app.py

import os
from typing import Optional, Tuple

import gradio as gr
import pickle
from query_data import get_chain
from threading import Lock

with open("vectorstore.pkl", "rb") as f:
    vectorstore = pickle.load(f)


def set_openai_api_key(api_key: str):
    """Set the api key and return chain.
    If no api_key, then None is returned.
    """
    if api_key:
        os.environ["OPENAI_API_KEY"] = api_key
        chain = get_chain(vectorstore)
        os.environ["OPENAI_API_KEY"] = ""
        return chain
        

class ChatWrapper:

    def __init__(self):
        self.lock = Lock()
    def __call__(
        self, api_key: str, inp: str, history: Optional[Tuple[str, str]], chain
    ):
        """Execute the chat functionality."""
        self.lock.acquire()
        chain = set_openai_api_key('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')
        try:
            history = history or []
            # If chain is None, that is because no API key was provided.
            if chain is None:
                history.append((inp, "Please paste your OpenAI key to use"))
                return history, history
            # Set OpenAI key
            import openai
            openai.api_key = api_key
            # Run chain and append input.
            output = chain({"question": inp, "chat_history": history})["answer"]
            history.append((inp, output))
        except Exception as e:
            raise e
        finally:
            self.lock.release()
        return history, history

chat = ChatWrapper()
state = gr.State()
       
def echo(name, request: gr.Request):
    if request:
        print("Request headers dictionary:", request.headers)
        print("IP address:", request.client.host)
        print("Body", request.body)
    return name

def my_inference_function(name):
  return "Hello " + name + "!"

gradio_interface = gr.Interface(chat, inputs=['text',state], outputs=['text', state])
gradio_interface.launch()