import json import logging import os import time import httpx from sqlalchemy import select from sqlalchemy.ext.asyncio import AsyncSession from volcenginesdkarkruntime import AsyncArk from app.config import settings from app.enums.private_portrait import PRIVATE_PORTRAIT_ASSET_URI_PREFIX from app.models.video_engine import VideoEngine from app.services.operation_log_service import build_exception_detail, log_ai_model_event from app.utils.id_gen import generate_id from app.types.generation.provider import ( ProviderGenerationRecordLike, ProviderVideoEngineLike, ) logger = logging.getLogger("videogen") def _provider_log_context(engine, record, *, call_id: str, step_code: str) -> dict: generation_mode = str(getattr(record, "generation_mode", "") or "generation_record") owner_type = "chat_generation_task" if generation_mode != "generation_record" else "generation_record" return { "module": generation_mode, "step_code": step_code, "call_id": call_id, "source": "app.services.video_gen", "user_id": str(getattr(record, "user_id", "") or "") or None, "project_id": str(getattr(record, "project_id", "") or "") or None, "task_id": str(getattr(record, "id", "") or "") or None, "owner_type": owner_type, "owner_id": str(getattr(record, "id", "") or "") or None, "generation_attempt_no": int(getattr(record, "generation_attempt_no", 1) or 1), "model_config_id": str(getattr(engine, "id", "") or "") or None, "model_config_name": str(getattr(engine, "name", "") or "") or None, "model_name": str(getattr(engine, "model_name", "") or "") or None, "provider": str(getattr(engine, "provider", "") or "") or None, "api_base": str(getattr(engine, "api_base", "") or "") or None, } async def get_active_engine(db: AsyncSession) -> VideoEngine: """Get the active video engine with highest priority.""" result = await db.execute( select(VideoEngine) .where(VideoEngine.is_active == True, VideoEngine.deleted_at.is_(None)) .order_by(VideoEngine.priority.desc()) .limit(1) ) engine = result.scalar_one_or_none() if not engine: raise ValueError("没有可用的视频引擎，请联系管理员配置") return engine def _resolve_url(url: str) -> str: """Convert local path to base64 data URI, pass through remote URLs.""" # if url.startswith("http"): # return url # # Local file: read and encode as base64 data URI # file_path = os.path.join(settings.UPLOAD_LOCAL_PATH, url.replace("/uploads/", "")) # if not os.path.exists(file_path): # return url # mime = mimetypes.guess_type(file_path)[0] or "application/octet-stream" # with open(file_path, "rb") as f: # b64 = base64.b64encode(f.read()).decode() # return f"data:{mime};base64,{b64}" if url.startswith(("http://", "https://", "data:", PRIVATE_PORTRAIT_ASSET_URI_PREFIX)): return url return f"{settings.BASE_URL.rstrip('/')}/{url.lstrip('/')}" async def submit_video_task( db: AsyncSession, engine: ProviderVideoEngineLike, record: ProviderGenerationRecordLike, *, include_media_references: bool, ) -> str: """Submit a video generation task via Ark SDK. Returns task_id.""" client = AsyncArk( base_url=engine.api_base, api_key=engine.api_key, ) content = [{"type": "text", "text": record.optimized_prompt or record.original_prompt}] # GenerationRecord 的附件已在 API 提词优化阶段参与过 optimized_prompt 生成； # ChatGenerationTask 不走 API 提词优化，所以创建供应商任务时仍需携带附件。 if include_media_references and record.media_references: try: refs = json.loads(record.media_references) for ref in refs: ref_type = ref.get("type") ref_url = ref.get("url", "") ref_role = ref.get("role") if ref_type == "image" and ref_url: resolved = _resolve_url(ref_url) role = ref_role if ref_role in ("first_frame", "last_frame") else "reference_image" content.append({"type": "image_url", "image_url": {"url": resolved}, "role": role}) elif ref_type == "video" and ref_url: resolved = _resolve_url(ref_url) role = ref_role if ref_role else "reference_video" content.append({"type": "video_url", "video_url": {"url": resolved}, "role": role}) elif ref_type == "audio" and ref_url: resolved = _resolve_url(ref_url) role = ref_role if ref_role else "reference_audio" content.append({"type": "audio_url", "audio_url": {"url": resolved}, "role": role}) except (json.JSONDecodeError, TypeError): pass request_payload = { "model": engine.model_name, "content": content, "ratio": record.aspect_ratio, "duration": record.duration, "resolution": getattr(record, "provider_generation_resolution", None) or record.resolution, "generate_audio": True, "watermark": False, } call_id = generate_id() started = time.perf_counter() log_context = _provider_log_context( engine, record, call_id=call_id, step_code="video_create", ) log_ai_model_event( event_type="REQUEST", event_phase="REQUEST", event_status="started", remote_action="video_create", request={**request_payload, "include_media_references": include_media_references}, **log_context, ) try: result = await client.content_generation.tasks.create(**request_payload) task_id = result.id log_ai_model_event( event_type="RESPONSE", event_phase="RESPONSE", event_status="success", remote_action="video_create", remote_request_id=task_id, latency_ms=int((time.perf_counter() - started) * 1000), response={"task_id": task_id}, **log_context, ) except Exception as exc: log_ai_model_event( event_type="ERROR", event_phase="ERROR", event_status="failed", remote_action="video_create", latency_ms=int((time.perf_counter() - started) * 1000), detail=build_exception_detail(exc), error=str(exc), **log_context, ) raise finally: await client.close() return task_id async def poll_task_status(engine: VideoEngine, task_id: str) -> dict: """Query task status via Ark SDK. Returns {status, video_url, response_data}.""" client = AsyncArk( base_url=engine.api_base, api_key=engine.api_key, ) result = await client.content_generation.tasks.get(task_id=task_id) await client.close() # Serialize response response_dict = { "id": result.id, "model": result.model, "status": result.status, "created_at": result.created_at, "updated_at": result.updated_at, } video_url = None video_tokens = 0 if result.status == "succeeded" and result.content: video_url = getattr(result.content, "video_url", None) response_dict["video_url"] = video_url response_dict["duration"] = getattr(result, "duration", None) response_dict["ratio"] = getattr(result, "ratio", None) response_dict["resolution"] = getattr(result, "resolution", None) # Extract usage info if present usage = getattr(result, "usage", None) if usage: response_dict["usage"] = { "input_tokens": getattr(usage, "input_tokens", 0), "output_tokens": getattr(usage, "output_tokens", 0), "total_tokens": getattr(usage, "total_tokens", 0), } video_tokens = getattr(usage, "total_tokens", 0) elif result.status == "failed": response_dict["error"] = str(getattr(result, "error", "视频生成失败")) return { "status": result.status, "video_url": video_url, "video_tokens": video_tokens, "response_data": json.dumps(response_dict, ensure_ascii=False, default=str), "error": response_dict.get("error"), } async def download_video( video_url: str, dest_path: str, *, execution_guard=None, ) -> str: """Download video to local storage.""" import os os.makedirs(os.path.dirname(dest_path), exist_ok=True) async with httpx.AsyncClient(timeout=300) as client: async with client.stream("GET", video_url) as response: response.raise_for_status() with open(dest_path, "wb") as f: chunk_no = 0 async for chunk in response.aiter_bytes(chunk_size=8192): f.write(chunk) chunk_no += 1 if execution_guard is not None and chunk_no % 32 == 0: await execution_guard() if execution_guard is not None: await execution_guard() return dest_path