from langchain.chat_models import ChatOpenAI
from langchain.schema import AIMessage, HumanMessage
from langchain_community.chat_models import ChatOpenAI
from langchain_openai import ChatOpenAI
import openai, os
import gradio as gr
from dotenv import load_dotenv
load_dotenv()   

OPENAI_API_KEY = os.environ['GROQ_API_KEY']

llm = ChatOpenAI(temperature=1.0, model='gpt-3.5-turbo-0613')
# llm = ChatOpenAI(temperature=1.0, model='gpt-4-turbo')
# llm = openai(temperature=1.0, model='gpt-4o')

def predict(message, history):
    history_langchain_format = []
    for human, ai in history:
        history_langchain_format.append(HumanMessage(content=human))
        history_langchain_format.append(AIMessage(content=ai))
    history_langchain_format.append(HumanMessage(content=message))
    gpt_response = llm(history_langchain_format)
    return gpt_response.content

gr.ChatInterface(predict).launch()