storyforge/collector-service/app/main.py

from __future__ import annotations

import asyncio
import json
import os
import re
import secrets
import shutil
import subprocess
import uuid
from datetime import datetime, timezone
from pathlib import Path
from typing import Any

from fastapi import Body, Depends, FastAPI, File, Form, Header, HTTPException, Query, UploadFile
from fastapi.middleware.cors import CORSMiddleware
from fastapi.staticfiles import StaticFiles
from pydantic import BaseModel, Field

from .database import Database, utc_now
from .integrations import CutVideoClient, HuobaoDramaClient, N8NClient
from .openai_compat import OpenAICompatClient

BASE_DIR = Path(__file__).resolve().parents[2]
DATA_DIR = Path(os.getenv("DATA_DIR", BASE_DIR / "data" / "collector"))
DOWNLOADS_DIR = DATA_DIR / "downloads"
JOBS_DIR = DATA_DIR / "jobs"
MODELS_DIR = DATA_DIR / "models"
DB_PATH = os.getenv("DATABASE_PATH", str(DATA_DIR / "storyforge.db"))
DEFAULT_EXTERNAL_BASE_URL = os.getenv("DEFAULT_EXTERNAL_BASE_URL", "https://test.hyzq.net/storyforge")
LOCAL_OPENAI_BASE_URL = os.getenv("LOCAL_OPENAI_BASE_URL", "http://127.0.0.1:8317/v1")
LOCAL_OPENAI_MODEL = os.getenv("LOCAL_OPENAI_MODEL", "GLM-5")
LOCAL_OPENAI_API_KEY = os.getenv("LOCAL_OPENAI_API_KEY", "")
YTDLP_BIN = os.getenv("YTDLP_BIN", "yt-dlp")
FFMPEG_BIN = os.getenv("FFMPEG_BIN", "ffmpeg")
WHISPER_BIN = os.getenv("WHISPER_BIN", "")
WHISPER_MODEL = os.getenv("WHISPER_MODEL", str(MODELS_DIR / "ggml-base.en.bin"))
N8N_BASE_URL = os.getenv("N8N_BASE_URL", "http://127.0.0.1:5670")
N8N_ANALYSIS_WEBHOOK_PATH = os.getenv("N8N_ANALYSIS_WEBHOOK_PATH", "/webhook/storyforge-analysis")
N8N_REAL_CUT_WEBHOOK_PATH = os.getenv("N8N_REAL_CUT_WEBHOOK_PATH", "/webhook/storyforge-real-cut")
N8N_AI_VIDEO_WEBHOOK_PATH = os.getenv("N8N_AI_VIDEO_WEBHOOK_PATH", "/webhook/storyforge-ai-video")
ORCHESTRATOR_SHARED_SECRET = os.getenv("ORCHESTRATOR_SHARED_SECRET", "")
CUTVIDEO_BASE_URL = os.getenv("CUTVIDEO_BASE_URL", "")
CUTVIDEO_API_KEY = os.getenv("CUTVIDEO_API_KEY", "")
HUOBAO_BASE_URL = os.getenv("HUOBAO_BASE_URL", "http://127.0.0.1:5678")
CUTVIDEO_BASE_CONFIG = os.getenv("CUTVIDEO_BASE_CONFIG", "example.job.yaml")
CUTVIDEO_POLL_INTERVAL_SEC = int(os.getenv("CUTVIDEO_POLL_INTERVAL_SEC", "10"))
CUTVIDEO_MAX_WAIT_SEC = int(os.getenv("CUTVIDEO_MAX_WAIT_SEC", "1800"))
HUOBAO_POLL_INTERVAL_SEC = int(os.getenv("HUOBAO_POLL_INTERVAL_SEC", "10"))
HUOBAO_MAX_WAIT_SEC = int(os.getenv("HUOBAO_MAX_WAIT_SEC", "900"))

for path in (DATA_DIR, DOWNLOADS_DIR, JOBS_DIR, MODELS_DIR):
    path.mkdir(parents=True, exist_ok=True)

db = Database(DB_PATH)
openai_client = OpenAICompatClient()
n8n_client = N8NClient(
    base_url=N8N_BASE_URL,
    workflow_paths={
        "analysis_pipeline": N8N_ANALYSIS_WEBHOOK_PATH,
        "real_cut_pipeline": N8N_REAL_CUT_WEBHOOK_PATH,
        "ai_video_pipeline": N8N_AI_VIDEO_WEBHOOK_PATH,
    },
    shared_secret=ORCHESTRATOR_SHARED_SECRET,
)
cutvideo_client = CutVideoClient(base_url=CUTVIDEO_BASE_URL, api_key=CUTVIDEO_API_KEY)
huobao_client = HuobaoDramaClient(base_url=HUOBAO_BASE_URL)

app = FastAPI(title="StoryForge Collector Service", version="0.2.0")
app.add_middleware(
    CORSMiddleware,
    allow_origins=["*"],
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)
app.mount("/downloads", StaticFiles(directory=str(DOWNLOADS_DIR)), name="downloads")


class RegisterAccountRequest(BaseModel):
    username: str
    password: str
    display_name: str = ""


class LoginRequest(BaseModel):
    username: str
    password: str


class ModelProfileRequest(BaseModel):
    name: str
    base_url: str
    api_key: str = ""
    model_name: str
    is_default: bool = False


class PreferredModelRequest(BaseModel):
    model_profile_id: str


class KnowledgeBaseCreateRequest(BaseModel):
    name: str
    description: str = ""
    project_id: str = ""


class ExploreVideoLinkRequest(BaseModel):
    video_url: str
    title: str | None = None
    project_id: str | None = None
    knowledge_base_id: str | None = None
    assistant_id: str | None = None
    analysis_model_profile_id: str | None = None
    language: str = "auto"


class ExploreTextRequest(BaseModel):
    title: str
    content: str
    project_id: str | None = None
    knowledge_base_id: str | None = None
    assistant_id: str | None = None
    analysis_model_profile_id: str | None = None


class AssistantCreateRequest(BaseModel):
    name: str
    description: str = ""
    system_prompt: str = ""
    generation_goal: str = ""
    knowledge_base_ids: list[str] = Field(default_factory=list)
    project_id: str = ""
    model_profile_id: str = ""


class AssistantUpdateRequest(BaseModel):
    name: str | None = None
    description: str | None = None
    system_prompt: str | None = None
    generation_goal: str | None = None
    knowledge_base_ids: list[str] | None = None
    project_id: str | None = None
    model_profile_id: str | None = None


class GenerateCopyRequest(BaseModel):
    brief: str
    platform: str = "抖音"
    audience: str = "创业者"
    extra_requirements: str = ""
    knowledge_base_ids: list[str] = Field(default_factory=list)


class PublishAppUpdateRequest(BaseModel):
    platform: str = "android"
    channel: str = "stable"
    versionCode: int
    versionName: str
    minSupportedCode: int
    apkUrl: str
    apkSha256: str = ""
    notes: str = ""
    forceUpdate: bool = False
    isActive: bool = True


class ProjectCreateRequest(BaseModel):
    name: str
    description: str = ""


class ContentSourceCreateRequest(BaseModel):
    project_id: str = ""
    source_kind: str
    platform: str = ""
    handle: str = ""
    source_url: str = ""
    title: str = ""
    local_path: str = ""
    metadata: dict[str, Any] = Field(default_factory=dict)


class RealCutJobRequest(BaseModel):
    project_id: str = ""
    title: str
    input_dir: str
    base_config: str = ""
    objective: str = "保留高信息密度片段，输出适合短视频平台的粗剪结果"
    target_duration_sec: int = 60
    target_aspect_ratio: str = "9:16"
    ideal_segment_duration_sec: int = 8
    max_segment_duration_sec: int = 18
    transcript_backend: str = "auto"
    transcript_device: str = "cuda"
    review_enabled: bool = False
    dry_run: bool = False


class AiVideoJobRequest(BaseModel):
    project_id: str = ""
    assistant_id: str = ""
    knowledge_base_id: str = ""
    source_job_id: str = ""
    title: str
    brief: str
    style: str = "realistic"
    shots: int = 4
    image_provider: str = "openai"
    image_model: str = ""
    video_provider: str = "doubao"
    video_model: str = ""
    aspect_ratio: str = "9:16"
    duration: int = 5


class InternalStepRequest(BaseModel):
    job_id: str = ""
    jobId: str = ""
    payload: dict[str, Any] = Field(default_factory=dict)


class JobStatusUpdateRequest(BaseModel):
    status: str
    error: str = ""
    provider_name: str = ""
    provider_task_id: str = ""
    artifacts: dict[str, Any] = Field(default_factory=dict)
    result: dict[str, Any] = Field(default_factory=dict)


def now_ts() -> int:
    return int(datetime.now(timezone.utc).timestamp())


def make_id(prefix: str) -> str:
    return f"{prefix}_{uuid.uuid4().hex}"


def hash_password(password: str, salt: str) -> str:
    import hashlib

    return hashlib.pbkdf2_hmac("sha256", password.encode("utf-8"), salt.encode("utf-8"), 120_000).hex()


def create_password_hash(password: str) -> tuple[str, str]:
    salt = secrets.token_hex(16)
    return hash_password(password, salt), salt


def verify_password(password: str, hashed: str, salt: str) -> bool:
    return secrets.compare_digest(hash_password(password, salt), hashed)


def mask_api_key(value: str) -> str:
    if not value:
        return ""
    if len(value) <= 8:
        return "*" * len(value)
    return f"{value[:4]}***{value[-4:]}"


def normalize_model_profile(row: dict[str, Any]) -> dict[str, Any]:
    return {
        "id": row["id"],
        "owner_account_id": row.get("owner_account_id"),
        "name": row["name"],
        "provider": row["provider"],
        "base_url": row["base_url"],
        "api_key_masked": mask_api_key(row.get("api_key", "")),
        "model_name": row["model_name"],
        "is_system": bool(row.get("is_system", 0)),
        "is_default": bool(row.get("is_default", 0)),
        "created_at": row["created_at"],
        "updated_at": row["updated_at"],
    }


def normalize_account(row: dict[str, Any]) -> dict[str, Any]:
    return {
        "id": row["id"],
        "username": row["username"],
        "display_name": row["display_name"],
        "role": row["role"],
        "approval_status": row["approval_status"],
        "approved_by": row.get("approved_by"),
        "approved_at": row.get("approved_at"),
        "preferred_analysis_model_id": row.get("preferred_analysis_model_id") or "",
        "created_at": row["created_at"],
        "updated_at": row["updated_at"],
    }


def model_profile_for_account(account_id: str, requested_id: str | None) -> dict[str, Any]:
    if requested_id:
        row = db.fetch_one(
            "SELECT * FROM model_profiles WHERE id = ? AND (owner_account_id IS NULL OR owner_account_id = ?)",
            (requested_id, account_id),
        )
        if row:
            return row
    account = db.fetch_one("SELECT preferred_analysis_model_id FROM accounts WHERE id = ?", (account_id,))
    preferred_id = (account or {}).get("preferred_analysis_model_id") or ""
    if preferred_id:
        row = db.fetch_one(
            "SELECT * FROM model_profiles WHERE id = ? AND (owner_account_id IS NULL OR owner_account_id = ?)",
            (preferred_id, account_id),
        )
        if row:
            return row
    row = db.fetch_one("SELECT * FROM model_profiles WHERE is_default = 1 ORDER BY is_system DESC, created_at ASC LIMIT 1")
    if not row:
        raise HTTPException(status_code=500, detail="No model profile configured")
    return row


def project_payload(row: dict[str, Any]) -> dict[str, Any]:
    return {
        "id": row["id"],
        "user_id": row["user_id"],
        "name": row["name"],
        "description": row.get("description", ""),
        "created_at": row["created_at"],
        "updated_at": row["updated_at"],
    }


def content_source_payload(row: dict[str, Any]) -> dict[str, Any]:
    metadata = row.get("metadata_json") or "{}"
    try:
        metadata_map = json.loads(metadata)
    except json.JSONDecodeError:
        metadata_map = {}
    return {
        "id": row["id"],
        "user_id": row["user_id"],
        "project_id": row.get("project_id", ""),
        "source_kind": row["source_kind"],
        "platform": row.get("platform", ""),
        "handle": row.get("handle", ""),
        "source_url": row.get("source_url", ""),
        "title": row.get("title", ""),
        "local_path": row.get("local_path", ""),
        "metadata": metadata_map,
        "created_at": row["created_at"],
        "updated_at": row["updated_at"],
    }


def job_event_payload(row: dict[str, Any]) -> dict[str, Any]:
    return {
        "id": row["id"],
        "job_id": row["job_id"],
        "event_type": row["event_type"],
        "payload": parse_json_object(row.get("payload_json") or "{}"),
        "created_at": row["created_at"],
    }


def ensure_default_project(account_id: str, username: str = "默认用户") -> dict[str, Any]:
    project = db.fetch_one(
        "SELECT * FROM projects WHERE user_id = ? ORDER BY created_at ASC LIMIT 1",
        (account_id,),
    )
    if project:
        return project
    now = utc_now()
    project_id = make_id("project")
    db.execute(
        """
        INSERT INTO projects (id, user_id, name, description, created_at, updated_at)
        VALUES (?, ?, ?, ?, ?, ?)
        """,
        (
            project_id,
            account_id,
            f"{username} 默认项目",
            "系统自动创建",
            now,
            now,
        ),
    )
    return db.fetch_one("SELECT * FROM projects WHERE id = ?", (project_id,))


def resolve_target_project(account_id: str, requested_project_id: str | None, username: str = "默认用户") -> dict[str, Any]:
    if requested_project_id:
        project = db.fetch_one(
            "SELECT * FROM projects WHERE id = ? AND user_id = ?",
            (requested_project_id, account_id),
        )
        if project:
            return project
        raise HTTPException(status_code=404, detail="Project not found")
    return ensure_default_project(account_id, username=username)


def resolve_target_assistant(account_id: str, requested_assistant_id: str | None, project_id: str = "") -> dict[str, Any] | None:
    if not requested_assistant_id:
        return None
    assistant = db.fetch_one("SELECT * FROM assistants WHERE id = ? AND user_id = ?", (requested_assistant_id, account_id))
    if not assistant:
        raise HTTPException(status_code=404, detail="Assistant not found")
    if project_id and assistant.get("project_id") and assistant.get("project_id") != project_id:
        raise HTTPException(status_code=400, detail="Assistant does not belong to target project")
    return assistant


def append_job_event(job_id: str, event_type: str, payload: dict[str, Any] | None = None) -> None:
    db.execute(
        """
        INSERT INTO job_events (id, job_id, event_type, payload_json, created_at)
        VALUES (?, ?, ?, ?, ?)
        """,
        (
            make_id("evt"),
            job_id,
            event_type,
            json.dumps(payload or {}, ensure_ascii=False),
            utc_now(),
        ),
    )


def parse_json_object(raw_text: str) -> dict[str, Any]:
    cleaned = raw_text.strip()
    if not cleaned:
        return {}
    try:
        data = json.loads(cleaned)
        return data if isinstance(data, dict) else {}
    except json.JSONDecodeError:
        match = re.search(r"\{.*\}", cleaned, re.S)
        if not match:
            return {}
        try:
            data = json.loads(match.group(0))
            return data if isinstance(data, dict) else {}
        except json.JSONDecodeError:
            return {}


def knowledge_base_payload(row: dict[str, Any]) -> dict[str, Any]:
    document_count = db.fetch_one(
        "SELECT COUNT(*) AS count FROM knowledge_documents WHERE knowledge_base_id = ?",
        (row["id"],),
    )["count"]
    linked_count = db.fetch_one(
        "SELECT COUNT(*) AS count FROM assistant_knowledge_bases WHERE knowledge_base_id = ?",
        (row["id"],),
    )["count"]
    return {
        "id": row["id"],
        "user_id": row["user_id"],
        "project_id": row.get("project_id", ""),
        "name": row["name"],
        "description": row.get("description", ""),
        "sync_status": row.get("sync_status", "ready"),
        "document_count": document_count,
        "linked_assistant_count": linked_count,
        "created_at": row["created_at"],
        "updated_at": row["updated_at"],
    }


def assistant_payload(row: dict[str, Any]) -> dict[str, Any]:
    kb_rows = db.fetch_all(
        "SELECT knowledge_base_id FROM assistant_knowledge_bases WHERE assistant_id = ? ORDER BY knowledge_base_id ASC",
        (row["id"],),
    )
    return {
        "id": row["id"],
        "user_id": row["user_id"],
        "project_id": row.get("project_id", ""),
        "name": row["name"],
        "description": row.get("description", ""),
        "system_prompt": row.get("system_prompt", ""),
        "generation_goal": row.get("generation_goal", ""),
        "knowledge_base_ids": [item["knowledge_base_id"] for item in kb_rows],
        "config": parse_json_object(row.get("config_json") or "{}"),
        "model_profile_id": row.get("model_profile_id", ""),
        "created_at": row["created_at"],
        "updated_at": row["updated_at"],
    }


def document_payload(row: dict[str, Any]) -> dict[str, Any]:
    analysis_map = parse_json_object(row.get("analysis_json") or "{}")
    source_artifacts = parse_json_object(row.get("source_artifact_json") or "{}")
    storyboard_raw = row.get("storyboard_json") or "[]"
    try:
        storyboard_items = json.loads(storyboard_raw)
    except json.JSONDecodeError:
        storyboard_items = []
    return {
        "id": row["id"],
        "knowledge_base_id": row["knowledge_base_id"],
        "title": row["title"],
        "source_type": row["source_type"],
        "source_url": row.get("source_url", ""),
        "transcript_text": row.get("transcript_text", ""),
        "style_summary": row.get("style_summary", ""),
        "combined_text": row.get("combined_text", ""),
        "analysis": analysis_map,
        "storyboards": storyboard_items,
        "source_artifacts": source_artifacts,
        "analysis_model_profile_id": row.get("analysis_model_profile_id", ""),
        "created_at": row["created_at"],
        "updated_at": row["updated_at"],
    }


def job_payload(row: dict[str, Any]) -> dict[str, Any]:
    artifacts = row.get("artifacts_json") or "{}"
    result = row.get("result_json") or "{}"
    try:
        artifacts_map = json.loads(artifacts)
    except json.JSONDecodeError:
        artifacts_map = {}
    try:
        result_map = json.loads(result)
    except json.JSONDecodeError:
        result_map = {}
    return {
        "id": row["id"],
        "user_id": row["user_id"],
        "project_id": row.get("project_id", ""),
        "assistant_id": row.get("assistant_id"),
        "knowledge_base_id": row["knowledge_base_id"],
        "content_source_id": row.get("content_source_id", ""),
        "source_type": row["source_type"],
        "line_type": row.get("line_type", "analysis"),
        "workflow_key": row.get("workflow_key", ""),
        "orchestrator": row.get("orchestrator", "n8n"),
        "provider_name": row.get("provider_name", ""),
        "provider_task_id": row.get("provider_task_id", ""),
        "source_url": row.get("source_url"),
        "title": row["title"],
        "language": row.get("language", "auto"),
        "status": row["status"],
        "transcript_text": row.get("transcript_text", ""),
        "style_summary": row.get("style_summary", ""),
        "upload_status": row.get("upload_status", "pending"),
        "error": row.get("error", ""),
        "artifacts": artifacts_map,
        "result": result_map,
        "analysis_model_profile_id": row.get("analysis_model_profile_id", ""),
        "created_at": row["created_at"],
        "updated_at": row["updated_at"],
    }


def require_auth(authorization: str | None = Header(default=None)) -> dict[str, Any]:
    if not authorization or not authorization.startswith("Bearer "):
        raise HTTPException(status_code=401, detail="Missing bearer token")
    token = authorization.split(" ", 1)[1].strip()
    token_row = db.fetch_one("SELECT * FROM auth_tokens WHERE token = ?", (token,))
    if not token_row:
        raise HTTPException(status_code=401, detail="Invalid token")
    account = db.fetch_one("SELECT * FROM accounts WHERE id = ?", (token_row["account_id"],))
    if not account:
        raise HTTPException(status_code=401, detail="Account not found")
    return account


def require_approved(account: dict[str, Any] = Depends(require_auth)) -> dict[str, Any]:
    if account["approval_status"] != "approved":
        raise HTTPException(status_code=403, detail="Account pending approval")
    return account


def require_super_admin(account: dict[str, Any] = Depends(require_auth)) -> dict[str, Any]:
    if account["role"] != "super_admin":
        raise HTTPException(status_code=403, detail="Super admin required")
    return account


def require_orchestrator(x_orchestrator_secret: str | None = Header(default=None)) -> bool:
    if ORCHESTRATOR_SHARED_SECRET and x_orchestrator_secret != ORCHESTRATOR_SHARED_SECRET:
        raise HTTPException(status_code=401, detail="Invalid orchestrator secret")
    return True


def create_content_source(
    *,
    account_id: str,
    project_id: str,
    source_kind: str,
    platform: str = "",
    handle: str = "",
    source_url: str = "",
    title: str = "",
    local_path: str = "",
    metadata: dict[str, Any] | None = None,
) -> dict[str, Any]:
    source_id = make_id("source")
    now = utc_now()
    db.execute(
        """
        INSERT INTO content_sources (
            id, user_id, project_id, source_kind, platform, handle,
            source_url, title, local_path, metadata_json, created_at, updated_at
        ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
        """,
        (
            source_id,
            account_id,
            project_id,
            source_kind,
            platform,
            handle,
            source_url,
            title,
            local_path,
            json.dumps(metadata or {}, ensure_ascii=False),
            now,
            now,
        ),
    )
    return db.fetch_one("SELECT * FROM content_sources WHERE id = ?", (source_id,))


def merge_json_field(current_raw: str | None, updates: dict[str, Any]) -> str:
    current = parse_json_object(current_raw or "{}")
    current.update(updates)
    return json.dumps(current, ensure_ascii=False)


def update_job_state(
    job_id: str,
    *,
    status: str,
    error: str = "",
    provider_name: str | None = None,
    provider_task_id: str | None = None,
    artifacts: dict[str, Any] | None = None,
    result: dict[str, Any] | None = None,
) -> dict[str, Any]:
    row = db.fetch_one("SELECT * FROM jobs WHERE id = ?", (job_id,))
    if not row:
        raise HTTPException(status_code=404, detail="Job not found")
    merged_artifacts = merge_json_field(row.get("artifacts_json") or "{}", artifacts or {})
    merged_result = merge_json_field(row.get("result_json") or "{}", result or {})
    db.execute(
        """
        UPDATE jobs
        SET status = ?, error = ?, provider_name = ?, provider_task_id = ?,
            artifacts_json = ?, result_json = ?, updated_at = ?
        WHERE id = ?
        """,
        (
            status,
            error,
            provider_name if provider_name is not None else row.get("provider_name", ""),
            provider_task_id if provider_task_id is not None else row.get("provider_task_id", ""),
            merged_artifacts,
            merged_result,
            utc_now(),
            job_id,
        ),
    )
    append_job_event(
        job_id,
        f"job.{status}",
        {
            "provider_name": provider_name if provider_name is not None else row.get("provider_name", ""),
            "provider_task_id": provider_task_id if provider_task_id is not None else row.get("provider_task_id", ""),
            "error": error,
            "artifacts": artifacts or {},
            "result": result or {},
        },
    )
    return db.fetch_one("SELECT * FROM jobs WHERE id = ?", (job_id,))


def job_context_payload(row: dict[str, Any]) -> dict[str, Any]:
    payload = job_payload(row)
    payload["project"] = None
    payload["assistant"] = None
    payload["knowledge_base"] = None
    payload["content_source"] = None
    payload["events"] = []

    if row.get("project_id"):
        project = db.fetch_one("SELECT * FROM projects WHERE id = ?", (row["project_id"],))
        if project:
            payload["project"] = project_payload(project)

    if row.get("assistant_id"):
        assistant = db.fetch_one("SELECT * FROM assistants WHERE id = ?", (row["assistant_id"],))
        if assistant:
            payload["assistant"] = assistant_payload(assistant)

    kb = db.fetch_one("SELECT * FROM knowledge_bases WHERE id = ?", (row["knowledge_base_id"],))
    if kb:
        payload["knowledge_base"] = knowledge_base_payload(kb)

    if row.get("content_source_id"):
        source = db.fetch_one("SELECT * FROM content_sources WHERE id = ?", (row["content_source_id"],))
        if source:
            payload["content_source"] = content_source_payload(source)

    payload["events"] = [
        job_event_payload(item)
        for item in db.fetch_all("SELECT * FROM job_events WHERE job_id = ? ORDER BY created_at ASC", (row["id"],))
    ]

    return payload


async def trigger_orchestrated_job(job_row: dict[str, Any]) -> dict[str, Any]:
    workflow_key = job_row.get("workflow_key") or "analysis_pipeline"
    if not n8n_client.enabled:
        raise HTTPException(status_code=503, detail="n8n is not configured")
    append_job_event(job_row["id"], "workflow.trigger.requested", {"workflow_key": workflow_key})
    update_job_state(
        job_row["id"],
        status="queued",
        provider_name="n8n",
        provider_task_id="",
        result={"n8n_trigger": {"requested": True}},
    )
    trigger_result = await n8n_client.trigger(
        workflow_key,
        {
            "jobId": job_row["id"],
            "job_id": job_row["id"],
            "workflowKey": workflow_key,
            "workflow_key": workflow_key,
            "lineType": job_row.get("line_type", "analysis"),
            "line_type": job_row.get("line_type", "analysis"),
        },
    )
    provider_task_id = str(trigger_result.get("executionId") or "")
    db.execute(
        """
        UPDATE jobs
        SET provider_name = ?, provider_task_id = ?, result_json = ?, updated_at = ?
        WHERE id = ?
        """,
        (
            "n8n",
            provider_task_id,
            merge_json_field(
                db.fetch_one("SELECT result_json FROM jobs WHERE id = ?", (job_row["id"],)).get("result_json") or "{}",
                {"n8n_trigger": trigger_result},
            ),
            utc_now(),
            job_row["id"],
        ),
    )
    append_job_event(
        job_row["id"],
        "workflow.trigger.accepted",
        {"provider_task_id": provider_task_id, "trigger_result": trigger_result},
    )
    return db.fetch_one("SELECT * FROM jobs WHERE id = ?", (job_row["id"],))


async def call_model(profile: dict[str, Any], system_prompt: str, user_prompt: str, temperature: float = 0.4) -> str:
    try:
        content = await openai_client.chat_completion(
            base_url=profile["base_url"],
            api_key=profile.get("api_key", ""),
            model=profile["model_name"],
            system_prompt=system_prompt,
            user_prompt=user_prompt,
            temperature=temperature,
        )
        if content:
            return content.strip()
    except Exception:
        pass
    excerpt = user_prompt.strip().replace("\n", " ")[:220]
    return f"风格摘要：内容以强结论开头，节奏偏短句，强调冲突转折和行动指令。素材摘要：{excerpt}"


async def summarize_style(profile: dict[str, Any], transcript_text: str, title: str) -> str:
    prompt = (
        f"标题：{title}\n\n"
        f"素材全文：\n{transcript_text}\n\n"
        "请提炼这段素材的文案风格、结构节奏、开头钩子、情绪推进、收尾 CTA，并给出可复用的学习结论。"
    )
    system_prompt = "你是短视频文案拆解师，输出简洁、结构化、适合沉淀进知识库。"
    return await call_model(profile, system_prompt, prompt, temperature=0.3)


async def generate_content_blueprint(
    profile: dict[str, Any],
    *,
    title: str,
    transcript_text: str,
    style_summary: str,
    agent_prompt: str = "",
    generation_goal: str = "",
) -> dict[str, Any]:
    system_prompt = (
        "你是短视频内容策略师。"
        "必须输出 JSON 对象，不要输出 Markdown，不要输出多余解释。"
    )
    user_prompt = (
        f"标题：{title}\n\n"
        f"素材转写：\n{transcript_text}\n\n"
        f"风格拆解：\n{style_summary}\n\n"
        f"智能体补充约束：\n{agent_prompt or '无'}\n\n"
        f"生成目标：\n{generation_goal or '围绕原素材做二创短视频'}\n\n"
        "请输出如下 JSON 结构："
        "{"
        '"analysis":{"hook":"","structure":[],"style_tags":[],"cta":""},'
        '"rewrite":{"title":"","script":"","summary":""},'
        '"storyboards":['
        '{"shot_index":1,"title":"","narration":"","visual":"","first_frame_prompt":"","last_frame_prompt":"","video_prompt":"","duration_sec":5}'
        "]"
        "}"
    )
    raw = await call_model(profile, system_prompt, user_prompt, temperature=0.5)
    parsed = parse_json_object(raw)
    if parsed.get("storyboards"):
        return parsed

    fallback_storyboards: list[dict[str, Any]] = []
    paragraphs = [part.strip() for part in transcript_text.split("\n") if part.strip()]
    seed_segments = paragraphs[:4] or [transcript_text[:1200]]
    for idx, segment in enumerate(seed_segments, start=1):
        snippet = segment[:180]
        fallback_storyboards.append(
            {
                "shot_index": idx,
                "title": f"镜头{idx}",
                "narration": snippet,
                "visual": f"围绕这段内容构建具象画面：{snippet}",
                "first_frame_prompt": f"短视频首帧，突出主题：{snippet}",
                "last_frame_prompt": f"短视频尾帧，强化结论和行动指令：{snippet}",
                "video_prompt": f"基于首尾帧生成连贯镜头，内容是：{snippet}",
                "duration_sec": 5,
            }
        )

    return {
        "analysis": {
            "hook": title,
            "structure": ["结论开场", "核心论点", "例证推进", "收尾行动"],
            "style_tags": ["短句", "结论先行", "强 CTA"],
            "cta": "引导用户采取下一步行动",
        },
        "rewrite": {
            "title": title,
            "script": transcript_text[:3000],
            "summary": style_summary[:500],
        },
        "storyboards": fallback_storyboards,
    }


def fallback_transcript_from_text(title: str, content: str) -> str:
    return f"标题：{title}\n\n正文：\n{content.strip()}"


def command_exists(name: str) -> bool:
    return shutil.which(name) is not None


def run_command(command: list[str], cwd: Path | None = None) -> tuple[int, str, str]:
    proc = subprocess.run(command, cwd=str(cwd) if cwd else None, capture_output=True, text=True)
    return proc.returncode, proc.stdout, proc.stderr


def create_job_record(
    *,
    account_id: str,
    project_id: str,
    knowledge_base_id: str,
    source_type: str,
    line_type: str,
    workflow_key: str,
    title: str,
    language: str = "auto",
    source_url: str = "",
    assistant_id: str | None = None,
    content_source_id: str | None = None,
    artifacts: dict[str, Any] | None = None,
    analysis_model_profile_id: str = "",
) -> dict[str, Any]:
    job_id = make_id("job")
    now = utc_now()
    db.execute(
        """
        INSERT INTO jobs (
            id, user_id, project_id, assistant_id, knowledge_base_id, content_source_id,
            source_type, line_type, workflow_key, orchestrator, provider_name, provider_task_id,
            source_url, title, language, status, transcript_text, style_summary, upload_status,
            error, artifacts_json, result_json, analysis_model_profile_id, created_at, updated_at
        ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, 'n8n', '', '', ?, ?, ?, 'pending', '', '', 'pending', '', ?, '{}', ?, ?, ?)
        """,
        (
            job_id,
            account_id,
            project_id,
            assistant_id,
            knowledge_base_id,
            content_source_id,
            source_type,
            line_type,
            workflow_key,
            source_url or None,
            title,
            language,
            json.dumps(artifacts or {}, ensure_ascii=False),
            analysis_model_profile_id,
            now,
            now,
        ),
    )
    return db.fetch_one("SELECT * FROM jobs WHERE id = ?", (job_id,))


async def wait_for_huobao_image(image_id: str | int) -> dict[str, Any]:
    deadline = now_ts() + HUOBAO_MAX_WAIT_SEC
    last_payload: dict[str, Any] = {}
    while True:
        last_payload = await huobao_client.get_image(str(image_id))
        status = str(last_payload.get("status") or "").lower()
        if status in {"completed", "failed"}:
            return last_payload
        if now_ts() >= deadline:
            raise RuntimeError(f"Huobao image task timed out: {image_id}")
        await asyncio.sleep(HUOBAO_POLL_INTERVAL_SEC)


async def wait_for_huobao_video(video_id: str | int) -> dict[str, Any]:
    deadline = now_ts() + HUOBAO_MAX_WAIT_SEC
    last_payload: dict[str, Any] = {}
    while True:
        last_payload = await huobao_client.get_video(str(video_id))
        status = str(last_payload.get("status") or "").lower()
        if status in {"completed", "failed"}:
            return last_payload
        if now_ts() >= deadline:
            raise RuntimeError(f"Huobao video task timed out: {video_id}")
        await asyncio.sleep(HUOBAO_POLL_INTERVAL_SEC)


def coerce_storyboards(items: Any) -> list[dict[str, Any]]:
    if not isinstance(items, list):
        return []
    return [item for item in items if isinstance(item, dict)]


def huobao_image_size_for_aspect_ratio(aspect_ratio: str) -> str:
    normalized = str(aspect_ratio or "").strip()
    if normalized == "9:16":
        return "1024x1536"
    if normalized == "16:9":
        return "1536x1024"
    if normalized == "1:1":
        return "1024x1024"
    return "1024x1536"


def transcribe_media(job_dir: Path, source_path: Path, title: str, source_url: str = "") -> tuple[str, dict[str, str]]:
    artifacts: dict[str, str] = {}
    transcript = ""
    media_path = source_path
    artifacts["source_path"] = str(media_path)

    if not source_path.exists():
        transcript = (
            f"素材标题：{title}\n"
            f"素材来源：{source_url or source_path.name}\n\n"
            "当前环境未找到可直接处理的本地视频文件，已记录来源信息并进入降级学习流程。"
        )
        return transcript, artifacts

    audio_path = job_dir / "audio.wav"
    if command_exists(FFMPEG_BIN):
        code, _, err = run_command([FFMPEG_BIN, "-y", "-i", str(source_path), "-ar", "16000", "-ac", "1", str(audio_path)])
        if code == 0 and audio_path.exists():
            artifacts["audio_path"] = str(audio_path)
            media_path = audio_path
        elif err:
            artifacts["ffmpeg_error"] = err.strip()[:500]

    if WHISPER_BIN and Path(WHISPER_BIN).exists() and Path(WHISPER_MODEL).exists():
        out_prefix = job_dir / "whisper"
        code, stdout, stderr = run_command([
            WHISPER_BIN,
            "-m",
            WHISPER_MODEL,
            "-f",
            str(media_path),
            "-otxt",
            "-of",
            str(out_prefix),
        ])
        txt_path = Path(str(out_prefix) + ".txt")
        if code == 0 and txt_path.exists():
            transcript = txt_path.read_text(encoding="utf-8", errors="ignore").strip()
            artifacts["transcript_path"] = str(txt_path)
        else:
            artifacts["whisper_stdout"] = stdout.strip()[:500]
            artifacts["whisper_error"] = stderr.strip()[:500]

    if not transcript:
        transcript = (
            f"素材标题：{title}\n"
            f"素材来源：{source_url or source_path.name}\n\n"
            "当前环境未完成真实 ASR，已保留原始素材供后续转写。请结合标题、来源和上下文进行初步风格学习。"
        )
    return transcript, artifacts


def ensure_user_kb(account_id: str, project_id: str = "", username: str = "默认用户") -> dict[str, Any]:
    project = resolve_target_project(account_id, project_id or None, username=username)
    row = db.fetch_one(
        "SELECT * FROM knowledge_bases WHERE user_id = ? AND project_id = ? ORDER BY created_at ASC LIMIT 1",
        (account_id, project["id"]),
    )
    if row:
        return row
    kb_id = make_id("kb")
    now = utc_now()
    db.execute(
        """
        INSERT INTO knowledge_bases (id, user_id, project_id, name, description, sync_status, created_at, updated_at)
        VALUES (?, ?, ?, ?, ?, ?, ?, ?)
        """,
        (kb_id, account_id, project["id"], "默认知识库", "系统为新用户自动创建", "ready", now, now),
    )
    return db.fetch_one("SELECT * FROM knowledge_bases WHERE id = ?", (kb_id,))


async def process_job(job_id: str) -> None:
    row = db.fetch_one("SELECT * FROM jobs WHERE id = ?", (job_id,))
    if not row:
        return
    now = utc_now()
    db.execute("UPDATE jobs SET status = ?, updated_at = ? WHERE id = ?", ("processing", now, job_id))
    append_job_event(job_id, "job.processing", {})

    try:
        artifacts = json.loads(row.get("artifacts_json") or "{}")
        transcript_text = row.get("transcript_text", "")
        job_dir = JOBS_DIR / job_id
        job_dir.mkdir(parents=True, exist_ok=True)

        if row["source_type"] == "text":
            transcript_text = fallback_transcript_from_text(row["title"], artifacts.get("input_text", ""))
        elif row["source_type"] == "video_link":
            downloaded = job_dir / "source.mp4"
            if command_exists(YTDLP_BIN):
                code, stdout, stderr = run_command([
                    YTDLP_BIN,
                    "--no-playlist",
                    "-o",
                    str(downloaded),
                    row.get("source_url") or "",
                ], cwd=job_dir)
                if code == 0 and downloaded.exists():
                    artifacts["download_stdout"] = stdout.strip()[:500]
                else:
                    artifacts["download_error"] = stderr.strip()[:500]
            transcript_text, extra = transcribe_media(job_dir, downloaded if downloaded.exists() else job_dir / "placeholder.mp4", row["title"], row.get("source_url") or "")
            artifacts.update(extra)
        elif row["source_type"] == "upload_video":
            source_path = Path(artifacts.get("uploaded_path", ""))
            transcript_text, extra = transcribe_media(job_dir, source_path, row["title"], row.get("source_url") or "")
            artifacts.update(extra)

        profile = model_profile_for_account(row["user_id"], row.get("analysis_model_profile_id") or None)
        style_summary = await summarize_style(profile, transcript_text, row["title"])
        assistant = None
        if row.get("assistant_id"):
            assistant = db.fetch_one("SELECT * FROM assistants WHERE id = ?", (row["assistant_id"],))
        content_blueprint = await generate_content_blueprint(
            profile,
            title=row["title"],
            transcript_text=transcript_text,
            style_summary=style_summary,
            agent_prompt=(assistant or {}).get("system_prompt", ""),
            generation_goal=(assistant or {}).get("generation_goal", ""),
        )
        combined_text = (
            f"{transcript_text}\n\n"
            "------\n"
            f"风格学习结论：\n{style_summary}\n\n"
            "------\n"
            f"二创文案：\n{(content_blueprint.get('rewrite') or {}).get('script', '')}\n\n"
            "------\n"
            f"分镜：\n{json.dumps(content_blueprint.get('storyboards') or [], ensure_ascii=False, indent=2)}"
        )
        kb_row = db.fetch_one("SELECT * FROM knowledge_bases WHERE id = ?", (row["knowledge_base_id"],))
        if not kb_row:
            raise RuntimeError("Knowledge base not found")
        document_id = make_id("doc")
        timestamp = utc_now()
        db.execute(
            """
            INSERT INTO knowledge_documents (
                id, knowledge_base_id, title, source_type, source_url, transcript_text,
                style_summary, combined_text, analysis_json, storyboard_json, source_artifact_json,
                analysis_model_profile_id, created_at, updated_at
            ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
            """,
            (
                document_id,
                row["knowledge_base_id"],
                row["title"],
                row["source_type"],
                row.get("source_url") or "",
                transcript_text,
                style_summary,
                combined_text,
                json.dumps(content_blueprint.get("analysis") or {}, ensure_ascii=False),
                json.dumps(content_blueprint.get("storyboards") or [], ensure_ascii=False),
                json.dumps(artifacts, ensure_ascii=False),
                profile["id"],
                timestamp,
                timestamp,
            ),
        )
        update_job_state(
            job_id,
            status="completed",
            artifacts={
                "document_id": document_id,
                "project_job_dir": str(job_dir),
                **artifacts,
            },
            result={
                "analysis": content_blueprint.get("analysis") or {},
                "rewrite": content_blueprint.get("rewrite") or {},
                "storyboards": content_blueprint.get("storyboards") or [],
                "document_id": document_id,
            },
        )
        db.execute(
            """
            UPDATE jobs
            SET transcript_text = ?, style_summary = ?, upload_status = ?, updated_at = ?
            WHERE id = ?
            """,
            (transcript_text, style_summary, "ready", timestamp, job_id),
        )
        db.execute(
            "UPDATE knowledge_bases SET sync_status = ?, updated_at = ? WHERE id = ?",
            ("ready", timestamp, kb_row["id"]),
        )
    except Exception as exc:
        update_job_state(job_id, status="failed", error=str(exc))


@app.on_event("startup")
def on_startup() -> None:
    db.init_schema()
    seed_defaults()


@app.get("/healthz")
def healthz() -> dict[str, Any]:
    return {
        "status": "ok",
        "dbPath": DB_PATH,
        "defaultExternalBaseUrl": DEFAULT_EXTERNAL_BASE_URL,
        "localModelBaseUrl": LOCAL_OPENAI_BASE_URL,
        "n8nBaseUrl": N8N_BASE_URL,
        "cutvideoBaseUrl": CUTVIDEO_BASE_URL,
        "huobaoBaseUrl": HUOBAO_BASE_URL,
    }


def seed_defaults() -> None:
    if not db.fetch_one("SELECT id FROM model_profiles WHERE is_default = 1 LIMIT 1"):
        profile_id = make_id("model")
        now = utc_now()
        db.execute(
            """
            INSERT INTO model_profiles (id, owner_account_id, name, provider, base_url, api_key, model_name, is_system, is_default, created_at, updated_at)
            VALUES (?, NULL, ?, ?, ?, ?, ?, 1, 1, ?, ?)
            """,
            (
                profile_id,
                "本机默认模型",
                "openai_compat",
                LOCAL_OPENAI_BASE_URL,
                LOCAL_OPENAI_API_KEY,
                LOCAL_OPENAI_MODEL,
                now,
                now,
            ),
        )
    if not db.fetch_one("SELECT id FROM accounts WHERE username = ?", ("kris",)):
        account_id = make_id("acct")
        password_hash, password_salt = create_password_hash("Asd123456.")
        now = utc_now()
        model_row = db.fetch_one("SELECT id FROM model_profiles WHERE is_default = 1 LIMIT 1")
        db.execute(
            """
            INSERT INTO accounts (
                id, username, password_hash, password_salt, display_name, role,
                approval_status, approved_by, approved_at, preferred_analysis_model_id,
                created_at, updated_at
            ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
            """,
            (
                account_id,
                "kris",
                password_hash,
                password_salt,
                "Kris",
                "super_admin",
                "approved",
                account_id,
                now,
                model_row["id"] if model_row else "",
                now,
                now,
            ),
        )
        project = ensure_default_project(account_id, username="kris")
        kb = ensure_user_kb(account_id, project["id"], username="kris")
        assistant_id = make_id("assistant")
        db.execute(
            """
            INSERT INTO assistants (id, user_id, project_id, name, description, system_prompt, generation_goal, config_json, model_profile_id, created_at, updated_at)
            VALUES (?, ?, ?, ?, ?, ?, ?, '{}', ?, ?, ?)
            """,
            (
                assistant_id,
                account_id,
                project["id"],
                "默认文案助手",
                "系统为超级管理员预置",
                "你是一个擅长学习短视频文案风格的 AI 助手。",
                "为用户生成稳定风格的短视频文案。",
                model_row["id"] if model_row else "",
                now,
                now,
            ),
        )
        db.execute(
            "INSERT INTO assistant_knowledge_bases (assistant_id, knowledge_base_id) VALUES (?, ?)",
            (assistant_id, kb["id"]),
        )


@app.post("/v2/auth/register")
def register(request: RegisterAccountRequest) -> dict[str, Any]:
    username = request.username.strip()
    password = request.password.strip()
    display_name = request.display_name.strip() or username
    if not username or not password:
        raise HTTPException(status_code=400, detail="username and password are required")
    if db.fetch_one("SELECT id FROM accounts WHERE username = ?", (username,)):
        raise HTTPException(status_code=409, detail="username already exists")
    account_id = make_id("acct")
    password_hash, password_salt = create_password_hash(password)
    now = utc_now()
    default_model = db.fetch_one("SELECT id FROM model_profiles WHERE is_default = 1 LIMIT 1")
    db.execute(
        """
        INSERT INTO accounts (
            id, username, password_hash, password_salt, display_name, role,
            approval_status, approved_by, approved_at, preferred_analysis_model_id,
            created_at, updated_at
        ) VALUES (?, ?, ?, ?, ?, 'user', 'pending', NULL, NULL, ?, ?, ?)
        """,
        (
            account_id,
            username,
            password_hash,
            password_salt,
            display_name,
            default_model["id"] if default_model else "",
            now,
            now,
        ),
    )
    ensure_default_project(account_id, username=username)
    account = db.fetch_one("SELECT * FROM accounts WHERE id = ?", (account_id,))
    return normalize_account(account)


@app.post("/v2/auth/login")
def login(request: LoginRequest) -> dict[str, Any]:
    account = db.fetch_one("SELECT * FROM accounts WHERE username = ?", (request.username.strip(),))
    if not account or not verify_password(request.password, account["password_hash"], account["password_salt"]):
        raise HTTPException(status_code=401, detail="Invalid credentials")
    token = secrets.token_urlsafe(32)
    db.execute(
        "INSERT INTO auth_tokens (token, account_id, created_at) VALUES (?, ?, ?)",
        (token, account["id"], utc_now()),
    )
    return {
        "token": token,
        "account": normalize_account(account),
        "default_external_base_url": DEFAULT_EXTERNAL_BASE_URL,
    }


@app.post("/v2/auth/logout")
def logout(account: dict[str, Any] = Depends(require_auth), authorization: str | None = Header(default=None)) -> dict[str, bool]:
    token = authorization.split(" ", 1)[1].strip()
    db.execute("DELETE FROM auth_tokens WHERE token = ?", (token,))
    return {"saved": True}


@app.get("/v2/me")
def me(account: dict[str, Any] = Depends(require_auth)) -> dict[str, Any]:
    return normalize_account(account)


@app.get("/v2/me/dashboard")
def dashboard(account: dict[str, Any] = Depends(require_approved)) -> dict[str, Any]:
    projects = [project_payload(row) for row in db.fetch_all("SELECT * FROM projects WHERE user_id = ? ORDER BY created_at ASC", (account["id"],))]
    knowledge_bases = [knowledge_base_payload(row) for row in db.fetch_all("SELECT * FROM knowledge_bases WHERE user_id = ? ORDER BY created_at DESC", (account["id"],))]
    assistants = [assistant_payload(row) for row in db.fetch_all("SELECT * FROM assistants WHERE user_id = ? ORDER BY created_at DESC", (account["id"],))]
    jobs = [job_payload(row) for row in db.fetch_all("SELECT * FROM jobs WHERE user_id = ? ORDER BY created_at DESC LIMIT 20", (account["id"],))]
    model_profiles = [normalize_model_profile(row) for row in db.fetch_all("SELECT * FROM model_profiles WHERE owner_account_id IS NULL OR owner_account_id = ? ORDER BY is_default DESC, created_at ASC", (account["id"],))]
    return {
        "account": normalize_account(account),
        "projects": projects,
        "knowledge_bases": knowledge_bases,
        "assistants": assistants,
        "recent_jobs": jobs,
        "model_profiles": model_profiles,
    }


@app.get("/v2/projects")
def list_projects(account: dict[str, Any] = Depends(require_approved)) -> list[dict[str, Any]]:
    return [project_payload(row) for row in db.fetch_all("SELECT * FROM projects WHERE user_id = ? ORDER BY created_at ASC", (account["id"],))]


@app.post("/v2/projects")
def create_project(request: ProjectCreateRequest, account: dict[str, Any] = Depends(require_approved)) -> dict[str, Any]:
    project_id = make_id("project")
    now = utc_now()
    db.execute(
        """
        INSERT INTO projects (id, user_id, name, description, created_at, updated_at)
        VALUES (?, ?, ?, ?, ?, ?)
        """,
        (
            project_id,
            account["id"],
            request.name.strip(),
            request.description.strip(),
            now,
            now,
        ),
    )
    ensure_user_kb(account["id"], project_id, username=account["username"])
    return project_payload(db.fetch_one("SELECT * FROM projects WHERE id = ?", (project_id,)))


@app.get("/v2/content-sources")
def list_content_sources(
    project_id: str | None = Query(default=None),
    account: dict[str, Any] = Depends(require_approved),
) -> list[dict[str, Any]]:
    if project_id:
        resolve_target_project(account["id"], project_id, username=account["username"])
        rows = db.fetch_all(
            "SELECT * FROM content_sources WHERE user_id = ? AND project_id = ? ORDER BY created_at DESC",
            (account["id"], project_id),
        )
    else:
        rows = db.fetch_all("SELECT * FROM content_sources WHERE user_id = ? ORDER BY created_at DESC", (account["id"],))
    return [content_source_payload(row) for row in rows]


@app.post("/v2/content-sources")
def create_content_source_api(request: ContentSourceCreateRequest, account: dict[str, Any] = Depends(require_approved)) -> dict[str, Any]:
    project = resolve_target_project(account["id"], request.project_id or None, username=account["username"])
    row = create_content_source(
        account_id=account["id"],
        project_id=project["id"],
        source_kind=request.source_kind.strip(),
        platform=request.platform.strip(),
        handle=request.handle.strip(),
        source_url=request.source_url.strip(),
        title=request.title.strip(),
        local_path=request.local_path.strip(),
        metadata=request.metadata,
    )
    return content_source_payload(row)


@app.get("/v2/model-profiles")
def list_model_profiles(account: dict[str, Any] = Depends(require_approved)) -> list[dict[str, Any]]:
    rows = db.fetch_all(
        "SELECT * FROM model_profiles WHERE owner_account_id IS NULL OR owner_account_id = ? ORDER BY is_default DESC, is_system DESC, created_at ASC",
        (account["id"],),
    )
    return [normalize_model_profile(row) for row in rows]


@app.post("/v2/model-profiles")
def create_model_profile(request: ModelProfileRequest, account: dict[str, Any] = Depends(require_approved)) -> dict[str, Any]:
    model_id = make_id("model")
    now = utc_now()
    if request.is_default:
        db.execute("UPDATE model_profiles SET is_default = 0 WHERE owner_account_id = ?", (account["id"],))
    db.execute(
        """
        INSERT INTO model_profiles (id, owner_account_id, name, provider, base_url, api_key, model_name, is_system, is_default, created_at, updated_at)
        VALUES (?, ?, ?, 'openai_compat', ?, ?, ?, 0, ?, ?, ?)
        """,
        (model_id, account["id"], request.name.strip(), request.base_url.strip(), request.api_key.strip(), request.model_name.strip(), 1 if request.is_default else 0, now, now),
    )
    row = db.fetch_one("SELECT * FROM model_profiles WHERE id = ?", (model_id,))
    return normalize_model_profile(row)


@app.post("/v2/me/preferences/analysis-model")
def set_preferred_analysis_model(request: PreferredModelRequest, account: dict[str, Any] = Depends(require_approved)) -> dict[str, Any]:
    model = db.fetch_one(
        "SELECT * FROM model_profiles WHERE id = ? AND (owner_account_id IS NULL OR owner_account_id = ?)",
        (request.model_profile_id, account["id"]),
    )
    if not model:
        raise HTTPException(status_code=404, detail="Model profile not found")
    db.execute(
        "UPDATE accounts SET preferred_analysis_model_id = ?, updated_at = ? WHERE id = ?",
        (request.model_profile_id, utc_now(), account["id"]),
    )
    account = db.fetch_one("SELECT * FROM accounts WHERE id = ?", (account["id"],))
    return normalize_account(account)


@app.get("/v2/knowledge-bases")
def list_knowledge_bases(account: dict[str, Any] = Depends(require_approved)) -> list[dict[str, Any]]:
    return [knowledge_base_payload(row) for row in db.fetch_all("SELECT * FROM knowledge_bases WHERE user_id = ? ORDER BY created_at DESC", (account["id"],))]


@app.post("/v2/knowledge-bases")
def create_knowledge_base(request: KnowledgeBaseCreateRequest, account: dict[str, Any] = Depends(require_approved)) -> dict[str, Any]:
    project = resolve_target_project(account["id"], request.project_id or None, username=account["username"])
    kb_id = make_id("kb")
    now = utc_now()
    db.execute(
        """
        INSERT INTO knowledge_bases (id, user_id, project_id, name, description, sync_status, created_at, updated_at)
        VALUES (?, ?, ?, ?, ?, 'ready', ?, ?)
        """,
        (kb_id, account["id"], project["id"], request.name.strip(), request.description.strip(), now, now),
    )
    row = db.fetch_one("SELECT * FROM knowledge_bases WHERE id = ?", (kb_id,))
    return knowledge_base_payload(row)


@app.get("/v2/knowledge-bases/{knowledge_base_id}/documents")
def list_knowledge_documents(knowledge_base_id: str, account: dict[str, Any] = Depends(require_approved)) -> list[dict[str, Any]]:
    kb = db.fetch_one("SELECT * FROM knowledge_bases WHERE id = ? AND user_id = ?", (knowledge_base_id, account["id"]))
    if not kb:
        raise HTTPException(status_code=404, detail="Knowledge base not found")
    rows = db.fetch_all("SELECT * FROM knowledge_documents WHERE knowledge_base_id = ? ORDER BY created_at DESC", (knowledge_base_id,))
    return [document_payload(row) for row in rows]


@app.get("/v2/explore/jobs")
def list_jobs(account: dict[str, Any] = Depends(require_approved)) -> list[dict[str, Any]]:
    return [job_payload(row) for row in db.fetch_all("SELECT * FROM jobs WHERE user_id = ? ORDER BY created_at DESC", (account["id"],))]


@app.get("/v2/explore/jobs/{job_id}")
def get_job(job_id: str, account: dict[str, Any] = Depends(require_approved)) -> dict[str, Any]:
    row = db.fetch_one("SELECT * FROM jobs WHERE id = ? AND user_id = ?", (job_id, account["id"]))
    if not row:
        raise HTTPException(status_code=404, detail="Job not found")
    return job_payload(row)


@app.get("/v2/explore/jobs/{job_id}/events")
def get_job_events(job_id: str, account: dict[str, Any] = Depends(require_approved)) -> list[dict[str, Any]]:
    row = db.fetch_one("SELECT id FROM jobs WHERE id = ? AND user_id = ?", (job_id, account["id"]))
    if not row:
        raise HTTPException(status_code=404, detail="Job not found")
    return [
        job_event_payload(item)
        for item in db.fetch_all("SELECT * FROM job_events WHERE job_id = ? ORDER BY created_at ASC", (job_id,))
    ]


def resolve_target_kb(account_id: str, requested_kb_id: str | None, project_id: str = "", username: str = "默认用户") -> dict[str, Any]:
    if requested_kb_id:
        kb = db.fetch_one("SELECT * FROM knowledge_bases WHERE id = ? AND user_id = ?", (requested_kb_id, account_id))
        if kb:
            if project_id and kb.get("project_id") and kb.get("project_id") != project_id:
                raise HTTPException(status_code=400, detail="Knowledge base does not belong to target project")
            return kb
        raise HTTPException(status_code=404, detail="Knowledge base not found")
    return ensure_user_kb(account_id, project_id, username=username)


@app.post("/v2/explore/text")
async def create_text_job(request: ExploreTextRequest, account: dict[str, Any] = Depends(require_approved)) -> dict[str, Any]:
    project = resolve_target_project(account["id"], request.project_id or None, username=account["username"])
    kb = resolve_target_kb(account["id"], request.knowledge_base_id, project["id"], username=account["username"])
    assistant = resolve_target_assistant(account["id"], request.assistant_id, project["id"])
    profile = model_profile_for_account(account["id"], request.analysis_model_profile_id)
    source = create_content_source(
        account_id=account["id"],
        project_id=project["id"],
        source_kind="inline_text",
        title=request.title.strip(),
        metadata={"content_preview": request.content[:280]},
    )
    job_row = create_job_record(
        account_id=account["id"],
        project_id=project["id"],
        knowledge_base_id=kb["id"],
        source_type="text",
        line_type="analysis",
        workflow_key="analysis_pipeline",
        title=request.title.strip(),
        language="zh-CN",
        assistant_id=(assistant or {}).get("id"),
        content_source_id=source["id"],
        artifacts={"input_text": request.content},
        analysis_model_profile_id=profile["id"],
    )
    return job_payload(await trigger_orchestrated_job(job_row))


@app.post("/v2/explore/video-link")
async def create_video_link_job(request: ExploreVideoLinkRequest, account: dict[str, Any] = Depends(require_approved)) -> dict[str, Any]:
    project = resolve_target_project(account["id"], request.project_id or None, username=account["username"])
    kb = resolve_target_kb(account["id"], request.knowledge_base_id, project["id"], username=account["username"])
    assistant = resolve_target_assistant(account["id"], request.assistant_id, project["id"])
    profile = model_profile_for_account(account["id"], request.analysis_model_profile_id)
    source = create_content_source(
        account_id=account["id"],
        project_id=project["id"],
        source_kind="video_link",
        source_url=request.video_url.strip(),
        title=(request.title or "短视频素材").strip(),
        metadata={"platform": "video_link"},
    )
    job_row = create_job_record(
        account_id=account["id"],
        project_id=project["id"],
        knowledge_base_id=kb["id"],
        source_type="video_link",
        line_type="analysis",
        workflow_key="analysis_pipeline",
        title=(request.title or "短视频素材").strip(),
        language=request.language,
        source_url=request.video_url.strip(),
        assistant_id=(assistant or {}).get("id"),
        content_source_id=source["id"],
        artifacts={},
        analysis_model_profile_id=profile["id"],
    )
    return job_payload(await trigger_orchestrated_job(job_row))


@app.post("/v2/explore/upload-video")
async def upload_video(
    file: UploadFile = File(...),
    title: str = Form(""),
    project_id: str = Form(""),
    knowledge_base_id: str = Form(""),
    assistant_id: str = Form(""),
    analysis_model_profile_id: str = Form(""),
    account: dict[str, Any] = Depends(require_approved),
) -> dict[str, Any]:
    project = resolve_target_project(account["id"], project_id or None, username=account["username"])
    kb = resolve_target_kb(account["id"], knowledge_base_id or None, project["id"], username=account["username"])
    assistant = resolve_target_assistant(account["id"], assistant_id or None, project["id"])
    profile = model_profile_for_account(account["id"], analysis_model_profile_id or None)
    job_id = make_id("job_upload")
    job_dir = JOBS_DIR / job_id
    job_dir.mkdir(parents=True, exist_ok=True)
    suffix = Path(file.filename or "upload.mp4").suffix or ".mp4"
    target_path = job_dir / f"source{suffix}"
    with target_path.open("wb") as handle:
        shutil.copyfileobj(file.file, handle)
    source = create_content_source(
        account_id=account["id"],
        project_id=project["id"],
        source_kind="upload_video",
        source_url=file.filename or "",
        title=(title or file.filename or "上传视频素材").strip(),
        local_path=str(target_path),
        metadata={"filename": file.filename or "", "size_bytes": target_path.stat().st_size},
    )
    job_row = create_job_record(
        account_id=account["id"],
        project_id=project["id"],
        knowledge_base_id=kb["id"],
        source_type="upload_video",
        line_type="analysis",
        workflow_key="analysis_pipeline",
        title=(title or file.filename or "上传视频素材").strip(),
        source_url=file.filename or "",
        assistant_id=(assistant or {}).get("id"),
        content_source_id=source["id"],
        artifacts={"uploaded_path": str(target_path)},
        analysis_model_profile_id=profile["id"],
    )
    return job_payload(await trigger_orchestrated_job(job_row))


@app.post("/v2/pipelines/real-cut")
async def create_real_cut_job(request: RealCutJobRequest, account: dict[str, Any] = Depends(require_approved)) -> dict[str, Any]:
    project = resolve_target_project(account["id"], request.project_id or None, username=account["username"])
    kb = ensure_user_kb(account["id"], project["id"], username=account["username"])
    source = create_content_source(
        account_id=account["id"],
        project_id=project["id"],
        source_kind="real_cut_input",
        title=request.title.strip(),
        local_path=request.input_dir.strip(),
        metadata={"line_type": "real_cut"},
    )
    job_row = create_job_record(
        account_id=account["id"],
        project_id=project["id"],
        knowledge_base_id=kb["id"],
        source_type="real_cut",
        line_type="real_cut",
        workflow_key="real_cut_pipeline",
        title=request.title.strip(),
        source_url=request.input_dir.strip(),
        content_source_id=source["id"],
        artifacts={
            "cutvideo_request": {
                "base_config": request.base_config.strip() or CUTVIDEO_BASE_CONFIG,
                "name": request.title.strip(),
                "input_dir": request.input_dir.strip(),
                "objective": request.objective,
                "target_duration_sec": request.target_duration_sec,
                "target_aspect_ratio": request.target_aspect_ratio,
                "ideal_segment_duration_sec": request.ideal_segment_duration_sec,
                "max_segment_duration_sec": request.max_segment_duration_sec,
                "transcript_backend": request.transcript_backend,
                "transcript_device": request.transcript_device,
                "review_enabled": request.review_enabled,
                "dry_run": request.dry_run,
            }
        },
    )
    return job_payload(await trigger_orchestrated_job(job_row))


@app.post("/v2/pipelines/ai-video")
async def create_ai_video_job(request: AiVideoJobRequest, account: dict[str, Any] = Depends(require_approved)) -> dict[str, Any]:
    source_job = None
    source_project_id = ""
    source_kb_id = ""
    if request.source_job_id.strip():
        source_job = db.fetch_one("SELECT * FROM jobs WHERE id = ? AND user_id = ?", (request.source_job_id.strip(), account["id"]))
        if not source_job:
            raise HTTPException(status_code=404, detail="Source job not found")
        if source_job["status"] != "completed":
            raise HTTPException(status_code=409, detail="Source job must be completed before AI video generation")
        source_project_id = source_job.get("project_id", "")
        source_kb_id = source_job.get("knowledge_base_id", "")

    requested_project_id = request.project_id or source_project_id
    project = resolve_target_project(account["id"], requested_project_id or None, username=account["username"])
    kb = resolve_target_kb(account["id"], request.knowledge_base_id or source_kb_id or None, project["id"], username=account["username"])
    assistant = resolve_target_assistant(account["id"], request.assistant_id or None, project["id"])
    source = create_content_source(
        account_id=account["id"],
        project_id=project["id"],
        source_kind="ai_video_brief",
        title=request.title.strip(),
        metadata={"source_job_id": request.source_job_id.strip()},
    )
    job_row = create_job_record(
        account_id=account["id"],
        project_id=project["id"],
        knowledge_base_id=kb["id"],
        source_type="ai_video",
        line_type="ai_video",
        workflow_key="ai_video_pipeline",
        title=request.title.strip(),
        assistant_id=(assistant or {}).get("id"),
        content_source_id=source["id"],
        artifacts={
            "brief": request.brief,
            "style": request.style,
            "shots": request.shots,
            "image_provider": request.image_provider,
            "image_model": request.image_model,
            "video_provider": request.video_provider,
            "video_model": request.video_model,
            "aspect_ratio": request.aspect_ratio,
            "duration": request.duration,
            "source_job_id": request.source_job_id.strip(),
        },
    )
    return job_payload(await trigger_orchestrated_job(job_row))


@app.get("/v2/assistants")
def list_assistants(account: dict[str, Any] = Depends(require_approved)) -> list[dict[str, Any]]:
    return [assistant_payload(row) for row in db.fetch_all("SELECT * FROM assistants WHERE user_id = ? ORDER BY created_at DESC", (account["id"],))]


@app.post("/v2/assistants")
def create_assistant(request: AssistantCreateRequest, account: dict[str, Any] = Depends(require_approved)) -> dict[str, Any]:
    assistant_id = make_id("assistant")
    now = utc_now()
    project = resolve_target_project(account["id"], request.project_id or None, username=account["username"])
    model_profile = model_profile_for_account(account["id"], request.model_profile_id or None)
    db.execute(
        """
        INSERT INTO assistants (id, user_id, project_id, name, description, system_prompt, generation_goal, config_json, model_profile_id, created_at, updated_at)
        VALUES (?, ?, ?, ?, ?, ?, ?, '{}', ?, ?, ?)
        """,
        (
            assistant_id,
            account["id"],
            project["id"],
            request.name.strip(),
            request.description.strip(),
            request.system_prompt.strip(),
            request.generation_goal.strip(),
            model_profile["id"],
            now,
            now,
        ),
    )
    for kb_id in request.knowledge_base_ids:
        kb = db.fetch_one("SELECT id FROM knowledge_bases WHERE id = ? AND user_id = ?", (kb_id, account["id"]))
        if kb:
            db.execute("INSERT OR IGNORE INTO assistant_knowledge_bases (assistant_id, knowledge_base_id) VALUES (?, ?)", (assistant_id, kb_id))
    return assistant_payload(db.fetch_one("SELECT * FROM assistants WHERE id = ?", (assistant_id,)))


@app.patch("/v2/assistants/{assistant_id}")
def update_assistant(assistant_id: str, request: AssistantUpdateRequest, account: dict[str, Any] = Depends(require_approved)) -> dict[str, Any]:
    current = db.fetch_one("SELECT * FROM assistants WHERE id = ? AND user_id = ?", (assistant_id, account["id"]))
    if not current:
        raise HTTPException(status_code=404, detail="Assistant not found")
    project_id = current.get("project_id", "")
    if request.project_id is not None:
        project_id = resolve_target_project(account["id"], request.project_id, username=account["username"])["id"]
    payload = {
        "name": request.name if request.name is not None else current["name"],
        "description": request.description if request.description is not None else current.get("description", ""),
        "system_prompt": request.system_prompt if request.system_prompt is not None else current.get("system_prompt", ""),
        "generation_goal": request.generation_goal if request.generation_goal is not None else current.get("generation_goal", ""),
        "project_id": project_id,
        "model_profile_id": current.get("model_profile_id", ""),
    }
    if request.model_profile_id is not None:
        payload["model_profile_id"] = model_profile_for_account(account["id"], request.model_profile_id)["id"]
    db.execute(
        """
        UPDATE assistants
        SET project_id = ?, name = ?, description = ?, system_prompt = ?, generation_goal = ?, model_profile_id = ?, updated_at = ?
        WHERE id = ?
        """,
        (
            payload["project_id"],
            payload["name"],
            payload["description"],
            payload["system_prompt"],
            payload["generation_goal"],
            payload["model_profile_id"],
            utc_now(),
            assistant_id,
        ),
    )
    if request.knowledge_base_ids is not None:
        db.execute("DELETE FROM assistant_knowledge_bases WHERE assistant_id = ?", (assistant_id,))
        for kb_id in request.knowledge_base_ids:
            kb = db.fetch_one("SELECT id FROM knowledge_bases WHERE id = ? AND user_id = ?", (kb_id, account["id"]))
            if kb:
                db.execute("INSERT OR IGNORE INTO assistant_knowledge_bases (assistant_id, knowledge_base_id) VALUES (?, ?)", (assistant_id, kb_id))
    return assistant_payload(db.fetch_one("SELECT * FROM assistants WHERE id = ?", (assistant_id,)))


@app.get("/v2/agents")
def list_agents(account: dict[str, Any] = Depends(require_approved)) -> list[dict[str, Any]]:
    return list_assistants(account)


@app.post("/v2/agents")
def create_agent(request: AssistantCreateRequest, account: dict[str, Any] = Depends(require_approved)) -> dict[str, Any]:
    return create_assistant(request, account)


@app.patch("/v2/agents/{assistant_id}")
def update_agent(assistant_id: str, request: AssistantUpdateRequest, account: dict[str, Any] = Depends(require_approved)) -> dict[str, Any]:
    return update_assistant(assistant_id, request, account)


@app.post("/v2/assistants/{assistant_id}/generate")
async def generate_copy(assistant_id: str, request: GenerateCopyRequest, account: dict[str, Any] = Depends(require_approved)) -> dict[str, Any]:
    assistant = db.fetch_one("SELECT * FROM assistants WHERE id = ? AND user_id = ?", (assistant_id, account["id"]))
    if not assistant:
        raise HTTPException(status_code=404, detail="Assistant not found")
    kb_ids = request.knowledge_base_ids or [row["knowledge_base_id"] for row in db.fetch_all("SELECT knowledge_base_id FROM assistant_knowledge_bases WHERE assistant_id = ?", (assistant_id,))]
    used_documents: list[dict[str, Any]] = []
    excerpts: list[str] = []
    for kb_id in kb_ids:
        docs = db.fetch_all("SELECT * FROM knowledge_documents WHERE knowledge_base_id = ? ORDER BY created_at DESC LIMIT 3", (kb_id,))
        for doc in docs:
            payload = document_payload(doc)
            used_documents.append(payload)
            excerpt = payload["combined_text"] or payload["style_summary"] or payload["transcript_text"]
            excerpts.append(f"[{payload['title']}]\n{excerpt[:1200]}")
    prompt_excerpt = "\n\n".join(excerpts)[:6000]
    system_prompt = assistant.get("system_prompt") or "你是文案助手。"
    generation_goal = assistant.get("generation_goal") or "生成短视频文案。"
    user_prompt = (
        f"任务目标：{generation_goal}\n"
        f"创作需求：{request.brief}\n"
        f"平台：{request.platform}\n"
        f"受众：{request.audience}\n"
        f"额外要求：{request.extra_requirements or '无'}\n\n"
        f"参考知识库素材：\n{prompt_excerpt or '暂无参考素材，请按通用短视频结构输出。'}\n\n"
        "请输出完整文案，包含标题、开场钩子、正文结构和结尾行动指令。"
    )
    profile = model_profile_for_account(account["id"], assistant.get("model_profile_id") or None)
    content = await call_model(profile, system_prompt, user_prompt, temperature=0.7)
    return {
        "assistant_id": assistant_id,
        "knowledge_base_ids": kb_ids,
        "content": content,
        "prompt_excerpt": prompt_excerpt[:2000],
        "used_documents": used_documents,
    }


def load_owned_job(job_id: str, account_id: str) -> dict[str, Any]:
    row = db.fetch_one("SELECT * FROM jobs WHERE id = ? AND user_id = ?", (job_id, account_id))
    if not row:
        raise HTTPException(status_code=404, detail="Job not found")
    return row


def load_internal_job(job_id: str) -> dict[str, Any]:
    row = db.fetch_one("SELECT * FROM jobs WHERE id = ?", (job_id,))
    if not row:
        raise HTTPException(status_code=404, detail="Job not found")
    return row


def parse_job_artifacts(row: dict[str, Any]) -> dict[str, Any]:
    raw = row.get("artifacts_json") or "{}"
    try:
        return json.loads(raw)
    except json.JSONDecodeError:
        return {}


def parse_job_result(row: dict[str, Any]) -> dict[str, Any]:
    raw = row.get("result_json") or "{}"
    try:
        data = json.loads(raw)
        return data if isinstance(data, dict) else {}
    except json.JSONDecodeError:
        return {}


def extract_source_storyboards(source_job: dict[str, Any] | None) -> list[dict[str, Any]]:
    if not source_job:
        return []
    return coerce_storyboards(parse_job_result(source_job).get("storyboards"))


def resolve_internal_job_id(request: InternalStepRequest | None, query_job_id: str = "") -> str:
    resolved = (query_job_id or "").strip()
    if not resolved and request is not None:
        resolved = (
            request.job_id
            or request.jobId
            or str(request.payload.get("job_id") or request.payload.get("jobId") or "")
        ).strip()
    return resolved


def load_step_job(request: InternalStepRequest | None, query_job_id: str, workflow_key: str) -> dict[str, Any]:
    resolved_job_id = resolve_internal_job_id(request, query_job_id)
    if resolved_job_id:
        return load_internal_job(resolved_job_id)
    row = db.fetch_one(
        """
        SELECT * FROM jobs
        WHERE workflow_key = ? AND status IN ('pending', 'queued')
        ORDER BY created_at ASC
        LIMIT 1
        """,
        (workflow_key,),
    )
    if not row:
        raise HTTPException(status_code=400, detail="job_id is required")
    return row


@app.get("/internal/jobs/{job_id}/context")
def internal_job_context(job_id: str, _: bool = Depends(require_orchestrator)) -> dict[str, Any]:
    return job_context_payload(load_internal_job(job_id))


@app.post("/internal/jobs/steps/analyze")
async def internal_run_analysis(
    request: InternalStepRequest | None = Body(default=None),
    job_id: str = Query(default=""),
    _: bool = Depends(require_orchestrator),
) -> dict[str, Any]:
    row = load_step_job(request, job_id, "analysis_pipeline")
    await process_job(row["id"])
    return job_context_payload(load_internal_job(row["id"]))


@app.post("/internal/jobs/steps/real-cut/submit")
async def internal_real_cut_submit(
    request: InternalStepRequest | None = Body(default=None),
    job_id: str = Query(default=""),
    _: bool = Depends(require_orchestrator),
) -> dict[str, Any]:
    if not cutvideo_client.enabled:
        raise HTTPException(status_code=503, detail="CutVideo is not configured")
    row = load_step_job(request, job_id, "real_cut_pipeline")
    artifacts = parse_job_artifacts(row)
    cutvideo_request = artifacts.get("cutvideo_request") or {}
    if not isinstance(cutvideo_request, dict):
        raise HTTPException(status_code=400, detail="Invalid cutvideo request payload")
    append_job_event(row["id"], "cutvideo.submit.requested", cutvideo_request)
    submit_result = await cutvideo_client.submit_job(cutvideo_request)
    task_id = str(submit_result.get("task_id") or "")
    updated = update_job_state(
        row["id"],
        status="processing",
        provider_name="cutvideo",
        provider_task_id=task_id,
        result={"cutvideo_submit": submit_result},
    )
    return job_context_payload(updated)


@app.post("/internal/jobs/steps/real-cut/poll")
async def internal_real_cut_poll(
    request: InternalStepRequest | None = Body(default=None),
    job_id: str = Query(default=""),
    _: bool = Depends(require_orchestrator),
) -> dict[str, Any]:
    row = load_step_job(request, job_id, "real_cut_pipeline")
    if not row.get("provider_task_id"):
        raise HTTPException(status_code=409, detail="CutVideo task has not been submitted")
    task_payload = await cutvideo_client.get_task(row["provider_task_id"])
    status = str(task_payload.get("status") or "").lower()
    run_payload: dict[str, Any] = {}
    artifacts: dict[str, Any] = {"cutvideo_task": task_payload}
    next_status = row["status"]
    error = row.get("error", "")
    if status == "completed":
        next_status = "completed"
        run_id = str(task_payload.get("run_id") or "")
        if run_id:
            run_payload = await cutvideo_client.get_run(run_id)
            artifacts["cutvideo_run"] = run_payload
    elif status == "failed":
        next_status = "failed"
        error = str(task_payload.get("error") or "CutVideo task failed")
    else:
        next_status = "processing"

    updated = update_job_state(
        row["id"],
        status=next_status,
        error=error,
        provider_name="cutvideo",
        provider_task_id=row["provider_task_id"],
        artifacts=artifacts,
        result={"cutvideo_run": run_payload} if run_payload else {"cutvideo_task": task_payload},
    )
    return job_context_payload(updated)


@app.post("/internal/jobs/steps/real-cut/run")
async def internal_real_cut_run(
    request: InternalStepRequest | None = Body(default=None),
    job_id: str = Query(default=""),
    _: bool = Depends(require_orchestrator),
) -> dict[str, Any]:
    if not cutvideo_client.enabled:
        raise HTTPException(status_code=503, detail="CutVideo is not configured")

    row = load_step_job(request, job_id, "real_cut_pipeline")
    if not row.get("provider_task_id"):
        artifacts = parse_job_artifacts(row)
        cutvideo_request = artifacts.get("cutvideo_request") or {}
        if not isinstance(cutvideo_request, dict):
            raise HTTPException(status_code=400, detail="Invalid cutvideo request payload")
        submit_result = await cutvideo_client.submit_job(cutvideo_request)
        row = update_job_state(
            row["id"],
            status="processing",
            provider_name="cutvideo",
            provider_task_id=str(submit_result.get("task_id") or ""),
            result={"cutvideo_submit": submit_result},
        )

    deadline = now_ts() + HUOBAO_MAX_WAIT_SEC
    while True:
        task_payload = await cutvideo_client.get_task(row["provider_task_id"])
        status = str(task_payload.get("status") or "").lower()
        if status == "completed":
            run_payload: dict[str, Any] = {}
            run_id = str(task_payload.get("run_id") or "")
            if run_id:
                run_payload = await cutvideo_client.get_run(run_id)
            updated = update_job_state(
                row["id"],
                status="completed",
                provider_name="cutvideo",
                provider_task_id=row["provider_task_id"],
                artifacts={"cutvideo_task": task_payload, "cutvideo_run": run_payload},
                result={"cutvideo_task": task_payload, "cutvideo_run": run_payload},
            )
            return job_context_payload(updated)
        if status == "failed":
            updated = update_job_state(
                row["id"],
                status="failed",
                error=str(task_payload.get("error") or "CutVideo task failed"),
                provider_name="cutvideo",
                provider_task_id=row["provider_task_id"],
                artifacts={"cutvideo_task": task_payload},
                result={"cutvideo_task": task_payload},
            )
            return job_context_payload(updated)
        if now_ts() >= deadline:
            updated = update_job_state(
                row["id"],
                status="failed",
                error="CutVideo task timed out",
                provider_name="cutvideo",
                provider_task_id=row["provider_task_id"],
                artifacts={"cutvideo_task": task_payload},
                result={"cutvideo_task": task_payload},
            )
            return job_context_payload(updated)
        await asyncio.sleep(CUTVIDEO_POLL_INTERVAL_SEC)
        row = load_internal_job(row["id"])


@app.post("/internal/jobs/steps/ai-video/render")
async def internal_ai_video_render(
    request: InternalStepRequest | None = Body(default=None),
    job_id: str = Query(default=""),
    _: bool = Depends(require_orchestrator),
) -> dict[str, Any]:
    if not huobao_client.enabled:
        raise HTTPException(status_code=503, detail="Huobao is not configured")

    row = load_step_job(request, job_id, "ai_video_pipeline")
    artifacts = parse_job_artifacts(row)
    assistant = db.fetch_one("SELECT * FROM assistants WHERE id = ?", (row["assistant_id"],)) if row.get("assistant_id") else None
    source_job = None
    source_storyboards: list[dict[str, Any]] = []
    source_job_id = str(artifacts.get("source_job_id") or "").strip()
    if source_job_id:
        source_job = db.fetch_one("SELECT * FROM jobs WHERE id = ? AND user_id = ?", (source_job_id, row["user_id"]))
        if source_job:
            source_storyboards = extract_source_storyboards(source_job)

    if source_storyboards:
        storyboard_items = source_storyboards[: max(int(artifacts.get("shots") or 4), 1)]
    else:
        profile = model_profile_for_account(row["user_id"], row.get("analysis_model_profile_id") or None)
        blueprint = await generate_content_blueprint(
            profile,
            title=row["title"],
            transcript_text=str(artifacts.get("brief") or row["title"]),
            style_summary=str(artifacts.get("style") or ""),
            agent_prompt=(assistant or {}).get("system_prompt", ""),
            generation_goal=(assistant or {}).get("generation_goal", "") or "生成适合视频模型的分镜与提示词",
        )
        storyboard_items = coerce_storyboards(blueprint.get("storyboards"))[: max(int(artifacts.get("shots") or 4), 1)]

    if not storyboard_items:
        raise HTTPException(status_code=400, detail="No storyboards available for AI video rendering")

    drama_payload = await huobao_client.create_drama(
        {
            "title": row["title"],
            "description": str(artifacts.get("brief") or row["title"]),
            "style": str(artifacts.get("style") or "realistic"),
            "genre": "short_video",
            "tags": "storyforge",
        }
    )
    drama_id = str(drama_payload.get("id") or "")
    if not drama_id:
        raise RuntimeError("Huobao did not return drama id")

    update_job_state(
        row["id"],
        status="processing",
        provider_name="huobao-drama",
        provider_task_id=drama_id,
        result={"huobao_drama": drama_payload},
    )

    rendered_scenes: list[dict[str, Any]] = []
    image_provider = str(artifacts.get("image_provider") or "openai")
    image_model = str(artifacts.get("image_model") or "")
    video_provider = str(artifacts.get("video_provider") or "doubao")
    video_model = str(artifacts.get("video_model") or "")
    aspect_ratio = str(artifacts.get("aspect_ratio") or "9:16")
    image_size = huobao_image_size_for_aspect_ratio(aspect_ratio)
    duration = int(artifacts.get("duration") or 5)
    style = str(artifacts.get("style") or "realistic")

    for idx, storyboard in enumerate(storyboard_items, start=1):
        first_prompt = str(storyboard.get("first_frame_prompt") or storyboard.get("visual") or storyboard.get("title") or row["title"])
        last_prompt = str(storyboard.get("last_frame_prompt") or storyboard.get("visual") or storyboard.get("title") or row["title"])
        video_prompt = str(storyboard.get("video_prompt") or storyboard.get("narration") or storyboard.get("title") or row["title"])

        first_image = await huobao_client.generate_image(
            {
                "drama_id": drama_id,
                "image_type": "storyboard",
                "frame_type": "first",
                "prompt": first_prompt,
                "provider": image_provider,
                "model": image_model,
                "size": image_size,
                "style": style,
            }
        )
        last_image = await huobao_client.generate_image(
            {
                "drama_id": drama_id,
                "image_type": "storyboard",
                "frame_type": "last",
                "prompt": last_prompt,
                "provider": image_provider,
                "model": image_model,
                "size": image_size,
                "style": style,
            }
        )

        first_ready = await wait_for_huobao_image(str(first_image.get("id") or ""))
        last_ready = await wait_for_huobao_image(str(last_image.get("id") or ""))
        if str(first_ready.get("status") or "").lower() != "completed":
            raise RuntimeError(f"First frame generation failed for scene {idx}")
        if str(last_ready.get("status") or "").lower() != "completed":
            raise RuntimeError(f"Last frame generation failed for scene {idx}")

        first_frame_url = first_ready.get("image_url") or first_ready.get("local_path")
        last_frame_url = last_ready.get("image_url") or last_ready.get("local_path")
        if not first_frame_url or not last_frame_url:
            raise RuntimeError(f"Huobao image output missing for scene {idx}")

        video_payload = await huobao_client.generate_video(
            {
                "drama_id": drama_id,
                "prompt": video_prompt,
                "provider": video_provider,
                "model": video_model,
                "reference_mode": "first_last",
                "first_frame_url": first_frame_url,
                "last_frame_url": last_frame_url,
                "aspect_ratio": aspect_ratio,
                "duration": duration,
                "style": style,
            }
        )
        video_ready = await wait_for_huobao_video(str(video_payload.get("id") or ""))
        if str(video_ready.get("status") or "").lower() != "completed":
            raise RuntimeError(f"Video generation failed for scene {idx}")

        rendered_scenes.append(
            {
                "shot_index": storyboard.get("shot_index", idx),
                "title": storyboard.get("title", f"镜头{idx}"),
                "narration": storyboard.get("narration", ""),
                "first_frame": first_ready,
                "last_frame": last_ready,
                "video": video_ready,
            }
        )

    updated = update_job_state(
        row["id"],
        status="completed",
        provider_name="huobao-drama",
        provider_task_id=drama_id,
        artifacts={
            "huobao_drama_id": drama_id,
            "source_job_id": source_job_id,
        },
        result={
            "huobao_drama": drama_payload,
            "rendered_scenes": rendered_scenes,
            "storyboards": storyboard_items,
        },
    )
    return job_context_payload(updated)


@app.post("/internal/jobs/{job_id}/status")
def internal_update_job_status(job_id: str, request: JobStatusUpdateRequest, _: bool = Depends(require_orchestrator)) -> dict[str, Any]:
    updated = update_job_state(
        job_id,
        status=request.status,
        error=request.error,
        provider_name=request.provider_name or None,
        provider_task_id=request.provider_task_id or None,
        artifacts=request.artifacts,
        result=request.result,
    )
    return job_context_payload(updated)


@app.get("/v2/admin/accounts/pending")
def pending_accounts(admin: dict[str, Any] = Depends(require_super_admin)) -> list[dict[str, Any]]:
    rows = db.fetch_all("SELECT * FROM accounts WHERE approval_status = 'pending' ORDER BY created_at ASC")
    return [normalize_account(row) for row in rows]


@app.post("/v2/admin/accounts/{account_id}/approve")
def approve_account(account_id: str, admin: dict[str, Any] = Depends(require_super_admin)) -> dict[str, Any]:
    account = db.fetch_one("SELECT * FROM accounts WHERE id = ?", (account_id,))
    if not account:
        raise HTTPException(status_code=404, detail="Account not found")
    db.execute(
        "UPDATE accounts SET approval_status = 'approved', approved_by = ?, approved_at = ?, updated_at = ? WHERE id = ?",
        (admin["id"], utc_now(), utc_now(), account_id),
    )
    approved = db.fetch_one("SELECT * FROM accounts WHERE id = ?", (account_id,))
    project = ensure_default_project(account_id, username=approved["username"])
    ensure_user_kb(account_id, project["id"], username=approved["username"])
    return {"saved": True, "account": normalize_account(approved)}


@app.post("/v2/admin/accounts/{account_id}/reject")
def reject_account(account_id: str, admin: dict[str, Any] = Depends(require_super_admin)) -> dict[str, Any]:
    account = db.fetch_one("SELECT * FROM accounts WHERE id = ?", (account_id,))
    if not account:
        raise HTTPException(status_code=404, detail="Account not found")
    db.execute(
        "UPDATE accounts SET approval_status = 'rejected', approved_by = ?, approved_at = ?, updated_at = ? WHERE id = ?",
        (admin["id"], utc_now(), utc_now(), account_id),
    )
    rejected = db.fetch_one("SELECT * FROM accounts WHERE id = ?", (account_id,))
    return {"saved": True, "account": normalize_account(rejected)}


@app.get("/api/v1/app/update/latest")
def latest_update(
    platform: str = Query(default="android"),
    channel: str = Query(default="stable"),
    currentVersionCode: int | None = Query(default=None),
) -> dict[str, Any]:
    row = db.fetch_one(
        "SELECT * FROM app_updates WHERE platform = ? AND channel = ? AND is_active = 1 ORDER BY version_code DESC, published_at DESC LIMIT 1",
        (platform, channel),
    )
    if not row:
        return {
            "platform": platform,
            "channel": channel,
            "hasUpdate": False,
            "latestVersionCode": currentVersionCode or 0,
            "latestVersionName": "",
            "minSupportedCode": 0,
            "downloadUrl": "",
            "apkSha256": "",
            "releaseNotes": "",
            "forceUpdate": False,
            "publishedAt": 0,
        }
    latest_version_code = int(row["version_code"])
    return {
        "platform": row["platform"],
        "channel": row["channel"],
        "hasUpdate": currentVersionCode is None or latest_version_code > currentVersionCode,
        "latestVersionCode": latest_version_code,
        "latestVersionName": row["version_name"],
        "minSupportedCode": int(row["min_supported_code"]),
        "downloadUrl": row["apk_url"],
        "apkSha256": row.get("apk_sha256", ""),
        "releaseNotes": row.get("notes", ""),
        "forceUpdate": bool(row.get("force_update", 0)),
        "publishedAt": int(row.get("published_at", 0)),
    }


@app.post("/v2/admin/app/update/publish")
def publish_app_update(request: PublishAppUpdateRequest, admin: dict[str, Any] = Depends(require_super_admin)) -> dict[str, Any]:
    db.execute(
        "UPDATE app_updates SET is_active = 0 WHERE platform = ? AND channel = ?",
        (request.platform, request.channel),
    )
    db.execute(
        """
        INSERT INTO app_updates (
            platform, channel, version_code, version_name, min_supported_code,
            apk_url, apk_sha256, notes, force_update, is_active, published_at, created_by
        ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
        """,
        (
            request.platform,
            request.channel,
            request.versionCode,
            request.versionName,
            request.minSupportedCode,
            request.apkUrl,
            request.apkSha256,
            request.notes,
            1 if request.forceUpdate else 0,
            1 if request.isActive else 0,
            now_ts(),
            admin["id"],
        ),
    )
    row = db.fetch_one(
        """
        SELECT id
        FROM app_updates
        WHERE platform = ? AND channel = ? AND version_code = ?
        ORDER BY id DESC
        LIMIT 1
        """,
        (request.platform, request.channel, request.versionCode),
    )
    return {"saved": True, "action": "published", "updateId": row["id"] if row else 0}