Merge branch 'main' of https://gitee.com/wg123/video-gen

video-gen-api/alembic/versions/20da1d353914_repair_llm_billing_optimize_idempotency.py

@@ -0,0 +1,364 @@
+"""repair llm billing optimize idempotency
+
+Revision ID: 20da1d353914
+Revises: 6a3ea8d0b4c8
+Create Date: 2026-07-24 13:35:48.513710
+"""
+from __future__ import annotations
+
+import re
+from typing import Any, Sequence, Union
+
+from alembic import op
+import sqlalchemy as sa
+from sqlalchemy.engine import Connection
+
+
+# revision identifiers, used by Alembic.
+revision: str = "20da1d353914"
+down_revision: Union[str, None] = "6a3ea8d0b4c8"
+branch_labels: Union[str, Sequence[str], None] = None
+depends_on: Union[str, Sequence[str], None] = None
+
+
+_PROMPT_USAGE_COLUMN = "prompt_usage_snapshot_json"
+
+_INDEX_SPECS: tuple[dict[str, Any], ...] = (
+    {
+        "name": "uq_credit_records_user_refund_target",
+        "table": "credit_records",
+        "columns": ("user_id", "refund_for_biz_key"),
+        "where_sql": "type = 'refund' AND refund_for_biz_key IS NOT NULL",
+        "definition_fragments": (
+            "(user_id, refund_for_biz_key)",
+            "type",
+            "refund",
+            "refund_for_biz_key is not null",
+        ),
+        "duplicate_sql": """
+            SELECT
+                user_id,
+                refund_for_biz_key,
+                COUNT(*) AS duplicate_count
+            FROM credit_records
+            WHERE type = 'refund'
+              AND refund_for_biz_key IS NOT NULL
+            GROUP BY user_id, refund_for_biz_key
+            HAVING COUNT(*) > 1
+            ORDER BY duplicate_count DESC, user_id, refund_for_biz_key
+            LIMIT 20
+        """,
+    },
+    {
+        "name": "uq_genrec_user_idempotency_active",
+        "table": "generation_records",
+        "columns": ("user_id", "idempotency_key"),
+        "where_sql": "idempotency_key IS NOT NULL AND deleted_at IS NULL",
+        "definition_fragments": (
+            "(user_id, idempotency_key)",
+            "idempotency_key is not null",
+            "deleted_at is null",
+        ),
+        "duplicate_sql": """
+            SELECT
+                user_id,
+                idempotency_key,
+                COUNT(*) AS duplicate_count
+            FROM generation_records
+            WHERE idempotency_key IS NOT NULL
+              AND deleted_at IS NULL
+            GROUP BY user_id, idempotency_key
+            HAVING COUNT(*) > 1
+            ORDER BY duplicate_count DESC, user_id, idempotency_key
+            LIMIT 20
+        """,
+    },
+    {
+        "name": "uq_token_usage_user_biz_key",
+        "table": "token_usage",
+        "columns": ("user_id", "biz_key"),
+        "where_sql": "biz_key IS NOT NULL",
+        "definition_fragments": (
+            "(user_id, biz_key)",
+            "biz_key is not null",
+        ),
+        "duplicate_sql": """
+            SELECT
+                user_id,
+                biz_key,
+                COUNT(*) AS duplicate_count
+            FROM token_usage
+            WHERE user_id IS NOT NULL
+              AND biz_key IS NOT NULL
+            GROUP BY user_id, biz_key
+            HAVING COUNT(*) > 1
+            ORDER BY duplicate_count DESC, user_id, biz_key
+            LIMIT 20
+        """,
+    },
+)
+
+
+def _bind() -> Connection:
+    bind = op.get_bind()
+    if bind.dialect.name != "postgresql":
+        raise RuntimeError(
+            "Migration 20da1d353914 requires PostgreSQL; "
+            f"current dialect is {bind.dialect.name!r}."
+        )
+    return bind
+
+
+def _current_schema(bind: Connection) -> str:
+    schema = bind.execute(sa.text("SELECT current_schema()")).scalar_one_or_none()
+    if not schema:
+        raise RuntimeError("Unable to resolve PostgreSQL current_schema().")
+    return str(schema)
+
+
+def _require_table(bind: Connection, schema: str, table_name: str) -> None:
+    exists = bind.execute(
+        sa.text(
+            """
+            SELECT EXISTS (
+                SELECT 1
+                FROM information_schema.tables
+                WHERE table_schema = :schema
+                  AND table_name = :table_name
+            )
+            """
+        ),
+        {"schema": schema, "table_name": table_name},
+    ).scalar_one()
+    if not bool(exists):
+        raise RuntimeError(
+            f"Required table {schema}.{table_name} does not exist; "
+            "refusing to apply migration on an unexpected schema baseline."
+        )
+
+
+def _column_exists(
+    bind: Connection,
+    schema: str,
+    table_name: str,
+    column_name: str,
+) -> bool:
+    return bool(
+        bind.execute(
+            sa.text(
+                """
+                SELECT EXISTS (
+                    SELECT 1
+                    FROM information_schema.columns
+                    WHERE table_schema = :schema
+                      AND table_name = :table_name
+                      AND column_name = :column_name
+                )
+                """
+            ),
+            {
+                "schema": schema,
+                "table_name": table_name,
+                "column_name": column_name,
+            },
+        ).scalar_one()
+    )
+
+
+def _index_info(
+    bind: Connection,
+    schema: str,
+    index_name: str,
+) -> dict[str, Any] | None:
+    row = bind.execute(
+        sa.text(
+            """
+            SELECT
+                table_rel.relname AS table_name,
+                index_meta.indisvalid AS is_valid,
+                index_meta.indisunique AS is_unique,
+                pg_get_indexdef(index_rel.oid) AS index_definition
+            FROM pg_class AS index_rel
+            JOIN pg_namespace AS namespace_rel
+              ON namespace_rel.oid = index_rel.relnamespace
+            JOIN pg_index AS index_meta
+              ON index_meta.indexrelid = index_rel.oid
+            JOIN pg_class AS table_rel
+              ON table_rel.oid = index_meta.indrelid
+            WHERE namespace_rel.nspname = :schema
+              AND index_rel.relname = :index_name
+            """
+        ),
+        {"schema": schema, "index_name": index_name},
+    ).mappings().one_or_none()
+    return dict(row) if row is not None else None
+
+
+def _normalize_index_definition(value: str) -> str:
+    normalized = value.lower().replace('"', "")
+    normalized = re.sub(r"::[a-z_ ]+(?:\[\])?", "", normalized)
+    normalized = re.sub(r"[()]", lambda match: match.group(0), normalized)
+    normalized = re.sub(r"\s+", " ", normalized)
+    return normalized.strip()
+
+
+def _assert_existing_index_matches(spec: dict[str, Any], info: dict[str, Any]) -> None:
+    if str(info["table_name"]) != str(spec["table"]):
+        raise RuntimeError(
+            f"Index {spec['name']} already exists on table {info['table_name']}, "
+            f"expected table {spec['table']}."
+        )
+    if not bool(info["is_unique"]):
+        raise RuntimeError(
+            f"Index {spec['name']} already exists but is not UNIQUE."
+        )
+
+    definition = _normalize_index_definition(str(info["index_definition"] or ""))
+    missing = [
+        fragment
+        for fragment in spec["definition_fragments"]
+        if fragment not in definition
+    ]
+    if missing:
+        raise RuntimeError(
+            f"Index {spec['name']} already exists with an unexpected definition; "
+            f"missing expected fragments: {missing}. Actual definition: "
+            f"{info['index_definition']}"
+        )
+
+
+def _assert_no_duplicates(bind: Connection, spec: dict[str, Any]) -> None:
+    rows = bind.execute(sa.text(spec["duplicate_sql"])).mappings().all()
+    if not rows:
+        return
+
+    samples = "; ".join(
+        ", ".join(f"{key}={value!r}" for key, value in row.items())
+        for row in rows
+    )
+    raise RuntimeError(
+        f"Cannot create unique index {spec['name']}: duplicate historical data "
+        f"exists. Resolve the conflicts first. Samples: {samples}"
+    )
+
+
+def _quote_identifier(bind: Connection, value: str) -> str:
+    return bind.dialect.identifier_preparer.quote(value)
+
+
+def _create_missing_indexes_concurrently(
+    bind: Connection,
+    schema: str,
+) -> None:
+    missing_specs: list[dict[str, Any]] = []
+
+    for spec in _INDEX_SPECS:
+        _require_table(bind, schema, str(spec["table"]))
+        info = _index_info(bind, schema, str(spec["name"]))
+        if info is None:
+            _assert_no_duplicates(bind, spec)
+            missing_specs.append(spec)
+            continue
+
+        if bool(info["is_valid"]):
+            _assert_existing_index_matches(spec, info)
+            continue
+
+        # A failed CREATE INDEX CONCURRENTLY may leave an invalid index behind.
+        # Remove only the invalid index with this migration-owned name, then retry.
+        missing_specs.append(spec)
+
+    if not missing_specs:
+        return
+
+    context = op.get_context()
+    with context.autocommit_block():
+        for spec in missing_specs:
+            current = _index_info(bind, schema, str(spec["name"]))
+            quoted_index = _quote_identifier(bind, str(spec["name"]))
+            quoted_schema = _quote_identifier(bind, schema)
+            if current is not None:
+                if bool(current["is_valid"]):
+                    _assert_existing_index_matches(spec, current)
+                    continue
+                op.execute(
+                    sa.text(
+                        f"DROP INDEX CONCURRENTLY IF EXISTS "
+                        f"{quoted_schema}.{quoted_index}"
+                    )
+                )
+
+            quoted_table = _quote_identifier(bind, str(spec["table"]))
+            quoted_columns = ", ".join(
+                _quote_identifier(bind, str(column))
+                for column in spec["columns"]
+            )
+            op.execute(
+                sa.text(
+                    f"CREATE UNIQUE INDEX CONCURRENTLY {quoted_index} "
+                    f"ON {quoted_schema}.{quoted_table} ({quoted_columns}) "
+                    f"WHERE {spec['where_sql']}"
+                )
+            )
+
+
+def _drop_indexes_concurrently(bind: Connection, schema: str) -> None:
+    existing_names = [
+        str(spec["name"])
+        for spec in _INDEX_SPECS
+        if _index_info(bind, schema, str(spec["name"])) is not None
+    ]
+    if not existing_names:
+        return
+
+    quoted_schema = _quote_identifier(bind, schema)
+    context = op.get_context()
+    with context.autocommit_block():
+        for index_name in existing_names:
+            quoted_index = _quote_identifier(bind, index_name)
+            op.execute(
+                sa.text(
+                    f"DROP INDEX CONCURRENTLY IF EXISTS "
+                    f"{quoted_schema}.{quoted_index}"
+                )
+            )
+
+
+def upgrade() -> None:
+    bind = _bind()
+    schema = _current_schema(bind)
+
+    _require_table(bind, schema, "generation_records")
+    if not _column_exists(
+        bind,
+        schema,
+        "generation_records",
+        _PROMPT_USAGE_COLUMN,
+    ):
+        op.add_column(
+            "generation_records",
+            sa.Column(_PROMPT_USAGE_COLUMN, sa.Text(), nullable=True),
+            schema=schema,
+        )
+
+    _create_missing_indexes_concurrently(bind, schema)
+
+
+def downgrade() -> None:
+    bind = _bind()
+    schema = _current_schema(bind)
+
+    _drop_indexes_concurrently(bind, schema)
+
+    _require_table(bind, schema, "generation_records")
+    if _column_exists(
+        bind,
+        schema,
+        "generation_records",
+        _PROMPT_USAGE_COLUMN,
+    ):
+        op.drop_column(
+            "generation_records",
+            _PROMPT_USAGE_COLUMN,
+            schema=schema,
+        )

video-gen-api/app/api/v1/auth.py

@@ -360,10 +360,10 @@ async def get_site_info(db: AsyncSession = Depends(get_db)):
         return f"{base_url}{path}"
 
     return {
-        "site_name": info.get("site_name", "VideoGen.AI"),
+        "site_name": info.get("site_name", "智创"),
         "site_logo": to_full_url(info.get("site_logo")),
         "user_agreement_privacy_url": to_full_url(info.get("user_agreement_privacy_url")),
-        "site_copyright": info.get("site_copyright", "© 2024 民众智创 版权所有"),
+        "site_copyright": info.get("site_copyright", "© 2026 智创 版权所有"),
         "operation_manual": info.get("operation_manual", ""),
         "login_bg_video": to_full_url(info.get("login_bg_video")) if info.get("login_bg_video") else "",
         "optimize_hold_credits": int(info.get("optimize_hold_credits") or 5),

video-gen-api/app/api/v1/generation.py

@@ -26,7 +26,6 @@ from app.services.generation.pipeline.db_lock_service import (
     DatabaseRowLockBusy,
     execute_with_lock_timeout,
 )
-from app.services.llm import optimize_prompt
 from app.services.video_url import validate_and_get_record_id, get_video_stream_url
 from app.services.private_portrait.reference_resolver import batch_resolve_private_portrait_reference_display_urls, resolve_private_portrait_reference_display_urls
 from app.services.resource_signed_url_service import build_resource_signed_url
@@ -43,21 +42,6 @@ from app.enums.generation_status import (
     GenerationType,
 )
 from app.enums.common import LogEventStatusEnum
-from app.enums.credit_record import (
-    CreditRecordBillingScene,
-    CreditRecordChargeKind,
-    CreditRecordSourceModule,
-)
-from app.enums.llm_billing import LlmBillingConfigKey
-from app.services.llm_billing import (
-    LlmBillingContext,
-    log_provider_failure,
-    log_provider_start,
-    log_provider_success,
-    release_on_failure,
-    settle_success,
-    start_hold,
-)
 from app.enums.generation_record import (
     GenerationRecordConfigSourceEnum,
     GenerationRecordEventTypeEnum,
@@ -70,12 +54,9 @@ from app.services.generation.billing_service import (
 from app.services.generation.ai.engine_service import (
     get_image_engine,
     get_video_engine,
-    image_supported_sizes,
-    parse_json_list,
 )
 from app.services.generation.pipeline.generation_record_config_service import (
     ensure_generation_record_config_frozen,
-    freeze_generation_record_config_with_log,
     frozen_generation_record_engine_view,
     generation_record_config_fallback_hint,
     generation_record_engine_snapshot,
@@ -87,12 +68,12 @@ from app.services.generation.media_reference_service import (
     calculate_media_reference_usage,
     validate_media_reference_usage_for_engine,
 )
+from app.services.generation.prompt_optimize_service import optimize_generation_prompt
 from app.enums.audio_reference import (
     AUDIO_ALLOWED_EXTENSIONS,
     AUDIO_ALLOWED_MIME_TYPES,
     AUDIO_MAX_FILE_SIZE_MB,
 )
-from app.utils.id_gen import generate_id
 from app.utils.exceptions import RecordNotFoundError, InvalidStatusError
 
 router = APIRouter(prefix="/generation-records", tags=["generation"])
@@ -107,43 +88,12 @@ def _record_config_complete(record: GenerationRecord) -> bool:
     return is_generation_record_config_complete(record)
 
 
-def _canonical_references(value: object) -> str:
-    return json.dumps(value or [], ensure_ascii=False, sort_keys=True, separators=(",", ":"))
-
-
-def _idempotency_config_matches(record: GenerationRecord, req: OptimizeParams) -> bool:
-    try:
-        existing_references = json.loads(record.media_references) if record.media_references else []
-    except (TypeError, json.JSONDecodeError):
-        return False
-    if (
-        str(record.project_id) != str(req.project_id)
-        or record.original_prompt != req.prompt
-        or record.gen_type != req.gen_type.value
-        or str(record.engine_id or "") != str(req.engine_id)
-        or bool(record.include_media_references) != bool(req.include_media_references)
-        or _canonical_references(existing_references) != _canonical_references(req.references)
-    ):
-        return False
-    if req.gen_type == GenerationType.video:
-        return (
-            record.duration == req.duration
-            and record.aspect_ratio == req.aspect_ratio
-            and record.resolution == req.resolution
-        )
-    return (
-        record.image_size == req.image_size
-        and record.image_proportion == req.image_proportion
-        and record.image_px == req.image_px
-    )
-
-
 def _record_status_view(record: GenerationRecord) -> dict[str, object]:
     config_complete = _record_config_complete(record)
     config_recoverable = is_generation_record_config_recoverable(record)
     prompt_failure = record.status == "failed" and record.resource_generation_started_at is None
     resource_failure = record.status == "failed" and record.resource_generation_started_at is not None
-    if record.status in {"pending", "optimizing"}:
+    if record.status in {"pending", "optimizing", "settlement_pending"}:
         client_status = "prompt_processing"
         operation_phase = "prompt"
     elif record.status == "prompt_optimized":
@@ -164,7 +114,7 @@ def _record_status_view(record: GenerationRecord) -> dict[str, object]:
         "config_fallback_hint": generation_record_config_fallback_hint(record),
         "can_generate": record.status == "prompt_optimized" and (config_complete or config_recoverable),
         "can_retry": resource_failure and config_complete and record.pipeline_stage != GenerationRecordPipelineStage.UPSCALE_FAILED.value,
-        "should_poll": record.status in {"optimizing", "generating"},
+        "should_poll": record.status in {"optimizing", "settlement_pending", "generating"},
         "client_status": client_status,
         "operation_phase": operation_phase,
     }
@@ -174,26 +124,6 @@ def _frozen_engine_view(record: GenerationRecord) -> SimpleNamespace:
     return frozen_generation_record_engine_view(record)
 
 
-def _validate_video_engine_selection(engine, *, aspect_ratio: str, resolution: str, duration: int) -> None:
-    ratios = [str(item) for item in parse_json_list(engine.supported_ratios, [])]
-    resolutions = [str(item) for item in parse_json_list(engine.supported_resolutions, [])]
-    durations = [int(item) for item in parse_json_list(engine.supported_durations, []) if str(item).isdigit()]
-    if ratios and aspect_ratio not in ratios:
-        raise HTTPException(status_code=400, detail="当前视频引擎不支持所选画面比例")
-    if resolutions and resolution not in resolutions:
-        raise HTTPException(status_code=400, detail="当前视频引擎不支持所选分辨率")
-    if durations and duration not in durations:
-        raise HTTPException(status_code=400, detail="当前视频引擎不支持所选时长")
-    if int(engine.max_duration or 0) > 0 and duration > int(engine.max_duration):
-        raise HTTPException(status_code=400, detail="生成时长超过当前视频引擎上限")
-
-
-def _validate_image_engine_selection(engine, *, image_size: str) -> None:
-    sizes = image_supported_sizes(engine)
-    if sizes and image_size not in sizes:
-        raise HTTPException(status_code=400, detail="当前图片引擎不支持所选画面分辨率")
-
-
 def _record_to_out(record: GenerationRecord, project_name: str, refs_override: list[dict] | None = None) -> GenerationRecordOut:
     refs = refs_override
     if refs is None and record.media_references:
@@ -286,6 +216,8 @@ async def list_records(
     db: AsyncSession = Depends(get_db),
 ):
     allowed_statuses = {
+        "optimizing",
+        "settlement_pending",
         "prompt_optimized",
         "generating",
         "failed",
@@ -295,7 +227,7 @@ async def list_records(
     if status and status not in allowed_statuses:
         raise HTTPException(
             status_code=400,
-            detail="状态参数错误，仅支持：prompt_optimized、generating、failed、completed",
+            detail="状态参数错误，仅支持：optimizing、settlement_pending、prompt_optimized、generating、failed、completed",
         )
 
     offset = (page - 1) * page_size
@@ -356,324 +288,20 @@ async def optimize(
     db: AsyncSession = Depends(get_db),
 ):
     user_id_snapshot = str(current_user.id)
-    # Validate project, engine and the complete generation configuration before
+    service_result = await optimize_generation_prompt(
-    # charging prompt credits or invoking the LLM.
+        db,
-    proj_result = await db.execute(
+        req=req,
-        select(Project).where(
-            Project.id == req.project_id,
-            Project.user_id == user_id_snapshot,
-            Project.deleted_at.is_(None),
-        ).limit(1)
-    )
-    project = proj_result.scalar_one_or_none()
-    if not project:
-        raise HTTPException(status_code=404, detail="项目不存在")
-
-    log_generation_record_config_event(
-        event_type=GenerationRecordEventTypeEnum.PROMPT_CONFIG_VALIDATE_START,
-        event_status=LogEventStatusEnum.STARTED,
-        source=GenerationRecordConfigSourceEnum.PROMPT_OPTIMIZE,
-        record=GenerationRecord(
-            id=req.idempotency_key or "pending",
-            user_id=user_id_snapshot,
-            project_id=req.project_id,
-            original_prompt=req.prompt,
-            gen_type=req.gen_type.value,
-            duration=req.duration if req.gen_type == GenerationType.video else None,
-            aspect_ratio=req.aspect_ratio if req.gen_type == GenerationType.video else None,
-            resolution=req.resolution if req.gen_type == GenerationType.video else None,
-            image_size=req.image_size if req.gen_type == GenerationType.image else None,
-            image_proportion=req.image_proportion if req.gen_type == GenerationType.image else None,
-            image_px=req.image_px if req.gen_type == GenerationType.image else None,
-            include_media_references=bool(req.include_media_references),
-            media_references=json.dumps(req.references, ensure_ascii=False) if req.references else None,
-            engine_id=req.engine_id,
-        ),
-        detail={
-            "project_id": req.project_id,
-            "gen_type": req.gen_type.value,
-            "engine_id": req.engine_id,
-            "include_media_references": bool(req.include_media_references),
-            "reference_count": len(req.references or []),
-            "source": GenerationRecordConfigSourceEnum.PROMPT_OPTIMIZE.value,
-        },
-    )
-
-    # Idempotency must be checked before the temporary prompt-credit hold. The
-    # key is bound to one immutable generation configuration; reusing it with a
-    # different engine, parameter set or attachment selection is rejected.
-    if req.idempotency_key:
-        existing = await db.execute(
-            select(GenerationRecord, Project.name)
-            .join(Project, GenerationRecord.project_id == Project.id)
-            .where(
-                GenerationRecord.user_id == user_id_snapshot,
-                GenerationRecord.deleted_at.is_(None),
-                Project.deleted_at.is_(None),
-                GenerationRecord.idempotency_key == req.idempotency_key,
-            )
-            .order_by(GenerationRecord.created_at.desc())
-            .limit(1)
-        )
-        row = existing.first()
-        if row:
-            existing_record, project_name = row
-            if not _idempotency_config_matches(existing_record, req):
-                raise HTTPException(
-                    status_code=409,
-                    detail="幂等键已绑定其他生成配置，请重新提交",
-                )
-            if not existing_record.optimized_prompt or not _record_config_complete(existing_record):
-                raise HTTPException(
-                    status_code=409,
-                    detail="幂等记录配置不完整，请使用新的幂等键重新提交",
-                )
-            refs = await resolve_private_portrait_reference_display_urls(
-                db,
-                json.loads(existing_record.media_references) if existing_record.media_references else None,
-                user_id=user_id_snapshot,
-            )
-            return OptimizeResult(
-                optimized_prompt=existing_record.optimized_prompt,
-                text_credits_cost=existing_record.text_credits_cost or 0.0,
-                text_tokens_used=existing_record.text_tokens_used or 0,
-                record=_record_to_out(existing_record, project_name, refs_override=refs),
-            )
-
-
-    if req.gen_type == GenerationType.video:
-        if req.duration not in DURATIONS:
-            raise HTTPException(status_code=400, detail=f"视频时长必须为{DURATIONS}秒之一")
-        if req.aspect_ratio not in ASPECT_RATIOS:
-            raise HTTPException(status_code=400, detail="不支持的画面比例")
-        if req.resolution not in RESOLUTIONS:
-            raise HTTPException(status_code=400, detail="不支持的分辨率")
-        engine = await get_video_engine(db, req.engine_id)
-        _validate_video_engine_selection(
-            engine,
-            aspect_ratio=req.aspect_ratio,
-            resolution=req.resolution,
-            duration=int(req.duration),
-        )
-    else:
-        if req.image_size not in IMAGE_SIZES:
-            raise HTTPException(status_code=400, detail=f"图片分辨率必须为{IMAGE_SIZES}之一")
-        if not req.image_proportion or not req.image_px:
-            raise HTTPException(status_code=400, detail="图片生成需要指定比例和像素尺寸")
-        engine = await get_image_engine(db, req.engine_id)
-        _validate_image_engine_selection(engine, image_size=req.image_size)
-
-    project_name_snapshot = str(project.name)
-    project_industry_snapshot = str(project.industry or "")
-    engine_snapshot_source = SimpleNamespace(
-        **{
-            key: value
-            for key, value in vars(engine).items()
-            if key != "_sa_instance_state"
-        }
-    )
-
-    reference_usage = calculate_media_reference_usage(
-        json.dumps(req.references, ensure_ascii=False) if req.references else None,
-        include=bool(req.include_media_references),
-    )
-    validate_media_reference_usage_for_engine(
-        reference_usage,
-        gen_type=req.gen_type.value,
-        engine=engine,
-    )
-
-
-    log_generation_record_config_event(
-        event_type=GenerationRecordEventTypeEnum.PROMPT_CONFIG_VALIDATE_SUCCESS,
-        event_status=LogEventStatusEnum.SUCCESS,
-        source=GenerationRecordConfigSourceEnum.PROMPT_OPTIMIZE,
-        record=GenerationRecord(
-            id=req.idempotency_key or "pending",
-            user_id=user_id_snapshot,
-            project_id=req.project_id,
-            original_prompt=req.prompt,
-            gen_type=req.gen_type.value,
-            duration=req.duration if req.gen_type == GenerationType.video else None,
-            aspect_ratio=req.aspect_ratio if req.gen_type == GenerationType.video else None,
-            resolution=req.resolution if req.gen_type == GenerationType.video else None,
-            image_size=req.image_size if req.gen_type == GenerationType.image else None,
-            image_proportion=req.image_proportion if req.gen_type == GenerationType.image else None,
-            image_px=req.image_px if req.gen_type == GenerationType.image else None,
-            include_media_references=bool(req.include_media_references),
-            media_references=json.dumps(req.references, ensure_ascii=False) if req.references else None,
-            engine_id=req.engine_id,
-        ),
-        detail={
-            "project_id": req.project_id,
-            "gen_type": req.gen_type.value,
-            "engine_id": req.engine_id,
-            "include_media_references": bool(req.include_media_references),
-            "reference_count": len(req.references or []),
-            "media_reference_usage": getattr(reference_usage, "__dict__", None) or str(reference_usage),
-            "source": GenerationRecordConfigSourceEnum.PROMPT_OPTIMIZE.value,
-        },
-    )
-
-
-    record_id_value = generate_id()
-    prompt_attempt_no = 1
-    llm_billing_context = LlmBillingContext(
         user_id=user_id_snapshot,
-        owner_type=OWNER_GENERATION_RECORD,
-        owner_id=record_id_value,
-        attempt_no=prompt_attempt_no,
-        charge_kind=CreditRecordChargeKind.TEXT_PROMPT.value,
-        billing_scene=CreditRecordBillingScene.GENERATION_RECORD_TEXT_PROMPT_OPTIMIZE.value,
-        source_module=CreditRecordSourceModule.GENERATION_RECORD.value,
-        related_id=record_id_value,
-        hold_config_key=LlmBillingConfigKey.HOLD_GENERATION_RECORD_PROMPT.value,
-        description_prefix="AI创作提示词优化",
-        trace_id=f"generation-optimize:{record_id_value}",
-        request_id=req.idempotency_key,
     )
-    await start_hold(db, llm_billing_context)
-    await db.commit()
-
-    log_provider_start(llm_billing_context, detail={"gen_type": req.gen_type.value})
-    try:
-        optimized, token_usage = await optimize_prompt(
-            db,
-            req.prompt,
-            user_id=user_id_snapshot,
-            industry_key=project_industry_snapshot,
-            duration=req.duration if req.gen_type == GenerationType.video else None,
-            image_size=req.image_size if req.gen_type == GenerationType.image else None,
-            image_proportion=req.image_proportion if req.gen_type == GenerationType.image else None,
-            image_px=req.image_px if req.gen_type == GenerationType.image else None,
-            references=req.references,
-            gen_type=req.gen_type.value,
-            log_module="generation_record",
-            log_step="prompt_optimize",
-            log_project_id=req.project_id,
-            log_owner_type=OWNER_GENERATION_RECORD,
-            log_owner_id=record_id_value,
-            generation_attempt_no=prompt_attempt_no,
-        )
-        log_provider_success(llm_billing_context, usage=token_usage)
-    except Exception as exc:
-        from app.services.error_codes import extract_error_message
-
-        await db.rollback()
-        log_provider_failure(llm_billing_context, error=str(exc))
-        await release_on_failure(db, llm_billing_context, error=str(exc))
-        await db.commit()
-        raise HTTPException(
-            status_code=502,
-            detail=f"AI模型调用失败: {extract_error_message(exc, '提示词')}",
-        ) from exc
-
-    async def _persist_optimized_result() -> str:
-        existing_result = await db.execute(
-            select(GenerationRecord)
-            .where(GenerationRecord.id == record_id_value)
-            .with_for_update()
-            .limit(1)
-        )
-        record = existing_result.scalar_one_or_none()
-        if record is None:
-            record = GenerationRecord(
-                id=record_id_value,
-                user_id=user_id_snapshot,
-                project_id=req.project_id,
-                original_prompt=req.prompt,
-                optimized_prompt=optimized,
-                gen_type=req.gen_type.value,
-                duration=req.duration if req.gen_type == GenerationType.video else None,
-                aspect_ratio=req.aspect_ratio if req.gen_type == GenerationType.video else None,
-                resolution=req.resolution if req.gen_type == GenerationType.video else None,
-                image_size=req.image_size if req.gen_type == GenerationType.image else None,
-                image_proportion=req.image_proportion if req.gen_type == GenerationType.image else None,
-                image_px=req.image_px if req.gen_type == GenerationType.image else None,
-                status="prompt_optimized",
-                pipeline_stage=None,
-                credits_cost=0,
-                text_credits_cost=0,
-                text_tokens_used=int(token_usage.get("total_tokens", 0) or 0),
-                media_references=json.dumps(req.references, ensure_ascii=False) if req.references else None,
-                include_media_references=bool(req.include_media_references),
-                idempotency_key=req.idempotency_key,
-            )
-            db.add(record)
-        else:
-            # commit 结果不确定或本地持久化重试时，复用同一主键和同一账务 attempt。
-            record.optimized_prompt = optimized
-            record.status = "prompt_optimized"
-            record.pipeline_stage = None
-            record.error_message = None
-            record.text_credits_cost = 0
-            record.text_tokens_used = int(token_usage.get("total_tokens", 0) or 0)
-
-        if req.gen_type == GenerationType.video:
-            from app.services.video_upscale.snapshot_service import build_video_upscale_snapshot
-
-            provider_resolution, upscale_enabled, upscale_snapshot_json = await build_video_upscale_snapshot(
-                db,
-                target_resolution=req.resolution,
-                aspect_ratio=req.aspect_ratio,
-                supported_provider_resolutions=parse_json_list(
-                    engine_snapshot_source.supported_resolutions,
-                    [],
-                ),
-            )
-            record.provider_generation_resolution = provider_resolution
-            record.video_upscale_enabled_snapshot = upscale_enabled
-            record.video_upscale_snapshot_json = upscale_snapshot_json
-        else:
-            record.provider_generation_resolution = None
-            record.video_upscale_enabled_snapshot = False
-            record.video_upscale_snapshot_json = None
-
-        freeze_generation_record_config_with_log(
-            record,
-            engine=engine_snapshot_source,
-            source=GenerationRecordConfigSourceEnum.PROMPT_OPTIMIZE,
-        )
-        await db.flush()
-        billing = await settle_success(
-            db,
-            llm_billing_context,
-            usage=token_usage,
-            description=f"提示词优化 - {project_name_snapshot}",
-        )
-        charge_item = next(
-            (item for item in billing.items if item.biz_key == llm_billing_context.charge_biz_key),
-            None,
-        )
-        if charge_item:
-            record.text_credits_cost = round(charge_item.amount, 2)
-        record_id_snapshot = str(record.id)
-        await db.commit()
-        return record_id_snapshot
-
-    try:
-        record_id_snapshot = await _persist_optimized_result()
-    except Exception as first_exc:
-        await db.rollback()
-        logger.exception(
-            "prompt optimize local persistence/settlement failed after provider success; retry once: record_id=%s",
-            record_id_value,
-        )
-        try:
-            record_id_snapshot = await _persist_optimized_result()
-        except Exception:
-            await db.rollback()
-            logger.exception(
-                "prompt optimize idempotent persistence retry failed; active HOLD retained for repair: record_id=%s",
-                record_id_value,
-            )
-            raise first_exc
-
-
     refreshed = await db.execute(
         select(GenerationRecord, Project.name)
         .join(Project, GenerationRecord.project_id == Project.id)
-        .where(GenerationRecord.id == record_id_snapshot)
+        .where(
+            GenerationRecord.id == service_result.record_id,
+            GenerationRecord.user_id == user_id_snapshot,
+            GenerationRecord.deleted_at.is_(None),
+            Project.deleted_at.is_(None),
+        )
         .limit(1)
     )
     refreshed_row = refreshed.first()

video-gen-api/app/api/v1/shot_replicate.py

@@ -18,6 +18,7 @@ from app.enums.credit_record import (
     CreditRecordBillingScene,
     CreditRecordChargeKind,
     CreditRecordOwnerType,
+    CreditRecordSourceStepCode,
 )
 from app.enums.llm_billing import LlmBillingConfigKey
 from app.enums.shot_replicate import (
@@ -274,7 +275,7 @@ def _analysis_dispatch_billing_context(
         source_module=MODULE,
         source_project_id=task_set_id,
         source_step_id=owner_id,
-        source_step_code=ShotReplicateStepCodeEnum.VIDEO_ANALYSIS.value,
+        source_step_code=CreditRecordSourceStepCode.VIDEO_ANALYSIS.value,
         related_id=owner_id,
         hold_config_key=LlmBillingConfigKey.HOLD_SHOT_VIDEO_ANALYSIS.value,
         description_prefix=(
@@ -569,7 +570,7 @@ async def create_shot_task_set(
         from app.tasks.shot_replicate_tasks import analyze_original_video
 
         analyze_original_video.apply_async(
-            args=[task_set_id],
+            args=[task_set_id, analysis_attempt_no],
             queue=CeleryQueue.GEN_SHOT_ANALYSIS.value,
             countdown=0,
             task_id=celery_task_id,
@@ -590,6 +591,7 @@ async def create_shot_task_set(
                 db,
                 current_user=_user_context(current_user),
                 task_set_id=task_set_id,
+                expected_attempt_no=analysis_attempt_no,
                 error_message=f"拆镜分析任务投递失败: {exc}",
             )
             await db.commit()
@@ -672,7 +674,7 @@ async def get_shot_task_set(
     "/task-sets/{task_set_id}/reanalyze",
     response_model=ShotReanalyzeOut,
     summary="重新投递原视频 AI 分析任务",
-    description="用于处理原视频分析失败或待处理的异常数据；重置分析状态后重新投递 analyze_original_video。",
+    description="仅用于重新处理原视频分析失败的数据；处理中、待处理或已完成状态均拒绝重复投递。",
 )
 async def reanalyze_task_set(
     task_set_id: str = Path(..., description="拆镜总任务集ID，即 shot_replicate_task_sets.id"),
@@ -686,7 +688,6 @@ async def reanalyze_task_set(
             db,
             current_user=current_user,
             task_set_id=task_set_id,
-            force=req.force,
             reason=req.reason,
         )
         analysis_attempt_no = int(out.analysis_attempt_no)
@@ -729,7 +730,7 @@ async def reanalyze_task_set(
         from app.tasks.shot_replicate_tasks import analyze_original_video
 
         analyze_original_video.apply_async(
-            args=[task_set_id],
+            args=[task_set_id, analysis_attempt_no],
             queue=CeleryQueue.GEN_SHOT_ANALYSIS.value,
             countdown=0,
             task_id=celery_task_id,
@@ -758,6 +759,7 @@ async def reanalyze_task_set(
                 db,
                 current_user=_user_context(current_user),
                 task_set_id=task_set_id,
+                expected_attempt_no=analysis_attempt_no,
                 error_message=f"原视频再次分析任务投递失败: {exc}",
             )
             await db.commit()
@@ -923,7 +925,7 @@ async def get_segment(
     "/segments/{segment_id}/reanalyze",
     response_model=ShotReanalyzeOut,
     summary="重新投递切片视频 AI 分析任务",
-    description="用于处理自定义切片视频分析失败或待处理的异常数据；重置分析状态后重新投递 analyze_custom_segment_video。",
+    description="仅用于重新处理自定义切片视频分析失败的数据；处理中、待处理或已完成状态均拒绝重复投递。",
 )
 async def reanalyze_segment(
     segment_id: str = Path(..., description="拆镜片段ID，即 shot_replicate_segments.id"),
@@ -937,7 +939,6 @@ async def reanalyze_segment(
             db,
             current_user=current_user,
             segment_id=segment_id,
-            force=req.force,
             reason=req.reason,
         )
         task_set_id = str(out.task_set_id)
@@ -981,7 +982,7 @@ async def reanalyze_segment(
         from app.tasks.shot_replicate_tasks import analyze_custom_segment_video
 
         analyze_custom_segment_video.apply_async(
-            args=[segment_id],
+            args=[segment_id, analysis_attempt_no],
             queue=CeleryQueue.GEN_SHOT_ANALYSIS.value,
             countdown=0,
             task_id=celery_task_id,
@@ -1012,6 +1013,7 @@ async def reanalyze_segment(
                 db,
                 current_user=_user_context(current_user),
                 segment_id=segment_id,
+                expected_attempt_no=analysis_attempt_no,
                 error_message=f"切片视频再次分析任务投递失败: {exc}",
             )
             await db.commit()

video-gen-api/app/config.py

@@ -170,7 +170,7 @@ class Settings(BaseSettings):
     CELERY_RUNTIME_GC_INTERVAL_SECONDS: int = 600
     CELERY_RUNTIME_GC_BATCH_SIZE: int = 500
 
-    CHATAPI_REQUEST_TIMEOUT_SECONDS: int = 180
+    CHATAPI_REQUEST_TIMEOUT_SECONDS: int = 600
     CHATAPI_VIDEO_FPS: float = 0.5
     CHATAPI_ASYNC_MAX_RETRIES: int = 3
     CHATAPI_ASYNC_RETRY_BACKOFF_SECONDS: int = 30
@@ -307,7 +307,7 @@ class Settings(BaseSettings):
     SHOT_ANALYSIS_ACTIVE_REDIS_ZSET_KEY: str = "vg:celery:shot_analysis:active_index"
     SHOT_ANALYSIS_LOCK_KEY_PREFIX: str = "vg:lock:shot_analysis"
     SHOT_ANALYSIS_TEMPERATURE: float = 0.1
-    SHOT_ANALYSIS_MAX_TOKENS: int = 5000
+    SHOT_ANALYSIS_MAX_TOKENS: int = 10000
     SHOT_ANALYSIS_VIDEO_FPS: float = 1.0
     SHOT_ANALYSIS_MAX_LOCAL_VIDEO_MB: int = 45
 

video-gen-api/app/enums/common.py

@@ -26,6 +26,7 @@ class LogSourceEnum(StrEnum):
     CELERY = "celery"
     RECOVERY = "recovery"
     REMOTE_API = "remote_api"
+    CLI = "cli"
 
 class ModuleGenerationFlowVersionEnum(StrEnum):
     """模块生成项目流程版本。"""

video-gen-api/app/enums/generation_record.py

@@ -20,6 +20,12 @@ class GenerationRecordEventTypeEnum(StrEnum):
     PROMPT_CONFIG_FREEZE_START = "PROMPT_CONFIG_FREEZE_START"
     PROMPT_CONFIG_FREEZE_SUCCESS = "PROMPT_CONFIG_FREEZE_SUCCESS"
     PROMPT_CONFIG_FREEZE_FAILED = "PROMPT_CONFIG_FREEZE_FAILED"
+    PROMPT_OPTIMIZE_PLACEHOLDER_CREATED = "PROMPT_OPTIMIZE_PLACEHOLDER_CREATED"
+    PROMPT_OPTIMIZE_IDEMPOTENCY_HIT = "PROMPT_OPTIMIZE_IDEMPOTENCY_HIT"
+    PROMPT_OPTIMIZE_PROVIDER_RESULT_STAGED = "PROMPT_OPTIMIZE_PROVIDER_RESULT_STAGED"
+    PROMPT_OPTIMIZE_SETTLEMENT_PENDING = "PROMPT_OPTIMIZE_SETTLEMENT_PENDING"
+    PROMPT_OPTIMIZE_SETTLEMENT_SUCCESS = "PROMPT_OPTIMIZE_SETTLEMENT_SUCCESS"
+    PROMPT_OPTIMIZE_FAILED_RELEASED = "PROMPT_OPTIMIZE_FAILED_RELEASED"
     LEGACY_CONFIG_FALLBACK_START = "LEGACY_CONFIG_FALLBACK_START"
     LEGACY_CONFIG_FALLBACK_SUCCESS = "LEGACY_CONFIG_FALLBACK_SUCCESS"
     LEGACY_CONFIG_FALLBACK_FAILED = "LEGACY_CONFIG_FALLBACK_FAILED"

video-gen-api/app/enums/generation_status.py

@@ -3,6 +3,8 @@ from enum import Enum
 
 class GenerationStatus(str, Enum):
     """生成状态。"""
+    optimizing = "optimizing"
+    settlement_pending = "settlement_pending"
     prompt_optimized = "prompt_optimized"
     generating = "generating"
     completed = "completed"

video-gen-api/app/enums/llm_billing.py

@@ -50,6 +50,12 @@ class LlmBillingEvent(StrEnum):
     CELERY_DISPATCH_SUCCESS = "LLM_CELERY_DISPATCH_SUCCESS"
     CELERY_DISPATCH_FAILURE = "LLM_CELERY_DISPATCH_FAILURE"
     CELERY_DISPATCH_COMPENSATED = "LLM_CELERY_DISPATCH_COMPENSATED"
+    RETRY_PREVIOUS_ATTEMPT_VALIDATE_START = "LLM_RETRY_PREVIOUS_ATTEMPT_VALIDATE_START"
+    RETRY_PREVIOUS_ATTEMPT_VALIDATE_SUCCESS = "LLM_RETRY_PREVIOUS_ATTEMPT_VALIDATE_SUCCESS"
+    RETRY_PREVIOUS_ATTEMPT_BLOCKED = "LLM_RETRY_PREVIOUS_ATTEMPT_BLOCKED"
+    USAGE_INVALID = "LLM_USAGE_INVALID"
+    TOKEN_USAGE_CREATED = "LLM_TOKEN_USAGE_CREATED"
+    TOKEN_USAGE_REUSED = "LLM_TOKEN_USAGE_REUSED"
 
 
 class LlmBillingDomain(StrEnum):

video-gen-api/app/enums/shot_replicate.py

@@ -118,6 +118,7 @@ class ShotReplicateLogEventEnum(StrEnum):
     ANALYSIS_REMOTE_API_FAILED = "SHOT_ANALYSIS_REMOTE_API_FAILED"
     ANALYSIS_RESPONSE_PARSE_FAILED = "SHOT_ANALYSIS_RESPONSE_PARSE_FAILED"
     ANALYSIS_RESPONSE_EMPTY = "SHOT_ANALYSIS_RESPONSE_EMPTY"
+    ANALYSIS_STALE_ATTEMPT_SKIPPED = "SHOT_ANALYSIS_STALE_ATTEMPT_SKIPPED"
 
     SEGMENT_REANALYZE_RECEIVED = "SHOT_SEGMENT_REANALYZE_RECEIVED"
     SEGMENT_REANALYZE_SUBMITTED = "SHOT_SEGMENT_REANALYZE_SUBMITTED"
@@ -131,6 +132,7 @@ class ShotReplicateLogEventEnum(StrEnum):
     SEGMENT_ANALYSIS_REMOTE_API_FAILED = "SHOT_SEGMENT_ANALYSIS_REMOTE_API_FAILED"
 
     SPLIT_STATUS_CHANGED = "SHOT_SPLIT_STATUS_CHANGED"
+    SPLIT_SUMMARY_REPAIRED = "SHOT_SPLIT_SUMMARY_REPAIRED"
     SPLIT_BY_AI_SUBMITTED = "SHOT_SPLIT_BY_AI_SUBMITTED"
     SPLIT_CUSTOM_SUBMITTED = "SHOT_SPLIT_CUSTOM_SUBMITTED"
     SEGMENT_DELETED = "SHOT_SEGMENT_DELETED"

video-gen-api/app/models/credit_record.py

@@ -1,4 +1,4 @@
-from sqlalchemy import Float, ForeignKey, Index, Integer, String
+from sqlalchemy import Float, ForeignKey, Index, Integer, String, text
 from sqlalchemy.orm import Mapped, mapped_column
 
 from app.models.base import Base, TimestampMixin
@@ -11,6 +11,13 @@ class CreditRecord(Base, TimestampMixin):
         # PostgreSQL/MySQL/SQLite 对 nullable unique 的处理都允许多条 NULL，兼容历史数据。
         Index("uq_credit_records_user_biz_key", "user_id", "biz_key", unique=True),
         Index("ix_credit_records_user_refund_for_biz_key", "user_id", "refund_for_biz_key"),
+        Index(
+            "uq_credit_records_user_refund_target",
+            "user_id",
+            "refund_for_biz_key",
+            unique=True,
+            postgresql_where=text("type = 'refund' AND refund_for_biz_key IS NOT NULL"),
+        ),
         Index("ix_credit_records_related_type", "related_id", "type"),
         Index("ix_credit_records_owner", "owner_type", "owner_id"),
         Index("ix_credit_records_subject_media", "credit_subject", "media_type"),

video-gen-api/app/models/generation_record.py

@@ -18,6 +18,7 @@ class GenerationRecord(Base, TimestampMixin, SoftDeleteMixin):
     )
     original_prompt: Mapped[str] = mapped_column(Text)
     optimized_prompt: Mapped[str | None] = mapped_column(Text, nullable=True)
+    prompt_usage_snapshot_json: Mapped[str | None] = mapped_column(Text, nullable=True)
     gen_type: Mapped[str] = mapped_column(String(16), default="video")
     duration: Mapped[int | None] = mapped_column(Integer, nullable=True)
     aspect_ratio: Mapped[str | None] = mapped_column(String(8), nullable=True)
@@ -95,6 +96,13 @@ class GenerationRecord(Base, TimestampMixin, SoftDeleteMixin):
     __table_args__ = (
         Index('idx_genrec_user_status_created', 'user_id', 'status', 'created_at'),
         Index('idx_genrec_project_status', 'project_id', 'status'),
+        Index(
+            'uq_genrec_user_idempotency_active',
+            'user_id',
+            'idempotency_key',
+            unique=True,
+            postgresql_where=text("idempotency_key IS NOT NULL AND deleted_at IS NULL"),
+        ),
         Index(
             'idx_genrec_next_poll_at',
             'next_poll_at',

video-gen-api/app/models/token_usage.py

@@ -1,4 +1,4 @@
-from sqlalchemy import ForeignKey, Index, Integer, String
+from sqlalchemy import ForeignKey, Index, Integer, String, text
 from sqlalchemy.orm import Mapped, mapped_column
 
 from app.models.base import Base, TimestampMixin
@@ -9,6 +9,13 @@ class TokenUsage(Base, TimestampMixin):
     __table_args__ = (
         Index("ix_token_usage_owner", "owner_type", "owner_id"),
         Index("ix_token_usage_biz_key", "biz_key"),
+        Index(
+            "uq_token_usage_user_biz_key",
+            "user_id",
+            "biz_key",
+            unique=True,
+            postgresql_where=text("biz_key IS NOT NULL"),
+        ),
     )
 
     id: Mapped[str] = mapped_column(String(32), primary_key=True)

video-gen-api/app/schemas/shot_replicate.py

@@ -729,7 +729,7 @@ class ShotSegmentListOut(BaseModel):
 
 
 class ShotReanalyzeRequest(BaseModel):
-    force: bool = Field(False, description="是否强制重跑；默认 false。当前仅允许失败/待处理数据重试，已完成数据不建议强制覆盖")
+    force: bool = Field(False, description="兼容旧客户端保留字段；后端不再支持强制重跑，仅分析失败状态允许重新分析")
     reason: str | None = Field(None, max_length=200, description="再次分析原因，会写入模块日志")
 
     @field_validator("reason", mode="before")

video-gen-api/app/services/generation/prompt_optimize_service.py

@@ -0,0 +1,647 @@
+from __future__ import annotations
+
+import json
+import logging
+from dataclasses import dataclass
+from typing import Any
+
+from fastapi import HTTPException
+from sqlalchemy import select
+from sqlalchemy.exc import IntegrityError
+from sqlalchemy.ext.asyncio import AsyncSession
+
+from app.enums.common import LogEventStatusEnum
+from app.enums.credit_record import (
+    CreditRecordBillingScene,
+    CreditRecordChargeKind,
+    CreditRecordSourceModule,
+)
+from app.enums.generation_record import (
+    GenerationRecordConfigSourceEnum,
+    GenerationRecordEventTypeEnum,
+)
+from app.enums.generation_status import (
+    ASPECT_RATIOS,
+    DURATIONS,
+    IMAGE_SIZES,
+    RESOLUTIONS,
+    GenerationStatus,
+    GenerationType,
+)
+from app.enums.llm_billing import LlmBillingConfigKey
+from app.models.generation_record import GenerationRecord
+from app.models.project import Project
+from app.schemas.generation import OptimizeParams
+from app.services.error_codes import extract_error_message
+from app.services.generation.ai.engine_service import (
+    get_image_engine,
+    get_video_engine,
+    image_supported_sizes,
+    parse_json_list,
+)
+from app.services.generation.billing_service import OWNER_GENERATION_RECORD
+from app.services.generation.media_reference_service import (
+    calculate_media_reference_usage,
+    validate_media_reference_usage_for_engine,
+)
+from app.services.generation.pipeline.generation_record_config_service import (
+    freeze_generation_record_config_with_log,
+    is_generation_record_config_complete,
+)
+from app.services.llm import optimize_prompt
+from app.services.llm_billing import (
+    LlmBillingContext,
+    log_provider_failure,
+    log_provider_start,
+    log_provider_success,
+    release_on_failure,
+    settle_success,
+    start_hold,
+)
+from app.services.operation_log_service import log_operation_error, log_operation_event
+from app.services.video_upscale.snapshot_service import build_video_upscale_snapshot
+from app.utils.id_gen import generate_id
+
+logger = logging.getLogger("videogen")
+
+_PROMPT_ATTEMPT_NO = 1
+_LOG_DOMAIN = "generation_record"
+_LOG_MODULE = "generation_record"
+_LOG_SOURCE = GenerationRecordConfigSourceEnum.PROMPT_OPTIMIZE.value
+
+
+@dataclass(slots=True, frozen=True)
+class PromptOptimizeServiceResult:
+    record_id: str
+    idempotent: bool = False
+
+
+def _log_event(
+    event: GenerationRecordEventTypeEnum,
+    *,
+    status: LogEventStatusEnum = LogEventStatusEnum.SUCCESS,
+    user_id: str,
+    project_id: str | None,
+    record_id: str | None,
+    detail: dict[str, Any] | None = None,
+    error: str | None = None,
+) -> None:
+    log_operation_event(
+        domain=_LOG_DOMAIN,
+        module=_LOG_MODULE,
+        event_type=event.value,
+        event_status=status.value,
+        source=_LOG_SOURCE,
+        user_id=user_id,
+        project_id=project_id,
+        task_id=record_id,
+        detail=detail,
+        error=error,
+    )
+
+
+def _billing_context(*, user_id: str, record_id: str, request_id: str | None) -> LlmBillingContext:
+    return LlmBillingContext(
+        user_id=user_id,
+        owner_type=OWNER_GENERATION_RECORD,
+        owner_id=record_id,
+        attempt_no=_PROMPT_ATTEMPT_NO,
+        charge_kind=CreditRecordChargeKind.TEXT_PROMPT.value,
+        billing_scene=CreditRecordBillingScene.GENERATION_RECORD_TEXT_PROMPT_OPTIMIZE.value,
+        source_module=CreditRecordSourceModule.GENERATION_RECORD.value,
+        related_id=record_id,
+        hold_config_key=LlmBillingConfigKey.HOLD_GENERATION_RECORD_PROMPT.value,
+        description_prefix="AI创作提示词优化",
+        trace_id=f"generation-optimize:{record_id}",
+        request_id=request_id,
+    )
+
+
+def _canonical_references(value: object) -> str:
+    return json.dumps(value or [], ensure_ascii=False, sort_keys=True, separators=(",", ":"))
+
+
+def _idempotency_config_matches(record: GenerationRecord, req: OptimizeParams) -> bool:
+    try:
+        existing_references = json.loads(record.media_references) if record.media_references else []
+    except (TypeError, json.JSONDecodeError):
+        return False
+    if (
+        str(record.project_id) != str(req.project_id)
+        or record.original_prompt != req.prompt
+        or record.gen_type != req.gen_type.value
+        or str(record.engine_id or "") != str(req.engine_id)
+        or bool(record.include_media_references) != bool(req.include_media_references)
+        or _canonical_references(existing_references) != _canonical_references(req.references)
+    ):
+        return False
+    if req.gen_type == GenerationType.video:
+        return (
+            record.duration == req.duration
+            and record.aspect_ratio == req.aspect_ratio
+            and record.resolution == req.resolution
+        )
+    return (
+        record.image_size == req.image_size
+        and record.image_proportion == req.image_proportion
+        and record.image_px == req.image_px
+    )
+
+
+def _validate_video_engine_selection(engine: Any, *, aspect_ratio: str, resolution: str, duration: int) -> None:
+    ratios = [str(item) for item in parse_json_list(engine.supported_ratios, [])]
+    resolutions = [str(item) for item in parse_json_list(engine.supported_resolutions, [])]
+    durations = [int(item) for item in parse_json_list(engine.supported_durations, []) if str(item).isdigit()]
+    if ratios and aspect_ratio not in ratios:
+        raise HTTPException(status_code=400, detail="当前视频引擎不支持所选画面比例")
+    if resolutions and resolution not in resolutions:
+        raise HTTPException(status_code=400, detail="当前视频引擎不支持所选分辨率")
+    if durations and duration not in durations:
+        raise HTTPException(status_code=400, detail="当前视频引擎不支持所选时长")
+    if int(engine.max_duration or 0) > 0 and duration > int(engine.max_duration):
+        raise HTTPException(status_code=400, detail="生成时长超过当前视频引擎上限")
+
+
+def _validate_image_engine_selection(engine: Any, *, image_size: str) -> None:
+    sizes = image_supported_sizes(engine)
+    if sizes and image_size not in sizes:
+        raise HTTPException(status_code=400, detail="当前图片引擎不支持所选画面分辨率")
+
+
+async def _find_idempotency_record(
+    db: AsyncSession,
+    *,
+    user_id: str,
+    idempotency_key: str | None,
+) -> GenerationRecord | None:
+    if not idempotency_key:
+        return None
+    stmt = (
+        select(GenerationRecord)
+        .where(
+            GenerationRecord.user_id == user_id,
+            GenerationRecord.idempotency_key == idempotency_key,
+            GenerationRecord.deleted_at.is_(None),
+        )
+        .order_by(GenerationRecord.created_at.desc(), GenerationRecord.id.desc())
+        .limit(1)
+    )
+    result = await db.execute(stmt)
+    return result.scalar_one_or_none()
+
+
+async def _settle_staged_result(
+    db: AsyncSession,
+    *,
+    record_id: str,
+    user_id: str,
+    project_name: str,
+    request_id: str | None,
+) -> PromptOptimizeServiceResult:
+    result = await db.execute(
+        select(GenerationRecord)
+        .where(
+            GenerationRecord.id == record_id,
+            GenerationRecord.user_id == user_id,
+            GenerationRecord.deleted_at.is_(None),
+        )
+        .with_for_update()
+        .limit(1)
+    )
+    record = result.scalar_one_or_none()
+    if record is None:
+        raise HTTPException(status_code=404, detail="生成记录不存在")
+    if record.status in {
+        GenerationStatus.prompt_optimized.value,
+        GenerationStatus.generating.value,
+        GenerationStatus.completed.value,
+    }:
+        await db.rollback()
+        return PromptOptimizeServiceResult(record_id=record_id, idempotent=True)
+    if record.status != GenerationStatus.settlement_pending.value:
+        await db.rollback()
+        raise HTTPException(status_code=409, detail=f"当前提词状态不可结算：{record.status}")
+    if not record.optimized_prompt or not record.prompt_usage_snapshot_json:
+        await db.rollback()
+        raise HTTPException(status_code=409, detail="提词结果或计费快照缺失，需人工排查")
+
+    try:
+        usage = json.loads(record.prompt_usage_snapshot_json)
+    except (TypeError, json.JSONDecodeError) as exc:
+        await db.rollback()
+        raise HTTPException(status_code=409, detail="提词计费快照损坏，需人工排查") from exc
+    if not isinstance(usage, dict):
+        await db.rollback()
+        raise HTTPException(status_code=409, detail="提词计费快照格式错误，需人工排查")
+
+    project_id_snapshot = str(record.project_id)
+    status_snapshot = str(record.status)
+    ctx = _billing_context(user_id=user_id, record_id=record_id, request_id=request_id)
+    _log_event(
+        GenerationRecordEventTypeEnum.PROMPT_OPTIMIZE_SETTLEMENT_PENDING,
+        status=LogEventStatusEnum.STARTED,
+        user_id=user_id,
+        project_id=project_id_snapshot,
+        record_id=record_id,
+        detail={"status": status_snapshot, "attempt_no": _PROMPT_ATTEMPT_NO},
+    )
+    try:
+        billing = await settle_success(
+            db,
+            ctx,
+            usage=usage,
+            description=f"提示词优化 - {project_name}",
+        )
+        charge_item = next(
+            (item for item in billing.items if item.biz_key == ctx.charge_biz_key),
+            None,
+        )
+        record.text_credits_cost = round(float(charge_item.amount if charge_item else 0.0), 2)
+        record.text_tokens_used = int(usage.get("total_tokens", 0) or 0)
+        record.status = GenerationStatus.prompt_optimized.value
+        record.pipeline_stage = None
+        record.error_message = None
+        credits_snapshot = float(record.text_credits_cost or 0.0)
+        tokens_snapshot = int(record.text_tokens_used or 0)
+        await db.commit()
+    except Exception as exc:
+        await db.rollback()
+        _log_event(
+            GenerationRecordEventTypeEnum.PROMPT_OPTIMIZE_SETTLEMENT_PENDING,
+            status=LogEventStatusEnum.FAILED,
+            user_id=user_id,
+            project_id=project_id_snapshot,
+            record_id=record_id,
+            detail={"attempt_no": _PROMPT_ATTEMPT_NO, "error_type": type(exc).__name__},
+            error=str(exc),
+        )
+        raise HTTPException(status_code=503, detail="提词已生成，积分结算暂未完成，请使用相同幂等键重试") from exc
+
+    _log_event(
+        GenerationRecordEventTypeEnum.PROMPT_OPTIMIZE_SETTLEMENT_SUCCESS,
+        user_id=user_id,
+        project_id=project_id_snapshot,
+        record_id=record_id,
+        detail={
+            "attempt_no": _PROMPT_ATTEMPT_NO,
+            "text_credits_cost": credits_snapshot,
+            "text_tokens_used": tokens_snapshot,
+        },
+    )
+    return PromptOptimizeServiceResult(record_id=record_id, idempotent=False)
+
+
+async def _handle_existing_record(
+    db: AsyncSession,
+    *,
+    record: GenerationRecord,
+    req: OptimizeParams,
+    user_id: str,
+    project_name: str,
+) -> PromptOptimizeServiceResult:
+    record_id = str(record.id)
+    project_id = str(record.project_id)
+    status = str(record.status)
+    if not _idempotency_config_matches(record, req):
+        await db.rollback()
+        raise HTTPException(status_code=409, detail="幂等键已绑定其他生成配置，请重新提交")
+
+    _log_event(
+        GenerationRecordEventTypeEnum.PROMPT_OPTIMIZE_IDEMPOTENCY_HIT,
+        status=LogEventStatusEnum.SKIPPED,
+        user_id=user_id,
+        project_id=project_id,
+        record_id=record_id,
+        detail={"record_status": status, "idempotency_key": req.idempotency_key},
+    )
+    if status == GenerationStatus.settlement_pending.value:
+        await db.rollback()
+        return await _settle_staged_result(
+            db,
+            record_id=record_id,
+            user_id=user_id,
+            project_name=project_name,
+            request_id=req.idempotency_key,
+        )
+    if status == GenerationStatus.optimizing.value:
+        await db.rollback()
+        raise HTTPException(status_code=409, detail="相同幂等请求正在处理，请勿重复提交")
+    if status == GenerationStatus.failed.value:
+        await db.rollback()
+        raise HTTPException(status_code=409, detail="该幂等请求已失败，请使用新的幂等键重新提交")
+    if record.optimized_prompt and is_generation_record_config_complete(record):
+        await db.rollback()
+        return PromptOptimizeServiceResult(record_id=record_id, idempotent=True)
+    await db.rollback()
+    raise HTTPException(status_code=409, detail="幂等记录配置不完整，需人工排查或使用新的幂等键")
+
+
+async def optimize_generation_prompt(
+    db: AsyncSession,
+    *,
+    req: OptimizeParams,
+    user_id: str,
+) -> PromptOptimizeServiceResult:
+    project_result = await db.execute(
+        select(Project).where(
+            Project.id == req.project_id,
+            Project.user_id == user_id,
+            Project.deleted_at.is_(None),
+        ).limit(1)
+    )
+    project = project_result.scalar_one_or_none()
+    if project is None:
+        raise HTTPException(status_code=404, detail="项目不存在")
+    project_name = str(project.name)
+    project_industry = str(project.industry or "")
+    project_id = str(project.id)
+
+    existing = await _find_idempotency_record(
+        db,
+        user_id=user_id,
+        idempotency_key=req.idempotency_key,
+    )
+    if existing is not None:
+        return await _handle_existing_record(
+            db,
+            record=existing,
+            req=req,
+            user_id=user_id,
+            project_name=project_name,
+        )
+
+    if req.gen_type == GenerationType.video:
+        if req.duration not in DURATIONS:
+            raise HTTPException(status_code=400, detail=f"视频时长必须为{DURATIONS}秒之一")
+        if req.aspect_ratio not in ASPECT_RATIOS:
+            raise HTTPException(status_code=400, detail="不支持的画面比例")
+        if req.resolution not in RESOLUTIONS:
+            raise HTTPException(status_code=400, detail="不支持的分辨率")
+        engine = await get_video_engine(db, req.engine_id)
+        _validate_video_engine_selection(
+            engine,
+            aspect_ratio=str(req.aspect_ratio),
+            resolution=str(req.resolution),
+            duration=int(req.duration),
+        )
+    else:
+        if req.image_size not in IMAGE_SIZES:
+            raise HTTPException(status_code=400, detail=f"图片分辨率必须为{IMAGE_SIZES}之一")
+        if not req.image_proportion or not req.image_px:
+            raise HTTPException(status_code=400, detail="图片生成需要指定比例和像素尺寸")
+        engine = await get_image_engine(db, req.engine_id)
+        _validate_image_engine_selection(engine, image_size=str(req.image_size))
+
+    reference_usage = calculate_media_reference_usage(
+        json.dumps(req.references, ensure_ascii=False) if req.references else None,
+        include=bool(req.include_media_references),
+    )
+    validate_media_reference_usage_for_engine(
+        reference_usage,
+        gen_type=req.gen_type.value,
+        engine=engine,
+    )
+
+    record_id = generate_id()
+    record = GenerationRecord(
+        id=record_id,
+        user_id=user_id,
+        project_id=project_id,
+        original_prompt=req.prompt,
+        optimized_prompt=None,
+        prompt_usage_snapshot_json=None,
+        gen_type=req.gen_type.value,
+        duration=req.duration if req.gen_type == GenerationType.video else None,
+        aspect_ratio=req.aspect_ratio if req.gen_type == GenerationType.video else None,
+        resolution=req.resolution if req.gen_type == GenerationType.video else None,
+        image_size=req.image_size if req.gen_type == GenerationType.image else None,
+        image_proportion=req.image_proportion if req.gen_type == GenerationType.image else None,
+        image_px=req.image_px if req.gen_type == GenerationType.image else None,
+        status=GenerationStatus.optimizing.value,
+        pipeline_stage=None,
+        credits_cost=0,
+        text_credits_cost=0,
+        text_tokens_used=0,
+        media_references=json.dumps(req.references, ensure_ascii=False) if req.references else None,
+        include_media_references=bool(req.include_media_references),
+        idempotency_key=req.idempotency_key,
+        engine_id=req.engine_id,
+    )
+    if req.gen_type == GenerationType.video:
+        provider_resolution, upscale_enabled, upscale_snapshot_json = await build_video_upscale_snapshot(
+            db,
+            target_resolution=str(req.resolution),
+            aspect_ratio=str(req.aspect_ratio),
+            supported_provider_resolutions=parse_json_list(engine.supported_resolutions, []),
+        )
+        record.provider_generation_resolution = provider_resolution
+        record.video_upscale_enabled_snapshot = upscale_enabled
+        record.video_upscale_snapshot_json = upscale_snapshot_json
+    else:
+        record.provider_generation_resolution = None
+        record.video_upscale_enabled_snapshot = False
+        record.video_upscale_snapshot_json = None
+    freeze_generation_record_config_with_log(
+        record,
+        engine=engine,
+        source=GenerationRecordConfigSourceEnum.PROMPT_OPTIMIZE,
+    )
+    db.add(record)
+    try:
+        await db.flush()
+    except IntegrityError:
+        await db.rollback()
+        conflicting = await _find_idempotency_record(
+            db,
+            user_id=user_id,
+            idempotency_key=req.idempotency_key,
+        )
+        if conflicting is None:
+            raise
+        return await _handle_existing_record(
+            db,
+            record=conflicting,
+            req=req,
+            user_id=user_id,
+            project_name=project_name,
+        )
+
+    ctx = _billing_context(user_id=user_id, record_id=record_id, request_id=req.idempotency_key)
+    try:
+        await start_hold(db, ctx)
+        await db.commit()
+    except Exception:
+        await db.rollback()
+        raise
+
+    _log_event(
+        GenerationRecordEventTypeEnum.PROMPT_OPTIMIZE_PLACEHOLDER_CREATED,
+        user_id=user_id,
+        project_id=project_id,
+        record_id=record_id,
+        detail={
+            "idempotency_key": req.idempotency_key,
+            "gen_type": req.gen_type.value,
+            "engine_id": req.engine_id,
+            "attempt_no": _PROMPT_ATTEMPT_NO,
+            "reference_count": len(req.references or []),
+        },
+    )
+
+    log_provider_start(ctx, detail={"gen_type": req.gen_type.value})
+    try:
+        optimized_prompt, usage = await optimize_prompt(
+            db,
+            req.prompt,
+            user_id=user_id,
+            industry_key=project_industry,
+            duration=req.duration if req.gen_type == GenerationType.video else None,
+            image_size=req.image_size if req.gen_type == GenerationType.image else None,
+            image_proportion=req.image_proportion if req.gen_type == GenerationType.image else None,
+            image_px=req.image_px if req.gen_type == GenerationType.image else None,
+            references=req.references,
+            gen_type=req.gen_type.value,
+            log_module="generation_record",
+            log_step="prompt_optimize",
+            log_project_id=project_id,
+            log_owner_type=OWNER_GENERATION_RECORD,
+            log_owner_id=record_id,
+            generation_attempt_no=_PROMPT_ATTEMPT_NO,
+        )
+        log_provider_success(ctx, usage=usage)
+    except Exception as exc:
+        await db.rollback()
+        log_provider_failure(ctx, error=str(exc))
+        compensated = False
+        try:
+            failed_result = await db.execute(
+                select(GenerationRecord)
+                .where(GenerationRecord.id == record_id, GenerationRecord.deleted_at.is_(None))
+                .with_for_update()
+                .limit(1)
+            )
+            failed_record = failed_result.scalar_one_or_none()
+            if failed_record is not None and failed_record.status == GenerationStatus.optimizing.value:
+                failed_record.status = GenerationStatus.failed.value
+                failed_record.error_message = extract_error_message(exc, "提示词")
+                await release_on_failure(db, ctx, error=str(exc))
+                compensated = True
+            await db.commit()
+        except Exception:
+            await db.rollback()
+            logger.exception("prompt optimize failure compensation failed: record_id=%s", record_id)
+            raise
+        _log_event(
+            GenerationRecordEventTypeEnum.PROMPT_OPTIMIZE_FAILED_RELEASED,
+            status=(LogEventStatusEnum.FAILED if compensated else LogEventStatusEnum.SKIPPED),
+            user_id=user_id,
+            project_id=project_id,
+            record_id=record_id,
+            detail={
+                "attempt_no": _PROMPT_ATTEMPT_NO,
+                "error_type": type(exc).__name__,
+                "compensated": compensated,
+            },
+            error=str(exc),
+        )
+        raise HTTPException(
+            status_code=502,
+            detail=f"AI模型调用失败: {extract_error_message(exc, '提示词')}",
+        ) from exc
+
+    usage_snapshot = dict(usage or {})
+    try:
+        input_tokens = int(usage_snapshot.get("input_tokens", 0) or 0)
+        output_tokens = int(usage_snapshot.get("output_tokens", 0) or 0)
+    except (TypeError, ValueError):
+        # 保留原始 usage 交给统一账务校验拒绝；这里只避免展示字段写入异常。
+        input_tokens = 0
+        output_tokens = 0
+    if input_tokens >= 0 and output_tokens >= 0:
+        reported_total = usage_snapshot.get("total_tokens")
+        normalized_total = input_tokens + output_tokens
+        if reported_total not in (None, ""):
+            try:
+                if int(reported_total) != normalized_total:
+                    usage_snapshot["reported_total_tokens"] = int(reported_total)
+            except (TypeError, ValueError):
+                usage_snapshot["reported_total_tokens"] = reported_total
+        usage_snapshot["total_tokens"] = normalized_total
+    usage_snapshot.setdefault("source_module", "generation_record")
+    usage_snapshot.setdefault("source_step_code", "prompt_optimize")
+    staged = False
+    last_stage_error: Exception | None = None
+    for _ in range(2):
+        try:
+            await db.rollback()
+            stage_result = await db.execute(
+                select(GenerationRecord)
+                .where(
+                    GenerationRecord.id == record_id,
+                    GenerationRecord.user_id == user_id,
+                    GenerationRecord.deleted_at.is_(None),
+                )
+                .with_for_update()
+                .limit(1)
+            )
+            staged_record = stage_result.scalar_one_or_none()
+            if staged_record is None:
+                raise RuntimeError("prompt optimize owner record missing")
+            if staged_record.status in {
+                GenerationStatus.prompt_optimized.value,
+                GenerationStatus.generating.value,
+                GenerationStatus.completed.value,
+            }:
+                await db.rollback()
+                return PromptOptimizeServiceResult(record_id=record_id, idempotent=True)
+            staged_record.optimized_prompt = optimized_prompt
+            staged_record.prompt_usage_snapshot_json = json.dumps(
+                usage_snapshot,
+                ensure_ascii=False,
+                sort_keys=True,
+                default=str,
+            )
+            staged_record.text_tokens_used = int(usage_snapshot.get("total_tokens", 0) or 0)
+            staged_record.status = GenerationStatus.settlement_pending.value
+            staged_record.pipeline_stage = None
+            staged_record.error_message = None
+            await db.commit()
+            staged = True
+            break
+        except Exception as exc:
+            last_stage_error = exc
+            await db.rollback()
+            logger.exception("prompt optimize provider result staging failed: record_id=%s", record_id)
+    if not staged:
+        log_operation_error(
+            domain=_LOG_DOMAIN,
+            event_type=GenerationRecordEventTypeEnum.PROMPT_OPTIMIZE_PROVIDER_RESULT_STAGED.value,
+            module=_LOG_MODULE,
+            source=_LOG_SOURCE,
+            user_id=user_id,
+            project_id=project_id,
+            task_id=record_id,
+            detail={"attempt_no": _PROMPT_ATTEMPT_NO, "stage": "provider_result_persistence"},
+            exc=last_stage_error or RuntimeError("unknown staging failure"),
+        )
+        raise HTTPException(status_code=503, detail="提词已生成但本地暂存失败，请联系管理员根据模型日志处理")
+
+    _log_event(
+        GenerationRecordEventTypeEnum.PROMPT_OPTIMIZE_PROVIDER_RESULT_STAGED,
+        user_id=user_id,
+        project_id=project_id,
+        record_id=record_id,
+        detail={
+            "attempt_no": _PROMPT_ATTEMPT_NO,
+            "input_tokens": usage_snapshot.get("input_tokens"),
+            "output_tokens": usage_snapshot.get("output_tokens"),
+            "total_tokens": usage_snapshot.get("total_tokens"),
+        },
+    )
+    return await _settle_staged_result(
+        db,
+        record_id=record_id,
+        user_id=user_id,
+        project_name=project_name,
+        request_id=req.idempotency_key,
+    )

video-gen-api/app/services/generation/refund_service.py

@@ -8,7 +8,7 @@ from app.models.chat_generation_task import ChatGenerationTask
 from app.models.credit_record import CreditRecord
 from app.models.generation_record import GenerationRecord
 from app.services.generation.pipeline.db_lock_service import execute_with_lock_timeout
-from app.services.credits import refund_credits
+from app.services.credits import add_credits_result
 from app.services.credit_record_meta_service import build_refund_meta_from_charge
 from app.services.generation.billing_service import (
     CHARGE_MEDIA,
@@ -113,17 +113,19 @@ async def refund_unrefunded_media_charges(
         amount = abs(_round2(charge.amount))
         if amount <= 0:
             continue
-        await refund_credits(
+        mutation = await add_credits_result(
             db,
             user_id=user_id,
             amount=amount,
             description=f"{description_prefix}失败积分回退",
             related_id=owner_id,
+            record_type="refund",
             biz_key=refund_biz_key,
             refund_for_biz_key=charge.biz_key,
             record_meta=build_refund_meta_from_charge(charge, attempt_no=attempt_no),
         )
-        total_refunded = round(total_refunded + amount, 2)
+        if mutation.created:
+            total_refunded = round(total_refunded + mutation.amount, 2)
     return total_refunded
 
 

video-gen-api/app/services/hot_opening_replicate_service.py

@@ -370,6 +370,16 @@ async def _soft_delete_steps_from_index(
 
 
 def _step_to_out(step: ModuleGenerationStep) -> HotOpeningStepOut:
+    error_message = step.error_message
+    if error_message:
+        from app.services.error_codes import ARK_ERRORS
+        import re
+        # 兼容两种格式: code='xxx' 或 'code': 'xxx'
+        match = re.search(r"""code['"]?\s*[:=]\s*['"]([^'"]+)['"]""", error_message)
+        if match:
+            code = match.group(1)
+            if code in ARK_ERRORS:
+                error_message = ARK_ERRORS[code]
     return HotOpeningStepOut(
         id=step.id,
         project_id=step.project_id,
@@ -384,7 +394,7 @@ def _step_to_out(step: ModuleGenerationStep) -> HotOpeningStepOut:
         chat_task_id=step.chat_task_id,
         input=_parse_json(step.input_json, {}),
         output=_parse_json(step.output_json, {}),
-        error_message=step.error_message,
+        error_message=error_message,
         created_at=step.created_at,
         updated_at=step.updated_at,
         completed_at=step.completed_at,
@@ -1152,10 +1162,10 @@ async def run_image_prompt_optimize(
             await db.commit()
             return None
         step.status = ModuleStepStatusEnum.FAILED.value
-        step.error_message = str(exc)
+        step.error_message = str(exc) if str(exc) else type(exc).__name__
         step.completed_at = _now()
         project.status = ModuleProjectStatusEnum.FAILED.value
-        project.error_message = f"图片 AI 提词生成失败: {exc}"
+        project.error_message = f"图片 AI 提词生成失败: {str(exc) if str(exc) else type(exc).__name__}"
         log_module_prompt_event(
             event_type="module_prompt_error",
             project_id=project.id,
@@ -1623,10 +1633,10 @@ async def run_video_prompt_optimize(
             await db.commit()
             return None
         step.status = ModuleStepStatusEnum.FAILED.value
-        step.error_message = str(exc)
+        step.error_message = str(exc) if str(exc) else type(exc).__name__
         step.completed_at = _now()
         project.status = ModuleProjectStatusEnum.FAILED.value
-        project.error_message = f"视频 AI 提词生成失败: {exc}"
+        project.error_message = f"视频 AI 提词生成失败: {str(exc) if str(exc) else type(exc).__name__}"
         log_module_prompt_event(
             event_type="module_prompt_error",
             project_id=project.id,

video-gen-api/app/services/hot_opening_video_prompt_service.py

@@ -25,9 +25,8 @@ from app.enums.common import (
 )
 from app.enums.video_prompt_schema import PromptSchemaVersionEnum, VideoPromptSchemaUsageEnum
 from app.models.model_config import ModelConfig
-from app.models.token_usage import TokenUsage
-from app.utils.id_gen import generate_id
 from app.services.resource_signed_url_service import build_resource_signed_url
+from app.utils.id_gen import generate_id
 
 DEFAULT_FRAME_RATE = "30fps"
 DEFAULT_REFERENCE_VIDEO_FPS = 1
@@ -1599,7 +1598,13 @@ async def optimize_hot_opening_video_prompt(
     await db.rollback()
     if not config:
         result = normalize_video_prompt_schema_from_ai(_mock_result(video_config, target_platform), video_config, schema_config_snapshot)
-        return result, build_final_video_prompt(result), {"input_tokens": 0, "output_tokens": 0, "total_tokens": 0}
+        return result, build_final_video_prompt(result), {
+            "input_tokens": 0,
+            "output_tokens": 0,
+            "total_tokens": 0,
+            "usage_reported": True,
+            "billing_free": True,
+        }
 
     if use_base64:
         video_url_final = await media_to_base64(material_video_url, "video/mp4")
@@ -1628,7 +1633,7 @@ async def optimize_hot_opening_video_prompt(
     request_data = {
         "model": config.model_name,
         "messages": [{"role": "system", "content": build_system_prompt()}, user_message],
-        "max_tokens": 6000,
+        "max_tokens": 10000,
         "temperature": 0.15,
         "response_format": {"type": "json_object"},
     }
@@ -1739,27 +1744,20 @@ async def optimize_hot_opening_video_prompt(
             error=str(exc),
         )
         raise
-    usage = data.get("usage", {}) or {}
+    raw_usage = data.get("usage")
+    usage_reported = bool(
+        isinstance(raw_usage, dict)
+        and any(key in raw_usage for key in ("prompt_tokens", "completion_tokens", "total_tokens"))
+    )
+    usage = raw_usage if isinstance(raw_usage, dict) else {}
     token_usage = {
         "input_tokens": int(usage.get("prompt_tokens") or 0),
         "output_tokens": int(usage.get("completion_tokens") or 0),
         "total_tokens": int(usage.get("total_tokens") or 0),
+        "usage_reported": usage_reported,
         # "log_user_message": log_user_message,
     }
-    token_usage_id = generate_id()
-    db.add(
-        TokenUsage(
-            id=token_usage_id,
-            model_config_id=config.id,
-            user_id=user_id,
-            input_tokens=token_usage["input_tokens"],
-            output_tokens=token_usage["output_tokens"],
-            total_tokens=token_usage["total_tokens"],
-        )
-    )
-    await db.flush()
     token_usage.update({
-        "token_usage_id": token_usage_id,
         "model_config_id": config.id,
         "model_config_name": config.name,
         "model_provider": config.provider,

video-gen-api/app/services/llm.py

@@ -8,9 +8,8 @@ from sqlalchemy.ext.asyncio import AsyncSession
 
 from app.config import settings
 from app.models.model_config import ModelConfig
-from app.models.token_usage import TokenUsage
-from app.utils.id_gen import generate_id
 from app.services.operation_log_service import build_exception_detail, log_ai_model_event
+from app.utils.id_gen import generate_id
 
 
 
@@ -47,7 +46,13 @@ def _get_default_prompt(prompt: str, gen_type: str = "video") -> tuple[str, dict
             f"smooth camera movements. Theme: {prompt}. Cinematic shooting techniques with "
             f"rich lighting layers and strong visual impact, suitable for commercial distribution."
         )
-    return optimized, {"input_tokens": 0, "output_tokens": 0, "total_tokens": 0}
+    return optimized, {
+        "input_tokens": 0,
+        "output_tokens": 0,
+        "total_tokens": 0,
+        "usage_reported": True,
+        "billing_free": True,
+    }
 
 
 async def optimize_prompt(
@@ -135,7 +140,13 @@ def _mock_optimize(prompt: str, gen_type: str = "video") -> tuple[str, dict]:
     """Return a keyword-matched mock optimized prompt."""
     for keyword, optimized in MOCK_OPTIMIZED_PROMPTS.items():
         if keyword in prompt:
-            return optimized, {"input_tokens": 0, "output_tokens": 0, "total_tokens": 0}
+            return optimized, {
+                "input_tokens": 0,
+                "output_tokens": 0,
+                "total_tokens": 0,
+                "usage_reported": True,
+                "billing_free": True,
+            }
     return _get_default_prompt(prompt, gen_type)
 
 
@@ -425,7 +436,15 @@ async def _call_openai_compatible(
             raise LLMProviderCallError(f"{type(exc).__name__}: {exc}") from exc
 
         try:
-            usage = data.get("usage", {})
+            raw_usage = data.get("usage")
+            usage_reported = bool(
+                isinstance(raw_usage, dict)
+                and any(
+                    key in raw_usage
+                    for key in ("prompt_tokens", "completion_tokens", "total_tokens")
+                )
+            )
+            usage = raw_usage if isinstance(raw_usage, dict) else {}
             input_tokens = int(usage.get("prompt_tokens", 0) or 0)
             output_tokens = int(usage.get("completion_tokens", 0) or 0)
             total_tokens = int(usage.get("total_tokens", input_tokens + output_tokens) or 0)
@@ -444,40 +463,7 @@ async def _call_openai_compatible(
             )
             raise LLMProviderCallError(f"模型响应解析失败: {exc}") from exc
 
-        token_usage_id = None
-        if db is not None:
-            try:
-                token_usage_id = generate_id()
-                record = TokenUsage(
-                    id=token_usage_id,
-                    model_config_id=config.id,
-                    user_id=user_id,
-                    input_tokens=input_tokens,
-                    output_tokens=output_tokens,
-                    total_tokens=total_tokens,
-                    source_module=log_module,
-                    source_step_code=log_step,
-                    owner_type=log_owner_type,
-                    owner_id=log_owner_id,
-                )
-                db.add(record)
-                await db.flush()
-            except Exception as exc:
-                log_ai_model_event(
-                    event_type="ERROR",
-                    event_phase="ERROR",
-                    event_status="failed",
-                    latency_ms=int((time.perf_counter() - started) * 1000),
-                    detail=build_exception_detail(exc, {"stage": "token_usage_persistence"}),
-                    error=str(exc),
-                    **common_log,
-                )
-                # A local transaction failure must not call a second provider after
-                # the first provider has already returned a valid response.
-                raise
-
         token_usage = {
-            "token_usage_id": token_usage_id,
             "model_config_id": config.id,
             "model_config_name": config.name,
             "model_provider": config.provider,
@@ -487,5 +473,6 @@ async def _call_openai_compatible(
             "input_tokens": input_tokens,
             "output_tokens": output_tokens,
             "total_tokens": total_tokens,
+            "usage_reported": usage_reported,
         }
         return content, token_usage

video-gen-api/app/services/llm_billing/__init__.py

@@ -19,6 +19,7 @@ from app.services.llm_billing.service import (
     release_on_failure,
     settle_success,
     start_hold,
+    validate_retryable_previous_attempt,
 )
 
 __all__ = [
@@ -31,6 +32,7 @@ __all__ = [
     "start_hold",
     "ensure_hold_exists",
     "get_llm_ledger_states",
+    "validate_retryable_previous_attempt",
     "log_provider_start",
     "log_provider_success",
     "log_provider_failure",

video-gen-api/app/services/llm_billing/service.py

@@ -4,6 +4,7 @@ from dataclasses import dataclass
 from typing import Any, Iterable, Mapping
 
 from sqlalchemy import select
+from sqlalchemy.exc import IntegrityError
 from sqlalchemy.ext.asyncio import AsyncSession
 
 from app.enums.credit_record import (
@@ -210,8 +211,21 @@ def _action_valid(record: CreditRecord | None, expected: CreditRecordAction) ->
 
 
 
+def _record_meta_matches_context(record: CreditRecord | None, ctx: LlmBillingContext) -> bool:
+    if record is None:
+        return True
+    checks = (
+        (record.owner_type, ctx.owner_type),
+        (record.owner_id, ctx.owner_id),
+        (record.attempt_no, ctx.attempt_no),
+        (record.charge_kind, ctx.charge_kind),
+    )
+    return all(actual is None or str(actual) == str(expected) for actual, expected in checks)
+
+
 def _classify_ledger(
     *,
+    ctx: LlmBillingContext,
     hold: CreditRecord | None,
     release: CreditRecord | None,
     charge: CreditRecord | None,
@@ -222,17 +236,39 @@ def _classify_ledger(
         return _LedgerRecords(LlmBillingLedgerState.INVALID, hold, release, charge, "release_action_mismatch")
     if not _action_valid(charge, CreditRecordAction.CHARGE):
         return _LedgerRecords(LlmBillingLedgerState.INVALID, hold, release, charge, "charge_action_mismatch")
+    if not _record_meta_matches_context(hold, ctx):
+        return _LedgerRecords(LlmBillingLedgerState.INVALID, hold, release, charge, "hold_context_mismatch")
+    if not _record_meta_matches_context(release, ctx):
+        return _LedgerRecords(LlmBillingLedgerState.INVALID, hold, release, charge, "release_context_mismatch")
+    if not _record_meta_matches_context(charge, ctx):
+        return _LedgerRecords(LlmBillingLedgerState.INVALID, hold, release, charge, "charge_context_mismatch")
     if hold is None:
         if release is not None or charge is not None:
             return _LedgerRecords(LlmBillingLedgerState.INVALID, hold, release, charge, "hold_missing_with_followup")
         return _LedgerRecords(LlmBillingLedgerState.MISSING)
     if release is None and charge is None:
+        if hold.type != "consume" or _round2(float(hold.amount or 0)) >= 0:
+            return _LedgerRecords(LlmBillingLedgerState.INVALID, hold, release, charge, "hold_type_or_sign_invalid")
         if _round2(abs(float(hold.amount or 0))) <= 0:
             return _LedgerRecords(LlmBillingLedgerState.INVALID, hold, release, charge, "hold_amount_not_positive")
         return _LedgerRecords(LlmBillingLedgerState.ACTIVE, hold)
     if release is not None and charge is None:
+        if release.type != "refund" or _round2(float(release.amount or 0)) <= 0:
+            return _LedgerRecords(LlmBillingLedgerState.INVALID, hold, release, charge, "release_type_or_sign_invalid")
+        if str(release.refund_for_biz_key or "") != str(ctx.hold_biz_key):
+            return _LedgerRecords(LlmBillingLedgerState.INVALID, hold, release, charge, "release_target_mismatch")
+        if _round2(release.amount) != _round2(abs(float(hold.amount or 0))):
+            return _LedgerRecords(LlmBillingLedgerState.INVALID, hold, release, charge, "release_amount_mismatch")
         return _LedgerRecords(LlmBillingLedgerState.RELEASED, hold, release)
     if release is not None and charge is not None:
+        if release.type != "refund" or _round2(float(release.amount or 0)) <= 0:
+            return _LedgerRecords(LlmBillingLedgerState.INVALID, hold, release, charge, "release_type_or_sign_invalid")
+        if str(release.refund_for_biz_key or "") != str(ctx.hold_biz_key):
+            return _LedgerRecords(LlmBillingLedgerState.INVALID, hold, release, charge, "release_target_mismatch")
+        if _round2(release.amount) != _round2(abs(float(hold.amount or 0))):
+            return _LedgerRecords(LlmBillingLedgerState.INVALID, hold, release, charge, "release_amount_mismatch")
+        if charge.type != "consume" or _round2(float(charge.amount or 0)) > 0:
+            return _LedgerRecords(LlmBillingLedgerState.INVALID, hold, release, charge, "charge_type_or_sign_invalid")
         return _LedgerRecords(LlmBillingLedgerState.CHARGED, hold, release, charge)
     return _LedgerRecords(LlmBillingLedgerState.INVALID, hold, release, charge, "charge_without_release")
 
@@ -264,7 +300,7 @@ async def _load_ledgers(
         hold = record_map.get((ctx.user_id, ctx.hold_biz_key))
         release = record_map.get((ctx.user_id, ctx.hold_release_biz_key))
         charge = record_map.get((ctx.user_id, ctx.charge_biz_key))
-        output[ctx.hold_biz_key] = _classify_ledger(hold=hold, release=release, charge=charge)
+        output[ctx.hold_biz_key] = _classify_ledger(ctx=ctx, hold=hold, release=release, charge=charge)
     return output
 
 
@@ -291,6 +327,104 @@ async def get_llm_ledger_states(
     }
 
 
+async def validate_retryable_previous_attempt(
+    db: AsyncSession,
+    ctx: LlmBillingContext,
+) -> LlmHoldValidation:
+    """校验失败 attempt 的账务是否已关闭，供业务创建下一 attempt 前调用。
+
+    只有已释放 HOLD，或当前计费明确关闭且旧 attempt 没有流水时，才允许创建
+    新 attempt。这里不主动退款，避免重试入口承担失败补偿职责。
+    """
+    _log(
+        ctx,
+        LlmBillingEvent.RETRY_PREVIOUS_ATTEMPT_VALIDATE_START,
+        status="started",
+    )
+    ledger = await _load_ledger(db, ctx)
+
+    if ledger.state == LlmBillingLedgerState.RELEASED:
+        result = LlmHoldValidation(
+            True,
+            ledger.hold_amount,
+            ledger.state,
+            hold_record_id=ledger.hold.id if ledger.hold else None,
+        )
+        _log(
+            ctx,
+            LlmBillingEvent.RETRY_PREVIOUS_ATTEMPT_VALIDATE_SUCCESS,
+            detail=_context_detail(
+                ctx,
+                ledger_state=result.state.value,
+                hold_credits=result.amount,
+                hold_record_id=result.hold_record_id,
+            ),
+        )
+        return result
+
+    if ledger.state == LlmBillingLedgerState.MISSING:
+        policy = await get_llm_billing_policy(
+            db,
+            config_key=ctx.hold_config_key,
+            explicit_hold_credits=None,
+        )
+        if policy.bypassed:
+            result = LlmHoldValidation(
+                True,
+                0.0,
+                LlmBillingLedgerState.BILLING_BYPASSED,
+                "billing_disabled",
+            )
+            _log(
+                ctx,
+                LlmBillingEvent.RETRY_PREVIOUS_ATTEMPT_VALIDATE_SUCCESS,
+                status="skipped",
+                detail=_context_detail(
+                    ctx,
+                    ledger_state=result.state.value,
+                    billing_bypassed=True,
+                ),
+            )
+            return result
+        if not policy.valid:
+            result = LlmHoldValidation(
+                False,
+                0.0,
+                LlmBillingLedgerState.INVALID,
+                policy.error or "billing_config_invalid",
+            )
+        else:
+            result = LlmHoldValidation(
+                False,
+                0.0,
+                ledger.state,
+                "previous_attempt_hold_missing",
+            )
+    else:
+        result = LlmHoldValidation(
+            False,
+            ledger.hold_amount,
+            ledger.state,
+            ledger.reason or f"previous_attempt_ledger_{ledger.state.value}",
+            ledger.hold.id if ledger.hold else None,
+        )
+
+    _log(
+        ctx,
+        LlmBillingEvent.RETRY_PREVIOUS_ATTEMPT_BLOCKED,
+        status="failed",
+        detail=_context_detail(
+            ctx,
+            ledger_state=result.state.value,
+            hold_credits=result.amount,
+            hold_record_id=result.hold_record_id,
+            skip_reason=result.reason,
+        ),
+        error="旧attempt账务尚未关闭，拒绝创建新的分析attempt",
+    )
+    return result
+
+
 async def start_hold(db: AsyncSession, ctx: LlmBillingContext) -> LlmHoldResult:
     # 幂等/异常 attempt 优先由已落库流水判定；只有全新 attempt 才读取配置。
     ledger = await _load_ledger(db, ctx)
@@ -659,6 +793,147 @@ async def release_on_failure(db: AsyncSession, ctx: LlmBillingContext, *, error:
     return BillingSummary(record_id=ctx.owner_id, user_id=ctx.user_id, items=[item])
 
 
+def _normalize_settlement_usage(
+    ctx: LlmBillingContext,
+    usage: Mapping[str, Any],
+) -> dict[str, Any]:
+    snapshot = dict(usage or {})
+    try:
+        if snapshot.get("usage_reported") is False and not bool(snapshot.get("billing_free")):
+            raise ValueError("provider_usage_missing")
+        if "input_tokens" not in snapshot or "output_tokens" not in snapshot:
+            raise ValueError("input_or_output_tokens_missing")
+        input_tokens = int(snapshot.get("input_tokens"))
+        output_tokens = int(snapshot.get("output_tokens"))
+        if input_tokens < 0 or output_tokens < 0:
+            raise ValueError("token_count_negative")
+        normalized_total = input_tokens + output_tokens
+        raw_total = snapshot.get("total_tokens")
+        if raw_total not in (None, ""):
+            total_tokens = int(raw_total)
+            if total_tokens < 0:
+                raise ValueError("total_tokens_negative")
+        else:
+            total_tokens = normalized_total
+        if total_tokens != normalized_total:
+            snapshot["reported_total_tokens"] = total_tokens
+            total_tokens = normalized_total
+        snapshot["input_tokens"] = input_tokens
+        snapshot["output_tokens"] = output_tokens
+        snapshot["total_tokens"] = total_tokens
+        return snapshot
+    except (TypeError, ValueError) as exc:
+        _log(
+            ctx,
+            LlmBillingEvent.USAGE_INVALID,
+            status="failed",
+            detail=_context_detail(ctx, usage=snapshot, reason=str(exc)),
+            error="LLM usage 无效，拒绝释放 HOLD 和创建真实扣费",
+        )
+        raise LlmBillingStateError(f"LLM usage 无效：{exc}") from exc
+
+
+async def _ensure_token_usage_once(
+    db: AsyncSession,
+    ctx: LlmBillingContext,
+    usage: dict[str, Any],
+) -> TokenUsage:
+    supplied_id = str(usage.get("token_usage_id") or "").strip() or None
+    if supplied_id:
+        supplied_result = await db.execute(
+            select(TokenUsage).where(TokenUsage.id == supplied_id).limit(1)
+        )
+        supplied = supplied_result.scalar_one_or_none()
+        if supplied is not None:
+            if supplied.user_id not in (None, ctx.user_id):
+                raise LlmBillingStateError("TokenUsage 用户归属与当前账务上下文不一致")
+            if supplied.biz_key not in (None, ctx.charge_biz_key):
+                raise LlmBillingStateError("TokenUsage biz_key 与当前 charge 不一致")
+            supplied.user_id = supplied.user_id or ctx.user_id
+            supplied.owner_type = supplied.owner_type or ctx.owner_type
+            supplied.owner_id = supplied.owner_id or ctx.owner_id
+            supplied.biz_key = supplied.biz_key or ctx.charge_biz_key
+            supplied.source_module = supplied.source_module or ctx.source_module
+            supplied.source_step_code = supplied.source_step_code or ctx.source_step_code
+            usage["token_usage_id"] = supplied.id
+            ctx.token_usage_id = supplied.id
+            _log(
+                ctx,
+                LlmBillingEvent.TOKEN_USAGE_REUSED,
+                detail=_context_detail(ctx, token_usage_id=supplied.id, source="supplied_id"),
+            )
+            return supplied
+
+    result = await db.execute(
+        select(TokenUsage)
+        .where(
+            TokenUsage.user_id == ctx.user_id,
+            TokenUsage.biz_key == ctx.charge_biz_key,
+        )
+        .limit(1)
+    )
+    existing = result.scalar_one_or_none()
+    if existing is not None:
+        usage["token_usage_id"] = existing.id
+        ctx.token_usage_id = existing.id
+        _log(
+            ctx,
+            LlmBillingEvent.TOKEN_USAGE_REUSED,
+            detail=_context_detail(ctx, token_usage_id=existing.id, source="biz_key"),
+        )
+        return existing
+
+    token_usage = TokenUsage(
+        id=generate_id(),
+        model_config_id=usage.get("model_config_id"),
+        user_id=ctx.user_id,
+        input_tokens=int(usage["input_tokens"]),
+        output_tokens=int(usage["output_tokens"]),
+        total_tokens=int(usage["total_tokens"]),
+        owner_type=ctx.owner_type,
+        owner_id=ctx.owner_id,
+        biz_key=ctx.charge_biz_key,
+        source_module=ctx.source_module,
+        source_step_code=ctx.source_step_code,
+    )
+    try:
+        async with db.begin_nested():
+            db.add(token_usage)
+            await db.flush()
+    except IntegrityError:
+        if token_usage in db.sync_session:
+            db.sync_session.expunge(token_usage)
+        result = await db.execute(
+            select(TokenUsage)
+            .where(
+                TokenUsage.user_id == ctx.user_id,
+                TokenUsage.biz_key == ctx.charge_biz_key,
+            )
+            .limit(1)
+        )
+        token_usage = result.scalar_one_or_none()
+        if token_usage is None:
+            raise
+        event = LlmBillingEvent.TOKEN_USAGE_REUSED
+    else:
+        event = LlmBillingEvent.TOKEN_USAGE_CREATED
+
+    usage["token_usage_id"] = token_usage.id
+    ctx.token_usage_id = token_usage.id
+    _log(
+        ctx,
+        event,
+        detail=_context_detail(
+            ctx,
+            token_usage_id=token_usage.id,
+            input_tokens=token_usage.input_tokens,
+            output_tokens=token_usage.output_tokens,
+            total_tokens=token_usage.total_tokens,
+        ),
+    )
+    return token_usage
+
+
 async def _build_charge_meta(db: AsyncSession, ctx: LlmBillingContext, usage: Mapping[str, Any]) -> CreditRecordMeta:
     usage_snapshot = dict(usage or {})
     ctx.provider = str(usage_snapshot.get("provider") or usage_snapshot.get("model_provider") or "") or ctx.provider
@@ -680,26 +955,6 @@ async def _build_charge_meta(db: AsyncSession, ctx: LlmBillingContext, usage: Ma
             usage=usage_snapshot,
         )
     if ctx.charge_kind == CreditRecordChargeKind.VIDEO_ANALYSIS.value:
-        if not usage_snapshot.get("token_usage_id"):
-            input_tokens = _safe_int(usage_snapshot.get("input_tokens"))
-            output_tokens = _safe_int(usage_snapshot.get("output_tokens"))
-            token_usage = TokenUsage(
-                id=generate_id(),
-                model_config_id=usage_snapshot.get("model_config_id"),
-                user_id=ctx.user_id,
-                input_tokens=input_tokens,
-                output_tokens=output_tokens,
-                total_tokens=_safe_int(usage_snapshot.get("total_tokens"), input_tokens + output_tokens),
-                owner_type=ctx.owner_type,
-                owner_id=ctx.owner_id,
-                biz_key=ctx.charge_biz_key,
-                source_module=ctx.source_module or CreditRecordSourceModule.SHOT_REPLICATE.value,
-                source_step_code=ctx.source_step_code,
-            )
-            db.add(token_usage)
-            await db.flush()
-            usage_snapshot["token_usage_id"] = token_usage.id
-            ctx.token_usage_id = token_usage.id
         return await build_shot_video_analysis_meta(
             db,
             owner_type=ctx.owner_type,
@@ -791,12 +1046,27 @@ async def _settle_success_impl(
             f"当前attempt账务状态为{ledger.state.value}，不能执行成功结算"
         )
 
-    _log(ctx, LlmBillingEvent.SETTLE_START, status="started", detail=_context_detail(ctx, ledger_state=ledger.state.value, usage=dict(usage or {})))
+    normalized_usage = _normalize_settlement_usage(ctx, usage)
-    release_item = await _release_active_hold(db, ctx, hold_record=ledger.hold, reason="success")
+    await _ensure_token_usage_once(db, ctx, normalized_usage)
-    input_tokens = _safe_int((usage or {}).get("input_tokens"))
+    _log(
-    output_tokens = _safe_int((usage or {}).get("output_tokens"))
+        ctx,
+        LlmBillingEvent.SETTLE_START,
+        status="started",
+        detail=_context_detail(
+            ctx,
+            ledger_state=ledger.state.value,
+            input_tokens=normalized_usage["input_tokens"],
+            output_tokens=normalized_usage["output_tokens"],
+            total_tokens=normalized_usage["total_tokens"],
+            provider=normalized_usage.get("provider") or normalized_usage.get("model_provider"),
+            model_name=normalized_usage.get("model_name") or normalized_usage.get("model"),
+        ),
+    )
+    input_tokens = int(normalized_usage["input_tokens"])
+    output_tokens = int(normalized_usage["output_tokens"])
     amount = await calc_text_credits(db, input_tokens, output_tokens)
-    meta = await _build_charge_meta(db, ctx, usage)
+    meta = await _build_charge_meta(db, ctx, normalized_usage)
+    release_item = await _release_active_hold(db, ctx, hold_record=ledger.hold, reason="success")
     if meta.charge_action is None:
         meta.charge_action = CreditRecordAction.CHARGE.value
     meta.billing_scene = meta.billing_scene or ctx.billing_scene
@@ -831,7 +1101,7 @@ async def _settle_success_impl(
         step = result.scalar_one_or_none()
         if step:
             step.token_usage_id = meta.token_usage_id
-            step.model_config_id = (usage or {}).get("model_config_id")
+            step.model_config_id = normalized_usage.get("model_config_id")
             step.input_tokens = meta.input_tokens
             step.output_tokens = meta.output_tokens
             step.total_tokens = meta.total_tokens

video-gen-api/app/services/module_generation_v2/flow_service.py

@@ -1066,10 +1066,10 @@ async def run_video_prompt_optimize_v2(
                 project, step = row
                 if step.status == ModuleStepStatusEnum.PROCESSING.value:
                     step.status = ModuleStepStatusEnum.FAILED.value
-                    step.error_message = str(exc)
+                    step.error_message = str(exc) if str(exc) else type(exc).__name__
                     step.completed_at = utc_now()
                     project.status = ModuleProjectStatusEnum.FAILED.value
-                    project.error_message = str(exc)
+                    project.error_message = str(exc) if str(exc) else type(exc).__name__
             # provider 已成功时 settle_success 已在当前事务写入 RELEASE/CHARGE；
             # 即使业务步骤已不存在或已不是 processing，也必须提交账务结算。
             await db.commit()

video-gen-api/app/services/shot_replicate_flow_service.py

@@ -381,6 +381,16 @@ async def _soft_delete_steps_from_index(
 
 
 def _step_to_out(step: ModuleGenerationStep) -> ShotReplicateStepOut:
+    error_message = step.error_message
+    if error_message:
+        from app.services.error_codes import ARK_ERRORS
+        import re
+        # 兼容两种格式: code='xxx' 或 'code': 'xxx'
+        match = re.search(r"""code['"]?\s*[:=]\s*['"]([^'"]+)['"]""", error_message)
+        if match:
+            code = match.group(1)
+            if code in ARK_ERRORS:
+                error_message = ARK_ERRORS[code]
     return ShotReplicateStepOut(
         id=step.id,
         project_id=step.project_id,
@@ -395,7 +405,7 @@ def _step_to_out(step: ModuleGenerationStep) -> ShotReplicateStepOut:
         chat_task_id=step.chat_task_id,
         input=_parse_json(step.input_json, {}),
         output=_parse_json(step.output_json, {}),
-        error_message=step.error_message,
+        error_message=error_message,
         created_at=step.created_at,
         updated_at=step.updated_at,
         completed_at=step.completed_at,
@@ -1100,10 +1110,10 @@ async def run_image_prompt_optimize(
             await db.commit()
             return None
         step.status = ModuleStepStatusEnum.FAILED.value
-        step.error_message = str(exc)
+        step.error_message = str(exc) if str(exc) else type(exc).__name__
         step.completed_at = _now()
         project.status = ModuleProjectStatusEnum.FAILED.value
-        project.error_message = f"图片 AI 提词生成失败: {exc}"
+        project.error_message = f"图片 AI 提词生成失败: {str(exc) if str(exc) else type(exc).__name__}"
         log_module_prompt_event(
             event_type="module_prompt_error",
             project_id=project.id,
@@ -1581,10 +1591,10 @@ async def run_video_prompt_optimize(
             await db.commit()
             return None
         step.status = ModuleStepStatusEnum.FAILED.value
-        step.error_message = str(exc)
+        step.error_message = str(exc) if str(exc) else type(exc).__name__
         step.completed_at = _now()
         project.status = ModuleProjectStatusEnum.FAILED.value
-        project.error_message = f"视频 AI 提词生成失败: {exc}"
+        project.error_message = f"视频 AI 提词生成失败: {str(exc) if str(exc) else type(exc).__name__}"
         log_module_prompt_event(
             event_type="module_prompt_error",
             project_id=project.id,

video-gen-api/app/services/shot_replicate_recovery_service.py

@@ -327,7 +327,7 @@ async def recover_shot_analysis_tasks_once(db: AsyncSession) -> dict[str, Any]:
         try:
             if owner_type == "task_set":
                 analyze_original_video.apply_async(
-                    args=[owner_id],
+                    args=[owner_id, attempt],
                     queue=CeleryQueue.GEN_SHOT_ANALYSIS.value,
                     countdown=0,
                     priority=settings.DOWNLOAD_TASK_PRIORITY_RECOVER,
@@ -335,7 +335,7 @@ async def recover_shot_analysis_tasks_once(db: AsyncSession) -> dict[str, Any]:
                 )
             else:
                 analyze_custom_segment_video.apply_async(
-                    args=[owner_id],
+                    args=[owner_id, attempt],
                     queue=CeleryQueue.GEN_SHOT_ANALYSIS.value,
                     countdown=0,
                     priority=settings.DOWNLOAD_TASK_PRIORITY_RECOVER,

video-gen-api/app/services/shot_replicate_taskset_service.py

@@ -54,7 +54,12 @@ from app.schemas.shot_replicate import (
     ShotTaskSetOut,
 )
 from app.services.module_generation_log_service import log_module_event_file
-from app.services.llm_billing import LlmBillingContext, release_on_failure, start_hold
+from app.services.llm_billing import (
+    LlmBillingContext,
+    release_on_failure,
+    start_hold,
+    validate_retryable_previous_attempt,
+)
 from app.services.resource_accounting_service import SOURCE_MODEL_SHOT_SEGMENT, soft_delete_resources_by_source
 from app.enums.upload_resource import UploadResourceModuleEnum, UploadResourceSourceModelEnum
 from app.services.upload_resource import release_upload_resources_by_source
@@ -398,10 +403,15 @@ async def _next_segment_index(db: AsyncSession, task_set_id: str) -> int:
     return int(result.scalar() or 0) + 1
 
 
-async def refresh_task_set_split_summaries(db: AsyncSession, task_set_ids: set[str] | list[str]) -> None:
+async def refresh_task_set_split_summaries(
+    db: AsyncSession,
+    task_set_ids: set[str] | list[str],
+    *,
+    log_changes: bool = True,
+) -> list[dict[str, Any]]:
     ids = sorted({str(item) for item in task_set_ids if item})
     if not ids:
-        return
+        return []
 
     task_set_result = await db.execute(
         select(ShotReplicateTaskSet)
@@ -411,7 +421,11 @@ async def refresh_task_set_split_summaries(db: AsyncSession, task_set_ids: set[s
     )
     task_sets = list(task_set_result.scalars().all())
     if not task_sets:
-        return
+        return []
+
+    # 项目 AsyncSession 关闭了 autoflush。聚合查询前必须把当前事务中刚修改的
+    # segment.split_status/deleted_at 等字段落到数据库，否则最后一个片段会少统计一次。
+    await db.flush()
 
     count_result = await db.execute(
         select(
@@ -441,14 +455,18 @@ async def refresh_task_set_split_summaries(db: AsyncSession, task_set_ids: set[s
         for row in count_result.all()
     }
 
+    changes: list[dict[str, Any]] = []
     for task_set in task_sets:
         total, completed, failed = count_map.get(str(task_set.id), (0, 0, 0))
+        old_status = task_set.status
+        old_split_status = task_set.split_status
+        old_total = int(task_set.segment_count or 0)
+        old_completed = int(task_set.completed_segment_count or 0)
+        old_failed = int(task_set.failed_segment_count or 0)
         task_set.segment_count = total
         task_set.completed_segment_count = completed
         task_set.failed_segment_count = failed
 
-        old_status = task_set.status
-        old_split_status = task_set.split_status
         if total <= 0:
             task_set.split_status = ShotSplitStatusEnum.NONE.value
             if task_set.analysis_status == ShotAnalysisStatusEnum.COMPLETED.value:
@@ -466,24 +484,39 @@ async def refresh_task_set_split_summaries(db: AsyncSession, task_set_ids: set[s
             task_set.split_status = ShotSplitStatusEnum.PROCESSING.value
             task_set.status = ShotTaskSetStatusEnum.SPLITTING.value
 
-        if old_status != task_set.status or old_split_status != task_set.split_status:
+        changed = (
-            log_module_event_file(
+            old_status != task_set.status
-                module=MODULE,
+            or old_split_status != task_set.split_status
-                event_type="SHOT_SPLIT_STATUS_CHANGED",
+            or old_total != total
-                project_id=task_set.id,
+            or old_completed != completed
-                user_id=task_set.user_id,
+            or old_failed != failed
-                message="拆镜总任务集拆分状态变更",
+        )
-                detail={
+        if changed:
-                    "task_set_id": task_set.id,
+            change = {
-                    "from_status": old_status,
+                "task_set_id": str(task_set.id),
-                    "to_status": task_set.status,
+                "user_id": str(task_set.user_id),
-                    "from_split_status": old_split_status,
+                "from_status": old_status,
-                    "to_split_status": task_set.split_status,
+                "to_status": task_set.status,
-                    "segment_count": total,
+                "from_split_status": old_split_status,
-                    "completed_segment_count": completed,
+                "to_split_status": task_set.split_status,
-                    "failed_segment_count": failed,
+                "from_segment_count": old_total,
-                },
+                "segment_count": total,
-            )
+                "from_completed_segment_count": old_completed,
+                "completed_segment_count": completed,
+                "from_failed_segment_count": old_failed,
+                "failed_segment_count": failed,
+            }
+            changes.append(change)
+            if log_changes:
+                log_module_event_file(
+                    module=MODULE,
+                    event_type=ShotReplicateLogEventEnum.SPLIT_STATUS_CHANGED.value,
+                    project_id=task_set.id,
+                    user_id=task_set.user_id,
+                    message="拆镜总任务集拆分状态变更",
+                    detail=change,
+                )
+    return changes
 
 
 async def refresh_task_set_split_summary(db: AsyncSession, task_set_id: str) -> None:
@@ -511,20 +544,20 @@ async def create_segments_by_ai(
         if not suggestions:
             raise HTTPException(status_code=400, detail="selected_indices 没有匹配到可用 AI 建议")
 
-    old_result = await db.execute(
+    # old_result = await db.execute(
-        select(ShotReplicateSegment).where(
+    #     select(ShotReplicateSegment).where(
-            ShotReplicateSegment.task_set_id == task_set.id,
+    #         ShotReplicateSegment.task_set_id == task_set.id,
-            ShotReplicateSegment.source_mode == ShotSegmentSourceModeEnum.AI_SUGGESTION.value,
+    #         ShotReplicateSegment.source_mode == ShotSegmentSourceModeEnum.AI_SUGGESTION.value,
-            ShotReplicateSegment.deleted_at.is_(None),
+    #         ShotReplicateSegment.deleted_at.is_(None),
-        )
+    #     )
-    )
+    # )
-    old_segments = list(old_result.scalars().all())
+    # old_segments = list(old_result.scalars().all())
-    if old_segments and not req.replace_existing:
+    # if old_segments and not req.replace_existing:
-        raise HTTPException(status_code=409, detail="已存在 AI 建议拆镜片段，如需重拆请传 replace_existing=true")
+    #     raise HTTPException(status_code=409, detail="已存在 AI 建议拆镜片段，如需重拆请传 replace_existing=true")
-    if old_segments and req.replace_existing:
+    # if old_segments and req.replace_existing:
-        now = _now()
+    #     now = _now()
-        for segment in old_segments:
+    #     for segment in old_segments:
-            segment.deleted_at = now
+    #         segment.deleted_at = now
 
     created: list[ShotReplicateSegment] = []
     next_index = await _next_segment_index(db, task_set.id)
@@ -576,7 +609,7 @@ async def create_segments_by_ai(
         detail={
             "task_set_id": task_set.id,
             "selected_indices": req.selected_indices,
-            "replace_existing": req.replace_existing,
+            # "replace_existing": req.replace_existing,
             "created_segment_count": len(created),
             "segment_ids": [segment.id for segment in created],
         },
@@ -1100,39 +1133,60 @@ async def prepare_reanalyze_task_set(
     *,
     current_user: User,
     task_set_id: str,
-    force: bool = False,
     reason: str | None = None,
 ) -> ShotReanalyzeOut:
-    """重置原视频分析状态，供 API 重新投递 Celery。"""
+    """仅对已失败且旧账务已关闭的原视频分析创建新 attempt。"""
     task_set = await get_task_set_for_user(db, task_set_id=task_set_id, user=current_user, for_update=True)
-    if task_set.analysis_status == ShotAnalysisStatusEnum.PROCESSING.value:
+    previous_attempt_no = max(1, int(task_set.analysis_attempt_no or 1))
+    if task_set.analysis_status != ShotAnalysisStatusEnum.FAILED.value:
         log_module_event_file(
             module=MODULE,
             event_type=ShotReplicateLogEventEnum.TASK_SET_REANALYZE_REJECTED.value,
             project_id=task_set.id,
             user_id=task_set.user_id,
-            message="原视频分析正在处理中，拒绝再次分析",
+            message="原视频分析不是失败终态，拒绝再次分析",
-            detail={"task_set_id": task_set.id, "analysis_status": task_set.analysis_status, "reason": reason},
+            detail={
+                "task_set_id": task_set.id,
+                "analysis_status": task_set.analysis_status,
+                "analysis_attempt_no": previous_attempt_no,
+                "reason": reason,
+            },
             event_status="rejected",
         )
-        raise HTTPException(status_code=409, detail="原视频分析正在处理中，不能重复投递")
+        raise HTTPException(
-    if task_set.analysis_status == ShotAnalysisStatusEnum.COMPLETED.value and not force:
+            status_code=409,
-        raise HTTPException(status_code=409, detail="原视频分析已完成，如确需重跑请传 force=true")
+            detail=f"只有分析失败的原视频任务才能重新分析，当前状态：{task_set.analysis_status}",
-    if force:
+        )
-        active_segments_result = await db.execute(
+
-            select(func.count())
+    previous_context = build_task_set_analysis_billing_context(task_set)
-            .select_from(ShotReplicateSegment)
+    previous_validation = await validate_retryable_previous_attempt(db, previous_context)
-            .where(
+    if not previous_validation.can_execute:
-                ShotReplicateSegment.task_set_id == task_set.id,
+        log_module_event_file(
-                ShotReplicateSegment.deleted_at.is_(None),
+            module=MODULE,
-            )
+            event_type=ShotReplicateLogEventEnum.TASK_SET_REANALYZE_REJECTED.value,
+            project_id=task_set.id,
+            user_id=task_set.user_id,
+            message="原视频旧分析 attempt 账务未关闭，拒绝再次分析",
+            detail={
+                "task_set_id": task_set.id,
+                "analysis_attempt_no": previous_attempt_no,
+                "ledger_state": previous_validation.state.value,
+                "ledger_reason": previous_validation.reason,
+                "reason": reason,
+            },
+            event_status="rejected",
+        )
+        raise HTTPException(
+            status_code=409,
+            detail=(
+                "上一次原视频分析的冻结积分尚未完成释放或账务状态异常，"
+                f"当前账务状态：{previous_validation.state.value}"
+            ),
         )
-        if int(active_segments_result.scalar() or 0) > 0:
-            raise HTTPException(status_code=409, detail="当前总任务集已存在拆镜片段，不能强制重跑原视频分析")
 
     task_set.status = ShotTaskSetStatusEnum.PENDING_ANALYSIS.value
     task_set.analysis_status = ShotAnalysisStatusEnum.PENDING.value
-    task_set.analysis_attempt_no = max(1, int(task_set.analysis_attempt_no or 1)) + 1
+    task_set.analysis_attempt_no = previous_attempt_no + 1
     task_set.analysis_claim_token = None
     task_set.analysis_started_at = None
     task_set.analysis_lease_until = None
@@ -1151,7 +1205,14 @@ async def prepare_reanalyze_task_set(
         project_id=task_set.id,
         user_id=task_set.user_id,
         message="原视频再次分析已重置状态",
-        detail={"task_set_id": task_set.id, "force": force, "reason": reason, "video_url": task_set.video_url},
+        detail={
+            "task_set_id": task_set.id,
+            "previous_analysis_attempt_no": previous_attempt_no,
+            "analysis_attempt_no": int(task_set.analysis_attempt_no),
+            "previous_ledger_state": previous_validation.state.value,
+            "reason": reason,
+            "video_url": task_set.video_url,
+        },
     )
     return ShotReanalyzeOut(
         message="原视频再次分析任务已准备投递",
@@ -1168,34 +1229,69 @@ async def prepare_reanalyze_segment(
     *,
     current_user: User,
     segment_id: str,
-    force: bool = False,
     reason: str | None = None,
 ) -> ShotReanalyzeOut:
-    """重置自定义切片视频分析状态，供 API 重新投递 Celery。"""
+    """仅对已失败且旧账务已关闭的自定义切片分析创建新 attempt。"""
     segment = await get_segment_for_user(db, segment_id=segment_id, user=current_user, for_update=True)
     if segment.split_status != ShotSplitStatusEnum.COMPLETED.value:
         raise HTTPException(status_code=409, detail="当前片段还未切割完成，不能再次分析")
     if not segment.segment_video_url:
         raise HTTPException(status_code=409, detail="当前片段缺少 segment_video_url，不能再次分析")
-    if segment.analysis_status == ShotSegmentAnalysisStatusEnum.PROCESSING.value:
+    if segment.source_mode != ShotSegmentSourceModeEnum.CUSTOM.value:
+        raise HTTPException(status_code=409, detail="只有自定义切片视频支持重新分析")
+
+    previous_attempt_no = max(1, int(segment.analysis_attempt_no or 1))
+    if segment.analysis_status != ShotSegmentAnalysisStatusEnum.FAILED.value:
         log_module_event_file(
             module=MODULE,
             event_type=ShotReplicateLogEventEnum.SEGMENT_REANALYZE_REJECTED.value,
             project_id=segment.task_set_id,
             step_id=segment.id,
             user_id=segment.user_id,
-            message="切片视频分析正在处理中，拒绝再次分析",
+            message="切片视频分析不是失败终态，拒绝再次分析",
-            detail={"segment_id": segment.id, "analysis_status": segment.analysis_status, "reason": reason},
+            detail={
+                "segment_id": segment.id,
+                "analysis_status": segment.analysis_status,
+                "analysis_attempt_no": previous_attempt_no,
+                "reason": reason,
+            },
             event_status="rejected",
         )
-        raise HTTPException(status_code=409, detail="切片视频分析正在处理中，不能重复投递")
+        raise HTTPException(
-    if segment.analysis_status == ShotSegmentAnalysisStatusEnum.COMPLETED.value and not force:
+            status_code=409,
-        raise HTTPException(status_code=409, detail="切片视频分析已完成，如确需重跑请传 force=true")
+            detail=f"只有分析失败的切片视频才能重新分析，当前状态：{segment.analysis_status}",
-    if segment.source_mode != ShotSegmentSourceModeEnum.CUSTOM.value and not force:
+        )
-        raise HTTPException(status_code=409, detail="AI 建议片段默认无需单独分析，如确需重跑请传 force=true")
+
+    previous_context = build_segment_analysis_billing_context(segment)
+    previous_validation = await validate_retryable_previous_attempt(db, previous_context)
+    if not previous_validation.can_execute:
+        log_module_event_file(
+            module=MODULE,
+            event_type=ShotReplicateLogEventEnum.SEGMENT_REANALYZE_REJECTED.value,
+            project_id=segment.task_set_id,
+            step_id=segment.id,
+            user_id=segment.user_id,
+            message="切片视频旧分析 attempt 账务未关闭，拒绝再次分析",
+            detail={
+                "segment_id": segment.id,
+                "task_set_id": segment.task_set_id,
+                "analysis_attempt_no": previous_attempt_no,
+                "ledger_state": previous_validation.state.value,
+                "ledger_reason": previous_validation.reason,
+                "reason": reason,
+            },
+            event_status="rejected",
+        )
+        raise HTTPException(
+            status_code=409,
+            detail=(
+                "上一次切片视频分析的冻结积分尚未完成释放或账务状态异常，"
+                f"当前账务状态：{previous_validation.state.value}"
+            ),
+        )
 
     segment.analysis_status = ShotSegmentAnalysisStatusEnum.PENDING.value
-    segment.analysis_attempt_no = max(1, int(segment.analysis_attempt_no or 1)) + 1
+    segment.analysis_attempt_no = previous_attempt_no + 1
     segment.analysis_claim_token = None
     segment.analysis_started_at = None
     segment.analysis_lease_until = None
@@ -1216,7 +1312,15 @@ async def prepare_reanalyze_segment(
         step_id=segment.id,
         user_id=segment.user_id,
         message="切片视频再次分析已重置状态",
-        detail={"segment_id": segment.id, "task_set_id": segment.task_set_id, "force": force, "reason": reason, "video_url": segment.segment_video_url},
+        detail={
+            "segment_id": segment.id,
+            "task_set_id": segment.task_set_id,
+            "previous_analysis_attempt_no": previous_attempt_no,
+            "analysis_attempt_no": int(segment.analysis_attempt_no),
+            "previous_ledger_state": previous_validation.state.value,
+            "reason": reason,
+            "video_url": segment.segment_video_url,
+        },
     )
     return ShotReanalyzeOut(
         message="切片视频再次分析任务已准备投递",
@@ -1233,9 +1337,12 @@ async def mark_task_set_analysis_dispatch_failed(
     *,
     current_user: User,
     task_set_id: str,
+    expected_attempt_no: int,
     error_message: str,
 ) -> bool:
     task_set = await get_task_set_for_user(db, task_set_id=task_set_id, user=current_user, for_update=True)
+    if int(task_set.analysis_attempt_no or 1) != int(expected_attempt_no):
+        return False
     if (
         task_set.analysis_status == ShotAnalysisStatusEnum.PROCESSING.value
         and task_set.analysis_claim_token
@@ -1245,12 +1352,11 @@ async def mark_task_set_analysis_dispatch_failed(
         return False
     if task_set.analysis_status in (ShotAnalysisStatusEnum.COMPLETED.value, ShotAnalysisStatusEnum.FAILED.value):
         return False
-    if task_set.analysis_status not in (ShotAnalysisStatusEnum.COMPLETED.value, ShotAnalysisStatusEnum.FAILED.value):
+    task_set.status = ShotTaskSetStatusEnum.ANALYSIS_FAILED.value
-        task_set.status = ShotTaskSetStatusEnum.ANALYSIS_FAILED.value
+    task_set.analysis_status = ShotAnalysisStatusEnum.FAILED.value
-        task_set.analysis_status = ShotAnalysisStatusEnum.FAILED.value
+    task_set.analysis_claim_token = None
-        task_set.analysis_claim_token = None
+    task_set.analysis_lease_until = None
-        task_set.analysis_lease_until = None
+    task_set.analysis_error_message = error_message
-        task_set.analysis_error_message = error_message
     await release_on_failure(db, build_task_set_analysis_billing_context(task_set), error=error_message)
     log_module_event_file(
         module=MODULE,
@@ -1269,9 +1375,12 @@ async def mark_segment_analysis_dispatch_failed(
     *,
     current_user: User,
     segment_id: str,
+    expected_attempt_no: int,
     error_message: str,
 ) -> bool:
     segment = await get_segment_for_user(db, segment_id=segment_id, user=current_user, for_update=True)
+    if int(segment.analysis_attempt_no or 1) != int(expected_attempt_no):
+        return False
     if (
         segment.analysis_status == ShotSegmentAnalysisStatusEnum.PROCESSING.value
         and segment.analysis_claim_token
@@ -1281,11 +1390,10 @@ async def mark_segment_analysis_dispatch_failed(
         return False
     if segment.analysis_status in (ShotSegmentAnalysisStatusEnum.COMPLETED.value, ShotSegmentAnalysisStatusEnum.FAILED.value):
         return False
-    if segment.analysis_status not in (ShotSegmentAnalysisStatusEnum.COMPLETED.value, ShotSegmentAnalysisStatusEnum.FAILED.value):
+    segment.analysis_status = ShotSegmentAnalysisStatusEnum.FAILED.value
-        segment.analysis_status = ShotSegmentAnalysisStatusEnum.FAILED.value
+    segment.analysis_claim_token = None
-        segment.analysis_claim_token = None
+    segment.analysis_lease_until = None
-        segment.analysis_lease_until = None
+    segment.analysis_error_message = error_message
-        segment.analysis_error_message = error_message
     await release_on_failure(db, build_segment_analysis_billing_context(segment), error=error_message)
     log_module_event_file(
         module=MODULE,

video-gen-api/app/services/shot_video_analysis_service.py

@@ -756,7 +756,12 @@ async def analyze_video_for_shot_split(
     result = ensure_result_schema(result)
     result = filter_and_normalize_breakdown(result, mode=mode)
 
-    usage = raw.get("usage") or {}
+    raw_usage = raw.get("usage")
+    usage_reported = bool(
+        isinstance(raw_usage, dict)
+        and any(key in raw_usage for key in ("prompt_tokens", "completion_tokens", "input_tokens", "output_tokens", "total_tokens"))
+    )
+    usage = raw_usage if isinstance(raw_usage, dict) else {}
     token_usage = {
         "input_tokens": _int_usage(usage.get("prompt_tokens") or usage.get("input_tokens")),
         "output_tokens": _int_usage(usage.get("completion_tokens") or usage.get("output_tokens")),
@@ -771,6 +776,7 @@ async def analyze_video_for_shot_split(
         "split_max_seconds": _split_max_seconds(),
         "analysis_mode": mode,
         "trace_id": trace_id,
+        "usage_reported": usage_reported,
     }
     if not token_usage["total_tokens"]:
         token_usage["total_tokens"] = token_usage["input_tokens"] + token_usage["output_tokens"]

video-gen-api/app/tasks/shot_replicate_tasks.py

@@ -33,7 +33,10 @@ from app.services.redis_registry_service import (
 )
 from app.services.celery_runtime.recovery_service import guard_periodic_recovery
 from app.services.celery_runtime.runtime_service import CeleryRuntimeLease, RuntimeIdentity
-from app.services.shot_replicate_taskset_service import refresh_task_set_split_summary
+from app.services.shot_replicate_taskset_service import (
+    build_segment_analysis_billing_context,
+    refresh_task_set_split_summary,
+)
 from app.services.shot_video_analysis_service import analyze_video_for_shot_split
 from app.services.llm_billing import (
     LlmBillingContext,
@@ -126,9 +129,237 @@ def _analysis_lock_key(owner_type: str, owner_id: str, attempt_no: int) -> str:
     return f"{settings.SHOT_ANALYSIS_LOCK_KEY_PREFIX}:{owner_type}:{owner_id}:attempt:{attempt_no}"
 
 
-async def _run_analyze_original_video(task_set_id: str) -> None:
+def _log_stale_analysis_attempt(
+    *,
+    owner_type: str,
+    owner_id: str,
+    expected_attempt_no: int | None,
+    actual_attempt_no: int | None,
+    analysis_status: str | None,
+    task_set_id: str | None = None,
+    user_id: str | None = None,
+    reason: str,
+) -> None:
+    project_id = task_set_id or (owner_id if owner_type == "shot_task_set" else None)
+    log_module_event_file(
+        module=MODULE,
+        event_type=ShotReplicateLogEventEnum.ANALYSIS_STALE_ATTEMPT_SKIPPED.value,
+        project_id=project_id,
+        step_id=owner_id if owner_type == "shot_segment" else None,
+        user_id=user_id,
+        message="拆镜分析任务 attempt 已失效，跳过执行",
+        detail={
+            "owner_type": owner_type,
+            "owner_id": owner_id,
+            "expected_attempt_no": expected_attempt_no,
+            "actual_attempt_no": actual_attempt_no,
+            "analysis_status": analysis_status,
+            "reason": reason,
+        },
+        event_status="skipped",
+    )
+
+
+async def _persist_original_analysis_result(
+    *,
+    task_set_id: str,
+    attempt_no: int,
+    token: str,
+    video_url: str | None,
+    analyzed: Any,
+    billing_context: LlmBillingContext,
+    allow_business_write: bool,
+) -> str:
+    """持久化原视频分析结果并完成账务；供应商成功后禁止再次调用模型。"""
+    async with async_session() as db:
+        result = await db.execute(
+            select(ShotReplicateTaskSet)
+            .where(
+                ShotReplicateTaskSet.id == task_set_id,
+                ShotReplicateTaskSet.deleted_at.is_(None),
+            )
+            .with_for_update()
+            .limit(1)
+        )
+        task_set = result.scalar_one_or_none()
+        is_current = bool(
+            allow_business_write
+            and task_set
+            and int(task_set.analysis_attempt_no or 1) == attempt_no
+            and task_set.analysis_claim_token == token
+            and str(task_set.video_url) == str(video_url)
+            and task_set.analysis_status == ShotAnalysisStatusEnum.PROCESSING.value
+        )
+        if is_current and task_set is not None:
+            result_json = analyzed.result
+            task_set.original_video_content = str(result_json.get("原视频内容") or "无")
+            task_set.original_video_category = str(result_json.get("原视频分类") or "无")
+            task_set.original_video_audience = str(result_json.get("原视频受众人群") or "无")
+            task_set.ai_suggestion_json = result_json.get("拆镜内容剖析") or []
+            task_set.analysis_raw_json = analyzed.raw_response
+            task_set.analysis_result_json = result_json
+            task_set.analysis_status = ShotAnalysisStatusEnum.COMPLETED.value
+            task_set.status = ShotTaskSetStatusEnum.ANALYSIS_COMPLETED.value
+            task_set.analysis_claim_token = None
+            task_set.analysis_lease_until = None
+            task_set.analysis_error_message = None
+            description = "拆镜复刻-原视频分析"
+            outcome = "completed"
+        else:
+            description = "拆镜复刻-原视频分析（失效结果结算）"
+            outcome = "stale_settled"
+        await settle_success(
+            db,
+            billing_context,
+            usage=analyzed.usage,
+            description=description,
+        )
+        await db.commit()
+        return outcome
+
+
+async def _persist_segment_analysis_result(
+    *,
+    segment_id: str,
+    attempt_no: int,
+    token: str,
+    video_url: str | None,
+    analyzed: Any,
+    billing_context: LlmBillingContext,
+    allow_business_write: bool,
+) -> str:
+    """持久化自定义切片分析结果并完成账务；供应商成功后禁止再次调用模型。"""
+    async with async_session() as db:
+        result = await db.execute(
+            select(ShotReplicateSegment)
+            .where(
+                ShotReplicateSegment.id == segment_id,
+                ShotReplicateSegment.deleted_at.is_(None),
+            )
+            .with_for_update()
+            .limit(1)
+        )
+        segment = result.scalar_one_or_none()
+        is_current = bool(
+            allow_business_write
+            and segment
+            and int(segment.analysis_attempt_no or 1) == attempt_no
+            and segment.analysis_claim_token == token
+            and str(segment.segment_video_url) == str(video_url)
+            and segment.analysis_status == ShotSegmentAnalysisStatusEnum.PROCESSING.value
+        )
+        if is_current and segment is not None:
+            result_json = analyzed.result
+            segment.original_video_content = str(result_json.get("原视频内容") or "无")
+            segment.original_video_category = str(result_json.get("原视频分类") or "无")
+            segment.original_video_audience = str(result_json.get("原视频受众人群") or "无")
+            segment.segment_content = segment.original_video_content
+            segment.segment_category = segment.original_video_category
+            segment.segment_audience = segment.original_video_audience
+            segment.analysis_json = result_json
+            segment.analysis_status = ShotSegmentAnalysisStatusEnum.COMPLETED.value
+            segment.analysis_claim_token = None
+            segment.analysis_lease_until = None
+            segment.analysis_error_message = None
+            description = "拆镜复刻-片段视频分析"
+            outcome = "completed"
+        else:
+            description = "拆镜复刻-片段视频分析（失效结果结算）"
+            outcome = "stale_settled"
+        await settle_success(
+            db,
+            billing_context,
+            usage=analyzed.usage,
+            description=description,
+        )
+        await db.commit()
+        return outcome
+
+
+async def _mark_original_provider_success_pending_manual(
+    *,
+    task_set_id: str,
+    attempt_no: int,
+    token: str,
+    error_message: str,
+) -> bool:
+    """供应商已成功但本地结算失败：终止自动恢复，保留 HOLD 等待人工对账。"""
+    async with async_session() as db:
+        result = await db.execute(
+            select(ShotReplicateTaskSet)
+            .where(
+                ShotReplicateTaskSet.id == task_set_id,
+                ShotReplicateTaskSet.deleted_at.is_(None),
+            )
+            .with_for_update()
+            .limit(1)
+        )
+        task_set = result.scalar_one_or_none()
+        if not (
+            task_set
+            and int(task_set.analysis_attempt_no or 1) == attempt_no
+            and task_set.analysis_claim_token == token
+            and task_set.analysis_status == ShotAnalysisStatusEnum.PROCESSING.value
+        ):
+            await db.rollback()
+            return False
+        task_set.status = ShotTaskSetStatusEnum.ANALYSIS_FAILED.value
+        task_set.analysis_status = ShotAnalysisStatusEnum.FAILED.value
+        task_set.analysis_claim_token = None
+        task_set.analysis_lease_until = None
+        task_set.analysis_error_message = error_message
+        await db.commit()
+        return True
+
+
+async def _mark_segment_provider_success_pending_manual(
+    *,
+    segment_id: str,
+    attempt_no: int,
+    token: str,
+    error_message: str,
+) -> bool:
+    """供应商已成功但本地结算失败：终止自动恢复，保留 HOLD 等待人工对账。"""
+    async with async_session() as db:
+        result = await db.execute(
+            select(ShotReplicateSegment)
+            .where(
+                ShotReplicateSegment.id == segment_id,
+                ShotReplicateSegment.deleted_at.is_(None),
+            )
+            .with_for_update()
+            .limit(1)
+        )
+        segment = result.scalar_one_or_none()
+        if not (
+            segment
+            and int(segment.analysis_attempt_no or 1) == attempt_no
+            and segment.analysis_claim_token == token
+            and segment.analysis_status == ShotSegmentAnalysisStatusEnum.PROCESSING.value
+        ):
+            await db.rollback()
+            return False
+        segment.analysis_status = ShotSegmentAnalysisStatusEnum.FAILED.value
+        segment.analysis_claim_token = None
+        segment.analysis_lease_until = None
+        segment.analysis_error_message = error_message
+        await db.commit()
+        return True
+
+
+async def _run_analyze_original_video(task_set_id: str, expected_attempt_no: int | None) -> None:
     token = uuid.uuid4().hex
-    attempt_no = 1
+    if expected_attempt_no is None:
+        _log_stale_analysis_attempt(
+            owner_type="shot_task_set",
+            owner_id=task_set_id,
+            expected_attempt_no=None,
+            actual_attempt_no=None,
+            analysis_status=None,
+            reason="missing_expected_attempt_no",
+        )
+        return
+    attempt_no = max(1, int(expected_attempt_no))
 
     async with async_session() as db:
         row = await db.execute(
@@ -137,9 +368,25 @@ async def _run_analyze_original_video(task_set_id: str) -> None:
             .limit(1)
         )
         initial = row.scalar_one_or_none()
-        if not initial or initial.analysis_status == ShotAnalysisStatusEnum.COMPLETED.value:
+        if not initial:
+            return
+        actual_attempt_no = int(initial.analysis_attempt_no or 1)
+        if (
+            actual_attempt_no != attempt_no
+            or initial.analysis_status
+            not in (ShotAnalysisStatusEnum.PENDING.value, ShotAnalysisStatusEnum.PROCESSING.value)
+        ):
+            _log_stale_analysis_attempt(
+                owner_type="shot_task_set",
+                owner_id=task_set_id,
+                expected_attempt_no=attempt_no,
+                actual_attempt_no=actual_attempt_no,
+                analysis_status=initial.analysis_status,
+                user_id=str(initial.user_id),
+                reason="attempt_or_status_mismatch_before_lock",
+            )
+            await db.rollback()
             return
-        attempt_no = int(initial.analysis_attempt_no or 1)
         await db.rollback()
 
     lease = await CeleryRuntimeLease.acquire(
@@ -174,7 +421,24 @@ async def _run_analyze_original_video(task_set_id: str) -> None:
                 .limit(1)
             )
             task_set = result.scalar_one_or_none()
-            if not task_set or task_set.analysis_status == ShotAnalysisStatusEnum.COMPLETED.value:
+            if not task_set:
+                await db.rollback()
+                return
+            actual_attempt_no = int(task_set.analysis_attempt_no or 1)
+            if (
+                actual_attempt_no != attempt_no
+                or task_set.analysis_status
+                not in (ShotAnalysisStatusEnum.PENDING.value, ShotAnalysisStatusEnum.PROCESSING.value)
+            ):
+                _log_stale_analysis_attempt(
+                    owner_type="shot_task_set",
+                    owner_id=task_set_id,
+                    expected_attempt_no=attempt_no,
+                    actual_attempt_no=actual_attempt_no,
+                    analysis_status=task_set.analysis_status,
+                    user_id=str(task_set.user_id),
+                    reason="attempt_or_status_mismatch_after_lock",
+                )
                 await db.rollback()
                 return
             current_lease = task_set.analysis_lease_until
@@ -186,9 +450,6 @@ async def _run_analyze_original_video(task_set_id: str) -> None:
             ):
                 await db.rollback()
                 return
-            if int(task_set.analysis_attempt_no or 1) != attempt_no:
-                await db.rollback()
-                return
             task_set_user_id = str(task_set.user_id)
             video_url = str(task_set.video_url)
             task_set.status = ShotTaskSetStatusEnum.ANALYZING.value
@@ -263,52 +524,25 @@ async def _run_analyze_original_video(task_set_id: str) -> None:
                 task_set_id=task_set_id,
                 trace_id=f"shot-task-set-analysis:{task_set_id}:attempt:{attempt_no}",
             )
-            provider_succeeded = True
+        provider_succeeded = True
-            log_provider_success(llm_billing_context, usage=analyzed.usage)
+        log_provider_success(llm_billing_context, usage=analyzed.usage)
+        try:
             await lease.ensure_owned()
-            result = await call_db.execute(
+            allow_business_write = True
-                select(ShotReplicateTaskSet)
+        except RedisExecutionLockError:
-                .where(ShotReplicateTaskSet.id == task_set_id, ShotReplicateTaskSet.deleted_at.is_(None))
+            # Provider 已成功后不能让 Celery retry 再次调用模型；失去执行权时仅结算。
-                .with_for_update()
+            allow_business_write = False
-                .limit(1)
+        persist_outcome = await _persist_original_analysis_result(
-            )
+            task_set_id=task_set_id,
-            task_set = result.scalar_one_or_none()
+            attempt_no=attempt_no,
-            if (
+            token=token,
-                not task_set
+            video_url=video_url,
-                or int(task_set.analysis_attempt_no or 1) != attempt_no
+            analyzed=analyzed,
-                or task_set.analysis_claim_token != token
+            billing_context=llm_billing_context,
-                or str(task_set.video_url) != str(video_url)
+            allow_business_write=allow_business_write,
-                or task_set.analysis_status != ShotAnalysisStatusEnum.PROCESSING.value
+        )
-            ):
+        if persist_outcome != "completed":
-                await call_db.rollback()
+            return
-                # Provider 已成功，旧业务对象失效也必须按真实 usage 结算。
-                await settle_success(
-                    call_db,
-                    llm_billing_context,
-                    usage=analyzed.usage,
-                    description="拆镜复刻-原视频分析（失效结果结算）",
-                )
-                await call_db.commit()
-                return
-            result_json = analyzed.result
-            task_set.original_video_content = str(result_json.get("原视频内容") or "无")
-            task_set.original_video_category = str(result_json.get("原视频分类") or "无")
-            task_set.original_video_audience = str(result_json.get("原视频受众人群") or "无")
-            task_set.ai_suggestion_json = result_json.get("拆镜内容剖析") or []
-            task_set.analysis_raw_json = analyzed.raw_response
-            task_set.analysis_result_json = result_json
-            task_set.analysis_status = ShotAnalysisStatusEnum.COMPLETED.value
-            task_set.status = ShotTaskSetStatusEnum.ANALYSIS_COMPLETED.value
-            task_set.analysis_claim_token = None
-            task_set.analysis_lease_until = None
-            task_set.analysis_error_message = None
-            await settle_success(
-                call_db,
-                llm_billing_context,
-                usage=analyzed.usage,
-                description="拆镜复刻-原视频分析",
-            )
-            await call_db.commit()
 
         log_module_prompt_event(
             event_type=ShotReplicateLogEventEnum.ANALYSIS_SUCCESS.value,
@@ -334,40 +568,67 @@ async def _run_analyze_original_video(task_set_id: str) -> None:
     except Exception as exc:
         if "llm_billing_context" in locals() and not locals().get("provider_succeeded", False):
             log_provider_failure(llm_billing_context, error=str(exc))
-        async with async_session() as db:
+        if "llm_billing_context" in locals() and locals().get("provider_succeeded", False) and locals().get("analyzed") is not None:
-            result = await db.execute(
+            try:
-                select(ShotReplicateTaskSet)
+                try:
-                .where(ShotReplicateTaskSet.id == task_set_id, ShotReplicateTaskSet.deleted_at.is_(None))
+                    await lease.ensure_owned()
-                .with_for_update()
+                    allow_business_write = True
-                .limit(1)
+                except RedisExecutionLockError:
-            )
+                    allow_business_write = False
-            task_set = result.scalar_one_or_none()
+                persist_outcome = await _persist_original_analysis_result(
-            task_set_is_current = bool(
+                    task_set_id=task_set_id,
-                task_set
+                    attempt_no=attempt_no,
-                and int(task_set.analysis_attempt_no or 1) == attempt_no
+                    token=token,
-                and task_set.analysis_claim_token == token
+                    video_url=video_url,
-                and task_set.analysis_status == ShotAnalysisStatusEnum.PROCESSING.value
+                    analyzed=analyzed,
-            )
+                    billing_context=llm_billing_context,
-            if task_set_is_current and task_set is not None:
+                    allow_business_write=allow_business_write,
-                task_set_user_id = task_set_user_id or str(task_set.user_id)
+                )
-                task_set.status = ShotTaskSetStatusEnum.ANALYSIS_FAILED.value
+                if persist_outcome == "completed":
-                task_set.analysis_status = ShotAnalysisStatusEnum.FAILED.value
+                    log_module_event_file(
-                task_set.analysis_claim_token = None
+                        module=MODULE,
-                task_set.analysis_lease_until = None
+                        event_type=ShotReplicateLogEventEnum.ANALYSIS_SUCCESS.value,
-                task_set.analysis_error_message = str(exc)
+                        project_id=task_set_id,
-            # 业务对象是否仍有效，不影响本 attempt 的账务终态：provider 已成功必须结算，
+                        user_id=task_set_user_id,
-            # provider 未成功则幂等释放。这样人工删库/异常换 attempt 也不会遗留 active HOLD。
+                        message="原视频分析本地异常后幂等恢复成功",
-            if "llm_billing_context" in locals():
+                        detail={"task_set_id": task_set_id, "analysis_attempt_no": attempt_no},
-                if locals().get("provider_succeeded", False) and locals().get("analyzed") is not None:
-                    await settle_success(
-                        db,
-                        llm_billing_context,
-                        usage=analyzed.usage,
-                        description="拆镜复刻-原视频分析（本地失败结算）",
                     )
-                else:
+                return
-                    await release_on_failure(db, llm_billing_context, error=str(exc))
+            except Exception as settlement_exc:
-            await db.commit()
+                manual_error = (
+                    "供应商已成功，但本地结果保存或积分结算失败；已终止自动恢复并保留冻结积分，"
+                    f"需人工对账。error={settlement_exc}"
+                )
+                await _mark_original_provider_success_pending_manual(
+                    task_set_id=task_set_id,
+                    attempt_no=attempt_no,
+                    token=token,
+                    error_message=manual_error,
+                )
+                exc = settlement_exc
+        elif "llm_billing_context" in locals():
+            async with async_session() as db:
+                result = await db.execute(
+                    select(ShotReplicateTaskSet)
+                    .where(ShotReplicateTaskSet.id == task_set_id, ShotReplicateTaskSet.deleted_at.is_(None))
+                    .with_for_update()
+                    .limit(1)
+                )
+                task_set = result.scalar_one_or_none()
+                if (
+                    task_set
+                    and int(task_set.analysis_attempt_no or 1) == attempt_no
+                    and task_set.analysis_claim_token == token
+                    and task_set.analysis_status == ShotAnalysisStatusEnum.PROCESSING.value
+                ):
+                    task_set_user_id = task_set_user_id or str(task_set.user_id)
+                    task_set.status = ShotTaskSetStatusEnum.ANALYSIS_FAILED.value
+                    task_set.analysis_status = ShotAnalysisStatusEnum.FAILED.value
+                    task_set.analysis_claim_token = None
+                    task_set.analysis_lease_until = None
+                    task_set.analysis_error_message = str(exc)
+                await release_on_failure(db, llm_billing_context, error=str(exc))
+                await db.commit()
         log_module_error(
             module=MODULE,
             event_type=ShotReplicateLogEventEnum.ANALYSIS_FAILED.value,
@@ -381,9 +642,19 @@ async def _run_analyze_original_video(task_set_id: str) -> None:
         await lease.close()
 
 
-async def _run_analyze_custom_segment_video(segment_id: str) -> None:
+async def _run_analyze_custom_segment_video(segment_id: str, expected_attempt_no: int | None) -> None:
     token = uuid.uuid4().hex
-    attempt_no = 1
+    if expected_attempt_no is None:
+        _log_stale_analysis_attempt(
+            owner_type="shot_segment",
+            owner_id=segment_id,
+            expected_attempt_no=None,
+            actual_attempt_no=None,
+            analysis_status=None,
+            reason="missing_expected_attempt_no",
+        )
+        return
+    attempt_no = max(1, int(expected_attempt_no))
     async with async_session() as db:
         row = await db.execute(
             select(ShotReplicateSegment)
@@ -391,9 +662,26 @@ async def _run_analyze_custom_segment_video(segment_id: str) -> None:
             .limit(1)
         )
         initial = row.scalar_one_or_none()
-        if not initial or not initial.segment_video_url or initial.analysis_status == ShotSegmentAnalysisStatusEnum.COMPLETED.value:
+        if not initial or not initial.segment_video_url:
+            return
+        actual_attempt_no = int(initial.analysis_attempt_no or 1)
+        if (
+            actual_attempt_no != attempt_no
+            or initial.analysis_status
+            not in (ShotSegmentAnalysisStatusEnum.PENDING.value, ShotSegmentAnalysisStatusEnum.PROCESSING.value)
+        ):
+            _log_stale_analysis_attempt(
+                owner_type="shot_segment",
+                owner_id=segment_id,
+                expected_attempt_no=attempt_no,
+                actual_attempt_no=actual_attempt_no,
+                analysis_status=initial.analysis_status,
+                task_set_id=str(initial.task_set_id),
+                user_id=str(initial.user_id),
+                reason="attempt_or_status_mismatch_before_lock",
+            )
+            await db.rollback()
             return
-        attempt_no = int(initial.analysis_attempt_no or 1)
         await db.rollback()
 
     lease = await CeleryRuntimeLease.acquire(
@@ -429,16 +717,31 @@ async def _run_analyze_custom_segment_video(segment_id: str) -> None:
                 .limit(1)
             )
             segment = result.scalar_one_or_none()
-            if not segment or not segment.segment_video_url or segment.analysis_status == ShotSegmentAnalysisStatusEnum.COMPLETED.value:
+            if not segment or not segment.segment_video_url:
+                await db.rollback()
+                return
+            actual_attempt_no = int(segment.analysis_attempt_no or 1)
+            if (
+                actual_attempt_no != attempt_no
+                or segment.analysis_status
+                not in (ShotSegmentAnalysisStatusEnum.PENDING.value, ShotSegmentAnalysisStatusEnum.PROCESSING.value)
+            ):
+                _log_stale_analysis_attempt(
+                    owner_type="shot_segment",
+                    owner_id=segment_id,
+                    expected_attempt_no=attempt_no,
+                    actual_attempt_no=actual_attempt_no,
+                    analysis_status=segment.analysis_status,
+                    task_set_id=str(segment.task_set_id),
+                    user_id=str(segment.user_id),
+                    reason="attempt_or_status_mismatch_after_lock",
+                )
                 await db.rollback()
                 return
             current_lease = segment.analysis_lease_until
             if segment.analysis_claim_token and segment.analysis_claim_token != token and current_lease and current_lease > _now():
                 await db.rollback()
                 return
-            if int(segment.analysis_attempt_no or 1) != attempt_no:
-                await db.rollback()
-                return
             user_id = str(segment.user_id)
             task_set_id = str(segment.task_set_id)
             video_url = str(segment.segment_video_url)
@@ -509,51 +812,24 @@ async def _run_analyze_custom_segment_video(segment_id: str) -> None:
                 segment_id=segment_id,
                 trace_id=f"shot-segment-analysis:{segment_id}:attempt:{attempt_no}",
             )
-            provider_succeeded = True
+        provider_succeeded = True
-            log_provider_success(llm_billing_context, usage=analyzed.usage)
+        log_provider_success(llm_billing_context, usage=analyzed.usage)
+        try:
             await lease.ensure_owned()
-            result = await call_db.execute(
+            allow_business_write = True
-                select(ShotReplicateSegment)
+        except RedisExecutionLockError:
-                .where(ShotReplicateSegment.id == segment_id, ShotReplicateSegment.deleted_at.is_(None))
+            allow_business_write = False
-                .with_for_update()
+        persist_outcome = await _persist_segment_analysis_result(
-                .limit(1)
+            segment_id=segment_id,
-            )
+            attempt_no=attempt_no,
-            segment = result.scalar_one_or_none()
+            token=token,
-            if (
+            video_url=video_url,
-                not segment
+            analyzed=analyzed,
-                or int(segment.analysis_attempt_no or 1) != attempt_no
+            billing_context=llm_billing_context,
-                or segment.analysis_claim_token != token
+            allow_business_write=allow_business_write,
-                or str(segment.segment_video_url) != str(video_url)
+        )
-                or segment.analysis_status != ShotSegmentAnalysisStatusEnum.PROCESSING.value
+        if persist_outcome != "completed":
-            ):
+            return
-                await call_db.rollback()
-                await settle_success(
-                    call_db,
-                    llm_billing_context,
-                    usage=analyzed.usage,
-                    description="拆镜复刻-片段视频分析（失效结果结算）",
-                )
-                await call_db.commit()
-                return
-            result_json = analyzed.result
-            segment.original_video_content = str(result_json.get("原视频内容") or "无")
-            segment.original_video_category = str(result_json.get("原视频分类") or "无")
-            segment.original_video_audience = str(result_json.get("原视频受众人群") or "无")
-            segment.segment_content = segment.original_video_content
-            segment.segment_category = segment.original_video_category
-            segment.segment_audience = segment.original_video_audience
-            segment.analysis_json = result_json
-            segment.analysis_status = ShotSegmentAnalysisStatusEnum.COMPLETED.value
-            segment.analysis_claim_token = None
-            segment.analysis_lease_until = None
-            segment.analysis_error_message = None
-            await settle_success(
-                call_db,
-                llm_billing_context,
-                usage=analyzed.usage,
-                description="拆镜复刻-片段视频分析",
-            )
-            await call_db.commit()
 
         log_module_prompt_event(
             event_type=ShotReplicateLogEventEnum.SEGMENT_ANALYSIS_SUCCESS.value,
@@ -580,38 +856,68 @@ async def _run_analyze_custom_segment_video(segment_id: str) -> None:
     except Exception as exc:
         if "llm_billing_context" in locals() and not locals().get("provider_succeeded", False):
             log_provider_failure(llm_billing_context, error=str(exc))
-        async with async_session() as db:
+        if "llm_billing_context" in locals() and locals().get("provider_succeeded", False) and locals().get("analyzed") is not None:
-            result = await db.execute(
+            try:
-                select(ShotReplicateSegment)
+                try:
-                .where(ShotReplicateSegment.id == segment_id, ShotReplicateSegment.deleted_at.is_(None))
+                    await lease.ensure_owned()
-                .with_for_update()
+                    allow_business_write = True
-                .limit(1)
+                except RedisExecutionLockError:
-            )
+                    allow_business_write = False
-            segment = result.scalar_one_or_none()
+                persist_outcome = await _persist_segment_analysis_result(
-            segment_is_current = bool(
+                    segment_id=segment_id,
-                segment
+                    attempt_no=attempt_no,
-                and int(segment.analysis_attempt_no or 1) == attempt_no
+                    token=token,
-                and segment.analysis_claim_token == token
+                    video_url=video_url,
-                and segment.analysis_status == ShotSegmentAnalysisStatusEnum.PROCESSING.value
+                    analyzed=analyzed,
-            )
+                    billing_context=llm_billing_context,
-            if segment_is_current and segment is not None:
+                    allow_business_write=allow_business_write,
-                user_id = user_id or str(segment.user_id)
+                )
-                task_set_id = task_set_id or str(segment.task_set_id)
+                if persist_outcome == "completed":
-                segment.analysis_status = ShotSegmentAnalysisStatusEnum.FAILED.value
+                    log_module_event_file(
-                segment.analysis_claim_token = None
+                        module=MODULE,
-                segment.analysis_lease_until = None
+                        event_type=ShotReplicateLogEventEnum.SEGMENT_ANALYSIS_SUCCESS.value,
-                segment.analysis_error_message = str(exc)
+                        project_id=task_set_id,
-            if "llm_billing_context" in locals():
+                        step_id=segment_id,
-                if locals().get("provider_succeeded", False) and locals().get("analyzed") is not None:
+                        user_id=user_id,
-                    await settle_success(
+                        message="切片视频分析本地异常后幂等恢复成功",
-                        db,
+                        detail={"segment_id": segment_id, "analysis_attempt_no": attempt_no},
-                        llm_billing_context,
-                        usage=analyzed.usage,
-                        description="拆镜复刻-片段视频分析（本地失败结算）",
                     )
-                else:
+                return
-                    await release_on_failure(db, llm_billing_context, error=str(exc))
+            except Exception as settlement_exc:
-            await db.commit()
+                manual_error = (
+                    "供应商已成功，但本地结果保存或积分结算失败；已终止自动恢复并保留冻结积分，"
+                    f"需人工对账。error={settlement_exc}"
+                )
+                await _mark_segment_provider_success_pending_manual(
+                    segment_id=segment_id,
+                    attempt_no=attempt_no,
+                    token=token,
+                    error_message=manual_error,
+                )
+                exc = settlement_exc
+        elif "llm_billing_context" in locals():
+            async with async_session() as db:
+                result = await db.execute(
+                    select(ShotReplicateSegment)
+                    .where(ShotReplicateSegment.id == segment_id, ShotReplicateSegment.deleted_at.is_(None))
+                    .with_for_update()
+                    .limit(1)
+                )
+                segment = result.scalar_one_or_none()
+                if (
+                    segment
+                    and int(segment.analysis_attempt_no or 1) == attempt_no
+                    and segment.analysis_claim_token == token
+                    and segment.analysis_status == ShotSegmentAnalysisStatusEnum.PROCESSING.value
+                ):
+                    user_id = user_id or str(segment.user_id)
+                    task_set_id = task_set_id or str(segment.task_set_id)
+                    segment.analysis_status = ShotSegmentAnalysisStatusEnum.FAILED.value
+                    segment.analysis_claim_token = None
+                    segment.analysis_lease_until = None
+                    segment.analysis_error_message = str(exc)
+                await release_on_failure(db, llm_billing_context, error=str(exc))
+                await db.commit()
         log_module_error(
             module=MODULE,
             event_type=ShotReplicateLogEventEnum.SEGMENT_ANALYSIS_FAILED.value,
@@ -643,6 +949,65 @@ async def _renew_split_lease(segment_id: str, attempt_no: int, token: str) -> bo
         return bool(result.rowcount == 1)
 
 
+async def _mark_auto_segment_analysis_dispatch_failed(
+    *,
+    segment_id: str,
+    expected_attempt_no: int,
+    error_message: str,
+) -> bool:
+    """切片成功后的自动分析投递失败补偿；不回滚或清理已完成的切片文件。"""
+    task_set_id: str | None = None
+    user_id: str | None = None
+    async with async_session() as db:
+        result = await db.execute(
+            select(ShotReplicateSegment)
+            .where(
+                ShotReplicateSegment.id == segment_id,
+                ShotReplicateSegment.deleted_at.is_(None),
+            )
+            .with_for_update()
+            .limit(1)
+        )
+        segment = result.scalar_one_or_none()
+        if (
+            not segment
+            or int(segment.analysis_attempt_no or 1) != int(expected_attempt_no)
+            or segment.analysis_status != ShotSegmentAnalysisStatusEnum.PENDING.value
+        ):
+            await db.rollback()
+            return False
+
+        task_set_id = str(segment.task_set_id)
+        user_id = str(segment.user_id)
+        segment.analysis_status = ShotSegmentAnalysisStatusEnum.FAILED.value
+        segment.analysis_claim_token = None
+        segment.analysis_started_at = None
+        segment.analysis_lease_until = None
+        segment.analysis_error_message = error_message
+        await release_on_failure(
+            db,
+            build_segment_analysis_billing_context(segment),
+            error=error_message,
+        )
+        await db.commit()
+
+    log_module_error(
+        module=MODULE,
+        event_type=ShotReplicateLogEventEnum.CELERY_DISPATCH_FAILED.value,
+        project_id=task_set_id,
+        step_id=segment_id,
+        user_id=user_id,
+        message="自定义切片分析任务投递失败，已标记分析失败并释放冻结积分",
+        detail={
+            "segment_id": segment_id,
+            "task_set_id": task_set_id,
+            "analysis_attempt_no": expected_attempt_no,
+        },
+        exc=RuntimeError(error_message),
+    )
+    return True
+
+
 async def _run_split_one_segment(segment_id: str) -> None:
     async with async_session() as db:
         row = await db.execute(
@@ -826,6 +1191,7 @@ async def _run_split_one_segment(segment_id: str) -> None:
             source_mode = str(segment.source_mode)
             final_task_set_id = str(segment.task_set_id)
             final_user_id = str(segment.user_id)
+            analysis_attempt_no = max(1, int(segment.analysis_attempt_no or 1))
             await refresh_task_set_split_summary(db, segment.task_set_id)
             await db.commit()
 
@@ -847,12 +1213,19 @@ async def _run_split_one_segment(segment_id: str) -> None:
         )
 
         if source_mode == ShotSegmentSourceModeEnum.CUSTOM.value and celery_app:
-            analyze_custom_segment_video.apply_async(
+            try:
-                args=[segment_id],
+                analyze_custom_segment_video.apply_async(
-                queue=ANALYSIS_QUEUE,
+                    args=[segment_id, analysis_attempt_no],
-                countdown=0,
+                    queue=ANALYSIS_QUEUE,
-                task_id=f"shot-analysis:segment:{segment_id}:attempt:1",
+                    countdown=0,
-            )
+                    task_id=f"shot-analysis:segment:{segment_id}:attempt:{analysis_attempt_no}",
+                )
+            except Exception as dispatch_exc:
+                await _mark_auto_segment_analysis_dispatch_failed(
+                    segment_id=segment_id,
+                    expected_attempt_no=analysis_attempt_no,
+                    error_message=f"自定义切片分析任务投递失败: {dispatch_exc}",
+                )
     except RedisExecutionLockError:
         cleanup_split_result(split_result)
         raise
@@ -980,9 +1353,9 @@ if celery_app:
         time_limit=settings.SHOT_ANALYSIS_TIME_LIMIT_SECONDS,
         ignore_result=True,
     )
-    def analyze_original_video(self, task_set_id: str) -> None:
+    def analyze_original_video(self, task_set_id: str, expected_attempt_no: int | None = None) -> None:
         try:
-            return run_async(_run_analyze_original_video(task_set_id))
+            return run_async(_run_analyze_original_video(task_set_id, expected_attempt_no))
         except RedisExecutionLockError as exc:
             raise self.retry(exc=exc, countdown=60)
 
@@ -1004,9 +1377,9 @@ if celery_app:
         time_limit=settings.SHOT_ANALYSIS_TIME_LIMIT_SECONDS,
         ignore_result=True,
     )
-    def analyze_custom_segment_video(self, segment_id: str) -> None:
+    def analyze_custom_segment_video(self, segment_id: str, expected_attempt_no: int | None = None) -> None:
         try:
-            return run_async(_run_analyze_custom_segment_video(segment_id))
+            return run_async(_run_analyze_custom_segment_video(segment_id, expected_attempt_no))
         except RedisExecutionLockError as exc:
             raise self.retry(exc=exc, countdown=60)
 

video-gen-app/src/api/index.ts

@@ -302,7 +302,7 @@ export async function verifyCaptcha(captchaId: string, x: number): Promise<strin
 }
 // ── Site Info ─────────────────────────────────────────────
 export async function getSiteInfo(): Promise<{ siteName: string; siteLogo: string; userAgreementPrivacyUrl: string; siteCopyright: string; operationManual: string; loginBgVideo: string; optimizeHoldCredits?: number }> {
-  if (USE_MOCK) return { siteName: 'VideoGen.AI', siteLogo: '', userAgreementPrivacyUrl: '', siteCopyright: '© 2024 民众智创 版权所有', operationManual: '', loginBgVideo: '' };
+  if (USE_MOCK) return { siteName: '智创', siteLogo: '', userAgreementPrivacyUrl: '', siteCopyright: '© 2026 智创 版权所有', operationManual: '', loginBgVideo: '' };
   return api.get('/auth/site-info', false);
 }
 // ── Video Engines ─────────────────────────────────────────

video-gen-app/src/components/Layout/AppLayout.tsx

@@ -385,7 +385,7 @@ const AppLayout: React.FC = () => {
 
   useEffect(() => {
     getSiteInfo().then(info => {
-      const name = info.siteName || '民众智创';
+      const name = info.siteName || '智创';
       const logo = info.siteLogo || '';
 
       if (name !== siteName) {

video-gen-app/src/pages/LoginPage.tsx

@@ -36,12 +36,12 @@ const LoginPage: React.FC = () => {
       if (cached) {
         const info = JSON.parse(cached);
         return {
-          siteName: info.siteName || 'VideoGen.AI',
+          siteName: info.siteName || '智创',
           siteLogo: info.siteLogo || '',
         };
       }
     } catch { }
-    return { siteName: 'VideoGen.AI', siteLogo: '' };
+    return { siteName: '智创', siteLogo: '' };
   };
   
   const initialInfo = getInitialSiteInfo();