mirror of
https://github.com/StanGirard/quivr.git
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339 lines
11 KiB
Python
339 lines
11 KiB
Python
import os
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import time
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from typing import List
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from uuid import UUID
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from venv import logger
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from auth import AuthBearer, get_current_user
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from fastapi import APIRouter, Depends, HTTPException, Query, Request
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from fastapi.responses import StreamingResponse
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from llm.openai import OpenAIBrainPicking
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from llm.qa_headless import HeadlessQA
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from models import (
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Brain,
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BrainEntity,
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Chat,
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ChatQuestion,
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UserIdentity,
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UserUsage,
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get_supabase_db,
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)
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from models.databases.supabase.supabase import SupabaseDB
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from repository.brain import get_brain_details
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from repository.chat import (
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ChatUpdatableProperties,
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CreateChatProperties,
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GetChatHistoryOutput,
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create_chat,
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get_chat_by_id,
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get_chat_history,
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get_user_chats,
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update_chat,
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)
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from repository.user_identity import get_user_identity
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chat_router = APIRouter()
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class NullableUUID(UUID):
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@classmethod
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def __get_validators__(cls):
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yield cls.validate
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@classmethod
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def validate(cls, v) -> UUID | None:
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if v == "":
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return None
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try:
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return UUID(v)
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except ValueError:
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return None
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def delete_chat_from_db(supabase_db: SupabaseDB, chat_id):
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try:
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supabase_db.delete_chat_history(chat_id)
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except Exception as e:
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print(e)
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pass
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try:
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supabase_db.delete_chat(chat_id)
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except Exception as e:
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print(e)
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pass
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def check_user_requests_limit(
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user: UserIdentity,
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):
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userDailyUsage = UserUsage(
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id=user.id, email=user.email, openai_api_key=user.openai_api_key
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)
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date = time.strftime("%Y%m%d")
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userDailyUsage.handle_increment_user_request_count(date)
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if user.openai_api_key is None:
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max_requests_number = int(os.getenv("MAX_REQUESTS_NUMBER", 1))
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if int(userDailyUsage.daily_requests_count) >= int(max_requests_number):
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raise HTTPException(
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status_code=429, # pyright: ignore reportPrivateUsage=none
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detail="You have reached the maximum number of requests for today.", # pyright: ignore reportPrivateUsage=none
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)
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else:
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pass
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@chat_router.get("/chat/healthz", tags=["Health"])
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async def healthz():
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return {"status": "ok"}
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# get all chats
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@chat_router.get("/chat", dependencies=[Depends(AuthBearer())], tags=["Chat"])
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async def get_chats(current_user: UserIdentity = Depends(get_current_user)):
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"""
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Retrieve all chats for the current user.
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- `current_user`: The current authenticated user.
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- Returns a list of all chats for the user.
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This endpoint retrieves all the chats associated with the current authenticated user. It returns a list of chat objects
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containing the chat ID and chat name for each chat.
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"""
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chats = get_user_chats(str(current_user.id))
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return {"chats": chats}
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# delete one chat
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@chat_router.delete(
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"/chat/{chat_id}", dependencies=[Depends(AuthBearer())], tags=["Chat"]
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)
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async def delete_chat(chat_id: UUID):
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"""
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Delete a specific chat by chat ID.
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"""
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supabase_db = get_supabase_db()
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delete_chat_from_db(supabase_db=supabase_db, chat_id=chat_id)
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return {"message": f"{chat_id} has been deleted."}
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# update existing chat metadata
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@chat_router.put(
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"/chat/{chat_id}/metadata", dependencies=[Depends(AuthBearer())], tags=["Chat"]
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)
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async def update_chat_metadata_handler(
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chat_data: ChatUpdatableProperties,
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chat_id: UUID,
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current_user: UserIdentity = Depends(get_current_user),
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) -> Chat:
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"""
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Update chat attributes
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"""
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chat = get_chat_by_id(chat_id) # pyright: ignore reportPrivateUsage=none
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if str(current_user.id) != chat.user_id:
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raise HTTPException(
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status_code=403, # pyright: ignore reportPrivateUsage=none
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detail="You should be the owner of the chat to update it.", # pyright: ignore reportPrivateUsage=none
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)
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return update_chat(chat_id=chat_id, chat_data=chat_data)
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# create new chat
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@chat_router.post("/chat", dependencies=[Depends(AuthBearer())], tags=["Chat"])
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async def create_chat_handler(
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chat_data: CreateChatProperties,
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current_user: UserIdentity = Depends(get_current_user),
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):
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"""
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Create a new chat with initial chat messages.
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"""
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return create_chat(user_id=current_user.id, chat_data=chat_data)
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# add new question to chat
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@chat_router.post(
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"/chat/{chat_id}/question",
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dependencies=[
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Depends(
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AuthBearer(),
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),
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],
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tags=["Chat"],
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)
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async def create_question_handler(
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request: Request,
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chat_question: ChatQuestion,
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chat_id: UUID,
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brain_id: NullableUUID
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| UUID
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| None = Query(..., description="The ID of the brain"),
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current_user: UserIdentity = Depends(get_current_user),
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) -> GetChatHistoryOutput:
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"""
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Add a new question to the chat.
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"""
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# Retrieve user's OpenAI API key
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current_user.openai_api_key = request.headers.get("Openai-Api-Key")
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brain = Brain(id=brain_id)
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if not current_user.openai_api_key and brain_id:
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brain_details = get_brain_details(brain_id)
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if brain_details:
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current_user.openai_api_key = brain_details.openai_api_key
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if not current_user.openai_api_key:
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user_identity = get_user_identity(current_user.id)
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if user_identity is not None:
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current_user.openai_api_key = user_identity.openai_api_key
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# Retrieve chat model (temperature, max_tokens, model)
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if (
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not chat_question.model
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or not chat_question.temperature
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or not chat_question.max_tokens
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):
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# TODO: create ChatConfig class (pick config from brain or user or chat) and use it here
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chat_question.model = chat_question.model or brain.model or "gpt-3.5-turbo"
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chat_question.temperature = chat_question.temperature or brain.temperature or 0
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chat_question.max_tokens = chat_question.max_tokens or brain.max_tokens or 256
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try:
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check_user_requests_limit(current_user)
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gpt_answer_generator: HeadlessQA | OpenAIBrainPicking
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if brain_id:
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gpt_answer_generator = OpenAIBrainPicking(
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chat_id=str(chat_id),
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model=chat_question.model,
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max_tokens=chat_question.max_tokens,
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temperature=chat_question.temperature,
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brain_id=str(brain_id),
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user_openai_api_key=current_user.openai_api_key, # pyright: ignore reportPrivateUsage=none
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prompt_id=chat_question.prompt_id,
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)
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else:
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gpt_answer_generator = HeadlessQA(
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model=chat_question.model,
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temperature=chat_question.temperature,
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max_tokens=chat_question.max_tokens,
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user_openai_api_key=current_user.openai_api_key, # pyright: ignore reportPrivateUsage=none
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chat_id=str(chat_id),
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prompt_id=chat_question.prompt_id,
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)
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chat_answer = gpt_answer_generator.generate_answer(chat_id, chat_question)
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return chat_answer
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except HTTPException as e:
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raise e
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# stream new question response from chat
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@chat_router.post(
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"/chat/{chat_id}/question/stream",
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dependencies=[
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Depends(
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AuthBearer(),
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),
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],
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tags=["Chat"],
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)
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async def create_stream_question_handler(
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request: Request,
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chat_question: ChatQuestion,
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chat_id: UUID,
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brain_id: NullableUUID
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| UUID
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| None = Query(..., description="The ID of the brain"),
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current_user: UserIdentity = Depends(get_current_user),
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) -> StreamingResponse:
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# TODO: check if the user has access to the brain
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# Retrieve user's OpenAI API key
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current_user.openai_api_key = request.headers.get("Openai-Api-Key")
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brain = Brain(id=brain_id)
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brain_details: BrainEntity | None = None
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if not current_user.openai_api_key and brain_id:
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brain_details = get_brain_details(brain_id)
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if brain_details:
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current_user.openai_api_key = brain_details.openai_api_key
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if not current_user.openai_api_key:
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user_identity = get_user_identity(current_user.id)
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if user_identity is not None:
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current_user.openai_api_key = user_identity.openai_api_key
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# Retrieve chat model (temperature, max_tokens, model)
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if (
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not chat_question.model
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or chat_question.temperature is None
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or not chat_question.max_tokens
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):
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# TODO: create ChatConfig class (pick config from brain or user or chat) and use it here
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chat_question.model = chat_question.model or brain.model or "gpt-3.5-turbo"
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chat_question.temperature = chat_question.temperature or brain.temperature or 0
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chat_question.max_tokens = chat_question.max_tokens or brain.max_tokens or 256
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try:
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logger.info(f"Streaming request for {chat_question.model}")
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check_user_requests_limit(current_user)
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gpt_answer_generator: HeadlessQA | OpenAIBrainPicking
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if brain_id:
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gpt_answer_generator = OpenAIBrainPicking(
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chat_id=str(chat_id),
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model=(brain_details or chat_question).model
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if current_user.openai_api_key
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else "gpt-3.5-turbo",
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max_tokens=(brain_details or chat_question).max_tokens
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if current_user.openai_api_key
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else 0,
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temperature=(brain_details or chat_question).temperature
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if current_user.openai_api_key
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else 256,
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brain_id=str(brain_id),
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user_openai_api_key=current_user.openai_api_key, # pyright: ignore reportPrivateUsage=none
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streaming=True,
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prompt_id=chat_question.prompt_id,
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)
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else:
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gpt_answer_generator = HeadlessQA(
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model=chat_question.model
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if current_user.openai_api_key
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else "gpt-3.5-turbo",
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temperature=chat_question.temperature
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if current_user.openai_api_key
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else 256,
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max_tokens=chat_question.max_tokens
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if current_user.openai_api_key
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else 0,
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user_openai_api_key=current_user.openai_api_key, # pyright: ignore reportPrivateUsage=none
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chat_id=str(chat_id),
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streaming=True,
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prompt_id=chat_question.prompt_id,
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)
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print("streaming")
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return StreamingResponse(
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gpt_answer_generator.generate_stream(chat_id, chat_question),
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media_type="text/event-stream",
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)
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except HTTPException as e:
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raise e
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# get chat history
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@chat_router.get(
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"/chat/{chat_id}/history", dependencies=[Depends(AuthBearer())], tags=["Chat"]
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)
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async def get_chat_history_handler(
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chat_id: UUID,
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) -> List[GetChatHistoryOutput]:
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# TODO: RBAC with current_user
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return get_chat_history(str(chat_id))
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