import gradio as gr import os # Simple chat function - replace with actual AI model integration def chat(message, history): """ Chat function that processes user messages. Replace this with actual AI model calls (e.g., Gemini, OpenAI, HuggingFace models). """ # Check if user wants to generate an image image_keywords = ["generate", "create", "draw", "make", "show me"] is_image_request = any(keyword in message.lower() for keyword in image_keywords) and \ any(word in message.lower() for word in ["image", "picture", "photo", "art", "drawing"]) if is_image_request: # Placeholder for image generation # In production, integrate with DALL-E, Stable Diffusion, etc. response = f"🎨 I would generate an image for: '{message}'\n\n" response += "To enable image generation, integrate with:\n" response += "- OpenAI DALL-E API\n" response += "- Stable Diffusion (HuggingFace)\n" response += "- Google Imagen\n\n" response += "Add your API keys in Space secrets and update this function." else: # Placeholder for text chat # In production, integrate with Gemini, GPT-4, Llama, etc. response = f"You said: {message}\n\n" response += "This is a placeholder response. To enable AI chat, integrate with:\n" response += "- Google Gemini API\n" response += "- OpenAI GPT-4 API\n" response += "- HuggingFace models (Llama, Mistral, etc.)\n\n" response += "Add your API keys in Space secrets and update the chat function." return response # Create Gradio Chat Interface demo = gr.ChatInterface( fn=chat, title="🤖 AI Chat Assistant", description="Chat with AI - Ask questions or request image generation!", examples=[ "Hello! How are you?", "Generate an image of a red sports car", "What is machine learning?", "Create a picture of a sunset over mountains" ] ) if __name__ == "__main__": demo.launch(server_name="0.0.0.0", server_port=7860)