app.py

import os
import gradio as gr
import requests

BACKEND_URL = "https://0learn-fastchat.hf.space"  # Update this with your actual FastAPI backend URL

class ConversationState:
    def __init__(self):
        self.conversation_id = None

state = ConversationState()

def chat_with_groq(message, history):
    messages = [{"role": "user" if i % 2 == 0 else "assistant", "content": msg} 
                for i, msg in enumerate(history + [message])]
    
    payload = {"messages": messages}
    if state.conversation_id:
        payload["conversation_id"] = state.conversation_id
    
    response = requests.post(f"{BACKEND_URL}/chat", json=payload)
    response_data = response.json()
    
    state.conversation_id = response_data["conversation_id"]
    return response_data["response"]

def load_conversation(conversation_id):
    response = requests.get(f"{BACKEND_URL}/conversations/{conversation_id}")
    if response.status_code == 200:
        conversation_data = response.json()
        state.conversation_id = conversation_id
        return conversation_data["messages"]
    else:
        return []

def respond(message, chat_history):
    bot_message = chat_with_groq(message, chat_history)
    chat_history.append((message, bot_message))
    return "", chat_history

with gr.Blocks() as demo:
    gr.Markdown("# Groq Chatbot with Conversation Persistence")
    
    with gr.Row():
        conversation_id_input = gr.Textbox(label="Conversation ID (optional)")
        load_button = gr.Button("Load Conversation")
    
    chatbot = gr.Chatbot()
    msg = gr.Textbox()
    clear = gr.Button("Clear")

    msg.submit(respond, [msg, chatbot], [msg, chatbot])
    clear.click(lambda: None, None, chatbot, queue=False)
    
    load_button.click(load_conversation, inputs=[conversation_id_input], outputs=[chatbot])

demo.launch()