Create minimal Gradio app for testing

- Remove all complex dependencies
- Create simple echo chatbot
- Use only gradio==4.19.2
- Test basic HuggingFace deployment

app.py

@@ -1,18 +1,30 @@
 """
-Hugging Face Spaces entry point for the AI Assistant Multi-Agent System
+Minimal Gradio app for HuggingFace Spaces
 """
-
-import sys
+import gradio as gr
 import os
 
-# Add the py directory to the Python path
-sys.path.insert(0, os.path.join(os.path.dirname(__file__), 'py'))
+def chat_function(message, history):
+    """Simple chat function that echoes the message"""
+    response = f"I received your message: '{message}'. This is a test deployment."
+    return response
 
-# Import and run the actual app
-from frontend.gradio_app import create_gradio_interface
+# Create interface
+with gr.Blocks() as demo:
+    gr.Markdown("# AI Assistant Multi-Agent System")
+    gr.Markdown("This is a simplified version for testing HuggingFace deployment.")
+    
+    chatbot = gr.Chatbot()
+    msg = gr.Textbox()
+    clear = gr.Button("Clear")
+    
+    def respond(message, chat_history):
+        bot_message = chat_function(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)
 
 if __name__ == "__main__":
-    # Create and launch the Gradio interface
-    demo = create_gradio_interface()
-    # Use Gradio's default launch settings for HuggingFace Spaces
     demo.launch()

requirements.txt

@@ -1,19 +1,2 @@
 # Core dependencies
-gradio==4.19.2
-openai
-tiktoken
-
-# LangChain
-langchain
-langchain-openai
-langchain-community
-
-# Vector operations
-numpy
-
-# Utilities
-python-dotenv
-pydantic
-pydantic-settings
-SQLAlchemy
-PyYAML
+gradio==4.19.2