import os
import gradio as gr
from langchain.chat_models import ChatOpenAI
from langchain.chains import ConversationChain
from langchain.memory import ConversationBufferMemory

# Load OpenAI API key from environment variable
openai_api_key = os.getenv("OPENAI_API_KEY")

# Initialize the language model
llm = ChatOpenAI(temperature=0.7, openai_api_key=openai_api_key)

# Initialize conversation memory
memory = ConversationBufferMemory()

# Create a conversation chain
conversation = ConversationChain(llm=llm, memory=memory)

# Define Gradio interface
def chat_with_agent(user_input):
    response = conversation.predict(input=user_input)
    return response

iface = gr.Interface(fn=chat_with_agent,
                     inputs=gr.Textbox(lines=2, placeholder="Ask me anything..."),
                     outputs="text",
                     title="LangChain Agent with GPT-3.5",
                     description="A simple conversational agent using LangChain and OpenAI GPT-3.5")

if __name__ == "__main__":
    iface.launch()