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import openai |
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from fastapi import FastAPI, HTTPException |
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from fastapi.responses import StreamingResponse |
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from fastapi.middleware.cors import CORSMiddleware |
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from pydantic import BaseModel |
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from fastapi import FastAPI, HTTPException, Depends, Request, Response |
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from fastapi.security import OAuth2PasswordBearer |
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from tinydb import TinyDB |
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from tinydb import Query |
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from datetime import datetime |
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from utils import generate_token |
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query = Query() |
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db = TinyDB(".token.json") |
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app = FastAPI() |
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origins = ["*"] |
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app.add_middleware( |
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CORSMiddleware, |
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allow_origins=origins, |
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allow_credentials=True, |
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allow_methods=["*"], |
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allow_headers=["*"], |
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) |
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oauth2_scheme = OAuth2PasswordBearer(tokenUrl="token") |
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REF_KEY = "F0eeQ419wvoCSPH7KBmsd9OiVkF0W0DxK1XE9T3BlbkFJ0" |
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model_name = "" |
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def verify_token(token: str = Depends(oauth2_scheme)): |
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expiry = -1 |
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res = db.get(query.token == token) |
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if res: |
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expiry = (datetime.strptime(res["expiry_date"], '%Y-%m-%d') - datetime.strptime(res["created_at"], '%Y-%m-%d')).days |
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if expiry < 0: |
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return {"message": "Token is not Valid"} |
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return token |
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class ChatInput(BaseModel): |
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message: str |
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openAI_token: str |
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class RefToken(BaseModel): |
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expiry_date: str |
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ref_key: str |
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def get_openai_generator(prompt: str): |
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openai_stream = openai.ChatCompletion.create( |
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model="gpt-3.5-turbo", |
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messages=[{"role": "user", "content": prompt}], |
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temperature=0.0, |
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stream=True, |
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) |
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for event in openai_stream: |
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if "content" in event["choices"][0].delta: |
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current_response = event["choices"][0].delta.content |
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yield current_response |
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@app.get("/") |
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async def base_url(): |
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try: |
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return { |
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"Please Check the documentation here": "https://huggingface.co/spaces/subhrajit-katonic/stream-chatapi/blob/main/README.md", |
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"Swagger UI" : "https://subhrajit-katonic-stream-chatapi.hf.space/docs" |
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} |
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except Exception as e: |
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raise HTTPException(status_code=500, detail="An error occurred while processing the request." + str(e)) |
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@app.post("/create") |
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async def create(data: RefToken): |
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token = "Reference Key is incorrect" |
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try: |
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if data.ref_key == REF_KEY: |
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token = generate_token(data.expiry_date, db) |
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return {"TOKEN": token} |
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except Exception as e: |
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raise HTTPException(status_code=500, detail="An error occurred while processing the request." + str(e)) |
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@app.get("/list") |
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async def list(token: str = Depends(verify_token)): |
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try: |
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data = db.all() |
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return {"data": data} |
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except Exception as e: |
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raise HTTPException(status_code=500, detail="An error occurred while processing the request." + str(e)) |
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@app.post("/chat") |
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async def chat(chat_input: ChatInput, token: str = Depends(verify_token)): |
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openai.api_key = chat_input.openAI_token |
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prompt = f"User: {chat_input.message}\nAI:" |
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try: |
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return StreamingResponse(get_openai_generator(prompt), media_type='text/event-stream') |
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except Exception as e: |
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raise HTTPException(status_code=500, detail="An error occurred while processing the request." + str(e)) |
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