Create app.py

app.py

@@ -1,39 +0,0 @@
-import gradio as gr
-from main import api as fastapi_app
-from main import invoke_agent, QueryRequest
-
-# This function is designed to accept ONE argument: a list of messages.
-def get_agent_response(messages: list):
-    """
-    This function is called by the Gradio UI.
-    'messages' is a list of dictionaries in the OpenAI format.
-    e.g., [{"role": "user", "content": "Hello!"}]
-    """
-    # The message list from Gradio is already in the correct format for our backend
-    request = QueryRequest(messages=messages)
-    
-    try:
-        # Call the invoke_agent function directly
-        response_data = invoke_agent(request)
-        # Return the content string for Gradio to display
-        return response_data["response"]
-    except Exception as e:
-        print(f"Error calling agent logic: {e}")
-        return "An error occurred while processing your request."
-
-# This component is configured to SEND ONE argument because of type="messages"
-chatbot_ui = gr.ChatInterface(
-    fn=get_agent_response,
-    title="Sarvam AI Agent",
-    description="Ask me about horoscopes, holidays, and more!",
-    # THIS LINE IS THE FIX. It makes the component and function match.
-    type="messages",
-    examples=[
-        "What is the horoscope for Leo today?", 
-        "Tell me the panchang for today",
-        "What are the Indian holidays in 2025?"
-    ]
-)
-
-# Mount the Gradio UI onto the FastAPI backend
-app = gr.mount_gradio_app(fastapi_app, chatbot_ui, path="/")