mirror of
https://github.com/jxxghp/MoviePilot.git
synced 2026-08-29 20:17:13 +08:00
693 lines
22 KiB
Python
693 lines
22 KiB
Python
import asyncio
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import json
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import time
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import uuid
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from threading import Lock
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from typing import AsyncIterator, List, Optional, Tuple
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from fastapi import APIRouter, Request, Security
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from fastapi.responses import JSONResponse, StreamingResponse
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from fastapi.security import HTTPAuthorizationCredentials
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from app.schemas.openai import OpenAIChatCompletionResponse as _SchemaOpenAIChatCompletionResponse
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from app.schemas.openai import OpenAIChatCompletionsRequest as _SchemaOpenAIChatCompletionsRequest
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from app.schemas.openai import OpenAIErrorDetail as _SchemaOpenAIErrorDetail
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from app.schemas.openai import OpenAIErrorResponse as _SchemaOpenAIErrorResponse
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from app.schemas.openai import OpenAIModelInfo as _SchemaOpenAIModelInfo
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from app.schemas.openai import OpenAIModelListResponse as _SchemaOpenAIModelListResponse
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from app.schemas.openai import OpenAIResponsesOutputMessage as _SchemaOpenAIResponsesOutputMessage
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from app.schemas.openai import OpenAIResponsesOutputText as _SchemaOpenAIResponsesOutputText
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from app.schemas.openai import OpenAIResponsesRequest as _SchemaOpenAIResponsesRequest
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from app.schemas.openai import OpenAIResponsesResponse as _SchemaOpenAIResponsesResponse
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from app.schemas.openai import OpenAIUsage as _SchemaOpenAIUsage
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from app.api.openai_utils import (
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build_completion_payload,
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build_prompt,
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build_responses_input,
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build_session_id,
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)
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from app.agent.runtime_loader import (
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get_moviepilot_agent_type,
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get_running_agent_manager,
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)
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from app.agent.contracts import ReplyMode
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from app.runtime.config import settings
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from app.adapters.web.security.access import openai_bearer_scheme
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from app.schemas.types import NotificationChannel
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OPENAI_ERROR_RESPONSES = {
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400: {"model": _SchemaOpenAIErrorResponse, "description": "请求格式错误"},
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401: {"model": _SchemaOpenAIErrorResponse, "description": "认证失败"},
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422: {"model": _SchemaOpenAIErrorResponse, "description": "请求参数校验失败"},
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500: {"model": _SchemaOpenAIErrorResponse, "description": "服务内部错误"},
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503: {"model": _SchemaOpenAIErrorResponse, "description": "AI Agent 不可用"},
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}
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router = APIRouter(responses=OPENAI_ERROR_RESPONSES)
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MODEL_ID = "moviepilot-agent"
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SESSION_PREFIX = "openai:"
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class _CollectingMoviePilotAgentMixin:
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"""
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捕获 Agent 最终输出，避免再通过消息渠道二次发送。
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"""
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def __init__(self, *args, stream_mode: bool = False, **kwargs):
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super().__init__(*args, **kwargs)
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self.collected_messages: List[str] = []
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self.stream_mode = stream_mode
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if stream_mode:
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self.stream_handler = _get_openai_streaming_handler_type()()
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def _should_stream(self) -> bool:
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return self.stream_mode
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def configure_protocol_request(
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self,
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*,
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stream_mode: bool,
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event_queue: Optional[asyncio.Queue],
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) -> None:
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"""切换请求级输出目标，并保持已编译工具引用的 handler identity。"""
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self.collected_messages = []
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self.stream_mode = stream_mode
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if isinstance(self.stream_handler, _OpenAIStreamingHandlerMixin):
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self.stream_handler.bind_queue(event_queue if stream_mode else None)
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return
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if not stream_mode:
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return
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self.stream_handler = _get_openai_streaming_handler_type()()
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self.stream_handler.bind_queue(event_queue)
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# 已编译工具持有旧 handler；identity 变化时必须重建图和工具目录。
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self._compiled_agent_bundle = None
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def release_protocol_request(
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self,
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event_queue: Optional[asyncio.Queue],
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) -> None:
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"""释放已结束请求的输出队列，不影响同会话已重绑的新请求。"""
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if isinstance(self.stream_handler, _OpenAIStreamingHandlerMixin):
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self.stream_handler.unbind_queue(event_queue)
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async def send_agent_message(self, message: str, title: str = ""):
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text = (message or "").strip()
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if title and text:
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text = f"{title}\n{text}"
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elif title:
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text = title.strip()
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if text:
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self.collected_messages.append(text)
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if self.stream_mode:
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self.stream_handler.emit(text)
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class _OpenAIStreamingHandlerMixin:
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"""
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将 Agent 流式输出转发到 OpenAI SSE 队列，不向站内消息系统落消息。
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"""
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def __init__(self):
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super().__init__()
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self._event_queue: Optional[asyncio.Queue] = None
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def bind_queue(self, queue: Optional[asyncio.Queue]):
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"""绑定当前协议请求的输出队列。"""
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self._event_queue = queue
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def unbind_queue(self, queue: Optional[asyncio.Queue]) -> None:
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"""仅当仍指向该请求时解除绑定，避免清掉已排队的新请求。"""
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if self._event_queue is queue:
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self._event_queue = None
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def emit(self, token: str):
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emitted = super().emit(token)
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if emitted and self._event_queue is not None:
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self._event_queue.put_nowait(emitted)
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def flush_pending_tool_summary(self) -> str:
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emitted = super().flush_pending_tool_summary()
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if emitted and self._event_queue is not None:
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self._event_queue.put_nowait(emitted)
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return emitted
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async def start_streaming(
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self,
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channel: Optional[str] = None,
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source: Optional[str] = None,
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user_id: Optional[str] = None,
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username: Optional[str] = None,
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original_message_id: Optional[str] = None,
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original_chat_id: Optional[str] = None,
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title: str = "",
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):
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self._channel = channel
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self._source = source
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self._user_id = user_id
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self._username = username
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self._original_message_id = original_message_id
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self._original_chat_id = original_chat_id
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self._title = title
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self._streaming_enabled = True
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self._sent_text = ""
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self._message_response = None
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self._msg_start_offset = 0
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self._max_message_length = 0
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async def stop_streaming(self) -> Tuple[bool, str]:
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if not self._streaming_enabled:
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return False, ""
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self._streaming_enabled = False
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with self._lock:
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final_text = self._buffer
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self._buffer = ""
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self._sent_text = ""
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self._message_response = None
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self._msg_start_offset = 0
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return True, final_text
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def _get_openai_streaming_handler_type() -> type:
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"""首次兼容协议调用时才解析完整流式处理器。"""
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global _OPENAI_STREAMING_HANDLER_TYPE
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if _OPENAI_STREAMING_HANDLER_TYPE is not None:
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return _OPENAI_STREAMING_HANDLER_TYPE
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with _OPENAI_STREAMING_HANDLER_TYPE_LOCK:
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if _OPENAI_STREAMING_HANDLER_TYPE is None:
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from app.agent.callback import StreamingHandler
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_OPENAI_STREAMING_HANDLER_TYPE = type(
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"_RuntimeOpenAIStreamingHandler",
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(_OpenAIStreamingHandlerMixin, StreamingHandler),
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{"__module__": __name__},
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)
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return _OPENAI_STREAMING_HANDLER_TYPE
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_OPENAI_STREAMING_HANDLER_TYPE_LOCK = Lock()
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_OPENAI_STREAMING_HANDLER_TYPE: Optional[type] = None
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def _build_collecting_agent_type(agent_base_type: type) -> type:
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"""为 OpenAI 与 Anthropic 兼容协议组合唯一的运行时类型。"""
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return type(
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"_RuntimeCollectingMoviePilotAgent",
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(_CollectingMoviePilotAgentMixin, agent_base_type),
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{"__module__": __name__},
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)
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_COLLECTING_AGENT_TYPE_LOCK = Lock()
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_COLLECTING_AGENT_TYPE: Optional[type] = None
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def _get_collecting_agent_type() -> type:
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"""在首个真实兼容协议请求边界 single-flight 解析 Agent 类型。"""
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global _COLLECTING_AGENT_TYPE
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if _COLLECTING_AGENT_TYPE is not None:
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return _COLLECTING_AGENT_TYPE
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with _COLLECTING_AGENT_TYPE_LOCK:
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if _COLLECTING_AGENT_TYPE is None:
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_COLLECTING_AGENT_TYPE = _build_collecting_agent_type(
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get_moviepilot_agent_type()
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)
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return _COLLECTING_AGENT_TYPE
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def _sse_payload(data: dict) -> str:
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return f"data: {json.dumps(data, ensure_ascii=False)}\n\n"
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async def _stream_response(
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manager,
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session_id: str,
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user_id: str,
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username: str,
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prompt: str,
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images: List[str],
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cleanup_session: bool,
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) -> AsyncIterator[str]:
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event_queue: asyncio.Queue = asyncio.Queue()
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created = int(time.time())
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completion_id = f"chatcmpl-{uuid.uuid4().hex}"
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finished = False
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async def _run_agent():
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try:
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await _run_managed_agent(
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manager=manager,
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session_id=session_id,
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user_id=user_id,
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username=username,
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source="openai",
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prompt=prompt,
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images=images,
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stream_mode=True,
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event_queue=event_queue,
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)
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except asyncio.CancelledError:
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await event_queue.put({"error": "MoviePilot AI agent is unavailable."})
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except Exception as exc:
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await event_queue.put({"error": str(exc)})
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finally:
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await event_queue.put(None)
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task = asyncio.create_task(_run_agent())
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try:
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yield _sse_payload(
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{
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"id": completion_id,
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"object": "chat.completion.chunk",
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"created": created,
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"model": MODEL_ID,
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"choices": [
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{
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"index": 0,
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"delta": {"role": "assistant"},
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"finish_reason": None,
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}
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],
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}
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)
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while True:
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item = await event_queue.get()
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if item is None:
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break
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if isinstance(item, dict) and item.get("error"):
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yield _sse_payload(
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{
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"error": {
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"message": str(item["error"]),
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"type": "server_error",
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"code": "agent_execution_failed",
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}
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}
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)
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yield "data: [DONE]\n\n"
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return
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text = str(item or "")
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if not text:
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continue
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yield _sse_payload(
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{
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"id": completion_id,
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"object": "chat.completion.chunk",
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"created": created,
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"model": MODEL_ID,
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"choices": [
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{
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"index": 0,
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"delta": {"content": text},
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"finish_reason": None,
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}
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],
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}
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)
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finished = True
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yield _sse_payload(
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{
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"id": completion_id,
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"object": "chat.completion.chunk",
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"created": created,
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"model": MODEL_ID,
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"choices": [
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{
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"index": 0,
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"delta": {},
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"finish_reason": "stop",
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}
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],
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}
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)
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yield "data: [DONE]\n\n"
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finally:
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if cleanup_session:
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await manager.clear_session(session_id=session_id, user_id=user_id)
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elif not task.done():
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await manager.stop_current_task(session_id)
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if not task.done():
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task.cancel()
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try:
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await task
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except asyncio.CancelledError:
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pass
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elif finished:
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await task
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def _is_manager_unavailable(error: BaseException) -> bool:
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"""识别 manager acceptance gate 的稳定错误，不导入完整编排模块。"""
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return getattr(error, "code", None) == "agent_manager_unavailable"
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async def _run_managed_agent(
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*,
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manager,
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session_id: str,
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user_id: str,
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username: str,
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source: str,
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prompt: str,
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images: List[str],
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stream_mode: bool,
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event_queue: Optional[asyncio.Queue] = None,
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) -> tuple[str, List[str]]:
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"""通过 AgentManager 执行协议请求，并在 worker 内配置请求级输出。"""
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agent_holder = {}
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def configure_agent(agent) -> None:
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agent.configure_protocol_request(
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stream_mode=stream_mode,
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event_queue=event_queue,
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)
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agent_holder["agent"] = agent
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try:
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result = await manager.process_message(
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session_id=session_id,
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user_id=user_id,
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message=prompt,
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images=images,
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files=None,
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channel=NotificationChannel.Web.value,
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source=source,
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username=username,
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reply_mode=ReplyMode.CAPTURE_ONLY,
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allow_message_tools=True,
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agent_factory=_get_collecting_agent_type(),
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agent_setup=configure_agent,
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wait_for_completion=True,
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)
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agent = agent_holder.get("agent")
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return result, list(agent.collected_messages if agent else [])
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finally:
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agent = agent_holder.get("agent")
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if agent is not None:
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agent.release_protocol_request(event_queue)
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def _error_response(
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message: str,
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status_code: int,
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error_type: str = "invalid_request_error",
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code: Optional[str] = None,
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) -> JSONResponse:
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return JSONResponse(
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status_code=status_code,
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content=_SchemaOpenAIErrorResponse(
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error=_SchemaOpenAIErrorDetail(
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message=message,
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type=error_type,
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code=code,
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)
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).model_dump(),
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headers={"WWW-Authenticate": "Bearer"},
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)
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|
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def _check_auth(
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credentials: Optional[HTTPAuthorizationCredentials],
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) -> Optional[JSONResponse]:
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"""
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OpenAI 兼容接口以 API_TOKEN 认证受信客户端，认证通过即按管理员级 Agent 集成处理。
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"""
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if not credentials or credentials.scheme.lower() != "bearer":
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return _error_response(
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"Invalid bearer token.",
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401,
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error_type="authentication_error",
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code="invalid_api_key",
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)
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if credentials.credentials != settings.API_TOKEN:
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return _error_response(
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"Invalid bearer token.",
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401,
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error_type="authentication_error",
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code="invalid_api_key",
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)
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return None
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|
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@router.get(
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"/models",
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summary="OpenAI compatible models",
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response_model=_SchemaOpenAIModelListResponse,
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)
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async def list_models(
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credentials: Optional[HTTPAuthorizationCredentials] = Security(
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openai_bearer_scheme
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),
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):
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auth_error = _check_auth(credentials)
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if auth_error:
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return auth_error
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now = int(time.time())
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return _SchemaOpenAIModelListResponse(
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data=[_SchemaOpenAIModelInfo(id=MODEL_ID, created=now)]
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)
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|
|
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@router.post(
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"/chat/completions",
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summary="OpenAI compatible chat completions",
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response_model=_SchemaOpenAIChatCompletionResponse,
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responses={
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200: {
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"description": "OpenAI chat completion 或 SSE 数据流",
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"content": {
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"text/event-stream": {"schema": {"type": "string"}},
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},
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}
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},
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)
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async def chat_completions(
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payload: _SchemaOpenAIChatCompletionsRequest,
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request: Request,
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credentials: Optional[HTTPAuthorizationCredentials] = Security(
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openai_bearer_scheme
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),
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):
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auth_error = _check_auth(credentials)
|
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if auth_error:
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return auth_error
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|
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if not settings.AI_AGENT_ENABLE:
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return _error_response(
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"MoviePilot AI agent is disabled.",
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503,
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error_type="server_error",
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code="ai_agent_disabled",
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)
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manager = get_running_agent_manager()
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if manager is None:
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return _error_response(
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"MoviePilot AI agent is unavailable.",
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503,
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error_type="server_error",
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code="ai_agent_unavailable",
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)
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if not payload.messages:
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return _error_response(
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"`messages` must be a non-empty array.",
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400,
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code="invalid_messages",
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)
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session_key = (
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str(payload.user or "").strip()
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or str(request.headers.get("x-session-id") or "").strip()
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or str(uuid.uuid4())
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)
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use_server_session = bool(
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str(payload.user or "").strip()
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or str(request.headers.get("x-session-id") or "").strip()
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)
|
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try:
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prompt, images = build_prompt(
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payload.messages, use_server_session=use_server_session
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)
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except ValueError as exc:
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return _error_response(str(exc), 400, code="invalid_messages")
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|
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session_id = build_session_id(session_key, SESSION_PREFIX)
|
|
username = str(payload.user or "openai-client")
|
|
if payload.stream:
|
|
return StreamingResponse(
|
|
_stream_response(
|
|
manager=manager,
|
|
session_id=session_id,
|
|
user_id=session_key,
|
|
username=username,
|
|
prompt=prompt,
|
|
images=images,
|
|
cleanup_session=not use_server_session,
|
|
),
|
|
media_type="text/event-stream",
|
|
headers={
|
|
"Cache-Control": "no-cache",
|
|
"Connection": "keep-alive",
|
|
"X-Accel-Buffering": "no",
|
|
},
|
|
)
|
|
|
|
collected_messages = []
|
|
try:
|
|
result, collected_messages = await _run_managed_agent(
|
|
manager=manager,
|
|
session_id=session_id,
|
|
user_id=session_key,
|
|
username=username,
|
|
source="openai",
|
|
prompt=prompt,
|
|
images=images,
|
|
stream_mode=False,
|
|
)
|
|
except Exception as exc:
|
|
if _is_manager_unavailable(exc):
|
|
return _error_response(
|
|
"MoviePilot AI agent is unavailable.",
|
|
503,
|
|
error_type="server_error",
|
|
code="ai_agent_unavailable",
|
|
)
|
|
return _error_response(
|
|
str(exc),
|
|
500,
|
|
error_type="server_error",
|
|
code="agent_execution_failed",
|
|
)
|
|
finally:
|
|
if not use_server_session:
|
|
await manager.clear_session(session_id=session_id, user_id=session_key)
|
|
|
|
content = "\n\n".join(
|
|
message.strip()
|
|
for message in collected_messages
|
|
if message and message.strip()
|
|
).strip()
|
|
if not content and result:
|
|
content = str(result).strip()
|
|
if not content:
|
|
content = "未获得有效回复。"
|
|
|
|
return JSONResponse(content=build_completion_payload(content, MODEL_ID))
|
|
|
|
|
|
@router.post(
|
|
"/responses",
|
|
summary="OpenAI compatible responses",
|
|
response_model=_SchemaOpenAIResponsesResponse,
|
|
)
|
|
async def responses(
|
|
payload: _SchemaOpenAIResponsesRequest,
|
|
credentials: Optional[HTTPAuthorizationCredentials] = Security(
|
|
openai_bearer_scheme
|
|
),
|
|
):
|
|
auth_error = _check_auth(credentials)
|
|
if auth_error:
|
|
return auth_error
|
|
|
|
if not settings.AI_AGENT_ENABLE:
|
|
return _error_response(
|
|
"MoviePilot AI agent is disabled.",
|
|
503,
|
|
error_type="server_error",
|
|
code="ai_agent_disabled",
|
|
)
|
|
manager = get_running_agent_manager()
|
|
if manager is None:
|
|
return _error_response(
|
|
"MoviePilot AI agent is unavailable.",
|
|
503,
|
|
error_type="server_error",
|
|
code="ai_agent_unavailable",
|
|
)
|
|
|
|
if payload.stream:
|
|
return _error_response(
|
|
"Streaming is not supported for /responses yet.",
|
|
400,
|
|
code="unsupported_stream",
|
|
)
|
|
|
|
normalized_messages = build_responses_input(
|
|
payload.input, instructions=payload.instructions
|
|
)
|
|
if not normalized_messages:
|
|
return _error_response(
|
|
"`input` must include at least one usable message.",
|
|
400,
|
|
code="invalid_input",
|
|
)
|
|
|
|
try:
|
|
prompt, images = build_prompt(
|
|
normalized_messages, use_server_session=bool(payload.user)
|
|
)
|
|
except ValueError as exc:
|
|
return _error_response(str(exc), 400, code="invalid_input")
|
|
|
|
session_key = str(payload.user or uuid.uuid4())
|
|
session_id = build_session_id(session_key, SESSION_PREFIX)
|
|
collected_messages = []
|
|
try:
|
|
result, collected_messages = await _run_managed_agent(
|
|
manager=manager,
|
|
session_id=session_id,
|
|
user_id=session_key,
|
|
username=str(payload.user or "openai-client"),
|
|
source="openai.responses",
|
|
prompt=prompt,
|
|
images=images,
|
|
stream_mode=False,
|
|
)
|
|
except Exception as exc:
|
|
if _is_manager_unavailable(exc):
|
|
return _error_response(
|
|
"MoviePilot AI agent is unavailable.",
|
|
503,
|
|
error_type="server_error",
|
|
code="ai_agent_unavailable",
|
|
)
|
|
return _error_response(
|
|
str(exc),
|
|
500,
|
|
error_type="server_error",
|
|
code="agent_execution_failed",
|
|
)
|
|
finally:
|
|
if not payload.user:
|
|
await manager.clear_session(session_id=session_id, user_id=session_key)
|
|
|
|
content = "\n\n".join(
|
|
message.strip()
|
|
for message in collected_messages
|
|
if message and message.strip()
|
|
).strip()
|
|
if not content and result:
|
|
content = str(result).strip()
|
|
if not content:
|
|
content = "未获得有效回复。"
|
|
|
|
created_at = int(time.time())
|
|
response_id = f"resp_{uuid.uuid4().hex}"
|
|
output_message = _SchemaOpenAIResponsesOutputMessage(
|
|
id=f"msg_{uuid.uuid4().hex}",
|
|
content=[_SchemaOpenAIResponsesOutputText(text=content)],
|
|
)
|
|
return _SchemaOpenAIResponsesResponse(
|
|
id=response_id,
|
|
created_at=created_at,
|
|
model=MODEL_ID,
|
|
output=[output_message],
|
|
usage=_SchemaOpenAIUsage(),
|
|
)
|