Create app.py

app.py

@@ -0,0 +1,57 @@
+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 []
+
+with gr.Blocks() as iface:
+    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")
+
+    def respond(message, chat_history):
+        bot_message = chat_with_groq(message, chat_history)
+        chat_history.append((message, bot_message))
+        return "", chat_history
+
+    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])
+
+if __name__ == "__main__":
+    iface.launch()