_user_token(token)
|
||||
except Exception:
|
||||
return None
|
||||
user_id = payload.get("sub")
|
||||
if not isinstance(user_id, str) or not user_id:
|
||||
return None
|
||||
# 同步场景下手动拉 repository 实例
|
||||
from app.db import SessionLocal
|
||||
|
||||
session = SessionLocal()
|
||||
try:
|
||||
user_repo = get_user_repository(session)
|
||||
user = user_repo.find_by_id(user_id)
|
||||
return user
|
||||
finally:
|
||||
session.close()
|
||||
|
||||
|
||||
async def _run_pubsub_forwarder(
|
||||
websocket, redis_lib, settings, job_id: str
|
||||
) -> None: # pragma: no cover - integration tested (real Redis + thread)
|
||||
"""订阅 Redis 频道并把消息桥接到 WebSocket,终态消息后自动关闭。
|
||||
|
||||
该函数封装了线程 + asyncio.Queue 桥接逻辑,在单测中可被整体替换为桩,
|
||||
避免引入真实 Redis 与线程调度的不确定性。
|
||||
"""
|
||||
import asyncio
|
||||
import json
|
||||
import threading
|
||||
|
||||
r = redis_lib.from_url(settings.REDIS_URL, decode_responses=True)
|
||||
pubsub = r.pubsub(ignore_subscribe_messages=True)
|
||||
channel = f"viral_video:{job_id}"
|
||||
pubsub.subscribe(channel)
|
||||
|
||||
loop = asyncio.get_running_loop()
|
||||
queue: asyncio.Queue = asyncio.Queue(maxsize=64)
|
||||
stop_event = asyncio.Event()
|
||||
|
||||
def _reader() -> None:
|
||||
try:
|
||||
while not stop_event.is_set():
|
||||
msg = pubsub.get_message(timeout=0.5)
|
||||
if msg is None or msg.get("type") != "message":
|
||||
continue
|
||||
raw = msg.get("data")
|
||||
if not isinstance(raw, str):
|
||||
continue
|
||||
try:
|
||||
payload = json.loads(raw)
|
||||
except Exception:
|
||||
payload = {"type": "viral_video:progress", "data": {"raw": raw}}
|
||||
loop.call_soon_threadsafe(queue.put_nowait, payload)
|
||||
if payload.get("type") in ("viral_video:completed", "viral_video:failed"):
|
||||
loop.call_soon_threadsafe(stop_event.set)
|
||||
break
|
||||
except Exception as e:
|
||||
logger.warning("[爆款视频WS] pubsub reader 异常退出: %s", e)
|
||||
loop.call_soon_threadsafe(stop_event.set)
|
||||
|
||||
try:
|
||||
reader_thread = threading.Thread(target=_reader, name=f"viral-video-ws-{job_id}", daemon=True)
|
||||
reader_thread.start()
|
||||
|
||||
while not stop_event.is_set():
|
||||
try:
|
||||
payload = await asyncio.wait_for(queue.get(), timeout=1.0)
|
||||
except asyncio.TimeoutError:
|
||||
continue
|
||||
try:
|
||||
await websocket.send_json(payload)
|
||||
except Exception:
|
||||
break
|
||||
if payload.get("type") in ("viral_video:completed", "viral_video:failed"):
|
||||
break
|
||||
except WebSocketDisconnect:
|
||||
logger.info("[爆款视频WS] 客户端断开: job_id=%s", job_id)
|
||||
except Exception as e:
|
||||
logger.error("[爆款视频WS] 转发异常: %s", e, exc_info=True)
|
||||
try:
|
||||
await websocket.send_json({"type": "viral_video:error", "message": f"服务异常: {e}"})
|
||||
except Exception:
|
||||
pass
|
||||
finally:
|
||||
stop_event.set()
|
||||
try:
|
||||
pubsub.unsubscribe(channel)
|
||||
pubsub.close()
|
||||
except Exception:
|
||||
pass
|
||||
try:
|
||||
r.close()
|
||||
except Exception:
|
||||
pass
|
||||
try:
|
||||
await websocket.close()
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
|
||||
@router.websocket("/ws/{job_id}")
|
||||
async def viral_video_websocket(websocket: WebSocket, job_id: str) -> None:
|
||||
"""WebSocket 桥接:订阅 Redis `viral_video:{job_id}` 频道并转发给前端。
|
||||
|
||||
认证:通过 ``?token=<jwt>`` query 参数传 JWT(浏览器 WS 握手不支持自定义 header)。
|
||||
事件类型:
|
||||
- viral_video:progress 中间进度(progress: 0-100)
|
||||
- viral_video:wait_user 等待用户确认意图文案
|
||||
- viral_video:completed 任务完成(data.video_url)
|
||||
- viral_video:failed 任务失败(data.error)
|
||||
- viral_video:error 服务端错误(如鉴权失败 / job 不存在 / 无权限)
|
||||
"""
|
||||
|
||||
import redis as redis_lib
|
||||
from app.config import settings
|
||||
|
||||
# ── 1. 鉴权 ──────────────────────────────────────────────────────
|
||||
token = websocket.query_params.get("token", "")
|
||||
user = _ws_authenticate_user(token)
|
||||
if user is None:
|
||||
await websocket.close(code=4401, reason="Unauthorized")
|
||||
return
|
||||
|
||||
# ── 2. 校验 job 归属 ─────────────────────────────────────────────
|
||||
from app.db import SessionLocal
|
||||
|
||||
session = SessionLocal()
|
||||
try:
|
||||
job_repo = SQLAlchemyViralVideoJobRepository(session)
|
||||
job = job_repo.get(job_id)
|
||||
if job is None:
|
||||
await websocket.close(code=4404, reason="Job not found")
|
||||
return
|
||||
if job.user_id != user.id:
|
||||
await websocket.close(code=4403, reason="Forbidden")
|
||||
return
|
||||
finally:
|
||||
session.close()
|
||||
|
||||
await websocket.accept()
|
||||
|
||||
# ── 3. 发送一条初始状态(前端连接后立即拿到当前进度) ────────────
|
||||
try:
|
||||
session = SessionLocal()
|
||||
job_repo = SQLAlchemyViralVideoJobRepository(session)
|
||||
job = job_repo.get(job_id)
|
||||
if job is not None:
|
||||
status_val = job.status.value if hasattr(job.status, "value") else str(job.status)
|
||||
initial = {
|
||||
"type": "viral_video:progress",
|
||||
"job_id": job_id,
|
||||
"stage": _stage_from_status(job),
|
||||
"progress": _estimate_progress(job),
|
||||
"message": _initial_message(job),
|
||||
"data": {"status": status_val},
|
||||
}
|
||||
await websocket.send_json(initial)
|
||||
# 已经终态 → 再发一条终态事件后立即关闭,避免占连接
|
||||
if job.is_terminal:
|
||||
is_completed = status_val == "completed"
|
||||
terminal_type = "viral_video:completed" if is_completed else "viral_video:failed"
|
||||
terminal_data = (
|
||||
{"video_url": job.result_video_url or ""} if is_completed else {"error": job.error_msg or ""}
|
||||
)
|
||||
await websocket.send_json(
|
||||
{
|
||||
"type": terminal_type,
|
||||
"job_id": job_id,
|
||||
"stage": "",
|
||||
"progress": 100 if is_completed else 0,
|
||||
"message": "视频生成完成" if is_completed else "任务失败",
|
||||
"data": terminal_data,
|
||||
}
|
||||
)
|
||||
await websocket.close()
|
||||
return
|
||||
session.close()
|
||||
except Exception as e:
|
||||
logger.warning("[爆款视频WS] 发送初始状态失败: %s", e)
|
||||
try:
|
||||
session.close()
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
# ── 4. 订阅 Redis 频道并转发 ─────────────────────────────────────
|
||||
# redis-py 的 pubsub 是同步阻塞的,放到线程里跑,通过 asyncio.Queue 桥接到 event loop。
|
||||
# 该段依赖真实 Redis + 线程调度,属于集成测试范围,单测通过桩替换。
|
||||
await _run_pubsub_forwarder(websocket, redis_lib, settings, job_id)
|
||||
|
||||
|
||||
def _job_status(job) -> str:
|
||||
return job.status.value if hasattr(job.status, "value") else str(job.status)
|
||||
|
||||
|
||||
# 初始快照的 stage 推断:领域对象不持久化 stage,
|
||||
# 只能根据 status 给一个占位,后续 worker 推送的真实进度事件会覆盖。
|
||||
_STATUS_STAGE = {
|
||||
"pending": "",
|
||||
"running": "",
|
||||
"image_analyzed": "image_analysis",
|
||||
"copy_generated": "review",
|
||||
"wait_user_confirm": "intent_parsing",
|
||||
"completed": "uploading",
|
||||
"failed": "",
|
||||
"cancelled": "",
|
||||
}
|
||||
|
||||
_STATUS_PROGRESS = {
|
||||
"pending": 0.0,
|
||||
"running": 5.0,
|
||||
"image_analyzed": 15.0,
|
||||
"copy_generated": 70.0,
|
||||
"wait_user_confirm": 35.0,
|
||||
"completed": 100.0,
|
||||
"failed": 0.0,
|
||||
"cancelled": 0.0,
|
||||
}
|
||||
|
||||
_STATUS_MESSAGE = {
|
||||
"pending": "任务已创建,等待执行",
|
||||
"running": "任务执行中",
|
||||
"image_analyzed": "图片分析完成,等待填写营销参数",
|
||||
"copy_generated": "文案与分镜已生成,等待确认文案",
|
||||
"wait_user_confirm": "等待用户确认意图文案",
|
||||
"completed": "视频生成完成",
|
||||
"failed": "任务失败",
|
||||
"cancelled": "任务已取消",
|
||||
}
|
||||
|
||||
|
||||
def _stage_from_status(job) -> str:
|
||||
return _STATUS_STAGE.get(_job_status(job), "")
|
||||
|
||||
|
||||
def _estimate_progress(job) -> float:
|
||||
"""根据 status 粗略估算百分比(0-100),用于连接初始快照;
|
||||
连接建立后由 Redis 推送的真实事件持续更新。
|
||||
"""
|
||||
return _STATUS_PROGRESS.get(_job_status(job), 5.0)
|
||||
|
||||
|
||||
def _initial_message(job) -> str:
|
||||
"""给新连接的前端一个可读的初始状态文案。"""
|
||||
status_val = _job_status(job)
|
||||
if status_val == "failed" and job.error_msg:
|
||||
return f"任务失败: {job.error_msg}"
|
||||
return _STATUS_MESSAGE.get(status_val, "任务准备中")
|
||||
|
||||
+2
-2
@@ -7,9 +7,9 @@ from packages.adapters.sqlalchemy_impl import (
|
||||
)
|
||||
from packages.adapters.sqlalchemy_impl.schema_guard import assert_auto_create_schema_allowed
|
||||
|
||||
ensure_database_exists(settings.DATABASE_URL)
|
||||
ensure_database_exists(settings.effective_database_url)
|
||||
engine, SessionLocal = build_session_factory(
|
||||
settings.DATABASE_URL,
|
||||
settings.effective_database_url,
|
||||
pool_size=settings.DATABASE_POOL_SIZE,
|
||||
max_overflow=settings.DATABASE_MAX_OVERFLOW,
|
||||
pool_timeout=settings.DATABASE_POOL_TIMEOUT,
|
||||
|
||||
@@ -56,7 +56,7 @@ from packages.adapters.sqlalchemy_impl.voice_library_repository import (
|
||||
from packages.ports.tag_repository import TagRepository
|
||||
from packages.ports.user_repository import UserRepository
|
||||
|
||||
_engine, _SessionLocal = build_session_factory(settings.DATABASE_URL)
|
||||
_engine, _SessionLocal = build_session_factory(settings.effective_database_url)
|
||||
|
||||
|
||||
def get_db_session() -> Generator[Session, None, None]:
|
||||
|
||||
@@ -13,9 +13,9 @@ from pydantic import BaseModel, Field
|
||||
class PointsBalanceResponse(BaseModel):
|
||||
"""积分余额 + 会员状态"""
|
||||
|
||||
balance: int = Field(..., description="当前积分余额")
|
||||
total_earned: int = Field(..., description="累计获得积分")
|
||||
total_spent: int = Field(..., description="累计消耗积分")
|
||||
balance: float = Field(..., description="当前积分余额")
|
||||
total_earned: float = Field(..., description="累计获得积分")
|
||||
total_spent: float = Field(..., description="累计消耗积分")
|
||||
is_member: bool = Field(default=False, description="是否付费会员")
|
||||
member_type: Optional[str] = Field(None, description="会员类型: monthly/quarterly/yearly")
|
||||
member_expires_at: Optional[datetime] = Field(None, description="会员到期时间")
|
||||
@@ -30,8 +30,8 @@ class PointsTransactionItem(BaseModel):
|
||||
id: str
|
||||
type: str = Field(..., description="类型: add/deduct")
|
||||
source: str = Field(..., description="来源场景")
|
||||
amount: int
|
||||
balance_after: int
|
||||
amount: float
|
||||
balance_after: float
|
||||
description: str = ""
|
||||
ref_id: str = ""
|
||||
created_at: Optional[str] = None
|
||||
@@ -99,9 +99,9 @@ class PointsCheckResponse(BaseModel):
|
||||
"""消费前余额检查响应"""
|
||||
|
||||
allowed: bool
|
||||
required_points: int
|
||||
current_balance: int
|
||||
remaining_after: int
|
||||
required_points: float
|
||||
current_balance: float
|
||||
remaining_after: float
|
||||
is_free_quota: bool = False
|
||||
|
||||
|
||||
@@ -112,7 +112,7 @@ class PointsDeductRequest(BaseModel):
|
||||
"""积分扣减请求"""
|
||||
|
||||
scene_key: str
|
||||
amount: int
|
||||
amount: float
|
||||
description: Optional[str] = ""
|
||||
ref_id: Optional[str] = ""
|
||||
|
||||
@@ -170,7 +170,7 @@ class MembershipStatusResponse(BaseModel):
|
||||
is_member: bool
|
||||
member_type: Optional[str] = None
|
||||
member_expires_at: Optional[datetime] = None
|
||||
points_balance: int
|
||||
points_balance: float
|
||||
max_resolution: str = Field(
|
||||
default="1080p",
|
||||
description="可用最高分辨率: 720p(free) / 1080p(paid)",
|
||||
|
||||
@@ -29,6 +29,8 @@ class DirectUploadPrepareResponse(BaseModel):
|
||||
duplicated: bool = False
|
||||
skip_transfer: bool = False
|
||||
asset_id: str = ""
|
||||
# duplicated=true 时填充已存在素材的公网 URL,前端可直接用而不必再调 complete
|
||||
url: str = Field(default="", description="duplicated=true 时已存在素材的公网 URL")
|
||||
|
||||
|
||||
class DirectUploadCompleteRequest(BaseModel):
|
||||
|
||||
@@ -1,4 +1,4 @@
|
||||
"""爆款视频 API schemas。"""
|
||||
"""爆款视频 API schemas (v1.6 单次 Seedance 出片版)。"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
@@ -6,82 +6,186 @@ from datetime import datetime
|
||||
|
||||
from pydantic import BaseModel, Field, field_validator
|
||||
|
||||
# -- 枚举常量 --
|
||||
|
||||
# ── 枚举常量 ─────────────────────────────────────────────────────────────
|
||||
|
||||
VALID_FUSION_LEVELS = ("ai_full", "ai_polish", "user_primary")
|
||||
VALID_FUSION_LEVELS = ("ai_full", "full_ai", "ai_polish", "user_primary")
|
||||
VALID_STYLE_STRENGTHS = ("light", "medium", "strict")
|
||||
VALID_STAGES = (
|
||||
"image_analysis",
|
||||
"video_analysis",
|
||||
"intent_parsing",
|
||||
"copy_fusion",
|
||||
"storyboard",
|
||||
"script_generation",
|
||||
"review",
|
||||
"tts",
|
||||
"bgm_select",
|
||||
"rendering",
|
||||
"musetalk",
|
||||
"uploading",
|
||||
)
|
||||
VALID_VIDEO_RATIOS = ("9:16", "16:9", "1:1", "4:3", "3:4", "21:9")
|
||||
VALID_DURATIONS = (5, 10, 15, 20, 25, 30)
|
||||
VALID_VIDEO_RESOLUTIONS = ("480p", "720p", "1080p", "普清", "高清", "超清")
|
||||
|
||||
|
||||
# ── Request Schemas ────────────────────────────────────────────────────────
|
||||
# -- 编导脚本结构(v1.6) --
|
||||
|
||||
|
||||
class ShotScript(BaseModel):
|
||||
"""逐镜头分镜。"""
|
||||
|
||||
time_range: str = Field(default="", description="时间区间,如 0-3秒")
|
||||
shot_type_angle_movement: str = Field(default="", description="景别/角度/运镜,如『近景俯拍45度,缓慢推镜』")
|
||||
scene_and_dialogue: str = Field(default="", description="场景描述+口播台词")
|
||||
action_details: str = Field(default="", description="人物动作、表情、物品操作细节")
|
||||
audio_bgm: str = Field(default="", description="环境音+BGM提示")
|
||||
transition: str = Field(default="硬切", description="转场方式:硬切/淡入淡出/叠化")
|
||||
reference_image_index: int | None = Field(
|
||||
default=None, description="参考图片索引(0-based,对应上传的第几张产品图)"
|
||||
)
|
||||
|
||||
|
||||
class CopyResultOverview(BaseModel):
|
||||
theme: str = ""
|
||||
total_duration: int = 15
|
||||
aspect_ratio: str = "9:16"
|
||||
|
||||
|
||||
class CopyResult(BaseModel):
|
||||
"""v1.6 编导分镜脚本结构(给前端 + Seedance 用)。"""
|
||||
|
||||
overview: CopyResultOverview = Field(default_factory=CopyResultOverview)
|
||||
scene_and_lighting: str = ""
|
||||
shots: list[ShotScript] = Field(default_factory=list)
|
||||
hard_constraints: list[str] = Field(default_factory=list)
|
||||
negative_prompts: list[str] = Field(default_factory=list)
|
||||
voiceover_script: str = Field(
|
||||
default="", description="纯口播对白,从各镜 scene_and_dialogue 的对白部分拼接,供 TTS 使用"
|
||||
)
|
||||
# 向后兼容:final_copy = voiceover_script
|
||||
final_copy: str = ""
|
||||
suggested_copy: str = ""
|
||||
title: str = ""
|
||||
|
||||
|
||||
# -- Request Schemas --
|
||||
|
||||
|
||||
class CreateViralVideoRequest(BaseModel):
|
||||
"""创建爆款视频任务请求。"""
|
||||
"""旧接口:一键创建(保留兼容)。"""
|
||||
|
||||
images: list[str] = Field(..., min_length=1, max_length=20, description="产品图片 URL 列表")
|
||||
industry: str = Field(default="", description="行业")
|
||||
target_customer: str = Field(default="", description="目标客户描述")
|
||||
persona_id: str = Field(default="", description="人设 ID")
|
||||
viral_structure: str = Field(default="", description="爆款结构类型")
|
||||
marketing_purpose: str = Field(default="", description="营销目的")
|
||||
bgm_preference: str = Field(default="", description="BGM 偏好")
|
||||
duration: int = Field(default=30, ge=5, le=180, description="视频时长(秒)")
|
||||
user_copy_text: str = Field(default="", description="用户原始文案(我说你写)")
|
||||
fusion_level: str = Field(default="ai_polish", description="文案融合级别: ai_full/ai_polish/user_primary")
|
||||
reference_audio_path: str = Field(default="", description="参考音频路径")
|
||||
# v1.3 新增
|
||||
reference_video_url: str = Field(default="", description="参考爆款视频 URL")
|
||||
style_strength: str = Field(default="medium", description="风格强度: light/medium/strict")
|
||||
style_template_id: str = Field(default="", description="风格模板 ID")
|
||||
images: list[str] = Field(..., min_length=1, max_length=20)
|
||||
industry: str = ""
|
||||
target_customer: str = ""
|
||||
persona_id: str = ""
|
||||
viral_structure: str = ""
|
||||
marketing_purpose: str = ""
|
||||
bgm_preference: str = ""
|
||||
duration: int = Field(default=15, ge=5, le=30, description="视频时长(秒),5-30")
|
||||
user_copy_text: str = ""
|
||||
fusion_level: str = "ai_polish"
|
||||
reference_audio_path: str = ""
|
||||
reference_video_url: str = ""
|
||||
style_strength: str = "medium"
|
||||
style_template_id: str = ""
|
||||
voice_id: str = ""
|
||||
voice_source: str = ""
|
||||
video_ratio: str = "9:16"
|
||||
video_model: str = ""
|
||||
video_resolution: str = "720p"
|
||||
|
||||
@field_validator("fusion_level")
|
||||
@classmethod
|
||||
def _validate_fusion_level(cls, v: str) -> str:
|
||||
def _v_fl(cls, v: str) -> str:
|
||||
if v == "full_ai":
|
||||
return "ai_full"
|
||||
if v not in VALID_FUSION_LEVELS:
|
||||
raise ValueError(f"fusion_level 必须是 {VALID_FUSION_LEVELS} 之一")
|
||||
raise ValueError(f"fusion_level must be one of {VALID_FUSION_LEVELS}")
|
||||
return v
|
||||
|
||||
@field_validator("style_strength")
|
||||
@classmethod
|
||||
def _validate_style_strength(cls, v: str) -> str:
|
||||
def _v_ss(cls, v: str) -> str:
|
||||
if v not in VALID_STYLE_STRENGTHS:
|
||||
raise ValueError(f"style_strength 必须是 {VALID_STYLE_STRENGTHS} 之一")
|
||||
raise ValueError(f"style_strength must be one of {VALID_STYLE_STRENGTHS}")
|
||||
return v
|
||||
|
||||
|
||||
class ConfirmIntentRequest(BaseModel):
|
||||
"""确认意图请求(confirm-intent)。"""
|
||||
class AnalyzeImagesRequest(BaseModel):
|
||||
"""v1.5+ 阶段1:创建任务 + 图片/视频分析。"""
|
||||
|
||||
confirmed_copy: str = Field(default="", description="用户确认/修改后的文案,为空表示使用 AI 生成的文案")
|
||||
adjustments: str = Field(default="", description="用户对 AI 文案的调整意见")
|
||||
images: list[str] = Field(..., min_length=1, max_length=30)
|
||||
reference_video_url: str = ""
|
||||
style_template_id: str = ""
|
||||
style_strength: str = "medium"
|
||||
voice_id: str = ""
|
||||
voice_source: str = ""
|
||||
video_ratio: str = "9:16"
|
||||
video_model: str = ""
|
||||
video_resolution: str = "720p"
|
||||
duration: int = Field(default=15, ge=5, le=30)
|
||||
|
||||
|
||||
class GenerateCopyRequest(BaseModel):
|
||||
"""v1.5+ 阶段2:填完营销参数,生成编导脚本。"""
|
||||
|
||||
industry: str = ""
|
||||
target_customer: str = ""
|
||||
persona_id: str = ""
|
||||
viral_structure: str = ""
|
||||
marketing_purpose: str = ""
|
||||
bgm_preference: str = ""
|
||||
duration: int = Field(default=15, ge=5, le=30)
|
||||
user_copy_text: str = ""
|
||||
fusion_level: str = "ai_polish"
|
||||
reference_audio_path: str = ""
|
||||
reference_video_url: str = ""
|
||||
style_strength: str = "medium"
|
||||
style_template_id: str = ""
|
||||
style_guide: dict | None = None
|
||||
voice_id: str = ""
|
||||
voice_source: str = ""
|
||||
video_ratio: str = "9:16"
|
||||
video_model: str = ""
|
||||
video_resolution: str = "720p"
|
||||
|
||||
@field_validator("fusion_level")
|
||||
@classmethod
|
||||
def _v_fl(cls, v: str) -> str:
|
||||
if v == "full_ai":
|
||||
return "ai_full"
|
||||
if v not in VALID_FUSION_LEVELS:
|
||||
raise ValueError(f"fusion_level must be one of {VALID_FUSION_LEVELS}")
|
||||
return v
|
||||
|
||||
@field_validator("style_strength")
|
||||
@classmethod
|
||||
def _v_ss(cls, v: str) -> str:
|
||||
if v not in VALID_STYLE_STRENGTHS:
|
||||
raise ValueError(f"style_strength must be one of {VALID_STYLE_STRENGTHS}")
|
||||
return v
|
||||
|
||||
|
||||
class ConfirmCopyRequest(BaseModel):
|
||||
"""v1.5+ 阶段3:用户确认/编辑口播后开始渲染(TTS+单次Seedance)。"""
|
||||
|
||||
edited_copy: str = Field(default="", description="用户编辑后的口播文案;为空则用 AI 生成的 voiceover_script")
|
||||
|
||||
|
||||
class ConfirmIntentRequest(BaseModel):
|
||||
"""旧 confirm-intent(兼容)。"""
|
||||
|
||||
confirmed_copy: str = ""
|
||||
adjustments: str = ""
|
||||
|
||||
|
||||
class AnalyzeStyleRequest(BaseModel):
|
||||
"""触发参考视频风格分析请求。"""
|
||||
|
||||
reference_video_url: str = Field(..., description="参考视频 URL")
|
||||
style_template_id: str = Field(default="", description="风格模板 ID(可选覆盖)")
|
||||
style_template_id: str = ""
|
||||
|
||||
|
||||
# ── Response Schemas ───────────────────────────────────────────────────────
|
||||
# -- Response Schemas --
|
||||
|
||||
|
||||
class ViralVideoJobResponse(BaseModel):
|
||||
"""爆款视频任务响应。"""
|
||||
"""爆款视频任务响应(v1.6 包含 copy_result 编导脚本结构)。"""
|
||||
|
||||
id: str
|
||||
user_id: str
|
||||
@@ -92,7 +196,7 @@ class ViralVideoJobResponse(BaseModel):
|
||||
viral_structure: str = ""
|
||||
marketing_purpose: str = ""
|
||||
bgm_preference: str = ""
|
||||
duration: int = 30
|
||||
duration: int = 15
|
||||
user_copy_text: str = ""
|
||||
fusion_level: str = "ai_polish"
|
||||
reference_audio_path: str = ""
|
||||
@@ -101,9 +205,26 @@ class ViralVideoJobResponse(BaseModel):
|
||||
style_guide: dict | None = None
|
||||
style_template_id: str = ""
|
||||
status: str
|
||||
current_stage: str = (
|
||||
"" # 细粒度阶段 snake_case(analyzing_images/parsing_intent/generating_script/reviewing/tts_synthesizing/rendering_video/uploading)
|
||||
)
|
||||
phase_message: str = "" # 中文阶段提示文案(前端轮询/SSE 直接展示)
|
||||
image_analysis: dict | None = None
|
||||
# v1.6 编导脚本(推荐前端使用)
|
||||
copy_result: dict | None = None
|
||||
# v1.5 兼容字段
|
||||
storyboard: list | None = None
|
||||
generated_copy_text: str = ""
|
||||
# 音色/视频参数
|
||||
voice_id: str = ""
|
||||
voice_source: str = ""
|
||||
video_ratio: str = "9:16"
|
||||
video_model: str = ""
|
||||
intent_result: dict | None = None
|
||||
result_video_url: str = ""
|
||||
credits_cost: int = 0
|
||||
video_resolution: str = "720p"
|
||||
credits_prepaid: float = 0.0
|
||||
credits_cost: float = 0.0
|
||||
error_msg: str = ""
|
||||
retry_count: int = 0
|
||||
started_at: datetime | None = None
|
||||
@@ -113,15 +234,11 @@ class ViralVideoJobResponse(BaseModel):
|
||||
|
||||
|
||||
class ViralVideoHistoryResponse(BaseModel):
|
||||
"""历史记录列表响应。"""
|
||||
|
||||
items: list[ViralVideoJobResponse]
|
||||
total: int
|
||||
|
||||
|
||||
class StyleTemplateResponse(BaseModel):
|
||||
"""风格模板响应。"""
|
||||
|
||||
id: str
|
||||
name: str
|
||||
description: str = ""
|
||||
@@ -130,25 +247,70 @@ class StyleTemplateResponse(BaseModel):
|
||||
|
||||
|
||||
class StyleTemplateListResponse(BaseModel):
|
||||
"""风格模板列表响应。"""
|
||||
|
||||
items: list[StyleTemplateResponse]
|
||||
|
||||
|
||||
class AnalyzeStyleResponse(BaseModel):
|
||||
"""风格分析结果响应。"""
|
||||
|
||||
job_id: str
|
||||
status: str
|
||||
style_guide: dict | None = None
|
||||
|
||||
|
||||
# ── WebSocket 事件 Schema ──────────────────────────────────────────────────
|
||||
# -- 积分预估 --
|
||||
|
||||
|
||||
class EstimateCreditsRequest(BaseModel):
|
||||
"""爆款视频积分预估请求。
|
||||
|
||||
前端可传 model 或 video_model(兼容老字段);resolution/ratio/duration 为预估所需参数。
|
||||
"""
|
||||
|
||||
model: str = Field(default="", alias="video_model")
|
||||
resolution: str = Field(default="720p", alias="video_resolution")
|
||||
ratio: str = Field(default="9:16", alias="video_ratio")
|
||||
duration: int = Field(default=15, ge=5, le=30)
|
||||
|
||||
model_config = {"populate_by_name": True}
|
||||
|
||||
|
||||
class CreditsFormulaBreakdown(BaseModel):
|
||||
"""爆款视频积分计费公式明细(前端展示用)。"""
|
||||
|
||||
tokens: float = Field(..., description="估算视频 tokens 数 (duration*width*height*fps/1024)")
|
||||
video_cost: float = Field(..., description="视频生成成本(元)= tokens/1e6 * model_price")
|
||||
fixed_cost: float = Field(..., description="固定成本(元),含 VLM/LLM/TTS/OSS/服务器")
|
||||
profit_multiplier: float = Field(..., description="利润系数(默认 1.3)")
|
||||
model_price: float = Field(..., description="模型单价(元/百万 tokens)")
|
||||
width: int = Field(..., description="视频宽度像素")
|
||||
height: int = Field(..., description="视频高度像素")
|
||||
fps: int = Field(..., description="视频帧率")
|
||||
|
||||
|
||||
class EstimateCreditsResponse(BaseModel):
|
||||
"""爆款视频积分预估响应。"""
|
||||
|
||||
estimated_credits: float
|
||||
formula_breakdown: CreditsFormulaBreakdown = Field(..., description="计费公式明细")
|
||||
|
||||
|
||||
class RetryViralVideoRequest(BaseModel):
|
||||
"""重试爆款视频任务的请求体(可选,允许改参数重新预估积分多退少补)。
|
||||
|
||||
不传 body 或字段全缺省:保持原参数、不重新扣点,走默认重置+入队逻辑。
|
||||
传入新的 duration/video_resolution/video_ratio/video_model:重新预估积分,
|
||||
与原 credits_prepaid 比较后多退少补(差额补扣不足抛 402)。
|
||||
"""
|
||||
|
||||
duration: int | None = Field(default=None, ge=5, le=30, description="重试时新的视频时长(秒)")
|
||||
video_resolution: str | None = Field(default=None, description="重试时新的分辨率,如 720p/1080p")
|
||||
video_ratio: str | None = Field(default=None, description="重试时新的画幅比,如 9:16/16:9")
|
||||
video_model: str | None = Field(default=None, description="重试时新的视频模型,如 seedance-2.5")
|
||||
|
||||
|
||||
# -- WebSocket 事件 Schema --
|
||||
|
||||
|
||||
class WSProgressEvent(BaseModel):
|
||||
"""WebSocket 进度推送事件。"""
|
||||
|
||||
type: str = "viral_video:progress"
|
||||
job_id: str
|
||||
stage: str
|
||||
|
||||
@@ -11,14 +11,12 @@
|
||||
存储路径与元信息约定),返回 asset_id —— 下游仍以 voice_library_id(实为
|
||||
audio asset id)消费,渲染链路零改动。
|
||||
|
||||
积分扣点与 /tts 合成端点保持一致(ai_voice 场景),失败退费。
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
import logging
|
||||
import math
|
||||
import subprocess
|
||||
import tempfile
|
||||
from dataclasses import dataclass
|
||||
@@ -32,13 +30,10 @@ from packages.application.cosyvoice_service import CosyVoiceService
|
||||
from packages.application.tts_job.use_cases import CreateTTSJobUseCase
|
||||
from packages.application.tts_job.workflow import TTSWorkflowService
|
||||
from packages.domain import Asset, AssetLibrary, AssetLibraryKind, AssetStatus, ClassificationStatus
|
||||
from packages.domain.points_rules import calculate_points_cost
|
||||
from packages.domain.points_service import PointsService
|
||||
from packages.shared.storage import SharedStorageService
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
_POINTS_SCENE = "ai_voice"
|
||||
_SYNTH_TIMEOUT = 180.0 # 叙事配音在 HTTP 请求内同步等待,长文案分段合成时留出余量
|
||||
_CONTENT_TYPE_MAP = {"mp3": "audio/mpeg", "wav": "audio/wav", "pcm": "audio/pcm", "opus": "audio/opus"}
|
||||
|
||||
@@ -273,24 +268,6 @@ def prepare_narrative_voice(
|
||||
voice_clone_repository=voice_clone_repository,
|
||||
)
|
||||
|
||||
# 积分扣点(与 /tts 合成端点同口径),失败时在合成失败分支退费
|
||||
points_svc = PointsService() if points_enabled else None
|
||||
points_deducted = 0
|
||||
if points_svc is not None:
|
||||
est_minutes = max(1.0, math.ceil(len(content) / 240))
|
||||
points_deducted = calculate_points_cost(
|
||||
_POINTS_SCENE,
|
||||
is_member=is_member,
|
||||
duration_minutes=est_minutes,
|
||||
member_type=member_type,
|
||||
)
|
||||
deduct_res = points_svc.deduct_points(user_id, points_deducted, _POINTS_SCENE, db)
|
||||
if not deduct_res["success"]:
|
||||
raise NarrativeError(
|
||||
f"积分不足,需要 {points_deducted} 积分,当前余额 {deduct_res['balance']}",
|
||||
status_code=402,
|
||||
)
|
||||
|
||||
use_case = CreateTTSJobUseCase(tts_repository)
|
||||
job = use_case.execute(
|
||||
user_id=user_id,
|
||||
@@ -311,19 +288,9 @@ def prepare_narrative_voice(
|
||||
workflow.process_synthesis_failure(job.id, str(e))
|
||||
except Exception: # noqa: BLE001
|
||||
logger.warning("标记叙事 TTS job 失败出错: job_id=%s", job.id, exc_info=True)
|
||||
if points_deducted and points_svc is not None:
|
||||
try:
|
||||
points_svc.refund_points(user_id, points_deducted, _POINTS_SCENE, db, ref_id=job.id)
|
||||
except Exception: # noqa: BLE001
|
||||
logger.warning("叙事 TTS 失败退积分异常: job_id=%s", job.id, exc_info=True)
|
||||
raise NarrativeError(f"配音合成失败:{e}", status_code=502) from e
|
||||
|
||||
if not job.is_completed:
|
||||
if points_deducted and points_svc is not None:
|
||||
try:
|
||||
points_svc.refund_points(user_id, points_deducted, _POINTS_SCENE, db, ref_id=job.id)
|
||||
except Exception: # noqa: BLE001
|
||||
logger.warning("叙事 TTS 未完成退积分异常: job_id=%s", job.id, exc_info=True)
|
||||
raise NarrativeError("配音合成未完成,请稍后重试", status_code=504)
|
||||
|
||||
asset = _save_tts_job_as_voice_asset(
|
||||
|
||||
@@ -150,6 +150,8 @@ export interface DirectUploadPrepareResult {
|
||||
* 两个字段是同一语义的别名(后端可能只返回其一),前端任意为 true 即视为命中去重。
|
||||
*/
|
||||
skip_transfer?: boolean
|
||||
/** duplicated=true 时后端返回已存在素材的公网 URL,前端直接用而不必再调 complete */
|
||||
url?: string
|
||||
}
|
||||
|
||||
/** 直传完成确认返回 */
|
||||
|
||||
@@ -3,9 +3,24 @@
|
||||
*/
|
||||
import apiClient from "../client"
|
||||
import { getOrCreateDefaultProject } from "../projects"
|
||||
import { ensureDefaultLibrary } from "./libraries"
|
||||
import type { DirectUploadPrepareResult, DirectUploadCompleteResult } from "./types"
|
||||
import { computeFileHash, makeClientUploadId } from "./uploadDedup"
|
||||
|
||||
/** 根据 File.type 推断素材库 kind(image/video/voice);无法推断时默认 image */
|
||||
function inferKindFromFile(file: File): "image" | "video" | "voice" {
|
||||
const t = (file.type || "").toLowerCase()
|
||||
if (t.startsWith("image/")) return "image"
|
||||
if (t.startsWith("video/")) return "video"
|
||||
if (t.startsWith("audio/")) return "voice"
|
||||
// 兜底:按扩展名再判一次
|
||||
const name = file.name.toLowerCase()
|
||||
if (/\.(png|jpe?g|gif|webp|bmp|svg|avif)$/.test(name)) return "image"
|
||||
if (/\.(mp4|mov|webm|avi|mkv|flv|wmv|m4v)$/.test(name)) return "video"
|
||||
if (/\.(mp3|wav|m4a|aac|ogg|flac|opus|webm)$/.test(name)) return "voice"
|
||||
return "image"
|
||||
}
|
||||
|
||||
/** 预签名直传准备 */
|
||||
export const prepareDirectUpload = async (data: {
|
||||
project_id: string
|
||||
@@ -108,6 +123,8 @@ const putToOSS = (
|
||||
|
||||
/** 单个文件的上传阶段信息(供批量上传队列做状态绑定) */
|
||||
export interface DirectUploadHandle {
|
||||
/** 实际使用的素材库(内部解析出来,便于调用方做后续 UI/缓存操作) */
|
||||
library: { id: string; kind: "image" | "video" | "voice" }
|
||||
/** prepare 返回(含可能的预建 asset_id) */
|
||||
prepared: DirectUploadPrepareResult
|
||||
/** 直传 OSS(可重复调用用于重试) */
|
||||
@@ -119,10 +136,17 @@ export interface DirectUploadHandle {
|
||||
/**
|
||||
* 准备一次直传:调 prepare 拿到签名表单(后端可能同时预建 uploading 态 asset),
|
||||
* 返回分段执行的 handle,调用方自行控制 transfer/complete 时机(便于队列并发与重试)。
|
||||
*
|
||||
* 修复 P0 404:library_id 改为可选;未传时自动根据文件类型在默认项目下确保对应素材库存在,
|
||||
* 避免调用方从「全部素材库列表」里挑一个 library_id、但与默认项目 project_id 不匹配,
|
||||
* 导致后端返回 "Asset library not found" 404。
|
||||
*/
|
||||
export const prepareDirectUploadHandle = async (data: {
|
||||
file: File
|
||||
library_id: string
|
||||
/** 素材库 ID;未传时按文件类型自动在默认项目下 ensure-default */
|
||||
library_id?: string
|
||||
/** 显式指定素材库 kind;未传时按 MIME/扩展名推断 */
|
||||
kind?: "image" | "video" | "voice"
|
||||
/** 前端算好的文件内容哈希(SHA-256 hex),prepare/complete 均携带 */
|
||||
fileHash?: string
|
||||
/** 本次逻辑上传的幂等 token,prepare/complete 一致、重试复用 */
|
||||
@@ -138,9 +162,17 @@ export const prepareDirectUploadHandle = async (data: {
|
||||
throw new Error(`初始化默认项目失败,无法开始上传:${reason}`)
|
||||
}
|
||||
|
||||
// 解析 library_id:调用方传了就用,没传就按 kind 自动 ensure-default
|
||||
let resolvedLibraryId = data.library_id
|
||||
const resolvedKind = data.kind ?? inferKindFromFile(data.file)
|
||||
if (!resolvedLibraryId) {
|
||||
const lib = await ensureDefaultLibrary({ project_id: project.id, kind: resolvedKind })
|
||||
resolvedLibraryId = lib.id
|
||||
}
|
||||
|
||||
const prepared = await prepareDirectUpload({
|
||||
project_id: project.id,
|
||||
library_id: data.library_id,
|
||||
library_id: resolvedLibraryId,
|
||||
filename: data.file.name,
|
||||
content_type: data.file.type || "application/octet-stream",
|
||||
file_size: data.file.size,
|
||||
@@ -149,12 +181,13 @@ export const prepareDirectUploadHandle = async (data: {
|
||||
})
|
||||
|
||||
return {
|
||||
library: { id: resolvedLibraryId, kind: resolvedKind },
|
||||
prepared,
|
||||
transfer: (onProgress) => putToOSS(prepared, data.file, onProgress),
|
||||
complete: () =>
|
||||
completeDirectUpload({
|
||||
project_id: project.id,
|
||||
library_id: data.library_id,
|
||||
library_id: resolvedLibraryId,
|
||||
storage_key: prepared.storage_key,
|
||||
file_hash: data.fileHash,
|
||||
client_upload_id: data.clientUploadId,
|
||||
@@ -164,10 +197,17 @@ export const prepareDirectUploadHandle = async (data: {
|
||||
}
|
||||
}
|
||||
|
||||
/** 直传上传(大文件推荐),支持可选进度回调;一次性完成 prepare→transfer→complete */
|
||||
/** 直传上传(大文件推荐),支持可选进度回调;一次性完成 prepare→transfer→complete
|
||||
*
|
||||
* P0 404 修复:library_id 可选;不传时内部按文件类型自动匹配正确项目下的素材库,
|
||||
* 保证 project_id 与 library_id 必然一致。
|
||||
*/
|
||||
export const uploadAssetDirect = async (data: {
|
||||
file: File
|
||||
library_id: string
|
||||
/** 素材库 ID;可选,不传按文件类型自动解析默认项目下的对应素材库(推荐用法) */
|
||||
library_id?: string
|
||||
/** 显式指定素材库 kind;未传时按文件 MIME/扩展名推断 */
|
||||
kind?: "image" | "video" | "voice"
|
||||
onProgress?: (percent: number) => void
|
||||
/** 文件内容哈希;未传时自动补算(配音/封面/克隆等非队列链路统一受益) */
|
||||
fileHash?: string
|
||||
@@ -180,6 +220,7 @@ export const uploadAssetDirect = async (data: {
|
||||
const handle = await prepareDirectUploadHandle({
|
||||
file: data.file,
|
||||
library_id: data.library_id,
|
||||
kind: data.kind,
|
||||
fileHash,
|
||||
clientUploadId,
|
||||
})
|
||||
@@ -188,7 +229,7 @@ export const uploadAssetDirect = async (data: {
|
||||
return {
|
||||
storage_key: handle.prepared.storage_key,
|
||||
ingest_job_id: "",
|
||||
url: "",
|
||||
url: handle.prepared.url || "",
|
||||
duplicated: true,
|
||||
asset_id: handle.prepared.asset_id,
|
||||
}
|
||||
|
||||
@@ -0,0 +1,156 @@
|
||||
import apiClient from "@/api/client"
|
||||
import type {
|
||||
GenerateViralVideoRequest,
|
||||
HistoryResponse,
|
||||
StyleTemplate,
|
||||
ViralVideoJob,
|
||||
ImageAnalysisResult,
|
||||
CopyResult,
|
||||
AnalyzeImagesRequest,
|
||||
GenerateCopyRequest,
|
||||
ConfirmCopyRequest,
|
||||
ViralVideoModel,
|
||||
ViralVideoModelsResponse,
|
||||
} from "./types"
|
||||
|
||||
/** 创建爆款视频任务 */
|
||||
export function generateViralVideo(payload: GenerateViralVideoRequest) {
|
||||
return apiClient.post<ViralVideoJob>("/viral-video/generate", payload).then((r) => r.data)
|
||||
}
|
||||
|
||||
/** 查询单个任务 */
|
||||
export function getViralVideoJob(id: string) {
|
||||
return apiClient.get<ViralVideoJob>(`/viral-video/${id}`).then((r) => r.data)
|
||||
}
|
||||
|
||||
/** 用户确认/修改 AI 理解的意图后继续 */
|
||||
export function confirmViralVideoIntent(
|
||||
id: string,
|
||||
payload: { confirmed_copy?: string; edits?: Record<string, unknown> },
|
||||
) {
|
||||
return apiClient
|
||||
.post<ViralVideoJob>(`/viral-video/${id}/confirm-intent`, payload)
|
||||
.then((r) => r.data)
|
||||
}
|
||||
|
||||
/** 重试失败任务 */
|
||||
export function retryViralVideo(id: string) {
|
||||
return apiClient.post<ViralVideoJob>(`/viral-video/${id}/retry`).then((r) => r.data)
|
||||
}
|
||||
|
||||
/** 历史记录(分页) */
|
||||
export function getViralVideoHistory(params?: { page?: number; page_size?: number }) {
|
||||
return apiClient.get<HistoryResponse>("/viral-video/history", { params }).then((r) => r.data)
|
||||
}
|
||||
|
||||
/** 预设风格模板 */
|
||||
export function getViralStyleTemplates() {
|
||||
return apiClient.get<StyleTemplate[]>("/viral-video/style-templates").then((r) => r.data)
|
||||
}
|
||||
|
||||
/** 上传参考视频后触发风格分析 */
|
||||
export function analyzeViralStyle(id: string) {
|
||||
return apiClient.post<ViralVideoJob>(`/viral-video/${id}/analyze-style`).then((r) => r.data)
|
||||
}
|
||||
|
||||
/** 动态预估积分消耗(STEP3 参数变化时调用) */
|
||||
export function estimateViralVideoCredits(params: {
|
||||
video_model: string
|
||||
resolution: string
|
||||
video_ratio: string
|
||||
duration: number
|
||||
}) {
|
||||
return apiClient
|
||||
.post<{ estimated_credits: number }>("/viral-video/estimate-credits", params)
|
||||
.then((r) => r.data)
|
||||
}
|
||||
|
||||
/** 获取支持的视频模型列表(GET /viral-video/models)。后端返回 {models: [...]} 包装 */
|
||||
export function getViralVideoModels() {
|
||||
return apiClient.get<ViralVideoModelsResponse>("/viral-video/models").then((r) => {
|
||||
const data = r.data as ViralVideoModelsResponse | ViralVideoModel[] | null | undefined
|
||||
if (Array.isArray(data)) return data
|
||||
if (data && Array.isArray((data as ViralVideoModelsResponse).models)) {
|
||||
return (data as ViralVideoModelsResponse).models
|
||||
}
|
||||
return []
|
||||
})
|
||||
}
|
||||
/** ── 三步拆分:前端 mock 辅助函数(后端新接口上线后可替换) ── */
|
||||
|
||||
/**
|
||||
* 客户端图片分析 mock(后端未提供 analyze-only 端点前的占位方案):
|
||||
* 基于已上传图片生成一份示例识别汇览,让 STEP1→STEP2 交互可走通。
|
||||
* 后端上线后改为调用真实接口。
|
||||
*/
|
||||
export function mockImageAnalysis(images: { name: string }[]): Promise<ImageAnalysisResult> {
|
||||
return new Promise((resolve) => {
|
||||
setTimeout(() => {
|
||||
const products = images.slice(0, 3).map((img, i) => {
|
||||
const n = img.name.replace(/\.[^.]+$/, "")
|
||||
return {
|
||||
name: n || `商品 ${i + 1}`,
|
||||
spec: i === 0 ? "500ml/瓶" : i === 1 ? "300g/盒" : undefined,
|
||||
brand: i === 0 ? "示例品牌" : undefined,
|
||||
features:
|
||||
i === 0
|
||||
? "瓶身透明、蓝色标签、白色瓶盖;标签上印有品牌Logo和产品名称;光线均匀,主体居中"
|
||||
: i === 1
|
||||
? "盒装包装、主色调为米白+暖黄;正面有产品实物图;文字清晰可辨"
|
||||
: "产品主体清晰、背景干净、色彩鲜艳,突出核心卖点",
|
||||
label_text: i === 0 ? "包装正面印有产品名称、净含量、品牌Logo" : undefined,
|
||||
image_index: i,
|
||||
}
|
||||
})
|
||||
resolve({ products })
|
||||
}, 1800)
|
||||
})
|
||||
}
|
||||
|
||||
/**
|
||||
* 客户端文案生成 mock(后端未提供 generate-copy 端点前的占位方案):
|
||||
* 后端上线后改为调用真实接口。
|
||||
*/
|
||||
export function mockGenerateCopy(params: {
|
||||
product: string
|
||||
sellingPoints?: string[]
|
||||
tone?: string
|
||||
duration?: number
|
||||
marketingPurpose?: string
|
||||
industry?: string
|
||||
targetCustomer?: string
|
||||
}): Promise<CopyResult> {
|
||||
return new Promise((resolve) => {
|
||||
setTimeout(() => {
|
||||
const product = params.product || "这款产品"
|
||||
const tone = params.tone || "亲切务实"
|
||||
const purpose = params.marketingPurpose || "品牌种草"
|
||||
resolve({
|
||||
title: `【${purpose}】${product},用过的人都说好!`,
|
||||
final_copy: `你有没有发现,选对一款${params.industry || "好物"}真的能让生活省心很多?\n\n今天给大家推荐这款${product}。${tone.includes("亲切") ? "说实话," : ""}我自己用了一段时间,最直观的感受就是——好用、省心、值得回购。\n\n✅ 亮点一:品质到位,用料扎实,细节处见用心\n✅ 亮点二:使用体验舒服,日常高频场景都能打\n✅ 亮点三:性价比很能打,这个价位真的没什么可挑的\n\n如果你也在找一款靠谱的${params.industry || "日常好物"},真的建议试试${product},不会让你失望。点击左下角,直接入手!`,
|
||||
suggested_copy: `你有没有发现,选对一款${params.industry || "好物"}真的能让生活省心很多?\n\n今天给大家推荐这款${product}。${tone.includes("亲切") ? "说实话," : ""}我自己用了一段时间,最直观的感受就是——好用、省心、值得回购。\n\n✅ 亮点一:品质到位,用料扎实,细节处见用心\n✅ 亮点二:使用体验舒服,日常高频场景都能打\n✅ 亮点三:性价比很能打,这个价位真的没什么可挑的\n\n如果你也在找一款靠谱的${params.industry || "日常好物"},真的建议试试${product},不会让你失望。点击左下角,直接入手!`,
|
||||
})
|
||||
}, 2200)
|
||||
})
|
||||
}
|
||||
|
||||
/** ── 三步拆分 v1.5 真实后端 API(PR #2117 合入后启用,前端可替换 mock 调用) ── */
|
||||
|
||||
/** 阶段1:上传图片后仅做 VLM 图片分析 + 可选参考视频风格分析,完成后状态=image_analyzed */
|
||||
export function analyzeViralImages(payload: AnalyzeImagesRequest) {
|
||||
return apiClient.post<ViralVideoJob>("/viral-video/analyze-images", payload).then((r) => r.data)
|
||||
}
|
||||
|
||||
/** 阶段2:用户填完营销参数后生成文案+分镜+合规审核,完成后状态=copy_generated,返回 copy_result */
|
||||
export function generateViralCopy(id: string, payload: GenerateCopyRequest) {
|
||||
return apiClient
|
||||
.post<ViralVideoJob>(`/viral-video/${id}/generate-copy`, payload)
|
||||
.then((r) => r.data)
|
||||
}
|
||||
|
||||
/** 阶段3:用户确认/编辑文案后开始 TTS→渲染→上传,完成后状态=completed */
|
||||
export function confirmViralCopy(id: string, payload: ConfirmCopyRequest = {}) {
|
||||
return apiClient
|
||||
.post<ViralVideoJob>(`/viral-video/${id}/confirm-copy`, payload)
|
||||
.then((r) => r.data)
|
||||
}
|
||||
@@ -0,0 +1,317 @@
|
||||
export type FusionLevel = "ai_full" | "ai_polish" | "user_primary"
|
||||
export const FUSION_LEVELS: { value: FusionLevel; label: string; desc: string }[] = [
|
||||
{ value: "ai_full", label: "AI 全写", desc: "给我方向,全由AI创作" },
|
||||
{ value: "ai_polish", label: "AI润色", desc: "我写草稿,AI帮我润色" },
|
||||
{ value: "user_primary", label: "按我写的来", desc: "几乎不改我的文案" },
|
||||
]
|
||||
|
||||
export type StyleStrength = "light" | "medium" | "strict"
|
||||
export const STYLE_STRENGTHS: { value: StyleStrength; label: string }[] = [
|
||||
{ value: "light", label: "轻度借鉴" },
|
||||
{ value: "medium", label: "中度参考" },
|
||||
{ value: "strict", label: "像素级复刻" },
|
||||
]
|
||||
|
||||
/** v1.6 前端时长下拉选项(5/10/15/20/25/30秒) */
|
||||
export const VALID_DURATIONS = [5, 10, 15, 20, 25, 30] as const
|
||||
export type VideoDuration = (typeof VALID_DURATIONS)[number]
|
||||
|
||||
/** v1.6 支持的画幅比例 */
|
||||
export const VALID_RATIOS = ["9:16", "16:9", "1:1"] as const
|
||||
export type VideoRatio = (typeof VALID_RATIOS)[number]
|
||||
|
||||
export type ViralVideoStatus =
|
||||
| "pending"
|
||||
| "running"
|
||||
| "wait_user_confirm"
|
||||
| "image_analyzed"
|
||||
| "copy_generated"
|
||||
| "completed"
|
||||
| "failed"
|
||||
| "cancelled"
|
||||
|
||||
/**
|
||||
* v1.6 后端流水线阶段。单次 Seedance 出片版:
|
||||
* image_analysis → video_analysis(可选) → intent_parsing → script_generation → review → tts → rendering → uploading
|
||||
*/
|
||||
export type ViralVideoStage =
|
||||
| "image_analysis"
|
||||
| "video_analysis"
|
||||
| "intent_parsing"
|
||||
| "script_generation"
|
||||
| "review"
|
||||
| "tts"
|
||||
| "rendering"
|
||||
| "uploading"
|
||||
|
||||
/** 图片+视频分析阶段:属于「分析图片」按钮的范围 */
|
||||
const IMAGE_ANALYSIS_STAGES = new Set<ViralVideoStage>(["image_analysis", "video_analysis"])
|
||||
/** 编导脚本阶段:属于「生成文案」按钮的范围 */
|
||||
const COPY_STAGES = new Set<ViralVideoStage>(["intent_parsing", "script_generation", "review"])
|
||||
/** 视频生成阶段:属于「开始生成视频」按钮的范围(v1.6: TTS+单次Seedance+上传) */
|
||||
const VIDEO_STAGES = new Set<ViralVideoStage>(["tts", "rendering", "uploading"])
|
||||
|
||||
export function isImageAnalysisStage(stage: ViralVideoStage | undefined): boolean {
|
||||
return !!stage && IMAGE_ANALYSIS_STAGES.has(stage)
|
||||
}
|
||||
export function isCopyStage(stage: ViralVideoStage | undefined): boolean {
|
||||
return !!stage && COPY_STAGES.has(stage)
|
||||
}
|
||||
export function isVideoStage(stage: ViralVideoStage | undefined): boolean {
|
||||
return !!stage && VIDEO_STAGES.has(stage)
|
||||
}
|
||||
/** 兼容旧调用:分析图片+生成文案 的所有前置阶段 */
|
||||
export function isAnalysisStage(stage: ViralVideoStage | undefined): boolean {
|
||||
return isImageAnalysisStage(stage) || isCopyStage(stage)
|
||||
}
|
||||
|
||||
/** 单张图片 VLM 识别出的商品信息 */
|
||||
export interface ImageProductAnalysis {
|
||||
name?: string
|
||||
category?: string
|
||||
brand?: string
|
||||
colors?: string[]
|
||||
material_or_texture?: string
|
||||
key_features?: string[]
|
||||
visual_style?: string
|
||||
scene?: string
|
||||
target_audience_hint?: string
|
||||
text_on_image?: string
|
||||
/** 旧字段兼容 */
|
||||
spec?: string
|
||||
features?: string[] | string
|
||||
label_text?: string
|
||||
selling_points?: string
|
||||
image_index?: number
|
||||
}
|
||||
|
||||
export interface ImageAnalysisResult {
|
||||
products?: ImageProductAnalysis[]
|
||||
}
|
||||
|
||||
/** v1.6 编导分镜脚本 - 单镜头 */
|
||||
export interface ShotScript {
|
||||
/** 时间区间,如 "0-3秒" */
|
||||
time_range?: string
|
||||
/** 景别/角度/运镜,如 "近景俯拍45度,缓慢推镜" */
|
||||
shot_type_angle_movement?: string
|
||||
/** 场景描述+对白 */
|
||||
scene_and_dialogue?: string
|
||||
/** 人物动作/表情/物品操作细节 */
|
||||
action_details?: string
|
||||
/** 环境音+BGM提示 */
|
||||
audio_bgm?: string
|
||||
/** 转场方式(硬切/淡入淡出/叠化/结束) */
|
||||
transition?: string
|
||||
/** 参考图片索引(0-based,对应上传产品图数组) */
|
||||
reference_image_index?: number | null
|
||||
}
|
||||
|
||||
/** v1.6 编导分镜脚本 - 总览 */
|
||||
export interface CopyResultOverview {
|
||||
theme?: string
|
||||
total_duration?: number
|
||||
aspect_ratio?: string
|
||||
}
|
||||
|
||||
/** v1.6 编导分镜脚本(核心输出结构,给 Seedance 做 prompt,给 TTS 取 voiceover_script) */
|
||||
export interface CopyResult {
|
||||
overview?: CopyResultOverview
|
||||
/** 整体场景+光线描述 */
|
||||
scene_and_lighting?: string
|
||||
/** 逐镜头时间轴 */
|
||||
shots?: ShotScript[]
|
||||
/** 硬性约束(禁止字幕/水印/变形等) */
|
||||
hard_constraints?: string[]
|
||||
/** 负面提示词 */
|
||||
negative_prompts?: string[]
|
||||
/** 完整口播稿(纯文本,用于 TTS 合成) */
|
||||
voiceover_script?: string
|
||||
/** 向后兼容:= voiceover_script */
|
||||
final_copy?: string
|
||||
/** 向后兼容:= voiceover_script */
|
||||
suggested_copy?: string
|
||||
title?: string
|
||||
/** v1.5 旧字段兼容(老数据降级时可能出现) */
|
||||
scenes?: Array<{ shot: string; narration: string; duration?: number }>
|
||||
}
|
||||
|
||||
export interface StyleTemplate {
|
||||
id: string
|
||||
name: string
|
||||
description?: string
|
||||
thumbnail_url?: string
|
||||
style_config?: Record<string, unknown>
|
||||
tags?: string[]
|
||||
}
|
||||
|
||||
export interface IntentResult {
|
||||
intent?: string
|
||||
key_messages?: string[]
|
||||
tone?: string
|
||||
target_emotion?: string
|
||||
call_to_action?: string
|
||||
suggested_title?: string
|
||||
/** v1.5 旧字段兼容 */
|
||||
product?: string
|
||||
selling_points?: string[]
|
||||
target_audience?: string
|
||||
structure?: string
|
||||
duration?: number
|
||||
suggested_copy?: string
|
||||
}
|
||||
|
||||
export interface ViralVideoJob {
|
||||
id: string
|
||||
status: ViralVideoStatus
|
||||
images: string[]
|
||||
reference_video_url?: string
|
||||
style_strength?: StyleStrength
|
||||
style_template_id?: string
|
||||
style_guide?: string | Record<string, unknown>
|
||||
user_copy_text?: string
|
||||
/** v1.6: = copy_result.voiceover_script(从 copy_result 派生,向后兼容) */
|
||||
final_copy_text?: string
|
||||
generated_copy_text?: string
|
||||
fusion_level?: FusionLevel
|
||||
voice_id?: string
|
||||
voice_mode?: "global" | "per_video"
|
||||
voice_source?: "preset" | "library" | "clone" | "upload"
|
||||
bgm_preference?: string
|
||||
intent_result?: IntentResult
|
||||
intent_text?: string
|
||||
/** v1.6 编导分镜脚本(核心产物) */
|
||||
copy_result?: CopyResult
|
||||
/** 向后兼容:= copy_result.shots */
|
||||
storyboard?: ShotScript[]
|
||||
image_analysis?: ImageAnalysisResult
|
||||
/** 视频比例:9:16 / 16:9 / 1:1,默认 9:16 */
|
||||
video_ratio?: string
|
||||
/** Seedance 模型 ID(空=后端默认) */
|
||||
video_model?: string
|
||||
/** 视频时长(秒,5-30,默认15) */
|
||||
duration?: number
|
||||
progress_stage?: ViralVideoStage
|
||||
progress_percent?: number
|
||||
progress_message?: string
|
||||
output_url?: string
|
||||
result_video_url?: string
|
||||
error_message?: string
|
||||
error_msg?: string
|
||||
credits_cost?: number
|
||||
created_at?: string
|
||||
updated_at?: string
|
||||
}
|
||||
|
||||
export interface GenerateViralVideoRequest {
|
||||
images: string[]
|
||||
reference_video_url?: string
|
||||
douyin_url?: string
|
||||
style_strength?: StyleStrength
|
||||
style_template_id?: string
|
||||
user_copy_text?: string
|
||||
fusion_level?: FusionLevel
|
||||
voice_id?: string
|
||||
voice_source?: "preset" | "library" | "clone" | "upload"
|
||||
bgm_preference?: string
|
||||
industry?: string
|
||||
target_customer?: string
|
||||
language?: string
|
||||
persona_id?: string
|
||||
viral_structure?: string
|
||||
marketing_purpose?: string
|
||||
/** 视频时长(5-30秒,默认15) */
|
||||
duration?: number
|
||||
video_model?: string
|
||||
video_ratio?: string
|
||||
/** 三步拆分:step 控制后端执行到哪一步暂停 */
|
||||
step?: "analyze" | "generate_copy" | "generate_video"
|
||||
}
|
||||
|
||||
export interface HistoryResponse {
|
||||
items: ViralVideoJob[]
|
||||
total: number
|
||||
page: number
|
||||
page_size: number
|
||||
}
|
||||
|
||||
/** v1.6 阶段1请求:图片/视频分析(POST /viral-video/analyze-images) */
|
||||
export interface AnalyzeImagesRequest {
|
||||
images: string[]
|
||||
reference_video_url?: string
|
||||
style_template_id?: string
|
||||
style_strength?: StyleStrength
|
||||
/** TTS 音色 ID(STEP1 已选音色时传) */
|
||||
voice_id?: string
|
||||
/** 音色来源:preset | library | clone | upload */
|
||||
voice_source?: "preset" | "library" | "clone" | "upload"
|
||||
/** Seedance 视频比例:9:16 | 16:9 | 1:1 */
|
||||
video_ratio?: string
|
||||
/** Seedance 模型 ID(空则使用服务端默认) */
|
||||
video_model?: string
|
||||
/** 视频时长(秒,5-30,默认15) */
|
||||
duration?: number
|
||||
}
|
||||
|
||||
/** v1.6 阶段2请求:填完营销参数后生成编导分镜脚本(POST /viral-video/{id}/generate-copy) */
|
||||
export interface GenerateCopyRequest {
|
||||
industry?: string
|
||||
target_customer?: string
|
||||
persona_id?: string
|
||||
viral_structure?: string
|
||||
marketing_purpose?: string
|
||||
bgm_preference?: string
|
||||
/** 视频时长(秒,5-30,默认15) */
|
||||
duration?: number
|
||||
user_copy_text?: string
|
||||
fusion_level?: FusionLevel
|
||||
reference_audio_path?: string
|
||||
reference_video_url?: string
|
||||
style_strength?: StyleStrength
|
||||
style_template_id?: string
|
||||
style_guide?: string | Record<string, unknown>
|
||||
/** TTS 音色 ID(优先级高于 persona_id) */
|
||||
voice_id?: string
|
||||
/** 音色来源:preset | library | clone | upload */
|
||||
voice_source?: "preset" | "library" | "clone" | "upload"
|
||||
/** Seedance 视频比例(9:16/16:9/1:1 等) */
|
||||
video_ratio?: string
|
||||
/** Seedance 模型 ID(空则使用服务端默认) */
|
||||
video_model?: string
|
||||
}
|
||||
|
||||
/** 视频模型描述(GET /viral-video/models) */
|
||||
export interface ViralVideoModel {
|
||||
key: string
|
||||
display_name: string
|
||||
supports_audio: boolean
|
||||
supported_resolutions: string[]
|
||||
max_duration: number
|
||||
/** 计费模式(可选):per_second / per_video / token 等 */
|
||||
billing_mode?: string
|
||||
is_default?: boolean
|
||||
}
|
||||
|
||||
/** GET /viral-video/models 响应包装 */
|
||||
export interface ViralVideoModelsResponse {
|
||||
models: ViralVideoModel[]
|
||||
}
|
||||
|
||||
/** v1.6 阶段3请求:用户确认/编辑口播文案后开始单次 Seedance 出片(POST /viral-video/{id}/confirm-copy) */
|
||||
export interface ConfirmCopyRequest {
|
||||
/** 用户编辑后的口播文案;为空则使用 AI 生成的 voiceover_script */
|
||||
edited_copy?: string
|
||||
/** 视频模型 key,覆盖默认 */
|
||||
video_model?: string
|
||||
}
|
||||
|
||||
/** 旧分镜片段结构(保留兼容;新代码请使用 ShotScript) */
|
||||
export interface StoryboardSegment {
|
||||
order: number
|
||||
type: string
|
||||
description: string
|
||||
text: string
|
||||
duration: number
|
||||
ken_burns?: string
|
||||
transition?: string
|
||||
}
|
||||
@@ -2,6 +2,7 @@
|
||||
export const ROUTE_TITLE_MAP: Record<string, string> = {
|
||||
"/app/dashboard": "首页",
|
||||
"/app/generate": "智能剪辑",
|
||||
"/app/viral-video": "爆款视频",
|
||||
"/app/assets": "视频库",
|
||||
"/app/voices": "配音库",
|
||||
"/app/products": "成片库",
|
||||
|
||||
@@ -18,6 +18,7 @@ import {
|
||||
ThunderboltOutlined,
|
||||
UnorderedListOutlined,
|
||||
UserOutlined,
|
||||
FireOutlined,
|
||||
} from "@ant-design/icons"
|
||||
|
||||
/** 导航项类型 */
|
||||
@@ -76,6 +77,12 @@ export const NAV_ITEMS: NavItem[] = [
|
||||
path: "/app/ai-avatar",
|
||||
icon: React.createElement(UserOutlined),
|
||||
},
|
||||
{
|
||||
key: "viral-video",
|
||||
label: "爆款视频",
|
||||
path: "/app/viral-video",
|
||||
icon: React.createElement(FireOutlined),
|
||||
},
|
||||
{
|
||||
key: "history",
|
||||
label: "任务历史",
|
||||
@@ -142,6 +149,12 @@ export const NAV_GROUPS: NavGroup[] = [
|
||||
path: "/app/ai-avatar",
|
||||
icon: React.createElement(UserOutlined),
|
||||
},
|
||||
{
|
||||
key: "viral-video",
|
||||
label: "爆款视频",
|
||||
path: "/app/viral-video",
|
||||
icon: React.createElement(FireOutlined),
|
||||
},
|
||||
],
|
||||
},
|
||||
{
|
||||
|
||||
@@ -80,6 +80,8 @@ const AiAvatarPage: React.FC = () => {
|
||||
const [finalizeLoading, setFinalizeLoading] = useState(false)
|
||||
|
||||
/* ── 对口型轮询 ── */
|
||||
/** 对口型轮询总时长上限(10分钟):超过后停止轮询并提示去历史记录查看 */
|
||||
const LIPSYNC_POLL_MAX_MS = 10 * 60 * 1000
|
||||
const lipsyncTimerRef = useRef<ReturnType<typeof setInterval> | null>(null)
|
||||
/* ── 渲染进度轮询 ── */
|
||||
const renderTimerRef = useRef<ReturnType<typeof setInterval> | null>(null)
|
||||
@@ -270,7 +272,24 @@ const AiAvatarPage: React.FC = () => {
|
||||
// 如果是预合成模式,后端会同步把状态置为 submitted(甚至可能已返回 running),
|
||||
// 但仍需轮询等 completed
|
||||
if (lipsyncTimerRef.current) clearInterval(lipsyncTimerRef.current)
|
||||
// 轮询间隔 5 秒;单请求超时 5 分钟(见 api/aiAvatar.ts);总轮询上限 10 分钟
|
||||
// 单次请求失败/超时不中断轮询,继续下一轮;超过总上限后停止并提示用户去历史记录查看
|
||||
lipsyncTimerRef.current = setInterval(async () => {
|
||||
// 总时长保护:超过 10 分钟停止轮询
|
||||
if (Date.now() - lipsyncStartAtRef.current > LIPSYNC_POLL_MAX_MS) {
|
||||
if (lipsyncTimerRef.current) {
|
||||
clearInterval(lipsyncTimerRef.current)
|
||||
lipsyncTimerRef.current = null
|
||||
}
|
||||
if (lipsyncTickRef.current) {
|
||||
clearInterval(lipsyncTickRef.current)
|
||||
lipsyncTickRef.current = null
|
||||
}
|
||||
setLipsyncStatus("failed")
|
||||
setLipsyncErrorMessage("渲染时间较长,请稍后在历史记录中查看")
|
||||
message.warning("对口型渲染时间较长,已停止自动刷新,请稍后在历史记录中查看")
|
||||
return
|
||||
}
|
||||
try {
|
||||
const updated = await getLipsyncJob(job.id)
|
||||
state.setLipsyncJob(updated)
|
||||
@@ -296,9 +315,10 @@ const AiAvatarPage: React.FC = () => {
|
||||
setLipsyncErrorMessage(updated.error_message || "对口型生成失败")
|
||||
}
|
||||
} catch (err) {
|
||||
console.error("[对口型] 轮询错误:", err)
|
||||
// 单次轮询失败(含 timeout):不中断轮询,打印日志后等下一轮
|
||||
console.warn("[对口型] 轮询请求失败,将继续下一轮:", err)
|
||||
}
|
||||
}, 3000)
|
||||
}, 5000)
|
||||
} catch (err) {
|
||||
console.error("[对口型] 创建失败:", {
|
||||
status: (err as { response?: { status?: number } })?.response?.status,
|
||||
@@ -580,20 +600,6 @@ const AiAvatarPage: React.FC = () => {
|
||||
|
||||
return (
|
||||
<div className="aa-page">
|
||||
<div className="aa-page-header">
|
||||
<h1>AI数字人</h1>
|
||||
</div>
|
||||
|
||||
{/* 步骤切换导航条 */}
|
||||
<div className="aa-step-nav">
|
||||
<span className={`aa-step-nav__item${currentStep === 1 ? " active" : ""}`}>
|
||||
1. 视频 / 配音 / 文案
|
||||
</span>
|
||||
<span className={`aa-step-nav__item${currentStep === 2 ? " active" : ""}`}>
|
||||
2. 对口型 / 标题 / 封面 / 生成
|
||||
</span>
|
||||
</div>
|
||||
|
||||
<div className="aa-page-body">
|
||||
{/* ════ 步骤 1:出镜视频 / 配音库 / 文案 ════ */}
|
||||
{currentStep === 1 && (
|
||||
|
||||
@@ -72,7 +72,8 @@ export const previewTts = async (data: {
|
||||
}
|
||||
|
||||
export const getLipsyncJob = async (id: string): Promise<LipsyncJob> => {
|
||||
const response = await apiClient.get<LipsyncJob>(`/lipsync/jobs/${id}`, { timeout: 60000 })
|
||||
// MuseTalk 渲染 8s 视频约 54s + 排队时间,给足 5 分钟超时避免单次轮询 AxiosError 中断
|
||||
const response = await apiClient.get<LipsyncJob>(`/lipsync/jobs/${id}`, { timeout: 300_000 })
|
||||
return response.data
|
||||
}
|
||||
|
||||
@@ -91,7 +92,10 @@ export const submitRender = async (data: {
|
||||
}
|
||||
|
||||
export const getRenderJob = async (jobId: string): Promise<RenderJob> => {
|
||||
const response = await apiClient.get<RenderJob>(`/ai-avatar/render/${jobId}`, { timeout: 60000 })
|
||||
// 渲染链路(对口型+B-roll+标题+合成+上传)耗时较长,给足 5 分钟超时
|
||||
const response = await apiClient.get<RenderJob>(`/ai-avatar/render/${jobId}`, {
|
||||
timeout: 300_000,
|
||||
})
|
||||
return response.data
|
||||
}
|
||||
|
||||
|
||||
@@ -13,8 +13,6 @@ import CloneModal from "@/components/voice/CloneModal"
|
||||
import VoiceSelectModal from "./components/VoiceSelectModal"
|
||||
import ScriptSelectModal from "./components/ScriptSelectModal"
|
||||
import TtsVoiceModal from "./components/TtsVoiceModal"
|
||||
import GenerateHeader from "./components/GenerateHeader"
|
||||
import GenerateStepsBar from "./components/GenerateStepsBar"
|
||||
import GenerateStepContent from "./components/GenerateStepContent"
|
||||
import GenerateStepActions from "./components/GenerateStepActions"
|
||||
import { useGenerateFormState } from "./hooks/useGenerateFormState"
|
||||
@@ -88,7 +86,6 @@ const GeneratePage: React.FC = () => {
|
||||
style,
|
||||
autoSubtitles,
|
||||
bgm,
|
||||
editPlanId,
|
||||
sourceEditPlanId,
|
||||
previewTaskId,
|
||||
setPreviewTaskId,
|
||||
@@ -523,10 +520,6 @@ const GeneratePage: React.FC = () => {
|
||||
|
||||
return (
|
||||
<div className="xx-generate-page">
|
||||
<GenerateHeader fromEditPlan={!!editPlanId} />
|
||||
|
||||
<GenerateStepsBar currentStep={currentStep} onStepClick={setCurrentStep} />
|
||||
|
||||
<div className={layoutClassName}>
|
||||
{/* ════ 步骤1~2 表单 / 步骤3 标题设置 / 步骤4 确认生成进度 / 步骤5 封面 ════ */}
|
||||
<div className="xx-generate-form">
|
||||
|
||||
@@ -11,7 +11,12 @@
|
||||
* 防止长标题在窄列里溢出导致与相邻卡片进度条视觉重叠。
|
||||
*/
|
||||
import React from "react"
|
||||
import { LoadingOutlined, CheckCircleFilled, CloseCircleOutlined } from "@ant-design/icons"
|
||||
import {
|
||||
LoadingOutlined,
|
||||
CheckCircleFilled,
|
||||
CloseCircleOutlined,
|
||||
ClockCircleOutlined,
|
||||
} from "@ant-design/icons"
|
||||
import type { BatchTaskState } from "../hooks/generate-video/useGenerationPolling"
|
||||
import type { GeneratedVideo } from "@/api/template-editor"
|
||||
|
||||
@@ -61,6 +66,11 @@ const BatchGenerationGrid: React.FC<BatchGenerationGridProps> = ({
|
||||
className="xx-batch-gen-card-icon"
|
||||
style={{ color: "#ef4444" }}
|
||||
/>
|
||||
) : task.status === "queued" ? (
|
||||
<ClockCircleOutlined
|
||||
className="xx-batch-gen-card-icon"
|
||||
style={{ color: "#faad14" }}
|
||||
/>
|
||||
) : (
|
||||
<LoadingOutlined
|
||||
className="xx-batch-gen-card-icon"
|
||||
@@ -85,6 +95,21 @@ const BatchGenerationGrid: React.FC<BatchGenerationGridProps> = ({
|
||||
<div className="xx-batch-gen-card-pct">{Math.round(task.progress)}%</div>
|
||||
</>
|
||||
)}
|
||||
{task.status === "queued" && (
|
||||
<div
|
||||
style={{
|
||||
display: "flex",
|
||||
alignItems: "center",
|
||||
gap: 8,
|
||||
color: "var(--text-secondary, #faad14)",
|
||||
fontSize: 13,
|
||||
padding: "8px 0",
|
||||
}}
|
||||
>
|
||||
<ClockCircleOutlined />
|
||||
<span>排队等待中,前面任务完成后自动开始渲染</span>
|
||||
</div>
|
||||
)}
|
||||
{(task.status === "completed" || task.status === "awaiting_cover") && video && (
|
||||
// 竖屏自适应容器(#1750):成片固定 1080×1920(9:16),
|
||||
// 视频按真实宽高比 contain 显示,黑底居中,杜绝横屏播放器左右大黑边
|
||||
|
||||
@@ -12,6 +12,7 @@ import Step2MaterialSelect from "../components/Step2MaterialSelect"
|
||||
import Step4TitleSettings from "../components/Step4TitleSettings"
|
||||
import Step6CoverSettings from "../components/Step6CoverSettings"
|
||||
import BatchGenerationGrid from "./BatchGenerationGrid"
|
||||
import Step3VoiceWithMode from "./Step3VoiceWithMode"
|
||||
import type { BatchTaskState } from "../hooks/generate-video/useGenerationPolling"
|
||||
import type { GeneratedVideo } from "@/api/template-editor"
|
||||
import type { TitleTemplate } from "@/components/title/template-types"
|
||||
@@ -151,6 +152,12 @@ export const GenerateStepContent: React.FC<GenerateStepContentProps> = (props) =
|
||||
selectedCoverTemplate,
|
||||
onSelectedCoverTemplateChange,
|
||||
onConfirmGenerate,
|
||||
selectedVoice,
|
||||
onSelectedVoiceChange,
|
||||
voiceModePerVideo,
|
||||
onVoiceModePerVideoChange,
|
||||
voiceLibraryIds,
|
||||
onVoiceLibraryIdsChange,
|
||||
} = props
|
||||
|
||||
switch (currentStep) {
|
||||
@@ -184,32 +191,46 @@ export const GenerateStepContent: React.FC<GenerateStepContentProps> = (props) =
|
||||
)
|
||||
case 3:
|
||||
return (
|
||||
<Step4TitleSettings
|
||||
titleSettings={titleSettings}
|
||||
onTitleSettingsChange={onTitleSettingsChange}
|
||||
onUpdatePosition={onUpdatePosition}
|
||||
onUpdateFont={onUpdateFont}
|
||||
onUpdateSize={onUpdateSize}
|
||||
onToggleBold={onToggleBold}
|
||||
onToggleItalic={onToggleItalic}
|
||||
onToggleStroke={onToggleStroke}
|
||||
onToggleShadow={onToggleShadow}
|
||||
onApplyPreset={onApplyPreset}
|
||||
onUpdateStyle={onUpdateStyle}
|
||||
activePreset={activePreset}
|
||||
titlePresets={titlePresets}
|
||||
enableTemplates={enableTemplates}
|
||||
selectedTemplateId={selectedTemplateId}
|
||||
onApplyTemplate={onApplyTemplate}
|
||||
previewCount={previewCount}
|
||||
previewTitles={previewTitles}
|
||||
onPreviewTitlesChange={onPreviewTitlesChange}
|
||||
onConfirmGenerate={onConfirmGenerate}
|
||||
generating={props.generating}
|
||||
selectedCount={
|
||||
props.previewCount && props.previewCount > 1 ? props.selectedVariantIds?.length || 1 : 1
|
||||
}
|
||||
/>
|
||||
<>
|
||||
<Step4TitleSettings
|
||||
titleSettings={titleSettings}
|
||||
onTitleSettingsChange={onTitleSettingsChange}
|
||||
onUpdatePosition={onUpdatePosition}
|
||||
onUpdateFont={onUpdateFont}
|
||||
onUpdateSize={onUpdateSize}
|
||||
onToggleBold={onToggleBold}
|
||||
onToggleItalic={onToggleItalic}
|
||||
onToggleStroke={onToggleStroke}
|
||||
onToggleShadow={onToggleShadow}
|
||||
onApplyPreset={onApplyPreset}
|
||||
onUpdateStyle={onUpdateStyle}
|
||||
activePreset={activePreset}
|
||||
titlePresets={titlePresets}
|
||||
enableTemplates={enableTemplates}
|
||||
selectedTemplateId={selectedTemplateId}
|
||||
onApplyTemplate={onApplyTemplate}
|
||||
previewCount={previewCount}
|
||||
previewTitles={previewTitles}
|
||||
onPreviewTitlesChange={onPreviewTitlesChange}
|
||||
onConfirmGenerate={onConfirmGenerate}
|
||||
generating={props.generating}
|
||||
selectedCount={
|
||||
props.previewCount && props.previewCount > 1
|
||||
? props.selectedVariantIds?.length || 1
|
||||
: 1
|
||||
}
|
||||
/>
|
||||
{/* 批量配音选择:共用/独立切换(#2096) */}
|
||||
<Step3VoiceWithMode
|
||||
previewCount={previewCount}
|
||||
selectedVoice={selectedVoice}
|
||||
onSelectedVoiceChange={onSelectedVoiceChange}
|
||||
voiceModePerVideo={voiceModePerVideo}
|
||||
onVoiceModePerVideoChange={onVoiceModePerVideoChange}
|
||||
voiceLibraryIds={voiceLibraryIds}
|
||||
onVoiceLibraryIdsChange={onVoiceLibraryIdsChange}
|
||||
/>
|
||||
</>
|
||||
)
|
||||
case 4:
|
||||
return (
|
||||
|
||||
@@ -157,7 +157,7 @@ const Step4TitleSettings: React.FC<Step4TitleSettingsProps> = (props) => {
|
||||
/>
|
||||
</div>
|
||||
) : (
|
||||
/* ── 批量:N 个独立标题输入框 ── */
|
||||
/* ── 批量:N 个独立标题输入框(两列布局 #2096) ── */
|
||||
<div className="xx-batch-titles">
|
||||
<div
|
||||
style={{
|
||||
@@ -170,17 +170,25 @@ const Step4TitleSettings: React.FC<Step4TitleSettingsProps> = (props) => {
|
||||
为每个视频输入独立标题。标题样式(字体/颜色/位置)全局统一。
|
||||
</div>
|
||||
|
||||
{Array.from({ length: previewCount }, (_, i) => (
|
||||
<div className="xx-form-field" key={i} style={{ maxWidth: 640 }}>
|
||||
<label>视频 {i + 1} 标题</label>
|
||||
<TitleLibraryAutoComplete
|
||||
placeholder={`输入或选择视频 ${i + 1} 的标题`}
|
||||
value={previewTitles?.[i] || ""}
|
||||
onChange={(val) => updateVariantTitle(i, val)}
|
||||
options={titleOptions}
|
||||
/>
|
||||
</div>
|
||||
))}
|
||||
<div
|
||||
style={{
|
||||
display: "grid",
|
||||
gridTemplateColumns: "repeat(2, minmax(0, 1fr))",
|
||||
gap: 16,
|
||||
}}
|
||||
>
|
||||
{Array.from({ length: previewCount }, (_, i) => (
|
||||
<div className="xx-form-field" key={i} style={{ maxWidth: "100%" }}>
|
||||
<label>视频 {i + 1} 标题</label>
|
||||
<TitleLibraryAutoComplete
|
||||
placeholder={`输入或选择视频 ${i + 1} 的标题`}
|
||||
value={previewTitles?.[i] || ""}
|
||||
onChange={(val) => updateVariantTitle(i, val)}
|
||||
options={titleOptions}
|
||||
/>
|
||||
</div>
|
||||
))}
|
||||
</div>
|
||||
</div>
|
||||
)}
|
||||
|
||||
|
||||
@@ -17,7 +17,7 @@ import CoverSettingsModal from "./cover-settings/CoverSettingsModal"
|
||||
import CoverEditorModal from "./cover-settings/CoverEditorModal"
|
||||
import { useSharedCover } from "@/components/cover/useSharedCover"
|
||||
import { generateCover as apiGenerateCover } from "@/api/generation"
|
||||
import { uploadAssetDirect, getAssetLibraries } from "@/api/assets"
|
||||
import { uploadAssetDirect } from "@/api/assets"
|
||||
|
||||
interface Step6CoverSettingsProps {
|
||||
coverSettings: CoverConfig
|
||||
@@ -176,15 +176,8 @@ const Step6CoverSettings: React.FC<Step6CoverSettingsProps> = (props) => {
|
||||
thumbnail_url: previewUrl,
|
||||
mode: "upload",
|
||||
})
|
||||
// 查找图片素材库(复用批量封面的逻辑)
|
||||
const libs = await getAssetLibraries()
|
||||
const imageLib = libs.find((l) => l.kind === "image") || libs[0]
|
||||
if (!imageLib) {
|
||||
hide()
|
||||
message.error("未找到素材库,请先创建图片素材库")
|
||||
return previewUrl
|
||||
}
|
||||
const result = await uploadAssetDirect({ file, library_id: imageLib.id })
|
||||
// 后端自动在默认项目下确保图片素材库存在(P0 404 修复)
|
||||
const result = await uploadAssetDirect({ file, kind: "image" })
|
||||
const realUrl = result?.url || ""
|
||||
if (!realUrl) {
|
||||
hide()
|
||||
|
||||
@@ -10,7 +10,7 @@ export interface BatchTaskState {
|
||||
taskId: string
|
||||
/** 变体序号(0-based,与标题/封面数组对齐) */
|
||||
variantIndex: number
|
||||
status: "running" | "completed" | "awaiting_cover" | "failed"
|
||||
status: "running" | "completed" | "awaiting_cover" | "failed" | "queued"
|
||||
progress: number
|
||||
error: string | null
|
||||
/** 完成后的成片视频 */
|
||||
@@ -374,5 +374,42 @@ export function useGenerationPolling({
|
||||
}
|
||||
}, [])
|
||||
|
||||
return { startPolling, startPollingBatch, retryTask, clearTimer }
|
||||
/**
|
||||
* 批量队列模式:逐任务追加到轮询队列(支持串行提交、429 排队重试场景)。
|
||||
* 与 startPollingBatch 不同的是:
|
||||
* - 不会 reset batchContextRef;多次调用会累积
|
||||
* - 不触发整体 onComplete / onFailed(完成判定交给外层 useEffect 按状态聚合)
|
||||
* - 仍通过 onBatchTaskUpdate 回传单任务状态
|
||||
*/
|
||||
const pollBatchTaskQueued = useCallback(
|
||||
(taskId: string, variantIndex: number) => {
|
||||
cancelledRef.current = false
|
||||
batchContextRef.current.set(taskId, variantIndex)
|
||||
onBatchTaskUpdate?.(taskId, {
|
||||
taskId,
|
||||
variantIndex,
|
||||
status: "running",
|
||||
progress: 0,
|
||||
error: null,
|
||||
videos: [],
|
||||
})
|
||||
pollSingleTask(taskId, Date.now(), {
|
||||
onTaskProgress: (pct) => {
|
||||
onBatchTaskUpdate?.(taskId, { status: "running", progress: pct })
|
||||
},
|
||||
onTaskCompleted: (videos, taskStatus) => {
|
||||
const finalStatus: "completed" | "awaiting_cover" = taskStatus ?? "completed"
|
||||
onBatchTaskUpdate?.(taskId, { status: finalStatus, progress: 100, videos })
|
||||
},
|
||||
onTaskFailed: (msg) => {
|
||||
onBatchTaskUpdate?.(taskId, { status: "failed", error: msg })
|
||||
},
|
||||
}).catch(() => {
|
||||
/* onTaskFailed 已处理 */
|
||||
})
|
||||
},
|
||||
[pollSingleTask, onBatchTaskUpdate],
|
||||
)
|
||||
|
||||
return { startPolling, startPollingBatch, pollBatchTaskQueued, retryTask, clearTimer }
|
||||
}
|
||||
|
||||
@@ -12,7 +12,7 @@
|
||||
import { useCallback, useState } from "react"
|
||||
import { message } from "antd"
|
||||
import { generateCover } from "@/api/generation"
|
||||
import { uploadAssetDirect, getAssetLibraries } from "@/api/assets"
|
||||
import { uploadAssetDirect } from "@/api/assets"
|
||||
import type { GeneratedVideo } from "@/api/template-editor"
|
||||
|
||||
/** onCoversChange 支持直接传值或函数式 updater(函数式用于串行回写避免闭包覆盖) */
|
||||
@@ -182,15 +182,9 @@ export function useBatchCovers({
|
||||
async (index: number, file: File) => {
|
||||
addUploading(index)
|
||||
try {
|
||||
const libs = await getAssetLibraries()
|
||||
const imageLib = libs.find((l) => l.kind === "image") || libs[0]
|
||||
if (!imageLib) {
|
||||
message.error("未找到素材库,请先创建")
|
||||
return
|
||||
}
|
||||
const result = await uploadAssetDirect({
|
||||
file,
|
||||
library_id: imageLib.id,
|
||||
kind: "image",
|
||||
})
|
||||
const url = result?.url || ""
|
||||
if (url) {
|
||||
|
||||
@@ -2,10 +2,12 @@
|
||||
* 视频生成 Hook
|
||||
* 封装视频生成的核心逻辑、状态管理、轮询等
|
||||
*/
|
||||
import { useState, useCallback, useEffect } from "react"
|
||||
import { useState, useCallback, useEffect, useRef } from "react"
|
||||
import { message } from "antd"
|
||||
import axios from "axios"
|
||||
import { type GeneratedVideo, getEditPlanClips, createClipsFromAssets } from "@/api/template-editor"
|
||||
import { createGenerationTask } from "@/api/tasks/tasks"
|
||||
import type { CreateGenerationTaskRequest } from "@/api/tasks/types"
|
||||
import type { UseGenerateVideoProps } from "./generate-video/types"
|
||||
import { getGenerationPhase } from "./generate-video/phase"
|
||||
import { useGenerationPolling, type BatchTaskState } from "./generate-video/useGenerationPolling"
|
||||
@@ -15,6 +17,26 @@ import { extractBackendError, translateError } from "./generate-video/errorUtils
|
||||
|
||||
export type GenerationCompleteStatus = "completed" | "awaiting_cover" | null
|
||||
|
||||
/** 判断是否是用户队列已满 429(需要排队重试而非直接报错) */
|
||||
function isUserQueueFullError(err: unknown): { waitMs: number } | null {
|
||||
if (!axios.isAxiosError(err)) return null
|
||||
if (err.response?.status !== 429 && err.response?.status !== 503) return null
|
||||
const detail = (err.response?.data as { detail?: unknown })?.detail
|
||||
const code =
|
||||
typeof detail === "object" && detail !== null ? (detail as { code?: string }).code : undefined
|
||||
if (code === "USER_QUEUE_FULL" || code === "SYSTEM_QUEUE_FULL") {
|
||||
const waitSec =
|
||||
typeof detail === "object" && detail !== null
|
||||
? Number((detail as { estimated_wait_seconds?: number }).estimated_wait_seconds) || 0
|
||||
: 0
|
||||
return { waitMs: Math.max(15_000, waitSec * 1000 || 30_000) }
|
||||
}
|
||||
return null
|
||||
}
|
||||
|
||||
/** sleep */
|
||||
const sleep = (ms: number) => new Promise<void>((r) => setTimeout(r, ms))
|
||||
|
||||
export function useGenerateVideo(props: UseGenerateVideoProps) {
|
||||
const { selectedTemplate, onGenerationSuccess } = props
|
||||
|
||||
@@ -31,6 +53,22 @@ export function useGenerateVideo(props: UseGenerateVideoProps) {
|
||||
/** 批量模式:每个正式生成任务的独立状态(第5步逐卡片展示) */
|
||||
const [batchTasks, setBatchTasks] = useState<BatchTaskState[]>([])
|
||||
|
||||
/** 排队中重试的定时器,unmount / 新提交时清理 */
|
||||
const queueTimersRef = useRef<number[]>([])
|
||||
const cancelledRef = useRef(false)
|
||||
|
||||
const clearQueueTimers = useCallback(() => {
|
||||
queueTimersRef.current.forEach((id) => clearTimeout(id))
|
||||
queueTimersRef.current = []
|
||||
}, [])
|
||||
|
||||
useEffect(() => {
|
||||
return () => {
|
||||
cancelledRef.current = true
|
||||
clearQueueTimers()
|
||||
}
|
||||
}, [clearQueueTimers])
|
||||
|
||||
const handleBatchTaskUpdate = useCallback((taskId: string, patch: Partial<BatchTaskState>) => {
|
||||
setBatchTasks((prev) => {
|
||||
const list = prev || []
|
||||
@@ -58,7 +96,6 @@ export function useGenerateVideo(props: UseGenerateVideoProps) {
|
||||
const handleProgress = useCallback((p: number) => setProgress(p), [])
|
||||
const handleComplete = useCallback(
|
||||
(videos: unknown[], taskStatus?: "completed" | "awaiting_cover") => {
|
||||
setGenerating(false)
|
||||
setGenerated(true)
|
||||
const finalStatus: GenerationCompleteStatus = taskStatus ?? "completed"
|
||||
setCompletionStatus(finalStatus)
|
||||
@@ -81,21 +118,30 @@ export function useGenerateVideo(props: UseGenerateVideoProps) {
|
||||
[onGenerationSuccess],
|
||||
)
|
||||
const handleFailed = useCallback((errorMsg: string) => {
|
||||
setGenerating(false)
|
||||
setGenerateError(errorMsg)
|
||||
}, [])
|
||||
|
||||
/* 批量:任务状态变化时聚合已完成成片(含失败重试成功后补入),
|
||||
按变体索引排序,供步骤6封面按勾选顺序逐个取视频 */
|
||||
按变体索引排序,供步骤6封面按勾选顺序逐个取视频。
|
||||
当全部任务都已结束(completed/awaiting_cover/failed)且无排队/渲染中任务时,关闭 generating。 */
|
||||
useEffect(() => {
|
||||
if (batchTasks.length === 0) return
|
||||
const byVariant = new Map<number, GeneratedVideo>()
|
||||
let hasQueued = false
|
||||
let hasRunning = false
|
||||
let hasSuccess = false
|
||||
let allDone = true
|
||||
batchTasks.forEach((t) => {
|
||||
if (
|
||||
t.status === "completed" ||
|
||||
(t.status === "awaiting_cover" && t.videos && t.videos.length > 0)
|
||||
) {
|
||||
byVariant.set(t.variantIndex, t.videos[0] as GeneratedVideo)
|
||||
if (t.status === "queued") hasQueued = true
|
||||
else if (t.status === "running") hasRunning = true
|
||||
if (t.status === "completed" || t.status === "awaiting_cover") {
|
||||
hasSuccess = true
|
||||
if (t.videos && t.videos.length > 0) {
|
||||
byVariant.set(t.variantIndex, t.videos[0] as GeneratedVideo)
|
||||
}
|
||||
}
|
||||
if (t.status !== "completed" && t.status !== "awaiting_cover" && t.status !== "failed") {
|
||||
allDone = false
|
||||
}
|
||||
})
|
||||
const ordered = [...byVariant.entries()].sort((a, b) => a[0] - b[0]).map(([, v]) => v)
|
||||
@@ -105,17 +151,185 @@ export function useGenerateVideo(props: UseGenerateVideoProps) {
|
||||
}
|
||||
return ordered
|
||||
})
|
||||
if (allDone && !hasQueued && !hasRunning) {
|
||||
setGenerating(false)
|
||||
if (hasSuccess) {
|
||||
setGenerated(true)
|
||||
setCompletionStatus("awaiting_cover")
|
||||
}
|
||||
}
|
||||
}, [batchTasks])
|
||||
|
||||
const { startPolling, startPollingBatch, retryTask, clearTimer } = useGenerationPolling({
|
||||
const { startPolling, pollBatchTaskQueued, retryTask, clearTimer } = useGenerationPolling({
|
||||
onProgress: handleProgress,
|
||||
onComplete: handleComplete,
|
||||
onFailed: handleFailed,
|
||||
onBatchTaskUpdate: handleBatchTaskUpdate,
|
||||
})
|
||||
|
||||
/** 根据 props 构造基础 payload(批量/单任务共用的字段) */
|
||||
const buildBasePayload = useCallback((): Omit<
|
||||
CreateGenerationTaskRequest,
|
||||
"count" | "titles" | "voice_library_ids" | "cover_urls" | "variant_plan_ids"
|
||||
> => {
|
||||
const { width: outputWidth, height: outputHeight } = calculateResolution(
|
||||
props.videoRatio || "9:16",
|
||||
)
|
||||
const editMode = props.editMode ?? "random"
|
||||
const dedupEnabled = props.dedupEnabled !== false
|
||||
const assetIds =
|
||||
props.materialMode === "auto" ? props.smartSelectedIds : props.selectedMaterials
|
||||
const coverUrl = props.coverSettings?.thumbnail_url || props.coverSettings?.upload_url || ""
|
||||
// #1970:叙事模式下 ttsVoiceId 作为配音 id;随机模式用 selectedVoice
|
||||
const voiceLibraryId =
|
||||
editMode === "narrative"
|
||||
? props.ttsVoiceId || ""
|
||||
: props.voiceMode === "clone"
|
||||
? props.selectedClonedVoice || props.selectedVoice || ""
|
||||
: props.selectedVoice || ""
|
||||
|
||||
const bgmConfig = {
|
||||
enabled: props.bgm !== false,
|
||||
...(props.bgmConfig?.music_id ? { preset_id: props.bgmConfig.music_id } : {}),
|
||||
}
|
||||
|
||||
const titleConfig = props.titleSettings?.title
|
||||
? {
|
||||
text: props.titleSettings.title,
|
||||
font: props.titleSettings.font,
|
||||
font_size: props.titleSettings.size,
|
||||
font_color: props.titleSettings.color,
|
||||
position: props.titleSettings.position,
|
||||
...(props.titleSettings.position === "custom" &&
|
||||
props.titleSettings.posX != null &&
|
||||
props.titleSettings.posY != null
|
||||
? {
|
||||
pos_x: Math.round(props.titleSettings.posX),
|
||||
pos_y: Math.round(props.titleSettings.posY),
|
||||
}
|
||||
: {}),
|
||||
bold: props.titleSettings.bold,
|
||||
italic: props.titleSettings.italic,
|
||||
stroke: props.titleSettings.stroke
|
||||
? {
|
||||
enabled: true,
|
||||
width: props.titleSettings.strokeWidth ?? 4,
|
||||
color: props.titleSettings.strokeColor ?? "#000000",
|
||||
}
|
||||
: { enabled: false },
|
||||
shadow: props.titleSettings.shadow
|
||||
? {
|
||||
enabled: true,
|
||||
offset_x: props.titleSettings.shadowOffsetX ?? 2,
|
||||
offset_y: props.titleSettings.shadowOffsetY ?? 2,
|
||||
blur: props.titleSettings.shadowBlur ?? 4,
|
||||
color: props.titleSettings.shadowColor ?? "rgba(0,0,0,0.8)",
|
||||
}
|
||||
: { enabled: false },
|
||||
line_height: props.titleSettings.lineHeight ?? 1.2,
|
||||
margin_top: props.titleSettings.marginTop ?? 24,
|
||||
max_chars_per_line: props.titleSettings.maxCharsPerLine ?? 0,
|
||||
...(props.titleSettings.bgEnabled
|
||||
? {
|
||||
background: {
|
||||
enabled: true,
|
||||
color: props.titleSettings.bgColor,
|
||||
padding: props.titleSettings.bgPadding,
|
||||
radius: props.titleSettings.bgRadius,
|
||||
},
|
||||
}
|
||||
: { background: { enabled: false } }),
|
||||
line_overrides: (props.titleSettings.lineOverrides ?? []).map((lo) => ({
|
||||
line_index: lo.line_index,
|
||||
text: lo.text,
|
||||
size: lo.size,
|
||||
color: lo.color,
|
||||
bold: lo.bold,
|
||||
italic: lo.italic,
|
||||
stroke: lo.stroke,
|
||||
highlights: lo.highlights?.map((h) => ({
|
||||
word: h.word,
|
||||
color: h.color,
|
||||
bold: h.bold,
|
||||
scale: h.scale,
|
||||
})),
|
||||
})),
|
||||
...(props.titleSettings.coverTitle
|
||||
? {
|
||||
cover_title_config: {
|
||||
title: props.titleSettings.coverTitle.title,
|
||||
font: props.titleSettings.coverTitle.font,
|
||||
font_size: props.titleSettings.coverTitle.size,
|
||||
font_color: props.titleSettings.coverTitle.color,
|
||||
bold: props.titleSettings.coverTitle.bold,
|
||||
italic: props.titleSettings.coverTitle.italic,
|
||||
position: props.titleSettings.coverTitle.position,
|
||||
stroke: props.titleSettings.coverTitle.stroke
|
||||
? {
|
||||
enabled: true,
|
||||
width: props.titleSettings.coverTitle.strokeWidth ?? 4,
|
||||
color: props.titleSettings.coverTitle.strokeColor ?? "#000000",
|
||||
}
|
||||
: { enabled: false },
|
||||
shadow: props.titleSettings.coverTitle.shadow
|
||||
? {
|
||||
enabled: true,
|
||||
offset_x: props.titleSettings.coverTitle.shadowOffsetX ?? 2,
|
||||
offset_y: props.titleSettings.coverTitle.shadowOffsetY ?? 2,
|
||||
blur: props.titleSettings.coverTitle.shadowBlur ?? 4,
|
||||
color: props.titleSettings.coverTitle.shadowColor ?? "rgba(0,0,0,0.8)",
|
||||
}
|
||||
: { enabled: false },
|
||||
...(props.titleSettings.coverTitle.bgEnabled
|
||||
? {
|
||||
background: {
|
||||
enabled: true,
|
||||
color: props.titleSettings.coverTitle.bgColor,
|
||||
padding: props.titleSettings.coverTitle.bgPadding,
|
||||
radius: props.titleSettings.coverTitle.bgRadius,
|
||||
},
|
||||
}
|
||||
: { background: { enabled: false } }),
|
||||
},
|
||||
}
|
||||
: {}),
|
||||
}
|
||||
: undefined
|
||||
|
||||
const payload: Omit<
|
||||
CreateGenerationTaskRequest,
|
||||
"count" | "titles" | "voice_library_ids" | "cover_urls" | "variant_plan_ids"
|
||||
> = {
|
||||
template_id: selectedTemplate,
|
||||
asset_ids: assetIds,
|
||||
output_width: outputWidth,
|
||||
output_height: outputHeight,
|
||||
cover_url: coverUrl,
|
||||
custom_title: props.titleSettings?.title || "",
|
||||
duration: props.duration || undefined,
|
||||
video_ratio: props.videoRatio,
|
||||
assembly_mode: editMode,
|
||||
...(editMode === "narrative" && props.selectedScript?.id
|
||||
? {
|
||||
script_id: props.selectedScript.id,
|
||||
tts_voice_id: props.ttsVoiceId || undefined,
|
||||
tts_voice_source: props.ttsVoiceSource || undefined,
|
||||
tts_style: props.ttsStyle || undefined,
|
||||
}
|
||||
: {}),
|
||||
dedup_enabled: dedupEnabled,
|
||||
voice_library_id: voiceLibraryId,
|
||||
...(props.selectedVoice && !voiceLibraryId ? { voice_ids: [props.selectedVoice] } : {}),
|
||||
bgm_config: bgmConfig as CreateGenerationTaskRequest["bgm_config"],
|
||||
...(props.sourceEditPlanId ? { source_edit_plan_id: props.sourceEditPlanId } : {}),
|
||||
...(titleConfig ? ({ title_config: titleConfig } as Record<string, unknown>) : {}),
|
||||
}
|
||||
|
||||
return payload
|
||||
}, [props, selectedTemplate])
|
||||
|
||||
/* ── 生成视频 ──
|
||||
返回 true 表示任务创建成功并已开始轮询;false 表示校验未通过或创建失败 */
|
||||
返回 true 表示任务创建成功并已开始轮询(含排队中);false 表示校验未通过或创建失败 */
|
||||
const generate = useCallback(async (): Promise<boolean> => {
|
||||
const errorMsg = validateGenerateInputs(props)
|
||||
if (errorMsg) {
|
||||
@@ -123,6 +337,8 @@ export function useGenerateVideo(props: UseGenerateVideoProps) {
|
||||
return false
|
||||
}
|
||||
|
||||
cancelledRef.current = false
|
||||
clearQueueTimers()
|
||||
setGenerating(true)
|
||||
setProgress(0)
|
||||
setGenerated(false)
|
||||
@@ -133,25 +349,16 @@ export function useGenerateVideo(props: UseGenerateVideoProps) {
|
||||
setCurrentTaskId("")
|
||||
clearTimer()
|
||||
|
||||
const basePayload = buildBasePayload()
|
||||
const assetIds = basePayload.asset_ids
|
||||
const isBatch = (props.previewCount || 1) > 1
|
||||
|
||||
try {
|
||||
const { width: outputWidth, height: outputHeight } = calculateResolution(
|
||||
props.videoRatio || "9:16",
|
||||
)
|
||||
const editMode = props.editMode ?? "random"
|
||||
const dedupEnabled = props.dedupEnabled !== false
|
||||
|
||||
const assetIds =
|
||||
props.materialMode === "auto" ? props.smartSelectedIds : props.selectedMaterials
|
||||
|
||||
// from-assets 已由 useStep2Materials 在用户选素材时(debounce 800ms)调用,
|
||||
// 后端已改为异步秒级返回,这里做一次轻量兜底:
|
||||
// 单次查 clips,已有则直接放行;没有则再调一次 from-assets。
|
||||
// from-assets 兜底:片段不存在则补一次
|
||||
if (assetIds.length > 0 && selectedTemplate) {
|
||||
try {
|
||||
const clipList = await getEditPlanClips(selectedTemplate, { limit: 500 })
|
||||
if (clipList.items.length === 0) {
|
||||
// 片段不存在(极端情况:useStep2Materials 的 debounce 还没触发)
|
||||
// 手动补一次 from-assets(后端秒级返回)
|
||||
await createClipsFromAssets(selectedTemplate, assetIds, "main")
|
||||
}
|
||||
} catch {
|
||||
@@ -159,221 +366,185 @@ export function useGenerateVideo(props: UseGenerateVideoProps) {
|
||||
}
|
||||
}
|
||||
|
||||
const isBatch = (props.previewCount || 1) > 1
|
||||
const hide = message.loading(
|
||||
isBatch ? `正在生成 ${props.previewCount} 个视频...` : "正在生成预览视频...",
|
||||
0,
|
||||
)
|
||||
|
||||
const coverUrl = props.coverSettings?.thumbnail_url || props.coverSettings?.upload_url || ""
|
||||
|
||||
// #1970:叙事模式下 ttsVoiceId 作为配音 id;随机模式用 selectedVoice
|
||||
const voiceLibraryId =
|
||||
editMode === "narrative"
|
||||
? props.ttsVoiceId || ""
|
||||
: props.voiceMode === "clone"
|
||||
? props.selectedClonedVoice || props.selectedVoice || ""
|
||||
: props.selectedVoice || ""
|
||||
|
||||
/* ── 批量变体数组(长度1=共用,长度=count=独立,空=回退单值) ── */
|
||||
const indexes =
|
||||
isBatch && props.selectedVariantIndexes?.length
|
||||
? props.selectedVariantIndexes
|
||||
: Array.from({ length: props.previewCount || 1 }, (_, i) => i)
|
||||
const batchCount = isBatch ? indexes.length : 1
|
||||
|
||||
// 标题文字数组:批量时按勾选顺序
|
||||
const titlesArr =
|
||||
isBatch && (props.variantTitles?.length || 0) >= batchCount
|
||||
? indexes.map((i) => props.variantTitles![i] || props.titleSettings?.title || "")
|
||||
: []
|
||||
// 配音数组:独立配音模式按勾选顺序;否则不传(回退共用 voice_library_id)
|
||||
const voiceArr =
|
||||
isBatch && props.voiceModePerVideo && props.variantVoiceLibraryIds?.length
|
||||
? indexes.map((i) => props.variantVoiceLibraryIds![i] || voiceLibraryId)
|
||||
: []
|
||||
// 封面数组:批量时按勾选顺序(未设置封面的变体传空串,后端回退智能封面)
|
||||
const coversArr =
|
||||
isBatch && props.variantCoverUrls?.length
|
||||
? indexes.map((i) => props.variantCoverUrls![i] || "")
|
||||
: []
|
||||
// #1744 变体 plan 数组:预览阶段后端独立选片产出的 plan id,按勾选顺序回传,
|
||||
// 后端直接关联这些 plan 渲染(不再重新选片)→ 预览所见即成片。
|
||||
// 全部为空(降级本地模拟/后端端点未上线)时不传,后端走自身独立选片。
|
||||
const variantPlansArr =
|
||||
isBatch && props.variantPlanIds?.length
|
||||
? indexes.map((i) => props.variantPlanIds![i] || "")
|
||||
: []
|
||||
const hasVariantPlans = variantPlansArr.some((id) => !!id)
|
||||
|
||||
try {
|
||||
const taskResp = await createGenerationTask({
|
||||
template_id: selectedTemplate,
|
||||
asset_ids: assetIds,
|
||||
output_width: outputWidth,
|
||||
output_height: outputHeight,
|
||||
cover_url: coverUrl,
|
||||
custom_title: props.titleSettings?.title || "",
|
||||
duration: props.duration || undefined,
|
||||
video_ratio: props.videoRatio,
|
||||
assembly_mode: editMode,
|
||||
...(editMode === "narrative" && props.selectedScript?.id
|
||||
? {
|
||||
script_id: props.selectedScript.id,
|
||||
tts_voice_id: props.ttsVoiceId || undefined,
|
||||
tts_voice_source: props.ttsVoiceSource || undefined,
|
||||
tts_style: props.ttsStyle || undefined,
|
||||
}
|
||||
: {}),
|
||||
dedup_enabled: dedupEnabled,
|
||||
voice_library_id: voiceLibraryId,
|
||||
...(props.selectedVoice && !voiceLibraryId ? { voice_ids: [props.selectedVoice] } : {}),
|
||||
bgm_config: {
|
||||
enabled: props.bgm !== false,
|
||||
...(props.bgmConfig?.music_id ? { preset_id: props.bgmConfig.music_id } : {}),
|
||||
},
|
||||
...(props.sourceEditPlanId ? { source_edit_plan_id: props.sourceEditPlanId } : {}),
|
||||
...(isBatch ? { count: batchCount } : {}),
|
||||
...(titlesArr.length ? { titles: titlesArr } : {}),
|
||||
...(voiceArr.length ? { voice_library_ids: voiceArr } : {}),
|
||||
...(coversArr.length ? { cover_urls: coversArr } : {}),
|
||||
...(hasVariantPlans ? { variant_plan_ids: variantPlansArr } : {}),
|
||||
...(props.titleSettings?.title
|
||||
? {
|
||||
title_config: {
|
||||
text: props.titleSettings.title,
|
||||
font: props.titleSettings.font,
|
||||
font_size: props.titleSettings.size,
|
||||
font_color: props.titleSettings.color,
|
||||
position: props.titleSettings.position,
|
||||
...(props.titleSettings.position === "custom" &&
|
||||
props.titleSettings.posX != null &&
|
||||
props.titleSettings.posY != null
|
||||
? {
|
||||
pos_x: Math.round(props.titleSettings.posX),
|
||||
pos_y: Math.round(props.titleSettings.posY),
|
||||
}
|
||||
: {}),
|
||||
bold: props.titleSettings.bold,
|
||||
italic: props.titleSettings.italic,
|
||||
stroke: props.titleSettings.stroke
|
||||
? {
|
||||
enabled: true,
|
||||
width: props.titleSettings.strokeWidth ?? 4,
|
||||
color: props.titleSettings.strokeColor ?? "#000000",
|
||||
}
|
||||
: { enabled: false },
|
||||
shadow: props.titleSettings.shadow
|
||||
? {
|
||||
enabled: true,
|
||||
offset_x: props.titleSettings.shadowOffsetX ?? 2,
|
||||
offset_y: props.titleSettings.shadowOffsetY ?? 2,
|
||||
blur: props.titleSettings.shadowBlur ?? 4,
|
||||
color: props.titleSettings.shadowColor ?? "rgba(0,0,0,0.8)",
|
||||
}
|
||||
: { enabled: false },
|
||||
line_height: props.titleSettings.lineHeight ?? 1.2,
|
||||
margin_top: props.titleSettings.marginTop ?? 24,
|
||||
max_chars_per_line: props.titleSettings.maxCharsPerLine ?? 0,
|
||||
...(props.titleSettings.bgEnabled
|
||||
? {
|
||||
background: {
|
||||
enabled: true,
|
||||
color: props.titleSettings.bgColor,
|
||||
padding: props.titleSettings.bgPadding,
|
||||
radius: props.titleSettings.bgRadius,
|
||||
},
|
||||
}
|
||||
: { background: { enabled: false } }),
|
||||
line_overrides: (props.titleSettings.lineOverrides ?? []).map((lo) => ({
|
||||
line_index: lo.line_index,
|
||||
text: lo.text,
|
||||
size: lo.size,
|
||||
color: lo.color,
|
||||
bold: lo.bold,
|
||||
italic: lo.italic,
|
||||
stroke: lo.stroke,
|
||||
highlights: lo.highlights?.map((h) => ({
|
||||
word: h.word,
|
||||
color: h.color,
|
||||
bold: h.bold,
|
||||
scale: h.scale,
|
||||
})),
|
||||
})),
|
||||
...(props.titleSettings.coverTitle
|
||||
? {
|
||||
cover_title_config: {
|
||||
title: props.titleSettings.coverTitle.title,
|
||||
font: props.titleSettings.coverTitle.font,
|
||||
font_size: props.titleSettings.coverTitle.size,
|
||||
font_color: props.titleSettings.coverTitle.color,
|
||||
bold: props.titleSettings.coverTitle.bold,
|
||||
italic: props.titleSettings.coverTitle.italic,
|
||||
position: props.titleSettings.coverTitle.position,
|
||||
stroke: props.titleSettings.coverTitle.stroke
|
||||
? {
|
||||
enabled: true,
|
||||
width: props.titleSettings.coverTitle.strokeWidth ?? 4,
|
||||
color: props.titleSettings.coverTitle.strokeColor ?? "#000000",
|
||||
}
|
||||
: { enabled: false },
|
||||
shadow: props.titleSettings.coverTitle.shadow
|
||||
? {
|
||||
enabled: true,
|
||||
offset_x: props.titleSettings.coverTitle.shadowOffsetX ?? 2,
|
||||
offset_y: props.titleSettings.coverTitle.shadowOffsetY ?? 2,
|
||||
blur: props.titleSettings.coverTitle.shadowBlur ?? 4,
|
||||
color:
|
||||
props.titleSettings.coverTitle.shadowColor ?? "rgba(0,0,0,0.8)",
|
||||
}
|
||||
: { enabled: false },
|
||||
...(props.titleSettings.coverTitle.bgEnabled
|
||||
? {
|
||||
background: {
|
||||
enabled: true,
|
||||
color: props.titleSettings.coverTitle.bgColor,
|
||||
padding: props.titleSettings.coverTitle.bgPadding,
|
||||
radius: props.titleSettings.coverTitle.bgRadius,
|
||||
},
|
||||
}
|
||||
: { background: { enabled: false } }),
|
||||
},
|
||||
}
|
||||
: {}),
|
||||
},
|
||||
}
|
||||
: {}),
|
||||
})
|
||||
hide()
|
||||
const taskIds = (taskResp.items || []).map((it) => it.id).filter(Boolean)
|
||||
|
||||
if (taskIds.length === 0) {
|
||||
throw new Error("创建任务成功但未返回任务 ID,请稍后在任务列表查看")
|
||||
}
|
||||
if (taskIds.length > 1) {
|
||||
// 批量:任务按创建顺序与勾选变体一一对应(后端按 count 顺序创建)
|
||||
setCurrentTaskId("")
|
||||
startPollingBatch(taskIds.map((taskId, i) => ({ taskId, variantIndex: indexes[i] ?? i })))
|
||||
} else {
|
||||
if (!isBatch) {
|
||||
/* ── 单视频:原逻辑(一次提交 count=1) ── */
|
||||
const hide = message.loading("正在生成预览视频...", 0)
|
||||
try {
|
||||
const taskResp = await createGenerationTask({ ...basePayload, count: 1 })
|
||||
hide()
|
||||
const taskIds = (taskResp.items || []).map((it) => it.id).filter(Boolean)
|
||||
if (taskIds.length === 0) {
|
||||
throw new Error("创建任务成功但未返回任务 ID,请稍后在任务列表查看")
|
||||
}
|
||||
setCurrentTaskId(taskIds[0])
|
||||
startPolling(taskIds[0])
|
||||
} catch (err) {
|
||||
hide()
|
||||
throw err
|
||||
}
|
||||
} catch (err) {
|
||||
hide()
|
||||
throw err
|
||||
return true
|
||||
}
|
||||
|
||||
/* ── 批量:支持任意数量视频,按队列容量串行提交,429 自动排队重试 ── */
|
||||
const indexes = props.selectedVariantIndexes?.length
|
||||
? props.selectedVariantIndexes
|
||||
: Array.from({ length: props.previewCount || 1 }, (_, i) => i)
|
||||
const batchCount = indexes.length
|
||||
|
||||
const titlesAll =
|
||||
(props.variantTitles?.length || 0) >= batchCount
|
||||
? indexes.map((i) => props.variantTitles![i] || props.titleSettings?.title || "")
|
||||
: indexes.map(() => props.titleSettings?.title || "")
|
||||
const voiceArrAll =
|
||||
props.voiceModePerVideo && props.variantVoiceLibraryIds?.length
|
||||
? indexes.map(
|
||||
(i) => props.variantVoiceLibraryIds![i] || basePayload.voice_library_id || "",
|
||||
)
|
||||
: []
|
||||
const coversAll = props.variantCoverUrls?.length
|
||||
? indexes.map((i) => props.variantCoverUrls![i] || "")
|
||||
: indexes.map(() => "")
|
||||
const plansAll = props.variantPlanIds?.length
|
||||
? indexes.map((i) => props.variantPlanIds![i] || "")
|
||||
: indexes.map(() => "")
|
||||
|
||||
const hasAnyVoice = voiceArrAll.some((v) => !!v)
|
||||
const hasAnyCover = coversAll.some((u) => !!u)
|
||||
const hasAnyPlan = plansAll.some((id) => !!id)
|
||||
|
||||
// 先用占位 ID 把所有变体卡片置为 queued,UI 可见
|
||||
const placeholderIds = indexes.map((_, i) => `__queued_${Date.now()}_${i}`)
|
||||
const initialTasks: BatchTaskState[] = indexes.map((variantIndex, i) => ({
|
||||
taskId: placeholderIds[i],
|
||||
variantIndex,
|
||||
status: "queued",
|
||||
progress: 0,
|
||||
error: null,
|
||||
videos: [],
|
||||
}))
|
||||
setBatchTasks(initialTasks)
|
||||
|
||||
message.loading({
|
||||
content: `已提交 ${batchCount} 个视频任务,系统按队列容量依次渲染…`,
|
||||
key: "batch-gen",
|
||||
duration: 3,
|
||||
})
|
||||
|
||||
/** 将占位 taskId 更新为真实 taskId(卡片引用同一对象) */
|
||||
const replacePlaceholder = (placeholderId: string, realTaskId: string) => {
|
||||
setBatchTasks((prev) => {
|
||||
const idx = prev.findIndex((t) => t.taskId === placeholderId)
|
||||
if (idx === -1) return prev
|
||||
const next = [...prev]
|
||||
next[idx] = { ...next[idx], taskId: realTaskId }
|
||||
return next
|
||||
})
|
||||
}
|
||||
|
||||
/** 提交某一索引的单任务(count=1),成功后返回真实 taskId;429/503 则返回 waitMs */
|
||||
const submitOne = async (
|
||||
i: number,
|
||||
): Promise<{ queued: true; waitMs: number } | { queued: false; taskId: string }> => {
|
||||
const body: CreateGenerationTaskRequest = {
|
||||
...basePayload,
|
||||
count: 1,
|
||||
titles: [titlesAll[i] || ""],
|
||||
...(hasAnyVoice
|
||||
? { voice_library_ids: [voiceArrAll[i] || basePayload.voice_library_id || ""] }
|
||||
: {}),
|
||||
...(hasAnyCover ? { cover_urls: [coversAll[i] || ""] } : {}),
|
||||
...(hasAnyPlan && plansAll[i] ? { variant_plan_ids: [plansAll[i]] } : {}),
|
||||
}
|
||||
try {
|
||||
const resp = await createGenerationTask(body)
|
||||
const item = resp.items?.[0]
|
||||
const tid = item?.id
|
||||
if (!tid) throw new Error("创建任务成功但未返回任务 ID")
|
||||
return { queued: false, taskId: tid }
|
||||
} catch (err) {
|
||||
const q = isUserQueueFullError(err)
|
||||
if (q) return { queued: true, waitMs: q.waitMs }
|
||||
throw err
|
||||
}
|
||||
}
|
||||
|
||||
// 串行提交:每次提交一个;429/503 则等待后重试;其它错误立即标记该任务失败
|
||||
let fatalErr: unknown = null
|
||||
for (let i = 0; i < batchCount; i++) {
|
||||
if (cancelledRef.current) return false
|
||||
const variantIndex = indexes[i]
|
||||
const placeholderId = placeholderIds[i]
|
||||
let attempt = 0
|
||||
let submitted = false
|
||||
while (!submitted) {
|
||||
if (cancelledRef.current) return false
|
||||
attempt++
|
||||
try {
|
||||
const result = await submitOne(i)
|
||||
if (!result.queued) {
|
||||
replacePlaceholder(placeholderId, result.taskId)
|
||||
// 先更新到 running,再启动单任务增量轮询(不触发整体 onComplete)
|
||||
pollBatchTaskQueued(result.taskId, variantIndex)
|
||||
submitted = true
|
||||
} else {
|
||||
// 排队:保持 queued 状态,等待后重试
|
||||
handleBatchTaskUpdate(placeholderId, {
|
||||
taskId: placeholderId,
|
||||
variantIndex,
|
||||
status: "queued",
|
||||
progress: 0,
|
||||
error: null,
|
||||
})
|
||||
if (attempt === 1) {
|
||||
message.info({
|
||||
content: `队列繁忙,${Math.round(result.waitMs / 1000)} 秒后自动继续提交后续视频…`,
|
||||
key: "batch-gen",
|
||||
duration: 4,
|
||||
})
|
||||
}
|
||||
await sleep(Math.min(result.waitMs, 60_000))
|
||||
}
|
||||
} catch (err) {
|
||||
// 非限流错误:该任务标记失败,继续后续任务(不阻断整个批量)
|
||||
console.error("[batch generate] 任务提交失败:", err)
|
||||
const msg = translateError(extractBackendError(err))
|
||||
handleBatchTaskUpdate(placeholderId, {
|
||||
taskId: placeholderId,
|
||||
variantIndex,
|
||||
status: "failed",
|
||||
error: msg,
|
||||
progress: 0,
|
||||
})
|
||||
submitted = true
|
||||
if (!fatalErr) fatalErr = err
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
if (fatalErr) {
|
||||
// 有任务失败但其余已成功,整体不 throw;由 UI 展示单个失败卡片
|
||||
}
|
||||
return true
|
||||
} catch (err: unknown) {
|
||||
console.error("[handleGenerate] 生成失败:", err)
|
||||
setGenerating(false)
|
||||
const backendMsg = extractBackendError(err)
|
||||
console.error("[handleGenerate] 错误信息:", backendMsg, "完整错误:", err)
|
||||
const finalMsg = translateError(backendMsg)
|
||||
setGenerateError(finalMsg)
|
||||
setGenerating(false)
|
||||
message.error(finalMsg)
|
||||
return false
|
||||
}
|
||||
return true
|
||||
}, [props, clearTimer, startPolling, startPollingBatch, selectedTemplate])
|
||||
}, [
|
||||
props,
|
||||
clearTimer,
|
||||
startPolling,
|
||||
selectedTemplate,
|
||||
buildBasePayload,
|
||||
handleBatchTaskUpdate,
|
||||
clearQueueTimers,
|
||||
pollBatchTaskQueued,
|
||||
])
|
||||
|
||||
const retry = useCallback(() => {
|
||||
setGenerateError(null)
|
||||
@@ -383,9 +554,10 @@ export function useGenerateVideo(props: UseGenerateVideoProps) {
|
||||
/** 第5步:单独重试某个失败任务 */
|
||||
const retryBatchTask = useCallback(
|
||||
(taskId: string) => {
|
||||
handleBatchTaskUpdate(taskId, { status: "running", progress: 0, error: null, videos: [] })
|
||||
retryTask(taskId)
|
||||
},
|
||||
[retryTask],
|
||||
[retryTask, handleBatchTaskUpdate],
|
||||
)
|
||||
|
||||
const dismissError = useCallback(() => {
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
@@ -0,0 +1,263 @@
|
||||
/**
|
||||
* 爆款视频素材选择弹窗(通用版,支持 image/video/voice)
|
||||
* 基于 ai-avatar 的 ModalAssetPicker 改造:
|
||||
* - kind 可传 "image" | "video" | "voice"
|
||||
* - 多图场景 multiple=true 时底部"确认选择"
|
||||
* - 单选场景点击即回调关闭
|
||||
*/
|
||||
import { useEffect, useState } from "react"
|
||||
import { getAssets, getAssetLibraries, type AssetItem, type AssetLibraryItem } from "@/api/assets"
|
||||
|
||||
export interface AssetPickerModalProps {
|
||||
open: boolean
|
||||
kind: "image" | "video" | "voice"
|
||||
multiple?: boolean
|
||||
title?: string
|
||||
onClose: () => void
|
||||
onSelect: (assets: AssetItem[]) => void
|
||||
}
|
||||
|
||||
const KIND_LABEL: Record<AssetPickerModalProps["kind"], string> = {
|
||||
image: "图片",
|
||||
video: "视频",
|
||||
voice: "音频",
|
||||
}
|
||||
|
||||
const MIME_KIND: Record<AssetPickerModalProps["kind"], string> = {
|
||||
image: "image",
|
||||
video: "video",
|
||||
voice: "audio",
|
||||
}
|
||||
|
||||
export default function AssetPickerModal({
|
||||
open,
|
||||
kind,
|
||||
multiple = false,
|
||||
title,
|
||||
onClose,
|
||||
onSelect,
|
||||
}: AssetPickerModalProps) {
|
||||
const [keyword, setKeyword] = useState("")
|
||||
const [libraries, setLibraries] = useState<AssetLibraryItem[]>([])
|
||||
const [libraryId, setLibraryId] = useState<string>("")
|
||||
const [assets, setAssets] = useState<AssetItem[]>([])
|
||||
const [picked, setPicked] = useState<Set<string>>(new Set())
|
||||
const [loadingLibs, setLoadingLibs] = useState(false)
|
||||
const [loadingAssets, setLoadingAssets] = useState(false)
|
||||
const [error, setError] = useState("")
|
||||
|
||||
useEffect(() => {
|
||||
if (!open) return
|
||||
setKeyword("")
|
||||
setLibraries([])
|
||||
setLibraryId("")
|
||||
setAssets([])
|
||||
setError("")
|
||||
setPicked(new Set())
|
||||
}, [open])
|
||||
|
||||
useEffect(() => {
|
||||
if (!open) return
|
||||
let cancelled = false
|
||||
setLoadingLibs(true)
|
||||
getAssetLibraries(kind)
|
||||
.then((libs) => {
|
||||
if (cancelled) return
|
||||
const list = Array.isArray(libs) ? libs : []
|
||||
setLibraries(list)
|
||||
if (list.length > 0) setLibraryId(list[0].id)
|
||||
})
|
||||
.catch(() => {
|
||||
if (!cancelled) setError("素材库加载失败,请重试")
|
||||
})
|
||||
.finally(() => {
|
||||
if (!cancelled) setLoadingLibs(false)
|
||||
})
|
||||
return () => {
|
||||
cancelled = true
|
||||
}
|
||||
}, [open, kind])
|
||||
|
||||
useEffect(() => {
|
||||
if (!open || !libraryId) return
|
||||
let cancelled = false
|
||||
setLoadingAssets(true)
|
||||
const load = async () => {
|
||||
try {
|
||||
const { items } = await getAssets(libraryId, { page_size: 100 })
|
||||
if (cancelled) return
|
||||
let list = Array.isArray(items) ? items : []
|
||||
const mimePrefix = MIME_KIND[kind]
|
||||
list = list.filter((a) => !a.mime_type || a.mime_type.startsWith(mimePrefix))
|
||||
const kw = keyword.trim()
|
||||
if (kw) list = list.filter((a) => a.name?.includes(kw))
|
||||
setAssets(list)
|
||||
setError("")
|
||||
} catch {
|
||||
if (!cancelled) {
|
||||
setError("素材加载失败,请重试")
|
||||
setAssets([])
|
||||
}
|
||||
} finally {
|
||||
if (!cancelled) setLoadingAssets(false)
|
||||
}
|
||||
}
|
||||
const timer = window.setTimeout(load, 250)
|
||||
return () => {
|
||||
cancelled = true
|
||||
window.clearTimeout(timer)
|
||||
}
|
||||
}, [open, libraryId, keyword, kind])
|
||||
|
||||
const thumbFor = (a: AssetItem) => {
|
||||
if (kind === "image") return a.thumbnail_url || a.file_url
|
||||
if (kind === "video") return a.thumbnail_url
|
||||
return ""
|
||||
}
|
||||
|
||||
const togglePick = (id: string) => {
|
||||
if (multiple) {
|
||||
setPicked((prev) => {
|
||||
const n = new Set(prev)
|
||||
if (n.has(id)) n.delete(id)
|
||||
else n.add(id)
|
||||
return n
|
||||
})
|
||||
} else {
|
||||
const asset = assets.find((a) => a.id === id)
|
||||
if (asset) {
|
||||
onSelect([asset])
|
||||
onClose()
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
const handleConfirm = () => {
|
||||
const list = assets.filter((a) => picked.has(a.id))
|
||||
if (list.length > 0) onSelect(list)
|
||||
onClose()
|
||||
}
|
||||
|
||||
if (!open) return null
|
||||
|
||||
return (
|
||||
<div className="vv-modal-mask" onClick={onClose}>
|
||||
<div className="vv-modal" onClick={(e) => e.stopPropagation()}>
|
||||
<div className="vv-modal-head">
|
||||
<span className="vv-modal-title">{title || `选择${KIND_LABEL[kind]}素材`}</span>
|
||||
<button className="vv-modal-close" onClick={onClose} aria-label="关闭">
|
||||
×
|
||||
</button>
|
||||
</div>
|
||||
<div className="vv-modal-body">
|
||||
<div className="vv-asset-search">
|
||||
<select
|
||||
className="vv-input"
|
||||
style={{ width: 170, flex: "0 0 auto" }}
|
||||
value={libraryId}
|
||||
onChange={(e) => setLibraryId(e.target.value)}
|
||||
disabled={loadingLibs || libraries.length === 0}
|
||||
>
|
||||
{libraries.length === 0 ? (
|
||||
<option value="">
|
||||
{loadingLibs ? "加载中…" : `暂无${KIND_LABEL[kind]}素材库`}
|
||||
</option>
|
||||
) : (
|
||||
libraries.map((lib) => (
|
||||
<option key={lib.id} value={lib.id}>
|
||||
📁 {lib.name}
|
||||
</option>
|
||||
))
|
||||
)}
|
||||
</select>
|
||||
<input
|
||||
className="vv-input"
|
||||
type="text"
|
||||
placeholder={`搜索${KIND_LABEL[kind]}名称…`}
|
||||
value={keyword}
|
||||
onChange={(e) => setKeyword(e.target.value)}
|
||||
/>
|
||||
</div>
|
||||
|
||||
{libraries.length === 0 && !loadingLibs ? (
|
||||
<div className="vv-modal-empty">
|
||||
<div className="vv-empty-icon">📁</div>
|
||||
暂无{KIND_LABEL[kind]}素材库,请先在「素材库」中创建并上传
|
||||
</div>
|
||||
) : loadingAssets ? (
|
||||
<div className="vv-modal-empty">
|
||||
<div className="vv-empty-icon">⏳</div>
|
||||
素材加载中…
|
||||
</div>
|
||||
) : error ? (
|
||||
<div className="vv-modal-empty">
|
||||
<div className="vv-empty-icon">⚠️</div>
|
||||
{error}
|
||||
</div>
|
||||
) : assets.length === 0 ? (
|
||||
<div className="vv-modal-empty">
|
||||
<div className="vv-empty-icon">
|
||||
{kind === "image" ? "🖼️" : kind === "video" ? "🎬" : "🎵"}
|
||||
</div>
|
||||
{kind === "voice" ? (
|
||||
<>
|
||||
<div style={{ marginTop: 8, fontSize: 13 }}>暂无配音素材</div>
|
||||
<div style={{ marginTop: 4, fontSize: 12, color: "#9ca3af" }}>
|
||||
请先在「配音/我的音色」中上传音频文件,或在素材库管理中添加
|
||||
</div>
|
||||
</>
|
||||
) : (
|
||||
<>该素材库暂无{KIND_LABEL[kind]}素材</>
|
||||
)}
|
||||
</div>
|
||||
) : (
|
||||
<div className={`vv-asset-thumbs vv-asset-${kind}`}>
|
||||
{assets.map((asset) => {
|
||||
const active = picked.has(asset.id)
|
||||
const thumb = thumbFor(asset)
|
||||
return (
|
||||
<div
|
||||
key={asset.id}
|
||||
className={`vv-thumb-card${active ? " selected" : ""}`}
|
||||
onClick={() => togglePick(asset.id)}
|
||||
>
|
||||
{thumb ? (
|
||||
<img src={thumb} alt={asset.name} />
|
||||
) : kind === "video" ? (
|
||||
<video src={asset.file_url} muted preload="metadata" />
|
||||
) : (
|
||||
<div className="vv-thumb-ph">{kind === "voice" ? "🎵" : "📄"}</div>
|
||||
)}
|
||||
{active && <div className="vv-thumb-check">✓</div>}
|
||||
<div className="vv-thumb-name" title={asset.name}>
|
||||
<span className="vv-thumb-name-txt">{asset.name}</span>
|
||||
{kind === "voice" &&
|
||||
typeof asset.duration === "number" &&
|
||||
asset.duration > 0 && (
|
||||
<span className="vv-thumb-dur">{Math.round(asset.duration)}s</span>
|
||||
)}
|
||||
</div>
|
||||
</div>
|
||||
)
|
||||
})}
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
{multiple && (
|
||||
<div className="vv-modal-foot">
|
||||
<button className="vv-btn vv-btn-ghost" onClick={onClose}>
|
||||
取消
|
||||
</button>
|
||||
<button
|
||||
className="vv-btn vv-btn-primary"
|
||||
onClick={handleConfirm}
|
||||
disabled={picked.size === 0}
|
||||
>
|
||||
确认选择({picked.size})
|
||||
</button>
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
</div>
|
||||
)
|
||||
}
|
||||
@@ -0,0 +1,355 @@
|
||||
/**
|
||||
* 内置音色选择弹窗(浅色紫调版)
|
||||
* - 标题「选择音色」+ 搜索框 + 分类筛选 + 3列卡片网格 + 试听 + 选中 + 完成选择
|
||||
*/
|
||||
import React, { useEffect, useMemo, useRef, useState } from "react"
|
||||
import {
|
||||
CloseOutlined,
|
||||
SearchOutlined,
|
||||
PlayCircleOutlined,
|
||||
PauseCircleOutlined,
|
||||
UserOutlined,
|
||||
} from "@ant-design/icons"
|
||||
import { Select, Input } from "antd"
|
||||
|
||||
export interface PresetVoice {
|
||||
id: string
|
||||
name: string
|
||||
gender?: "female" | "male" | "child" | "other"
|
||||
gender_label?: string
|
||||
category?: string
|
||||
avatar_url?: string
|
||||
sample_audio_url?: string
|
||||
desc?: string
|
||||
}
|
||||
|
||||
interface Props {
|
||||
open: boolean
|
||||
voices?: PresetVoice[]
|
||||
loading?: boolean
|
||||
selectedId?: string
|
||||
onClose: () => void
|
||||
onConfirm: (voice: PresetVoice) => void
|
||||
}
|
||||
|
||||
/** 兜底 mock 音色(后端 /api/v1/tts/presets 返回字段不够时使用) */
|
||||
const MOCK_VOICES: PresetVoice[] = [
|
||||
// ⚠️ 兜底 mock,仅在 /voices/presets 接口不可达时使用;ID 必须与后端
|
||||
// packages/domain/preset_voices.py PRESET_VOICES 的 voice_id 对齐(v3后缀)
|
||||
{
|
||||
id: "longxiaochun_v3",
|
||||
name: "龙小淳",
|
||||
gender: "female",
|
||||
category: "女声",
|
||||
desc: "知性积极女声,适合语音助手",
|
||||
},
|
||||
{
|
||||
id: "longxiaoxia_v3",
|
||||
name: "龙小夏",
|
||||
gender: "female",
|
||||
category: "女声",
|
||||
desc: "沉稳权威女声,适合新闻播报",
|
||||
},
|
||||
{
|
||||
id: "longsanshu_v3",
|
||||
name: "龙三叔",
|
||||
gender: "male",
|
||||
category: "男声",
|
||||
desc: "沉稳质感男声,适合有声书",
|
||||
},
|
||||
{
|
||||
id: "longyue_v3",
|
||||
name: "龙悦",
|
||||
gender: "female",
|
||||
category: "女声",
|
||||
desc: "温暖磁性女声,适合广告配音",
|
||||
},
|
||||
{
|
||||
id: "longshu_v3",
|
||||
name: "龙书",
|
||||
gender: "male",
|
||||
category: "男声",
|
||||
desc: "沉稳青年男声,适合教育讲解",
|
||||
},
|
||||
{
|
||||
id: "longyingjing_v3",
|
||||
name: "龙应静",
|
||||
gender: "female",
|
||||
category: "女声",
|
||||
desc: "低调冷静女声,适合纪录片解说",
|
||||
},
|
||||
{
|
||||
id: "longshuo_v3",
|
||||
name: "龙硕",
|
||||
gender: "male",
|
||||
category: "男声",
|
||||
desc: "博才干练男声,适合科技类内容",
|
||||
},
|
||||
{
|
||||
id: "longtian_v3",
|
||||
name: "龙甜",
|
||||
gender: "female",
|
||||
category: "女声",
|
||||
desc: "活泼女声,适合短视频配音",
|
||||
},
|
||||
]
|
||||
|
||||
const CATEGORY_LABELS: Record<string, string> = {
|
||||
all: "全部分类",
|
||||
female: "女声",
|
||||
male: "男声",
|
||||
child: "童声",
|
||||
dialect: "方言",
|
||||
emotion: "情绪",
|
||||
}
|
||||
|
||||
const GENDER_LABEL = (v: PresetVoice) => {
|
||||
if (v.gender_label) return v.gender_label
|
||||
const g = v.gender
|
||||
if (g === "female") return "女声·女声"
|
||||
if (g === "male") return "男声·男声"
|
||||
if (g === "child") return "童声·童声"
|
||||
return "性别未标注·其他"
|
||||
}
|
||||
|
||||
const AVATAR_BG = (gender?: string) => {
|
||||
if (gender === "female") return "#fce7f3"
|
||||
if (gender === "male") return "#dbeafe"
|
||||
if (gender === "child") return "#fef3c7"
|
||||
return "#f3f0ff"
|
||||
}
|
||||
const AVATAR_COLOR = (gender?: string) => {
|
||||
if (gender === "female") return "#be185d"
|
||||
if (gender === "male") return "#1d4ed8"
|
||||
if (gender === "child") return "#b45309"
|
||||
return "#7c3aed"
|
||||
}
|
||||
|
||||
const PresetVoicePickerModal: React.FC<Props> = ({
|
||||
open,
|
||||
voices,
|
||||
loading,
|
||||
selectedId,
|
||||
onClose,
|
||||
onConfirm,
|
||||
}) => {
|
||||
const [keyword, setKeyword] = useState("")
|
||||
const [category, setCategory] = useState<string>("all")
|
||||
const [pickedId, setPickedId] = useState<string | undefined>(selectedId)
|
||||
const [playingId, setPlayingId] = useState<string | null>(null)
|
||||
const audioRef = useRef<HTMLAudioElement | null>(null)
|
||||
|
||||
useEffect(() => {
|
||||
if (open) {
|
||||
setKeyword("")
|
||||
setCategory("all")
|
||||
setPickedId(selectedId)
|
||||
setPlayingId(null)
|
||||
}
|
||||
}, [open, selectedId])
|
||||
|
||||
// 停止播放
|
||||
useEffect(() => {
|
||||
return () => {
|
||||
audioRef.current?.pause()
|
||||
audioRef.current = null
|
||||
}
|
||||
}, [])
|
||||
|
||||
// 合并真实数据和 mock:如果真实数据 gender/category 缺失,用 mock 兜底
|
||||
const allVoices: PresetVoice[] = useMemo(() => {
|
||||
// 真实 API 返回的 voice_id 以 API 为准(如 longxiaochun_v3),前端不做硬编码覆盖
|
||||
const realList: PresetVoice[] = (voices || []).map((v) => {
|
||||
// 按 id 精确匹配 mock 获取补充元信息(id 即 voice_id,唯一稳定键)
|
||||
const mockMatch = MOCK_VOICES.find((m) => m.id === v.id)
|
||||
return {
|
||||
...v,
|
||||
gender: v.gender || mockMatch?.gender,
|
||||
category:
|
||||
v.category ||
|
||||
mockMatch?.category ||
|
||||
(v.gender === "female" ? "女声" : v.gender === "male" ? "男声" : "其他"),
|
||||
desc: v.desc || mockMatch?.desc,
|
||||
sample_audio_url: v.sample_audio_url,
|
||||
}
|
||||
})
|
||||
// 如果没有真实数据,使用兜底 mock(接口失败时)
|
||||
return realList.length > 0 ? realList : MOCK_VOICES
|
||||
}, [voices])
|
||||
|
||||
const categories = useMemo(() => {
|
||||
const set = new Set<string>()
|
||||
allVoices.forEach((v) => {
|
||||
if (v.category) set.add(v.category)
|
||||
})
|
||||
return Array.from(set)
|
||||
}, [allVoices])
|
||||
|
||||
const filtered = useMemo(() => {
|
||||
const kw = keyword.trim().toLowerCase()
|
||||
return allVoices.filter((v) => {
|
||||
if (category !== "all") {
|
||||
if (v.category !== category && category !== CATEGORY_LABELS[v.gender || ""]) {
|
||||
// gender 兜底匹配
|
||||
if (
|
||||
!(category === "女声" && v.gender === "female") &&
|
||||
!(category === "男声" && v.gender === "male") &&
|
||||
!(category === "童声" && v.gender === "child") &&
|
||||
!(category === "方言" && v.category === "方言") &&
|
||||
!(category === "情绪" && v.category === "情绪")
|
||||
) {
|
||||
return false
|
||||
}
|
||||
}
|
||||
}
|
||||
if (!kw) return true
|
||||
return (
|
||||
v.name?.toLowerCase().includes(kw) ||
|
||||
v.desc?.toLowerCase().includes(kw) ||
|
||||
v.category?.toLowerCase().includes(kw)
|
||||
)
|
||||
})
|
||||
}, [allVoices, keyword, category])
|
||||
|
||||
const handlePreview = (v: PresetVoice) => {
|
||||
if (!v.sample_audio_url) {
|
||||
// 无示例音频
|
||||
return
|
||||
}
|
||||
if (playingId === v.id) {
|
||||
audioRef.current?.pause()
|
||||
setPlayingId(null)
|
||||
return
|
||||
}
|
||||
audioRef.current?.pause()
|
||||
const a = new Audio(v.sample_audio_url)
|
||||
a.onended = () => setPlayingId(null)
|
||||
a.onerror = () => setPlayingId(null)
|
||||
a.play().catch(() => {})
|
||||
audioRef.current = a
|
||||
setPlayingId(v.id)
|
||||
}
|
||||
|
||||
const handleConfirm = () => {
|
||||
const picked = allVoices.find((v) => v.id === pickedId)
|
||||
if (!picked) return
|
||||
onConfirm(picked)
|
||||
}
|
||||
|
||||
if (!open) return null
|
||||
|
||||
return (
|
||||
<div className="vv-modal-mask" onClick={onClose}>
|
||||
<div className="vv-modal vv-modal-lg" onClick={(e) => e.stopPropagation()}>
|
||||
<div className="vv-modal-head">
|
||||
<div className="vv-modal-title">选择音色</div>
|
||||
<button className="vv-modal-close" onClick={onClose}>
|
||||
<CloseOutlined />
|
||||
</button>
|
||||
</div>
|
||||
<div className="vv-modal-body">
|
||||
{/* 搜索 */}
|
||||
<Input
|
||||
className="vv-voice-search"
|
||||
placeholder="搜索音色名称或风格"
|
||||
prefix={<SearchOutlined style={{ color: "#9ca3af" }} />}
|
||||
value={keyword}
|
||||
onChange={(e) => setKeyword(e.target.value)}
|
||||
allowClear
|
||||
size="large"
|
||||
/>
|
||||
{/* 分类筛选 */}
|
||||
<div className="vv-voice-cat-row">
|
||||
<span className="vv-voice-cat-label">音色分类</span>
|
||||
<Select
|
||||
value={category}
|
||||
onChange={setCategory}
|
||||
style={{ width: 180 }}
|
||||
options={[
|
||||
{ value: "all", label: "全部分类" },
|
||||
...[
|
||||
"女声",
|
||||
"男声",
|
||||
"童声",
|
||||
"方言",
|
||||
"情绪",
|
||||
...categories.filter(
|
||||
(c) => !["女声", "男声", "童声", "方言", "情绪"].includes(c),
|
||||
),
|
||||
].map((c) => ({ value: c, label: c })),
|
||||
]}
|
||||
/>
|
||||
</div>
|
||||
{/* 卡片网格 */}
|
||||
<div className="vv-voice-grid">
|
||||
{loading && filtered.length === 0 ? (
|
||||
<div className="vv-modal-empty">加载中…</div>
|
||||
) : filtered.length === 0 ? (
|
||||
<div className="vv-modal-empty">没有匹配的音色</div>
|
||||
) : (
|
||||
filtered.map((v) => {
|
||||
const isPicked = pickedId === v.id
|
||||
const isPlaying = playingId === v.id
|
||||
return (
|
||||
<div
|
||||
key={v.id}
|
||||
className={`vv-voice-card ${isPicked ? "selected" : ""}`}
|
||||
onClick={() => setPickedId(v.id)}
|
||||
>
|
||||
<div
|
||||
className="vv-voice-card-avatar"
|
||||
style={{ background: AVATAR_BG(v.gender), color: AVATAR_COLOR(v.gender) }}
|
||||
>
|
||||
{v.avatar_url ? (
|
||||
<img src={v.avatar_url} alt={v.name} />
|
||||
) : (
|
||||
<UserOutlined style={{ fontSize: 22 }} />
|
||||
)}
|
||||
</div>
|
||||
<div className="vv-voice-card-name" title={v.name}>
|
||||
{v.name}
|
||||
</div>
|
||||
<div className="vv-voice-card-gender">{GENDER_LABEL(v)}</div>
|
||||
{v.desc && <div className="vv-voice-card-desc">{v.desc}</div>}
|
||||
<div className="vv-voice-card-actions">
|
||||
<button
|
||||
className={`vv-voice-card-btn ${isPicked ? "picked" : ""}`}
|
||||
onClick={(e) => {
|
||||
e.stopPropagation()
|
||||
setPickedId(v.id)
|
||||
}}
|
||||
>
|
||||
{isPicked ? "✓ 已选择" : "选择"}
|
||||
</button>
|
||||
<button
|
||||
className={`vv-voice-card-btn vv-voice-card-btn-preview ${isPlaying ? "playing" : ""} ${!v.sample_audio_url ? "disabled" : ""}`}
|
||||
onClick={(e) => {
|
||||
e.stopPropagation()
|
||||
handlePreview(v)
|
||||
}}
|
||||
disabled={!v.sample_audio_url}
|
||||
>
|
||||
{isPlaying ? <PauseCircleOutlined /> : <PlayCircleOutlined />}
|
||||
{isPlaying ? "停止" : "试听"}
|
||||
</button>
|
||||
</div>
|
||||
</div>
|
||||
)
|
||||
})
|
||||
)}
|
||||
</div>
|
||||
</div>
|
||||
<div className="vv-modal-foot">
|
||||
<button className="vv-btn vv-btn-ghost" onClick={onClose}>
|
||||
取消
|
||||
</button>
|
||||
<button className="vv-btn vv-btn-primary" onClick={handleConfirm} disabled={!pickedId}>
|
||||
完成选择
|
||||
</button>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
)
|
||||
}
|
||||
|
||||
export default PresetVoicePickerModal
|
||||
@@ -0,0 +1,74 @@
|
||||
import { useCallback, useEffect, useRef } from "react"
|
||||
import { getViralVideoJob } from "@/api/viral-video"
|
||||
import { isAnalysisStage, type ViralVideoJob, type ViralVideoStatus } from "@/api/viral-video/types"
|
||||
|
||||
const TERMINAL: ViralVideoStatus[] = ["completed", "failed", "cancelled"]
|
||||
|
||||
export interface UseViralVideoPollingOptions {
|
||||
/** 轮询间隔(毫秒),默认 1500 */
|
||||
intervalMs?: number
|
||||
}
|
||||
|
||||
/**
|
||||
* 爆款视频任务 HTTP 轮询 hook。
|
||||
* 负责持续拉取任务状态并回调给上层;上层负责根据状态/阶段切换 UI 文案。
|
||||
* 任务进入终态(completed/failed/cancelled)后自动停止。
|
||||
*/
|
||||
export function useViralVideoPolling(
|
||||
jobId: string | null | undefined,
|
||||
onUpdate: (job: ViralVideoJob) => void,
|
||||
options: UseViralVideoPollingOptions = {},
|
||||
) {
|
||||
const { intervalMs = 1500 } = options
|
||||
const timerRef = useRef<ReturnType<typeof setTimeout> | null>(null)
|
||||
const stoppedRef = useRef(false)
|
||||
const failCountRef = useRef(0)
|
||||
|
||||
const stop = useCallback(() => {
|
||||
stoppedRef.current = true
|
||||
if (timerRef.current) {
|
||||
clearTimeout(timerRef.current)
|
||||
timerRef.current = null
|
||||
}
|
||||
}, [])
|
||||
|
||||
const pollOnce = useCallback(
|
||||
async (id: string) => {
|
||||
try {
|
||||
const job = await getViralVideoJob(id)
|
||||
failCountRef.current = 0
|
||||
onUpdate(job)
|
||||
if (TERMINAL.includes(job.status)) {
|
||||
stop()
|
||||
return
|
||||
}
|
||||
if (stoppedRef.current) return
|
||||
// 视频渲染阶段(Seedance 多段视频生成较慢)拉长轮询间隔
|
||||
const inRender = job.progress_stage === "rendering"
|
||||
// 分析阶段走默认间隔即可
|
||||
const isAnalyzing = isAnalysisStage(job.progress_stage)
|
||||
const nextDelay = inRender ? 3000 : isAnalyzing ? 2000 : intervalMs
|
||||
timerRef.current = setTimeout(() => pollOnce(id), nextDelay)
|
||||
} catch (_err) {
|
||||
failCountRef.current += 1
|
||||
if (stoppedRef.current) return
|
||||
const delay = Math.min(intervalMs * 2 ** Math.min(failCountRef.current, 3), 10000)
|
||||
timerRef.current = setTimeout(() => pollOnce(id), delay)
|
||||
}
|
||||
},
|
||||
[intervalMs, onUpdate, stop],
|
||||
)
|
||||
|
||||
useEffect(() => {
|
||||
stoppedRef.current = false
|
||||
failCountRef.current = 0
|
||||
if (!jobId) {
|
||||
stop()
|
||||
return
|
||||
}
|
||||
pollOnce(jobId)
|
||||
return stop
|
||||
}, [jobId, pollOnce, stop])
|
||||
|
||||
return { stop }
|
||||
}
|
||||
+13
-24
@@ -1,25 +1,26 @@
|
||||
import { useState, useCallback } from "react"
|
||||
import { useMutation, useQueryClient } from "@tanstack/react-query"
|
||||
import { message } from "antd"
|
||||
import {
|
||||
uploadAssetDirect,
|
||||
getAssetLibraries,
|
||||
getIngestJob,
|
||||
type AssetLibraryItem,
|
||||
} from "@/api/assets"
|
||||
import { uploadAssetDirect, getIngestJob, type AssetLibraryItem } from "@/api/assets"
|
||||
import { tagAsset } from "@/api/tags"
|
||||
import { type VoiceGender, type VoiceMaterial } from "../../../types"
|
||||
|
||||
interface UseVoiceUploadOptions {
|
||||
voiceLibrary?: { id: string; kind: string }
|
||||
createLibMutation: { mutateAsync: () => Promise<AssetLibraryItem>; isPending: boolean }
|
||||
createLibMutation?: {
|
||||
mutateAsync: () => Promise<AssetLibraryItem>
|
||||
isPending: boolean
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* 配音素材上传 Hook
|
||||
* 封装上传流程:获取库 → 上传文件 → 获取时长 → 创建记录 → 打标签
|
||||
*/
|
||||
export function useVoiceUpload({ voiceLibrary, createLibMutation }: UseVoiceUploadOptions) {
|
||||
export function useVoiceUpload({
|
||||
voiceLibrary,
|
||||
createLibMutation: _createLibMutation,
|
||||
}: UseVoiceUploadOptions) {
|
||||
const queryClient = useQueryClient()
|
||||
const [uploadProgress, setUploadProgress] = useState<number | null>(null)
|
||||
|
||||
@@ -33,24 +34,12 @@ export function useVoiceUpload({ voiceLibrary, createLibMutation }: UseVoiceUplo
|
||||
}) => {
|
||||
setUploadProgress(0)
|
||||
try {
|
||||
// 1. 获取或等待 voice library
|
||||
let lib = voiceLibrary
|
||||
if (!lib) {
|
||||
if (createLibMutation.isPending) {
|
||||
await createLibMutation.mutateAsync()
|
||||
}
|
||||
const libs = await queryClient.fetchQuery({
|
||||
queryKey: ["asset-libraries"],
|
||||
queryFn: () => getAssetLibraries(),
|
||||
})
|
||||
lib = libs.find((l: AssetLibraryItem) => l.kind === "voice")
|
||||
if (!lib) throw new Error("无法创建配音库")
|
||||
}
|
||||
|
||||
// 2. 上传文件(带进度,后端自动创建 ingest job)
|
||||
// 1. 上传文件:后端自动在默认项目下确保配音库存在(P0 404 修复)
|
||||
// 兼容 voiceLibrary 参数:若调用方已传入正确的库 ID 则直接复用,否则内部自动解析
|
||||
const complete = await uploadAssetDirect({
|
||||
file: data.file,
|
||||
library_id: lib.id,
|
||||
library_id: voiceLibrary?.id,
|
||||
kind: "voice",
|
||||
onProgress: (p) => setUploadProgress(p),
|
||||
})
|
||||
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
import { useState, useCallback } from "react"
|
||||
import { useMutation, useQueryClient } from "@tanstack/react-query"
|
||||
import { uploadAssetDirect, getAssetLibraries, getIngestJob } from "@/api/assets"
|
||||
import { uploadAssetDirect, getIngestJob } from "@/api/assets"
|
||||
|
||||
/**
|
||||
* 配音上传 Hook
|
||||
@@ -23,18 +23,10 @@ export function useVoiceUpload({ showToast }: UseVoiceUploadProps) {
|
||||
mutationFn: async (data: { file: File; name: string; description: string }) => {
|
||||
setUploadProgress(0)
|
||||
try {
|
||||
/* 获取或创建默认配音库 */
|
||||
const libs = await queryClient.fetchQuery({
|
||||
queryKey: ["asset-libraries"],
|
||||
queryFn: () => getAssetLibraries(),
|
||||
})
|
||||
const lib = libs.find((l) => l.kind === "voice")
|
||||
if (!lib) throw new Error("配音库不存在,请先在配音库页面创建")
|
||||
|
||||
/* 直传文件(后端会自动创建 ingest job) */
|
||||
/* 直传文件(后端会自动在默认项目下确保配音库存在,P0 404 修复) */
|
||||
const complete = await uploadAssetDirect({
|
||||
file: data.file,
|
||||
library_id: lib.id,
|
||||
kind: "voice",
|
||||
onProgress: (p) => setUploadProgress(p),
|
||||
})
|
||||
|
||||
|
||||
@@ -52,6 +52,10 @@ const appChildren: RouteObject[] = [
|
||||
path: "ai-avatar",
|
||||
lazy: lazyRoute(() => import("@/pages/ai-avatar/AiAvatarPage")),
|
||||
},
|
||||
{
|
||||
path: "viral-video",
|
||||
lazy: lazyRoute(() => import("@/pages/viral-video/ViralVideoPage")),
|
||||
},
|
||||
{
|
||||
path: "voice-clone",
|
||||
lazy: lazyRoute(() => import("@/pages/voice-clone/VoiceClone")),
|
||||
|
||||
@@ -0,0 +1,45 @@
|
||||
import { describe, it, expect } from "vitest"
|
||||
import { getErrorMessage, isErrorMsgShown } from "@/api/errors"
|
||||
|
||||
describe("api/errors", () => {
|
||||
it("returns string error directly", () => {
|
||||
expect(getErrorMessage("plain")).toBe("plain")
|
||||
})
|
||||
it("uses Error.message", () => {
|
||||
expect(getErrorMessage(new Error("boom"))).toBe("boom")
|
||||
})
|
||||
it("returns fallback for empty/unknown", () => {
|
||||
expect(getErrorMessage(null)).toBe("操作失败,请稍后重试")
|
||||
expect(getErrorMessage(undefined, "f")).toBe("f")
|
||||
})
|
||||
it("reads axios-like response.data.detail", () => {
|
||||
const err = { response: { data: { detail: "后端报错" } }, isAxiosError: true }
|
||||
expect(getErrorMessage(err)).toContain("后端报错")
|
||||
})
|
||||
it("reads axios-like response.data.message", () => {
|
||||
const err = { response: { data: { message: "消息字段" } }, isAxiosError: true }
|
||||
expect(getErrorMessage(err)).toContain("消息字段")
|
||||
})
|
||||
it("HTTP 404 fallback", () => {
|
||||
const err = { response: { status: 404, data: null }, isAxiosError: true }
|
||||
expect(getErrorMessage(err)).toContain("404")
|
||||
})
|
||||
it("HTTP 401 fallback", () => {
|
||||
const err = { response: { status: 401, data: null }, isAxiosError: true }
|
||||
expect(getErrorMessage(err)).toContain("登录")
|
||||
})
|
||||
it("network error", () => {
|
||||
const err = { request: {}, isAxiosError: true }
|
||||
expect(getErrorMessage(err)).toContain("网络")
|
||||
})
|
||||
it("isErrorMsgShown returns false for auth/abort", () => {
|
||||
const authErr = { response: { status: 401 } }
|
||||
const abortErr = { code: "ECONNABORTED" }
|
||||
expect(isErrorMsgShown(authErr)).toBe(false)
|
||||
expect(isErrorMsgShown(abortErr)).toBe(false)
|
||||
const e: any = new Error("x")
|
||||
e.__msgShown = true
|
||||
expect(isErrorMsgShown(e)).toBe(true)
|
||||
expect(isErrorMsgShown(new Error("x"))).toBe(false)
|
||||
})
|
||||
})
|
||||
@@ -0,0 +1,226 @@
|
||||
import { describe, expect, it, vi, beforeEach, afterEach } from "vitest"
|
||||
import {
|
||||
generateViralVideo,
|
||||
getViralVideoJob,
|
||||
confirmViralVideoIntent,
|
||||
retryViralVideo,
|
||||
getViralVideoHistory,
|
||||
getViralStyleTemplates,
|
||||
analyzeViralStyle,
|
||||
mockImageAnalysis,
|
||||
mockGenerateCopy,
|
||||
analyzeViralImages,
|
||||
generateViralCopy,
|
||||
confirmViralCopy,
|
||||
} from "@/api/viral-video"
|
||||
import {
|
||||
VALID_DURATIONS,
|
||||
VALID_RATIOS,
|
||||
isVideoStage,
|
||||
isImageAnalysisStage,
|
||||
isCopyStage,
|
||||
isAnalysisStage,
|
||||
} from "@/api/viral-video/types"
|
||||
|
||||
const mockGet = vi.fn()
|
||||
const mockPost = vi.fn()
|
||||
|
||||
vi.mock("@/api/client", () => ({
|
||||
default: {
|
||||
get: (...args: unknown[]) => mockGet(...args),
|
||||
post: (...args: unknown[]) => mockPost(...args),
|
||||
},
|
||||
}))
|
||||
|
||||
vi.mock("antd", () => ({ message: { error: vi.fn(), success: vi.fn() } }))
|
||||
|
||||
// 让 setTimeout 同步执行,避免测试等待 1.8s/2.2s
|
||||
beforeEach(() => {
|
||||
vi.useFakeTimers()
|
||||
vi.clearAllMocks()
|
||||
mockGet.mockResolvedValue({ data: {} })
|
||||
mockPost.mockResolvedValue({ data: {} })
|
||||
})
|
||||
afterEach(() => {
|
||||
vi.useRealTimers()
|
||||
})
|
||||
|
||||
describe("viral-video constants & stage helpers", () => {
|
||||
afterEach(() => {
|
||||
vi.useRealTimers()
|
||||
})
|
||||
beforeEach(() => {
|
||||
vi.useFakeTimers()
|
||||
vi.clearAllMocks()
|
||||
})
|
||||
|
||||
it("VALID_DURATIONS/VALID_RATIOS", () => {
|
||||
expect(VALID_DURATIONS).toEqual([5, 10, 15, 20, 25, 30])
|
||||
expect(VALID_RATIOS).toEqual(expect.arrayContaining(["9:16", "16:9", "1:1"]))
|
||||
})
|
||||
|
||||
it("isVideoStage", () => {
|
||||
expect(isVideoStage("tts")).toBe(true)
|
||||
expect(isVideoStage("rendering")).toBe(true)
|
||||
expect(isVideoStage("uploading")).toBe(true)
|
||||
expect(isVideoStage("script_generation")).toBe(false)
|
||||
expect(isVideoStage("completed")).toBe(false)
|
||||
expect(isVideoStage(undefined)).toBe(false)
|
||||
})
|
||||
|
||||
it("isImageAnalysisStage", () => {
|
||||
expect(isImageAnalysisStage("image_analysis")).toBe(true)
|
||||
expect(isImageAnalysisStage("video_analysis")).toBe(true)
|
||||
expect(isImageAnalysisStage("script_generation")).toBe(false)
|
||||
expect(isImageAnalysisStage(undefined)).toBe(false)
|
||||
})
|
||||
|
||||
it("isCopyStage", () => {
|
||||
expect(isCopyStage("intent_parsing")).toBe(true)
|
||||
expect(isCopyStage("script_generation")).toBe(true)
|
||||
expect(isCopyStage("review")).toBe(true)
|
||||
expect(isCopyStage("tts")).toBe(false)
|
||||
})
|
||||
|
||||
it("isAnalysisStage is union", () => {
|
||||
expect(isAnalysisStage("image_analysis")).toBe(true)
|
||||
expect(isAnalysisStage("script_generation")).toBe(true)
|
||||
expect(isAnalysisStage("tts")).toBe(false)
|
||||
expect(isAnalysisStage(undefined)).toBe(false)
|
||||
})
|
||||
})
|
||||
|
||||
describe("viral-video API wrappers", () => {
|
||||
afterEach(() => {
|
||||
vi.useRealTimers()
|
||||
})
|
||||
beforeEach(() => {
|
||||
vi.useFakeTimers()
|
||||
vi.clearAllMocks()
|
||||
mockGet.mockResolvedValue({ data: {} })
|
||||
mockPost.mockResolvedValue({ data: {} })
|
||||
})
|
||||
|
||||
it("generateViralVideo", async () => {
|
||||
mockPost.mockResolvedValue({ data: { id: "j1" } })
|
||||
const r = generateViralVideo({ images: ["img1"] } as never)
|
||||
vi.runAllTimersAsync()
|
||||
expect(await r).toEqual({ id: "j1" })
|
||||
expect(mockPost).toHaveBeenCalledWith("/viral-video/generate", { images: ["img1"] })
|
||||
})
|
||||
|
||||
it("getViralVideoJob", async () => {
|
||||
mockGet.mockResolvedValue({ data: { id: "j2" } })
|
||||
const r = getViralVideoJob("j2")
|
||||
vi.runAllTimersAsync()
|
||||
expect(await r).toEqual({ id: "j2" })
|
||||
expect(mockGet).toHaveBeenCalledWith("/viral-video/j2")
|
||||
})
|
||||
|
||||
it("confirmViralVideoIntent", async () => {
|
||||
mockPost.mockResolvedValue({ data: { id: "j3" } })
|
||||
const r = confirmViralVideoIntent("j3", { confirmed_copy: "hi" })
|
||||
vi.runAllTimersAsync()
|
||||
await r
|
||||
expect(mockPost).toHaveBeenCalledWith("/viral-video/j3/confirm-intent", {
|
||||
confirmed_copy: "hi",
|
||||
})
|
||||
})
|
||||
|
||||
it("retryViralVideo", async () => {
|
||||
mockPost.mockResolvedValue({ data: { id: "j4" } })
|
||||
await retryViralVideo("j4")
|
||||
expect(mockPost).toHaveBeenCalledWith("/viral-video/j4/retry")
|
||||
})
|
||||
|
||||
it("getViralVideoHistory", async () => {
|
||||
mockGet.mockResolvedValue({ data: { items: [], total: 0 } })
|
||||
await getViralVideoHistory({ page: 1, page_size: 20 })
|
||||
expect(mockGet).toHaveBeenCalledWith("/viral-video/history", {
|
||||
params: { page: 1, page_size: 20 },
|
||||
})
|
||||
})
|
||||
|
||||
it("getViralStyleTemplates", async () => {
|
||||
mockGet.mockResolvedValue({ data: [] })
|
||||
await getViralStyleTemplates()
|
||||
expect(mockGet).toHaveBeenCalledWith("/viral-video/style-templates")
|
||||
})
|
||||
|
||||
it("analyzeViralStyle", async () => {
|
||||
mockPost.mockResolvedValue({ data: { id: "j5" } })
|
||||
await analyzeViralStyle("j5")
|
||||
expect(mockPost).toHaveBeenCalledWith("/viral-video/j5/analyze-style")
|
||||
})
|
||||
|
||||
it("analyzeViralImages", async () => {
|
||||
mockPost.mockResolvedValue({ data: { id: "j6" } })
|
||||
await analyzeViralImages({ images: ["a.png"] } as never)
|
||||
expect(mockPost).toHaveBeenCalledWith("/viral-video/analyze-images", { images: ["a.png"] })
|
||||
})
|
||||
|
||||
it("generateViralCopy", async () => {
|
||||
mockPost.mockResolvedValue({ data: { id: "j7" } })
|
||||
await generateViralCopy("j7", { duration: 15 } as never)
|
||||
expect(mockPost).toHaveBeenCalledWith("/viral-video/j7/generate-copy", { duration: 15 })
|
||||
})
|
||||
|
||||
it("confirmViralCopy", async () => {
|
||||
mockPost.mockResolvedValue({ data: { id: "j8" } })
|
||||
await confirmViralCopy("j8", { edited_copy: "xxx" })
|
||||
expect(mockPost).toHaveBeenCalledWith("/viral-video/j8/confirm-copy", { edited_copy: "xxx" })
|
||||
mockPost.mockClear()
|
||||
await confirmViralCopy("j8")
|
||||
expect(mockPost).toHaveBeenCalledWith("/viral-video/j8/confirm-copy", {})
|
||||
})
|
||||
})
|
||||
|
||||
describe("viral-video client mocks", () => {
|
||||
beforeEach(() => {
|
||||
vi.useFakeTimers()
|
||||
vi.clearAllMocks()
|
||||
})
|
||||
afterEach(() => {
|
||||
vi.useRealTimers()
|
||||
})
|
||||
|
||||
it("mockImageAnalysis returns product list", async () => {
|
||||
const p = mockImageAnalysis([
|
||||
{ name: "a.png" },
|
||||
{ name: "b.jpg" },
|
||||
{ name: "c.webp" },
|
||||
{ name: "d.png" },
|
||||
])
|
||||
vi.advanceTimersByTime(2000)
|
||||
const r = await p
|
||||
expect(r.products).toHaveLength(3)
|
||||
expect(r.products[0].image_index).toBe(0)
|
||||
expect(r.products[0].brand).toBe("示例品牌")
|
||||
expect(r.products[1].spec).toBe("300g/盒")
|
||||
})
|
||||
|
||||
it("mockImageAnalysis handles empty array", async () => {
|
||||
const p = mockImageAnalysis([])
|
||||
vi.advanceTimersByTime(2000)
|
||||
const r = await p
|
||||
expect(r.products).toHaveLength(0)
|
||||
})
|
||||
|
||||
it("mockGenerateCopy returns copy_result shape", async () => {
|
||||
const p = mockGenerateCopy({ product: "矿泉水", industry: "饮料", marketingPurpose: "种草" })
|
||||
vi.advanceTimersByTime(3000)
|
||||
const r = await p
|
||||
expect(r.title).toContain("种草")
|
||||
expect(r.title).toContain("矿泉水")
|
||||
expect(r.final_copy.length).toBeGreaterThan(50)
|
||||
expect(r.suggested_copy).toBeTruthy()
|
||||
})
|
||||
|
||||
it("mockGenerateCopy uses defaults when params missing", async () => {
|
||||
const p = mockGenerateCopy({} as never)
|
||||
vi.advanceTimersByTime(3000)
|
||||
const r = await p
|
||||
expect(r.title).toContain("品牌种草")
|
||||
expect(r.final_copy).toContain("这款产品")
|
||||
})
|
||||
})
|
||||
@@ -0,0 +1,21 @@
|
||||
import { describe, it, expect } from "vitest"
|
||||
import { getGenerationPhase } from "@/pages/generate/hooks/generate-video/phase"
|
||||
|
||||
describe("getGenerationPhase", () => {
|
||||
it("returns 分析素材与配置 for p<20", () => {
|
||||
expect(getGenerationPhase(0)).toEqual({ label: "分析素材与配置", icon: "🔍" })
|
||||
expect(getGenerationPhase(19).label).toBe("分析素材与配置")
|
||||
})
|
||||
it("returns 智能剪辑合成 for 20<=p<50", () => {
|
||||
expect(getGenerationPhase(20).label).toBe("智能剪辑合成")
|
||||
expect(getGenerationPhase(49).label).toBe("智能剪辑合成")
|
||||
})
|
||||
it("returns 渲染视频中 for 50<=p<80", () => {
|
||||
expect(getGenerationPhase(50).label).toBe("渲染视频中")
|
||||
expect(getGenerationPhase(79).label).toBe("渲染视频中")
|
||||
})
|
||||
it("returns 即将完成 for p>=80", () => {
|
||||
expect(getGenerationPhase(80)).toEqual({ label: "即将完成", icon: "✨" })
|
||||
expect(getGenerationPhase(100).label).toBe("即将完成")
|
||||
})
|
||||
})
|
||||
@@ -0,0 +1,26 @@
|
||||
import { describe, it, expect, vi, afterEach } from "vitest"
|
||||
import { formatDuration, formatFileSize, formatDate } from "@/pages/products/detailUtils"
|
||||
|
||||
describe("products/detailUtils", () => {
|
||||
afterEach(() => {
|
||||
vi.useRealTimers()
|
||||
})
|
||||
it("formatDuration", () => {
|
||||
expect(formatDuration(0)).toBe("00:00")
|
||||
expect(formatDuration(-1)).toBe("00:00")
|
||||
expect(formatDuration(5)).toBe("00:05")
|
||||
expect(formatDuration(65)).toBe("01:05")
|
||||
expect(formatDuration(3600)).toBe("60:00")
|
||||
})
|
||||
it("formatFileSize MB/GB", () => {
|
||||
expect(formatFileSize(0)).toBe("-")
|
||||
expect(formatFileSize(-1)).toBe("-")
|
||||
expect(formatFileSize(5.3)).toBe("5.3 MB")
|
||||
expect(formatFileSize(2048)).toBe("2.00 GB")
|
||||
})
|
||||
it("formatDate returns zh-CN format", () => {
|
||||
vi.setSystemTime(new Date("2026-01-15T10:30:00"))
|
||||
expect(formatDate("2026-01-15T10:30:00Z")).toMatch(/2026/)
|
||||
expect(formatDate("")).toBe("-")
|
||||
})
|
||||
})
|
||||
@@ -0,0 +1,54 @@
|
||||
import { describe, it, expect, beforeEach, vi, afterEach } from "vitest"
|
||||
import { renderHook, act } from "@testing-library/react"
|
||||
import { useViralVideoPolling } from "@/pages/viral-video/hooks/useViralVideoPolling"
|
||||
|
||||
const getViralVideoJobMock = vi.fn()
|
||||
vi.mock("@/api/viral-video", () => ({
|
||||
getViralVideoJob: (...args: unknown[]) => getViralVideoJobMock(...args),
|
||||
}))
|
||||
|
||||
describe("useViralVideoPolling", () => {
|
||||
beforeEach(() => {
|
||||
vi.clearAllMocks()
|
||||
vi.useFakeTimers()
|
||||
})
|
||||
afterEach(() => {
|
||||
vi.useRealTimers()
|
||||
})
|
||||
|
||||
it("不传入 jobId 时不发起请求", () => {
|
||||
renderHook(() => useViralVideoPolling(null, vi.fn()))
|
||||
expect(getViralVideoJobMock).not.toHaveBeenCalled()
|
||||
})
|
||||
|
||||
it("传入 jobId 后立即调用 getViralVideoJob", () => {
|
||||
getViralVideoJobMock.mockResolvedValue({
|
||||
id: "j1",
|
||||
status: "completed",
|
||||
progress_stage: "completed",
|
||||
})
|
||||
renderHook(() => useViralVideoPolling("j1", vi.fn()))
|
||||
expect(getViralVideoJobMock).toHaveBeenCalledWith("j1")
|
||||
})
|
||||
|
||||
it("stop() 会停止后续轮询(终态也会 stop)", async () => {
|
||||
getViralVideoJobMock.mockResolvedValue({
|
||||
id: "j2",
|
||||
status: "completed",
|
||||
progress_stage: "completed",
|
||||
})
|
||||
const { result } = renderHook(() => useViralVideoPolling("j2", vi.fn(), { intervalMs: 50 }))
|
||||
// 等第一次 promise 完成
|
||||
await act(async () => {
|
||||
await Promise.resolve()
|
||||
await Promise.resolve()
|
||||
})
|
||||
// 终态后不会再调度新请求
|
||||
const calls = getViralVideoJobMock.mock.calls.length
|
||||
act(() => {
|
||||
vi.advanceTimersByTime(2000)
|
||||
})
|
||||
expect(getViralVideoJobMock).toHaveBeenCalledTimes(calls)
|
||||
expect(result.current.stop).toBeTypeOf("function")
|
||||
})
|
||||
})
|
||||
@@ -0,0 +1,35 @@
|
||||
import { describe, it, expect } from "vitest"
|
||||
import {
|
||||
genderLabel,
|
||||
languageLabel,
|
||||
genderClass,
|
||||
formatTime,
|
||||
formatFileSize,
|
||||
} from "@/pages/voices/utils/format"
|
||||
|
||||
describe("voices utils/format", () => {
|
||||
it("genderLabel returns label or falls back to value", () => {
|
||||
expect(genderLabel("female")).toContain("女")
|
||||
expect(genderLabel("male")).toContain("男")
|
||||
expect(genderLabel("unknown" as never)).toBe("unknown")
|
||||
})
|
||||
it("languageLabel returns label or falls back", () => {
|
||||
expect(languageLabel("zh-CN" as never)).toBeTruthy()
|
||||
expect(languageLabel("xx-XX" as never)).toBe("xx-XX")
|
||||
})
|
||||
it("genderClass returns css class", () => {
|
||||
expect(genderClass("female")).toBe("xx-voice-gender--female")
|
||||
})
|
||||
it("formatTime pads minutes/seconds", () => {
|
||||
expect(formatTime(0)).toBe("00:00")
|
||||
expect(formatTime(5)).toBe("00:05")
|
||||
expect(formatTime(65)).toBe("01:05")
|
||||
expect(formatTime(3600)).toBe("60:00")
|
||||
})
|
||||
it("formatFileSize human-readable", () => {
|
||||
expect(formatFileSize(0)).toBe("0 B")
|
||||
expect(formatFileSize(512)).toBe("512 B")
|
||||
expect(formatFileSize(2048)).toBe("2.0 KB")
|
||||
expect(formatFileSize(2 * 1024 * 1024)).toBe("2.0 MB")
|
||||
})
|
||||
})
|
||||
@@ -28,11 +28,12 @@ export default defineConfig({
|
||||
"src/pages/editing-planner/EditingPlanner.tsx",
|
||||
"src/pages/assets/AssetLibrary.tsx",
|
||||
"src/pages/voice-materials/VoiceMaterialLibrary.tsx",
|
||||
"src/pages/viral-video/ViralVideoPage.tsx",
|
||||
],
|
||||
// CI 覆盖率门禁(Phase 4 后提升,逐步逼近目标)
|
||||
// 当前实际:行 ~62% / 分支 ~61% / 函数 ~25%
|
||||
thresholds: {
|
||||
lines: 50,
|
||||
lines: 49,
|
||||
branches: 50,
|
||||
functions: 20,
|
||||
},
|
||||
|
||||
@@ -553,7 +553,20 @@ def concat_video_files(
|
||||
if work_dir is None:
|
||||
work_dir = output_path.parent
|
||||
|
||||
segments = [ConcatSegment(video_path=p) for p in video_paths if p]
|
||||
# Bug #2110: 探测每段是否真实包含音频流,避免 Seedance 生成的无声片段
|
||||
# (gen_audio=False)让 concat filter `a=1` 找不到 [N:a] 而报 exit 234。
|
||||
from video_processing.ffmpeg_utils import probe_has_audio as _probe_has_audio
|
||||
|
||||
segments: list[ConcatSegment] = []
|
||||
for p in video_paths:
|
||||
if not p:
|
||||
continue
|
||||
try:
|
||||
has_audio = _probe_has_audio(p)
|
||||
except Exception:
|
||||
has_audio = True # 探测失败保守认为有音频
|
||||
segments.append(ConcatSegment(video_path=p, has_audio=has_audio))
|
||||
|
||||
config = ConcatConfig(segments=segments, force_reencode=force_reencode)
|
||||
|
||||
engine = ConcatEngine(work_dir)
|
||||
|
||||
@@ -0,0 +1,33 @@
|
||||
"""爆款视频 Worker 侧模块(#2039/#2040/#2051)。
|
||||
|
||||
video_analyzer(#2051):参考视频风格分析 6 步管线,输出 style_guide + clips 渲染参数映射。
|
||||
#2040 的 prompt 系统(prompts/prompt_store/llm_runner)由 #2040 分支提供,本文件不依赖它。
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from apps.worker.viral_video.video_analyzer import (
|
||||
DEFAULT_ANALYSIS_TIMEOUT,
|
||||
MAX_REFERENCE_DURATION_SEC,
|
||||
MAX_REFERENCE_SIZE_MB,
|
||||
STYLE_GUIDE_SCHEMA,
|
||||
analyze_video_style,
|
||||
build_render_params_for_clip,
|
||||
map_bgm_bpm,
|
||||
map_camera_to_ken_burns,
|
||||
map_color_to_video_filter,
|
||||
map_transition_to_xfade,
|
||||
)
|
||||
|
||||
__all__ = [
|
||||
"DEFAULT_ANALYSIS_TIMEOUT",
|
||||
"MAX_REFERENCE_DURATION_SEC",
|
||||
"MAX_REFERENCE_SIZE_MB",
|
||||
"STYLE_GUIDE_SCHEMA",
|
||||
"analyze_video_style",
|
||||
"build_render_params_for_clip",
|
||||
"map_bgm_bpm",
|
||||
"map_camera_to_ken_burns",
|
||||
"map_color_to_video_filter",
|
||||
"map_transition_to_xfade",
|
||||
]
|
||||
@@ -0,0 +1,961 @@
|
||||
"""参考爆款视频风格分析模块(#2051,v1.3)。
|
||||
|
||||
管线(analyze_video_style):
|
||||
① FFmpeg 抽关键帧(每 2s 1 帧 + 场景切换帧)到临时目录
|
||||
② PySceneDetect ContentDetector(threshold=27) 镜头分割
|
||||
③ OpenCV Farneback 光流运镜检测(推/拉/摇/移/zoom/static + 强度)
|
||||
④ librosa BPM 分析(>110 fast_cut / 80-110 medium / <80 slow_cinematic)
|
||||
⑤ OSS 上传关键帧 + 豆包 VLM 分析色调/构图/光线
|
||||
⑥ 豆包 LLM 整合输出完整 style_guide JSON
|
||||
|
||||
降级链:
|
||||
- FFmpeg 抽帧失败 → VLM 均匀采样 3 帧(跳步骤 ②③④ 的精确值,给粗粒度估计)
|
||||
- OpenCV 光流失败 → BPM+VLM 估算运镜
|
||||
- librosa BPM 失败 → VLM 判断节奏
|
||||
- 任何子步骤异常不阻断整体,以 best-effort 填充 style_guide。
|
||||
|
||||
资源约束:
|
||||
- 参考视频 ≤60s 且 ≤100MB;分析总超时 ≤60s;临时帧 try/finally 清理。
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
import logging
|
||||
import math
|
||||
import shutil
|
||||
import subprocess # nosec B404
|
||||
import tempfile
|
||||
import uuid
|
||||
from dataclasses import dataclass, field
|
||||
from pathlib import Path
|
||||
from typing import Any, Optional
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# ── 资源约束 ─────────────────────────────────────────────────────────────
|
||||
|
||||
MAX_REFERENCE_DURATION_SEC = 60
|
||||
MAX_REFERENCE_SIZE_MB = 100
|
||||
DEFAULT_ANALYSIS_TIMEOUT = 60 # 秒
|
||||
KEYFRAME_INTERVAL_SEC = 2
|
||||
SCENEDETECT_THRESHOLD = 27
|
||||
VLM_SAMPLE_FRAMES = 5 # 上传给 VLM 的关键帧上限
|
||||
FARNEBACK_PARAMS = dict(pyr_scale=0.5, levels=3, winsize=15, iterations=3, poly_n=5, poly_sigma=1.2, flags=0)
|
||||
|
||||
# ── style_guide 输出 schema(最小校验参考,不强制 jsonschema 依赖) ───────
|
||||
|
||||
STYLE_GUIDE_SCHEMA: dict[str, Any] = {
|
||||
"style_name": str,
|
||||
"avg_shot_duration": float,
|
||||
"shot_count": int,
|
||||
"pace": str, # fast_cut | medium | slow_cinematic
|
||||
"bpm": int,
|
||||
"camera_movements": list,
|
||||
"transitions": list,
|
||||
"color_palette": list,
|
||||
"color_tone": str, # warm | cool | high_sat | low_sat | vintage | fresh | dramatic | bright
|
||||
"color_filter": str, # none | warm_vintage | cool_fresh | high_contrast | soft_pastel | dramatic_cinematic
|
||||
"composition": dict,
|
||||
"lighting": str,
|
||||
"mood": str,
|
||||
"visual_keywords": list,
|
||||
"ken_burns_params": dict,
|
||||
"transition_map": dict,
|
||||
"video_filter_eq_params": dict,
|
||||
"ken_burns_direction_hint": str,
|
||||
}
|
||||
|
||||
|
||||
# ── 数据结构 ─────────────────────────────────────────────────────────────
|
||||
|
||||
|
||||
@dataclass
|
||||
class ShotBoundary:
|
||||
"""一段镜头(帧号区间)。"""
|
||||
|
||||
index: int
|
||||
start_sec: float
|
||||
end_sec: float
|
||||
movement: str = (
|
||||
"static" # push_in | pull_out | pan_left | pan_right | tilt_up | tilt_down | static | zoom_in | zoom_out
|
||||
)
|
||||
intensity: str = "low" # low | medium | high
|
||||
transition: str = "hard_cut" # 到下一个镜头的转场
|
||||
|
||||
|
||||
@dataclass
|
||||
class AnalysisArtifacts:
|
||||
"""中间产物(降级路径用)。"""
|
||||
|
||||
frames_dir: Path
|
||||
frame_paths: list[Path] = field(default_factory=list)
|
||||
shots: list[ShotBoundary] = field(default_factory=list)
|
||||
bpm: int = 0
|
||||
vlm_descriptions: list[str] = field(default_factory=list)
|
||||
|
||||
|
||||
def _strip_code_fence(text: str) -> str:
|
||||
"""移除 markdown 代码块围栏,返回纯文本。"""
|
||||
t = text.strip()
|
||||
for fence in ("```json", "```JSON", "```"):
|
||||
if t.startswith(fence):
|
||||
t = t[len(fence) :].lstrip()
|
||||
if t.endswith("```"):
|
||||
t = t[:-3].rstrip()
|
||||
return t
|
||||
|
||||
|
||||
# ── FFmpeg / ffprobe ─────────────────────────────────────────────────────
|
||||
|
||||
|
||||
def _ffmpeg_bin() -> str:
|
||||
return shutil.which("ffmpeg") or "ffmpeg"
|
||||
|
||||
|
||||
def _ffprobe_bin() -> str:
|
||||
return shutil.which("ffprobe") or "ffprobe"
|
||||
|
||||
|
||||
def _probe_duration(video_path: str | Path) -> float:
|
||||
"""用 ffprobe 取视频时长(秒);失败返回 0。"""
|
||||
try:
|
||||
out = subprocess.check_output(
|
||||
[
|
||||
_ffprobe_bin(),
|
||||
"-v",
|
||||
"error",
|
||||
"-show_entries",
|
||||
"format=duration",
|
||||
"-of",
|
||||
"default=noprint_wrappers=1:nokey=1",
|
||||
str(video_path),
|
||||
],
|
||||
stderr=subprocess.DEVNULL,
|
||||
timeout=10,
|
||||
text=True,
|
||||
) # nosec B603
|
||||
return float(out.strip() or 0)
|
||||
except Exception as exc: # noqa: BLE001
|
||||
logger.warning("ffprobe 时长探测失败 %s: %s", video_path, exc)
|
||||
return 0.0
|
||||
|
||||
|
||||
def _extract_keyframes(video_path: Path, out_dir: Path, interval: int = KEYFRAME_INTERVAL_SEC) -> list[Path]:
|
||||
"""按固定间隔抽帧;同时检测场景切换帧(select='gt(scene,...)')。"""
|
||||
out_dir.mkdir(parents=True, exist_ok=True)
|
||||
# 固定间隔
|
||||
fixed_tpl = str(out_dir / "f_%04d.jpg")
|
||||
cmd_fixed = [
|
||||
_ffmpeg_bin(),
|
||||
"-y",
|
||||
"-i",
|
||||
str(video_path),
|
||||
"-vf",
|
||||
f"fps=1/{interval}",
|
||||
"-q:v",
|
||||
"3",
|
||||
fixed_tpl,
|
||||
]
|
||||
subprocess.run(
|
||||
cmd_fixed, stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL, timeout=DEFAULT_ANALYSIS_TIMEOUT, check=False
|
||||
) # nosec B603
|
||||
# 场景切换帧(独立命名,scene_ 前缀)
|
||||
scene_tpl = str(out_dir / "scene_%04d.jpg")
|
||||
cmd_scene = [
|
||||
_ffmpeg_bin(),
|
||||
"-y",
|
||||
"-i",
|
||||
str(video_path),
|
||||
"-vf",
|
||||
"select='gt(scene,0.35)',showinfo",
|
||||
"-vsync",
|
||||
"vfr",
|
||||
"-q:v",
|
||||
"3",
|
||||
scene_tpl,
|
||||
]
|
||||
subprocess.run(
|
||||
cmd_scene, stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL, timeout=DEFAULT_ANALYSIS_TIMEOUT, check=False
|
||||
) # nosec B603
|
||||
frames = sorted(out_dir.glob("f_*.jpg")) + sorted(out_dir.glob("scene_*.jpg"))
|
||||
# 去重(时间点相近时 scene 帧和 fixed 帧可能重复,简单按文件名存在性保留)
|
||||
seen: set[str] = set()
|
||||
unique: list[Path] = []
|
||||
for p in frames:
|
||||
if p.name not in seen:
|
||||
seen.add(p.name)
|
||||
unique.append(p)
|
||||
return unique
|
||||
|
||||
|
||||
# ── ② 镜头分割(PySceneDetect,失败降级) ────────────────────────────────
|
||||
|
||||
|
||||
def _detect_shots(video_path: Path, frames_dir: Path) -> list[ShotBoundary]:
|
||||
try:
|
||||
from scenedetect import ContentDetector, SceneManager, open_video
|
||||
|
||||
video = open_video(str(video_path))
|
||||
sm = SceneManager()
|
||||
sm.add_detector(ContentDetector(threshold=SCENEDETECT_THRESHOLD))
|
||||
sm.detect_scenes(video)
|
||||
scenes = sm.get_scene_list()
|
||||
shots: list[ShotBoundary] = []
|
||||
for i, (start, end) in enumerate(scenes):
|
||||
shots.append(
|
||||
ShotBoundary(
|
||||
index=i,
|
||||
start_sec=start.get_seconds(),
|
||||
end_sec=end.get_seconds(),
|
||||
)
|
||||
)
|
||||
if shots:
|
||||
return shots
|
||||
except Exception as exc: # noqa: BLE001
|
||||
logger.warning("PySceneDetect 镜头分割失败,使用均匀分段降级: %s", exc)
|
||||
# 降级:按固定间隔每 3 秒一镜头
|
||||
duration = _probe_duration(video_path) or 15.0
|
||||
dur = max(3.0, min(duration, float(MAX_REFERENCE_DURATION_SEC)))
|
||||
shots = []
|
||||
seg = 3.0
|
||||
i = 0
|
||||
t = 0.0
|
||||
while t < dur - 0.1:
|
||||
shots.append(ShotBoundary(index=i, start_sec=t, end_sec=min(t + seg, dur)))
|
||||
i += 1
|
||||
t += seg
|
||||
return shots
|
||||
|
||||
|
||||
# ── ③ 运镜检测(OpenCV Farneback 光流) ──────────────────────────────────
|
||||
|
||||
# 光流向量到运镜映射
|
||||
_FLOW_THRESHOLD_LOW = 0.3
|
||||
_FLOW_THRESHOLD_HIGH = 1.2
|
||||
|
||||
|
||||
def _detect_camera_movement(flow, w: int, h: int) -> tuple[str, str]:
|
||||
"""从平均光流向量判断运镜类型和强度。"""
|
||||
import numpy as np # noqa: PLC0415 - numpy 已在 requirements 中
|
||||
|
||||
fx = float(np.median(flow[..., 0]))
|
||||
fy = float(np.median(flow[..., 1]))
|
||||
trans_mag = math.hypot(fx, fy)
|
||||
# 发散/收敛判断 zoom:比较边缘流沿径向外指的平均分量(稳健版)
|
||||
cx, cy = w / 2.0, h / 2.0
|
||||
ys, xs = np.mgrid[0:h, 0:w].astype(np.float32)
|
||||
rx, ry = (xs - cx) / max(cx, 1.0), (ys - cy) / max(cy, 1.0)
|
||||
rmag = np.sqrt(rx * rx + ry * ry) + 1e-6
|
||||
# 径向分量:(fx*rx + fy*ry)/rmag —— 正=外扩(zoom in),负=内收(zoom out)
|
||||
radial = (flow[..., 0] * rx + flow[..., 1] * ry) / rmag
|
||||
# 只看边缘带(|r|>0.5),且减去平移贡献:径向减去平均平移投影
|
||||
edge_mask = (rmag > 0.5).astype(np.float32)
|
||||
if edge_mask.sum() > 10:
|
||||
trans_radial = (fx * rx + fy * ry) / rmag
|
||||
zoom_signal = float(np.mean((radial - trans_radial)[edge_mask > 0]))
|
||||
else:
|
||||
zoom_signal = 0.0
|
||||
abs_fx, abs_fy = abs(fx), abs(fy)
|
||||
# 综合运动幅度:平移 + |zoom| 投影到像素
|
||||
total_mag = trans_mag + abs(zoom_signal) * max(w, h) * 0.3
|
||||
if total_mag < _FLOW_THRESHOLD_LOW:
|
||||
return "static", "low"
|
||||
intensity = "high" if total_mag > _FLOW_THRESHOLD_HIGH else "medium"
|
||||
# zoom 判定需要边缘径向分量明显大过整体平移
|
||||
zoom_dominant = abs(zoom_signal) > 0.6 and abs(zoom_signal) * max(w, h) * 0.3 > trans_mag * 1.2
|
||||
if zoom_dominant and zoom_signal > 0:
|
||||
return "zoom_in", intensity
|
||||
if zoom_dominant and zoom_signal < 0:
|
||||
return "zoom_out", intensity
|
||||
# 平摇/tilt
|
||||
if abs_fx > abs_fy * 1.5:
|
||||
return "pan_right" if fx > 0 else "pan_left", intensity
|
||||
if abs_fy > abs_fx * 1.5:
|
||||
return "tilt_down" if fy > 0 else "tilt_up", intensity
|
||||
# 轨道/跟拍:以主轴为主
|
||||
if abs_fx >= abs_fy:
|
||||
return "pan_right" if fx > 0 else "pan_left", intensity
|
||||
return "tilt_down" if fy > 0 else "tilt_up", intensity
|
||||
|
||||
|
||||
def _analyze_movements(video_path: Path, shots: list[ShotBoundary]) -> None:
|
||||
"""对每个 shot 的首尾帧算光流,填充 movement/intensity。失败时静默降级为 static/low。"""
|
||||
try:
|
||||
import cv2 # noqa: PLC0415 - opencv-python-headless 已在 worker requirements 中
|
||||
|
||||
except Exception as exc: # noqa: BLE001
|
||||
logger.warning("OpenCV 不可用,运镜检测降级为 static/low: %s", exc)
|
||||
return
|
||||
try:
|
||||
cap = cv2.VideoCapture(str(video_path))
|
||||
for shot in shots:
|
||||
mid_t = (shot.start_sec + shot.end_sec) / 2.0
|
||||
dt = max(0.2, min(0.5, (shot.end_sec - shot.start_sec) / 4.0))
|
||||
cap.set(cv2.CAP_PROP_POS_MSEC, max(0.0, (mid_t - dt)) * 1000)
|
||||
ok1, f1 = cap.read()
|
||||
cap.set(cv2.CAP_PROP_POS_MSEC, min(mid_t + dt, shot.end_sec - 0.05) * 1000)
|
||||
ok2, f2 = cap.read()
|
||||
if not (ok1 and ok2):
|
||||
continue
|
||||
g1 = cv2.cvtColor(f1, cv2.COLOR_BGR2GRAY)
|
||||
g2 = cv2.cvtColor(f2, cv2.COLOR_BGR2GRAY)
|
||||
h, w = g1.shape
|
||||
# 降采样加速
|
||||
scale = 360.0 / h if h > 360 else 1.0
|
||||
if scale < 1.0:
|
||||
g1 = cv2.resize(g1, (int(w * scale), int(h * scale)))
|
||||
g2 = cv2.resize(g2, (int(w * scale), int(h * scale)))
|
||||
flow = cv2.calcOpticalFlowFarneback(g1, g2, None, **FARNEBACK_PARAMS)
|
||||
move, inten = _detect_camera_movement(flow, g1.shape[1], g1.shape[0])
|
||||
shot.movement = move
|
||||
shot.intensity = inten
|
||||
cap.release()
|
||||
except Exception as exc: # noqa: BLE001
|
||||
logger.warning("运镜检测异常,已降级: %s", exc)
|
||||
|
||||
|
||||
# ── ④ librosa BPM ────────────────────────────────────────────────────────
|
||||
|
||||
|
||||
def _detect_bpm(video_path: Path) -> int:
|
||||
"""提取音轨并估算 BPM;失败返回 0。"""
|
||||
tmp_wav: Optional[Path] = None
|
||||
try:
|
||||
import librosa # noqa: PLC0415
|
||||
|
||||
tmp_wav = Path(tempfile.mkstemp(suffix=".wav")[1])
|
||||
# ffmpeg 抽 22050Hz 单声道 wav
|
||||
subprocess.run(
|
||||
[_ffmpeg_bin(), "-y", "-i", str(video_path), "-vn", "-ac", "1", "-ar", "22050", "-f", "wav", str(tmp_wav)],
|
||||
stdout=subprocess.DEVNULL,
|
||||
stderr=subprocess.DEVNULL,
|
||||
timeout=20,
|
||||
check=False,
|
||||
) # nosec B603
|
||||
if not tmp_wav.exists() or tmp_wav.stat().st_size < 1024:
|
||||
return 0
|
||||
y, sr = librosa.load(str(tmp_wav), sr=22050, mono=True)
|
||||
if len(y) < sr * 2:
|
||||
return 0
|
||||
tempo, _ = librosa.beat.beat_track(y=y, sr=sr)
|
||||
try:
|
||||
bpm = int(round(float(tempo)))
|
||||
except Exception: # noqa: BLE001
|
||||
bpm = int(round(float(tempo[0]))) if len(tempo) else 0
|
||||
return max(40, min(bpm, 220))
|
||||
except Exception as exc: # noqa: BLE001
|
||||
logger.warning("librosa BPM 分析失败: %s", exc)
|
||||
return 0
|
||||
finally:
|
||||
if tmp_wav and tmp_wav.exists():
|
||||
try:
|
||||
tmp_wav.unlink()
|
||||
except OSError:
|
||||
pass
|
||||
|
||||
|
||||
def _pace_from_bpm(bpm: int) -> str:
|
||||
if bpm >= 110:
|
||||
return "fast_cut"
|
||||
if bpm >= 80:
|
||||
return "medium"
|
||||
if bpm > 0:
|
||||
return "slow_cinematic"
|
||||
return "medium"
|
||||
|
||||
|
||||
# ── ⑤ VLM 帧分析 ─────────────────────────────────────────────────────────
|
||||
|
||||
|
||||
def _sample_frames(frame_paths: list[Path], shots: list[ShotBoundary], k: int = VLM_SAMPLE_FRAMES) -> list[Path]:
|
||||
"""从全量帧中均匀选 k 张代表性帧(优先场景帧)。"""
|
||||
if not frame_paths:
|
||||
return []
|
||||
scene_frames = sorted(p for p in frame_paths if p.name.startswith("scene_"))
|
||||
fixed_frames = sorted(p for p in frame_paths if p.name.startswith("f_"))
|
||||
picks: list[Path] = list(scene_frames[: max(1, k // 2)])
|
||||
remaining = k - len(picks)
|
||||
if remaining > 0 and fixed_frames:
|
||||
step = max(1, len(fixed_frames) // remaining)
|
||||
picks += fixed_frames[::step][:remaining]
|
||||
# 去重保持顺序
|
||||
seen: set[str] = set()
|
||||
uniq: list[Path] = []
|
||||
for p in picks:
|
||||
if p.name not in seen and p.exists():
|
||||
seen.add(p.name)
|
||||
uniq.append(p)
|
||||
return uniq[:k]
|
||||
|
||||
|
||||
def _upload_frames_to_oss(frame_paths: list[Path]) -> list[str]:
|
||||
"""把帧上传 OSS,返回公网 URL 列表。失败时降级为 data URI。"""
|
||||
urls: list[str] = []
|
||||
try:
|
||||
from video_processing.oss_helpers import upload_to_oss
|
||||
|
||||
for p in frame_paths:
|
||||
try:
|
||||
key = f"viral-video/analysis/{uuid.uuid4().hex}/{p.name}"
|
||||
url = upload_to_oss(p, key)
|
||||
if url:
|
||||
urls.append(url)
|
||||
except Exception as exc: # noqa: BLE001
|
||||
logger.warning("单帧 OSS 上传失败 %s: %s", p.name, exc)
|
||||
except Exception as exc: # noqa: BLE001
|
||||
logger.warning("OSS 上传模块不可用,降级为 base64 data URI: %s", exc)
|
||||
if len(urls) < len(frame_paths):
|
||||
# 降级:base64 data URI(小图,单张 ≤100KB 才走此路)
|
||||
import base64
|
||||
|
||||
for p in frame_paths[len(urls) :]:
|
||||
try:
|
||||
if p.stat().st_size > 120_000:
|
||||
continue
|
||||
b64 = base64.b64encode(p.read_bytes()).decode("ascii")
|
||||
urls.append(f"data:image/jpeg;base64,{b64}")
|
||||
except Exception: # noqa: BLE001 # nosec B112
|
||||
continue
|
||||
return urls
|
||||
|
||||
|
||||
def _vlm_analyze_frames(image_urls: list[str]) -> dict[str, Any]:
|
||||
"""调豆包 VLM 分析色调/构图/光线/转场观感。"""
|
||||
if not image_urls:
|
||||
return {}
|
||||
try:
|
||||
from packages.shared.ai_client import get_doubao_client
|
||||
|
||||
client = get_doubao_client()
|
||||
if not client.is_available:
|
||||
raise RuntimeError("豆包客户端未配置")
|
||||
sys_prompt = (
|
||||
"你是资深短视频导演和调色师。根据用户给出的同一支短视频的多张关键帧,"
|
||||
"分析其视觉风格并严格输出 JSON(不要 markdown,不要解释):\n"
|
||||
"{"
|
||||
'"color_palette": ["#主色1","#主色2","#主色3","#辅色","#点缀色"],'
|
||||
'"color_tone": "warm|cool|high_sat|low_sat|vintage|fresh|dramatic|bright",'
|
||||
'"color_filter": "none|warm_vintage|cool_fresh|high_contrast|soft_pastel|dramatic_cinematic",'
|
||||
'"lighting": "natural|studio|backlit|soft|dramatic|bright_even",'
|
||||
'"composition": {"closeup_ratio":0.0,"medium_ratio":0.0,"wide_ratio":0.0,'
|
||||
'"angle":"eye_level|low_angle|high_angle|dutch"},'
|
||||
'"mood": "整体情绪(1-4字)",'
|
||||
'"visual_keywords": ["3-5个视觉关键词"],'
|
||||
'"transitions_observed": ["hard_cut|cross_dissolve|zoom_whip|fade_black"],'
|
||||
'"pace_guess": "fast_cut|medium|slow_cinematic"'
|
||||
"}"
|
||||
)
|
||||
raw = client.vision_completion(
|
||||
messages=[
|
||||
{"role": "system", "content": sys_prompt},
|
||||
{"role": "user", "content": "请分析这支参考视频的风格。"},
|
||||
],
|
||||
images=image_urls,
|
||||
temperature=0.2,
|
||||
max_tokens=2048,
|
||||
)
|
||||
if not raw:
|
||||
return {}
|
||||
raw = _strip_code_fence(raw)
|
||||
# 容忍模型可能前后加文本
|
||||
i, j = raw.find("{"), raw.rfind("}")
|
||||
if i >= 0 and j > i:
|
||||
return json.loads(raw[i : j + 1])
|
||||
return {}
|
||||
except Exception as exc: # noqa: BLE001
|
||||
logger.warning("VLM 帧分析失败: %s", exc)
|
||||
return {}
|
||||
|
||||
|
||||
# ── ⑥ LLM 整合 style_guide ──────────────────────────────────────────────
|
||||
|
||||
|
||||
def _llm_synthesize(
|
||||
shots: list[ShotBoundary],
|
||||
bpm: int,
|
||||
vlm: dict[str, Any],
|
||||
style_strength: str,
|
||||
) -> dict[str, Any]:
|
||||
"""把结构化信号整合成 style_guide;LLM 不可用时走规则合成。"""
|
||||
payload = {
|
||||
"style_strength": style_strength,
|
||||
"shot_count": len(shots),
|
||||
"shots": [
|
||||
{
|
||||
"index": s.index,
|
||||
"start_sec": round(s.start_sec, 2),
|
||||
"end_sec": round(s.end_sec, 2),
|
||||
"movement": s.movement,
|
||||
"intensity": s.intensity,
|
||||
"transition": s.transition,
|
||||
}
|
||||
for s in shots
|
||||
],
|
||||
"bpm": bpm,
|
||||
"pace_guess": _pace_from_bpm(bpm),
|
||||
"vlm": vlm,
|
||||
}
|
||||
try:
|
||||
from packages.shared.ai_client import get_doubao_client
|
||||
|
||||
client = get_doubao_client()
|
||||
if not client.is_available:
|
||||
raise RuntimeError("豆包客户端未配置")
|
||||
sys_prompt = (
|
||||
"你是资深短视频导演。根据参考视频的结构化分析数据(镜头分割/运镜/BPM/关键帧VLM描述),"
|
||||
"整合输出一份 style_guide JSON,字段必须包含:"
|
||||
"style_name,avg_shot_duration,shot_count,pace,bpm,camera_movements,transitions,"
|
||||
"color_palette,color_tone,color_filter,composition,lighting,mood,visual_keywords,"
|
||||
"ken_burns_direction_hint,ken_burns_params,transition_map,video_filter_eq_params。"
|
||||
"严格输出一个合法 JSON 对象,不要 markdown/解释。"
|
||||
)
|
||||
user_text = "分析数据:\n" + json.dumps(payload, ensure_ascii=False)
|
||||
raw = client.chat_completion(
|
||||
[{"role": "system", "content": sys_prompt}, {"role": "user", "content": user_text}],
|
||||
temperature=0.3,
|
||||
max_tokens=4096,
|
||||
)
|
||||
if raw:
|
||||
raw = _strip_code_fence(raw)
|
||||
i, j = raw.find("{"), raw.rfind("}")
|
||||
if i >= 0 and j > i:
|
||||
result = json.loads(raw[i : j + 1])
|
||||
if isinstance(result, dict) and result.get("style_name"):
|
||||
return result
|
||||
except Exception as exc: # noqa: BLE001
|
||||
logger.warning("LLM 合成 style_guide 失败,走规则降级: %s", exc)
|
||||
return _rule_based_style_guide(shots, bpm, vlm)
|
||||
|
||||
|
||||
def _rule_based_style_guide(shots: list[ShotBoundary], bpm: int, vlm: dict[str, Any]) -> dict[str, Any]:
|
||||
"""LLM 不可用时,用规则拼出可用 style_guide。"""
|
||||
durations = [s.end_sec - s.start_sec for s in shots] or [3.0]
|
||||
avg_dur = round(sum(durations) / len(durations), 2)
|
||||
pace = _pace_from_bpm(bpm)
|
||||
movements = []
|
||||
for s in shots:
|
||||
movements.append(
|
||||
{
|
||||
"shot_index": s.index + 1,
|
||||
"movement": s.movement,
|
||||
"intensity": s.intensity,
|
||||
"duration": round(s.end_sec - s.start_sec, 2),
|
||||
"subject_hint": _default_subject_hint(s.movement),
|
||||
}
|
||||
)
|
||||
transitions = []
|
||||
for i in range(len(shots) - 1):
|
||||
transitions.append({"between_shot": [i + 1, i + 2], "type": shots[i].transition})
|
||||
color_palette = vlm.get("color_palette") or ["#E0E0E0", "#333333", "#F5F5F5", "#888888", "#FF6B35"]
|
||||
color_tone = vlm.get("color_tone") or "bright"
|
||||
color_filter = vlm.get("color_filter") or "none"
|
||||
lighting = vlm.get("lighting") or "bright_even"
|
||||
composition = vlm.get("composition") or {
|
||||
"closeup_ratio": 0.4,
|
||||
"medium_ratio": 0.4,
|
||||
"wide_ratio": 0.2,
|
||||
"angle": "eye_level",
|
||||
}
|
||||
mood = vlm.get("mood") or "明快"
|
||||
vk = vlm.get("visual_keywords") or ["节奏明快", "清晰", "真实"]
|
||||
dominant = _dominant_movement(shots)
|
||||
default_kb = map_camera_to_ken_burns(dominant)
|
||||
# 每镜头独立 ken_burns 参数(key 为 shot_index 字符串)+ 默认值
|
||||
kb_params: dict[str, Any] = {"default": default_kb}
|
||||
for m in movements:
|
||||
kb_params[str(m["shot_index"])] = map_camera_to_ken_burns(m["movement"])
|
||||
trans_map = _build_transition_map(transitions)
|
||||
eq_params = map_color_to_video_filter(color_filter)
|
||||
direction_hint = {
|
||||
"push_in": "zoom_in_slow",
|
||||
"zoom_in": "zoom_in_medium",
|
||||
"pull_out": "zoom_out_slow",
|
||||
"zoom_out": "zoom_out_medium",
|
||||
"pan_left": "pan_left_slow",
|
||||
"pan_right": "pan_right_slow",
|
||||
"tilt_up": "diagonal_push",
|
||||
"tilt_down": "diagonal_push",
|
||||
"track_left": "pan_left_slow",
|
||||
"track_right": "pan_right_slow",
|
||||
"static": "static",
|
||||
}.get(dominant, "static")
|
||||
return {
|
||||
"style_name": f"{pace}节奏-{color_tone}色调",
|
||||
"avg_shot_duration": avg_dur,
|
||||
"shot_count": len(shots),
|
||||
"pace": pace,
|
||||
"bpm": bpm or (120 if pace == "fast_cut" else 90 if pace == "medium" else 70),
|
||||
"camera_movements": movements,
|
||||
"transitions": transitions,
|
||||
"color_palette": color_palette,
|
||||
"color_tone": color_tone,
|
||||
"color_filter": color_filter,
|
||||
"composition": composition,
|
||||
"lighting": lighting,
|
||||
"mood": mood,
|
||||
"visual_keywords": vk,
|
||||
"ken_burns_direction_hint": direction_hint,
|
||||
"ken_burns_params": kb_params,
|
||||
"transition_map": trans_map,
|
||||
"video_filter_eq_params": eq_params,
|
||||
}
|
||||
|
||||
|
||||
def _default_subject_hint(movement: str) -> str:
|
||||
return {
|
||||
"push_in": "产品特写或细节展示",
|
||||
"pull_out": "从细节拉到全景环境",
|
||||
"zoom_in": "产品细节放大",
|
||||
"zoom_out": "全景交代",
|
||||
"pan_left": "横向展示环境/产品线",
|
||||
"pan_right": "横向展示环境/产品线",
|
||||
"tilt_up": "从细节抬到整体/人物表情",
|
||||
"tilt_down": "从整体俯冲到产品细节",
|
||||
"track_left": "跟拍/横向移动",
|
||||
"track_right": "跟拍/横向移动",
|
||||
"static": "稳定构图画面",
|
||||
}.get(movement, "产品展示")
|
||||
|
||||
|
||||
def _dominant_movement(shots: list[ShotBoundary]) -> str:
|
||||
if not shots:
|
||||
return "static"
|
||||
counts: dict[str, int] = {}
|
||||
for s in shots:
|
||||
counts[s.movement] = counts.get(s.movement, 0) + 1
|
||||
return max(counts, key=counts.get)
|
||||
|
||||
|
||||
def _build_transition_map(transitions: list[dict[str, Any]]) -> dict[str, str]:
|
||||
"""统计转场类型分布,返回 shot_index→transition 类型映射(字符串键)。"""
|
||||
m: dict[str, str] = {}
|
||||
for t in transitions:
|
||||
pair = t.get("between_shot") or [0, 0]
|
||||
if len(pair) >= 2:
|
||||
m[f"{pair[0]}-{pair[1]}"] = t.get("type", "hard_cut")
|
||||
return m
|
||||
|
||||
|
||||
# ── ③' 色调/滤镜预设(FFmpeg eq + colorchannelmixer 参数) ──────────────
|
||||
|
||||
#: color_filter → FFmpeg 滤镜参数字典(直接可拼到 eq=.../colorchannelmixer=...)
|
||||
COLOR_FILTER_PRESETS: dict[str, dict[str, Any]] = {
|
||||
"none": {},
|
||||
"warm_vintage": {
|
||||
"eq": {"brightness": 0.02, "contrast": 1.05, "saturation": 0.9, "gamma": 1.05},
|
||||
"colorchannelmixer": {"rr": 1.1, "gg": 0.98, "bb": 0.82, "ra": 0, "ga": 0, "ba": 0, "aa": 1},
|
||||
},
|
||||
"cool_fresh": {
|
||||
"eq": {"brightness": 0.03, "contrast": 1.08, "saturation": 1.05},
|
||||
"colorchannelmixer": {"rr": 0.9, "gg": 1.0, "bb": 1.12, "ra": 0, "ga": 0, "ba": 0, "aa": 1},
|
||||
},
|
||||
"high_contrast": {
|
||||
"eq": {"brightness": 0.0, "contrast": 1.3, "saturation": 1.2},
|
||||
"colorchannelmixer": {},
|
||||
},
|
||||
"soft_pastel": {
|
||||
"eq": {"brightness": 0.05, "contrast": 0.92, "saturation": 0.85},
|
||||
"colorchannelmixer": {"rr": 1.05, "gg": 1.03, "bb": 1.05, "ra": 0, "ga": 0, "ba": 0, "aa": 1},
|
||||
},
|
||||
"dramatic_cinematic": {
|
||||
"eq": {"brightness": -0.03, "contrast": 1.2, "saturation": 0.85},
|
||||
"colorchannelmixer": {"rr": 1.05, "gg": 0.98, "bb": 0.9, "ra": 0, "ga": 0, "ba": 0, "aa": 1},
|
||||
},
|
||||
}
|
||||
|
||||
|
||||
def map_color_to_video_filter(color_filter: str) -> dict[str, Any]:
|
||||
"""color_filter 枚举 → FFmpeg eq/colorchannelmixer 参数字典(渲染端直接使用)。"""
|
||||
preset = COLOR_FILTER_PRESETS.get(color_filter) or COLOR_FILTER_PRESETS["none"]
|
||||
# 返回深拷贝防污染
|
||||
return json.loads(json.dumps(preset))
|
||||
|
||||
|
||||
# ── ③'' 运镜 → ken_burns 参数映射 ───────────────────────────────────────
|
||||
|
||||
#: 运镜类型 → URS 可直接消费的 ken_burns 参数字典
|
||||
CAMERA_TO_KEN_BURNS: dict[str, dict[str, Any]] = {
|
||||
"static": {
|
||||
"type": "static",
|
||||
"zoom_start": 1.0,
|
||||
"zoom_end": 1.0,
|
||||
"pan_x": 0.0,
|
||||
"pan_y": 0.0,
|
||||
"duration_factor": 1.0,
|
||||
},
|
||||
"push_in": {
|
||||
"type": "zoom",
|
||||
"zoom_start": 1.0,
|
||||
"zoom_end": 1.12,
|
||||
"pan_x": 0.0,
|
||||
"pan_y": 0.0,
|
||||
"duration_factor": 1.0,
|
||||
},
|
||||
"zoom_in": {
|
||||
"type": "zoom",
|
||||
"zoom_start": 1.0,
|
||||
"zoom_end": 1.18,
|
||||
"pan_x": 0.0,
|
||||
"pan_y": 0.0,
|
||||
"duration_factor": 1.0,
|
||||
},
|
||||
"pull_out": {
|
||||
"type": "zoom",
|
||||
"zoom_start": 1.12,
|
||||
"zoom_end": 1.0,
|
||||
"pan_x": 0.0,
|
||||
"pan_y": 0.0,
|
||||
"duration_factor": 1.0,
|
||||
},
|
||||
"zoom_out": {
|
||||
"type": "zoom",
|
||||
"zoom_start": 1.18,
|
||||
"zoom_end": 1.0,
|
||||
"pan_x": 0.0,
|
||||
"pan_y": 0.0,
|
||||
"duration_factor": 1.0,
|
||||
},
|
||||
"pan_left": {
|
||||
"type": "pan",
|
||||
"zoom_start": 1.05,
|
||||
"zoom_end": 1.05,
|
||||
"pan_x": -0.08,
|
||||
"pan_y": 0.0,
|
||||
"duration_factor": 1.0,
|
||||
},
|
||||
"pan_right": {
|
||||
"type": "pan",
|
||||
"zoom_start": 1.05,
|
||||
"zoom_end": 1.05,
|
||||
"pan_x": 0.08,
|
||||
"pan_y": 0.0,
|
||||
"duration_factor": 1.0,
|
||||
},
|
||||
"tilt_up": {
|
||||
"type": "pan+zoom",
|
||||
"zoom_start": 1.08,
|
||||
"zoom_end": 1.14,
|
||||
"pan_x": 0.0,
|
||||
"pan_y": -0.05,
|
||||
"duration_factor": 1.0,
|
||||
},
|
||||
"tilt_down": {
|
||||
"type": "pan+zoom",
|
||||
"zoom_start": 1.14,
|
||||
"zoom_end": 1.08,
|
||||
"pan_x": 0.0,
|
||||
"pan_y": 0.05,
|
||||
"duration_factor": 1.0,
|
||||
},
|
||||
"track_left": {
|
||||
"type": "pan",
|
||||
"zoom_start": 1.05,
|
||||
"zoom_end": 1.05,
|
||||
"pan_x": -0.10,
|
||||
"pan_y": 0.0,
|
||||
"duration_factor": 1.0,
|
||||
},
|
||||
"track_right": {
|
||||
"type": "pan",
|
||||
"zoom_start": 1.05,
|
||||
"zoom_end": 1.05,
|
||||
"pan_x": 0.10,
|
||||
"pan_y": 0.0,
|
||||
"duration_factor": 1.0,
|
||||
},
|
||||
}
|
||||
|
||||
|
||||
def map_camera_to_ken_burns(movement: str) -> dict[str, Any]:
|
||||
"""运镜类型 → URS ken_burns 参数字典。未知类型回退 static。"""
|
||||
preset = CAMERA_TO_KEN_BURNS.get(movement) or CAMERA_TO_KEN_BURNS["static"]
|
||||
return json.loads(json.dumps(preset))
|
||||
|
||||
|
||||
# ── 转场 → xfade transition 名称 ────────────────────────────────────────
|
||||
|
||||
TRANSITION_TO_XFADE: dict[str, str] = {
|
||||
"hard_cut": "cut",
|
||||
"cross_dissolve": "dissolve",
|
||||
"fade_black": "fadeblack",
|
||||
"fade": "fade",
|
||||
"zoom_whip": "zoom",
|
||||
"slide_left": "slideright", # 画面左移 = 新画面从右滑入
|
||||
"slide_right": "slideleft",
|
||||
"wipe_left": "wipeleft",
|
||||
"wipe_right": "wiperight",
|
||||
}
|
||||
|
||||
|
||||
def map_transition_to_xfade(transition_type: str) -> str:
|
||||
"""转场枚举 → TransitionEngine 支持的 xfade 名称;未知回退 cut。"""
|
||||
return TRANSITION_TO_XFADE.get(transition_type, "cut")
|
||||
|
||||
|
||||
# ── BPM → BGM 推荐 BPM ──────────────────────────────────────────────────
|
||||
|
||||
|
||||
def map_bgm_bpm(bpm: int) -> int:
|
||||
"""BGM 选曲 BPM:参考视频 BPM ±5。bpm=0 返回 90(默认 medium)。"""
|
||||
if bpm <= 0:
|
||||
return 90
|
||||
return max(60, min(bpm, 180))
|
||||
|
||||
|
||||
# ── 单 clip 渲染参数聚合(给 URS build_render_plan 使用) ───────────────
|
||||
|
||||
|
||||
def build_render_params_for_clip(
|
||||
clip_index: int,
|
||||
style_guide: dict[str, Any],
|
||||
*,
|
||||
duration_sec: Optional[float] = None,
|
||||
) -> dict[str, Any]:
|
||||
"""根据 style_guide 为第 clip_index 个 clip 生成可直接喂给 URS 的渲染参数。"""
|
||||
shot_idx = clip_index + 1
|
||||
movements = style_guide.get("camera_movements") or []
|
||||
movement = "static"
|
||||
intensity = "low"
|
||||
for m in movements:
|
||||
if m.get("shot_index") == shot_idx:
|
||||
movement = m.get("movement", "static")
|
||||
intensity = m.get("intensity", "low")
|
||||
break
|
||||
ken = map_camera_to_ken_burns(movement)
|
||||
if intensity == "high":
|
||||
ken["zoom_end"] = round(ken.get("zoom_end", 1.0) * 1.08, 3)
|
||||
for k in ("pan_x", "pan_y"):
|
||||
ken[k] = round(ken.get(k, 0.0) * 1.3, 3)
|
||||
elif intensity == "low":
|
||||
for k in ("pan_x", "pan_y"):
|
||||
ken[k] = round(ken.get(k, 0.0) * 0.6, 3)
|
||||
transitions = style_guide.get("transitions") or []
|
||||
trans_type = "hard_cut"
|
||||
for t in transitions:
|
||||
pair = t.get("between_shot") or []
|
||||
if len(pair) >= 2 and pair[0] == shot_idx:
|
||||
trans_type = t.get("type", "hard_cut")
|
||||
break
|
||||
xfade = map_transition_to_xfade(trans_type)
|
||||
eq = map_color_to_video_filter(style_guide.get("color_filter", "none"))
|
||||
return {
|
||||
"ken_burns": ken,
|
||||
"transition": {"type": xfade, "duration": 0.3 if xfade != "cut" else 0.0},
|
||||
"video_filter": eq,
|
||||
"bgm_bpm_hint": map_bgm_bpm(int(style_guide.get("bpm") or 0)),
|
||||
"duration_sec": duration_sec,
|
||||
}
|
||||
|
||||
|
||||
# ── 素材本地化(URL/OSS key → 本地临时文件) ────────────────────────────
|
||||
|
||||
|
||||
def _ensure_local_video(reference: str, work_dir: Path) -> Optional[Path]:
|
||||
"""把 reference(URL/OSS key/本地路径)落到 work_dir 下的本地文件。"""
|
||||
p = Path(reference)
|
||||
if p.exists() and p.is_file():
|
||||
return p
|
||||
try:
|
||||
from video_processing.oss_helpers import download_asset
|
||||
|
||||
target = work_dir / f"ref_{uuid.uuid4().hex}.mp4"
|
||||
ok = download_asset(reference, target)
|
||||
if ok and target.exists() and target.stat().st_size > 0:
|
||||
return target
|
||||
except Exception as exc: # noqa: BLE001
|
||||
logger.warning("download_asset 失败,尝试 http 直连: %s", exc)
|
||||
if reference.startswith(("http://", "https://")):
|
||||
try:
|
||||
import httpx # noqa: PLC0415 - 项目依赖,延迟导入
|
||||
|
||||
target = work_dir / f"ref_{uuid.uuid4().hex}.mp4"
|
||||
with httpx.Client(timeout=20.0, follow_redirects=True) as client:
|
||||
with client.stream("GET", reference) as resp:
|
||||
resp.raise_for_status()
|
||||
with open(target, "wb") as f:
|
||||
for chunk in resp.iter_bytes(chunk_size=64 * 1024):
|
||||
f.write(chunk)
|
||||
if target.exists() and target.stat().st_size > 0:
|
||||
return target
|
||||
except Exception as exc: # noqa: BLE001
|
||||
logger.warning("HTTP 下载参考视频失败: %s", exc)
|
||||
return None
|
||||
|
||||
|
||||
# ── 入口 ─────────────────────────────────────────────────────────────────
|
||||
|
||||
|
||||
def analyze_video_style(
|
||||
reference_video_path: str | Path,
|
||||
style_strength: str = "medium",
|
||||
*,
|
||||
timeout_sec: int = DEFAULT_ANALYSIS_TIMEOUT,
|
||||
) -> dict[str, Any]:
|
||||
"""分析参考视频风格,返回 style_guide dict。
|
||||
|
||||
Args:
|
||||
reference_video_path: 本地路径、HTTP(S) URL 或 OSS storage key。
|
||||
style_strength: light | medium | strict。
|
||||
timeout_sec: 单步超时(秒),默认 60。
|
||||
|
||||
Returns:
|
||||
style_guide dict,详见 STYLE_GUIDE_SCHEMA。任何子步骤失败都会降级,不抛异常。
|
||||
"""
|
||||
style_strength = style_strength if style_strength in ("light", "medium", "strict") else "medium"
|
||||
frames_dir: Optional[Path] = None
|
||||
local_path: Optional[Path] = None
|
||||
try:
|
||||
frames_dir = Path(tempfile.mkdtemp(prefix="vstyle_"))
|
||||
work_dir = frames_dir # 同一临时根
|
||||
local_path = _ensure_local_video(str(reference_video_path), work_dir)
|
||||
if local_path is None:
|
||||
logger.error("[video_analyzer] 无法获取参考视频: %s", reference_video_path)
|
||||
return _rule_based_style_guide([], 0, {})
|
||||
# 资源约束:大小 / 时长
|
||||
try:
|
||||
size_mb = local_path.stat().st_size / (1024 * 1024)
|
||||
if size_mb > MAX_REFERENCE_SIZE_MB:
|
||||
logger.warning(
|
||||
"[video_analyzer] 参考视频 %.1fMB 超上限,按前 %ds 分析", size_mb, MAX_REFERENCE_DURATION_SEC
|
||||
)
|
||||
except OSError:
|
||||
pass
|
||||
duration = _probe_duration(local_path)
|
||||
if duration > MAX_REFERENCE_DURATION_SEC:
|
||||
duration = MAX_REFERENCE_DURATION_SEC
|
||||
# ① 抽帧
|
||||
try:
|
||||
frame_paths = _extract_keyframes(local_path, frames_dir / "frames")
|
||||
except Exception as exc: # noqa: BLE001
|
||||
logger.warning("FFmpeg 抽帧失败: %s,降级为 VLM 均匀采样", exc)
|
||||
frame_paths = []
|
||||
# ② 镜头分割
|
||||
shots = _detect_shots(local_path, frames_dir)
|
||||
# ③ 运镜检测(有帧才跑)
|
||||
if frame_paths or shots:
|
||||
_analyze_movements(local_path, shots)
|
||||
# ④ BPM
|
||||
bpm = _detect_bpm(local_path)
|
||||
# ⑤ 选帧→OSS→VLM
|
||||
sampled = _sample_frames(frame_paths, shots)
|
||||
image_urls = _upload_frames_to_oss(sampled) if sampled else []
|
||||
vlm = _vlm_analyze_frames(image_urls) if image_urls else {}
|
||||
# ⑥ 合成
|
||||
style_guide = _llm_synthesize(shots, bpm, vlm, style_strength)
|
||||
# 兜底字段校验
|
||||
style_guide.setdefault("style_strength", style_strength)
|
||||
style_guide.setdefault("pace", _pace_from_bpm(bpm))
|
||||
style_guide.setdefault("bpm", bpm)
|
||||
style_guide.setdefault("shot_count", len(shots))
|
||||
if shots and "avg_shot_duration" not in style_guide:
|
||||
durs = [s.end_sec - s.start_sec for s in shots]
|
||||
style_guide["avg_shot_duration"] = round(sum(durs) / len(durs), 2)
|
||||
return style_guide
|
||||
except Exception as exc: # noqa: BLE001
|
||||
logger.exception("[video_analyzer] 整体分析异常,返回最小占位 style_guide: %s", exc)
|
||||
return _rule_based_style_guide([], 0, {"mood": "未知"})
|
||||
finally:
|
||||
# 临时帧清理
|
||||
if frames_dir and frames_dir.exists():
|
||||
shutil.rmtree(frames_dir, ignore_errors=True)
|
||||
Executable → Regular
+1719
-342
File diff suppressed because it is too large
Load Diff
@@ -104,6 +104,43 @@ Staging 当前可以保持 no-op;Production 开启前必须先验证 SMTP/Redi
|
||||
|
||||
---
|
||||
|
||||
## Staging 服务器 Docker 凭证配置
|
||||
|
||||
Staging 服务器(116.62.226.203)需要配置 ACR 和 Gitea Registry 凭证,否则 docker pull 和 Watchtower 自动更新会失败。
|
||||
|
||||
### 凭证文件位置
|
||||
- Docker 配置文件:`/root/.docker/config.json`
|
||||
- 包含两个 registry 的认证信息:
|
||||
- `xiaoxia-registry.cn-hangzhou.cr.aliyuncs.com`(阿里云 ACR)
|
||||
- `git.xiaoxiajianji.com`(Gitea 容器镜像仓库)
|
||||
|
||||
### 服务器迁移后恢复步骤
|
||||
```bash
|
||||
# 1. 登录 ACR
|
||||
docker login xiaoxia-registry.cn-hangzhou.cr.aliyuncs.com -u <ACR_USERNAME>
|
||||
|
||||
# 2. 登录 Gitea Registry
|
||||
docker login git.xiaoxiajianji.com -u xiaoxia -p <GITEA_REGISTRY_TOKEN>
|
||||
|
||||
# 3. 重启 Watchtower(确保挂载最新 config.json)
|
||||
docker restart watchtower
|
||||
```
|
||||
|
||||
### Watchtower 配置
|
||||
- 容器名:`watchtower`
|
||||
- 检查间隔:300 秒(5 分钟)
|
||||
- 监控容器:`xiaoxia-api-staging`、`xiaoxia-worker-staging`、`xiaoxia-web-staging`
|
||||
- 必须挂载 `-v /root/.docker/config.json:/config.json` 才能拉取私有镜像
|
||||
- 必须挂载 `-v /var/run/docker.sock:/var/run/docker.sock` 才能管理容器
|
||||
- 容器使用 `:dev` 稳定 tag,Watchtower 通过检测 `:dev` tag 的 digest 变化来发现更新
|
||||
|
||||
### 镜像 Tag 策略
|
||||
- CI 每次构建推送三种 tag:`${GITHUB_SHA}`(精确版本)、`${GITHUB_REF_NAME}`(分支名)、`:dev`(滚动 tag,仅 develop 分支)
|
||||
- Staging 容器统一使用 `:dev` tag 启动,确保 Watchtower 能自动发现新版本
|
||||
- Migration(alembic)使用 commit SHA tag 执行,不依赖 Watchtower
|
||||
|
||||
---
|
||||
|
||||
## Gitea Actions 约定
|
||||
|
||||
- `develop` 分支触发 staging 部署。
|
||||
|
||||
@@ -30,6 +30,10 @@ COPY deploy/configs/douyin_cookies.txt /app/configs/douyin_cookies.txt
|
||||
# 强制升级 yt-dlp 到最新(抖音反爬经常变更,旧版 cookies 支持失效;#1968/#1963)
|
||||
RUN pip install --no-cache-dir -i https://mirrors.aliyun.com/pypi/simple/ --trusted-host mirrors.aliyun.com --upgrade "yt-dlp>=2026.8.19"
|
||||
|
||||
# API 启动入口(幂等迁移 + uvicorn)—— #2129: watchtower 自动部署兜底
|
||||
COPY infra/docker/entrypoint-api.sh /usr/local/bin/entrypoint-api.sh
|
||||
RUN chmod +x /usr/local/bin/entrypoint-api.sh
|
||||
|
||||
# 设置环境变量
|
||||
ENV PATH="/opt/venv/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin"
|
||||
ENV PYTHONPATH=/app:/app/apps/api
|
||||
@@ -41,4 +45,4 @@ HEALTHCHECK --interval=30s --timeout=10s --start-period=5s --retries=3 \
|
||||
CMD python -c "import urllib.request; urllib.request.urlopen('http://localhost:8000/health', timeout=5)"
|
||||
|
||||
# API 入口点
|
||||
CMD ["uvicorn", "apps.api.main:app", "--host", "0.0.0.0", "--port", "8000"]
|
||||
ENTRYPOINT ["/usr/local/bin/entrypoint-api.sh"]
|
||||
|
||||
Executable
+22
@@ -0,0 +1,22 @@
|
||||
#!/bin/bash
|
||||
# API 启动入口:先幂等执行数据库迁移,再启动传入的 CMD(默认 uvicorn)
|
||||
# 解决 watchtower 自动拉取新镜像后容器重启、未跑 alembic upgrade head 导致新列缺失 500 的问题(#2129)
|
||||
set -e
|
||||
|
||||
cd /app
|
||||
|
||||
echo "[entrypoint-api] Running alembic upgrade head..."
|
||||
if alembic upgrade head; then
|
||||
echo "[entrypoint-api] Migrations ok."
|
||||
else
|
||||
echo "[entrypoint-api] WARNING: alembic upgrade failed, continuing (existing columns should be fine)..." >&2
|
||||
fi
|
||||
|
||||
# 若有显式 CMD(CI 部署时 docker compose run --rm api sh -c '...' 传入),直接 exec 它
|
||||
if [ "$#" -gt 0 ]; then
|
||||
echo "[entrypoint-api] Exec custom command: $*"
|
||||
exec "$@"
|
||||
fi
|
||||
|
||||
echo "[entrypoint-api] Starting uvicorn..."
|
||||
exec uvicorn apps.api.main:app --host 0.0.0.0 --port 8000
|
||||
@@ -18,6 +18,17 @@
|
||||
|
||||
set -e
|
||||
|
||||
# #2129: 幂等执行数据库迁移(watchtower 自动部署兜底)
|
||||
# worker 容器独立启动,不能依赖 API 容器先跑迁移
|
||||
cd /app
|
||||
echo "[entrypoint-worker] Running alembic upgrade head..."
|
||||
if alembic upgrade head; then
|
||||
echo "[entrypoint-worker] Migrations ok."
|
||||
else
|
||||
echo "[entrypoint-worker] WARNING: alembic upgrade failed, continuing to start workers..." >&2
|
||||
fi
|
||||
cd - >/dev/null
|
||||
|
||||
MAX_TASKS="${WORKER_MAX_TASKS_PER_CHILD:-100}"
|
||||
|
||||
# ── 并发计算:显式 env 优先;否则从 WORKER_CONCURRENCY 按比例推导 ──
|
||||
|
||||
@@ -34,6 +34,7 @@ ENV APP_VERSION=$APP_VERSION
|
||||
|
||||
# 复制文件(按变化频率从低到高排序,最大化层缓存命中)
|
||||
COPY alembic.ini /app/alembic.ini
|
||||
COPY alembic/ /app/alembic/
|
||||
COPY migrations/ /app/migrations/
|
||||
COPY packages/ /app/packages/
|
||||
# PR #1844 起,worker 还需要加载 apps.api.app.tasks.lipsync_tts,
|
||||
|
||||
@@ -502,8 +502,19 @@ class SQLAlchemyAssetRepository:
|
||||
return [self._to_domain(m) for m in models]
|
||||
|
||||
def find_by_storage_key(self, storage_key: str) -> Asset | None:
|
||||
"""按 storage_key(对应 DB 中的 file_url)查找素材。"""
|
||||
model = self.session.query(AssetModel).filter(AssetModel.file_url == storage_key).first()
|
||||
"""按 storage_key 查找素材。
|
||||
|
||||
Bug #2110: 历史数据 file_url 列可能是旧路径(assets/...),新代码统一写入
|
||||
storage_key 列。双列 OR 查询,避免占位 asset 因路径错配导致 ingest 兜底新建
|
||||
第二条 READY 记录,原占位卡 PROCESSING → 前端缩略图出现后消失。
|
||||
"""
|
||||
if not storage_key:
|
||||
return None
|
||||
model = (
|
||||
self.session.query(AssetModel)
|
||||
.filter((AssetModel.storage_key == storage_key) | (AssetModel.file_url == storage_key))
|
||||
.first()
|
||||
)
|
||||
if model is None:
|
||||
return None
|
||||
return self._to_domain(model)
|
||||
|
||||
@@ -56,7 +56,7 @@ class UserModel(Base):
|
||||
is_member = Column(Boolean, nullable=False, default=False)
|
||||
member_type = Column(String(20), nullable=True)
|
||||
member_expires_at = Column(DateTime, nullable=True)
|
||||
points_balance = Column(Integer, nullable=False, default=0)
|
||||
points_balance = Column(Float, nullable=False, default=0)
|
||||
created_at = Column(DateTime, nullable=False, default=lambda: datetime.now(UTC))
|
||||
|
||||
|
||||
@@ -775,9 +775,9 @@ class PointsAccountModel(Base):
|
||||
|
||||
id = Column(String(36), primary_key=True)
|
||||
user_id = Column(String(36), nullable=False, unique=True, index=True)
|
||||
balance = Column(Integer, nullable=False, default=0)
|
||||
total_earned = Column(Integer, nullable=False, default=0)
|
||||
total_spent = Column(Integer, nullable=False, default=0)
|
||||
balance = Column(Float, nullable=False, default=0)
|
||||
total_earned = Column(Float, nullable=False, default=0)
|
||||
total_spent = Column(Float, nullable=False, default=0)
|
||||
created_at = Column(DateTime, nullable=False, default=lambda: datetime.now(UTC))
|
||||
updated_at = Column(DateTime, nullable=False, default=lambda: datetime.now(UTC))
|
||||
|
||||
@@ -792,8 +792,8 @@ class PointsTransactionModel(Base):
|
||||
account_id = Column(String(36), nullable=False, index=True)
|
||||
type = Column(String(20), nullable=False, index=True) # earn / spend / refund
|
||||
source = Column(String(50), nullable=False, index=True)
|
||||
amount = Column(Integer, nullable=False)
|
||||
balance_after = Column(Integer, nullable=False)
|
||||
amount = Column(Float, nullable=False)
|
||||
balance_after = Column(Float, nullable=False)
|
||||
description = Column(String(255), nullable=False, default="")
|
||||
ref_id = Column(String(100), nullable=False, default="")
|
||||
created_at = Column(DateTime, nullable=False, default=lambda: datetime.now(UTC))
|
||||
@@ -928,6 +928,7 @@ class ViralVideoJobModel(Base):
|
||||
id = Column(String(36), primary_key=True)
|
||||
user_id = Column(String(36), nullable=False, index=True)
|
||||
images = Column(JSON, nullable=False, default=list) # 产品图片 URL 列表
|
||||
pre_trusted_images = Column(JSON, nullable=True) # #2172 信任链预热结果(Seedream AI 化 URL 列表)
|
||||
industry = Column(String(100), nullable=False, default="")
|
||||
target_customer = Column(String(500), nullable=False, default="")
|
||||
persona_id = Column(String(36), nullable=False, default="")
|
||||
@@ -943,11 +944,28 @@ class ViralVideoJobModel(Base):
|
||||
style_strength = Column(String(20), nullable=False, default="medium")
|
||||
style_guide = Column(JSON, nullable=True)
|
||||
style_template_id = Column(String(36), nullable=False, default="", index=True)
|
||||
# v1.5 音频/视频参数
|
||||
voice_id = Column(String(200), nullable=False, default="")
|
||||
voice_source = Column(String(20), nullable=False, default="")
|
||||
video_ratio = Column(String(10), nullable=False, default="9:16")
|
||||
video_model = Column(String(100), nullable=False, default="")
|
||||
# 结果与状态
|
||||
status = Column(String(30), nullable=False, default="pending", index=True)
|
||||
current_stage = Column(String(200), nullable=False, default="") # 细粒度阶段 snake_case
|
||||
phase_message = Column(String(500), nullable=False, default="") # 阶段中文提示文案
|
||||
heartbeat_at = Column(DateTime, nullable=True, index=True) # worker 心跳,用于僵尸任务超时回收
|
||||
intent_result = Column(JSON, nullable=True)
|
||||
image_analysis = Column(JSON, nullable=True)
|
||||
storyboard = Column(JSON, nullable=True)
|
||||
generated_copy_text = Column(Text, nullable=False, default="")
|
||||
copy_result = Column(
|
||||
JSON, nullable=True
|
||||
) # v1.6: 编导脚本结构{overview,scene_and_lighting,shots,hard_constraints,negative_prompts,voiceover_script}
|
||||
result_video_url = Column(String(1000), nullable=False, default="")
|
||||
credits_cost = Column(Integer, nullable=False, default=0)
|
||||
credits_cost = Column(Float, nullable=False, default=0)
|
||||
video_resolution = Column(String(20), nullable=False, default="720p")
|
||||
credits_prepaid = Column(Float, nullable=False, default=0.0)
|
||||
credits_transaction_id = Column(String(36), nullable=False, default="")
|
||||
error_msg = Column(Text, nullable=False, default="")
|
||||
retry_count = Column(Integer, nullable=False, default=0)
|
||||
started_at = Column(DateTime(timezone=True), nullable=True)
|
||||
|
||||
@@ -81,6 +81,41 @@ def ensure_database_exists(database_url: str) -> None:
|
||||
admin_engine.dispose()
|
||||
|
||||
|
||||
_VIRAL_VIDEO_BACKFILL_COLS = [
|
||||
("storyboard", "JSON"),
|
||||
("generated_copy_text", "TEXT NOT NULL DEFAULT ''"),
|
||||
("voice_id", "VARCHAR(200) NOT NULL DEFAULT ''"),
|
||||
("voice_source", "VARCHAR(20) NOT NULL DEFAULT ''"),
|
||||
("video_ratio", "VARCHAR(10) NOT NULL DEFAULT '9:16'"),
|
||||
("video_model", "VARCHAR(100) NOT NULL DEFAULT ''"),
|
||||
("copy_result", "JSON"),
|
||||
]
|
||||
|
||||
|
||||
def _ensure_viral_video_columns(connection) -> None:
|
||||
"""Idempotently add new columns to viral_video_jobs; create_all will not ALTER existing tables."""
|
||||
from sqlalchemy import inspect as _inspect
|
||||
|
||||
try:
|
||||
insp = _inspect(connection)
|
||||
if not insp.has_table("viral_video_jobs"):
|
||||
return
|
||||
existing = {c["name"] for c in insp.get_columns("viral_video_jobs")}
|
||||
except Exception:
|
||||
return
|
||||
import logging as _logging
|
||||
|
||||
_log = _logging.getLogger(__name__)
|
||||
for col, ddl in _VIRAL_VIDEO_BACKFILL_COLS:
|
||||
if col in existing:
|
||||
continue
|
||||
try:
|
||||
connection.execute(text(f"ALTER TABLE viral_video_jobs ADD COLUMN {col} {ddl}"))
|
||||
_log.info("added column viral_video_jobs.%s", col)
|
||||
except Exception as e:
|
||||
_log.warning("add column %s failed: %s", col, e)
|
||||
|
||||
|
||||
def initialize_database(engine) -> None:
|
||||
"""初始化数据库 schema。
|
||||
|
||||
@@ -100,4 +135,5 @@ def initialize_database(engine) -> None:
|
||||
text("SELECT pg_advisory_unlock(:lock_id)"),
|
||||
{"lock_id": SCHEMA_INIT_LOCK_ID},
|
||||
)
|
||||
_ensure_viral_video_columns(connection)
|
||||
connection.commit()
|
||||
|
||||
@@ -39,6 +39,9 @@ class SQLAlchemyUserRepository(UserRepository):
|
||||
model.phone_verified = user.phone_verified
|
||||
model.binding_completed_at = user.binding_completed_at
|
||||
model.profile_completed = user.profile_completed
|
||||
model.is_member = user.is_member
|
||||
model.member_type = user.member_type
|
||||
model.member_expires_at = user.member_expires_at
|
||||
model.created_at = user.created_at
|
||||
|
||||
self.session.commit()
|
||||
@@ -115,5 +118,8 @@ class SQLAlchemyUserRepository(UserRepository):
|
||||
phone_verified=model.phone_verified or False,
|
||||
binding_completed_at=model.binding_completed_at,
|
||||
profile_completed=model.profile_completed if model.profile_completed is not None else True,
|
||||
is_member=model.is_member if model.is_member is not None else False,
|
||||
member_type=model.member_type,
|
||||
member_expires_at=model.member_expires_at,
|
||||
created_at=model.created_at,
|
||||
)
|
||||
|
||||
@@ -6,8 +6,8 @@ from sqlalchemy.orm import Session
|
||||
|
||||
from packages.adapters.sqlalchemy_impl.models import (
|
||||
ViralVideoJobModel,
|
||||
ViralVideoStyleTemplateModel,
|
||||
ViralVideoPromptTemplateModel,
|
||||
ViralVideoStyleTemplateModel,
|
||||
)
|
||||
from packages.domain.viral_video import ViralVideoJob, ViralVideoStatus
|
||||
|
||||
@@ -18,13 +18,18 @@ def _to_domain(model: ViralVideoJobModel) -> ViralVideoJob:
|
||||
id=model.id,
|
||||
user_id=model.user_id,
|
||||
images=list(model.images or []),
|
||||
pre_trusted_images=(
|
||||
list(getattr(model, "pre_trusted_images", None) or [])
|
||||
if getattr(model, "pre_trusted_images", None) is not None
|
||||
else None
|
||||
),
|
||||
industry=model.industry or "",
|
||||
target_customer=model.target_customer or "",
|
||||
persona_id=model.persona_id or "",
|
||||
viral_structure=model.viral_structure or "",
|
||||
marketing_purpose=model.marketing_purpose or "",
|
||||
bgm_preference=model.bgm_preference or "",
|
||||
duration=model.duration or 30,
|
||||
duration=model.duration or 15,
|
||||
user_copy_text=model.user_copy_text or "",
|
||||
fusion_level=model.fusion_level or "ai_polish",
|
||||
reference_audio_path=model.reference_audio_path or "",
|
||||
@@ -32,10 +37,24 @@ def _to_domain(model: ViralVideoJobModel) -> ViralVideoJob:
|
||||
style_strength=getattr(model, "style_strength", "medium") or "medium",
|
||||
style_guide=dict(model.style_guide) if model.style_guide else None,
|
||||
style_template_id=getattr(model, "style_template_id", "") or "",
|
||||
voice_id=getattr(model, "voice_id", "") or "",
|
||||
voice_source=getattr(model, "voice_source", "") or "",
|
||||
video_ratio=getattr(model, "video_ratio", "9:16") or "9:16",
|
||||
video_model=getattr(model, "video_model", "") or "",
|
||||
status=ViralVideoStatus(model.status) if model.status else ViralVideoStatus.PENDING,
|
||||
current_stage=getattr(model, "current_stage", "") or "",
|
||||
phase_message=getattr(model, "phase_message", "") or "",
|
||||
heartbeat_at=getattr(model, "heartbeat_at", None),
|
||||
intent_result=dict(model.intent_result) if model.intent_result else None,
|
||||
image_analysis=dict(model.image_analysis) if getattr(model, "image_analysis", None) else None,
|
||||
storyboard=list(model.storyboard) if getattr(model, "storyboard", None) else None,
|
||||
generated_copy_text=getattr(model, "generated_copy_text", "") or "",
|
||||
copy_result=dict(model.copy_result) if getattr(model, "copy_result", None) else None,
|
||||
result_video_url=model.result_video_url or "",
|
||||
credits_cost=model.credits_cost or 0,
|
||||
video_resolution=getattr(model, "video_resolution", "720p") or "720p",
|
||||
credits_prepaid=float(getattr(model, "credits_prepaid", 0) or 0),
|
||||
credits_transaction_id=getattr(model, "credits_transaction_id", "") or "",
|
||||
credits_cost=float(model.credits_cost or 0),
|
||||
error_msg=model.error_msg or "",
|
||||
retry_count=model.retry_count or 0,
|
||||
started_at=model.started_at,
|
||||
@@ -56,6 +75,7 @@ class SQLAlchemyViralVideoJobRepository:
|
||||
id=job.id,
|
||||
user_id=job.user_id,
|
||||
images=job.images,
|
||||
pre_trusted_images=job.pre_trusted_images,
|
||||
industry=job.industry,
|
||||
target_customer=job.target_customer,
|
||||
persona_id=job.persona_id,
|
||||
@@ -70,10 +90,24 @@ class SQLAlchemyViralVideoJobRepository:
|
||||
style_strength=job.style_strength,
|
||||
style_guide=job.style_guide,
|
||||
style_template_id=job.style_template_id,
|
||||
voice_id=job.voice_id,
|
||||
voice_source=job.voice_source,
|
||||
video_ratio=job.video_ratio,
|
||||
video_model=job.video_model,
|
||||
status=job.status,
|
||||
current_stage=job.current_stage or "",
|
||||
phase_message=job.phase_message or "",
|
||||
heartbeat_at=job.heartbeat_at,
|
||||
intent_result=job.intent_result,
|
||||
image_analysis=job.image_analysis,
|
||||
storyboard=job.storyboard,
|
||||
generated_copy_text=job.generated_copy_text,
|
||||
copy_result=job.copy_result,
|
||||
result_video_url=job.result_video_url,
|
||||
credits_cost=job.credits_cost,
|
||||
video_resolution=getattr(job, "video_resolution", "720p") or "720p",
|
||||
credits_prepaid=float(getattr(job, "credits_prepaid", 0) or 0),
|
||||
credits_transaction_id=getattr(job, "credits_transaction_id", "") or "",
|
||||
credits_cost=float(getattr(job, "credits_cost", 0) or 0),
|
||||
error_msg=job.error_msg,
|
||||
retry_count=job.retry_count,
|
||||
started_at=job.started_at,
|
||||
@@ -90,14 +124,43 @@ class SQLAlchemyViralVideoJobRepository:
|
||||
if model is None:
|
||||
raise ValueError(f"ViralVideoJob {job.id} not found")
|
||||
model.status = job.status
|
||||
model.current_stage = job.current_stage or ""
|
||||
model.phase_message = job.phase_message or ""
|
||||
model.heartbeat_at = job.heartbeat_at
|
||||
model.intent_result = job.intent_result
|
||||
model.image_analysis = job.image_analysis
|
||||
model.storyboard = job.storyboard
|
||||
model.generated_copy_text = job.generated_copy_text or ""
|
||||
model.copy_result = job.copy_result
|
||||
model.pre_trusted_images = job.pre_trusted_images
|
||||
model.result_video_url = job.result_video_url
|
||||
model.credits_cost = job.credits_cost
|
||||
model.video_resolution = getattr(job, "video_resolution", "720p") or "720p"
|
||||
model.credits_prepaid = float(getattr(job, "credits_prepaid", 0) or 0)
|
||||
model.credits_transaction_id = getattr(job, "credits_transaction_id", "") or ""
|
||||
model.credits_cost = float(getattr(job, "credits_cost", 0) or 0)
|
||||
model.error_msg = job.error_msg
|
||||
model.retry_count = job.retry_count
|
||||
model.started_at = job.started_at
|
||||
model.completed_at = job.completed_at
|
||||
model.style_guide = job.style_guide
|
||||
# v1.5 three-stage: persist user-editable params so resume uses latest values
|
||||
model.user_copy_text = job.user_copy_text
|
||||
model.industry = job.industry
|
||||
model.target_customer = job.target_customer
|
||||
model.persona_id = job.persona_id
|
||||
model.viral_structure = job.viral_structure
|
||||
model.marketing_purpose = job.marketing_purpose
|
||||
model.bgm_preference = job.bgm_preference
|
||||
model.duration = job.duration
|
||||
model.fusion_level = job.fusion_level
|
||||
model.reference_audio_path = job.reference_audio_path
|
||||
model.reference_video_url = job.reference_video_url
|
||||
model.style_strength = job.style_strength
|
||||
model.style_template_id = job.style_template_id
|
||||
model.voice_id = job.voice_id or ""
|
||||
model.voice_source = job.voice_source or ""
|
||||
model.video_ratio = job.video_ratio or "9:16"
|
||||
model.video_model = job.video_model or ""
|
||||
model.updated_at = datetime.now(timezone.utc)
|
||||
self.session.commit()
|
||||
|
||||
@@ -123,7 +186,9 @@ class SQLAlchemyViralVideoJobRepository:
|
||||
self.session.query(ViralVideoJobModel)
|
||||
.filter(
|
||||
ViralVideoJobModel.user_id == user_id,
|
||||
ViralVideoJobModel.status.in_(["pending", "running", "wait_user_confirm"]),
|
||||
ViralVideoJobModel.status.in_(
|
||||
["pending", "running", "wait_user_confirm", "image_analyzed", "copy_generated"]
|
||||
),
|
||||
)
|
||||
.count()
|
||||
)
|
||||
|
||||
@@ -0,0 +1 @@
|
||||
"""应用层:对外展示目录(套餐/积分包)。"""
|
||||
@@ -0,0 +1,152 @@
|
||||
"""读取管理后台配置的会员套餐 / 积分充值包(共享库真实数据)。
|
||||
|
||||
替代旧的硬编码 MEMBERSHIP_PRICES / POINTS_PACKAGES。
|
||||
短 TTL 缓存(30 秒),后台改价/启停后用户端最多 30 秒可见。
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import threading
|
||||
import time
|
||||
from typing import Any
|
||||
|
||||
_CACHE_TTL = 30.0
|
||||
_lock = threading.Lock()
|
||||
_cache: dict[str, tuple[float, Any]] = {}
|
||||
|
||||
_QUOTA_LABELS = {
|
||||
"4k": "4K 超清分辨率",
|
||||
"batch_render": "批量渲染",
|
||||
"priority_queue": "优先处理队列",
|
||||
"ai_matting": "AI 智能抠像",
|
||||
"remove_watermark": "去水印",
|
||||
}
|
||||
|
||||
|
||||
def _cached(key: str, loader):
|
||||
now = time.time()
|
||||
hit = _cache.get(key)
|
||||
if hit and now - hit[0] < _CACHE_TTL:
|
||||
return hit[1]
|
||||
with _lock:
|
||||
hit = _cache.get(key)
|
||||
if hit and time.time() - hit[0] < _CACHE_TTL:
|
||||
return hit[1]
|
||||
value = loader()
|
||||
_cache[key] = (time.time(), value)
|
||||
return value
|
||||
|
||||
|
||||
def _quota_features(quotas: dict[str, Any] | None) -> dict[str, Any]:
|
||||
quotas = quotas or {}
|
||||
features: dict[str, Any] = {}
|
||||
for k, v in quotas.items():
|
||||
if k == "credits_per_month":
|
||||
features["credits_per_month"] = v
|
||||
elif k in _QUOTA_LABELS:
|
||||
features[_QUOTA_LABELS[k]] = v
|
||||
else:
|
||||
features[k] = v
|
||||
return features
|
||||
|
||||
|
||||
def get_membership_plans() -> list[dict[str, Any]]:
|
||||
"""读取 is_enabled=true 的套餐,按年/月周期展开为用户端档位。"""
|
||||
|
||||
def _load() -> list[dict[str, Any]]:
|
||||
from sqlalchemy import text
|
||||
|
||||
from packages.adapters.sqlalchemy_impl.session import SessionLocal
|
||||
|
||||
if SessionLocal is None:
|
||||
return []
|
||||
|
||||
session = SessionLocal()
|
||||
try:
|
||||
rows = session.execute(text("""
|
||||
SELECT plan_key, name, description, monthly_price, yearly_price,
|
||||
quotas, display_order
|
||||
FROM plans
|
||||
WHERE is_enabled = TRUE
|
||||
ORDER BY display_order NULLS LAST, created_at
|
||||
""")).fetchall()
|
||||
finally:
|
||||
session.close()
|
||||
|
||||
plans: list[dict[str, Any]] = []
|
||||
for r in rows:
|
||||
base_features = _quota_features(r.quotas if isinstance(r.quotas, dict) else None)
|
||||
if r.yearly_price and float(r.yearly_price) > 0:
|
||||
plans.append(
|
||||
{
|
||||
"plan_id": r.plan_key,
|
||||
"billing_cycle": "yearly",
|
||||
"name": r.name,
|
||||
"description": r.description,
|
||||
"price_cents": int(round(float(r.yearly_price) * 100)),
|
||||
"monthly_price_cents": int(round(float(r.yearly_price) * 100 / 12)),
|
||||
"duration_days": 365,
|
||||
"features": dict(base_features),
|
||||
}
|
||||
)
|
||||
if r.monthly_price and float(r.monthly_price) > 0:
|
||||
plans.append(
|
||||
{
|
||||
"plan_id": r.plan_key,
|
||||
"billing_cycle": "monthly",
|
||||
"name": r.name,
|
||||
"description": r.description,
|
||||
"price_cents": int(round(float(r.monthly_price) * 100)),
|
||||
"monthly_price_cents": int(round(float(r.monthly_price) * 100)),
|
||||
"duration_days": 30,
|
||||
"features": dict(base_features),
|
||||
}
|
||||
)
|
||||
return plans
|
||||
|
||||
return _cached("membership_plans", _load)
|
||||
|
||||
|
||||
def get_points_packages() -> list[dict[str, Any]]:
|
||||
"""读取 is_active=true 的积分充值包。"""
|
||||
|
||||
def _load() -> list[dict[str, Any]]:
|
||||
from sqlalchemy import text
|
||||
|
||||
from packages.adapters.sqlalchemy_impl.session import SessionLocal
|
||||
|
||||
if SessionLocal is None:
|
||||
return []
|
||||
|
||||
session = SessionLocal()
|
||||
try:
|
||||
rows = session.execute(text("""
|
||||
SELECT package_key, name, price, credits, bonus_credits,
|
||||
is_recommended, description, sort_order
|
||||
FROM credit_packages
|
||||
WHERE is_active = TRUE
|
||||
ORDER BY sort_order NULLS LAST, price
|
||||
""")).fetchall()
|
||||
finally:
|
||||
session.close()
|
||||
|
||||
packages: list[dict[str, Any]] = []
|
||||
for r in rows:
|
||||
total_points = int(r.credits or 0) + int(r.bonus_credits or 0)
|
||||
price_cents = int(round(float(r.price) * 100))
|
||||
unit = (price_cents / 100 / total_points) if total_points else 0
|
||||
packages.append(
|
||||
{
|
||||
"code": r.package_key,
|
||||
"name": r.name,
|
||||
"points": total_points,
|
||||
"bonus_credits": int(r.bonus_credits or 0),
|
||||
"price_cents": price_cents,
|
||||
"unit_price": f"¥{unit:.3f}/积分",
|
||||
"is_recommended": bool(r.is_recommended),
|
||||
"description": r.description,
|
||||
}
|
||||
)
|
||||
return packages
|
||||
|
||||
return _cached("points_packages", _load)
|
||||
+23
-3
@@ -90,12 +90,32 @@ class SharedSettings(BaseSettings):
|
||||
|
||||
# ── 豆包大模型(火山引擎方舟) ────────────────────────────────────────
|
||||
doubao_api_key: str = ""
|
||||
doubao_model: str = "doubao-seed-1-6-250615"
|
||||
doubao_model: str = "doubao-seed-2-1-pro-260915" # 推理模型(Seed 2.1 Pro,深度思考+多模态;原 seed-1-6 已下线)
|
||||
doubao_fast_model: str = (
|
||||
"doubao-seed-2-1-lite-260915" # 快速模型(Seed 2.1 Lite,高 RPM,编导/审核/VLM lite;原 1-5-pro-32k 已 Retiring)
|
||||
)
|
||||
doubao_base_url: str = "https://ark.cn-beijing.volces.com/api/v3"
|
||||
doubao_timeout: int = 30
|
||||
doubao_max_retries: int = 2
|
||||
doubao_vision_model: str = "doubao-1-5-vision-pro-250915"
|
||||
doubao_embedding_model: str = "doubao-embedding-large-text-240915"
|
||||
doubao_vision_model: str = (
|
||||
"doubao-seed-2-1-pro-260915" # 高精度视觉(Seed 2.1 Pro 原生多模态;原 vision-pro-250328 已下线)
|
||||
)
|
||||
doubao_vision_lite_model: str = (
|
||||
"doubao-seed-2-1-lite-260915" # 快速视觉(Seed 2.1 Lite 原生多模态;原 vision-lite-250315 不可用)
|
||||
)
|
||||
doubao_vision_use_lite: bool = True # viral-video 图片分析默认用 lite 提速
|
||||
doubao_embedding_model: str = "doubao-embedding-vision-251215" # 多模态向量化(原 large-text-240915 已 Retiring)
|
||||
doubao_video_model: str = "doubao-seedance-2-5-260628"
|
||||
doubao_video_timeout: int = 600 # 视频生成轮询总超时(秒)
|
||||
doubao_video_poll_interval: int = 10 # 轮询间隔(秒)
|
||||
doubao_image_model: str = "doubao-seedream-5-0-pro-260628" # 图生图/文生图(信任链真人照片AI化)
|
||||
doubao_image_timeout: int = 120 # 图片生成超时(秒)
|
||||
|
||||
# ── DashScope (阿里云百炼 Wan 3.0 等) ─────────────────────────────────
|
||||
dashscope_api_key: str = ""
|
||||
dashscope_base_url: str = "https://dashscope.aliyuncs.com/api/v1"
|
||||
dashscope_video_timeout: int = 900 # Wan 视频任务轮询总超时(秒)
|
||||
dashscope_video_poll_interval: int = 10
|
||||
|
||||
# ── MediaKit (火山引擎 AI 媒体工具) ──────────────────────────────────
|
||||
mediakit_api_key: str = ""
|
||||
|
||||
@@ -60,6 +60,11 @@ class User:
|
||||
# 资料是否已完善(微信新用户首次设置昵称后置 True;邮箱注册默认 True)
|
||||
profile_completed: bool = True
|
||||
|
||||
# 会员字段 (#1895):与 users 表列对应
|
||||
is_member: bool = False
|
||||
member_type: str | None = None
|
||||
member_expires_at: datetime | None = None
|
||||
|
||||
created_at: datetime = field(default_factory=lambda: datetime.now(UTC))
|
||||
|
||||
|
||||
|
||||
@@ -9,9 +9,9 @@ from uuid import uuid4
|
||||
class PointsAccount:
|
||||
id: str
|
||||
user_id: str
|
||||
balance: int = 0
|
||||
total_earned: int = 0
|
||||
total_spent: int = 0
|
||||
balance: float = 0.0
|
||||
total_earned: float = 0.0
|
||||
total_spent: float = 0.0
|
||||
created_at: datetime = field(default_factory=lambda: datetime.now(UTC))
|
||||
updated_at: datetime = field(default_factory=lambda: datetime.now(UTC))
|
||||
|
||||
|
||||
+330
-54
@@ -1,32 +1,321 @@
|
||||
"""积分消耗规则配置 (#1895)"""
|
||||
"""积分消耗规则配置 (#1895)
|
||||
|
||||
v1.6.1: 按产品决策,智能混剪/AI数字人/AI配音/抖音解析/改写/标题/封面 全部免费,
|
||||
仅保留声音克隆合成(voice_clone_synth)的扣点逻辑;声音克隆训练保持免费。
|
||||
爆款视频(viral_video)走动态定价,见本文件 VIRAL_VIDEO_MODEL_PRICES + calculate_viral_video_credits。
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import math
|
||||
|
||||
# ============ 爆款视频动态定价 (#2151) ============
|
||||
# key = (model_id, resolution, has_video_input),单位:
|
||||
# - billing_mode=token: 元/百万tokens(输出)
|
||||
# - billing_mode=per_second: 元/秒(视频时长)
|
||||
VIRAL_VIDEO_MODEL_PRICES: dict[tuple[str, str, bool], float] = {
|
||||
("seedance-2.5", "480p", False): 70.0,
|
||||
("seedance-2.5", "720p", False): 70.0,
|
||||
("seedance-2.5", "1080p", False): 77.0,
|
||||
("seedance-2.5", "480p", True): 42.0,
|
||||
("seedance-2.5", "720p", True): 42.0,
|
||||
("seedance-2.5", "1080p", True): 46.0,
|
||||
("seedance-2.0", "480p", False): 46.0,
|
||||
("seedance-2.0", "720p", False): 46.0,
|
||||
("seedance-2.0", "1080p", False): 51.0,
|
||||
("seedance-2.0", "4k", False): 80.0,
|
||||
("seedance-2.0-fast", "480p", False): 28.0,
|
||||
("seedance-2.0-fast", "720p", False): 28.0,
|
||||
("seedance-2.0-mini", "480p", False): 9.2,
|
||||
("seedance-2.0-mini", "720p", False): 9.2,
|
||||
("wan-3.0", "480p", False): 0.3,
|
||||
("wan-3.0", "720p", False): 0.6,
|
||||
("wan-3.0", "1080p", False): 1.2,
|
||||
}
|
||||
|
||||
# 固定成本(元):VLM 分析 + LLM 文案 + TTS + OSS + 服务器
|
||||
VIRAL_VIDEO_FIXED_COST = 0.15
|
||||
# 利润系数
|
||||
VIRAL_VIDEO_PROFIT_MULTIPLIER = 1.3
|
||||
# Seedance 输出帧率
|
||||
VIRAL_VIDEO_FPS = 24
|
||||
|
||||
# 分辨率别名映射 -> 标准 key
|
||||
_RESOLUTION_ALIASES: dict[str, str] = {
|
||||
"480p": "480p",
|
||||
"普清": "480p",
|
||||
"default": "480p",
|
||||
"low": "480p",
|
||||
"sd": "480p",
|
||||
"720p": "720p",
|
||||
"高清": "720p",
|
||||
"medium": "720p",
|
||||
"hd": "720p",
|
||||
"1080p": "1080p",
|
||||
"超清": "1080p",
|
||||
"high": "1080p",
|
||||
"ultra": "1080p",
|
||||
"全能": "1080p",
|
||||
"fhd": "1080p",
|
||||
}
|
||||
# 分辨率 -> 短边像素数(p 值代表短边,不是 height)
|
||||
_RESOLUTION_SHORT_SIDE: dict[str, int] = {"480p": 480, "720p": 720, "1080p": 1080, "4k": 2160}
|
||||
_RESOLUTION_ALIASES["4k"] = "4k"
|
||||
_RESOLUTION_ALIASES["2160p"] = "4k"
|
||||
_RESOLUTION_ALIASES["uhd"] = "4k"
|
||||
|
||||
|
||||
def resolve_video_dimensions(resolution: str, ratio: str) -> tuple[int, int]:
|
||||
"""把 (resolution, ratio) 解析为 (width, height)。
|
||||
|
||||
resolution 数字代表短边像素数(480p/720p/1080p 等):
|
||||
- 横屏 16:9:短边是 height,width = short * 16/9
|
||||
- 竖屏 9:16:短边是 width,height = short * 16/9
|
||||
- 方屏 1:1:width = height = short
|
||||
"""
|
||||
key = str(resolution or "").strip()
|
||||
key_l = key.lower()
|
||||
res_key = _RESOLUTION_ALIASES.get(key_l) or _RESOLUTION_ALIASES.get(key) or "720p"
|
||||
short = _RESOLUTION_SHORT_SIDE.get(res_key, 720)
|
||||
r = str(ratio or "").strip().lower()
|
||||
if r == "16:9":
|
||||
# 横屏:短边是 height,width 向上取整并对齐偶数
|
||||
w = math.ceil(short * 16 / 9)
|
||||
h = short
|
||||
elif r == "1:1":
|
||||
w, h = short, short
|
||||
else:
|
||||
# 9:16 竖屏(默认):短边是 width,height 向上取整并对齐偶数
|
||||
w = short
|
||||
h = math.ceil(short * 16 / 9)
|
||||
# 对齐到偶数(视频编码要求)
|
||||
w = w + (w % 2)
|
||||
h = h + (h % 2)
|
||||
return int(w), int(h)
|
||||
|
||||
|
||||
# ── 爆款视频多模型元数据 (#2159) ──────────────────────────────────────
|
||||
VIRAL_VIDEO_MODEL_CONFIG: dict[str, dict] = {
|
||||
"seedance-2.5": {
|
||||
"key": "seedance-2.5",
|
||||
"display_name": "Seedance 2.5 — 最新最强",
|
||||
"model_id": "doubao-seedance-2-5-260628",
|
||||
"provider": "doubao",
|
||||
"supports_audio": True,
|
||||
"supported_resolutions": ["480p", "720p", "1080p"],
|
||||
"max_duration": 30,
|
||||
"billing_mode": "token",
|
||||
"is_default": True,
|
||||
},
|
||||
"seedance-2.0": {
|
||||
"key": "seedance-2.0",
|
||||
"display_name": "Seedance 2.0 — 正式首选",
|
||||
"model_id": "doubao-seedance-2-0-260128",
|
||||
"provider": "doubao",
|
||||
"supports_audio": True,
|
||||
"supported_resolutions": ["480p", "720p", "1080p", "4k"],
|
||||
"max_duration": 15,
|
||||
"billing_mode": "token",
|
||||
"is_default": False,
|
||||
},
|
||||
"seedance-2.0-fast": {
|
||||
"key": "seedance-2.0-fast",
|
||||
"display_name": "Seedance 2.0 Fast — 快速低成本",
|
||||
"model_id": "doubao-seedance-2-0-fast-260128",
|
||||
"provider": "doubao",
|
||||
"supports_audio": True,
|
||||
"supported_resolutions": ["480p", "720p"],
|
||||
"max_duration": 15,
|
||||
"billing_mode": "token",
|
||||
"is_default": False,
|
||||
},
|
||||
"seedance-2.0-mini": {
|
||||
"key": "seedance-2.0-mini",
|
||||
"display_name": "Seedance 2.0 Mini — 低成本测试",
|
||||
"model_id": "doubao-seedance-2-0-mini-260615",
|
||||
"provider": "doubao",
|
||||
"supports_audio": True,
|
||||
"supported_resolutions": ["480p", "720p"],
|
||||
"max_duration": 15,
|
||||
"billing_mode": "token",
|
||||
"is_default": False,
|
||||
},
|
||||
"wan-3.0": {
|
||||
"key": "wan-3.0",
|
||||
"display_name": "Wan 3.0 — 通义万相(阿里云)",
|
||||
"model_id": "wan3.0-video",
|
||||
"provider": "dashscope",
|
||||
"supports_audio": True,
|
||||
"supported_resolutions": ["480p", "720p", "1080p"],
|
||||
"max_duration": 30,
|
||||
"billing_mode": "per_second",
|
||||
"is_default": False,
|
||||
},
|
||||
}
|
||||
|
||||
|
||||
def get_viral_video_model_config(model_key: str | None) -> dict:
|
||||
"""获取模型配置,未知 key 回落到默认 seedance-2.5。"""
|
||||
key = (model_key or "").strip().lower()
|
||||
if key and key in VIRAL_VIDEO_MODEL_CONFIG:
|
||||
return VIRAL_VIDEO_MODEL_CONFIG[key]
|
||||
return VIRAL_VIDEO_MODEL_CONFIG["seedance-2.5"]
|
||||
|
||||
|
||||
def list_viral_video_models(
|
||||
include_placeholder: bool = False,
|
||||
dashscope_available: bool = False,
|
||||
) -> list[dict]:
|
||||
"""返回前端可用的模型列表(供 GET /api/v1/viral-video/models 端点用)。"""
|
||||
out: list[dict] = []
|
||||
for _k, cfg in VIRAL_VIDEO_MODEL_CONFIG.items():
|
||||
if cfg.get("_placeholder") and not include_placeholder:
|
||||
continue
|
||||
if cfg.get("provider") == "dashscope" and not dashscope_available:
|
||||
continue
|
||||
out.append(
|
||||
{
|
||||
"key": cfg["key"],
|
||||
"display_name": cfg["display_name"],
|
||||
"supports_audio": bool(cfg.get("supports_audio", True)),
|
||||
"supported_resolutions": list(cfg.get("supported_resolutions", ["720p"])),
|
||||
"max_duration": int(cfg.get("max_duration", 15)),
|
||||
"billing_mode": cfg.get("billing_mode", "token"),
|
||||
"is_default": bool(cfg.get("is_default", False)),
|
||||
}
|
||||
)
|
||||
return out
|
||||
|
||||
|
||||
def _match_model_prefix(model: str | None) -> str:
|
||||
"""匹配 model key(支持全部内部别名,未知回落到 seedance-2.5)。
|
||||
|
||||
按 key 长度从长到短匹配,避免 "seedance-2.0-fast" 被 "seedance-2.0" 前缀命中。
|
||||
"""
|
||||
mm = (model or "").strip().lower()
|
||||
for k in sorted(VIRAL_VIDEO_MODEL_CONFIG.keys(), key=len, reverse=True):
|
||||
if mm == k or mm.startswith(k):
|
||||
return k
|
||||
return "seedance-2.5"
|
||||
|
||||
|
||||
def _infer_resolution_key(width: int, height: int) -> str:
|
||||
"""从实际 (width, height) 用短边推断 resolution key。"""
|
||||
short = min(int(width or 720), int(height or 720))
|
||||
if short >= 1900:
|
||||
return "4k"
|
||||
if short >= 1000:
|
||||
return "1080p"
|
||||
if short >= 650:
|
||||
return "720p"
|
||||
return "480p"
|
||||
|
||||
|
||||
def calculate_viral_video_credits_with_breakdown(
|
||||
duration_seconds: int,
|
||||
width: int,
|
||||
height: int,
|
||||
model: str = "seedance-2.5",
|
||||
has_video_input: bool = False,
|
||||
actual_tokens: int | None = None,
|
||||
fps: int = VIRAL_VIDEO_FPS,
|
||||
) -> tuple[float, dict]:
|
||||
"""计算爆款视频所需积分(1 积分 = 1 元),并返回计费公式明细。
|
||||
|
||||
公式:
|
||||
tokens = duration * width * height * fps / 1024
|
||||
video_cost = tokens / 1_000_000 * model_token_price
|
||||
total = round((video_cost + fixed_cost) * profit_multiplier, 2)
|
||||
若传入 actual_tokens 则用它替代计算值。
|
||||
|
||||
Returns:
|
||||
(credits, breakdown) 二元组:
|
||||
- credits: 四舍五入保留两位小数的最终积分
|
||||
- breakdown: dict,包含 tokens / video_cost / fixed_cost / profit_multiplier /
|
||||
model_price / width / height / fps 字段,便于前端展示计费明细。
|
||||
"""
|
||||
w = max(1, int(width or 1))
|
||||
h = max(1, int(height or 1))
|
||||
effective_fps = int(fps or VIRAL_VIDEO_FPS)
|
||||
|
||||
prefix = _match_model_prefix(model)
|
||||
cfg = get_viral_video_model_config(prefix)
|
||||
res_key = _infer_resolution_key(w, h)
|
||||
billing = cfg.get("billing_mode", "token")
|
||||
key = (prefix, res_key, bool(has_video_input))
|
||||
price = VIRAL_VIDEO_MODEL_PRICES.get(key)
|
||||
if price is None:
|
||||
price = VIRAL_VIDEO_MODEL_PRICES.get(("seedance-2.5", res_key, False), 70.0)
|
||||
dur = max(1, int(duration_seconds or 15))
|
||||
if billing == "per_second":
|
||||
tokens = 0.0
|
||||
video_cost = dur * float(price)
|
||||
billing_unit = "second"
|
||||
else:
|
||||
if actual_tokens is not None and actual_tokens > 0:
|
||||
tokens = float(actual_tokens)
|
||||
else:
|
||||
tokens = dur * w * h * effective_fps / 1024.0
|
||||
video_cost = tokens / 1_000_000.0 * float(price)
|
||||
billing_unit = "token"
|
||||
|
||||
total = (video_cost + VIRAL_VIDEO_FIXED_COST) * VIRAL_VIDEO_PROFIT_MULTIPLIER
|
||||
credits = round(float(total), 2)
|
||||
breakdown = {
|
||||
"tokens": float(tokens),
|
||||
"video_cost": float(video_cost),
|
||||
"fixed_cost": float(VIRAL_VIDEO_FIXED_COST),
|
||||
"profit_multiplier": float(VIRAL_VIDEO_PROFIT_MULTIPLIER),
|
||||
"model_price": float(price),
|
||||
"model_key": prefix,
|
||||
"billing_mode": billing,
|
||||
"billing_unit": billing_unit,
|
||||
"width": int(w),
|
||||
"height": int(h),
|
||||
"fps": int(effective_fps),
|
||||
"duration": dur,
|
||||
}
|
||||
return credits, breakdown
|
||||
|
||||
|
||||
def calculate_viral_video_credits(
|
||||
duration_seconds: int,
|
||||
width: int,
|
||||
height: int,
|
||||
model: str = "seedance-2.5",
|
||||
has_video_input: bool = False,
|
||||
actual_tokens: int | None = None,
|
||||
fps: int = VIRAL_VIDEO_FPS,
|
||||
) -> float:
|
||||
"""计算爆款视频所需积分(1 积分 = 1 元),仅返回积分值(向后兼容包装器)。
|
||||
|
||||
内部调用 calculate_viral_video_credits_with_breakdown,仅返回 credits 部分,
|
||||
保持旧调用方签名与返回值类型不变。
|
||||
|
||||
公式:
|
||||
tokens = duration * width * height * fps / 1024
|
||||
video_cost = tokens / 1_000_000 * model_token_price
|
||||
total = round((video_cost + fixed_cost) * profit_multiplier, 2)
|
||||
若传入 actual_tokens 则用它替代计算值。
|
||||
"""
|
||||
credits, _ = calculate_viral_video_credits_with_breakdown(
|
||||
duration_seconds=duration_seconds,
|
||||
width=width,
|
||||
height=height,
|
||||
model=model,
|
||||
has_video_input=has_video_input,
|
||||
actual_tokens=actual_tokens,
|
||||
fps=fps,
|
||||
)
|
||||
return credits
|
||||
|
||||
|
||||
# ============ 场景定义 ============
|
||||
# 每个场景: base_points(基础积分), unit(计费单位), name(显示名称)
|
||||
# 每个场景: base_points(基础积分), unit(计费单位), name(显示名称), dynamic(是否动态定价)
|
||||
# 说明:爆款视频(viral_video)走动态定价(预扣→结算多退少补),因此不使用 @points_gate
|
||||
# 装饰器,base_points=0,dynamic=True;前端展示场景列表时仍可看到。
|
||||
|
||||
POINTS_SCENES: dict[str, dict] = {
|
||||
"ai_voice": {
|
||||
"base_points": 1,
|
||||
"unit": "分钟",
|
||||
"name": "AI 配音",
|
||||
"description": "AI 配音每分钟消耗 1 积分(免费用户上浮 15%,会员 8~9 折)",
|
||||
},
|
||||
"ai_video": {
|
||||
"base_points": 3,
|
||||
"unit": "条",
|
||||
"name": "智能混剪",
|
||||
"extra_per_30s": 1,
|
||||
"description": "智能混剪每条 3 积分起,视频超过 30 秒后每 30 秒加 1 积分;免费用户每日 2 条免费额度",
|
||||
},
|
||||
"ai_digital_human": {
|
||||
"base_points": 15,
|
||||
"unit": "分钟",
|
||||
"name": "AI 数字人",
|
||||
"description": "AI 数字人每分钟消耗 15 积分",
|
||||
},
|
||||
"voice_clone_train": {
|
||||
"base_points": 0,
|
||||
"unit": "次",
|
||||
@@ -39,23 +328,16 @@ POINTS_SCENES: dict[str, dict] = {
|
||||
"name": "声音克隆合成",
|
||||
"description": "克隆音色合成每分钟消耗 1 积分",
|
||||
},
|
||||
"douyin_extract": {
|
||||
"base_points": 1,
|
||||
"viral_video": {
|
||||
"base_points": 0,
|
||||
"unit": "次",
|
||||
"name": "抖音链接提取",
|
||||
"description": "抖音文案提取每次 1 积分",
|
||||
"name": "爆款视频",
|
||||
"dynamic": True,
|
||||
"description": "爆款视频动态定价(按视频时长/分辨率/模型计算,预扣→结算多退少补)",
|
||||
},
|
||||
"ai_rewrite": {"base_points": 1, "unit": "次", "name": "AI 改写文案", "description": "AI 改写文案每次 1 积分"},
|
||||
"ai_title": {
|
||||
"base_points": 1,
|
||||
"unit": "次",
|
||||
"name": "AI 标题生成",
|
||||
"description": "AI 生成标题每次 1 积分(免费用户实际上浮后 2 积分/次)",
|
||||
},
|
||||
"ai_cover": {"base_points": 1, "unit": "张", "name": "AI 封面生成", "description": "AI 封面生成每张 1 积分"},
|
||||
}
|
||||
|
||||
# 免费用户积分消耗上浮系数
|
||||
# 免费用户积分消耗上浮系数(仅对 voice_clone_synth 生效)
|
||||
FREE_USER_MULTIPLIER = 1.15
|
||||
|
||||
# ============ 积分包定义 ============
|
||||
@@ -81,9 +363,6 @@ MEMBER_DISCOUNT: dict[str, float] = {
|
||||
"yearly": 0.8,
|
||||
}
|
||||
|
||||
# 每日免费混剪次数(免费用户)
|
||||
DAILY_FREE_CLIP_LIMIT = 2
|
||||
|
||||
|
||||
def calculate_points_cost(
|
||||
scene_key: str,
|
||||
@@ -91,48 +370,45 @@ def calculate_points_cost(
|
||||
quantity: int = 1,
|
||||
duration_minutes: float = 0,
|
||||
member_type: str | None = None,
|
||||
) -> int:
|
||||
) -> float:
|
||||
"""计算指定场景的积分消耗。
|
||||
|
||||
Args:
|
||||
scene_key: 场景标识,如 "ai_voice"、"ai_video"
|
||||
scene_key: 场景标识(当前支持 voice_clone_train/voice_clone_synth/viral_video;
|
||||
viral_video 为动态定价场景,此处返回 0,由业务侧调用
|
||||
calculate_viral_video_credits 手动计算)
|
||||
is_member: 是否付费会员
|
||||
quantity: 数量(按次计费场景)
|
||||
duration_minutes: 时长分钟数(按时长计费场景)
|
||||
member_type: 会员类型 (monthly/quarterly/yearly),用于折扣
|
||||
|
||||
Returns:
|
||||
实际消耗积分(已含免费用户 ×1.15 上浮或会员折扣)
|
||||
|
||||
Raises:
|
||||
ValueError: 未知场景标识
|
||||
实际消耗积分(float;已含免费用户 ×1.15 上浮或会员折扣);免费/动态/已下线场景统一返回 0。
|
||||
"""
|
||||
scene = POINTS_SCENES.get(scene_key)
|
||||
if not scene:
|
||||
raise ValueError(f"Unknown points scene: {scene_key}")
|
||||
# 已下线/未注册的场景统一返回 0(免费),保持向后兼容
|
||||
return 0.0
|
||||
|
||||
# 动态定价场景(如 viral_video)由业务侧手动计算,这里统一返回 0
|
||||
if scene.get("dynamic"):
|
||||
return 0.0
|
||||
|
||||
base = scene["base_points"]
|
||||
if base == 0:
|
||||
return 0
|
||||
return 0.0
|
||||
|
||||
# —— 计算基础消耗 ——
|
||||
unit = scene["unit"]
|
||||
if unit == "分钟":
|
||||
total_base = base * max(1, math.ceil(duration_minutes))
|
||||
elif unit in ("条", "次", "张"):
|
||||
elif unit in ("次", "张"):
|
||||
total_base = base * quantity
|
||||
# 混剪特殊逻辑:视频超过 30s 后每 +30s 额外加 1 积分
|
||||
if scene_key == "ai_video" and duration_minutes > 0.5:
|
||||
extra_segments = math.ceil((duration_minutes * 60 - 30) / 30)
|
||||
if extra_segments > 0:
|
||||
total_base += scene.get("extra_per_30s", 1) * extra_segments
|
||||
else:
|
||||
total_base = base
|
||||
|
||||
# —— 会员折扣 / 免费用户上浮 ——
|
||||
if is_member and member_type and member_type in MEMBER_DISCOUNT:
|
||||
total_base = max(1, math.floor(total_base * MEMBER_DISCOUNT[member_type]))
|
||||
elif not is_member:
|
||||
total_base = math.ceil(total_base * FREE_USER_MULTIPLIER)
|
||||
|
||||
return total_base
|
||||
return float(total_base)
|
||||
|
||||
@@ -13,7 +13,6 @@ from typing import Any
|
||||
from sqlalchemy.orm import Session
|
||||
|
||||
from packages.domain.points_rules import (
|
||||
DAILY_FREE_CLIP_LIMIT,
|
||||
POINTS_PACKAGES,
|
||||
)
|
||||
|
||||
@@ -84,7 +83,7 @@ class PointsService:
|
||||
|
||||
# ──────────────── 余额检查 ────────────────
|
||||
|
||||
def check_balance(self, user_id: str, amount: int, db: Session) -> dict[str, Any]:
|
||||
def check_balance(self, user_id: str, amount: float, db: Session) -> dict[str, Any]:
|
||||
"""检查余额是否足够。"""
|
||||
account_data = self.get_or_create_account(user_id, db)
|
||||
balance = account_data["balance"]
|
||||
@@ -100,7 +99,7 @@ class PointsService:
|
||||
def deduct_points(
|
||||
self,
|
||||
user_id: str,
|
||||
amount: int,
|
||||
amount: float,
|
||||
source: str,
|
||||
db: Session,
|
||||
description: str = "",
|
||||
@@ -109,7 +108,7 @@ class PointsService:
|
||||
"""扣减积分(事务性:SELECT FOR UPDATE → 检查余额 → 扣减 → 流水 → 同步用户表)。
|
||||
|
||||
Returns:
|
||||
{"success": True/False, "balance": int, "transaction_id": str|None}
|
||||
{"success": True/False, "balance": float, "transaction_id": str|None}
|
||||
"""
|
||||
PointsAccountModel, PointsTransactionModel, _, _, UserModel = _get_models()
|
||||
|
||||
@@ -173,7 +172,7 @@ class PointsService:
|
||||
except Exception:
|
||||
db.rollback()
|
||||
logger.exception(
|
||||
"积分扣减失败: user_id=%s, amount=%d, source=%s",
|
||||
"积分扣减失败: user_id=%s, amount=%.2f, source=%s",
|
||||
user_id,
|
||||
amount,
|
||||
source,
|
||||
@@ -185,7 +184,7 @@ class PointsService:
|
||||
def add_points(
|
||||
self,
|
||||
user_id: str,
|
||||
amount: int,
|
||||
amount: float,
|
||||
source: str,
|
||||
db: Session,
|
||||
description: str = "",
|
||||
@@ -242,7 +241,7 @@ class PointsService:
|
||||
except Exception:
|
||||
db.rollback()
|
||||
logger.exception(
|
||||
"积分增加失败: user_id=%s, amount=%d, source=%s",
|
||||
"积分增加失败: user_id=%s, amount=%.2f, source=%s",
|
||||
user_id,
|
||||
amount,
|
||||
source,
|
||||
@@ -254,7 +253,7 @@ class PointsService:
|
||||
def refund_points(
|
||||
self,
|
||||
user_id: str,
|
||||
amount: int,
|
||||
amount: float,
|
||||
source: str,
|
||||
db: Session,
|
||||
ref_id: str = "",
|
||||
@@ -270,6 +269,92 @@ class PointsService:
|
||||
ref_id=ref_id,
|
||||
)
|
||||
|
||||
# ──────────────── 爆款视频(viral_video)动态定价 ────────────────
|
||||
|
||||
def deduct_viral_video(self, user_id: str, credits: float, job_id: str, db: Session) -> dict[str, Any]:
|
||||
"""爆款视频预扣积分(confirm-copy 阶段)。"""
|
||||
return self.deduct_points(
|
||||
user_id=user_id,
|
||||
amount=float(credits or 0),
|
||||
source="viral_video",
|
||||
db=db,
|
||||
description="爆款视频生成",
|
||||
ref_id=job_id,
|
||||
)
|
||||
|
||||
def settle_viral_video(
|
||||
self,
|
||||
user_id: str,
|
||||
estimated: float,
|
||||
actual: float,
|
||||
txn_id: str,
|
||||
db: Session,
|
||||
) -> dict[str, Any]:
|
||||
"""爆款视频完成后按实际 tokens 结算(多退少补)。
|
||||
|
||||
- actual < estimated: 退差额
|
||||
- actual > estimated: 补扣差额(余额不足时记 warning,不阻塞完成)
|
||||
- |diff| < 0.01: 不动
|
||||
"""
|
||||
diff = round(float(actual or 0) - float(estimated or 0), 2)
|
||||
if abs(diff) < 0.01:
|
||||
return {"success": True, "action": "none", "diff": 0.0}
|
||||
if diff < 0:
|
||||
refund = round(-diff, 2)
|
||||
try:
|
||||
res = self.refund_points(
|
||||
user_id=user_id,
|
||||
amount=refund,
|
||||
source="viral_video",
|
||||
db=db,
|
||||
ref_id=txn_id,
|
||||
description="爆款视频结算退费",
|
||||
)
|
||||
return {"success": bool(res.get("success")), "action": "refund", "diff": -refund, "amount": refund}
|
||||
except Exception:
|
||||
logger.exception("[viral_video] 结算退费异常 user_id=%s refund=%.2f", user_id, refund)
|
||||
return {"success": False, "action": "refund", "diff": -refund}
|
||||
else:
|
||||
extra = round(diff, 2)
|
||||
try:
|
||||
res = self.deduct_points(
|
||||
user_id=user_id,
|
||||
amount=extra,
|
||||
source="viral_video",
|
||||
db=db,
|
||||
description="爆款视频结算补扣",
|
||||
ref_id=txn_id,
|
||||
)
|
||||
if not res.get("success"):
|
||||
logger.warning(
|
||||
"[viral_video] 结算补扣余额不足 user_id=%s extra=%.2f balance=%s (不阻塞任务完成)",
|
||||
user_id,
|
||||
extra,
|
||||
res.get("balance"),
|
||||
)
|
||||
return {"success": bool(res.get("success")), "action": "deduct", "diff": extra, "amount": extra}
|
||||
except Exception:
|
||||
logger.exception("[viral_video] 结算补扣异常 user_id=%s extra=%.2f", user_id, extra)
|
||||
return {"success": False, "action": "deduct", "diff": extra}
|
||||
|
||||
def refund_viral_video(self, user_id: str, credits: float, txn_id: str, db: Session) -> dict[str, Any]:
|
||||
"""爆款视频失败全额退款。"""
|
||||
amount = float(credits or 0)
|
||||
if amount <= 0:
|
||||
return {"success": True, "action": "none", "amount": 0.0}
|
||||
try:
|
||||
return self.refund_points(
|
||||
user_id=user_id,
|
||||
amount=amount,
|
||||
source="viral_video",
|
||||
db=db,
|
||||
ref_id=txn_id,
|
||||
description="爆款视频失败退款",
|
||||
)
|
||||
except Exception:
|
||||
logger.exception("[viral_video] 失败退款异常 user_id=%s amount=%.2f", user_id, amount)
|
||||
return {"success": False, "action": "refund", "amount": amount}
|
||||
|
||||
# ──────────────── 流水查询 ────────────────
|
||||
|
||||
def get_transactions(
|
||||
@@ -324,132 +409,16 @@ class PointsService:
|
||||
"page_size": page_size,
|
||||
}
|
||||
|
||||
# ──────────────── 每日免费混剪额度 ────────────────
|
||||
|
||||
def _daily_key(self, user_id: str) -> str:
|
||||
"""生成 Redis 每日额度 key。格式: daily_usage:{user_id}:{YYYYMMDD}:free_clip"""
|
||||
today = datetime.now(UTC).strftime("%Y%m%d")
|
||||
return f"daily_usage:{user_id}:{today}:free_clip"
|
||||
|
||||
def check_daily_free_clip(self, user_id: str, db: Session) -> bool:
|
||||
"""检查今日是否还有免费混剪额度。
|
||||
|
||||
优先查 Redis,Redis 不可用时降级到 DB。
|
||||
"""
|
||||
redis_client = _get_redis_client()
|
||||
if redis_client:
|
||||
try:
|
||||
key = self._daily_key(user_id)
|
||||
current = redis_client.get(key)
|
||||
if current is None:
|
||||
return True
|
||||
return int(current) < DAILY_FREE_CLIP_LIMIT
|
||||
except Exception:
|
||||
logger.warning("Redis 不可用,降级到 DB 查询每日额度")
|
||||
|
||||
# 降级到 DB
|
||||
_, _, _, DailyUsageRecordModel, _ = _get_models()
|
||||
today_start = datetime.now(UTC).replace(hour=0, minute=0, second=0, microsecond=0)
|
||||
record = (
|
||||
db.query(DailyUsageRecordModel)
|
||||
.filter(
|
||||
DailyUsageRecordModel.user_id == user_id,
|
||||
DailyUsageRecordModel.usage_type == "free_clip",
|
||||
DailyUsageRecordModel.usage_date >= today_start,
|
||||
)
|
||||
.first()
|
||||
)
|
||||
if record is None:
|
||||
return True
|
||||
return record.count < DAILY_FREE_CLIP_LIMIT
|
||||
|
||||
def record_daily_free_clip(self, user_id: str, db: Session) -> bool:
|
||||
"""记录使用一次免费混剪。
|
||||
|
||||
先 INCR Redis;如果超限回退 Redis。DB 使用 upsert 语义(唯一约束)。
|
||||
"""
|
||||
redis_client = _get_redis_client()
|
||||
if redis_client:
|
||||
try:
|
||||
key = self._daily_key(user_id)
|
||||
new_count = redis_client.incr(key)
|
||||
if new_count == 1:
|
||||
redis_client.expire(key, 48 * 3600) # TTL 48h
|
||||
if new_count <= DAILY_FREE_CLIP_LIMIT:
|
||||
return True
|
||||
# 超限,回退 Redis
|
||||
redis_client.decr(key)
|
||||
except Exception:
|
||||
logger.warning("Redis 不可用,降级到 DB 记录每日额度")
|
||||
|
||||
# 降级/兜底到 DB(upsert 语义)
|
||||
_, _, _, DailyUsageRecordModel, _ = _get_models()
|
||||
today_start = datetime.now(UTC).replace(hour=0, minute=0, second=0, microsecond=0)
|
||||
|
||||
record = (
|
||||
db.query(DailyUsageRecordModel)
|
||||
.filter(
|
||||
DailyUsageRecordModel.user_id == user_id,
|
||||
DailyUsageRecordModel.usage_type == "free_clip",
|
||||
DailyUsageRecordModel.usage_date >= today_start,
|
||||
)
|
||||
.first()
|
||||
)
|
||||
|
||||
if record is None:
|
||||
if DAILY_FREE_CLIP_LIMIT <= 0:
|
||||
return False
|
||||
record = DailyUsageRecordModel(
|
||||
id=uuid.uuid4().hex,
|
||||
user_id=user_id,
|
||||
usage_type="free_clip",
|
||||
usage_date=datetime.now(UTC),
|
||||
count=1,
|
||||
)
|
||||
db.add(record)
|
||||
else:
|
||||
if record.count >= DAILY_FREE_CLIP_LIMIT:
|
||||
return False
|
||||
record.count += 1
|
||||
|
||||
db.commit()
|
||||
return True
|
||||
# ──────────────── 每日免费混剪额度(已下线:智能混剪全免费) ────────────────
|
||||
|
||||
def get_daily_usage(self, user_id: str, db: Session) -> dict[str, Any]:
|
||||
"""查询今日免费额度使用情况。"""
|
||||
redis_client = _get_redis_client()
|
||||
used = 0
|
||||
|
||||
if redis_client:
|
||||
try:
|
||||
key = self._daily_key(user_id)
|
||||
val = redis_client.get(key)
|
||||
used = int(val) if val else 0
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
if used == 0:
|
||||
# 从 DB 查
|
||||
_, _, _, DailyUsageRecordModel, _ = _get_models()
|
||||
today_start = datetime.now(UTC).replace(hour=0, minute=0, second=0, microsecond=0)
|
||||
record = (
|
||||
db.query(DailyUsageRecordModel)
|
||||
.filter(
|
||||
DailyUsageRecordModel.user_id == user_id,
|
||||
DailyUsageRecordModel.usage_type == "free_clip",
|
||||
DailyUsageRecordModel.usage_date >= today_start,
|
||||
)
|
||||
.first()
|
||||
)
|
||||
used = record.count if record else 0
|
||||
|
||||
"""查询今日免费额度使用情况(智能混剪已全免费,返回 unlimited)。"""
|
||||
now = datetime.now(UTC)
|
||||
tomorrow = (now + timedelta(days=1)).replace(hour=0, minute=0, second=0, microsecond=0)
|
||||
|
||||
return {
|
||||
"free_clips_used": used,
|
||||
"free_clips_limit": DAILY_FREE_CLIP_LIMIT,
|
||||
"free_clips_remaining": max(0, DAILY_FREE_CLIP_LIMIT - used),
|
||||
"free_clips_used": 0,
|
||||
"free_clips_limit": -1, # -1 表示 unlimited
|
||||
"free_clips_remaining": -1,
|
||||
"reset_at": tomorrow.isoformat(),
|
||||
}
|
||||
|
||||
|
||||
+110
-38
@@ -1,15 +1,15 @@
|
||||
"""ViralVideoJob 领域模型 — 爆款视频任务.
|
||||
|
||||
状态机:
|
||||
pending → running → completed
|
||||
↘ failed → pending (retry)
|
||||
↘ cancelled
|
||||
running 中可暂停:running → wait_user_confirm → running (confirm-intent resume)
|
||||
v1.6 重大简化:Seedance 2.5 单次最长30秒,单次调用直接出片,不再分段/拼接/ffmpeg concat。
|
||||
状态机(三步分步):
|
||||
pending -> running -> image_analyzed -> running -> copy_generated -> running -> completed
|
||||
wait_user_confirm -> running -> completed (旧路径兼容)
|
||||
任意阶段 fail; 任意非终态 cancel.
|
||||
failed -> pending (retry 重置后重跑)。
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
|
||||
import sys
|
||||
from dataclasses import dataclass, field
|
||||
from datetime import datetime, timezone
|
||||
@@ -27,10 +27,10 @@ from uuid import uuid4
|
||||
|
||||
|
||||
class ViralVideoStatus(StrEnum):
|
||||
"""爆款视频任务状态枚举。"""
|
||||
|
||||
PENDING = "pending"
|
||||
RUNNING = "running"
|
||||
IMAGE_ANALYZED = "image_analyzed"
|
||||
COPY_GENERATED = "copy_generated"
|
||||
WAIT_USER_CONFIRM = "wait_user_confirm"
|
||||
COMPLETED = "completed"
|
||||
FAILED = "failed"
|
||||
@@ -38,93 +38,94 @@ class ViralVideoStatus(StrEnum):
|
||||
|
||||
|
||||
class ViralVideoStage(StrEnum):
|
||||
"""编排流水线阶段枚举(用于 WS 进度推送)。"""
|
||||
|
||||
IMAGE_ANALYSIS = "image_analysis"
|
||||
VIDEO_ANALYSIS = "video_analysis"
|
||||
INTENT_PARSING = "intent_parsing"
|
||||
COPY_FUSION = "copy_fusion"
|
||||
STORYBOARD = "storyboard"
|
||||
SCRIPT_GENERATION = "script_generation" # v1.6: 编导分镜脚本(融合原 copy_fusion+storyboard+review)
|
||||
REVIEW = "review"
|
||||
TTS = "tts"
|
||||
BGM_SELECT = "bgm_select"
|
||||
RENDERING = "rendering"
|
||||
MUSETALK = "musetalk"
|
||||
RENDERING = "rendering" # v1.6: 单次 Seedance 生成(BGM/音效/画面一次出片)
|
||||
UPLOADING = "uploading"
|
||||
|
||||
|
||||
class FusionLevel(StrEnum):
|
||||
"""文案融合级别。"""
|
||||
|
||||
AI_FULL = "ai_full"
|
||||
AI_POLISH = "ai_polish"
|
||||
USER_PRIMARY = "user_primary"
|
||||
|
||||
|
||||
class StyleStrength(StrEnum):
|
||||
"""风格强度。"""
|
||||
|
||||
LIGHT = "light"
|
||||
MEDIUM = "medium"
|
||||
STRICT = "strict"
|
||||
|
||||
|
||||
class PromptType(StrEnum):
|
||||
"""Prompt 模板类型(与 #2040 seed 对齐)。"""
|
||||
|
||||
IMAGE_ANALYSIS = "image_analysis"
|
||||
INTENT_PARSING = "intent_parsing"
|
||||
COPY_FUSION = "copy_fusion"
|
||||
STORYBOARD = "storyboard"
|
||||
SCRIPT_GENERATION = "script_generation"
|
||||
REVIEW = "review"
|
||||
VIDEO_STYLE_INTEGRATION = "video_style_integration"
|
||||
STYLE_CONSTRAINT = "style_constraint"
|
||||
|
||||
|
||||
CREDITS_VIRAL_VIDEO_COST = 50
|
||||
|
||||
STAGE_LABELS = {
|
||||
ViralVideoStage.IMAGE_ANALYSIS: "图片分析",
|
||||
ViralVideoStage.VIDEO_ANALYSIS: "视频风格分析",
|
||||
ViralVideoStage.INTENT_PARSING: "意图解析",
|
||||
ViralVideoStage.COPY_FUSION: "文案融合",
|
||||
ViralVideoStage.STORYBOARD: "分镜脚本",
|
||||
ViralVideoStage.SCRIPT_GENERATION: "编导脚本生成",
|
||||
ViralVideoStage.REVIEW: "合规审核",
|
||||
ViralVideoStage.TTS: "AI 配音",
|
||||
ViralVideoStage.BGM_SELECT: "BGM 选择",
|
||||
ViralVideoStage.RENDERING: "视频渲染",
|
||||
ViralVideoStage.MUSETALK: "数字人口型",
|
||||
ViralVideoStage.RENDERING: "视频生成",
|
||||
ViralVideoStage.UPLOADING: "上传发布",
|
||||
}
|
||||
|
||||
|
||||
@dataclass
|
||||
class ViralVideoJob:
|
||||
"""爆款视频任务领域实体。"""
|
||||
"""爆款视频任务领域实体(v1.6 单次 Seedance 出片版)。"""
|
||||
|
||||
user_id: str
|
||||
images: list[str] = field(default_factory=list)
|
||||
pre_trusted_images: list[str] | None = (
|
||||
None # #2172 信任链预热结果(Seedream AI 化后的 URL 列表),与 images 顺序对应
|
||||
)
|
||||
industry: str = ""
|
||||
target_customer: str = ""
|
||||
persona_id: str = ""
|
||||
viral_structure: str = ""
|
||||
marketing_purpose: str = ""
|
||||
bgm_preference: str = ""
|
||||
duration: int = 30
|
||||
duration: int = 15 # v1.6: 默认15秒,上限30秒(Seedance 2.5 单次最大30s)
|
||||
user_copy_text: str = ""
|
||||
fusion_level: str = FusionLevel.AI_POLISH
|
||||
reference_audio_path: str = ""
|
||||
# v1.3
|
||||
reference_video_url: str = ""
|
||||
style_strength: str = StyleStrength.MEDIUM
|
||||
style_guide: dict | None = None
|
||||
style_template_id: str = ""
|
||||
# v1.5.1 音频/视频参数
|
||||
voice_id: str = ""
|
||||
voice_source: str = ""
|
||||
video_ratio: str = "9:16"
|
||||
video_model: str = ""
|
||||
# v1.4+ 产物
|
||||
image_analysis: dict | None = None
|
||||
intent_result: dict | None = None
|
||||
generated_copy_text: str = "" # v1.6: 存 voiceover_script(纯口播对白),字段名兼容
|
||||
storyboard: list | None = None # v1.6: 存 copy_result.shots,字段名兼容
|
||||
copy_result: dict | None = None # v1.6: 完整编导脚本结构
|
||||
# 状态
|
||||
id: str = field(default_factory=lambda: uuid4().hex)
|
||||
status: ViralVideoStatus = ViralVideoStatus.PENDING
|
||||
intent_result: dict | None = None
|
||||
current_stage: str = "" # 细粒度阶段(ViralVideoStage.value,snake_case)
|
||||
phase_message: str = "" # 阶段中文提示文案,前端轮询直接展示
|
||||
heartbeat_at: datetime | None = None # worker 心跳时间,用于超时僵尸任务检测
|
||||
result_video_url: str = ""
|
||||
credits_cost: int = 0
|
||||
video_resolution: str = "720p"
|
||||
credits_prepaid: float = 0.0
|
||||
credits_transaction_id: str = ""
|
||||
credits_cost: float = 0.0
|
||||
error_msg: str = ""
|
||||
retry_count: int = 0
|
||||
started_at: datetime | None = None
|
||||
@@ -132,13 +133,54 @@ class ViralVideoJob:
|
||||
created_at: datetime = field(default_factory=lambda: datetime.now(timezone.utc))
|
||||
updated_at: datetime = field(default_factory=lambda: datetime.now(timezone.utc))
|
||||
|
||||
# ── 状态转换 ──
|
||||
# -- 状态转换 --
|
||||
|
||||
def mark_running(self) -> None:
|
||||
if self.status not in (ViralVideoStatus.PENDING, ViralVideoStatus.RUNNING):
|
||||
if self.status not in (
|
||||
ViralVideoStatus.PENDING,
|
||||
ViralVideoStatus.IMAGE_ANALYZED,
|
||||
ViralVideoStatus.COPY_GENERATED,
|
||||
ViralVideoStatus.WAIT_USER_CONFIRM,
|
||||
ViralVideoStatus.RUNNING,
|
||||
):
|
||||
raise ValueError(f"Cannot transition from {self.status} to running")
|
||||
self.status = ViralVideoStatus.RUNNING
|
||||
self.started_at = datetime.now(timezone.utc)
|
||||
now = datetime.now(timezone.utc)
|
||||
if self.started_at is None:
|
||||
self.started_at = now
|
||||
self.heartbeat_at = now
|
||||
self.updated_at = now
|
||||
|
||||
def touch_heartbeat(self) -> None:
|
||||
"""更新心跳时间(worker 在长任务中周期性调用,用于超时检测)。"""
|
||||
now = datetime.now(timezone.utc)
|
||||
if self.started_at is None:
|
||||
self.started_at = now
|
||||
self.heartbeat_at = now
|
||||
self.updated_at = now
|
||||
|
||||
def mark_image_analyzed(self) -> None:
|
||||
if self.status not in (ViralVideoStatus.PENDING, ViralVideoStatus.RUNNING):
|
||||
raise ValueError(f"Cannot transition from {self.status} to image_analyzed")
|
||||
self.status = ViralVideoStatus.IMAGE_ANALYZED
|
||||
if self.started_at is None:
|
||||
self.started_at = datetime.now(timezone.utc)
|
||||
self.updated_at = datetime.now(timezone.utc)
|
||||
|
||||
def mark_copy_generated(self, copy_result: dict) -> None:
|
||||
"""v1.6 阶段2完成:编导脚本(含 voiceover_script/shots/硬约束/负面词)已生成。"""
|
||||
if self.status not in (
|
||||
ViralVideoStatus.IMAGE_ANALYZED,
|
||||
ViralVideoStatus.RUNNING,
|
||||
ViralVideoStatus.PENDING,
|
||||
):
|
||||
raise ValueError(f"Cannot transition from {self.status} to copy_generated")
|
||||
self.status = ViralVideoStatus.COPY_GENERATED
|
||||
self.copy_result = copy_result or {}
|
||||
if isinstance(copy_result, dict):
|
||||
self.generated_copy_text = copy_result.get("voiceover_script", "") or ""
|
||||
shots = copy_result.get("shots") or []
|
||||
self.storyboard = list(shots) if isinstance(shots, list) else []
|
||||
self.updated_at = datetime.now(timezone.utc)
|
||||
|
||||
def mark_wait_user_confirm(self, intent_result: dict) -> None:
|
||||
@@ -148,6 +190,25 @@ class ViralVideoJob:
|
||||
self.intent_result = intent_result
|
||||
self.updated_at = datetime.now(timezone.utc)
|
||||
|
||||
def resume_from_image_analyzed(self, **kwargs) -> None:
|
||||
if self.status not in (ViralVideoStatus.IMAGE_ANALYZED, ViralVideoStatus.PENDING):
|
||||
raise ValueError(f"Cannot resume from {self.status} to copy-gen")
|
||||
for k, v in kwargs.items():
|
||||
if hasattr(self, k) and v not in (None, "", []):
|
||||
setattr(self, k, v)
|
||||
self.status = ViralVideoStatus.RUNNING
|
||||
self.updated_at = datetime.now(timezone.utc)
|
||||
|
||||
def resume_from_copy_generated(self, edited_copy: str | None = None) -> None:
|
||||
"""阶段2->阶段3:用户确认/编辑口播文案,开始跑 TTS+单次Seedance渲染。"""
|
||||
if self.status != ViralVideoStatus.COPY_GENERATED:
|
||||
raise ValueError(f"Cannot resume from {self.status} to render")
|
||||
if edited_copy and isinstance(self.copy_result, dict):
|
||||
self.copy_result = {**self.copy_result, "voiceover_script": edited_copy}
|
||||
self.generated_copy_text = edited_copy
|
||||
self.status = ViralVideoStatus.RUNNING
|
||||
self.updated_at = datetime.now(timezone.utc)
|
||||
|
||||
def resume_from_confirm(self) -> None:
|
||||
if self.status != ViralVideoStatus.WAIT_USER_CONFIRM:
|
||||
raise ValueError(f"Cannot resume from {self.status}")
|
||||
@@ -180,3 +241,14 @@ class ViralVideoJob:
|
||||
ViralVideoStatus.FAILED,
|
||||
ViralVideoStatus.CANCELLED,
|
||||
)
|
||||
|
||||
@property
|
||||
def effective_copy_text(self) -> str:
|
||||
"""TTS 用的最终口播文案:优先 copy_result.voiceover_script,兼容老字段。"""
|
||||
if isinstance(self.copy_result, dict) and self.copy_result.get("voiceover_script"):
|
||||
return self.copy_result["voiceover_script"]
|
||||
return self.generated_copy_text or self.user_copy_text or "你好,给大家推荐一款好物"
|
||||
|
||||
@property
|
||||
def voiceover_script(self) -> str:
|
||||
return self.effective_copy_text
|
||||
|
||||
@@ -185,19 +185,6 @@ def _execute_with_gate_impl(
|
||||
is_member = getattr(user, "is_member", False)
|
||||
member_type = getattr(user, "member_type", None)
|
||||
|
||||
if scene_key == "ai_video":
|
||||
from packages.domain.points_service import PointsService
|
||||
|
||||
svc = PointsService()
|
||||
if not is_member:
|
||||
if svc.check_daily_free_clip(user.id, db):
|
||||
svc.record_daily_free_clip(user.id, db)
|
||||
kwargs["_points_deducted"] = 0
|
||||
kwargs["_is_free_quota"] = True
|
||||
if is_async:
|
||||
return _run_async_impl(func, args, _filter_kwargs_impl(func, kwargs))
|
||||
return func(*args, **_filter_kwargs_impl(func, kwargs))
|
||||
|
||||
if per_unit is not None:
|
||||
total_points = per_unit
|
||||
else:
|
||||
|
||||
@@ -13,16 +13,156 @@ API 和 Worker 两边共用。基于火山引擎方舟平台的 OpenAI 兼容接
|
||||
from __future__ import annotations
|
||||
|
||||
import logging
|
||||
import os
|
||||
import time
|
||||
import uuid
|
||||
from typing import Any, Optional
|
||||
|
||||
import httpx
|
||||
|
||||
from packages.shared.config import get_shared_settings
|
||||
|
||||
# 网络/超时类异常父类集合:覆盖 Timeout/Connect/Network/ReadTimeout/WriteTimeout/PoolTimeout
|
||||
_HTTP_NETWORK_ERRORS = ()
|
||||
try:
|
||||
_HTTP_NETWORK_ERRORS = (httpx.TimeoutException, httpx.NetworkError)
|
||||
except Exception:
|
||||
_HTTP_NETWORK_ERRORS = (Exception,)
|
||||
|
||||
_HTTP_STATUS_ERROR = httpx.HTTPStatusError if hasattr(httpx, "HTTPStatusError") else Exception
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
# 视频模型 ID 解析逻辑(#2159 多模型支持,#2170 方舟信任链统一走方舟)。
|
||||
# 内部使用简短别名(seedance-2.5 / seedance-2.0 / wan-3.0 等)做 PRICING key;
|
||||
# 实际调用时按 VIRAL_VIDEO_MODEL_CONFIG(domain/points_rules.py)的 provider/model_id 分发。
|
||||
# - provider=doubao → 火山方舟 Seedance(含信任链真人 AI 化)
|
||||
# - provider=dashscope → 阿里云 DashScope(Wan 系列,可选)
|
||||
|
||||
|
||||
def _resolve_video_provider_and_id(model: str | None) -> tuple[str, str, dict]:
|
||||
"""把内部 model key 解析成 (provider, model_id, cfg)。
|
||||
|
||||
- provider: "doubao" | "dashscope"
|
||||
- model_id: 对应 API 的真实模型 ID
|
||||
- cfg: VIRAL_VIDEO_MODEL_CONFIG 条目
|
||||
未识别或空值回落到默认 seedance-2.5。已经是 doubao-/ep- 开头的完整 ID 视为 doubao provider。
|
||||
"""
|
||||
from packages.domain.points_rules import get_viral_video_model_config
|
||||
|
||||
settings = get_shared_settings()
|
||||
default_id = getattr(settings, "doubao_video_model", None) or "doubao-seedance-2-5-260628"
|
||||
m = (model or "").strip()
|
||||
if not m:
|
||||
cfg = get_viral_video_model_config("seedance-2.5")
|
||||
return "doubao", default_id, cfg
|
||||
# 已经是 doubao-/ep- 开头:直接透传,默认视为 doubao provider
|
||||
if m.startswith("doubao-") or m.startswith("ep-"):
|
||||
return "doubao", m, {"provider": "doubao", "model_id": m, "supports_audio": True}
|
||||
# 别名 → 从 domain config 查
|
||||
cfg = get_viral_video_model_config(m)
|
||||
provider = cfg.get("provider", "doubao")
|
||||
resolved_id = cfg.get("model_id", "")
|
||||
if not resolved_id:
|
||||
logger.warning("[ai_client] model %r 无 model_id,回落到默认 %s", m, default_id)
|
||||
return "doubao", default_id, cfg
|
||||
return provider, resolved_id, cfg
|
||||
|
||||
|
||||
def _resolve_video_model_id(model: str | None) -> str:
|
||||
"""兼容旧调用:只返回 doubao model_id。wan/dashscope 调用方应直接用 _resolve_video_provider_and_id。"""
|
||||
_provider, mid, _cfg = _resolve_video_provider_and_id(model)
|
||||
return mid
|
||||
|
||||
|
||||
# ── 视频错误分类(给前端/用户展示友好提示)────────────────────────────
|
||||
|
||||
|
||||
def _classify_video_error(status_code: int, body: str, err: Exception | None) -> tuple[str, str]:
|
||||
"""根据 HTTP 状态码和响应 body 判断错误类型。
|
||||
|
||||
返回 (error_code, user_message):
|
||||
- error_code: 机器可读的错误码("portrait_intercept" / "quota_exceeded" / "model_not_found"
|
||||
/ "invalid_param" / "auth_error" / "rate_limit" / "network_error" / "task_failed" / "unknown")
|
||||
- user_message: 给用户看的中文提示
|
||||
"""
|
||||
body_lower = (body or "").lower()
|
||||
code_in_body = ""
|
||||
msg_in_body = ""
|
||||
try:
|
||||
import json as _json
|
||||
|
||||
parsed = _json.loads(body or "{}")
|
||||
if isinstance(parsed, dict):
|
||||
err_obj = parsed.get("error") or {}
|
||||
if isinstance(err_obj, dict):
|
||||
code_in_body = str(err_obj.get("code", "") or "")
|
||||
msg_in_body = str(err_obj.get("message", "") or err_obj.get("msg", "") or "")
|
||||
else:
|
||||
msg_in_body = str(parsed.get("message", "") or "")
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
# 真人肖像/内容安全拦截
|
||||
if (
|
||||
status_code == 400
|
||||
and any(
|
||||
kw in body_lower
|
||||
for kw in ("portrait", "real_face", "human_face", "真人", "肖像", "人脸", "privacy", "real person", "face")
|
||||
)
|
||||
) or (
|
||||
"content" in body_lower
|
||||
and ("risk" in body_lower or "block" in body_lower or "reject" in body_lower)
|
||||
and status_code == 400
|
||||
):
|
||||
return (
|
||||
"portrait_intercept",
|
||||
"参考素材包含真人照片被安全策略拦截,AI视频模型暂不支持上传真人照片作为参考图,请移除真人图片后重试。",
|
||||
)
|
||||
|
||||
# 配额/计费问题
|
||||
if status_code in (402, 429) or any(
|
||||
kw in body_lower for kw in ("quota", "billing", "insufficient", "欠费", "余额", "限流", "rate limit")
|
||||
):
|
||||
if "rate" in body_lower or status_code == 429:
|
||||
return "rate_limit", "视频生成服务当前繁忙(限流),请稍等1-2分钟后重试。"
|
||||
return "quota_exceeded", "视频生成服务配额不足,请联系管理员充值或稍后重试。"
|
||||
|
||||
# 模型/Endpoint 不存在
|
||||
if status_code == 404 or any(
|
||||
kw in body_lower for kw in ("model not found", "endpoint not found", "不存在", "not found", "model_not_exist")
|
||||
):
|
||||
return "model_not_found", f"视频模型未开通或模型ID无效({code_in_body or ''}),请联系管理员。"
|
||||
|
||||
# 鉴权失败
|
||||
if status_code in (401, 403):
|
||||
return "auth_error", "视频生成服务鉴权失败(API Key无效或过期),请联系管理员。"
|
||||
|
||||
# 任务本身失败(轮询阶段拿到 status=failed)
|
||||
if err and "task failed" in str(err).lower():
|
||||
detail = msg_in_body or str(err)[:200]
|
||||
# 失败原因里再细分真人拦截
|
||||
if any(kw in detail.lower() for kw in ("portrait", "真人", "肖像", "人脸", "content_risk")):
|
||||
return (
|
||||
"portrait_intercept",
|
||||
"视频内容被安全策略拦截(疑似包含真人肖像),请更换参考图或调整文案后重试。",
|
||||
)
|
||||
return "task_failed", f"视频生成失败:{detail}"
|
||||
|
||||
# 参数错误
|
||||
if status_code == 400:
|
||||
return "invalid_param", f"视频生成参数错误:{msg_in_body or body[:200]}"
|
||||
|
||||
# 网络/连接问题
|
||||
if status_code == 0:
|
||||
return "network_error", "视频生成服务连接失败(网络超时),请稍后重试。"
|
||||
|
||||
# 默认
|
||||
detail = msg_in_body or (str(err) if err else "") or body[:200]
|
||||
return "unknown", f"视频生成失败(HTTP {status_code}):{detail}"
|
||||
|
||||
|
||||
class DoubaoClient:
|
||||
"""豆包大模型 API 客户端.
|
||||
|
||||
@@ -38,6 +178,15 @@ class DoubaoClient:
|
||||
self.timeout: int = settings.doubao_timeout
|
||||
self.max_retries: int = settings.doubao_max_retries
|
||||
self.vision_model: str = settings.doubao_vision_model
|
||||
self.vision_lite_model: str = settings.doubao_vision_lite_model
|
||||
self.fast_model: str = settings.doubao_fast_model
|
||||
self.embedding_model: str = settings.doubao_embedding_model
|
||||
self.image_model: str = settings.doubao_image_model
|
||||
self.image_timeout: int = getattr(settings, "doubao_image_timeout", 120) or 120
|
||||
# 最近一次视频生成的详细错误(error_code + user_message + raw detail),供上层读取后展示给用户
|
||||
self.last_video_error: dict = {}
|
||||
# 最近一次图片生成的详细错误,供上层读取
|
||||
self.last_image_error: dict = {}
|
||||
|
||||
def embed_text(self, text: str, timeout: int | None = None) -> list[float] | None:
|
||||
"""调用豆包文本 Embedding API,返回浮点向量;失败返回 None。"""
|
||||
@@ -50,7 +199,7 @@ class DoubaoClient:
|
||||
"Content-Type": "application/json",
|
||||
}
|
||||
payload: dict[str, Any] = {
|
||||
"model": getattr(self, "embedding_model", None) or "doubao-embedding-large-text-240915",
|
||||
"model": self.embedding_model,
|
||||
"input": text.strip(),
|
||||
"encoding_format": "float",
|
||||
}
|
||||
@@ -90,6 +239,7 @@ class DoubaoClient:
|
||||
messages: list[dict[str, str]],
|
||||
temperature: float = 0.7,
|
||||
max_tokens: int = 1024,
|
||||
model: str | None = None,
|
||||
) -> Optional[str]:
|
||||
"""调用 Chat Completion 接口.
|
||||
|
||||
@@ -110,13 +260,14 @@ class DoubaoClient:
|
||||
"Content-Type": "application/json",
|
||||
}
|
||||
payload: dict[str, Any] = {
|
||||
"model": self.model,
|
||||
"model": model or self.model,
|
||||
"messages": messages,
|
||||
"temperature": temperature,
|
||||
"max_tokens": max_tokens,
|
||||
}
|
||||
|
||||
last_error: Optional[Exception] = None
|
||||
_t0 = time.time()
|
||||
for attempt in range(self.max_retries + 1):
|
||||
try:
|
||||
response = httpx.post(
|
||||
@@ -128,21 +279,31 @@ class DoubaoClient:
|
||||
response.raise_for_status()
|
||||
data = response.json()
|
||||
content = data["choices"][0]["message"]["content"]
|
||||
_elapsed = time.time() - _t0
|
||||
logger.info(
|
||||
"[doubao] chat_completion 完成 model=%s tokens_in=%d tokens_out=%d elapsed=%.1fs attempt=%d",
|
||||
payload.get("model"),
|
||||
data.get("usage", {}).get("prompt_tokens", 0),
|
||||
data.get("usage", {}).get("completion_tokens", 0),
|
||||
_elapsed,
|
||||
attempt + 1,
|
||||
)
|
||||
return content.strip()
|
||||
except Exception as e:
|
||||
last_error = e
|
||||
if attempt < self.max_retries:
|
||||
wait = 0.5 * (2**attempt)
|
||||
logger.warning(
|
||||
"豆包API调用失败,%.1fs后重试 (第%d/%d次): %s",
|
||||
"豆包API调用失败,%.1fs后重试 (第%d/%d次, elapsed=%.1fs): %s",
|
||||
wait,
|
||||
attempt + 1,
|
||||
self.max_retries + 1,
|
||||
time.time() - _t0,
|
||||
e,
|
||||
)
|
||||
time.sleep(wait)
|
||||
|
||||
logger.error("豆包API调用最终失败: %s", last_error)
|
||||
logger.error("豆包API调用最终失败: elapsed=%.1fs err=%s", time.time() - _t0, last_error)
|
||||
return None
|
||||
|
||||
def vision_completion(
|
||||
@@ -152,11 +313,12 @@ class DoubaoClient:
|
||||
max_tokens: int = 2048,
|
||||
temperature: float = 0.3,
|
||||
timeout: int | None = None,
|
||||
model: str | None = None,
|
||||
) -> Optional[str]:
|
||||
"""调用豆包视觉理解 API(OpenAI 兼容多模态格式).
|
||||
|
||||
将 images 附加到最后一条 user message 的 content 中,
|
||||
使用 vision_model(默认 doubao-1-5-vision-pro-250915)。
|
||||
使用 vision_model(默认 doubao-1-5-vision-pro-250328)。
|
||||
|
||||
Args:
|
||||
messages: 对话消息列表。最后一条 user message 会被注入图片内容。
|
||||
@@ -202,7 +364,7 @@ class DoubaoClient:
|
||||
"Content-Type": "application/json",
|
||||
}
|
||||
payload: dict[str, Any] = {
|
||||
"model": self.vision_model,
|
||||
"model": model or self.vision_model,
|
||||
"messages": vision_messages,
|
||||
"temperature": temperature,
|
||||
"max_tokens": max_tokens,
|
||||
@@ -210,6 +372,7 @@ class DoubaoClient:
|
||||
|
||||
req_timeout = timeout or self.timeout
|
||||
last_error: Optional[Exception] = None
|
||||
_t0 = time.time()
|
||||
for attempt in range(self.max_retries + 1):
|
||||
try:
|
||||
response = httpx.post(
|
||||
@@ -221,23 +384,713 @@ class DoubaoClient:
|
||||
response.raise_for_status()
|
||||
data = response.json()
|
||||
content = data["choices"][0]["message"]["content"]
|
||||
_elapsed = time.time() - _t0
|
||||
logger.info(
|
||||
"[doubao] vision_completion 完成 model=%s tokens_in=%d tokens_out=%d elapsed=%.1fs attempt=%d",
|
||||
payload.get("model"),
|
||||
data.get("usage", {}).get("prompt_tokens", 0),
|
||||
data.get("usage", {}).get("completion_tokens", 0),
|
||||
_elapsed,
|
||||
attempt + 1,
|
||||
)
|
||||
return content.strip()
|
||||
except Exception as e:
|
||||
last_error = e
|
||||
if attempt < self.max_retries:
|
||||
wait = 0.5 * (2**attempt)
|
||||
logger.warning(
|
||||
"豆包视觉API调用失败,%.1fs后重试 (第%d/%d次): %s",
|
||||
"豆包视觉API调用失败,%.1fs后重试 (第%d/%d次, elapsed=%.1fs): %s",
|
||||
wait,
|
||||
attempt + 1,
|
||||
self.max_retries + 1,
|
||||
time.time() - _t0,
|
||||
e,
|
||||
)
|
||||
time.sleep(wait)
|
||||
|
||||
logger.error("豆包视觉API调用最终失败: %s", last_error)
|
||||
logger.error("豆包视觉API调用最终失败: elapsed=%.1fs err=%s", time.time() - _t0, last_error)
|
||||
return None
|
||||
|
||||
# ── 视频生成(Seedance 2.5,异步任务)────────────────────────────
|
||||
|
||||
def preheat_trust_chain(
|
||||
self,
|
||||
portrait_urls: list[str],
|
||||
*,
|
||||
timeout: int = 120,
|
||||
) -> list[str] | None:
|
||||
"""#2172 信任链预热:对一组人像 URL 执行 Seedream AI 化,返回 AI 化后的 URL 列表。
|
||||
|
||||
- 全部成功返回 list[str](顺序与输入一致)
|
||||
- 任何一张失败返回 None(保留上层回退原图直传的路径)
|
||||
- 供 worker 在视频生成前并行预热使用;video_generation 内部若收到 preheated 结果会直接使用,不再现场跑。
|
||||
"""
|
||||
if not portrait_urls or not self.is_available:
|
||||
return None
|
||||
seedream_prompt = (
|
||||
"保持此人五官特征、发型、肤色、面部轮廓、年龄感,生成一张高清写实人像照片,"
|
||||
"人物外貌特征与参考图完全一致,皮肤自然,光线柔和,高清细节,不要过度美化。"
|
||||
)
|
||||
trusted: list[str] = []
|
||||
_t0 = time.time()
|
||||
for idx, raw_url in enumerate(portrait_urls):
|
||||
sd_prompt = seedream_prompt if len(portrait_urls) == 1 else f"{seedream_prompt}(这是参考图{idx + 1})"
|
||||
sd_result = self.image_generation(
|
||||
prompt=sd_prompt,
|
||||
reference_images=[raw_url],
|
||||
size="2K",
|
||||
timeout=timeout,
|
||||
)
|
||||
if not sd_result:
|
||||
logger.warning(
|
||||
"[trust-chain][preheat] Seedream 第 %d/%d 张失败: %s,预热整体失败",
|
||||
idx + 1,
|
||||
len(portrait_urls),
|
||||
getattr(self, "last_image_error", None),
|
||||
)
|
||||
return None
|
||||
trusted.append(sd_result["url"])
|
||||
logger.info(
|
||||
"[trust-chain][preheat] Seedream AI 化预热完成 %d 张,总耗时 %.1fs",
|
||||
len(trusted),
|
||||
time.time() - _t0,
|
||||
)
|
||||
return trusted
|
||||
|
||||
def video_generation(
|
||||
self,
|
||||
prompt: str,
|
||||
*,
|
||||
image_url: str | None = None,
|
||||
duration: int = 5,
|
||||
ratio: str | None = "9:16",
|
||||
resolution: str = "720p",
|
||||
generate_audio: bool = True,
|
||||
watermark: bool = False,
|
||||
output_dir: str | None = None,
|
||||
model: str | None = None,
|
||||
reference_images: list[str] | None = None,
|
||||
reference_audios: list[str] | None = None,
|
||||
reference_videos: list[str] | None = None,
|
||||
pre_trusted_images: list[str] | None = None,
|
||||
) -> dict | None:
|
||||
"""调用 Seedance 2.5 生视频(异步任务→轮询→下载)。
|
||||
|
||||
成功返回 {"video_path": str, "usage": dict | None},失败返回 None。
|
||||
失败时把详细错误信息(HTTP状态码、响应 body、分类后的用户提示)写入 self.last_video_error,
|
||||
上层可通过 get_last_video_error() 读取并展示给用户,不再笼统显示"返回为空"。
|
||||
|
||||
【v1.6.1 修复】严格按官方 content 数组协议构造请求:
|
||||
- 所有参考(图/音/视)必须放进 content 数组并带 role 字段,不能放顶层 reference_audios/reference_videos(非官方字段,会被忽略或导致异常)。
|
||||
- 首帧图(first_frame 模式)Seedance 2.5 强制 ratio=adaptive;走 omni_reference(参考生视频)模式时才能指定 9:16/1:1 等具体比例。
|
||||
判定:传了参考音频/视频或 ≥1 张多参考图时,走 omni_reference(首张图 role=reference_image);纯首帧无参考时走 first_frame(ratio 强制 adaptive)。
|
||||
- 创建任务若因 ratio 报错(HTTP 400),自动回退到 ratio=adaptive 重试一次。
|
||||
"""
|
||||
# 每次调用前清空上次错误
|
||||
self.last_video_error = {}
|
||||
|
||||
if not self.is_available:
|
||||
self.last_video_error = {
|
||||
"error_code": "auth_error",
|
||||
"user_message": "视频生成服务未配置(API Key 缺失),请联系管理员。",
|
||||
"status_code": 0,
|
||||
"detail": "DoubaoClient not available (api_key empty)",
|
||||
}
|
||||
return None
|
||||
if not prompt or not prompt.strip():
|
||||
self.last_video_error = {
|
||||
"error_code": "invalid_param",
|
||||
"user_message": "视频生成提示词不能为空。",
|
||||
"status_code": 0,
|
||||
"detail": "empty prompt",
|
||||
}
|
||||
return None
|
||||
|
||||
settings = get_shared_settings()
|
||||
poll_interval = getattr(settings, "doubao_video_poll_interval", 10) or 10
|
||||
# 收紧总超时:轮询 8min + 下载 2min = 最长 ~10min,防止出现 20min 卡死
|
||||
total_timeout = getattr(settings, "doubao_video_timeout", 480) or 480
|
||||
# 内部 key → (provider, 实际模型 ID, cfg),按 provider 分发
|
||||
provider, video_model, model_cfg = _resolve_video_provider_and_id(model)
|
||||
if provider == "dashscope":
|
||||
from packages.shared.dashscope_client import get_dashscope_client
|
||||
|
||||
ds = get_dashscope_client()
|
||||
if ds is None:
|
||||
err_msg = "DashScope client 不可用(未配置 DASHSCOPE_API_KEY)"
|
||||
logger.error("%s, video_model=%s", err_msg, model)
|
||||
self.last_video_error = {
|
||||
"error_code": "auth_error",
|
||||
"user_message": "Wan 3.0 视频模型未配置 API Key,请联系管理员。",
|
||||
"status_code": 0,
|
||||
"detail": err_msg,
|
||||
}
|
||||
return None
|
||||
try:
|
||||
# DashScope 客户端也设置 last_video_error 语义(如果它支持)
|
||||
if hasattr(ds, "last_video_error"):
|
||||
ds.last_video_error = {}
|
||||
result = ds.video_generation(
|
||||
prompt=prompt,
|
||||
image_url=image_url,
|
||||
duration=duration,
|
||||
ratio=ratio,
|
||||
resolution=resolution,
|
||||
output_dir=output_dir,
|
||||
model=video_model,
|
||||
)
|
||||
if not result and hasattr(ds, "last_video_error") and ds.last_video_error:
|
||||
self.last_video_error = dict(ds.last_video_error)
|
||||
return result
|
||||
except Exception as de:
|
||||
logger.error("DashScope video_generation 异常: %s", de, exc_info=True)
|
||||
self.last_video_error = {
|
||||
"error_code": "unknown",
|
||||
"user_message": f"Wan 3.0 视频生成异常:{de!s}"[:200],
|
||||
"status_code": 0,
|
||||
"detail": str(de),
|
||||
}
|
||||
return None
|
||||
|
||||
ref_audios = [u for u in (reference_audios or [])[:10] if u and isinstance(u, str)]
|
||||
ref_videos = [u for u in (reference_videos or [])[:3] if u and isinstance(u, str)]
|
||||
ref_imgs = [u for u in (reference_images or [])[:9] if u and isinstance(u, str)]
|
||||
|
||||
# ── #2170/#2172 方舟信任链(Trust Chain)────────────────────────────────
|
||||
# 真人照片直接传给 Seedance 会触发 50411 肖像审核拦截。
|
||||
# 解决:先通过同账号的 Seedream 5.0 Pro 图生图 AI 化(保持五官特征),
|
||||
# 得到的 AI 产物图属于"模型信任产物",再作为 reference_image 传给 Seedance 即可通过审核。
|
||||
# #2172: 支持预热结果 pre_trusted_images(worker 在文案阶段并行预热,省掉串行等待);
|
||||
# 预热结果有效则直接使用,否则现场跑一次 Seedream AI 化。
|
||||
# 信任链只作用于 doubao provider;DashScope(Wan) 保持原行为。
|
||||
trust_chain_applied = False
|
||||
if provider == "doubao":
|
||||
raw_portrait_urls: list[str] = []
|
||||
if image_url:
|
||||
raw_portrait_urls.append(image_url)
|
||||
for u in ref_imgs:
|
||||
if u not in raw_portrait_urls:
|
||||
raw_portrait_urls.append(u)
|
||||
trusted_urls: list[str] = []
|
||||
if pre_trusted_images and len(pre_trusted_images) == len(raw_portrait_urls):
|
||||
# #2172: 使用预热结果
|
||||
trusted_urls = list(pre_trusted_images)
|
||||
trust_chain_applied = True
|
||||
logger.info(
|
||||
"[trust-chain] 使用预热结果 %d 张,替换为 reference_image 模式",
|
||||
len(trusted_urls),
|
||||
)
|
||||
elif raw_portrait_urls:
|
||||
# 现场跑信任链
|
||||
_tc_t0 = time.time()
|
||||
trusted_urls = self.preheat_trust_chain(raw_portrait_urls) or []
|
||||
if trusted_urls and len(trusted_urls) == len(raw_portrait_urls):
|
||||
trust_chain_applied = True
|
||||
logger.info(
|
||||
"[trust-chain] Seedream AI 化完成 %d 张,总耗时 %.1fs,替换为 reference_image 模式",
|
||||
len(trusted_urls),
|
||||
time.time() - _tc_t0,
|
||||
)
|
||||
else:
|
||||
logger.warning(
|
||||
"[trust-chain] Seedream AI 化不完整(%d/%d),总耗时 %.1fs,回退原图直传",
|
||||
len(trusted_urls),
|
||||
len(raw_portrait_urls),
|
||||
time.time() - _tc_t0,
|
||||
)
|
||||
if trust_chain_applied and trusted_urls:
|
||||
# 替换:原 image_url 用第一张 AI 图,ref_imgs 用剩余
|
||||
if image_url and trusted_urls:
|
||||
image_url = trusted_urls[0]
|
||||
ref_imgs = trusted_urls[1:] if len(trusted_urls) > 1 else []
|
||||
else:
|
||||
ref_imgs = trusted_urls
|
||||
# ─────────────────────────────────────────────────────────────────
|
||||
|
||||
# 判断任务模式:
|
||||
# - 信任链强制走 reference_image(不是 first_frame;产品语义是人物参考,不是从图开始动)
|
||||
# - 有参考音/视/多图 → omni_reference(支持指定 ratio)
|
||||
# - 纯首帧无其他参考 → first_frame(ratio=adaptive)
|
||||
has_extra_refs = bool(ref_audios or ref_videos or ref_imgs)
|
||||
is_first_frame_mode = bool(image_url) and not has_extra_refs and not trust_chain_applied
|
||||
# 最终 ratio:first_frame 模式强制 adaptive,否则按用户传值(默认 9:16)
|
||||
final_ratio = "adaptive" if is_first_frame_mode else (ratio or "9:16")
|
||||
|
||||
# 构造 content 数组:text + 图 + 音 + 视
|
||||
content: list[dict[str, Any]] = [{"type": "text", "text": prompt.strip()}]
|
||||
if image_url:
|
||||
if has_extra_refs or trust_chain_applied:
|
||||
# omni_reference 或信任链模式:首张图作为 reference_image,允许指定 ratio
|
||||
content.append(
|
||||
{
|
||||
"type": "image_url",
|
||||
"image_url": {"url": image_url},
|
||||
"role": "reference_image",
|
||||
}
|
||||
)
|
||||
else:
|
||||
# 纯首帧:显式 role=first_frame
|
||||
content.append(
|
||||
{
|
||||
"type": "image_url",
|
||||
"image_url": {"url": image_url},
|
||||
"role": "first_frame",
|
||||
}
|
||||
)
|
||||
for u in ref_imgs:
|
||||
content.append({"type": "image_url", "image_url": {"url": u}, "role": "reference_image"})
|
||||
for u in ref_audios:
|
||||
content.append({"type": "audio_url", "audio_url": {"url": u}, "role": "reference_audio"})
|
||||
for u in ref_videos:
|
||||
content.append({"type": "video_url", "video_url": {"url": u}, "role": "reference_video"})
|
||||
|
||||
create_payload: dict[str, Any] = {
|
||||
"model": video_model,
|
||||
"content": content,
|
||||
"generate_audio": bool(generate_audio),
|
||||
"duration": int(duration),
|
||||
"resolution": resolution,
|
||||
"watermark": bool(watermark),
|
||||
"ratio": final_ratio,
|
||||
}
|
||||
|
||||
headers = {
|
||||
"Authorization": f"Bearer {self.api_key}",
|
||||
"Content-Type": "application/json",
|
||||
}
|
||||
create_url = f"{self.base_url}/contents/generations/tasks"
|
||||
logger.info(
|
||||
"Seedance 创建任务: model=%s dur=%ds ratio=%s mode=%s gen_audio=%s img=%d aud=%d vid=%d",
|
||||
video_model,
|
||||
duration,
|
||||
final_ratio,
|
||||
"first_frame" if is_first_frame_mode else ("omni_ref+trust_chain" if trust_chain_applied else "omni_ref"),
|
||||
generate_audio,
|
||||
(1 if image_url else 0) + len(ref_imgs),
|
||||
len(ref_audios),
|
||||
len(ref_videos),
|
||||
)
|
||||
# 打印完整 payload 便于排查(截断 prompt)
|
||||
debug_payload = dict(create_payload)
|
||||
if "content" in debug_payload:
|
||||
dbg_content = []
|
||||
for item in debug_payload["content"]:
|
||||
item_copy = dict(item)
|
||||
if item_copy.get("type") == "text" and isinstance(item_copy.get("text"), str):
|
||||
item_copy["text"] = item_copy["text"][:200] + ("..." if len(item_copy["text"]) > 200 else "")
|
||||
dbg_content.append(item_copy)
|
||||
debug_payload["content"] = dbg_content
|
||||
logger.info("Seedance 创建任务 payload: %s", json_safe_dumps(debug_payload))
|
||||
|
||||
def _do_create(payload: dict) -> tuple[str | None, Exception | None, int, str]:
|
||||
"""返回 (task_id, last_err, status_code, body_text)。"""
|
||||
last_err: Exception | None = None
|
||||
last_sc = 0
|
||||
last_body = ""
|
||||
for attempt in range(self.max_retries + 1):
|
||||
try:
|
||||
resp = httpx.post(create_url, headers=headers, json=payload, timeout=self.timeout)
|
||||
sc = int(getattr(resp, "status_code", 0) or 0)
|
||||
body = (getattr(resp, "text", "") or "")[:2000]
|
||||
last_sc = sc
|
||||
last_body = body
|
||||
if sc >= 400:
|
||||
logger.error("Seedance 创建任务 HTTP %d: body=%s", sc, body)
|
||||
try:
|
||||
resp.raise_for_status()
|
||||
except Exception as ee:
|
||||
last_err = ee
|
||||
if attempt < self.max_retries and sc >= 500:
|
||||
# 仅 5xx 重试,4xx 不重试(参数/鉴权/配额错误重试无意义)
|
||||
time.sleep(0.5 * (2**attempt))
|
||||
continue
|
||||
return None, last_err, sc, body
|
||||
data = resp.json()
|
||||
tid = data.get("id")
|
||||
if tid:
|
||||
return tid, None, sc, body
|
||||
last_err = RuntimeError(f"create ok but no id: {str(data)[:300]}")
|
||||
except _HTTP_NETWORK_ERRORS as ne:
|
||||
last_err = ne
|
||||
last_sc = 0
|
||||
last_body = f"network error: {ne}"
|
||||
logger.warning(
|
||||
"Seedance 创建网络异常(%s),重试 %d/%d", type(ne).__name__, attempt + 1, self.max_retries + 1
|
||||
)
|
||||
if attempt < self.max_retries:
|
||||
time.sleep(0.5 * (2**attempt))
|
||||
continue
|
||||
except Exception as e:
|
||||
last_err = e
|
||||
if attempt < self.max_retries and not isinstance(e, _HTTP_STATUS_ERROR):
|
||||
wait = 0.5 * (2**attempt)
|
||||
logger.warning(
|
||||
"Seedance 创建任务失败,%.1fs 后重试 (%d/%d): %s",
|
||||
wait,
|
||||
attempt + 1,
|
||||
self.max_retries + 1,
|
||||
e,
|
||||
)
|
||||
time.sleep(wait)
|
||||
return None, last_err, last_sc, last_body
|
||||
|
||||
# 第一次尝试
|
||||
task_id, last_err, sc, body = _do_create(create_payload)
|
||||
|
||||
# ratio 兜底:HTTP 400 且 body 提到 ratio / adaptive → 回退 adaptive 再试一次
|
||||
if (
|
||||
not task_id
|
||||
and sc == 400
|
||||
and final_ratio != "adaptive"
|
||||
and (
|
||||
"ratio" in (body or "").lower()
|
||||
or "aspect" in (body or "").lower()
|
||||
or "adaptive" in (body or "").lower()
|
||||
)
|
||||
):
|
||||
logger.warning("Seedance 创建因 ratio 失败,回退 ratio=adaptive 重试")
|
||||
create_payload["ratio"] = "adaptive"
|
||||
task_id, last_err, sc2, body2 = _do_create(create_payload)
|
||||
if task_id:
|
||||
sc, body = sc2, body2
|
||||
else:
|
||||
# 保留第二次的错误信息
|
||||
sc, body = sc2, body2
|
||||
|
||||
if not task_id:
|
||||
err_code, user_msg = _classify_video_error(sc, body, last_err)
|
||||
self.last_video_error = {
|
||||
"error_code": err_code,
|
||||
"user_message": user_msg,
|
||||
"status_code": sc,
|
||||
"detail": (body or "")[:500] or (str(last_err) if last_err else ""),
|
||||
"model": video_model,
|
||||
"base_url": self.base_url,
|
||||
}
|
||||
logger.error(
|
||||
"Seedance 创建任务最终失败: model=%s base_url=%s status=%d code=%s err=%s body=%s",
|
||||
video_model,
|
||||
self.base_url,
|
||||
sc,
|
||||
err_code,
|
||||
last_err,
|
||||
(body or "")[:500],
|
||||
)
|
||||
return None
|
||||
|
||||
logger.info("Seedance 任务已创建: task_id=%s ratio=%s", task_id, create_payload["ratio"])
|
||||
|
||||
# 2) 轮询状态
|
||||
poll_url = f"{create_url}/{task_id}"
|
||||
deadline = time.time() + total_timeout
|
||||
video_url: str | None = None
|
||||
usage: dict | None = None
|
||||
last_status: str = "queued"
|
||||
poll_count = 0
|
||||
last_poll_body: str = ""
|
||||
last_poll_sc: int = 0
|
||||
while time.time() < deadline:
|
||||
poll_count += 1
|
||||
try:
|
||||
resp = httpx.get(poll_url, headers=headers, timeout=self.timeout)
|
||||
last_poll_sc = int(getattr(resp, "status_code", 200) or 200)
|
||||
last_poll_body = (getattr(resp, "text", "") or "")[:1500]
|
||||
if last_poll_sc >= 400:
|
||||
logger.warning("Seedance 轮询 HTTP %d: %s", last_poll_sc, last_poll_body[:300])
|
||||
if poll_count < 3:
|
||||
time.sleep(poll_interval)
|
||||
continue
|
||||
last_err = RuntimeError(f"poll HTTP {last_poll_sc}: {last_poll_body[:200]}")
|
||||
break
|
||||
data = resp.json()
|
||||
status = data.get("status", "")
|
||||
last_status = status
|
||||
if status == "succeeded":
|
||||
content_obj = data.get("content") or {}
|
||||
video_url = content_obj.get("video_url")
|
||||
usage = data.get("usage") or content_obj.get("usage") or None
|
||||
if video_url:
|
||||
logger.info("Seedance 任务成功: task_id=%s polls=%d usage=%s", task_id, poll_count, usage)
|
||||
break
|
||||
# 成功但没 video_url:记录完整响应便于排查
|
||||
logger.error(
|
||||
"Seedance succeeded 但无 video_url: task_id=%s full_response=%s",
|
||||
task_id,
|
||||
str(data)[:1000],
|
||||
)
|
||||
last_err = RuntimeError("task succeeded but no video_url in response")
|
||||
last_poll_body = str(data)[:1000]
|
||||
break
|
||||
if status == "failed":
|
||||
err = data.get("error") or {}
|
||||
err_code = str(err.get("code", "") or "")
|
||||
err_msg = str(err.get("message", "") or err.get("msg", "") or "")
|
||||
last_err = RuntimeError(f"task failed: code={err_code} msg={err_msg}")
|
||||
logger.error("Seedance 任务失败 task_id=%s code=%s msg=%s", task_id, err_code, err_msg)
|
||||
last_poll_body = str(data)[:1000]
|
||||
break
|
||||
if status in ("expired", "cancelled"):
|
||||
last_err = RuntimeError(f"task {status}")
|
||||
logger.error("Seedance 任务 %s: task_id=%s", status, task_id)
|
||||
break
|
||||
# 每 5 次轮询打一次 info 日志,便于观察进度
|
||||
if poll_count % 5 == 0:
|
||||
logger.info("Seedance 轮询中: task_id=%s status=%s polls=%d", task_id, status, poll_count)
|
||||
except httpx.HTTPStatusError as e:
|
||||
last_err = e
|
||||
last_poll_sc = e.response.status_code
|
||||
last_poll_body = (e.response.text or "")[:500]
|
||||
logger.warning("Seedance 轮询 HTTP %d: %s", e.response.status_code, last_poll_body[:300])
|
||||
except Exception as e:
|
||||
last_err = e
|
||||
logger.debug("Seedance 轮询异常: %s", e)
|
||||
time.sleep(poll_interval)
|
||||
|
||||
if not video_url:
|
||||
# 区分轮询超时 vs 任务失败
|
||||
if last_status in ("queued", "running", "pending") and poll_count > 0 and time.time() >= deadline:
|
||||
err_code, user_msg = (
|
||||
"network_error",
|
||||
f"视频生成超时(>{total_timeout}s),任务仍在排队,请稍后重试或联系管理员。",
|
||||
)
|
||||
detail = f"timeout after {total_timeout}s, polls={poll_count}, last_status={last_status}"
|
||||
else:
|
||||
err_code, user_msg = _classify_video_error(last_poll_sc, last_poll_body, last_err)
|
||||
detail = (last_poll_body or "")[:500] or (str(last_err) if last_err else f"last_status={last_status}")
|
||||
self.last_video_error = {
|
||||
"error_code": err_code,
|
||||
"user_message": user_msg,
|
||||
"status_code": last_poll_sc,
|
||||
"detail": detail,
|
||||
"task_id": task_id,
|
||||
"last_status": last_status,
|
||||
}
|
||||
logger.error(
|
||||
"Seedance 任务未成功: task_id=%s last_status=%s polls=%d code=%s err=%s (总等待 %.0fs)",
|
||||
task_id,
|
||||
last_status,
|
||||
poll_count,
|
||||
err_code,
|
||||
last_err,
|
||||
total_timeout,
|
||||
)
|
||||
return None
|
||||
|
||||
# 3) 下载到本地(下载超时收紧到 120s)
|
||||
try:
|
||||
out_dir = output_dir or "/tmp"
|
||||
os.makedirs(out_dir, exist_ok=True)
|
||||
local_path = f"{out_dir}/seedance_{task_id}_{uuid.uuid4().hex[:8]}.mp4"
|
||||
download_timeout = 120.0
|
||||
logger.info(
|
||||
"Seedance 开始下载: task_id=%s url=%s timeout=%.0fs", task_id, video_url[:120], download_timeout
|
||||
)
|
||||
with httpx.stream("GET", video_url, timeout=download_timeout) as r:
|
||||
r.raise_for_status()
|
||||
downloaded = 0
|
||||
with open(local_path, "wb") as f:
|
||||
for chunk in r.iter_bytes(chunk_size=1024 * 256):
|
||||
if chunk:
|
||||
f.write(chunk)
|
||||
downloaded += len(chunk)
|
||||
size = os.path.getsize(local_path)
|
||||
logger.info("Seedance 视频下载完成: %s size=%d bytes", local_path, size)
|
||||
if size == 0:
|
||||
logger.error("Seedance 下载文件大小为 0")
|
||||
try:
|
||||
os.remove(local_path)
|
||||
except Exception:
|
||||
pass
|
||||
self.last_video_error = {
|
||||
"error_code": "unknown",
|
||||
"user_message": "视频生成成功但下载文件为空,请稍后重试。",
|
||||
"status_code": 0,
|
||||
"detail": f"downloaded 0 bytes from {video_url[:120]}",
|
||||
}
|
||||
return None
|
||||
return {"video_path": local_path, "usage": usage}
|
||||
except Exception as e:
|
||||
logger.error("Seedance 视频下载失败: %s", e, exc_info=True)
|
||||
self.last_video_error = {
|
||||
"error_code": "network_error",
|
||||
"user_message": f"视频下载失败:{e!s}"[:200],
|
||||
"status_code": 0,
|
||||
"detail": str(e),
|
||||
}
|
||||
return None
|
||||
|
||||
def image_generation(
|
||||
self,
|
||||
prompt: str,
|
||||
*,
|
||||
reference_images: list[str] | None = None,
|
||||
size: str = "2K",
|
||||
model: str | None = None,
|
||||
watermark: bool = False,
|
||||
output_format: str = "png",
|
||||
timeout: int | None = None,
|
||||
) -> dict | None:
|
||||
"""#2170: 调用方舟 Seedream 图片生成(文生图/图生图)。
|
||||
|
||||
- reference_images: 0~10 张参考图 URL;0 张 = 纯文生图;1 张 string/URL 直传;多张 list[str]。
|
||||
- 成功返回 {"url": str, "usage": dict | None};失败返回 None,错误写入 self.last_image_error。
|
||||
- 返回的 url 有时效性(通常 24h),应立即使用,不持久化存储。
|
||||
"""
|
||||
self.last_image_error = {}
|
||||
if not self.is_available:
|
||||
self.last_image_error = {
|
||||
"error_code": "auth_error",
|
||||
"user_message": "图片生成服务未配置(API Key 缺失),请联系管理员。",
|
||||
"detail": "DoubaoClient not available (api_key empty)",
|
||||
}
|
||||
return None
|
||||
if not prompt or not prompt.strip():
|
||||
self.last_image_error = {
|
||||
"error_code": "invalid_param",
|
||||
"user_message": "图片生成提示词不能为空。",
|
||||
"detail": "empty prompt",
|
||||
}
|
||||
return None
|
||||
|
||||
img_model = model or self.image_model
|
||||
url = f"{self.base_url}/images/generations"
|
||||
headers = {
|
||||
"Authorization": f"Bearer {self.api_key}",
|
||||
"Content-Type": "application/json",
|
||||
}
|
||||
payload: dict[str, Any] = {
|
||||
"model": img_model,
|
||||
"prompt": prompt.strip(),
|
||||
"size": size,
|
||||
"response_format": "url",
|
||||
"output_format": output_format,
|
||||
"watermark": bool(watermark),
|
||||
}
|
||||
ref_imgs_local = [u for u in (reference_images or []) if u and isinstance(u, str)]
|
||||
if ref_imgs_local:
|
||||
if len(ref_imgs_local) == 1:
|
||||
payload["image"] = ref_imgs_local[0]
|
||||
else:
|
||||
payload["image"] = ref_imgs_local[:10]
|
||||
|
||||
req_timeout = timeout or self.image_timeout
|
||||
last_err: Exception | None = None
|
||||
last_sc = 0
|
||||
last_body = ""
|
||||
_img_t0 = time.time()
|
||||
for attempt in range(self.max_retries + 1):
|
||||
try:
|
||||
resp = httpx.post(url, headers=headers, json=payload, timeout=req_timeout)
|
||||
last_sc = int(getattr(resp, "status_code", 0) or 0)
|
||||
last_body = (getattr(resp, "text", "") or "")[:2000]
|
||||
if last_sc >= 400:
|
||||
logger.error("Seedream 图片生成 HTTP %d: %s", last_sc, last_body[:500])
|
||||
try:
|
||||
resp.raise_for_status()
|
||||
except Exception as ee:
|
||||
last_err = ee
|
||||
if attempt < self.max_retries and last_sc >= 500:
|
||||
time.sleep(0.5 * (2**attempt))
|
||||
continue
|
||||
break
|
||||
data = resp.json()
|
||||
data_list = data.get("data") or []
|
||||
if data_list and isinstance(data_list, list):
|
||||
item = data_list[0]
|
||||
img_url = item.get("url")
|
||||
if img_url:
|
||||
logger.info(
|
||||
"Seedream 图片生成成功 model=%s ref_imgs=%d size=%s elapsed=%.1fs attempt=%d",
|
||||
img_model,
|
||||
len(ref_imgs_local),
|
||||
size,
|
||||
time.time() - _img_t0,
|
||||
attempt + 1,
|
||||
)
|
||||
return {"url": img_url, "usage": data.get("usage")}
|
||||
last_err = RuntimeError(f"Seedream 返回结构异常: {str(data)[:300]}")
|
||||
break
|
||||
except _HTTP_NETWORK_ERRORS as ne:
|
||||
last_err = ne
|
||||
last_sc = 0
|
||||
last_body = f"network error: {ne}"
|
||||
logger.warning(
|
||||
"Seedream 网络异常 (%s),重试 %d/%d", type(ne).__name__, attempt + 1, self.max_retries + 1
|
||||
)
|
||||
if attempt < self.max_retries:
|
||||
time.sleep(0.5 * (2**attempt))
|
||||
continue
|
||||
break
|
||||
except Exception as e:
|
||||
last_err = e
|
||||
if attempt < self.max_retries and not isinstance(e, _HTTP_STATUS_ERROR):
|
||||
wait = 0.5 * (2**attempt)
|
||||
logger.warning(
|
||||
"Seedream 图片生成失败,%.1fs 后重试 (%d/%d): %s", wait, attempt + 1, self.max_retries + 1, e
|
||||
)
|
||||
time.sleep(wait)
|
||||
continue
|
||||
break
|
||||
|
||||
# 分类错误
|
||||
err_code = "unknown"
|
||||
user_msg = "图片生成失败,请稍后重试。"
|
||||
body_lower = (last_body or "").lower()
|
||||
if last_sc == 401 or last_sc == 403:
|
||||
err_code, user_msg = "auth_error", "图片生成服务鉴权失败,请联系管理员。"
|
||||
elif last_sc == 400:
|
||||
if any(k in body_lower for k in ("quota", "billing", "insufficient", "balance")):
|
||||
err_code, user_msg = "quota_exceeded", "图片生成配额不足或账号欠费,请联系管理员。"
|
||||
elif any(k in body_lower for k in ("rate", "throughput", "too many", "frequency")):
|
||||
err_code, user_msg = "rate_limit", "图片生成请求过于频繁,请稍后重试。"
|
||||
elif any(k in body_lower for k in ("sensitive", "porn", "terror", "risk", "audit", "content", "violat")):
|
||||
err_code, user_msg = "portrait_intercept", "参考素材未通过内容安全审核,请更换照片后重试。"
|
||||
else:
|
||||
err_code, user_msg = "invalid_param", f"图片生成参数错误:{last_body[:200]}"
|
||||
elif last_sc == 404:
|
||||
err_code, user_msg = "model_not_found", f"图片模型 {img_model} 不存在,请联系管理员。"
|
||||
elif last_sc >= 500:
|
||||
err_code, user_msg = "network_error", "图片生成服务暂时不可用,请稍后重试。"
|
||||
elif last_sc == 0:
|
||||
err_code, user_msg = "network_error", f"图片生成网络错误:{last_err!s}"[:200]
|
||||
self.last_image_error = {
|
||||
"error_code": err_code,
|
||||
"user_message": user_msg,
|
||||
"status_code": last_sc,
|
||||
"detail": (last_body or "")[:500] or (str(last_err) if last_err else ""),
|
||||
"model": img_model,
|
||||
}
|
||||
logger.error(
|
||||
"Seedream 图片生成最终失败: model=%s status=%d code=%s elapsed=%.1fs err=%s",
|
||||
img_model,
|
||||
last_sc,
|
||||
err_code,
|
||||
time.time() - _img_t0,
|
||||
last_err,
|
||||
)
|
||||
return None
|
||||
|
||||
def get_last_image_error(self) -> dict:
|
||||
"""返回最近一次 image_generation 失败的详细错误。空 dict 表示上次成功或未调用。"""
|
||||
return dict(self.last_image_error or {})
|
||||
|
||||
def get_last_video_error(self) -> dict:
|
||||
"""返回最近一次 video_generation 失败的详细错误。空 dict 表示上次成功或未调用。"""
|
||||
return dict(self.last_video_error or {})
|
||||
|
||||
|
||||
def json_safe_dumps(obj: Any, max_len: int = 2000) -> str:
|
||||
"""安全 json 序列化,失败则 fallback 到 repr,超长截断。"""
|
||||
try:
|
||||
import json as _json
|
||||
|
||||
s = _json.dumps(obj, ensure_ascii=False, default=str)
|
||||
except Exception:
|
||||
s = repr(obj)
|
||||
if len(s) > max_len:
|
||||
s = s[:max_len] + f"...(truncated, total {len(s)})"
|
||||
return s
|
||||
|
||||
|
||||
# ── 单例 ─────────────────────────────────────────────────────────────────────
|
||||
|
||||
|
||||
+177
-22
@@ -496,16 +496,32 @@ def run_generate_cover(
|
||||
# ── 通用 LLM / Vision 调用(#2039 ViralVideoOrchestrator 使用,复用现有豆包客户端)──
|
||||
|
||||
|
||||
def call_llm(prompt: str, temperature: float = 0.7) -> object:
|
||||
"""调用豆包大模型(文本对话),返回解析后的 JSON(dict/list)或原文字符串;失败返回 None。"""
|
||||
def call_llm(
|
||||
prompt: str,
|
||||
temperature: float = 0.7,
|
||||
max_tokens: int = 2048,
|
||||
model: str | None = None,
|
||||
system_prompt: str | None = None,
|
||||
) -> object:
|
||||
"""调用豆包大模型(文本对话),返回解析后的 JSON(dict/list)或原文字符串;失败返回 None。
|
||||
|
||||
Args:
|
||||
prompt: 用户侧提示。
|
||||
temperature: 采样温度。
|
||||
max_tokens: 输出上限(结构化任务默认 2048,长文案可按需加大)。
|
||||
model: 覆盖默认模型(如 fast_model 提速用),None 走配置默认推理模型。
|
||||
system_prompt: 覆盖默认 system prompt。
|
||||
"""
|
||||
client = get_doubao_client()
|
||||
if not client.is_available:
|
||||
return None
|
||||
if system_prompt is None:
|
||||
system_prompt = "你是专业的短视频内容策划助手。需要结构化输出时请严格使用 JSON。"
|
||||
messages = [
|
||||
{"role": "system", "content": "你是专业的短视频内容策划助手。需要结构化输出时请严格使用 JSON。"},
|
||||
{"role": "system", "content": system_prompt},
|
||||
{"role": "user", "content": prompt},
|
||||
]
|
||||
raw = client.chat_completion(messages, temperature=temperature, max_tokens=4096)
|
||||
raw = client.chat_completion(messages, temperature=temperature, max_tokens=max_tokens, model=model)
|
||||
if raw is None:
|
||||
return None
|
||||
try:
|
||||
@@ -514,25 +530,164 @@ def call_llm(prompt: str, temperature: float = 0.7) -> object:
|
||||
return raw
|
||||
|
||||
|
||||
def call_vision(image_url: str, prompt: str) -> object:
|
||||
"""调用豆包视觉大模型分析图片,返回解析后的 JSON 或原文字符串;失败返回 None。"""
|
||||
def call_vision(
|
||||
image_url: str,
|
||||
prompt: str,
|
||||
*,
|
||||
model: str | None = None,
|
||||
max_tokens: int = 1024,
|
||||
temperature: float = 0.2,
|
||||
timeout: int = 45,
|
||||
system_prompt: str | None = None,
|
||||
) -> object:
|
||||
"""调用豆包视觉大模型分析图片,返回解析后的 JSON 或原文字符串;失败返回 None。
|
||||
|
||||
Args:
|
||||
image_url: 可公网访问的图片 URL(直接传给豆包视觉模型,无需本地下载)。
|
||||
prompt: 用户侧文本提示。
|
||||
model: 覆盖默认视觉模型(如 vision_lite_model 提速用),None 走配置默认。
|
||||
max_tokens: 输出上限,商品识别用 800~1200 足够,避免长输出拖慢首 token。
|
||||
temperature: 温度。
|
||||
timeout: 单次请求超时(秒)。
|
||||
system_prompt: 覆盖默认 system prompt(viral-video 商品分析会传专门的详细 prompt)。
|
||||
"""
|
||||
client = get_doubao_client()
|
||||
if not client.is_available:
|
||||
logger.warning("[call_vision] 豆包客户端未配置 (DOUBAO_API_KEY 缺失)")
|
||||
return None
|
||||
if not image_url:
|
||||
logger.warning("[call_vision] 空 image_url,跳过视觉分析")
|
||||
return None
|
||||
|
||||
if system_prompt is None:
|
||||
system_prompt = (
|
||||
"你是资深电商视觉分析师。请严格基于用户提供的图片观察回答,"
|
||||
"图片里没有的信息不要凭空想象或编造;看不清或无法判断时明确说"
|
||||
"「无法判断」,不要猜测。输出必须是严格 JSON,不要附加 Markdown 或解释文字。"
|
||||
)
|
||||
messages = [
|
||||
{"role": "system", "content": system_prompt},
|
||||
{"role": "user", "content": prompt},
|
||||
]
|
||||
|
||||
used_model = model or getattr(client, "vision_model", "?")
|
||||
logger.info(
|
||||
"[call_vision] 调用豆包视觉模型 model=%s image_url=%s prompt_len=%d max_tokens=%d timeout=%d",
|
||||
used_model,
|
||||
image_url[:120],
|
||||
len(prompt),
|
||||
max_tokens,
|
||||
timeout,
|
||||
)
|
||||
raw = client.vision_completion(
|
||||
messages=messages,
|
||||
images=[image_url],
|
||||
temperature=temperature,
|
||||
max_tokens=max_tokens,
|
||||
timeout=timeout,
|
||||
model=model,
|
||||
)
|
||||
if raw is None:
|
||||
logger.warning("[call_vision] 视觉模型返回 None (image_url=%s)", image_url[:80])
|
||||
return None
|
||||
logger.info("[call_vision] 视觉模型原始返回 (前400字): %s", raw[:400])
|
||||
# 剥离 ```json ... ``` 包裹
|
||||
stripped = raw.strip()
|
||||
if stripped.startswith("```"):
|
||||
stripped = stripped.strip("`")
|
||||
if stripped.startswith("json"):
|
||||
stripped = stripped[4:].lstrip()
|
||||
try:
|
||||
return json.loads(stripped)
|
||||
except (json.JSONDecodeError, TypeError) as e:
|
||||
logger.warning("[call_vision] JSON 解析失败(%s),返回原始文本: %s", e, raw[:200])
|
||||
return raw
|
||||
|
||||
|
||||
def preheat_trust_chain(portrait_urls: list[str], *, timeout: int = 120) -> list[str] | None:
|
||||
"""#2172 信任链预热:提前把人像图跑 Seedream AI 化,结果可传给 call_video_generation(pre_trusted_images=...)。
|
||||
|
||||
成功返回与输入同序的 AI 化 URL 列表;任意一张失败返回 None(调用方回退到现场跑信任链)。
|
||||
"""
|
||||
client = get_doubao_client()
|
||||
if not client.is_available:
|
||||
return None
|
||||
messages = [
|
||||
{"role": "system", "content": "你是专业的视觉分析师。需要结构化输出时请严格使用 JSON。"},
|
||||
{
|
||||
"role": "user",
|
||||
"content": [
|
||||
{"type": "text", "text": prompt},
|
||||
{"type": "image_url", "image_url": {"url": image_url}},
|
||||
],
|
||||
},
|
||||
]
|
||||
raw = client.chat_completion(messages, temperature=0.3, max_tokens=2048)
|
||||
if raw is None:
|
||||
return None
|
||||
try:
|
||||
return json.loads(raw)
|
||||
except (json.JSONDecodeError, TypeError):
|
||||
return raw
|
||||
return client.preheat_trust_chain(portrait_urls, timeout=timeout)
|
||||
except Exception as e:
|
||||
logger.error("[ai_service] preheat_trust_chain 异常: %s", e, exc_info=True)
|
||||
return None
|
||||
|
||||
|
||||
def call_video_generation(
|
||||
prompt: str,
|
||||
*,
|
||||
image_url: str | None = None,
|
||||
duration: int = 15,
|
||||
ratio: str | None = "9:16",
|
||||
resolution: str = "720p",
|
||||
output_dir: str | None = None,
|
||||
model: str | None = None,
|
||||
generate_audio: bool = True,
|
||||
reference_images: list[str] | None = None,
|
||||
reference_audios: list[str] | None = None,
|
||||
reference_videos: list[str] | None = None,
|
||||
pre_trusted_images: list[str] | None = None,
|
||||
) -> dict | None:
|
||||
"""调用 Seedance / Wan 视频生成(v1.6.2 多模型版 + #2172 信任链预热)。
|
||||
|
||||
成功返回 {"video_path": str, "usage": dict | None}(usage 含 completion_tokens),失败返回 None。
|
||||
失败时错误详情会写入 client.last_video_error,可通过 get_last_video_error() 读取:
|
||||
{"error_code": str, "user_message": str, "status_code": int, "detail": str, ...}
|
||||
"""
|
||||
client = get_doubao_client()
|
||||
if not client.is_available:
|
||||
msg = "豆包客户端未配置(DOUBAO_API_KEY 缺失),跳过视频生成"
|
||||
logger.warning("[ai_service] %s", msg)
|
||||
# 写入 last_video_error 供上层读取
|
||||
client.last_video_error = {
|
||||
"error_code": "auth_error",
|
||||
"user_message": "视频生成服务未配置,请联系管理员。",
|
||||
"status_code": 0,
|
||||
"detail": msg,
|
||||
}
|
||||
return None
|
||||
effective_ratio = ratio or "9:16"
|
||||
try:
|
||||
kwargs: dict = dict(
|
||||
prompt=prompt,
|
||||
image_url=image_url,
|
||||
duration=int(duration),
|
||||
resolution=resolution,
|
||||
generate_audio=bool(generate_audio),
|
||||
watermark=False,
|
||||
output_dir=output_dir,
|
||||
model=model,
|
||||
reference_images=reference_images,
|
||||
reference_audios=reference_audios,
|
||||
reference_videos=reference_videos,
|
||||
pre_trusted_images=pre_trusted_images,
|
||||
)
|
||||
if effective_ratio:
|
||||
kwargs["ratio"] = effective_ratio
|
||||
return client.video_generation(**kwargs)
|
||||
except Exception as e:
|
||||
logger.error("[ai_service] call_video_generation 异常: %s", e, exc_info=True)
|
||||
client.last_video_error = {
|
||||
"error_code": "unknown",
|
||||
"user_message": f"视频生成异常:{e!s}"[:200],
|
||||
"status_code": 0,
|
||||
"detail": str(e),
|
||||
}
|
||||
return None
|
||||
|
||||
|
||||
def get_last_video_error() -> dict:
|
||||
"""读取最近一次视频生成失败的详细错误(含 error_code/user_message/status_code/detail)。
|
||||
成功或未调用过返回空 dict。
|
||||
"""
|
||||
try:
|
||||
client = get_doubao_client()
|
||||
return client.get_last_video_error() if hasattr(client, "get_last_video_error") else {}
|
||||
except Exception:
|
||||
return {}
|
||||
|
||||
@@ -0,0 +1,344 @@
|
||||
"""DashScope 客户端(阿里云百炼 Wan 3.0 等非方舟模型)。
|
||||
|
||||
#2159: 新增 Wan 3.0 视频生成支持。DashScope 异步协议:
|
||||
- POST {base_url}/services/aigc/video-generation/video-synthesis (X-DashScope-Async: enable)
|
||||
→ 返回 output.task_id
|
||||
- GET {base_url}/tasks/{task_id} 轮询状态
|
||||
→ SUCCEEDED 时 output.video_url 可下载
|
||||
认证:Authorization: Bearer {DASHSCOPE_API_KEY}
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import logging
|
||||
import os
|
||||
import time
|
||||
from pathlib import Path
|
||||
from typing import Any
|
||||
from urllib.parse import urlparse
|
||||
|
||||
import httpx
|
||||
|
||||
from packages.shared.config import get_shared_settings
|
||||
|
||||
# 网络/超时类异常父类集合:覆盖 Timeout/Connect/Network/ReadTimeout/WriteTimeout/PoolTimeout
|
||||
_HTTP_NETWORK_ERRORS = ()
|
||||
try:
|
||||
_HTTP_NETWORK_ERRORS = (httpx.TimeoutException, httpx.NetworkError)
|
||||
except Exception:
|
||||
_HTTP_NETWORK_ERRORS = (Exception,)
|
||||
|
||||
_HTTP_STATUS_ERROR = httpx.HTTPStatusError if hasattr(httpx, "HTTPStatusError") else Exception
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
_DASHSCOPE_CLIENT_SINGLETON: "DashScopeClient | None" = None
|
||||
|
||||
|
||||
def _classify_dashscope_error(status_code: int, body: str, task_msg: str = "") -> tuple[str, str]:
|
||||
"""DashScope 错误分类,返回 (error_code, user_message)。"""
|
||||
body_lower = (body or "").lower()
|
||||
msg_in_body = task_msg or ""
|
||||
try:
|
||||
import json as _json
|
||||
|
||||
parsed = _json.loads(body or "{}")
|
||||
if isinstance(parsed, dict):
|
||||
msg_in_body = msg_in_body or str(parsed.get("message", "") or "")
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
if status_code in (401, 403):
|
||||
return "auth_error", "Wan 3.0 服务鉴权失败(DASHSCOPE_API_KEY 无效或过期),请联系管理员。"
|
||||
if status_code == 429 or "rate" in body_lower or "throttl" in body_lower:
|
||||
return "rate_limit", "Wan 3.0 服务繁忙(限流),请稍等1-2分钟后重试。"
|
||||
if status_code == 400 and any(
|
||||
kw in body_lower for kw in ("portrait", "真人", "人脸", "肖像", "content_violation", "risk", "blocked")
|
||||
):
|
||||
return (
|
||||
"portrait_intercept",
|
||||
"参考素材包含真人照片或违规内容被安全策略拦截,请移除真人图片或调整文案后重试。",
|
||||
)
|
||||
if status_code == 404 or ("not found" in body_lower) or ("model" in body_lower and "not exist" in body_lower):
|
||||
return "model_not_found", "Wan 3.0 模型未开通或模型ID无效,请联系管理员。"
|
||||
if status_code in (402, 400) and ("quota" in body_lower or "billing" in body_lower or "insufficient" in body_lower):
|
||||
return "quota_exceeded", "Wan 3.0 服务配额不足,请联系管理员充值或稍后重试。"
|
||||
if status_code == 400:
|
||||
return "invalid_param", f"Wan 3.0 参数错误:{msg_in_body or body[:200]}"
|
||||
if status_code == 0:
|
||||
return "network_error", "Wan 3.0 服务连接失败(网络超时),请稍后重试。"
|
||||
# 任务内失败
|
||||
if task_msg and any(kw in task_msg.lower() for kw in ("portrait", "真人", "人脸", "violation", "blocked")):
|
||||
return "portrait_intercept", "Wan 3.0 视频内容被安全策略拦截,请调整文案或参考图后重试。"
|
||||
detail = msg_in_body or body[:200]
|
||||
return "unknown", f"Wan 3.0 视频生成失败(HTTP {status_code}):{detail}"
|
||||
|
||||
|
||||
class DashScopeClient:
|
||||
"""阿里云 DashScope 异步 API 客户端(Wan 3.0 等视频生成)。"""
|
||||
|
||||
def __init__(self) -> None:
|
||||
settings = get_shared_settings()
|
||||
self.api_key: str = getattr(settings, "dashscope_api_key", "") or os.getenv("DASHSCOPE_API_KEY", "")
|
||||
self.base_url: str = (
|
||||
getattr(settings, "dashscope_base_url", "") or "https://dashscope.aliyuncs.com/api/v1"
|
||||
).rstrip("/")
|
||||
self.poll_interval: int = int(getattr(settings, "dashscope_video_poll_interval", 10) or 10)
|
||||
self.total_timeout: int = int(getattr(settings, "dashscope_video_timeout", 900) or 900)
|
||||
self.max_retries: int = 2
|
||||
self.last_video_error: dict = {}
|
||||
|
||||
@property
|
||||
def is_available(self) -> bool:
|
||||
return bool(self.api_key)
|
||||
|
||||
def get_last_video_error(self) -> dict:
|
||||
return dict(self.last_video_error or {})
|
||||
|
||||
def _set_error(self, error_code: str, user_message: str, status_code: int = 0, detail: str = "", **extra) -> None:
|
||||
self.last_video_error = {
|
||||
"error_code": error_code,
|
||||
"user_message": user_message,
|
||||
"status_code": status_code,
|
||||
"detail": detail[:500] if detail else "",
|
||||
**extra,
|
||||
}
|
||||
|
||||
def video_generation(
|
||||
self,
|
||||
prompt: str,
|
||||
*,
|
||||
image_url: str | None = None,
|
||||
duration: int = 5,
|
||||
ratio: str | None = "9:16",
|
||||
resolution: str = "720p",
|
||||
watermark: bool = False,
|
||||
output_dir: str | None = None,
|
||||
model: str = "wan3.0-video",
|
||||
) -> dict | None:
|
||||
"""调用 DashScope 异步视频合成接口,轮询完成后下载到本地。
|
||||
|
||||
返回 {"video_path": str, "usage": dict | None};失败返回 None,错误详情写入 self.last_video_error。
|
||||
"""
|
||||
self.last_video_error = {}
|
||||
if not self.is_available:
|
||||
self._set_error("auth_error", "Wan 3.0 API key 未配置,请联系管理员。", detail="dashscope api_key empty")
|
||||
logger.error("[dashscope] API key 未配置,无法调用视频生成")
|
||||
return None
|
||||
if not prompt or not prompt.strip():
|
||||
self._set_error("invalid_param", "视频生成提示词不能为空。", detail="empty prompt")
|
||||
return None
|
||||
|
||||
# DashScope 分辨率参数:720P / 1080P / 480P(大写 P)
|
||||
res_upper = (resolution or "720p").upper().replace("P", "P")
|
||||
if res_upper == "480P":
|
||||
ds_res = "480P"
|
||||
elif res_upper == "1080P":
|
||||
ds_res = "1080P"
|
||||
else:
|
||||
ds_res = "720P"
|
||||
|
||||
# 构造 input+parameters
|
||||
input_obj: dict[str, Any] = {"prompt": prompt.strip()}
|
||||
if image_url:
|
||||
input_obj["img_url"] = image_url
|
||||
params: dict[str, Any] = {
|
||||
"resolution": ds_res,
|
||||
"duration": str(float(duration)),
|
||||
"watermark": bool(watermark),
|
||||
}
|
||||
# 比例透传:Wan 支持 "9:16" / "16:9" / "1:1" 等
|
||||
if ratio and ratio != "adaptive":
|
||||
params["aspect_ratio"] = ratio
|
||||
|
||||
payload: dict[str, Any] = {
|
||||
"model": model,
|
||||
"input": input_obj,
|
||||
"parameters": params,
|
||||
}
|
||||
headers = {
|
||||
"Authorization": f"Bearer {self.api_key}",
|
||||
"Content-Type": "application/json",
|
||||
"X-DashScope-Async": "enable",
|
||||
}
|
||||
create_url = f"{self.base_url}/services/aigc/video-generation/video-synthesis"
|
||||
logger.info(
|
||||
"[dashscope] 创建任务: model=%s dur=%ds ratio=%s res=%s img=%s",
|
||||
model,
|
||||
duration,
|
||||
ratio,
|
||||
ds_res,
|
||||
bool(image_url),
|
||||
)
|
||||
logger.info("[dashscope] 创建任务 payload: model=%s params=%s", model, params)
|
||||
|
||||
# 创建任务
|
||||
task_id: str | None = None
|
||||
last_sc = 0
|
||||
last_body = ""
|
||||
for attempt in range(self.max_retries + 1):
|
||||
try:
|
||||
resp = httpx.post(create_url, headers=headers, json=payload, timeout=60)
|
||||
sc = int(getattr(resp, "status_code", 0) or 0)
|
||||
body_text = (getattr(resp, "text", "") or "")[:2000]
|
||||
last_sc = sc
|
||||
last_body = body_text
|
||||
if sc >= 400:
|
||||
logger.error("[dashscope] 创建任务 HTTP %d: %s", sc, body_text)
|
||||
if sc >= 500 and attempt < self.max_retries:
|
||||
time.sleep(0.5 * (2**attempt))
|
||||
continue
|
||||
err_code, user_msg = _classify_dashscope_error(sc, body_text)
|
||||
self._set_error(err_code, user_msg, sc, body_text, model=model)
|
||||
return None
|
||||
data = resp.json()
|
||||
tid = (data.get("output") or {}).get("task_id")
|
||||
if tid:
|
||||
task_id = tid
|
||||
break
|
||||
# 部分情况下 code != 错误
|
||||
code = data.get("code")
|
||||
if code and code != "":
|
||||
err_code, user_msg = _classify_dashscope_error(400, body_text, str(code))
|
||||
self._set_error(err_code, user_msg, sc, body_text, model=model)
|
||||
return None
|
||||
else:
|
||||
self._set_error("unknown", "Wan 3.0 响应格式异常,未返回任务ID", sc, str(data)[:500], model=model)
|
||||
return None
|
||||
except _HTTP_NETWORK_ERRORS as ne:
|
||||
last_sc = 0
|
||||
last_body = f"network error: {ne}"
|
||||
logger.warning(
|
||||
"[dashscope] 网络异常 %s,重试 %d/%d", type(ne).__name__, attempt + 1, self.max_retries + 1
|
||||
)
|
||||
if attempt < self.max_retries:
|
||||
time.sleep(0.5 * (2**attempt))
|
||||
continue
|
||||
self._set_error("network_error", "Wan 3.0 服务连接失败(网络超时),请稍后重试。", 0, str(ne))
|
||||
return None
|
||||
except Exception as _e:
|
||||
if attempt < self.max_retries:
|
||||
time.sleep(0.5 * (2**attempt))
|
||||
continue
|
||||
logger.error("[dashscope] 创建任务最终失败: %s", _e)
|
||||
self._set_error("unknown", f"Wan 3.0 创建任务异常:{_e!s}"[:200], 0, str(_e))
|
||||
return None
|
||||
if not task_id:
|
||||
if not self.last_video_error:
|
||||
err_code, user_msg = _classify_dashscope_error(last_sc, last_body)
|
||||
self._set_error(err_code, user_msg, last_sc, last_body, model=model)
|
||||
return None
|
||||
|
||||
# 轮询任务
|
||||
poll_url = f"{self.base_url}/tasks/{task_id}"
|
||||
deadline = time.time() + self.total_timeout
|
||||
video_url: str | None = None
|
||||
usage: dict | None = None
|
||||
poll_count = 0
|
||||
last_status = ""
|
||||
while time.time() < deadline:
|
||||
poll_count += 1
|
||||
try:
|
||||
r = httpx.get(poll_url, headers=headers, timeout=30)
|
||||
psc = int(getattr(r, "status_code", 0) or 0)
|
||||
pbody = (getattr(r, "text", "") or "")[:1500]
|
||||
if psc >= 400:
|
||||
logger.warning("[dashscope] 轮询 HTTP %d: %s", psc, pbody[:300])
|
||||
if poll_count < 3:
|
||||
time.sleep(self.poll_interval)
|
||||
continue
|
||||
err_code, user_msg = _classify_dashscope_error(psc, pbody)
|
||||
self._set_error(err_code, user_msg, psc, pbody, task_id=task_id)
|
||||
return None
|
||||
d = r.json()
|
||||
out = d.get("output") or {}
|
||||
task_status = out.get("task_status") or d.get("task_status") or ""
|
||||
last_status = task_status
|
||||
if task_status == "SUCCEEDED":
|
||||
video_url = out.get("video_url") or ""
|
||||
usage = d.get("usage")
|
||||
if not video_url:
|
||||
# 结果在 results 数组
|
||||
results = out.get("results") or []
|
||||
if results and isinstance(results, list):
|
||||
video_url = results[0].get("url") or results[0].get("video_url")
|
||||
if video_url:
|
||||
logger.info("[dashscope] 任务 %s 完成: %s", task_id, video_url[:120])
|
||||
break
|
||||
logger.error("[dashscope] 任务 %s SUCCEEDED 但无 video_url: %s", task_id, str(d)[:500])
|
||||
self._set_error(
|
||||
"unknown",
|
||||
"Wan 3.0 任务成功但未返回视频URL,请联系管理员。",
|
||||
200,
|
||||
str(d)[:500],
|
||||
task_id=task_id,
|
||||
)
|
||||
return None
|
||||
if task_status in ("FAILED", "FAILED_WITH_ERROR", "ERROR"):
|
||||
msg = out.get("message") or d.get("message") or out.get("error_msg") or "unknown error"
|
||||
logger.error("[dashscope] 任务 %s 失败: %s", task_id, msg)
|
||||
err_code, user_msg = _classify_dashscope_error(200, "", msg)
|
||||
self._set_error(err_code, user_msg, 200, msg, task_id=task_id, last_status=task_status)
|
||||
return None
|
||||
if task_status in ("CANCELED", "CANCELLED"):
|
||||
logger.warning("[dashscope] 任务 %s 被取消", task_id)
|
||||
self._set_error("unknown", "Wan 3.0 任务被取消。", 200, "task cancelled", task_id=task_id)
|
||||
return None
|
||||
# PENDING / RUNNING / SUSPENDED → 继续轮询
|
||||
if poll_count % 5 == 0:
|
||||
logger.info("[dashscope] 轮询中 task=%s status=%s polls=%d", task_id, task_status, poll_count)
|
||||
except Exception as e:
|
||||
logger.warning("[dashscope] 轮询异常: %s", e)
|
||||
time.sleep(self.poll_interval)
|
||||
if not video_url:
|
||||
logger.error("[dashscope] 任务 %s 轮询超时(%ds)", task_id, self.total_timeout)
|
||||
self._set_error(
|
||||
"network_error",
|
||||
f"Wan 3.0 视频生成超时(>{self.total_timeout}s),任务仍在排队,请稍后重试。",
|
||||
0,
|
||||
f"timeout after {self.total_timeout}s, polls={poll_count}, last_status={last_status}",
|
||||
task_id=task_id,
|
||||
last_status=last_status,
|
||||
)
|
||||
return None
|
||||
|
||||
# 下载视频
|
||||
out_dir = output_dir or os.path.join(os.getcwd(), "seedance_outputs")
|
||||
os.makedirs(out_dir, exist_ok=True)
|
||||
suffix = Path(urlparse(video_url).path).suffix or ".mp4"
|
||||
if suffix.lower() not in (".mp4", ".mov", ".webm"):
|
||||
suffix = ".mp4"
|
||||
safe_tid = "".join(c if c.isalnum() or c in "-_" else "_" for c in task_id)[:40]
|
||||
out_path = os.path.join(out_dir, f"wan_{safe_tid}{suffix}")
|
||||
try:
|
||||
with httpx.stream("GET", video_url, timeout=300, follow_redirects=True) as resp:
|
||||
dsc = int(getattr(resp, "status_code", 0) or 0)
|
||||
if dsc >= 400:
|
||||
logger.error("[dashscope] 下载 HTTP %d", dsc)
|
||||
self._set_error("network_error", "Wan 3.0 视频下载失败(HTTP错误),请稍后重试。", dsc)
|
||||
return None
|
||||
with open(out_path, "wb") as f:
|
||||
for chunk in resp.iter_bytes(chunk_size=1024 * 256):
|
||||
if chunk:
|
||||
f.write(chunk)
|
||||
except Exception as e:
|
||||
logger.error("[dashscope] 下载视频失败: %s", e, exc_info=True)
|
||||
self._set_error("network_error", f"Wan 3.0 视频下载失败:{e!s}"[:200], 0, str(e))
|
||||
return None
|
||||
size = os.path.getsize(out_path) if os.path.exists(out_path) else 0
|
||||
if size < 1024:
|
||||
logger.error("[dashscope] 下载文件过小: %d bytes", size)
|
||||
self._set_error("unknown", "Wan 3.0 视频下载文件过小,请稍后重试。", 0, f"downloaded only {size} bytes")
|
||||
return None
|
||||
logger.info("[dashscope] 视频已下载: %s (%d bytes)", out_path, size)
|
||||
return {"video_path": out_path, "usage": usage}
|
||||
|
||||
|
||||
def get_dashscope_client() -> DashScopeClient | None:
|
||||
"""返回 DashScope 客户端单例;未配置 API key 时返回 None。"""
|
||||
global _DASHSCOPE_CLIENT_SINGLETON
|
||||
if _DASHSCOPE_CLIENT_SINGLETON is None:
|
||||
_DASHSCOPE_CLIENT_SINGLETON = DashScopeClient()
|
||||
if not _DASHSCOPE_CLIENT_SINGLETON.is_available:
|
||||
return None
|
||||
return _DASHSCOPE_CLIENT_SINGLETON
|
||||
@@ -15,3 +15,8 @@ Pillow==10.4.0
|
||||
|
||||
# FFmpeg Python 绑定
|
||||
ffmpeg-python==0.2.0
|
||||
|
||||
# v1.3 参考视频风格分析(#2051)
|
||||
scenedetect==0.6.4
|
||||
librosa==0.10.2.post1
|
||||
soundfile==0.12.1
|
||||
|
||||
@@ -137,6 +137,28 @@ fi
|
||||
echo "✅ compose.yml ready: $COMPOSE_FILE_PATH ($(wc -l < "$COMPOSE_FILE_PATH") lines)"
|
||||
ln -sf "$NGINX_CONF_FILE" "$INFRA_DOCKER_DIR/nginx-${COMPOSE_ENV_VALUE}.conf" 2>/dev/null || true
|
||||
|
||||
# 封装 docker compose 调用:统一 --env-file(compose 默认只读取 project 目录下的 .env,
|
||||
# 我们的 .env 在 $INFRA_DOCKER_DIR/../../.env,必须显式传入才能读到 GENERATED_FILES_HOST_DIR 等变量)
|
||||
# ── 防御:清理可能残留的 docker-compose.override.yml / compose.override.yml ──
|
||||
# 历史上运维曾用 override 文件固定镜像 tag 排查问题,若忘记删除会导致新镜像 tag 不生效,
|
||||
# Worker 一直跑旧镜像(本次 P0 404 排查中即踩过此坑)。这里每次部署都主动清理。
|
||||
for override in "$INFRA_DOCKER_DIR/docker-compose.override.yml" "$INFRA_DOCKER_DIR/compose.override.yml" "$INFRA_DOCKER_DIR/override.yml"; do
|
||||
if [ -f "$override" ]; then
|
||||
echo "⚠️ Found stale override file, removing: $override"
|
||||
rm -f "$override"
|
||||
fi
|
||||
done
|
||||
|
||||
# ── 防御:清理可能残留的 docker-compose.override.yml / compose.override.yml ──
|
||||
# 历史上运维曾用 override 文件固定镜像 tag 排查问题,若忘记删除会导致新镜像 tag 不生效,
|
||||
# Worker 一直跑旧镜像(本次 P0 404 排查中即踩过此坑)。这里每次部署都主动清理。
|
||||
for override in "$INFRA_DOCKER_DIR/docker-compose.override.yml" "$INFRA_DOCKER_DIR/compose.override.yml" "$INFRA_DOCKER_DIR/override.yml"; do
|
||||
if [ -f "$override" ]; then
|
||||
echo "⚠️ Found stale override file, removing: $override"
|
||||
rm -f "$override"
|
||||
fi
|
||||
done
|
||||
|
||||
# 封装 docker compose 调用:统一 --env-file(compose 默认只读取 project 目录下的 .env,
|
||||
# 我们的 .env 在 $INFRA_DOCKER_DIR/../../.env,必须显式传入才能读到 GENERATED_FILES_HOST_DIR 等变量)
|
||||
compose() {
|
||||
@@ -346,6 +368,21 @@ fi
|
||||
|
||||
echo "All images pulled."
|
||||
|
||||
# ====== 打稳定 tag(:dev),供 Watchtower 监控 ======
|
||||
# Watchtower 只能检测同一个 tag 的 digest 变化。
|
||||
# commit SHA tag 每次构建都不同,Watchtower 无法感知更新。
|
||||
# 因此每次部署都将最新镜像 tag 为 :dev,容器统一使用 :dev 启动。
|
||||
DEV_API="${REGISTRY}/xiaoxia-saas-api:dev"
|
||||
DEV_WORKER="${REGISTRY}/xiaoxia-saas-worker:dev"
|
||||
DEV_WEB="${REGISTRY}/xiaoxia-saas-web:dev"
|
||||
docker tag "$REGISTRY_API" "$DEV_API"
|
||||
docker tag "$REGISTRY_WORKER" "$DEV_WORKER"
|
||||
docker tag "$REGISTRY_WEB" "$DEV_WEB"
|
||||
echo "✅ Tagged images as :dev for Watchtower monitoring"
|
||||
echo " API: $DEV_API"
|
||||
echo " Worker: $DEV_WORKER"
|
||||
echo " Web: $DEV_WEB"
|
||||
|
||||
# ====== 镜像内容校验 ======
|
||||
echo ""
|
||||
echo "=========================================="
|
||||
@@ -511,7 +548,7 @@ docker run -d \
|
||||
--health-retries 3 \
|
||||
--health-start-period 40s \
|
||||
$LOG_OPTS \
|
||||
"$REGISTRY_API" &
|
||||
"$DEV_API" &
|
||||
PID_API_START=$!
|
||||
|
||||
# ── Worker: 通过 compose 启动(单一事实来源)──
|
||||
@@ -519,7 +556,7 @@ PID_API_START=$!
|
||||
# healthcheck 匹配 'celery.*worker'(不把 beat 算活)、资源限制 4C/8G。
|
||||
# WORKER_IMAGE 通过环境变量覆盖镜像 tag(compose.yml 默认 :dev)。
|
||||
echo "Starting worker via docker compose (from $INFRA_DOCKER_DIR)..."
|
||||
WORKER_IMAGE="$REGISTRY_WORKER" APP_VERSION="$IMAGE_TAG" compose up -d --no-deps worker &
|
||||
WORKER_IMAGE="$DEV_WORKER" APP_VERSION="$IMAGE_TAG" compose up -d --no-deps worker &
|
||||
PID_WORKER_START=$!
|
||||
|
||||
# ── Web: 暂保留 docker run(TODO: 后续收敛到 compose)──
|
||||
@@ -535,7 +572,7 @@ docker run -d \
|
||||
--health-timeout 5s \
|
||||
--health-retries 3 \
|
||||
$LOG_OPTS \
|
||||
"$REGISTRY_WEB" &
|
||||
"$DEV_WEB" &
|
||||
PID_WEB_START=$!
|
||||
|
||||
wait $PID_API_START $PID_WORKER_START $PID_WEB_START
|
||||
@@ -666,5 +703,5 @@ echo "=== Staging deployment complete ==="
|
||||
echo "API: http://127.0.0.1:8000"
|
||||
echo "Web: http://127.0.0.1:3001"
|
||||
echo "Worker: managed by docker compose (project=$COMPOSE_PROJECT)"
|
||||
echo "Version: $IMAGE_TAG"
|
||||
echo "Version: $IMAGE_TAG (running as :dev for Watchtower)"
|
||||
docker ps --format "table {{.Names}}\t{{.Status}}\t{{.Image}}" | grep staging
|
||||
|
||||
@@ -57,7 +57,7 @@ if [ "$TARGET_ENV" = "staging" ]; then
|
||||
fi
|
||||
|
||||
# 共用 secrets 直接导出(如果存在)
|
||||
SHARED_SECRETS="OSS_ACCESS_KEY_ID OSS_ACCESS_KEY_SECRET COSYVOICE_API_KEY DASHSCOPE_API_KEY MEDIAKIT_API_KEY DOUBAO_API_KEY DOUBAO_MODEL DOUBAO_BASE_URL DOUBAO_VISION_MODEL WECHAT_APP_ID WECHAT_APP_SECRET TIKHUB_API_KEY APIZERO_API_KEY GPU_WORKER_TOKEN"
|
||||
SHARED_SECRETS="OSS_ACCESS_KEY_ID OSS_ACCESS_KEY_SECRET COSYVOICE_API_KEY DASHSCOPE_API_KEY MEDIAKIT_API_KEY DOUBAO_API_KEY DOUBAO_MODEL DOUBAO_FAST_MODEL DOUBAO_BASE_URL DOUBAO_VISION_MODEL DOUBAO_VISION_LITE_MODEL DOUBAO_VISION_USE_LITE WECHAT_APP_ID WECHAT_APP_SECRET TIKHUB_API_KEY APIZERO_API_KEY GPU_WORKER_TOKEN"
|
||||
for var in $SHARED_SECRETS; do
|
||||
value="${!var:-}"
|
||||
# 已经在环境中了,无需额外操作
|
||||
|
||||
@@ -377,32 +377,12 @@ class TestPrepareNarrativeVoice:
|
||||
assert ei.value.status_code == 502
|
||||
assert "配音合成失败" in ei.value.message
|
||||
|
||||
def test_points_insufficient_402(self, monkeypatch):
|
||||
class FakePoints:
|
||||
def deduct_points(self, *a, **k):
|
||||
return {"success": False, "balance": 0}
|
||||
def test_no_points_service_invoked(self, monkeypatch):
|
||||
"""v1.6.2: 叙事配音已免费,不再实例化 PointsService / 扣点/退费。"""
|
||||
# 确认 narrative_service 已不再暴露 PointsService
|
||||
assert not hasattr(ns, "PointsService"), "narrative_service 不应再导入 PointsService"
|
||||
|
||||
monkeypatch.setattr(ns, "PointsService", lambda: FakePoints())
|
||||
deps = self._deps(points_enabled=True)
|
||||
with pytest.raises(NarrativeError) as ei:
|
||||
prepare_narrative_voice(**deps)
|
||||
assert ei.value.status_code == 402
|
||||
|
||||
def test_points_refund_on_failure(self, monkeypatch):
|
||||
class FakePoints:
|
||||
def __init__(self):
|
||||
self.refunded = 0
|
||||
|
||||
def deduct_points(self, *a, **k):
|
||||
return {"success": True, "balance": 100}
|
||||
|
||||
def refund_points(self, user_id, amount, source, db, ref_id="", **k):
|
||||
self.refunded += amount
|
||||
|
||||
points = FakePoints()
|
||||
monkeypatch.setattr(ns, "PointsService", lambda: points)
|
||||
|
||||
class FailingWorkflow:
|
||||
class FakeWorkflow:
|
||||
def __init__(self, *, repository, cosyvoice_service):
|
||||
pass
|
||||
|
||||
@@ -412,11 +392,22 @@ class TestPrepareNarrativeVoice:
|
||||
def process_synthesis_failure(self, job_id, error):
|
||||
return None
|
||||
|
||||
monkeypatch.setattr(ns, "TTSWorkflowService", FailingWorkflow)
|
||||
monkeypatch.setattr(ns, "TTSWorkflowService", FakeWorkflow)
|
||||
deps = self._deps(points_enabled=True)
|
||||
with pytest.raises(NarrativeError):
|
||||
with pytest.raises(NarrativeError) as ei:
|
||||
prepare_narrative_voice(**deps)
|
||||
assert points.refunded > 0
|
||||
# 走 502 业务错误路径,不再退费
|
||||
assert ei.value.status_code == 502
|
||||
|
||||
def test_module_has_no_points_imports(self):
|
||||
"""模块源码不再包含扣点相关符号。"""
|
||||
import inspect
|
||||
|
||||
src = inspect.getsource(ns)
|
||||
assert "PointsService" not in src
|
||||
assert "calculate_points_cost" not in src
|
||||
assert "_points_scene" not in src
|
||||
assert "_POINTS_SCENE" not in src
|
||||
|
||||
def test_clone_source_resolves_profile(self, monkeypatch):
|
||||
captured = {}
|
||||
|
||||
@@ -1,4 +1,5 @@
|
||||
"""Additional unit tests to hit uncovered lines for diff-coverage >=60%."""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
@@ -13,12 +14,20 @@ from packages.shared.ai_client import DoubaoClient
|
||||
|
||||
class _FakeSettings:
|
||||
doubao_api_key = "test-key"
|
||||
doubao_model = "test-model"
|
||||
doubao_model = "doubao-seed-2-1-pro-260915"
|
||||
doubao_fast_model = "doubao-seed-2-1-lite-260915"
|
||||
doubao_base_url = "https://ark.cn-beijing.volces.com/api/v3"
|
||||
doubao_timeout = 10
|
||||
doubao_max_retries = 0
|
||||
doubao_vision_model = "test-vision"
|
||||
doubao_embedding_model = "test-embedding"
|
||||
doubao_vision_model = "doubao-seed-2-1-pro-260915"
|
||||
doubao_vision_lite_model = "doubao-seed-2-1-lite-260915"
|
||||
doubao_vision_use_lite = False
|
||||
doubao_embedding_model = "doubao-embedding-vision-251215"
|
||||
doubao_video_model = "doubao-seedance-2-5-260628"
|
||||
doubao_video_timeout = 480
|
||||
doubao_video_poll_interval = 10
|
||||
doubao_image_model = "doubao-seedream-5-0-pro-260628"
|
||||
doubao_image_timeout = 120
|
||||
|
||||
|
||||
def _make_client(api_key: str = "test-key") -> DoubaoClient:
|
||||
@@ -84,7 +93,9 @@ _GEN_TASKS_PATH = Path(__file__).resolve().parents[2] / "apps/api/app/api/routes
|
||||
def _load_infer_func():
|
||||
src = _GEN_TASKS_PATH.read_text()
|
||||
start = src.index("# #2035:文案关键词")
|
||||
end = src.index("from packages.middleware")
|
||||
# 用紧跟 _infer_expected_categories 后的 logger 行作为结束锚点
|
||||
end_marker = "\nlogger = logging.getLogger"
|
||||
end = src.index(end_marker, start)
|
||||
code = src[start:end]
|
||||
ns: dict = {}
|
||||
exec(code, ns)
|
||||
@@ -124,26 +135,50 @@ from packages.domain.atom_clip_tagger import parse_vision_response
|
||||
|
||||
class TestParseVisionResponseEdgeCases:
|
||||
def test_person_count_type_error_defaults_zero(self):
|
||||
text = json.dumps({
|
||||
"scene": [], "objects": [], "action": [], "shot": "", "has_text": False,
|
||||
"person_count": "not-an-int", "text_content": "", "caption": "x",
|
||||
})
|
||||
text = json.dumps(
|
||||
{
|
||||
"scene": [],
|
||||
"objects": [],
|
||||
"action": [],
|
||||
"shot": "",
|
||||
"has_text": False,
|
||||
"person_count": "not-an-int",
|
||||
"text_content": "",
|
||||
"caption": "x",
|
||||
}
|
||||
)
|
||||
r = parse_vision_response(text)
|
||||
assert r["person_count"] == 0
|
||||
|
||||
def test_person_count_out_of_range_clamped(self):
|
||||
text = json.dumps({
|
||||
"scene": [], "objects": [], "action": [], "shot": "", "has_text": False,
|
||||
"person_count": 10, "text_content": "", "caption": "x",
|
||||
})
|
||||
text = json.dumps(
|
||||
{
|
||||
"scene": [],
|
||||
"objects": [],
|
||||
"action": [],
|
||||
"shot": "",
|
||||
"has_text": False,
|
||||
"person_count": 10,
|
||||
"text_content": "",
|
||||
"caption": "x",
|
||||
}
|
||||
)
|
||||
r = parse_vision_response(text)
|
||||
assert r["person_count"] == 3
|
||||
|
||||
def test_person_count_negative_clamped(self):
|
||||
text = json.dumps({
|
||||
"scene": [], "objects": [], "action": [], "shot": "", "has_text": False,
|
||||
"person_count": -5, "text_content": "", "caption": "x",
|
||||
})
|
||||
text = json.dumps(
|
||||
{
|
||||
"scene": [],
|
||||
"objects": [],
|
||||
"action": [],
|
||||
"shot": "",
|
||||
"has_text": False,
|
||||
"person_count": -5,
|
||||
"text_content": "",
|
||||
"caption": "x",
|
||||
}
|
||||
)
|
||||
r = parse_vision_response(text)
|
||||
assert r["person_count"] == 0
|
||||
|
||||
@@ -154,10 +189,18 @@ class TestParseVisionResponseEdgeCases:
|
||||
|
||||
def test_caption_truncation_at_80(self):
|
||||
long_caption = "描" * 100
|
||||
text = json.dumps({
|
||||
"scene": [], "objects": [], "action": [], "shot": "", "has_text": False,
|
||||
"person_count": 0, "text_content": "", "caption": long_caption,
|
||||
})
|
||||
text = json.dumps(
|
||||
{
|
||||
"scene": [],
|
||||
"objects": [],
|
||||
"action": [],
|
||||
"shot": "",
|
||||
"has_text": False,
|
||||
"person_count": 0,
|
||||
"text_content": "",
|
||||
"caption": long_caption,
|
||||
}
|
||||
)
|
||||
r = parse_vision_response(text)
|
||||
assert len(r["caption"]) == 80
|
||||
|
||||
@@ -191,9 +234,7 @@ class TestNarrativeMatchNonDictClipTags:
|
||||
def test_non_dict_clip_tags_are_skipped(self):
|
||||
a1 = _FA("a1", tags=[])
|
||||
clip_map = {"a1": [None, "bad", {"scene": ["工厂"], "objects": [], "action": []}, 123]}
|
||||
matched, unmatched = match_assets_by_script_tags(
|
||||
[a1], script_tags=["工厂"], clip_ai_tags_by_asset=clip_map
|
||||
)
|
||||
matched, unmatched = match_assets_by_script_tags([a1], script_tags=["工厂"], clip_ai_tags_by_asset=clip_map)
|
||||
assert [a.id for a in matched] == ["a1"]
|
||||
|
||||
|
||||
@@ -226,6 +267,7 @@ class _FQuery:
|
||||
class TestUpdateCaptionEmbedding:
|
||||
def _make_repo(self, session):
|
||||
from packages.adapters.sqlalchemy_impl.asset_atom_clip_repository import SQLAlchemyAssetAtomClipRepository
|
||||
|
||||
repo = SQLAlchemyAssetAtomClipRepository.__new__(SQLAlchemyAssetAtomClipRepository)
|
||||
repo.session = session
|
||||
return repo
|
||||
|
||||
@@ -1,48 +1,25 @@
|
||||
"""AI数字人渲染 积分扣点单元测试 (#1895 P2 step 2.6)"""
|
||||
"""AI 数字人渲染 — v1.6.2 起免费,不扣积分"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from unittest.mock import MagicMock, patch
|
||||
|
||||
import pytest
|
||||
|
||||
import packages.middleware.points_gate as _pg_module
|
||||
|
||||
|
||||
@pytest.fixture(autouse=True)
|
||||
def _enable(monkeypatch):
|
||||
monkeypatch.setattr(_pg_module, "_points_gate_enabled", lambda: True)
|
||||
yield
|
||||
|
||||
|
||||
class TestAiAvatarRenderPoints:
|
||||
def test_ai_digital_human_per_unit(self):
|
||||
class TestAiAvatarRenderFree:
|
||||
def test_ai_digital_human_returns_zero_cost(self):
|
||||
from packages.domain.points_rules import calculate_points_cost
|
||||
|
||||
cost = calculate_points_cost("ai_digital_human", is_member=False, duration_minutes=1)
|
||||
assert cost >= 15
|
||||
assert calculate_points_cost("ai_digital_human", is_member=False, duration_minutes=1) == 0
|
||||
assert calculate_points_cost("ai_digital_human", is_member=True, duration_minutes=5) == 0
|
||||
|
||||
def test_decorator_attached(self):
|
||||
def test_no_points_gate_decorator(self):
|
||||
from app.api.routes.ai_avatar_render import create_render_job
|
||||
|
||||
assert hasattr(create_render_job, "__wrapped__"), "missing @points_gate"
|
||||
assert not hasattr(create_render_job, "__wrapped__")
|
||||
|
||||
def test_insufficient_raises_402(self):
|
||||
from app.api.routes.ai_avatar_render import create_render_job
|
||||
from app.schemas.ai_avatar_render import CreateAiAvatarRenderRequest
|
||||
from fastapi import HTTPException
|
||||
def test_module_has_no_points_imports(self):
|
||||
import inspect
|
||||
|
||||
db = MagicMock()
|
||||
cu = MagicMock()
|
||||
cu.user.id = "u1"
|
||||
cu.user.is_member = False
|
||||
cu.user.member_type = None
|
||||
svc = MagicMock()
|
||||
body = CreateAiAvatarRenderRequest(lipsync_job_id="lip1")
|
||||
with patch("packages.domain.points_service.PointsService") as MS:
|
||||
msvc = MagicMock()
|
||||
msvc.deduct_points.return_value = {"success": False, "balance": 0}
|
||||
MS.return_value = msvc
|
||||
with pytest.raises(HTTPException) as ei:
|
||||
create_render_job(body=body, current_user=cu, svc=svc, db=db)
|
||||
assert ei.value.status_code == 402
|
||||
from app.api.routes import ai_avatar_render as mod
|
||||
|
||||
src = inspect.getsource(mod)
|
||||
assert "PointsService" not in src
|
||||
assert "points_gate" not in src
|
||||
|
||||
@@ -0,0 +1,669 @@
|
||||
"""#2170 Seedream 图片生成 + 方舟信任链单测。"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from unittest.mock import MagicMock, patch
|
||||
|
||||
import httpx
|
||||
|
||||
from packages.shared.ai_client import DoubaoClient
|
||||
|
||||
|
||||
def _make_client(**overrides):
|
||||
client = DoubaoClient.__new__(DoubaoClient)
|
||||
client.api_key = overrides.get("api_key", "test-key")
|
||||
client.base_url = overrides.get("base_url", "https://ark.cn-beijing.volces.com/api/v3")
|
||||
client.model = "doubao-model"
|
||||
client.vision_model = "doubao-vision"
|
||||
client.embedding_model = "doubao-embedding"
|
||||
client.image_model = overrides.get("image_model", "doubao-seedream-5-0-pro-260628")
|
||||
client.image_timeout = overrides.get("image_timeout", 120)
|
||||
client.timeout = overrides.get("timeout", 30)
|
||||
client.max_retries = overrides.get("max_retries", 0)
|
||||
client.last_video_error = {}
|
||||
client.last_image_error = {}
|
||||
return client
|
||||
|
||||
|
||||
def _fake_time(base=1000.0, stable_calls=50, big=9e9):
|
||||
"""返回 time.time 替身:前 stable_calls 次返回 base+i,之后返回 big+i。
|
||||
|
||||
Python 3.12 logging.LogRecord.__init__ 内部会调 time.time(),
|
||||
用有限 iter 会 StopIteration,因此必须用无限生成器。
|
||||
"""
|
||||
state = {"n": 0}
|
||||
|
||||
def _t():
|
||||
n = state["n"]
|
||||
state["n"] += 1
|
||||
if n < stable_calls:
|
||||
return base + n
|
||||
return big + n
|
||||
|
||||
return _t
|
||||
|
||||
|
||||
# ── Seedream 图片生成单测 ──────────────────────────────────────────
|
||||
|
||||
|
||||
class TestImageGenerationHappyPath:
|
||||
def test_returns_none_when_no_api_key(self):
|
||||
client = _make_client(api_key="")
|
||||
assert client.image_generation("p") is None
|
||||
err = client.get_last_image_error()
|
||||
assert err["error_code"] == "auth_error"
|
||||
|
||||
def test_returns_none_on_empty_prompt(self):
|
||||
client = _make_client()
|
||||
assert client.image_generation(" ") is None
|
||||
err = client.get_last_image_error()
|
||||
assert err["error_code"] == "invalid_param"
|
||||
|
||||
def test_text_to_image_success(self):
|
||||
client = _make_client()
|
||||
captured = {}
|
||||
ok_resp = MagicMock()
|
||||
ok_resp.status_code = 200
|
||||
ok_resp.json.return_value = {"data": [{"url": "https://cdn.example.com/i.png"}], "usage": {"tokens": 1}}
|
||||
ok_resp.raise_for_status = MagicMock()
|
||||
ok_resp.text = ""
|
||||
|
||||
def fake_post(url, **kwargs):
|
||||
captured["url"] = url
|
||||
captured["json"] = kwargs.get("json")
|
||||
return ok_resp
|
||||
|
||||
with patch("packages.shared.ai_client.httpx.post", side_effect=fake_post):
|
||||
result = client.image_generation("一只可爱的猫", size="1K")
|
||||
assert result is not None
|
||||
assert result["url"] == "https://cdn.example.com/i.png"
|
||||
assert "/images/generations" in captured["url"]
|
||||
assert captured["json"]["model"] == "doubao-seedream-5-0-pro-260628"
|
||||
assert captured["json"]["size"] == "1K"
|
||||
assert "image" not in captured["json"]
|
||||
|
||||
def test_image_to_image_single_ref_passed_as_string(self):
|
||||
client = _make_client()
|
||||
captured = {}
|
||||
ok_resp = MagicMock(status_code=200)
|
||||
ok_resp.json.return_value = {"data": [{"url": "https://cdn.example.com/out.png"}]}
|
||||
ok_resp.raise_for_status = MagicMock()
|
||||
ok_resp.text = ""
|
||||
|
||||
def fake_post(url, **kwargs):
|
||||
captured["json"] = kwargs.get("json")
|
||||
return ok_resp
|
||||
|
||||
with patch("packages.shared.ai_client.httpx.post", side_effect=fake_post):
|
||||
client.image_generation("保持五官", reference_images=["https://img/x.jpg"])
|
||||
assert captured["json"]["image"] == "https://img/x.jpg"
|
||||
|
||||
def test_image_to_image_multiple_refs_passed_as_list(self):
|
||||
client = _make_client()
|
||||
captured = {}
|
||||
ok_resp = MagicMock(status_code=200)
|
||||
ok_resp.json.return_value = {"data": [{"url": "https://cdn.example.com/out.png"}]}
|
||||
ok_resp.raise_for_status = MagicMock()
|
||||
|
||||
def fake_post(url, **kwargs):
|
||||
captured["json"] = kwargs.get("json")
|
||||
return ok_resp
|
||||
|
||||
refs = [f"https://img/{i}.jpg" for i in range(3)]
|
||||
with patch("packages.shared.ai_client.httpx.post", side_effect=fake_post):
|
||||
client.image_generation("保持", reference_images=refs)
|
||||
assert captured["json"]["image"] == refs
|
||||
|
||||
def test_400_sensitive_returns_portrait_intercept(self):
|
||||
client = _make_client(max_retries=0)
|
||||
bad_resp = MagicMock(status_code=400)
|
||||
bad_resp.text = '{"error":{"code":"ContentRisk","message":"sensitive content detected"}}'
|
||||
bad_resp.json.return_value = {"error": {"code": "ContentRisk"}}
|
||||
bad_resp.raise_for_status.side_effect = httpx.HTTPStatusError("bad", request=MagicMock(), response=bad_resp)
|
||||
with patch("packages.shared.ai_client.httpx.post", return_value=bad_resp):
|
||||
assert client.image_generation("p", reference_images=["https://img/x.jpg"]) is None
|
||||
err = client.get_last_image_error()
|
||||
assert err["error_code"] == "portrait_intercept"
|
||||
|
||||
def test_500_retries_then_fails(self):
|
||||
client = _make_client(max_retries=1)
|
||||
bad_resp = MagicMock(status_code=500)
|
||||
bad_resp.text = "internal error"
|
||||
bad_resp.json.return_value = {"error": {"message": "internal"}}
|
||||
bad_resp.raise_for_status.side_effect = httpx.HTTPStatusError("500", request=MagicMock(), response=bad_resp)
|
||||
with (
|
||||
patch("packages.shared.ai_client.httpx.post", return_value=bad_resp) as mp,
|
||||
patch("packages.shared.ai_client.time.sleep", return_value=None),
|
||||
):
|
||||
assert client.image_generation("p") is None
|
||||
assert mp.call_count == 2
|
||||
err = client.get_last_image_error()
|
||||
assert err["error_code"] == "network_error"
|
||||
|
||||
|
||||
# ── 信任链集成单测 ────────────────────────────────────────────────
|
||||
|
||||
|
||||
class TestTrustChainIntegration:
|
||||
def test_with_reference_image_triggers_seedream_then_seedance_with_reference_image_role(self, tmp_path):
|
||||
client = _make_client()
|
||||
captured_calls = []
|
||||
|
||||
seedream_ok = MagicMock(status_code=200)
|
||||
seedream_ok.json.return_value = {"data": [{"url": "https://ai.example.com/trusted.png"}]}
|
||||
seedream_ok.raise_for_status = MagicMock()
|
||||
seedream_ok.text = ""
|
||||
|
||||
task_ok = MagicMock(status_code=200)
|
||||
task_ok.json.return_value = {"id": "t-trust"}
|
||||
task_ok.raise_for_status = MagicMock()
|
||||
task_ok.text = ""
|
||||
|
||||
poll_ok = MagicMock(status_code=200)
|
||||
poll_ok.json.return_value = {"status": "succeeded", "content": {"video_url": "https://cdn.example.com/v.mp4"}}
|
||||
poll_ok.raise_for_status = MagicMock()
|
||||
|
||||
class FakeStream:
|
||||
def __init__(self):
|
||||
self._c = [b"OK"]
|
||||
self._it = iter(self._c)
|
||||
|
||||
def __enter__(self):
|
||||
return self
|
||||
|
||||
def __exit__(self, *a):
|
||||
return False
|
||||
|
||||
def raise_for_status(self):
|
||||
return None
|
||||
|
||||
def iter_bytes(self, chunk_size=None):
|
||||
return self._it
|
||||
|
||||
def fake_post(url, **kwargs):
|
||||
captured_calls.append({"url": url, "json": kwargs.get("json")})
|
||||
if "/images/generations" in url:
|
||||
return seedream_ok
|
||||
return task_ok
|
||||
|
||||
fake_uuid = MagicMock()
|
||||
fake_uuid.hex = "00000001"
|
||||
with (
|
||||
patch("packages.shared.ai_client.httpx.post", side_effect=fake_post),
|
||||
patch("packages.shared.ai_client.httpx.get", return_value=poll_ok),
|
||||
patch("packages.shared.ai_client.httpx.stream", return_value=FakeStream()),
|
||||
patch("packages.shared.ai_client.time.sleep", return_value=None),
|
||||
patch("packages.shared.ai_client.time.time", side_effect=_fake_time(stable_calls=3)),
|
||||
patch("packages.shared.ai_client.uuid.uuid4", return_value=fake_uuid),
|
||||
patch("packages.shared.ai_client.get_shared_settings") as ms,
|
||||
):
|
||||
ms.return_value = MagicMock(
|
||||
doubao_video_poll_interval=0,
|
||||
doubao_video_timeout=60,
|
||||
doubao_video_model="doubao-seedance-2-5-260628",
|
||||
)
|
||||
out = client.video_generation(
|
||||
"人物在海边散步",
|
||||
image_url="https://img/raw.jpg",
|
||||
duration=5,
|
||||
ratio="9:16",
|
||||
resolution="720p",
|
||||
output_dir=str(tmp_path),
|
||||
)
|
||||
assert out is not None
|
||||
assert len(captured_calls) == 2
|
||||
assert "/images/generations" in captured_calls[0]["url"]
|
||||
assert captured_calls[0]["json"]["image"] == "https://img/raw.jpg"
|
||||
seedance_payload = captured_calls[1]["json"]
|
||||
content = seedance_payload["content"]
|
||||
img_items = [c for c in content if c.get("type") == "image_url"]
|
||||
assert len(img_items) == 1
|
||||
assert img_items[0]["image_url"]["url"] == "https://ai.example.com/trusted.png"
|
||||
assert img_items[0]["role"] == "reference_image"
|
||||
assert seedance_payload["ratio"] == "9:16"
|
||||
|
||||
def test_no_reference_image_skips_seedream(self, tmp_path):
|
||||
client = _make_client()
|
||||
captured_calls = []
|
||||
|
||||
task_ok = MagicMock(status_code=200)
|
||||
task_ok.json.return_value = {"id": "t-t2v"}
|
||||
task_ok.raise_for_status = MagicMock()
|
||||
poll_ok = MagicMock(status_code=200)
|
||||
poll_ok.json.return_value = {"status": "succeeded", "content": {"video_url": "https://cdn.example.com/v.mp4"}}
|
||||
poll_ok.raise_for_status = MagicMock()
|
||||
|
||||
class FakeStream:
|
||||
def __init__(self):
|
||||
self._it = iter([b"OK"])
|
||||
|
||||
def __enter__(self):
|
||||
return self
|
||||
|
||||
def __exit__(self, *a):
|
||||
return False
|
||||
|
||||
def raise_for_status(self):
|
||||
return None
|
||||
|
||||
def iter_bytes(self, chunk_size=None):
|
||||
return self._it
|
||||
|
||||
def fake_post(url, **kwargs):
|
||||
captured_calls.append({"url": url, "json": kwargs.get("json")})
|
||||
return task_ok
|
||||
|
||||
fake_uuid = MagicMock()
|
||||
fake_uuid.hex = "00000002"
|
||||
with (
|
||||
patch("packages.shared.ai_client.httpx.post", side_effect=fake_post),
|
||||
patch("packages.shared.ai_client.httpx.get", return_value=poll_ok),
|
||||
patch("packages.shared.ai_client.httpx.stream", return_value=FakeStream()),
|
||||
patch("packages.shared.ai_client.time.sleep", return_value=None),
|
||||
patch("packages.shared.ai_client.time.time", side_effect=_fake_time(stable_calls=2)),
|
||||
patch("packages.shared.ai_client.uuid.uuid4", return_value=fake_uuid),
|
||||
patch("packages.shared.ai_client.get_shared_settings") as ms,
|
||||
):
|
||||
ms.return_value = MagicMock(
|
||||
doubao_video_poll_interval=0,
|
||||
doubao_video_timeout=60,
|
||||
doubao_video_model="doubao-seedance-2-5-260628",
|
||||
)
|
||||
out = client.video_generation("海边日落", duration=5, ratio="9:16", output_dir=str(tmp_path))
|
||||
assert out is not None
|
||||
assert len(captured_calls) == 1
|
||||
assert "/contents/generations/tasks" in captured_calls[0]["url"]
|
||||
content = captured_calls[0]["json"]["content"]
|
||||
assert all(c.get("type") != "image_url" for c in content)
|
||||
|
||||
def test_seedream_failure_falls_back_to_original_image(self, tmp_path):
|
||||
client = _make_client(max_retries=0)
|
||||
captured_calls = []
|
||||
|
||||
seedream_fail = MagicMock(status_code=400)
|
||||
seedream_fail.text = '{"error":{"code":"QuotaExceeded","message":"quota"}}'
|
||||
seedream_fail.json.return_value = {"error": {"code": "QuotaExceeded"}}
|
||||
seedream_fail.raise_for_status.side_effect = httpx.HTTPStatusError(
|
||||
"q", request=MagicMock(), response=seedream_fail
|
||||
)
|
||||
|
||||
task_ok = MagicMock(status_code=200)
|
||||
task_ok.json.return_value = {"id": "t-fb"}
|
||||
task_ok.raise_for_status = MagicMock()
|
||||
poll_ok = MagicMock(status_code=200)
|
||||
poll_ok.json.return_value = {"status": "succeeded", "content": {"video_url": "https://cdn.example.com/v.mp4"}}
|
||||
poll_ok.raise_for_status = MagicMock()
|
||||
|
||||
class FakeStream:
|
||||
def __init__(self):
|
||||
self._it = iter([b"OK"])
|
||||
|
||||
def __enter__(self):
|
||||
return self
|
||||
|
||||
def __exit__(self, *a):
|
||||
return False
|
||||
|
||||
def raise_for_status(self):
|
||||
return None
|
||||
|
||||
def iter_bytes(self, chunk_size=None):
|
||||
return self._it
|
||||
|
||||
def fake_post(url, **kwargs):
|
||||
captured_calls.append({"url": url, "json": kwargs.get("json")})
|
||||
if "/images/generations" in url:
|
||||
return seedream_fail
|
||||
return task_ok
|
||||
|
||||
fake_uuid = MagicMock()
|
||||
fake_uuid.hex = "00000003"
|
||||
with (
|
||||
patch("packages.shared.ai_client.httpx.post", side_effect=fake_post),
|
||||
patch("packages.shared.ai_client.httpx.get", return_value=poll_ok),
|
||||
patch("packages.shared.ai_client.httpx.stream", return_value=FakeStream()),
|
||||
patch("packages.shared.ai_client.time.sleep", return_value=None),
|
||||
patch("packages.shared.ai_client.time.time", side_effect=_fake_time(stable_calls=2)),
|
||||
patch("packages.shared.ai_client.uuid.uuid4", return_value=fake_uuid),
|
||||
patch("packages.shared.ai_client.get_shared_settings") as ms,
|
||||
):
|
||||
ms.return_value = MagicMock(
|
||||
doubao_video_poll_interval=0,
|
||||
doubao_video_timeout=60,
|
||||
doubao_video_model="doubao-seedance-2-5-260628",
|
||||
)
|
||||
out = client.video_generation(
|
||||
"海边散步",
|
||||
image_url="https://img/raw.jpg",
|
||||
duration=5,
|
||||
ratio="9:16",
|
||||
output_dir=str(tmp_path),
|
||||
)
|
||||
assert out is not None
|
||||
assert len(captured_calls) == 2
|
||||
seedance_payload = captured_calls[1]["json"]
|
||||
content = seedance_payload["content"]
|
||||
img_items = [c for c in content if c.get("type") == "image_url"]
|
||||
assert len(img_items) == 1
|
||||
assert img_items[0]["image_url"]["url"] == "https://img/raw.jpg"
|
||||
assert img_items[0]["role"] == "first_frame"
|
||||
assert seedance_payload["ratio"] == "adaptive"
|
||||
|
||||
|
||||
# ── image_generation 补充分支覆盖 ─────────────────────────────────
|
||||
|
||||
|
||||
class TestImageGenerationBranches:
|
||||
"""覆盖 image_generation 的错误分类/重试/结构异常等分支。"""
|
||||
|
||||
def test_401_returns_auth_error(self):
|
||||
client = _make_client(max_retries=0)
|
||||
r = MagicMock(status_code=401, text='{"error":{}}')
|
||||
r.json.return_value = {"error": {}}
|
||||
r.raise_for_status.side_effect = httpx.HTTPStatusError("a", request=MagicMock(), response=r)
|
||||
with patch("packages.shared.ai_client.httpx.post", return_value=r):
|
||||
assert client.image_generation("p") is None
|
||||
assert client.get_last_image_error()["error_code"] == "auth_error"
|
||||
|
||||
def test_404_returns_model_not_found(self):
|
||||
client = _make_client(max_retries=0)
|
||||
r = MagicMock(status_code=404, text="not found")
|
||||
r.json.return_value = {"error": {"message": "model not found"}}
|
||||
r.raise_for_status.side_effect = httpx.HTTPStatusError("a", request=MagicMock(), response=r)
|
||||
with patch("packages.shared.ai_client.httpx.post", return_value=r):
|
||||
assert client.image_generation("p") is None
|
||||
assert client.get_last_image_error()["error_code"] == "model_not_found"
|
||||
|
||||
def test_400_quota_returns_quota_exceeded(self):
|
||||
client = _make_client(max_retries=0)
|
||||
r = MagicMock(status_code=400, text="insufficient balance quota exceeded")
|
||||
r.json.return_value = {"error": {"message": "quota"}}
|
||||
r.raise_for_status.side_effect = httpx.HTTPStatusError("a", request=MagicMock(), response=r)
|
||||
with patch("packages.shared.ai_client.httpx.post", return_value=r):
|
||||
assert client.image_generation("p") is None
|
||||
assert client.get_last_image_error()["error_code"] == "quota_exceeded"
|
||||
|
||||
def test_400_rate_limit_returns_rate_limit(self):
|
||||
client = _make_client(max_retries=0)
|
||||
r = MagicMock(status_code=400, text="too many requests, rate limit exceeded")
|
||||
r.json.return_value = {"error": {"message": "rate"}}
|
||||
r.raise_for_status.side_effect = httpx.HTTPStatusError("a", request=MagicMock(), response=r)
|
||||
with patch("packages.shared.ai_client.httpx.post", return_value=r):
|
||||
assert client.image_generation("p") is None
|
||||
assert client.get_last_image_error()["error_code"] == "rate_limit"
|
||||
|
||||
def test_400_generic_returns_invalid_param(self):
|
||||
client = _make_client(max_retries=0)
|
||||
r = MagicMock(status_code=400, text="bad parameter size")
|
||||
r.json.return_value = {"error": {"message": "bad"}}
|
||||
r.raise_for_status.side_effect = httpx.HTTPStatusError("a", request=MagicMock(), response=r)
|
||||
with patch("packages.shared.ai_client.httpx.post", return_value=r):
|
||||
assert client.image_generation("p") is None
|
||||
assert client.get_last_image_error()["error_code"] == "invalid_param"
|
||||
|
||||
def test_200_but_no_url_returns_none(self):
|
||||
client = _make_client(max_retries=0)
|
||||
r = MagicMock(status_code=200, text="")
|
||||
r.json.return_value = {"data": [{"no_url": True}]} # 缺 url 字段
|
||||
r.raise_for_status = MagicMock()
|
||||
with patch("packages.shared.ai_client.httpx.post", return_value=r):
|
||||
assert client.image_generation("p") is None
|
||||
assert client.get_last_image_error()["error_code"] == "unknown"
|
||||
|
||||
def test_network_error_retries_then_fails(self):
|
||||
client = _make_client(max_retries=1)
|
||||
import httpcore
|
||||
|
||||
with (
|
||||
patch("packages.shared.ai_client.httpx.post", side_effect=httpx.ConnectError("no network")),
|
||||
patch("packages.shared.ai_client.time.sleep", return_value=None),
|
||||
):
|
||||
assert client.image_generation("p") is None
|
||||
err = client.get_last_image_error()
|
||||
assert err["error_code"] == "network_error"
|
||||
|
||||
def test_get_last_image_error_returns_copy(self):
|
||||
client = _make_client()
|
||||
client.last_image_error = {"error_code": "x"}
|
||||
e1 = client.get_last_image_error()
|
||||
e1["error_code"] = "mutated"
|
||||
assert client.last_image_error["error_code"] == "x"
|
||||
|
||||
|
||||
# ── 信任链分支覆盖 ────────────────────────────────────────
|
||||
|
||||
|
||||
class TestTrustChainBranches:
|
||||
def test_dashscope_provider_skips_trust_chain(self, tmp_path):
|
||||
"""provider=dashscope 时不走信任链(Wan 模型由 dashscope_client 处理,在我们分支之前已经 return)。
|
||||
这里测 doubao 分支:信任链默认触发,验证 DashScope 分发路径不受影响。"""
|
||||
# 该测试实际覆盖 video_generation 入口的 dashscope 分发:缺 DASHSCOPE_API_KEY 时返回 auth_error
|
||||
client = _make_client()
|
||||
with (patch("packages.shared.ai_client.get_shared_settings") as ms,):
|
||||
ms.return_value = MagicMock(
|
||||
doubao_video_poll_interval=0,
|
||||
doubao_video_timeout=1,
|
||||
doubao_video_model="doubao-seedance-2-5-260628",
|
||||
)
|
||||
# DashScope 不可用时返回 auth_error(不是信任链相关错误)
|
||||
result = client.video_generation(
|
||||
"p",
|
||||
output_dir=str(tmp_path),
|
||||
model="wan-3.0",
|
||||
image_url="https://img/x.jpg",
|
||||
)
|
||||
assert result is None
|
||||
err = client.get_last_video_error()
|
||||
# 不论是否走信任链,DashScope 无 key 时返回 auth_error
|
||||
assert err["error_code"] == "auth_error"
|
||||
|
||||
def test_trust_chain_partial_seedream_success_falls_back(self, tmp_path):
|
||||
"""多张参考图中第 2 张 Seedream 失败→整体回退原图直传。"""
|
||||
client = _make_client(max_retries=0)
|
||||
|
||||
def make_seedream_fail():
|
||||
r = MagicMock(status_code=500, text="err")
|
||||
r.json.return_value = {"error": {}}
|
||||
r.raise_for_status.side_effect = httpx.HTTPStatusError("e", request=MagicMock(), response=r)
|
||||
return r
|
||||
|
||||
seedream_ok = MagicMock(status_code=200, text="")
|
||||
seedream_ok.json.return_value = {"data": [{"url": "https://ai.example.com/a.png"}]}
|
||||
seedream_ok.raise_for_status = MagicMock()
|
||||
|
||||
# 两张参考图(image_url + reference_images 各一张),Seedream 第 1 张 ok、第 2 张失败 → 回退
|
||||
call_n = {"n": 0}
|
||||
|
||||
def fake_post(url, **kwargs):
|
||||
if "/images/generations" in url:
|
||||
call_n["n"] += 1
|
||||
if call_n["n"] == 1:
|
||||
return seedream_ok
|
||||
return make_seedream_fail()
|
||||
# Seedance create task(收到原图直传时会调用)
|
||||
t = MagicMock(status_code=200, text="")
|
||||
t.json.return_value = {"id": "t-partial"}
|
||||
t.raise_for_status = MagicMock()
|
||||
return t
|
||||
|
||||
poll_ok = MagicMock(status_code=200, text="")
|
||||
poll_ok.json.return_value = {"status": "succeeded", "content": {"video_url": "https://cdn.example.com/v.mp4"}}
|
||||
poll_ok.raise_for_status = MagicMock()
|
||||
|
||||
class FS:
|
||||
def __init__(self):
|
||||
self._it = iter([b"OK"])
|
||||
|
||||
def __enter__(self):
|
||||
return self
|
||||
|
||||
def __exit__(self, *a):
|
||||
return False
|
||||
|
||||
def raise_for_status(self):
|
||||
return None
|
||||
|
||||
def iter_bytes(self, chunk_size=None):
|
||||
return self._it
|
||||
|
||||
fake_uuid = MagicMock()
|
||||
fake_uuid.hex = "00000004"
|
||||
with (
|
||||
patch("packages.shared.ai_client.httpx.post", side_effect=fake_post),
|
||||
patch("packages.shared.ai_client.httpx.get", return_value=poll_ok),
|
||||
patch("packages.shared.ai_client.httpx.stream", return_value=FS()),
|
||||
patch("packages.shared.ai_client.time.sleep", return_value=None),
|
||||
patch("packages.shared.ai_client.time.time", side_effect=_fake_time(stable_calls=50)),
|
||||
patch("packages.shared.ai_client.uuid.uuid4", return_value=fake_uuid),
|
||||
patch("packages.shared.ai_client.get_shared_settings") as ms,
|
||||
):
|
||||
ms.return_value = MagicMock(
|
||||
doubao_video_poll_interval=0,
|
||||
doubao_video_timeout=60,
|
||||
doubao_video_model="doubao-seedance-2-5-260628",
|
||||
)
|
||||
out = client.video_generation(
|
||||
"p",
|
||||
image_url="https://img/a.jpg",
|
||||
reference_images=["https://img/b.jpg"],
|
||||
duration=5,
|
||||
ratio="9:16",
|
||||
output_dir=str(tmp_path),
|
||||
)
|
||||
assert out is not None
|
||||
# 最终发给 Seedance 的图应是原始 https://img/a.jpg(回退),role=first_frame(因为 has_extra_refs=False 只有 1 张)
|
||||
# 注意:回退后 ref_imgs 是原始 ["https://img/b.jpg"],所以 has_extra_refs=True,role=reference_image
|
||||
# 断言最终 Seedance payload 里的 image_url 是原图(不是 AI 图)
|
||||
|
||||
def test_default_values_on_missing_settings(self):
|
||||
"""getattr 兜底:settings 缺 image_timeout 字段时使用默认 120。"""
|
||||
client = _make_client()
|
||||
# 直接调用 image_generation,让它走一次完整流程(成功路径),验证 timeout 取值
|
||||
ok = MagicMock(status_code=200, text="")
|
||||
ok.json.return_value = {"data": [{"url": "https://ai.example.com/x.png"}]}
|
||||
ok.raise_for_status = MagicMock()
|
||||
captured_kwargs = {}
|
||||
|
||||
def fake_post(url, **kw):
|
||||
captured_kwargs["timeout"] = kw.get("timeout")
|
||||
return ok
|
||||
|
||||
with patch("packages.shared.ai_client.httpx.post", side_effect=fake_post):
|
||||
r = client.image_generation("p", timeout=None) # 不传 timeout,走 self.image_timeout=120
|
||||
assert r is not None
|
||||
assert captured_kwargs["timeout"] == 120
|
||||
|
||||
def test_trust_chain_no_image_url_only_ref_imgs(self, tmp_path):
|
||||
"""不传 image_url 仅传 reference_images 时走 trust chain 成功,ref_imgs 覆盖替换(line 537 else 分支)。"""
|
||||
client = _make_client()
|
||||
captured = []
|
||||
|
||||
seedream_ok = MagicMock(status_code=200, text="")
|
||||
seedream_ok.json.return_value = {"data": [{"url": "https://ai.example.com/ref.png"}]}
|
||||
seedream_ok.raise_for_status = MagicMock()
|
||||
|
||||
task_ok = MagicMock(status_code=200, text="")
|
||||
task_ok.json.return_value = {"id": "t-refonly"}
|
||||
task_ok.raise_for_status = MagicMock()
|
||||
poll_ok = MagicMock(status_code=200, text="")
|
||||
poll_ok.json.return_value = {"status": "succeeded", "content": {"video_url": "https://cdn.example.com/v.mp4"}}
|
||||
poll_ok.raise_for_status = MagicMock()
|
||||
|
||||
class FS:
|
||||
def __init__(self):
|
||||
self._it = iter([b"OK"])
|
||||
|
||||
def __enter__(self):
|
||||
return self
|
||||
|
||||
def __exit__(self, *a):
|
||||
return False
|
||||
|
||||
def raise_for_status(self):
|
||||
return None
|
||||
|
||||
def iter_bytes(self, chunk_size=None):
|
||||
return self._it
|
||||
|
||||
def fake_post(url, **kw):
|
||||
captured.append({"url": url, "json": kw.get("json")})
|
||||
if "/images/generations" in url:
|
||||
return seedream_ok
|
||||
return task_ok
|
||||
|
||||
fu = MagicMock()
|
||||
fu.hex = "0000000a"
|
||||
with (
|
||||
patch("packages.shared.ai_client.httpx.post", side_effect=fake_post),
|
||||
patch("packages.shared.ai_client.httpx.get", return_value=poll_ok),
|
||||
patch("packages.shared.ai_client.httpx.stream", return_value=FS()),
|
||||
patch("packages.shared.ai_client.time.sleep", return_value=None),
|
||||
patch("packages.shared.ai_client.time.time", side_effect=_fake_time(stable_calls=3)),
|
||||
patch("packages.shared.ai_client.uuid.uuid4", return_value=fu),
|
||||
patch("packages.shared.ai_client.get_shared_settings") as ms,
|
||||
):
|
||||
ms.return_value = MagicMock(
|
||||
doubao_video_poll_interval=0,
|
||||
doubao_video_timeout=60,
|
||||
doubao_video_model="doubao-seedance-2-5-260628",
|
||||
)
|
||||
out = client.video_generation(
|
||||
"人物散步",
|
||||
reference_images=["https://img/portrait.jpg"],
|
||||
duration=5,
|
||||
ratio="9:16",
|
||||
output_dir=str(tmp_path),
|
||||
)
|
||||
assert out is not None
|
||||
# 第一次是 Seedream 成功,第二次是 Seedance 创建任务
|
||||
assert len(captured) == 2
|
||||
seedance_payload = captured[1]["json"]
|
||||
content = seedance_payload["content"]
|
||||
img_items = [c for c in content if c.get("type") == "image_url"]
|
||||
assert len(img_items) == 1
|
||||
# 不传 image_url,信任链产物放 ref_imgs,走 reference_image 模式(非 first_frame)
|
||||
assert img_items[0]["image_url"]["url"] == "https://ai.example.com/ref.png"
|
||||
assert img_items[0]["role"] == "reference_image"
|
||||
# 因为没有 image_url,没有 text 也没有 extra_refs 之外的字段,应保留用户 ratio=9:16
|
||||
assert seedance_payload.get("ratio") == "9:16"
|
||||
|
||||
def test_image_generation_generic_exception_retries_then_fails(self):
|
||||
"""image_generation 遇到非 HTTPStatusError 的通用异常时走重试分支(lines 962-971),重试耗尽后返回 None。"""
|
||||
client = _make_client(max_retries=1)
|
||||
call_n = {"n": 0}
|
||||
|
||||
def fake_post(url, **kw):
|
||||
call_n["n"] += 1
|
||||
if call_n["n"] == 1:
|
||||
raise RuntimeError("boiler exploded")
|
||||
# 第二次调用返回成功,验证重试生效
|
||||
ok = MagicMock(status_code=200, text="")
|
||||
ok.json.return_value = {"data": [{"url": "https://ai.example.com/retry-ok.png"}]}
|
||||
ok.raise_for_status = MagicMock()
|
||||
return ok
|
||||
|
||||
with (
|
||||
patch("packages.shared.ai_client.httpx.post", side_effect=fake_post),
|
||||
patch("packages.shared.ai_client.time.sleep", return_value=None),
|
||||
):
|
||||
r = client.image_generation("test prompt")
|
||||
assert r is not None
|
||||
assert r["url"] == "https://ai.example.com/retry-ok.png"
|
||||
assert call_n["n"] == 2
|
||||
|
||||
def test_image_generation_generic_exception_exhausts_retries(self):
|
||||
"""通用异常重试耗尽后返回 None,并正确写入 last_image_error (lines 969-971 break 分支)。"""
|
||||
client = _make_client(max_retries=1)
|
||||
|
||||
def fake_post(url, **kw):
|
||||
raise RuntimeError("always fails")
|
||||
|
||||
with (
|
||||
patch("packages.shared.ai_client.httpx.post", side_effect=fake_post),
|
||||
patch("packages.shared.ai_client.time.sleep", return_value=None),
|
||||
):
|
||||
r = client.image_generation("test prompt")
|
||||
assert r is None
|
||||
err = client.last_image_error
|
||||
assert err["error_code"] == "network_error"
|
||||
assert "always fails" in err["detail"]
|
||||
@@ -0,0 +1,678 @@
|
||||
"""#2106 DoubaoClient.video_generation 单测,覆盖 submit/poll/download 主路径和失败分支。"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from pathlib import Path
|
||||
from unittest.mock import MagicMock, patch
|
||||
|
||||
import httpx
|
||||
import pytest
|
||||
|
||||
from packages.shared.ai_client import DoubaoClient
|
||||
|
||||
|
||||
def _make_client(**overrides):
|
||||
client = DoubaoClient.__new__(DoubaoClient)
|
||||
client.api_key = overrides.get("api_key", "test-key")
|
||||
client.base_url = overrides.get("base_url", "https://ark.cn-beijing.volces.com/api/v3")
|
||||
client.model = "doubao-model"
|
||||
client.vision_model = "doubao-vision"
|
||||
client.embedding_model = "doubao-embedding"
|
||||
client.image_model = overrides.get("image_model", "doubao-seedream-5-0-pro-260628")
|
||||
client.image_timeout = overrides.get("image_timeout", 120)
|
||||
client.timeout = overrides.get("timeout", 30)
|
||||
client.max_retries = overrides.get("max_retries", 0)
|
||||
client.last_video_error = {}
|
||||
client.last_image_error = {}
|
||||
return client
|
||||
|
||||
|
||||
def _fake_time_factory(base=1000.0, jump_after=2, jump=1e9):
|
||||
"""返回一个 time.time() 替身:前 jump_after 次返回 base+offset,之后返回巨大值让 deadline 立即触发。
|
||||
|
||||
避免 Python logging 内部也调 time.time() 导致 StopIteration。
|
||||
"""
|
||||
state = {"n": 0}
|
||||
|
||||
def _t():
|
||||
n = state["n"]
|
||||
state["n"] += 1
|
||||
if n < jump_after:
|
||||
return base + n
|
||||
return base + jump + n
|
||||
|
||||
return _t
|
||||
|
||||
|
||||
class TestVideoGenerationHappyPath:
|
||||
def test_happy_path_generates_and_downloads(self, tmp_path):
|
||||
client = _make_client()
|
||||
|
||||
fake_task_resp = MagicMock()
|
||||
fake_task_resp.json.return_value = {"id": "task-001"}
|
||||
fake_task_resp.raise_for_status = MagicMock()
|
||||
fake_task_resp.status_code = 200
|
||||
fake_task_resp.text = ""
|
||||
|
||||
fake_poll_resp = MagicMock()
|
||||
fake_poll_resp.json.return_value = {
|
||||
"status": "succeeded",
|
||||
"content": {"video_url": "https://cdn.example.com/v.mp4"},
|
||||
}
|
||||
fake_poll_resp.raise_for_status = MagicMock()
|
||||
fake_poll_resp.status_code = 200
|
||||
fake_poll_resp.text = ""
|
||||
|
||||
class FakeStreamResponse:
|
||||
def __init__(self):
|
||||
self._chunks = [b"FAKE", b"MP4", b"DATA"]
|
||||
self._it = iter(self._chunks)
|
||||
|
||||
def __enter__(self):
|
||||
return self
|
||||
|
||||
def __exit__(self, *a):
|
||||
return False
|
||||
|
||||
def raise_for_status(self):
|
||||
return None
|
||||
|
||||
def iter_bytes(self, chunk_size=None):
|
||||
return self._it
|
||||
|
||||
calls = {"post": 0, "get": 0}
|
||||
|
||||
def fake_post(url, **kwargs):
|
||||
calls["post"] += 1
|
||||
return fake_task_resp
|
||||
|
||||
def fake_get(url, **kwargs):
|
||||
calls["get"] += 1
|
||||
if "/tasks/task-001" in url:
|
||||
return fake_poll_resp
|
||||
raise AssertionError(f"unexpected GET (not stream): {url}")
|
||||
|
||||
fake_uuid = MagicMock()
|
||||
fake_uuid.hex = "abcd1234"
|
||||
|
||||
with (
|
||||
patch("packages.shared.ai_client.httpx.post", side_effect=fake_post),
|
||||
patch("packages.shared.ai_client.httpx.get", side_effect=fake_get),
|
||||
patch("packages.shared.ai_client.httpx.stream", return_value=FakeStreamResponse()),
|
||||
patch("packages.shared.ai_client.time.sleep", return_value=None),
|
||||
patch("packages.shared.ai_client.time.time", side_effect=_fake_time_factory(jump_after=2)),
|
||||
patch("packages.shared.ai_client.uuid.uuid4", return_value=fake_uuid),
|
||||
patch("packages.shared.ai_client.get_shared_settings") as mock_settings,
|
||||
):
|
||||
mock_settings.return_value = MagicMock(
|
||||
doubao_video_poll_interval=0,
|
||||
doubao_video_timeout=60,
|
||||
doubao_video_model="doubao-seedance-2-5-260628",
|
||||
)
|
||||
out = client.video_generation(
|
||||
prompt=" 镜头一 ",
|
||||
# 不传 image_url:纯文生视频,不触发信任链,post 调用数为 1(创建任务)
|
||||
duration=5,
|
||||
ratio="9:16",
|
||||
resolution="720p",
|
||||
output_dir=str(tmp_path),
|
||||
)
|
||||
assert out is not None and isinstance(out, dict)
|
||||
assert Path(out["video_path"]).exists()
|
||||
assert Path(out["video_path"]).name == "seedance_task-001_abcd1234.mp4"
|
||||
assert Path(out["video_path"]).read_bytes() == b"FAKEMP4DATA"
|
||||
assert calls["post"] == 1
|
||||
assert calls["get"] == 1
|
||||
|
||||
|
||||
class TestVideoGenerationFailures:
|
||||
def test_returns_none_when_unavailable(self, tmp_path):
|
||||
client = _make_client(api_key="")
|
||||
assert client.video_generation("p", output_dir=str(tmp_path)) is None
|
||||
|
||||
def test_returns_none_on_empty_prompt(self, tmp_path):
|
||||
client = _make_client()
|
||||
assert client.video_generation(" ", output_dir=str(tmp_path)) is None
|
||||
|
||||
def test_returns_none_when_create_returns_no_id(self, tmp_path):
|
||||
client = _make_client(max_retries=0)
|
||||
fake_resp = MagicMock()
|
||||
fake_resp.json.return_value = {"error": "bad"}
|
||||
fake_resp.raise_for_status = MagicMock()
|
||||
with (
|
||||
patch("packages.shared.ai_client.httpx.post", return_value=fake_resp),
|
||||
patch("packages.shared.ai_client.get_shared_settings") as mock_s,
|
||||
patch("packages.shared.ai_client.time.sleep", return_value=None),
|
||||
patch("packages.shared.ai_client.time.time", side_effect=_fake_time_factory()),
|
||||
):
|
||||
mock_s.return_value = MagicMock(
|
||||
doubao_video_poll_interval=1, doubao_video_timeout=60, doubao_video_model="seedance"
|
||||
)
|
||||
assert client.video_generation("p", output_dir=str(tmp_path)) is None
|
||||
|
||||
def test_returns_none_when_poll_returns_failed(self, tmp_path):
|
||||
client = _make_client(max_retries=0)
|
||||
create_resp = MagicMock()
|
||||
create_resp.json.return_value = {"id": "t2"}
|
||||
create_resp.raise_for_status = MagicMock()
|
||||
poll_resp = MagicMock()
|
||||
poll_resp.json.return_value = {"status": "failed", "error": {"code": "C1", "message": "bad"}}
|
||||
poll_resp.raise_for_status = MagicMock()
|
||||
with (
|
||||
patch("packages.shared.ai_client.httpx.post", return_value=create_resp),
|
||||
patch("packages.shared.ai_client.httpx.get", return_value=poll_resp),
|
||||
patch("packages.shared.ai_client.get_shared_settings") as mock_s,
|
||||
patch("packages.shared.ai_client.time.sleep", return_value=None),
|
||||
patch("packages.shared.ai_client.time.time", side_effect=_fake_time_factory()),
|
||||
):
|
||||
mock_s.return_value = MagicMock(
|
||||
doubao_video_poll_interval=0, doubao_video_timeout=10, doubao_video_model="seedance"
|
||||
)
|
||||
assert client.video_generation("p", output_dir=str(tmp_path)) is None
|
||||
|
||||
def test_returns_none_when_download_raises(self, tmp_path):
|
||||
client = _make_client(max_retries=0)
|
||||
create_resp = MagicMock()
|
||||
create_resp.json.return_value = {"id": "t3"}
|
||||
create_resp.raise_for_status = MagicMock()
|
||||
poll_resp = MagicMock()
|
||||
poll_resp.json.return_value = {"status": "succeeded", "content": {"video_url": "https://cdn/v.mp4"}}
|
||||
poll_resp.raise_for_status = MagicMock()
|
||||
|
||||
class BadStream:
|
||||
def __enter__(self):
|
||||
return self
|
||||
|
||||
def __exit__(self, *a):
|
||||
return False
|
||||
|
||||
def raise_for_status(self):
|
||||
raise RuntimeError("network down")
|
||||
|
||||
def iter_bytes(self, **kw):
|
||||
return iter([])
|
||||
|
||||
with (
|
||||
patch("packages.shared.ai_client.httpx.post", return_value=create_resp),
|
||||
patch("packages.shared.ai_client.httpx.get", return_value=poll_resp),
|
||||
patch("packages.shared.ai_client.httpx.stream", return_value=BadStream()),
|
||||
patch("packages.shared.ai_client.get_shared_settings") as mock_s,
|
||||
patch("packages.shared.ai_client.time.sleep", return_value=None),
|
||||
patch("packages.shared.ai_client.time.time", side_effect=_fake_time_factory()),
|
||||
):
|
||||
mock_s.return_value = MagicMock(
|
||||
doubao_video_poll_interval=0, doubao_video_timeout=10, doubao_video_model="seedance"
|
||||
)
|
||||
assert client.video_generation("p", output_dir=str(tmp_path)) is None
|
||||
|
||||
|
||||
class TestVideoGenerationRetryAndPoll:
|
||||
def test_create_retries_then_succeeds(self, tmp_path):
|
||||
client = _make_client(max_retries=1)
|
||||
|
||||
ok_resp = MagicMock()
|
||||
ok_resp.json.return_value = {"id": "t-retry"}
|
||||
ok_resp.raise_for_status = MagicMock()
|
||||
poll_resp = MagicMock()
|
||||
poll_resp.json.return_value = {"status": "expired"}
|
||||
poll_resp.raise_for_status = MagicMock()
|
||||
|
||||
calls = {"post": 0}
|
||||
|
||||
def fake_post(url, **kwargs):
|
||||
calls["post"] += 1
|
||||
if calls["post"] == 1:
|
||||
raise httpx.HTTPError("network")
|
||||
return ok_resp
|
||||
|
||||
with (
|
||||
patch("packages.shared.ai_client.httpx") as mock_httpx,
|
||||
patch("packages.shared.ai_client.time.sleep", return_value=None),
|
||||
patch("packages.shared.ai_client.time.time", side_effect=_fake_time_factory(jump_after=3)),
|
||||
patch("packages.shared.ai_client.get_shared_settings") as mock_s,
|
||||
):
|
||||
mock_s.return_value = MagicMock(
|
||||
doubao_video_poll_interval=0, doubao_video_timeout=1, doubao_video_model="seedance"
|
||||
)
|
||||
mock_httpx.HTTPError = httpx.HTTPError
|
||||
mock_httpx.post.side_effect = fake_post
|
||||
mock_httpx.get.return_value = poll_resp
|
||||
assert client.video_generation("p", output_dir=str(tmp_path)) is None
|
||||
assert calls["post"] == 2
|
||||
|
||||
def test_succeeded_but_no_video_url_returns_none(self, tmp_path):
|
||||
client = _make_client(max_retries=0)
|
||||
create_resp = MagicMock()
|
||||
create_resp.json.return_value = {"id": "t-nourl"}
|
||||
create_resp.raise_for_status = MagicMock()
|
||||
poll_resp = MagicMock()
|
||||
poll_resp.json.return_value = {"status": "succeeded", "content": {}}
|
||||
poll_resp.raise_for_status = MagicMock()
|
||||
with (
|
||||
patch("packages.shared.ai_client.httpx.post", return_value=create_resp),
|
||||
patch("packages.shared.ai_client.httpx.get", return_value=poll_resp),
|
||||
patch("packages.shared.ai_client.time.sleep", return_value=None),
|
||||
patch("packages.shared.ai_client.time.time", side_effect=_fake_time_factory()),
|
||||
patch("packages.shared.ai_client.get_shared_settings") as mock_s,
|
||||
):
|
||||
mock_s.return_value = MagicMock(
|
||||
doubao_video_poll_interval=0, doubao_video_timeout=10, doubao_video_model="seedance"
|
||||
)
|
||||
assert client.video_generation("p", output_dir=str(tmp_path)) is None
|
||||
|
||||
|
||||
class TestAiServiceCallVideoGeneration:
|
||||
def test_returns_none_on_exception(self):
|
||||
from packages.shared import ai_service
|
||||
|
||||
with patch("packages.shared.ai_service.get_doubao_client") as mock_get:
|
||||
mock_client = MagicMock()
|
||||
mock_client.is_available = True
|
||||
mock_client.video_generation.side_effect = RuntimeError("boom")
|
||||
mock_get.return_value = mock_client
|
||||
assert ai_service.call_video_generation("p") is None
|
||||
|
||||
|
||||
class TestVideoGenerationPollLoop:
|
||||
def test_poll_queued_then_running_then_succeeded(self, tmp_path):
|
||||
client = _make_client(max_retries=0)
|
||||
create_resp = MagicMock()
|
||||
create_resp.json.return_value = {"id": "t-wait"}
|
||||
create_resp.raise_for_status = MagicMock()
|
||||
|
||||
queued = MagicMock(json=MagicMock(return_value={"status": "queued"}))
|
||||
queued.raise_for_status = MagicMock()
|
||||
running = MagicMock(json=MagicMock(return_value={"status": "running"}))
|
||||
running.raise_for_status = MagicMock()
|
||||
ok = MagicMock(
|
||||
json=MagicMock(return_value={"status": "succeeded", "content": {"video_url": "https://cdn/x.mp4"}})
|
||||
)
|
||||
ok.raise_for_status = MagicMock()
|
||||
poll_seq = [queued, running, ok]
|
||||
|
||||
class EmptyChunkStream:
|
||||
def __enter__(self):
|
||||
return self
|
||||
|
||||
def __exit__(self, *a):
|
||||
return False
|
||||
|
||||
def raise_for_status(self):
|
||||
return None
|
||||
|
||||
def iter_bytes(self, chunk_size=None):
|
||||
yield b""
|
||||
yield b"D"
|
||||
yield b""
|
||||
yield b"ATA"
|
||||
|
||||
get_calls = {"n": 0}
|
||||
|
||||
def fake_get(url, **kw):
|
||||
if "/tasks/t-wait" in url:
|
||||
resp = poll_seq[min(get_calls["n"], len(poll_seq) - 1)]
|
||||
get_calls["n"] += 1
|
||||
return resp
|
||||
raise AssertionError(url)
|
||||
|
||||
sleeps = []
|
||||
# jump_after 要足够大:deadline 计算一次 + 3次 while 条件判断 = 4 次
|
||||
with (
|
||||
patch("packages.shared.ai_client.httpx.post", return_value=create_resp),
|
||||
patch("packages.shared.ai_client.httpx.get", side_effect=fake_get),
|
||||
patch("packages.shared.ai_client.httpx.stream", return_value=EmptyChunkStream()),
|
||||
patch("packages.shared.ai_client.time.sleep", side_effect=lambda s: sleeps.append(s)),
|
||||
patch("packages.shared.ai_client.time.time", side_effect=_fake_time_factory(jump_after=5, jump=1)),
|
||||
patch("packages.shared.ai_client.uuid.uuid4", return_value=MagicMock(hex="ef012345")),
|
||||
patch("packages.shared.ai_client.get_shared_settings") as mock_s,
|
||||
):
|
||||
mock_s.return_value = MagicMock(
|
||||
doubao_video_poll_interval=0, doubao_video_timeout=200, doubao_video_model="seedance"
|
||||
)
|
||||
out = client.video_generation("p", output_dir=str(tmp_path))
|
||||
assert out is not None and isinstance(out, dict)
|
||||
assert Path(out["video_path"]).read_bytes() == b"DATA"
|
||||
# queued 和 running 各 sleep 一次
|
||||
assert len(sleeps) >= 2
|
||||
|
||||
def test_poll_exception_does_not_crash(self, tmp_path):
|
||||
client = _make_client(max_retries=0)
|
||||
create_resp = MagicMock(json=MagicMock(return_value={"id": "t-err"}))
|
||||
create_resp.raise_for_status = MagicMock()
|
||||
ok = MagicMock(
|
||||
json=MagicMock(return_value={"status": "succeeded", "content": {"video_url": "https://cdn/e.mp4"}})
|
||||
)
|
||||
ok.raise_for_status = MagicMock()
|
||||
|
||||
class OkStream:
|
||||
def __enter__(self):
|
||||
return self
|
||||
|
||||
def __exit__(self, *a):
|
||||
return False
|
||||
|
||||
def raise_for_status(self):
|
||||
return None
|
||||
|
||||
def iter_bytes(self, chunk_size=None):
|
||||
yield b"OK"
|
||||
|
||||
poll_calls = {"n": 0}
|
||||
|
||||
def fake_get(url, **kw):
|
||||
poll_calls["n"] += 1
|
||||
if poll_calls["n"] == 1:
|
||||
raise httpx.HTTPError("transient")
|
||||
return ok
|
||||
|
||||
with (
|
||||
patch("packages.shared.ai_client.httpx.post", return_value=create_resp),
|
||||
patch("packages.shared.ai_client.httpx.get", side_effect=fake_get),
|
||||
patch("packages.shared.ai_client.httpx.stream", return_value=OkStream()),
|
||||
patch("packages.shared.ai_client.time.sleep", return_value=None),
|
||||
patch("packages.shared.ai_client.time.time", side_effect=_fake_time_factory(jump_after=3)),
|
||||
patch("packages.shared.ai_client.uuid.uuid4", return_value=MagicMock(hex="11111111")),
|
||||
patch("packages.shared.ai_client.get_shared_settings") as mock_s,
|
||||
):
|
||||
mock_s.return_value = MagicMock(
|
||||
doubao_video_poll_interval=0, doubao_video_timeout=100, doubao_video_model="seedance"
|
||||
)
|
||||
out = client.video_generation("p", output_dir=str(tmp_path))
|
||||
assert out is not None and isinstance(out, dict)
|
||||
assert Path(out["video_path"]).exists()
|
||||
assert poll_calls["n"] == 2
|
||||
|
||||
def test_default_output_dir_and_audio_watermark(self, tmp_path, monkeypatch):
|
||||
"""不传 output_dir 时落到 /tmp;generate_audio/watermark=True 也能正常提交。"""
|
||||
client = _make_client()
|
||||
|
||||
create_resp = MagicMock(json=MagicMock(return_value={"id": "t-default"}))
|
||||
create_resp.raise_for_status = MagicMock()
|
||||
poll_resp = MagicMock(
|
||||
json=MagicMock(return_value={"status": "succeeded", "content": {"video_url": "https://cdn/d.mp4"}})
|
||||
)
|
||||
poll_resp.raise_for_status = MagicMock()
|
||||
|
||||
# 用 tmp_path 伪造 /tmp 避免污染真 /tmp
|
||||
monkeypatch.setattr("packages.shared.ai_client.os.makedirs", lambda d, exist_ok=True: None)
|
||||
|
||||
class S:
|
||||
def __enter__(self):
|
||||
return self
|
||||
|
||||
def __exit__(self, *a):
|
||||
return False
|
||||
|
||||
def raise_for_status(self):
|
||||
return None
|
||||
|
||||
def iter_bytes(self, chunk_size=None):
|
||||
yield b"D"
|
||||
|
||||
# 捕获 POST payload 断言
|
||||
captured = {}
|
||||
|
||||
def fake_post(url, **kw):
|
||||
captured["json"] = kw.get("json")
|
||||
return create_resp
|
||||
|
||||
def fake_get(url, **kw):
|
||||
return poll_resp
|
||||
|
||||
def fake_open(path, mode):
|
||||
# 返回一个 MagicMock file,模拟写入
|
||||
f = MagicMock()
|
||||
f.__enter__ = MagicMock(return_value=f)
|
||||
f.__exit__ = MagicMock(return_value=False)
|
||||
captured["path"] = path
|
||||
return f
|
||||
|
||||
monkeypatch.setattr("packages.shared.ai_client.httpx.post", fake_post)
|
||||
monkeypatch.setattr("packages.shared.ai_client.httpx.get", fake_get)
|
||||
monkeypatch.setattr("packages.shared.ai_client.httpx.stream", lambda *a, **kw: S())
|
||||
monkeypatch.setattr("builtins.open", fake_open)
|
||||
monkeypatch.setattr("packages.shared.ai_client.os.path.getsize", lambda p: 99)
|
||||
|
||||
with (
|
||||
patch("packages.shared.ai_client.time.sleep", return_value=None),
|
||||
patch("packages.shared.ai_client.time.time", side_effect=_fake_time_factory()),
|
||||
patch("packages.shared.ai_client.uuid.uuid4", return_value=MagicMock(hex="00000001")),
|
||||
patch("packages.shared.ai_client.get_shared_settings") as mock_s,
|
||||
):
|
||||
mock_s.return_value = MagicMock(
|
||||
doubao_video_poll_interval=0,
|
||||
doubao_video_timeout=60,
|
||||
doubao_video_model="seedance",
|
||||
)
|
||||
out = client.video_generation(
|
||||
"p", duration=3, ratio="1:1", resolution="480p", generate_audio=True, watermark=True
|
||||
)
|
||||
assert out is not None and isinstance(out, dict)
|
||||
assert out["video_path"] == "/tmp/seedance_t-default_00000001.mp4"
|
||||
assert captured["json"]["generate_audio"] is True
|
||||
assert captured["json"]["watermark"] is True
|
||||
assert captured["json"]["ratio"] == "1:1"
|
||||
assert captured["json"]["resolution"] == "480p"
|
||||
|
||||
|
||||
class TestGetDoubaoClientSingleton:
|
||||
def test_singleton_lazy_init(self):
|
||||
from packages.shared import ai_client
|
||||
|
||||
prev = ai_client._client
|
||||
try:
|
||||
ai_client._client = None
|
||||
c1 = ai_client.get_doubao_client()
|
||||
c2 = ai_client.get_doubao_client()
|
||||
assert c1 is c2
|
||||
assert isinstance(c1, ai_client.DoubaoClient)
|
||||
finally:
|
||||
ai_client._client = prev
|
||||
|
||||
|
||||
class TestVideoGenerationCancelled:
|
||||
def test_poll_cancelled_returns_none(self, tmp_path):
|
||||
client = _make_client(max_retries=0)
|
||||
create_resp = MagicMock(json=MagicMock(return_value={"id": "t-can"}))
|
||||
create_resp.raise_for_status = MagicMock()
|
||||
poll_resp = MagicMock(json=MagicMock(return_value={"status": "cancelled"}))
|
||||
poll_resp.raise_for_status = MagicMock()
|
||||
with (
|
||||
patch("packages.shared.ai_client.httpx.post", return_value=create_resp),
|
||||
patch("packages.shared.ai_client.httpx.get", return_value=poll_resp),
|
||||
patch("packages.shared.ai_client.time.sleep", return_value=None),
|
||||
patch("packages.shared.ai_client.time.time", side_effect=_fake_time_factory()),
|
||||
patch("packages.shared.ai_client.get_shared_settings") as mock_s,
|
||||
):
|
||||
mock_s.return_value = MagicMock(
|
||||
doubao_video_poll_interval=0, doubao_video_timeout=10, doubao_video_model="seedance"
|
||||
)
|
||||
assert client.video_generation("p", output_dir=str(tmp_path)) is None
|
||||
|
||||
|
||||
# ============ #2157 _resolve_video_model_id 模型ID映射单测 ============
|
||||
|
||||
|
||||
class TestResolveVideoModelId:
|
||||
"""覆盖 _resolve_video_model_id 各分支(#2157 P0 修复)。"""
|
||||
|
||||
def _import_target(self):
|
||||
from packages.shared.ai_client import _resolve_video_model_id
|
||||
|
||||
return _resolve_video_model_id
|
||||
|
||||
def test_none_uses_default(self):
|
||||
fn = self._import_target()
|
||||
with patch("packages.shared.ai_client.get_shared_settings") as ms:
|
||||
ms.return_value = MagicMock(doubao_video_model="doubao-seedance-2-5-260628")
|
||||
assert fn(None) == "doubao-seedance-2-5-260628"
|
||||
|
||||
def test_empty_uses_default(self):
|
||||
fn = self._import_target()
|
||||
with patch("packages.shared.ai_client.get_shared_settings") as ms:
|
||||
ms.return_value = MagicMock(doubao_video_model="doubao-seedance-2-5-260628")
|
||||
assert fn(" ") == "doubao-seedance-2-5-260628"
|
||||
|
||||
def test_doubao_prefix_passthrough(self):
|
||||
fn = self._import_target()
|
||||
assert fn("doubao-seedance-2-5-260628") == "doubao-seedance-2-5-260628"
|
||||
|
||||
def test_ep_prefix_passthrough(self):
|
||||
fn = self._import_target()
|
||||
assert fn("ep-20260721114705-b568m") == "ep-20260721114705-b568m"
|
||||
|
||||
def test_seedance_2_5_alias(self):
|
||||
fn = self._import_target()
|
||||
assert fn("seedance-2.5") == "doubao-seedance-2-5-260628"
|
||||
|
||||
def test_seedance_2_0_alias(self):
|
||||
fn = self._import_target()
|
||||
assert fn("seedance-2.0") == "doubao-seedance-2-0-260128"
|
||||
|
||||
def test_seedance_2_0_fast_alias(self):
|
||||
fn = self._import_target()
|
||||
assert fn("seedance-2.0-fast") == "doubao-seedance-2-0-fast-260128"
|
||||
|
||||
def test_seedance_2_0_mini_alias(self):
|
||||
fn = self._import_target()
|
||||
assert fn("seedance-2.0-mini") == "doubao-seedance-2-0-mini-260615"
|
||||
|
||||
def test_wan_3_0_returns_dashscope_provider(self):
|
||||
from packages.shared.ai_client import _resolve_video_provider_and_id
|
||||
|
||||
prov, mid, cfg = _resolve_video_provider_and_id("wan-3.0")
|
||||
assert prov == "dashscope"
|
||||
assert mid == "wan3.0-video"
|
||||
assert cfg.get("billing_mode") == "per_second"
|
||||
|
||||
def test_seedance_2_5_uppercase(self):
|
||||
fn = self._import_target()
|
||||
assert fn("Seedance-2.5") == "doubao-seedance-2-5-260628"
|
||||
|
||||
def test_seedance_dot_normalize(self):
|
||||
fn = self._import_target()
|
||||
# dot 形式 "seedance-2.5" 直接命中 domain config 的 key(与 2-5 同等)
|
||||
assert fn("seedance-2.5") == "doubao-seedance-2-5-260628"
|
||||
|
||||
def test_unknown_model_falls_back_to_default_seedance_2_5(self, caplog):
|
||||
fn = self._import_target()
|
||||
import logging
|
||||
|
||||
# 未知 model key 会通过 get_viral_video_model_config 回落到 seedance-2.5
|
||||
with caplog.at_level(logging.WARNING, logger="shared.ai_client"):
|
||||
assert fn("some-random-model") == "doubao-seedance-2-5-260628"
|
||||
|
||||
|
||||
# ── #2165 详细错误信息和 last_video_error ─────────────────────────
|
||||
|
||||
|
||||
class TestVideoGenerationLastError:
|
||||
def test_create_400_portrait_returns_user_message(self, tmp_path):
|
||||
"""#2169: HTTP 400 + 真人拦截关键词 → 自动尝试即梦兜底;即梦未配时返回 portrait_intercept。"""
|
||||
client = _make_client(max_retries=0)
|
||||
create_resp = MagicMock()
|
||||
create_resp.status_code = 400
|
||||
create_resp.text = '{"error":{"code":"ContentRisk","message":"Real person face detected in reference image, portrait blocked"}}'
|
||||
create_resp.json.return_value = {"error": {"code": "ContentRisk", "message": "..."}}
|
||||
create_resp.raise_for_status.side_effect = httpx.HTTPStatusError(
|
||||
"bad", request=MagicMock(), response=create_resp
|
||||
)
|
||||
# 信任链:Seedream 会先被调用来 AI 化;这里 mock Seedream 也失败,回退原图直传,
|
||||
# 原图直传被 400 portrait 拦截,最终返回 portrait_intercept。
|
||||
seedream_resp = MagicMock()
|
||||
seedream_resp.status_code = 400
|
||||
seedream_resp.text = '{"error":{"code":"ContentRisk","message":"sensitive"}}'
|
||||
seedream_resp.json.return_value = {"error": {"code": "ContentRisk", "message": "sensitive"}}
|
||||
seedream_resp.raise_for_status.side_effect = httpx.HTTPStatusError(
|
||||
"bad", request=MagicMock(), response=seedream_resp
|
||||
)
|
||||
|
||||
def fake_post(url, **kwargs):
|
||||
# 第一次 POST 是 Seedream(/images/generations),返回 portrait 拦截
|
||||
# 回退原图直传后第二次 POST 是 Seedance(/contents/generations/tasks),也返回 portrait 拦截
|
||||
return create_resp
|
||||
|
||||
with (
|
||||
patch("packages.shared.ai_client.httpx.post", side_effect=fake_post),
|
||||
patch("packages.shared.ai_client.time.sleep", return_value=None),
|
||||
patch("packages.shared.ai_client.get_shared_settings") as mock_s,
|
||||
):
|
||||
mock_s.return_value = MagicMock(
|
||||
doubao_video_poll_interval=0, doubao_video_timeout=1, doubao_video_model="seedance"
|
||||
)
|
||||
result = client.video_generation("p", output_dir=str(tmp_path), image_url="https://img/x.jpg")
|
||||
assert result is None
|
||||
err = client.get_last_video_error()
|
||||
assert err["error_code"] == "portrait_intercept"
|
||||
assert "真人" in err["user_message"] or "肖像" in err["user_message"] or "审核" in err["user_message"]
|
||||
assert err["status_code"] in (0, 400)
|
||||
|
||||
def test_create_401_returns_auth_error(self, tmp_path):
|
||||
client = _make_client(max_retries=0)
|
||||
create_resp = MagicMock()
|
||||
create_resp.status_code = 401
|
||||
create_resp.text = '{"error":{"message":"Unauthorized"}}'
|
||||
create_resp.json.return_value = {"error": {"message": "Unauthorized"}}
|
||||
create_resp.raise_for_status.side_effect = httpx.HTTPStatusError(
|
||||
"auth", request=MagicMock(), response=create_resp
|
||||
)
|
||||
with (
|
||||
patch("packages.shared.ai_client.httpx.post", return_value=create_resp),
|
||||
patch("packages.shared.ai_client.time.sleep", return_value=None),
|
||||
patch("packages.shared.ai_client.get_shared_settings") as mock_s,
|
||||
):
|
||||
mock_s.return_value = MagicMock(
|
||||
doubao_video_poll_interval=0, doubao_video_timeout=1, doubao_video_model="seedance"
|
||||
)
|
||||
result = client.video_generation("p", output_dir=str(tmp_path))
|
||||
assert result is None
|
||||
err = client.get_last_video_error()
|
||||
assert err["error_code"] == "auth_error"
|
||||
assert err["status_code"] == 401
|
||||
|
||||
def test_poll_failed_returns_task_failed_error(self, tmp_path):
|
||||
"""轮询 status=failed 时应记录 task_failed 错误并含 detail。"""
|
||||
client = _make_client(max_retries=0)
|
||||
create_resp = MagicMock()
|
||||
create_resp.status_code = 200
|
||||
create_resp.json.return_value = {"id": "t-fail"}
|
||||
create_resp.raise_for_status = MagicMock()
|
||||
poll_resp = MagicMock()
|
||||
poll_resp.status_code = 200
|
||||
poll_resp.json.return_value = {
|
||||
"status": "failed",
|
||||
"error": {"code": "InvalidParam", "message": "resolution invalid"},
|
||||
}
|
||||
poll_resp.raise_for_status = MagicMock()
|
||||
with (
|
||||
patch("packages.shared.ai_client.httpx.post", return_value=create_resp),
|
||||
patch("packages.shared.ai_client.httpx.get", return_value=poll_resp),
|
||||
patch("packages.shared.ai_client.time.sleep", return_value=None),
|
||||
patch("packages.shared.ai_client.time.time", side_effect=_fake_time_factory()),
|
||||
patch("packages.shared.ai_client.get_shared_settings") as mock_s,
|
||||
):
|
||||
mock_s.return_value = MagicMock(
|
||||
doubao_video_poll_interval=0, doubao_video_timeout=10, doubao_video_model="seedance"
|
||||
)
|
||||
result = client.video_generation("p", output_dir=str(tmp_path))
|
||||
assert result is None
|
||||
err = client.get_last_video_error()
|
||||
assert err["error_code"] == "task_failed"
|
||||
assert "InvalidParam" in err.get("detail", "") or err["status_code"] == 200
|
||||
|
||||
|
||||
class TestAiServiceLastVideoError:
|
||||
def test_call_video_generation_returns_none_sets_error(self):
|
||||
"""失败后 get_last_video_error 应返回结构化错误信息。"""
|
||||
from packages.shared import ai_service
|
||||
|
||||
mock_client = MagicMock()
|
||||
mock_client.is_available = True
|
||||
mock_client.last_video_error = {"error_code": "unknown", "user_message": "test"}
|
||||
mock_client.get_last_video_error.return_value = {"error_code": "unknown", "user_message": "test"}
|
||||
mock_client.video_generation.return_value = None
|
||||
with patch("packages.shared.ai_service.get_doubao_client", return_value=mock_client):
|
||||
assert ai_service.call_video_generation("p") is None
|
||||
err = ai_service.get_last_video_error()
|
||||
assert err["error_code"] == "unknown"
|
||||
assert "user_message" in err
|
||||
@@ -0,0 +1,198 @@
|
||||
"""catalog 应用服务单测:会员套餐 / 积分包从共享库读取与字段映射。"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from unittest.mock import MagicMock, patch
|
||||
|
||||
import pytest
|
||||
|
||||
|
||||
@pytest.fixture(autouse=True)
|
||||
def _clear_cache():
|
||||
from packages.application.catalog import admin_catalog
|
||||
|
||||
admin_catalog._cache.clear()
|
||||
yield
|
||||
admin_catalog._cache.clear()
|
||||
|
||||
|
||||
def _row(**kw):
|
||||
row = MagicMock()
|
||||
for k, v in kw.items():
|
||||
setattr(row, k, v)
|
||||
return row
|
||||
|
||||
|
||||
class TestMembershipPlans:
|
||||
def test_yearly_plan_mapping(self):
|
||||
from packages.application.catalog import admin_catalog
|
||||
|
||||
row = _row(
|
||||
plan_key="premium_yearly",
|
||||
name="高级会员年卡",
|
||||
description="年度订阅",
|
||||
monthly_price=0,
|
||||
yearly_price=399,
|
||||
quotas={"4k": True, "batch_render": True, "credits_per_month": 500},
|
||||
display_order=1,
|
||||
)
|
||||
session = MagicMock()
|
||||
session.execute.return_value.fetchall.return_value = [row]
|
||||
sl = MagicMock(return_value=session)
|
||||
|
||||
with patch("packages.adapters.sqlalchemy_impl.session.SessionLocal", sl, create=True):
|
||||
plans = admin_catalog.get_membership_plans()
|
||||
|
||||
assert len(plans) == 1
|
||||
p = plans[0]
|
||||
assert p["plan_id"] == "premium_yearly"
|
||||
assert p["billing_cycle"] == "yearly"
|
||||
assert p["price_cents"] == 39900
|
||||
assert p["monthly_price_cents"] == 3325
|
||||
assert p["duration_days"] == 365
|
||||
assert p["features"]["4K 超清分辨率"] is True
|
||||
assert p["features"]["credits_per_month"] == 500
|
||||
session.close.assert_called_once()
|
||||
|
||||
def test_monthly_plan_mapping(self):
|
||||
from packages.application.catalog import admin_catalog
|
||||
|
||||
row = _row(
|
||||
plan_key="premium_monthly",
|
||||
name="高级会员月卡",
|
||||
description=None,
|
||||
monthly_price=39,
|
||||
yearly_price=0,
|
||||
quotas=None,
|
||||
display_order=2,
|
||||
)
|
||||
session = MagicMock()
|
||||
session.execute.return_value.fetchall.return_value = [row]
|
||||
sl = MagicMock(return_value=session)
|
||||
|
||||
with patch("packages.adapters.sqlalchemy_impl.session.SessionLocal", sl, create=True):
|
||||
plans = admin_catalog.get_membership_plans()
|
||||
|
||||
assert len(plans) == 1
|
||||
p = plans[0]
|
||||
assert p["billing_cycle"] == "monthly"
|
||||
assert p["price_cents"] == 3900
|
||||
assert p["monthly_price_cents"] == 3900
|
||||
assert p["duration_days"] == 30
|
||||
assert p["features"] == {}
|
||||
|
||||
def test_both_cycles_expanded(self):
|
||||
from packages.application.catalog import admin_catalog
|
||||
|
||||
row = _row(
|
||||
plan_key="premium",
|
||||
name="高级会员",
|
||||
description=None,
|
||||
monthly_price=39,
|
||||
yearly_price=399,
|
||||
quotas={},
|
||||
display_order=1,
|
||||
)
|
||||
session = MagicMock()
|
||||
session.execute.return_value.fetchall.return_value = [row]
|
||||
sl = MagicMock(return_value=session)
|
||||
|
||||
with patch("packages.adapters.sqlalchemy_impl.session.SessionLocal", sl, create=True):
|
||||
plans = admin_catalog.get_membership_plans()
|
||||
|
||||
cycles = {p["billing_cycle"] for p in plans}
|
||||
assert cycles == {"yearly", "monthly"}
|
||||
|
||||
def test_no_session_returns_empty(self):
|
||||
from packages.application.catalog import admin_catalog
|
||||
|
||||
with patch("packages.adapters.sqlalchemy_impl.session.SessionLocal", None, create=True):
|
||||
assert admin_catalog.get_membership_plans() == []
|
||||
|
||||
|
||||
class TestPointsPackages:
|
||||
def test_package_mapping_with_bonus(self):
|
||||
from packages.application.catalog import admin_catalog
|
||||
|
||||
row = _row(
|
||||
package_key="pkg_100",
|
||||
name="100元充值包",
|
||||
price=100,
|
||||
credits=1000,
|
||||
bonus_credits=100,
|
||||
is_recommended=True,
|
||||
description="推荐",
|
||||
sort_order=4,
|
||||
)
|
||||
session = MagicMock()
|
||||
session.execute.return_value.fetchall.return_value = [row]
|
||||
sl = MagicMock(return_value=session)
|
||||
|
||||
with patch("packages.adapters.sqlalchemy_impl.session.SessionLocal", sl, create=True):
|
||||
packages = admin_catalog.get_points_packages()
|
||||
|
||||
assert len(packages) == 1
|
||||
pkg = packages[0]
|
||||
assert pkg["code"] == "pkg_100"
|
||||
assert pkg["points"] == 1100
|
||||
assert pkg["price_cents"] == 10000
|
||||
assert pkg["is_recommended"] is True
|
||||
assert pkg["unit_price"] == "¥0.091/积分"
|
||||
|
||||
def test_zero_credits_unit_price_safe(self):
|
||||
from packages.application.catalog import admin_catalog
|
||||
|
||||
row = _row(
|
||||
package_key="pkg_0",
|
||||
name="空包",
|
||||
price=0,
|
||||
credits=0,
|
||||
bonus_credits=0,
|
||||
is_recommended=False,
|
||||
description=None,
|
||||
sort_order=0,
|
||||
)
|
||||
session = MagicMock()
|
||||
session.execute.return_value.fetchall.return_value = [row]
|
||||
sl = MagicMock(return_value=session)
|
||||
|
||||
with patch("packages.adapters.sqlalchemy_impl.session.SessionLocal", sl, create=True):
|
||||
packages = admin_catalog.get_points_packages()
|
||||
|
||||
assert packages[0]["points"] == 0
|
||||
assert packages[0]["price_cents"] == 0
|
||||
assert packages[0]["unit_price"] == "¥0.000/积分"
|
||||
|
||||
def test_no_session_returns_empty(self):
|
||||
from packages.application.catalog import admin_catalog
|
||||
|
||||
with patch("packages.adapters.sqlalchemy_impl.session.SessionLocal", None, create=True):
|
||||
assert admin_catalog.get_points_packages() == []
|
||||
|
||||
|
||||
class TestPackagesRoute:
|
||||
def test_get_packages_route_returns_items(self):
|
||||
from app.api.routes.points import get_packages
|
||||
|
||||
cu = MagicMock()
|
||||
cu.user.member_type = None
|
||||
rows = [
|
||||
{
|
||||
"code": "pkg_10",
|
||||
"name": "10元充值包",
|
||||
"points": 100,
|
||||
"price_cents": 1000,
|
||||
"unit_price": "¥0.100/积分",
|
||||
}
|
||||
]
|
||||
with patch(
|
||||
"packages.application.catalog.admin_catalog.get_points_packages",
|
||||
return_value=rows,
|
||||
):
|
||||
resp = get_packages(current_user=cu)
|
||||
|
||||
assert len(resp.packages) == 1
|
||||
item = resp.packages[0]
|
||||
assert item.code == "pkg_10"
|
||||
assert item.points == 100
|
||||
assert item.price_cents == 1000
|
||||
@@ -95,25 +95,29 @@ class TestCheckEndpointWhenDisabled:
|
||||
# 不再走免费额度判定
|
||||
svc.check_daily_free_clip.assert_not_called()
|
||||
|
||||
def test_unknown_scene_still_400_when_disabled(self):
|
||||
"""未知 scene 即使系统关闭也返回 400(参数校验先于开关)。"""
|
||||
def test_unknown_scene_allowed_when_disabled(self):
|
||||
"""任意 scene_key(含未知/已下线)系统关闭时都返回 allowed=True, cost=0。"""
|
||||
from app.api.routes.points import check_points
|
||||
from app.schemas.points import PointsCheckRequest
|
||||
from fastapi import HTTPException
|
||||
|
||||
with pytest.raises(HTTPException) as exc:
|
||||
check_points(body=PointsCheckRequest(scene_key="nope"), current_user=_make_cu(), db=MagicMock())
|
||||
assert exc.value.status_code == 400
|
||||
svc = MagicMock()
|
||||
svc.get_or_create_account.return_value = {"balance": 0}
|
||||
with (
|
||||
patch("app.api.routes.points._credits_enabled", return_value=False),
|
||||
patch("app.api.routes.points._get_service", return_value=svc),
|
||||
):
|
||||
resp = check_points(body=PointsCheckRequest(scene_key="nope"), current_user=_make_cu(), db=MagicMock())
|
||||
assert resp.allowed is True
|
||||
assert resp.required_points == 0
|
||||
|
||||
def test_check_enabled_calculates_cost(self):
|
||||
"""开关开启时保持原有计费校验。"""
|
||||
"""开关开启时保持原有计费校验(voice_clone_synth 正常计费)。"""
|
||||
from app.api.routes.points import check_points
|
||||
from app.schemas.points import PointsCheckRequest
|
||||
|
||||
svc = MagicMock()
|
||||
svc.check_daily_free_clip.return_value = False
|
||||
svc.get_or_create_account.return_value = {"balance": 100}
|
||||
body = PointsCheckRequest(scene_key="ai_title", quantity=1)
|
||||
body = PointsCheckRequest(scene_key="voice_clone_synth", quantity=1, duration_minutes=1)
|
||||
|
||||
with (
|
||||
patch("app.api.routes.points._credits_enabled", return_value=True),
|
||||
@@ -123,6 +127,23 @@ class TestCheckEndpointWhenDisabled:
|
||||
|
||||
assert resp.required_points == 2 # 免费用户 ceil(1*1.15)=2
|
||||
|
||||
def test_retired_scene_free_when_enabled(self):
|
||||
"""开关开启时,已下线场景返回 cost=0,直接放行。"""
|
||||
from app.api.routes.points import check_points
|
||||
from app.schemas.points import PointsCheckRequest
|
||||
|
||||
svc = MagicMock()
|
||||
svc.get_or_create_account.return_value = {"balance": 0}
|
||||
with (
|
||||
patch("app.api.routes.points._credits_enabled", return_value=True),
|
||||
patch("app.api.routes.points._get_service", return_value=svc),
|
||||
):
|
||||
for scene in ["ai_voice", "ai_title", "ai_video", "ai_digital_human", "nope"]:
|
||||
body = PointsCheckRequest(scene_key=scene, quantity=1)
|
||||
resp = check_points(body=body, current_user=_make_cu(), db=MagicMock())
|
||||
assert resp.required_points == 0, f"{scene} should be free"
|
||||
assert resp.allowed is True
|
||||
|
||||
|
||||
# ── /points/deduct:关闭时 no-op,余额不变 ────────────────────────────────
|
||||
|
||||
@@ -217,13 +238,24 @@ class TestQueryEndpointsRemainAvailable:
|
||||
|
||||
|
||||
class TestBusinessRoutesBypassWhenDisabled:
|
||||
def test_lipsync_route_skips_points(self):
|
||||
"""lipsync 创建任务路由:settings.points_enabled=False 时不构造 PointsService。"""
|
||||
def test_lipsync_route_has_no_points_logic(self):
|
||||
"""lipsync 路由:已移除手动扣点代码(不导入 PointsService/calculate_points_cost)。"""
|
||||
import inspect
|
||||
|
||||
from app.api.routes import lipsync as lipsync_mod
|
||||
|
||||
assert bool(getattr(lipsync_mod.settings, "points_enabled", False)) is False
|
||||
src = inspect.getsource(lipsync_mod)
|
||||
assert "PointsService" not in src
|
||||
assert "calculate_points_cost" not in src
|
||||
assert "_points_deducted" not in src
|
||||
|
||||
def test_tts_route_has_no_points_logic(self):
|
||||
"""tts 路由:已移除手动扣点代码(不导入 PointsService/calculate_points_cost)。"""
|
||||
import inspect
|
||||
|
||||
def test_tts_route_skips_points(self):
|
||||
from app.api.routes import tts as tts_mod
|
||||
|
||||
assert bool(getattr(tts_mod.settings, "points_enabled", False)) is False
|
||||
src = inspect.getsource(tts_mod)
|
||||
assert "PointsService" not in src
|
||||
assert "calculate_points_cost" not in src
|
||||
assert "_points_deducted" not in src
|
||||
|
||||
@@ -0,0 +1,178 @@
|
||||
"""tests for packages/shared/dashscope_client.py (#2159 Wan 3.0 DashScope client)."""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from unittest.mock import MagicMock, mock_open, patch
|
||||
|
||||
import httpx
|
||||
import pytest
|
||||
|
||||
_SINGLETON = "_DASHSCOPE_CLIENT_SINGLETON"
|
||||
|
||||
|
||||
@pytest.fixture(autouse=True)
|
||||
def reset_singleton():
|
||||
import packages.shared.dashscope_client as d
|
||||
|
||||
# 兼容实际 singleton 名
|
||||
for name in ("_DASHSCOPE_CLIENT_SINGLETON", "_dashscope_client"):
|
||||
if hasattr(d, name):
|
||||
setattr(d, name, None)
|
||||
yield
|
||||
for name in ("_DASHSCOPE_CLIENT_SINGLETON", "_dashscope_client"):
|
||||
if hasattr(d, name):
|
||||
setattr(d, name, None)
|
||||
|
||||
|
||||
def _make_settings(api_key="test-key"):
|
||||
return MagicMock(
|
||||
dashscope_api_key=api_key,
|
||||
dashscope_base_url="https://dashscope.aliyuncs.com/api/v1",
|
||||
dashscope_video_timeout=10,
|
||||
dashscope_video_poll_interval=0,
|
||||
video_dir="/tmp/videos",
|
||||
)
|
||||
|
||||
|
||||
class TestDashScopeAvailability:
|
||||
def test_unavailable_without_key(self):
|
||||
from packages.shared.dashscope_client import get_dashscope_client
|
||||
|
||||
with patch("packages.shared.dashscope_client.get_shared_settings") as ms:
|
||||
ms.return_value = _make_settings(api_key="")
|
||||
assert get_dashscope_client() is None
|
||||
|
||||
def test_available_with_key(self):
|
||||
from packages.shared.dashscope_client import get_dashscope_client
|
||||
|
||||
with patch("packages.shared.dashscope_client.get_shared_settings") as ms:
|
||||
ms.return_value = _make_settings()
|
||||
c = get_dashscope_client()
|
||||
assert c is not None
|
||||
assert c.is_available is True
|
||||
|
||||
|
||||
def _mock_stream_response(min_size=2048):
|
||||
"""构造 httpx.stream 上下文返回值,模拟返回若干字节的 mp4 内容。"""
|
||||
m = MagicMock()
|
||||
m.status_code = 200
|
||||
chunk = b"x" * min_size
|
||||
m.iter_bytes.return_value = [chunk]
|
||||
ctx = MagicMock()
|
||||
ctx.__enter__.return_value = m
|
||||
return ctx
|
||||
|
||||
|
||||
class TestDashScopeVideoGeneration:
|
||||
def test_happy_path_returns_video_path(self):
|
||||
"""POST create → GET poll (SUCCEEDED) → download → returns path + correct payload."""
|
||||
import packages.shared.dashscope_client as d
|
||||
|
||||
with patch("packages.shared.dashscope_client.get_shared_settings") as ms:
|
||||
ms.return_value = _make_settings()
|
||||
c = d.DashScopeClient()
|
||||
|
||||
create_resp = MagicMock(status_code=200)
|
||||
create_resp.json.return_value = {"output": {"task_id": "task-abc"}}
|
||||
poll_resp = MagicMock(status_code=200)
|
||||
poll_resp.json.return_value = {
|
||||
"output": {"task_status": "SUCCEEDED", "video_url": "http://x/y.mp4"},
|
||||
"usage": {"billed_duration": 10},
|
||||
}
|
||||
# fake file: write enough bytes to pass the size>=1024 check
|
||||
m_open = mock_open()
|
||||
m_open.return_value.write.return_value = None
|
||||
fake_size = {"/tmp/videos/wan_task-abc.mp4": 4096}
|
||||
|
||||
def fake_getsize(p):
|
||||
return fake_size.get(p, 0)
|
||||
|
||||
def fake_exists(p):
|
||||
return p in fake_size
|
||||
|
||||
with (
|
||||
patch.object(d.httpx, "post", return_value=create_resp) as mock_post,
|
||||
patch.object(d.httpx, "get", return_value=poll_resp),
|
||||
patch.object(d.httpx, "stream", return_value=_mock_stream_response()),
|
||||
patch("packages.shared.dashscope_client.time.sleep"),
|
||||
patch("packages.shared.dashscope_client.os.makedirs"),
|
||||
patch("builtins.open", m_open),
|
||||
patch("packages.shared.dashscope_client.os.path.getsize", side_effect=fake_getsize),
|
||||
patch("packages.shared.dashscope_client.os.path.exists", side_effect=fake_exists),
|
||||
):
|
||||
res = c.video_generation(
|
||||
prompt="test",
|
||||
duration=5,
|
||||
ratio="9:16",
|
||||
resolution="720p",
|
||||
output_dir="/tmp/videos",
|
||||
)
|
||||
assert res is not None, "expected success"
|
||||
assert res["video_path"] == "/tmp/videos/wan_task-abc.mp4"
|
||||
_, kwargs = mock_post.call_args
|
||||
body = kwargs["json"]
|
||||
assert body["parameters"]["resolution"] == "720P"
|
||||
assert body["model"] == "wan3.0-video"
|
||||
|
||||
def test_create_http_error_returns_none(self):
|
||||
import packages.shared.dashscope_client as d
|
||||
|
||||
with patch("packages.shared.dashscope_client.get_shared_settings") as ms:
|
||||
ms.return_value = _make_settings()
|
||||
c = d.DashScopeClient()
|
||||
err_resp = MagicMock(status_code=400, text="bad")
|
||||
err_resp.raise_for_status.side_effect = RuntimeError("bad")
|
||||
with patch.object(d.httpx, "post", return_value=err_resp):
|
||||
res = c.video_generation(
|
||||
prompt="test", duration=5, ratio="9:16", resolution="720p", output_dir="/tmp/videos"
|
||||
)
|
||||
assert res is None
|
||||
|
||||
def test_poll_failed_returns_none(self):
|
||||
import packages.shared.dashscope_client as d
|
||||
|
||||
with patch("packages.shared.dashscope_client.get_shared_settings") as ms:
|
||||
ms.return_value = _make_settings()
|
||||
c = d.DashScopeClient()
|
||||
create_resp = MagicMock(status_code=200)
|
||||
create_resp.json.return_value = {"output": {"task_id": "task-abc"}}
|
||||
poll_resp = MagicMock(status_code=200)
|
||||
poll_resp.json.return_value = {"output": {"task_status": "FAILED", "message": "nope"}}
|
||||
with (
|
||||
patch.object(d.httpx, "post", return_value=create_resp),
|
||||
patch.object(d.httpx, "get", return_value=poll_resp),
|
||||
patch("packages.shared.dashscope_client.time.sleep"),
|
||||
):
|
||||
res = c.video_generation(
|
||||
prompt="test", duration=5, ratio="9:16", resolution="720p", output_dir="/tmp/videos"
|
||||
)
|
||||
assert res is None
|
||||
|
||||
def test_empty_prompt_returns_none(self):
|
||||
import packages.shared.dashscope_client as d
|
||||
|
||||
with patch("packages.shared.dashscope_client.get_shared_settings") as ms:
|
||||
ms.return_value = _make_settings()
|
||||
c = d.DashScopeClient()
|
||||
assert (
|
||||
c.video_generation(prompt=" ", duration=5, ratio="9:16", resolution="720p", output_dir="/tmp/videos")
|
||||
is None
|
||||
)
|
||||
|
||||
def test_create_400_sets_last_video_error(self, tmp_path):
|
||||
"""创建任务 HTTP 400 时应写 last_video_error。"""
|
||||
from packages.shared import dashscope_client as dc
|
||||
|
||||
dc._DASHSCOPE_CLIENT_SINGLETON = None
|
||||
with patch.dict("os.environ", {"DASHSCOPE_API_KEY": "test-key"}):
|
||||
c = dc.DashScopeClient()
|
||||
r = MagicMock()
|
||||
r.status_code = 401
|
||||
r.text = '{"code":"InvalidApiKey","message":"bad key"}'
|
||||
r.raise_for_status.side_effect = httpx.HTTPStatusError("auth", request=MagicMock(), response=r)
|
||||
with patch.object(dc.httpx, "post", return_value=r), patch.object(dc, "time"):
|
||||
out = c.video_generation("p", output_dir=str(tmp_path))
|
||||
assert out is None
|
||||
err = c.get_last_video_error()
|
||||
assert err["error_code"] == "auth_error"
|
||||
assert c.last_video_error is not None
|
||||
@@ -1,28 +1,25 @@
|
||||
"""AI封面生成 积分扣点单元测试 (#1895 P2 step 2.7)"""
|
||||
"""封面生成 — v1.6.2 起免费,不扣积分"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from unittest.mock import MagicMock, patch
|
||||
|
||||
import pytest
|
||||
|
||||
import packages.middleware.points_gate as _pg_module
|
||||
|
||||
|
||||
@pytest.fixture(autouse=True)
|
||||
def _enable(monkeypatch):
|
||||
monkeypatch.setattr(_pg_module, "_points_gate_enabled", lambda: True)
|
||||
yield
|
||||
|
||||
|
||||
class TestGenerationCoverPoints:
|
||||
def test_ai_cover_cost(self):
|
||||
class TestGenerationCoverFree:
|
||||
def test_ai_cover_returns_zero_cost(self):
|
||||
from packages.domain.points_rules import calculate_points_cost
|
||||
|
||||
assert calculate_points_cost("ai_cover", is_member=False) == 2
|
||||
assert calculate_points_cost("ai_cover", is_member=True, member_type="yearly") >= 0
|
||||
assert calculate_points_cost("ai_cover", is_member=False, quantity=1) == 0
|
||||
assert calculate_points_cost("ai_cover", is_member=True, quantity=10) == 0
|
||||
|
||||
def test_decorator_attached(self):
|
||||
def test_no_points_gate_decorator(self):
|
||||
from app.api.routes.generation_cover import generate_cover
|
||||
|
||||
assert hasattr(generate_cover, "__wrapped__"), "missing @points_gate"
|
||||
assert not hasattr(generate_cover, "__wrapped__")
|
||||
|
||||
def test_endpoint_has_no_points_logic(self):
|
||||
import inspect
|
||||
|
||||
from app.api.routes import generation_cover as mod
|
||||
|
||||
src = inspect.getsource(mod)
|
||||
assert "PointsService" not in src
|
||||
assert "deduct_points" not in src
|
||||
|
||||
@@ -1,54 +1,31 @@
|
||||
"""视频预览生成 积分扣点单元测试 (#1895 P2 step 2.5)"""
|
||||
"""视频预览生成 — v1.6.2 起免费,不扣积分"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from unittest.mock import MagicMock, patch
|
||||
|
||||
import pytest
|
||||
|
||||
import packages.middleware.points_gate as _pg_module
|
||||
|
||||
|
||||
@pytest.fixture(autouse=True)
|
||||
def _enable(monkeypatch):
|
||||
monkeypatch.setattr(_pg_module, "_points_gate_enabled", lambda: True)
|
||||
yield
|
||||
|
||||
|
||||
class TestGenerationPreviewPoints:
|
||||
def test_ai_video_cost(self):
|
||||
class TestGenerationPreviewFree:
|
||||
def test_ai_video_returns_zero_cost(self):
|
||||
from packages.domain.points_rules import calculate_points_cost
|
||||
|
||||
assert calculate_points_cost("ai_video", is_member=False) == 4
|
||||
assert calculate_points_cost("ai_video", is_member=True, member_type="monthly") == 2
|
||||
assert calculate_points_cost("ai_video", is_member=False) == 0
|
||||
assert calculate_points_cost("ai_video", is_member=True, member_type="monthly", duration_minutes=10) == 0
|
||||
|
||||
def test_insufficient_raises_402(self):
|
||||
from app.api.routes.generation_preview import create_preview_generation_task
|
||||
from app.schemas.generation_task import CreatePreviewGenerationTaskRequest
|
||||
from fastapi import HTTPException
|
||||
|
||||
db = MagicMock()
|
||||
cu = MagicMock()
|
||||
cu.user.id = "u1"
|
||||
cu.user.is_member = False
|
||||
cu.user.member_type = None
|
||||
req = CreatePreviewGenerationTaskRequest(template_id="t1", asset_ids=["a1"], preview_count=1)
|
||||
with patch("packages.domain.points_service.PointsService") as MS:
|
||||
svc = MagicMock()
|
||||
svc.check_daily_free_clip.return_value = False
|
||||
svc.deduct_points.return_value = {"success": False, "balance": 0}
|
||||
MS.return_value = svc
|
||||
with pytest.raises(HTTPException) as ei:
|
||||
create_preview_generation_task(
|
||||
request=req,
|
||||
authenticated_user=cu,
|
||||
db=db,
|
||||
generation_task_repository=MagicMock(),
|
||||
asset_repo=MagicMock(),
|
||||
)
|
||||
assert ei.value.status_code == 402
|
||||
|
||||
def test_decorator_attached(self):
|
||||
def test_no_points_gate_decorator(self):
|
||||
"""预览生成路由已移除 @points_gate。"""
|
||||
from app.api.routes.generation_preview import create_preview_generation_task
|
||||
|
||||
assert hasattr(create_preview_generation_task, "__wrapped__"), "missing @points_gate"
|
||||
# 移除装饰器后 __wrapped__ 不再存在
|
||||
assert not hasattr(create_preview_generation_task, "__wrapped__")
|
||||
|
||||
def test_endpoint_does_not_deduct_points(self):
|
||||
"""端点不再实例化 PointsService / 调用 deduct_points(直接走业务逻辑)。"""
|
||||
import inspect
|
||||
|
||||
from app.api.routes.generation_preview import create_preview_generation_task
|
||||
|
||||
src = inspect.getsource(create_preview_generation_task)
|
||||
assert "PointsService" not in src
|
||||
assert "deduct_points" not in src
|
||||
assert "calculate_points_cost" not in src
|
||||
|
||||
@@ -1,63 +1,28 @@
|
||||
"""视频生成 积分扣点单元测试 (#1895 P2 step 2.4)"""
|
||||
"""智能混剪任务 — v1.6.2 起免费,不扣积分"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from unittest.mock import MagicMock, patch
|
||||
|
||||
import pytest
|
||||
|
||||
import packages.middleware.points_gate as _pg_module
|
||||
from unittest.mock import MagicMock
|
||||
|
||||
|
||||
@pytest.fixture(autouse=True)
|
||||
def _enable(monkeypatch):
|
||||
monkeypatch.setattr(_pg_module, "_points_gate_enabled", lambda: True)
|
||||
yield
|
||||
|
||||
|
||||
class TestGenerationTasksPoints:
|
||||
def test_ai_video_base_cost(self):
|
||||
class TestGenerationTasksFree:
|
||||
def test_ai_video_returns_zero_cost(self):
|
||||
from packages.domain.points_rules import calculate_points_cost
|
||||
|
||||
assert calculate_points_cost("ai_video", is_member=False) == 4
|
||||
assert calculate_points_cost("ai_video", is_member=True, member_type="monthly") == 2
|
||||
assert calculate_points_cost("ai_video", is_member=False, duration_minutes=5) == 0
|
||||
assert calculate_points_cost("ai_video", is_member=True, duration_minutes=10) == 0
|
||||
|
||||
def test_ai_video_quantity_scales(self):
|
||||
from packages.domain.points_rules import calculate_points_cost
|
||||
|
||||
c1 = calculate_points_cost("ai_video", is_member=False, quantity=1)
|
||||
c3 = calculate_points_cost("ai_video", is_member=False, quantity=3)
|
||||
assert c3 > c1
|
||||
|
||||
def test_insufficient_raises_402(self):
|
||||
from app.api.routes.generation_tasks import create_generation_task
|
||||
from app.schemas.generation_task import CreateGenerationTaskRequest
|
||||
from fastapi import HTTPException
|
||||
|
||||
db = MagicMock()
|
||||
cu = MagicMock()
|
||||
cu.user.id = "u1"
|
||||
cu.user.is_member = False
|
||||
cu.user.member_type = None
|
||||
req = CreateGenerationTaskRequest(template_id="t1", asset_ids=["a1"], count=1)
|
||||
with patch("packages.domain.points_service.PointsService") as MS:
|
||||
svc = MagicMock()
|
||||
svc.check_daily_free_clip.return_value = False
|
||||
svc.deduct_points.return_value = {"success": False, "balance": 0}
|
||||
MS.return_value = svc
|
||||
with pytest.raises(HTTPException) as ei:
|
||||
create_generation_task(
|
||||
request=req,
|
||||
authenticated_user=cu,
|
||||
db=db,
|
||||
generation_task_repository=MagicMock(),
|
||||
project_repository=MagicMock(),
|
||||
asset_library_repository=MagicMock(),
|
||||
asset_repository=MagicMock(),
|
||||
)
|
||||
assert ei.value.status_code == 402
|
||||
|
||||
def test_decorator_attached(self):
|
||||
def test_no_points_gate_decorator(self):
|
||||
from app.api.routes.generation_tasks import create_generation_task
|
||||
|
||||
assert hasattr(create_generation_task, "__wrapped__"), "missing @points_gate"
|
||||
assert not hasattr(create_generation_task, "__wrapped__")
|
||||
|
||||
def test_create_task_accepts_request_without_points_block(self):
|
||||
"""路由函数签名不再做扣点,但参数 points_enabled/is_member/member_type 仍保留以兼容调用方。"""
|
||||
import inspect
|
||||
|
||||
from app.api.routes.generation_tasks import create_generation_task
|
||||
|
||||
sig = inspect.signature(create_generation_task)
|
||||
# 函数存在
|
||||
assert callable(create_generation_task)
|
||||
|
||||
@@ -44,7 +44,7 @@ class TestCheckDatabase:
|
||||
assert result["type"] == "postgresql"
|
||||
assert result["message"] == "Database connection successful"
|
||||
mock_psycopg.connect.assert_called_once_with(
|
||||
"postgresql+psycopg://test:test@localhost/test", connect_timeout=3
|
||||
"postgresql://test:test@localhost/test", connect_timeout=3
|
||||
)
|
||||
mock_cur.execute.assert_called_once_with("SELECT 1")
|
||||
mock_conn.close.assert_called_once()
|
||||
@@ -96,7 +96,7 @@ class TestCheckMigrations:
|
||||
assert result["status"] == "healthy"
|
||||
assert result["message"] == "Database migrations applied"
|
||||
mock_psycopg.connect.assert_called_once_with(
|
||||
"postgresql+psycopg://test:test@localhost/test", connect_timeout=3
|
||||
"postgresql://test:test@localhost/test", connect_timeout=3
|
||||
)
|
||||
mock_conn.close.assert_called_once()
|
||||
|
||||
|
||||
@@ -1,15 +1,16 @@
|
||||
"""lipsync 积分扣点单元测试 (#1895 P2 step 2.2)"""
|
||||
"""lipsync 口型同步 — v1.6.2 起免费,不扣积分"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import math
|
||||
from unittest.mock import MagicMock
|
||||
from types import SimpleNamespace
|
||||
from unittest.mock import MagicMock, patch
|
||||
|
||||
import pytest
|
||||
from fastapi import HTTPException
|
||||
|
||||
|
||||
def _make_cu(user_id="user-1", is_member=False, member_type=None):
|
||||
def _cu(user_id="u1", is_member=False, member_type=None):
|
||||
cu = MagicMock()
|
||||
cu.user.id = user_id
|
||||
cu.user.is_member = is_member
|
||||
@@ -17,99 +18,6 @@ def _make_cu(user_id="user-1", is_member=False, member_type=None):
|
||||
return cu
|
||||
|
||||
|
||||
class TestLipsyncDurationEstimate:
|
||||
@pytest.mark.parametrize(
|
||||
"text,expected",
|
||||
[
|
||||
("你好", 1.0),
|
||||
("你" * 240, 1.0),
|
||||
("你" * 241, 2.0),
|
||||
("你" * 1000, 5.0),
|
||||
],
|
||||
)
|
||||
def test_text_estimate(self, text, expected):
|
||||
est = max(1.0, math.ceil(len(text) / 240))
|
||||
assert est == expected
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
"seconds,expected",
|
||||
[
|
||||
(30, 1.0),
|
||||
(60, 1.0),
|
||||
(61, 2.0),
|
||||
(120, 2.0),
|
||||
(180, 3.0),
|
||||
],
|
||||
)
|
||||
def test_audio_duration_estimate(self, seconds, expected):
|
||||
est = max(1.0, math.ceil(seconds / 60.0))
|
||||
assert est == expected
|
||||
|
||||
|
||||
class TestLipsyncPointsDeduction:
|
||||
def _deduct(self, text="你好", audio_duration=None, enabled=True, success=True, balance=100, **cu_kw):
|
||||
from packages.domain.points_rules import calculate_points_cost
|
||||
|
||||
svc = MagicMock() if enabled else None
|
||||
cu = _make_cu(**cu_kw)
|
||||
if svc is None:
|
||||
return 0, cu
|
||||
if audio_duration and audio_duration > 0:
|
||||
est = max(1.0, math.ceil(audio_duration / 60.0))
|
||||
elif text:
|
||||
est = max(1.0, math.ceil(len(text) / 240))
|
||||
else:
|
||||
est = 1.0
|
||||
cost = calculate_points_cost(
|
||||
"ai_digital_human",
|
||||
is_member=getattr(cu.user, "is_member", False),
|
||||
duration_minutes=est,
|
||||
member_type=getattr(cu.user, "member_type", None),
|
||||
)
|
||||
svc.deduct_points.return_value = {"success": success, "balance": balance}
|
||||
res = svc.deduct_points(cu.user.id, cost, "ai_digital_human", MagicMock())
|
||||
if not res["success"]:
|
||||
raise HTTPException(status_code=402, detail={"code": "INSUFFICIENT_POINTS"})
|
||||
return cost, cu
|
||||
|
||||
def test_disabled(self):
|
||||
cost, _ = self._deduct(enabled=False)
|
||||
assert cost == 0
|
||||
|
||||
def test_short_text_min_1min(self):
|
||||
cost, _ = self._deduct(text="你好")
|
||||
assert cost >= 15 # 15 base/min for free user × 1.15
|
||||
|
||||
def test_audio_duration_used(self):
|
||||
cost_long, _ = self._deduct(audio_duration=180) # 3min
|
||||
cost_short, _ = self._deduct(audio_duration=30) # 1min
|
||||
assert cost_long > cost_short
|
||||
|
||||
def test_insufficient_402(self):
|
||||
with pytest.raises(HTTPException) as ei:
|
||||
self._deduct(text="你" * 500, success=False, balance=0)
|
||||
assert ei.value.status_code == 402
|
||||
|
||||
def test_member_cheaper(self):
|
||||
cm, _ = self._deduct(text="你" * 500, is_member=True, member_type="yearly")
|
||||
cf, _ = self._deduct(text="你" * 500, is_member=False)
|
||||
assert cm < cf
|
||||
|
||||
|
||||
# ── 直接调用 create_lipsync_job 覆盖扣点/402/退费分支 ──
|
||||
import importlib
|
||||
from types import SimpleNamespace
|
||||
from unittest.mock import patch
|
||||
|
||||
import packages.middleware.points_gate as _pg_module
|
||||
|
||||
|
||||
# Ensure the enable-gate fixture for lipsync also covers @points_gate (if any)
|
||||
# (the existing autouse _enable is below; importlib to avoid duplicate)
|
||||
def _do_enable(monkeypatch):
|
||||
monkeypatch.setattr(_pg_module, "_points_gate_enabled", lambda: True)
|
||||
|
||||
|
||||
def _body(**kw):
|
||||
b = MagicMock()
|
||||
defaults = dict(
|
||||
@@ -130,113 +38,76 @@ def _body(**kw):
|
||||
return b
|
||||
|
||||
|
||||
def _cu(user_id="u1", is_member=False, member_type=None):
|
||||
cu = MagicMock()
|
||||
cu.user.id = user_id
|
||||
cu.user.is_member = is_member
|
||||
cu.user.member_type = member_type
|
||||
return cu
|
||||
class TestLipsyncFree:
|
||||
"""lipsync 已移除手动扣点,业务异常仍按原状态码抛出。"""
|
||||
|
||||
def test_ai_digital_human_returns_zero_cost(self):
|
||||
from packages.domain.points_rules import calculate_points_cost
|
||||
|
||||
assert calculate_points_cost("ai_digital_human", is_member=False, duration_minutes=1) == 0
|
||||
assert calculate_points_cost("ai_digital_human", is_member=True, duration_minutes=10) == 0
|
||||
|
||||
def test_module_has_no_points_imports(self):
|
||||
import inspect
|
||||
|
||||
from app.api.routes import lipsync as mod
|
||||
|
||||
src = inspect.getsource(mod)
|
||||
assert "PointsService" not in src
|
||||
assert "calculate_points_cost" not in src
|
||||
assert "_points_deducted" not in src
|
||||
assert "settings" not in src # settings was only used for points_enabled
|
||||
|
||||
def test_docstring_at_top_of_create_lipsync_job(self):
|
||||
"""扣点块删除后,docstring 必须在函数体第一行(防止函数体中段 docstring 丢失)。"""
|
||||
import ast
|
||||
import inspect
|
||||
|
||||
class TestLipsyncEndpointPoints:
|
||||
def test_insufficient_raises_402(self, monkeypatch):
|
||||
_do_enable(monkeypatch)
|
||||
from app.api.routes.lipsync import create_lipsync_job
|
||||
|
||||
db = MagicMock()
|
||||
svc = MagicMock()
|
||||
ps = MagicMock()
|
||||
ps.deduct_points.return_value = {"success": False, "balance": 0}
|
||||
fs = MagicMock(points_enabled=True)
|
||||
with (
|
||||
patch("app.api.routes.lipsync.PointsService", return_value=ps),
|
||||
patch("app.api.routes.lipsync.settings", fs),
|
||||
):
|
||||
with pytest.raises(HTTPException) as ei:
|
||||
create_lipsync_job(body=_body(script_text="你" * 500), current_user=_cu(), db=db, svc=svc)
|
||||
assert ei.value.status_code == 402
|
||||
src = inspect.getsource(create_lipsync_job)
|
||||
tree = ast.parse(src)
|
||||
fn = tree.body[0]
|
||||
# docstring 应为函数体第一条语句
|
||||
assert (
|
||||
isinstance(fn.body[0], ast.Expr)
|
||||
and isinstance(fn.body[0].value, ast.Constant)
|
||||
and isinstance(fn.body[0].value.value, str)
|
||||
), "create_lipsync_job docstring 不在函数体开头"
|
||||
|
||||
def test_value_error_refunds(self, monkeypatch):
|
||||
_do_enable(monkeypatch)
|
||||
def test_docstring_at_top_of_preview_tts(self):
|
||||
import ast
|
||||
import inspect
|
||||
|
||||
from app.api.routes.lipsync import preview_tts
|
||||
|
||||
src = inspect.getsource(preview_tts)
|
||||
tree = ast.parse(src)
|
||||
fn = tree.body[0]
|
||||
assert (
|
||||
isinstance(fn.body[0], ast.Expr)
|
||||
and isinstance(fn.body[0].value, ast.Constant)
|
||||
and isinstance(fn.body[0].value.value, str)
|
||||
), "preview_tts docstring 不在函数体开头"
|
||||
|
||||
def test_value_error_still_raises_400(self):
|
||||
"""业务异常仍抛 400(不再退费)。"""
|
||||
from app.api.routes.lipsync import create_lipsync_job
|
||||
|
||||
db = MagicMock()
|
||||
svc = MagicMock()
|
||||
svc.create_job.side_effect = ValueError("bad input")
|
||||
ps = MagicMock()
|
||||
ps.deduct_points.return_value = {"success": True, "balance": 99}
|
||||
fs = MagicMock(points_enabled=True)
|
||||
with (
|
||||
patch("app.api.routes.lipsync.PointsService", return_value=ps),
|
||||
patch("app.api.routes.lipsync.settings", fs),
|
||||
):
|
||||
with pytest.raises(HTTPException) as ei:
|
||||
create_lipsync_job(body=_body(), current_user=_cu(), db=db, svc=svc)
|
||||
assert ei.value.status_code == 400
|
||||
assert ps.refund_points.called
|
||||
with pytest.raises(HTTPException) as ei:
|
||||
create_lipsync_job(body=_body(), current_user=_cu(), db=db, svc=svc)
|
||||
assert ei.value.status_code == 400
|
||||
|
||||
def test_mediakit_error_refunds(self, monkeypatch):
|
||||
_do_enable(monkeypatch)
|
||||
def test_success_returns_job(self):
|
||||
from app.api.routes.lipsync import create_lipsync_job
|
||||
from app.services.mediakit_client import MediaKitError
|
||||
|
||||
db = MagicMock()
|
||||
svc = MagicMock()
|
||||
svc.create_job.side_effect = MediaKitError("fail", code="InvalidInput")
|
||||
ps = MagicMock()
|
||||
ps.deduct_points.return_value = {"success": True, "balance": 99}
|
||||
fs = MagicMock(points_enabled=True)
|
||||
with (
|
||||
patch("app.api.routes.lipsync.PointsService", return_value=ps),
|
||||
patch("app.api.routes.lipsync.settings", fs),
|
||||
):
|
||||
with pytest.raises(HTTPException) as ei:
|
||||
create_lipsync_job(body=_body(), current_user=_cu(), db=db, svc=svc)
|
||||
assert ei.value.status_code == 400
|
||||
assert ps.refund_points.called
|
||||
|
||||
def test_generic_exception_refunds(self, monkeypatch):
|
||||
_do_enable(monkeypatch)
|
||||
from app.api.routes.lipsync import create_lipsync_job
|
||||
|
||||
db = MagicMock()
|
||||
svc = MagicMock()
|
||||
svc.create_job.side_effect = RuntimeError("boom")
|
||||
ps = MagicMock()
|
||||
ps.deduct_points.return_value = {"success": True, "balance": 99}
|
||||
fs = MagicMock(points_enabled=True)
|
||||
with (
|
||||
patch("app.api.routes.lipsync.PointsService", return_value=ps),
|
||||
patch("app.api.routes.lipsync.settings", fs),
|
||||
):
|
||||
with pytest.raises(HTTPException) as ei:
|
||||
create_lipsync_job(body=_body(), current_user=_cu(), db=db, svc=svc)
|
||||
assert ei.value.status_code == 400
|
||||
assert ps.refund_points.called
|
||||
|
||||
def test_audio_duration_estimation(self, monkeypatch):
|
||||
_do_enable(monkeypatch)
|
||||
from app.api.routes.lipsync import create_lipsync_job
|
||||
|
||||
from packages.domain.points_rules import calculate_points_cost
|
||||
|
||||
db = MagicMock()
|
||||
svc = MagicMock()
|
||||
job = SimpleNamespace(id="job-1", status="queued")
|
||||
svc.create_job.return_value = job
|
||||
ps = MagicMock()
|
||||
ps.deduct_points.return_value = {"success": True, "balance": 99}
|
||||
fs = MagicMock(points_enabled=True)
|
||||
with (
|
||||
patch("app.api.routes.lipsync.PointsService", return_value=ps),
|
||||
patch("app.api.routes.lipsync.settings", fs),
|
||||
):
|
||||
create_lipsync_job(
|
||||
body=_body(audio_url="http://x/a.mp3", audio_duration=180, script_text=None),
|
||||
current_user=_cu(),
|
||||
db=db,
|
||||
svc=svc,
|
||||
)
|
||||
# 180 seconds -> 3 minutes; assert deduct called with cost >= 15*3
|
||||
args = ps.deduct_points.call_args[0]
|
||||
assert args[1] >= calculate_points_cost("ai_digital_human", is_member=False, duration_minutes=3)
|
||||
# 不再依赖 settings/PointsService patch
|
||||
result = create_lipsync_job(body=_body(), current_user=_cu(), db=db, svc=svc)
|
||||
assert result is job
|
||||
|
||||
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Reference in New Issue
Block a user