import traceback from fastapi import APIRouter, HTTPException from fastapi.responses import StreamingResponse from apps.chat.curd.chat import list_chats, get_chat_with_records, create_chat, rename_chat, \ delete_chat, get_chat_chart_data, get_chat_predict_data from apps.chat.models.chat_model import CreateChat, ChatRecord, RenameChat, ChatQuestion from apps.chat.task.llm import LLMService from common.core.deps import CurrentAssistant, SessionDep, CurrentUser router = APIRouter(tags=["Data Q&A"], prefix="/chat") @router.get("/list") async def chats(session: SessionDep, current_user: CurrentUser): return list_chats(session, current_user) @router.get("/get/{chart_id}") async def get_chat(session: SessionDep, current_user: CurrentUser, chart_id: int, current_assistant: CurrentAssistant): try: return get_chat_with_records(chart_id=chart_id, session=session, current_user=current_user, current_assistant=current_assistant) except Exception as e: raise HTTPException( status_code=500, detail=str(e) ) @router.get("/record/get/{chart_record_id}/data") async def chat_record_data(session: SessionDep, chart_record_id: int): try: return get_chat_chart_data(chart_record_id=chart_record_id, session=session) except Exception as e: raise HTTPException( status_code=500, detail=str(e) ) @router.get("/record/get/{chart_record_id}/predict_data") async def chat_predict_data(session: SessionDep, chart_record_id: int): try: return get_chat_predict_data(chart_record_id=chart_record_id, session=session) except Exception as e: raise HTTPException( status_code=500, detail=str(e) ) @router.post("/rename") async def rename(session: SessionDep, chat: RenameChat): try: return rename_chat(session=session, rename_object=chat) except Exception as e: raise HTTPException( status_code=500, detail=str(e) ) @router.get("/delete/{chart_id}") async def delete(session: SessionDep, chart_id: int): try: return delete_chat(session=session, chart_id=chart_id) except Exception as e: raise HTTPException( status_code=500, detail=str(e) ) @router.post("/start") async def start_chat(session: SessionDep, current_user: CurrentUser, create_chat_obj: CreateChat): try: return create_chat(session, current_user, create_chat_obj) except Exception as e: raise HTTPException( status_code=500, detail=str(e) ) @router.post("/assistant/start") async def start_chat(session: SessionDep, current_user: CurrentUser): try: return create_chat(session, current_user, CreateChat(origin=2), False) except Exception as e: raise HTTPException( status_code=500, detail=str(e) ) @router.post("/recommend_questions/{chat_record_id}") async def recommend_questions(session: SessionDep, current_user: CurrentUser, chat_record_id: int, current_assistant: CurrentAssistant): try: record = session.get(ChatRecord, chat_record_id) if not record: raise HTTPException( status_code=400, detail=f"Chat record with id {chat_record_id} not found" ) request_question = ChatQuestion(chat_id=record.chat_id, question=record.question if record.question else '') llm_service = LLMService(session, current_user, request_question, current_assistant) llm_service.set_record(record) llm_service.run_recommend_questions_task_async() except Exception as e: traceback.print_exc() raise HTTPException( status_code=500, detail=str(e) ) return StreamingResponse(llm_service.await_result(), media_type="text/event-stream") @router.post("/question") async def stream_sql(session: SessionDep, current_user: CurrentUser, request_question: ChatQuestion, current_assistant: CurrentAssistant): """Stream SQL analysis results Args: session: Database session current_user: CurrentUser request_question: User question model Returns: Streaming response with analysis results """ try: llm_service = LLMService(session, current_user, request_question, current_assistant) llm_service.init_record() llm_service.run_task_async() except Exception as e: traceback.print_exc() raise HTTPException( status_code=500, detail=str(e) ) return StreamingResponse(llm_service.await_result(), media_type="text/event-stream") @router.post("/record/{chat_record_id}/{action_type}") async def analysis_or_predict(session: SessionDep, current_user: CurrentUser, chat_record_id: int, action_type: str, current_assistant: CurrentAssistant): if action_type != 'analysis' and action_type != 'predict': raise HTTPException( status_code=404, detail="Not Found" ) record = session.query(ChatRecord).get(chat_record_id) if not record: raise HTTPException( status_code=400, detail=f"Chat record with id {chat_record_id} not found" ) if not record.chart: raise HTTPException( status_code=500, detail=f"Chat record with id {chat_record_id} has not generated chart, do not support to analyze it" ) request_question = ChatQuestion(chat_id=record.chat_id, question='') try: llm_service = LLMService(session, current_user, request_question, current_assistant) llm_service.run_analysis_or_predict_task_async(action_type, record) except Exception as e: traceback.print_exc() raise HTTPException( status_code=500, detail=str(e) ) return StreamingResponse(llm_service.await_result(), media_type="text/event-stream")