531d785629
- Replace plain image URLs with `<img src="..." data-url="...">` HTML tags in multimodal and document extractor services - Propagate citations from workflow end events to client responses - Update system prompts to instruct LLMs to render images using Markdown `` with strict UUID-preserving URL copying
329 lines
13 KiB
Python
329 lines
13 KiB
Python
"""App 服务接口 - 基于 API Key 认证"""
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import json
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from typing import Annotated
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from fastapi import APIRouter, Depends, Request, Body
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from sqlalchemy.orm import Session
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from starlette.responses import StreamingResponse
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from app.core.api_key_auth import require_api_key
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from app.core.error_codes import BizCode
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from app.core.exceptions import BusinessException
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from app.core.logging_config import get_business_logger
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from app.core.response_utils import success
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from app.db import get_db
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from app.models.app_model import App
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from app.models.app_model import AppType
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from app.models.app_release_model import AppRelease
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from app.repositories import knowledge_repository
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from app.repositories.end_user_repository import EndUserRepository
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from app.schemas import AppChatRequest, conversation_schema
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from app.schemas.api_key_schema import ApiKeyAuth
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from app.services import workspace_service
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from app.services.app_chat_service import AppChatService, get_app_chat_service
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from app.services.app_service import get_app_service, AppService
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from app.services.conversation_service import ConversationService, get_conversation_service
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from app.utils.app_config_utils import workflow_config_4_app_release, \
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agent_config_4_app_release, multi_agent_config_4_app_release
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router = APIRouter(prefix="/app", tags=["V1 - App API"])
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logger = get_business_logger()
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@router.get("")
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async def list_apps():
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"""列出可访问的应用（占位）"""
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return success(data=[], msg="App API - Coming Soon")
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# /v1/app/chat
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# @router.post("/chat")
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# @require_api_key(scopes=["app"])
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# async def chat2(
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# request: Request,
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# api_key_auth: ApiKeyAuth = None,
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# db: Session = Depends(get_db),
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# message: str = Body(..., description="聊天消息内容"),
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# ):
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# """
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# Agent 聊天接口demo
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# scopes: 所需的权限范围列表["app", "rag", "memory"]
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# Args:
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# message: 请求参数
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# request: 声明请求
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# api_key_auth: 包含验证后的API Key 信息
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# db: db_session
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# """
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# logger.info(f"API Key Auth: {api_key_auth}")
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# logger.info(f"Message: {message}")
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# return success(data={"received": True}, msg="消息已接收")
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def _checkAppConfig(release: AppRelease):
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if release.type == AppType.AGENT:
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if not release.config:
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raise BusinessException("Agent 应用未配置模型", BizCode.AGENT_CONFIG_MISSING)
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elif release.type == AppType.MULTI_AGENT:
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if not release.config:
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raise BusinessException("Multi-Agent 应用未配置模型", BizCode.AGENT_CONFIG_MISSING)
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elif release.type == AppType.WORKFLOW:
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if not release.config:
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raise BusinessException("工作流应用未配置模型", BizCode.AGENT_CONFIG_MISSING)
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else:
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raise BusinessException("不支持的应用类型", BizCode.APP_TYPE_NOT_SUPPORTED)
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@router.post("/chat")
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@require_api_key(scopes=["app"])
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async def chat(
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request: Request,
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api_key_auth: ApiKeyAuth = None,
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db: Session = Depends(get_db),
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conversation_service: Annotated[ConversationService, Depends(get_conversation_service)] = None,
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app_chat_service: Annotated[AppChatService, Depends(get_app_chat_service)] = None,
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app_service: Annotated[AppService, Depends(get_app_service)] = None,
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message: str = Body(..., description="聊天消息内容"),
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):
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"""
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Agent/Workflow 聊天接口
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- 不传 version：使用当前生效版本（current_release，回滚后为回滚目标版本）
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- 传 version=release_id：使用指定版本uuid的历史快照，例如 {"version": "{{release_id}}"}
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"""
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body = await request.json()
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payload = AppChatRequest(**body)
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app = app_service.get_app(api_key_auth.resource_id, api_key_auth.workspace_id)
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# 版本切换：指定 release_id 时查找对应历史快照，否则使用当前激活版本
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if payload.version is not None:
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active_release = app_service.get_release_by_id(app.id, payload.version)
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else:
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active_release = app.current_release
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other_id = payload.user_id
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workspace_id = api_key_auth.workspace_id
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end_user_repo = EndUserRepository(db)
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# 仅在新建终端用户时检查配额，已有用户复用不受限制
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existing_end_user = end_user_repo.get_end_user_by_other_id(workspace_id=workspace_id, other_id=other_id)
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if existing_end_user is None:
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from app.core.quota_manager import _check_quota
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from app.models.workspace_model import Workspace
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ws = db.query(Workspace).filter(Workspace.id == workspace_id).first()
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if ws:
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_check_quota(db, ws.tenant_id, "end_user_quota", "end_user", workspace_id=workspace_id)
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new_end_user = end_user_repo.get_or_create_end_user(
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app_id=app.id,
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workspace_id=workspace_id,
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other_id=other_id,
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)
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end_user_id = str(new_end_user.id)
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web_search = True
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memory = True
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# 提前验证和准备（在流式响应开始前完成）
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storage_type = workspace_service.get_workspace_storage_type_without_auth(
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db=db,
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workspace_id=workspace_id
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)
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if storage_type is None:
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storage_type = 'neo4j'
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user_rag_memory_id = ''
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if storage_type == 'rag':
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if workspace_id:
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knowledge = knowledge_repository.get_knowledge_by_name(
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db=db,
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name="USER_RAG_MERORY",
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workspace_id=workspace_id
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)
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if knowledge:
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user_rag_memory_id = str(knowledge.id)
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else:
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logger.warning(
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f"未找到名为 'USER_RAG_MERORY' 的知识库，workspace_id: {workspace_id}，将使用 neo4j 存储")
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storage_type = 'neo4j'
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else:
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logger.warning("workspace_id 为空，无法使用 rag 存储，将使用 neo4j 存储")
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storage_type = 'neo4j'
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app_type = app.type
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# check app config
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_checkAppConfig(active_release)
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# 获取或创建会话（提前验证）
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conversation = conversation_service.create_or_get_conversation(
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app_id=app.id,
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workspace_id=workspace_id,
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user_id=end_user_id,
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is_draft=False,
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conversation_id=payload.conversation_id
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)
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if app_type == AppType.AGENT:
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# print("="*50)
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# print(app.current_release.default_model_config_id)
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agent_config = agent_config_4_app_release(active_release)
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# print(agent_config.default_model_config_id)
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# thinking 开关：仅当 agent 配置了 deep_thinking 且请求 thinking=True 时才启用
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if not (agent_config.model_parameters.get("deep_thinking", False) and payload.thinking):
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agent_config.model_parameters["deep_thinking"] = False
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# 流式返回
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if payload.stream:
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async def event_generator():
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async for event in app_chat_service.agnet_chat_stream(
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message=payload.message,
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conversation_id=conversation.id, # 使用已创建的会话 ID
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user_id=end_user_id, # 转换为字符串
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variables=payload.variables,
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web_search=web_search,
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config=agent_config,
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memory=memory,
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storage_type=storage_type,
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user_rag_memory_id=user_rag_memory_id,
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workspace_id=workspace_id,
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files=payload.files # 传递多模态文件
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):
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yield event
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return StreamingResponse(
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event_generator(),
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media_type="text/event-stream",
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headers={
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"Cache-Control": "no-cache",
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"Connection": "keep-alive",
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"X-Accel-Buffering": "no"
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}
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)
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# 非流式返回
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result = await app_chat_service.agnet_chat(
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message=payload.message,
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conversation_id=conversation.id, # 使用已创建的会话 ID
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user_id=end_user_id, # 转换为字符串
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variables=payload.variables,
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config=agent_config,
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web_search=web_search,
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memory=memory,
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storage_type=storage_type,
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user_rag_memory_id=user_rag_memory_id,
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workspace_id=workspace_id,
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files=payload.files # 传递多模态文件
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)
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return success(data=conversation_schema.ChatResponse(**result).model_dump(mode="json"))
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elif app_type == AppType.MULTI_AGENT:
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# 多 Agent 流式返回
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config = multi_agent_config_4_app_release(active_release)
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if payload.stream:
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async def event_generator():
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async for event in app_chat_service.multi_agent_chat_stream(
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message=payload.message,
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conversation_id=conversation.id, # 使用已创建的会话 ID
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user_id=end_user_id, # 转换为字符串
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variables=payload.variables,
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config=config,
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web_search=web_search,
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memory=memory,
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storage_type=storage_type,
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user_rag_memory_id=user_rag_memory_id
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):
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yield event
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return StreamingResponse(
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event_generator(),
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media_type="text/event-stream",
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headers={
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"Cache-Control": "no-cache",
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"Connection": "keep-alive",
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"X-Accel-Buffering": "no"
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}
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)
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# 多 Agent 非流式返回
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result = await app_chat_service.multi_agent_chat(
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message=payload.message,
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conversation_id=conversation.id, # 使用已创建的会话 ID
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user_id=end_user_id, # 转换为字符串
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variables=payload.variables,
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config=config,
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web_search=web_search,
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memory=memory,
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storage_type=storage_type,
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user_rag_memory_id=user_rag_memory_id
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)
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return success(data=conversation_schema.ChatResponse(**result).model_dump(mode="json"))
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elif app_type == AppType.WORKFLOW:
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# 多 Agent 流式返回
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config = workflow_config_4_app_release(active_release)
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if payload.stream:
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async def event_generator():
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async for event in app_chat_service.workflow_chat_stream(
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message=payload.message,
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conversation_id=conversation.id, # 使用已创建的会话 ID
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user_id=end_user_id, # 转换为字符串
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variables=payload.variables,
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files=payload.files,
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config=config,
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web_search=web_search,
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memory=memory,
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storage_type=storage_type,
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user_rag_memory_id=user_rag_memory_id,
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app_id=app.id,
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workspace_id=workspace_id,
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release_id=active_release.id,
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public=True
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):
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event_type = event.get("event", "message")
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event_data = event.get("data", {})
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# 转换为标准 SSE 格式（字符串）
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sse_message = f"event: {event_type}\ndata: {json.dumps(event_data)}\n\n"
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yield sse_message
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return StreamingResponse(
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event_generator(),
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media_type="text/event-stream",
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headers={
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"Cache-Control": "no-cache",
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"Connection": "keep-alive",
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"X-Accel-Buffering": "no"
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}
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)
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# workflow 非流式返回
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result = await app_chat_service.workflow_chat(
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message=payload.message,
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conversation_id=conversation.id, # 使用已创建的会话 ID
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user_id=end_user_id, # 转换为字符串
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variables=payload.variables,
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config=config,
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web_search=web_search,
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memory=memory,
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storage_type=storage_type,
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user_rag_memory_id=user_rag_memory_id,
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files=payload.files,
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app_id=app.id,
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workspace_id=workspace_id,
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release_id=active_release.id
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)
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logger.debug(
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"工作流试运行返回结果",
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extra={
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"result_type": str(type(result)),
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"has_response": "response" in result if isinstance(result, dict) else False
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}
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)
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return success(
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data=result,
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msg="工作流任务执行成功"
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)
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else:
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raise BusinessException(f"不支持的应用类型: {app_type}", BizCode.APP_TYPE_NOT_SUPPORTED)
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