app.py

import os

import gradio as gr
from langchain.schema import AIMessage, HumanMessage
from langchain_openai import ChatOpenAI
from pydantic import BaseModel, SecretStr


class APIKey(BaseModel):
    api_key: SecretStr


def set_api_key(api_key: SecretStr):
    os.environ["OPENAI_API_KEY"] = api_key.get_secret_value()
    llm = ChatOpenAI(temperature=1.0, model="gpt-3.5-turbo-0125")
    return llm


def predict(message, chat_history, api_key):
    api_key_model = APIKey(api_key=api_key)
    llm = set_api_key(api_key_model.api_key)

    history_langchain_format = []
    for human, ai in chat_history:
        history_langchain_format.append(HumanMessage(content=human))
        history_langchain_format.append(AIMessage(content=ai))
    history_langchain_format.append(HumanMessage(content=message))
    openai_response = llm.invoke(history_langchain_format)
    chat_history.append((message, openai_response.content))
    return "", chat_history


with gr.Blocks() as demo:
    with gr.Row():
        api_key = gr.Textbox(
            label="Please enter your OpenAI API key",
            type="password",
            elem_id="lets-chat-langchain-oakey",
        )

    with gr.Row():
        msg = gr.Textbox(label="Please enter your message")

    with gr.Row():
        chatbot = gr.Chatbot(label="OpenAI Chatbot")

    with gr.Row():
        clear = gr.ClearButton([msg, chatbot])

    def respond(message, chat_history, api_key):
        return predict(message, chat_history, api_key)

    api_key.submit(respond, [msg, chatbot, api_key], [msg, chatbot])
    msg.submit(respond, [msg, chatbot, api_key], [msg, chatbot])

demo.launch()