mirror of
https://github.com/csunny/DB-GPT.git
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304 lines
9.7 KiB
Python
304 lines
9.7 KiB
Python
import uuid
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import json
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import asyncio
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import time
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import os
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from fastapi import (
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APIRouter,
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Request,
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Body,
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status,
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HTTPException,
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Response,
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BackgroundTasks,
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)
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from fastapi.responses import JSONResponse, HTMLResponse
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from fastapi.responses import StreamingResponse, FileResponse
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from fastapi.encoders import jsonable_encoder
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from fastapi.exceptions import RequestValidationError
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from sse_starlette.sse import EventSourceResponse
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from typing import List
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from pilot.openapi.api_v1.api_view_model import (
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Result,
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ConversationVo,
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MessageVo,
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ChatSceneVo,
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)
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from pilot.configs.config import Config
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from pilot.openapi.knowledge.knowledge_service import KnowledgeService
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from pilot.openapi.knowledge.request.knowledge_request import KnowledgeSpaceRequest
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from pilot.scene.base_chat import BaseChat
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from pilot.scene.base import ChatScene
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from pilot.scene.chat_factory import ChatFactory
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from pilot.configs.model_config import LOGDIR
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from pilot.utils import build_logger
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from pilot.scene.base_message import BaseMessage
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from pilot.memory.chat_history.duckdb_history import DuckdbHistoryMemory
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from pilot.scene.message import OnceConversation
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router = APIRouter()
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CFG = Config()
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CHAT_FACTORY = ChatFactory()
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logger = build_logger("api_v1", LOGDIR + "api_v1.log")
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knowledge_service = KnowledgeService()
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model_semaphore = None
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global_counter = 0
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static_file_path = os.path.join(os.getcwd(), "server/static")
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async def validation_exception_handler(request: Request, exc: RequestValidationError):
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message = ""
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for error in exc.errors():
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message += ".".join(error.get("loc")) + ":" + error.get("msg") + ";"
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return Result.faild(msg=message)
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def __get_conv_user_message(conversations: dict):
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messages = conversations["messages"]
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for item in messages:
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if item["type"] == "human":
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return item["data"]["content"]
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return ""
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def __new_conversation(chat_mode, user_id) -> ConversationVo:
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unique_id = uuid.uuid1()
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history_mem = DuckdbHistoryMemory(str(unique_id))
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return ConversationVo(conv_uid=str(unique_id), chat_mode=chat_mode)
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def get_db_list():
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db = CFG.local_db
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dbs = db.get_database_list()
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params: dict = {}
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for name in dbs:
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params.update({name: name})
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return params
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def plugins_select_info():
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plugins_infos: dict = {}
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for plugin in CFG.plugins:
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plugins_infos.update({f"【{plugin._name}】=>{plugin._description}": plugin._name})
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return plugins_infos
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def knowledge_list():
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"""return knowledge space list"""
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params: dict = {}
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request = KnowledgeSpaceRequest()
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spaces = knowledge_service.get_knowledge_space(request)
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for space in spaces:
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params.update({space.name: space.name})
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return params
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@router.get("/")
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async def read_main():
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return FileResponse(f"{static_file_path}/test.html")
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@router.get("/v1/chat/dialogue/list", response_model=Result[ConversationVo])
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async def dialogue_list(response: Response, user_id: str = None):
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# 设置CORS头部信息
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response.headers["Access-Control-Allow-Origin"] = "*"
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response.headers["Access-Control-Allow-Methods"] = "GET"
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response.headers["Access-Control-Request-Headers"] = "content-type"
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dialogues: List = []
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datas = DuckdbHistoryMemory.conv_list(user_id)
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for item in datas:
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conv_uid = item.get("conv_uid")
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summary = item.get("summary")
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chat_mode = item.get("chat_mode")
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conv_vo: ConversationVo = ConversationVo(
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conv_uid=conv_uid,
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user_input=summary,
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chat_mode=chat_mode,
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)
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dialogues.append(conv_vo)
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return Result[ConversationVo].succ(dialogues[-10:][::-1])
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@router.post("/v1/chat/dialogue/scenes", response_model=Result[List[ChatSceneVo]])
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async def dialogue_scenes():
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scene_vos: List[ChatSceneVo] = []
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new_modes: List[ChatScene] = [
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ChatScene.ChatWithDbExecute,
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ChatScene.ChatWithDbQA,
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ChatScene.ChatDashboard,
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ChatScene.ChatKnowledge,
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ChatScene.ChatExecution,
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]
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for scene in new_modes:
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if not scene.value in [
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ChatScene.ChatNormal.value,
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ChatScene.InnerChatDBSummary.value,
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]:
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scene_vo = ChatSceneVo(
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chat_scene=scene.value,
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scene_name=scene.name,
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param_title="Selection Param",
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)
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scene_vos.append(scene_vo)
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return Result.succ(scene_vos)
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@router.post("/v1/chat/dialogue/new", response_model=Result[ConversationVo])
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async def dialogue_new(
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chat_mode: str = ChatScene.ChatNormal.value, user_id: str = None
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):
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conv_vo = __new_conversation(chat_mode, user_id)
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return Result.succ(conv_vo)
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@router.post("/v1/chat/mode/params/list", response_model=Result[dict])
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async def params_list(chat_mode: str = ChatScene.ChatNormal.value):
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if ChatScene.ChatWithDbQA.value == chat_mode:
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return Result.succ(get_db_list())
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elif ChatScene.ChatWithDbExecute.value == chat_mode:
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return Result.succ(get_db_list())
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elif ChatScene.ChatDashboard.value == chat_mode:
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return Result.succ(get_db_list())
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elif ChatScene.ChatExecution.value == chat_mode:
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return Result.succ(plugins_select_info())
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elif ChatScene.ChatKnowledge.value == chat_mode:
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return Result.succ(knowledge_list())
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else:
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return Result.succ(None)
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@router.post("/v1/chat/dialogue/delete")
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async def dialogue_delete(con_uid: str):
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history_mem = DuckdbHistoryMemory(con_uid)
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history_mem.delete()
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return Result.succ(None)
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@router.get("/v1/chat/dialogue/messages/history", response_model=Result[MessageVo])
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async def dialogue_history_messages(con_uid: str):
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print(f"dialogue_history_messages:{con_uid}")
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message_vos: List[MessageVo] = []
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history_mem = DuckdbHistoryMemory(con_uid)
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history_messages: List[OnceConversation] = history_mem.get_messages()
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if history_messages:
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for once in history_messages:
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once_message_vos = [
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message2Vo(element, once["chat_order"]) for element in once["messages"]
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]
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message_vos.extend(once_message_vos)
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return Result.succ(message_vos)
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@router.post("/v1/chat/completions")
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async def chat_completions(dialogue: ConversationVo = Body()):
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print(f"chat_completions:{dialogue.chat_mode},{dialogue.select_param}")
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if not dialogue.chat_mode:
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dialogue.chat_mode = ChatScene.ChatNormal.value
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if not dialogue.conv_uid:
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conv_vo = __new_conversation(dialogue.chat_mode, dialogue.user_name)
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dialogue.conv_uid = conv_vo.conv_uid
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global model_semaphore, global_counter
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global_counter += 1
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if model_semaphore is None:
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model_semaphore = asyncio.Semaphore(CFG.LIMIT_MODEL_CONCURRENCY)
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await model_semaphore.acquire()
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if not ChatScene.is_valid_mode(dialogue.chat_mode):
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raise StopAsyncIteration(
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Result.faild("Unsupported Chat Mode," + dialogue.chat_mode + "!")
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)
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chat_param = {
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"chat_session_id": dialogue.conv_uid,
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"user_input": dialogue.user_input,
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}
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if ChatScene.ChatWithDbQA.value == dialogue.chat_mode:
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chat_param.update({"db_name": dialogue.select_param})
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elif ChatScene.ChatWithDbExecute.value == dialogue.chat_mode:
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chat_param.update({"db_name": dialogue.select_param})
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elif ChatScene.ChatDashboard.value == dialogue.chat_mode:
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chat_param.update({"db_name": dialogue.select_param})
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elif ChatScene.ChatExecution.value == dialogue.chat_mode:
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chat_param.update({"plugin_selector": dialogue.select_param})
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elif ChatScene.ChatKnowledge.value == dialogue.chat_mode:
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chat_param.update({"knowledge_space": dialogue.select_param})
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chat: BaseChat = CHAT_FACTORY.get_implementation(dialogue.chat_mode, **chat_param)
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background_tasks = BackgroundTasks()
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background_tasks.add_task(release_model_semaphore)
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headers = {
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# "Content-Type": "text/event-stream",
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"Cache-Control": "no-cache",
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"Connection": "keep-alive",
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# "Transfer-Encoding": "chunked",
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}
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if not chat.prompt_template.stream_out:
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return StreamingResponse(
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no_stream_generator(chat),
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headers=headers,
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media_type="text/event-stream",
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background=background_tasks,
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)
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else:
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return StreamingResponse(
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stream_generator(chat),
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headers=headers,
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media_type="text/plain",
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background=background_tasks,
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)
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def release_model_semaphore():
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model_semaphore.release()
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async def no_stream_generator(chat):
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msg = chat.nostream_call()
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msg = msg.replace("\n", "\\n")
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yield f"data: {msg}\n\n"
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async def stream_generator(chat):
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model_response = chat.stream_call()
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if not CFG.NEW_SERVER_MODE:
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for chunk in model_response.iter_lines(decode_unicode=False, delimiter=b"\0"):
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if chunk:
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msg = chat.prompt_template.output_parser.parse_model_stream_resp_ex(
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chunk, chat.skip_echo_len
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)
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msg = msg.replace("\n", "\\n")
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yield f"data:{msg}\n\n"
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await asyncio.sleep(0.1)
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else:
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for chunk in model_response:
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if chunk:
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msg = chat.prompt_template.output_parser.parse_model_stream_resp_ex(
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chunk, chat.skip_echo_len
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)
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msg = msg.replace("\n", "\\n")
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yield f"data:{msg}\n\n"
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await asyncio.sleep(0.1)
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chat.current_message.add_ai_message(msg)
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chat.current_message.add_view_message(msg)
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chat.memory.append(chat.current_message)
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def message2Vo(message: dict, order) -> MessageVo:
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return MessageVo(
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role=message["type"], context=message["data"]["content"], order=order
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)
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