Create app.py

app.py

@@ -0,0 +1,157 @@
+import gradio as gr
+import requests
+import os
+import time
+
+# Configuration
+API_TOKEN = os.environ.get("HF_TOKEN", "")
+MODEL_NAME = "deepseek-ai/Janus-Pro-7B"
+API_URL = f"https://api-inference.huggingface.co/models/{MODEL_NAME}"
+headers = {"Authorization": f"Bearer {API_TOKEN}"}
+
+def query_janus_model(payload):
+    """Send request to Hugging Face Inference API"""
+    try:
+        response = requests.post(API_URL, headers=headers, json=payload, timeout=30)
+        
+        if response.status_code == 503:
+            return {"error": "Model is loading, please try again in 30-60 seconds..."}
+        elif response.status_code != 200:
+            return {"error": f"API Error: {response.status_code} - {response.text}"}
+            
+        return response.json()
+    except requests.exceptions.Timeout:
+        return {"error": "Request timeout - model might be loading"}
+    except Exception as e:
+        return {"error": f"Connection error: {str(e)}"}
+
+def chat_with_janus(message, history):
+    """Chat function for Janus-Pro model"""
+    if not API_TOKEN:
+        return "⚠️ Please add your Hugging Face token in Space Settings → Repository secrets → HF_TOKEN"
+    
+    # Prepare the payload
+    payload = {
+        "inputs": message,
+        "parameters": {
+            "max_new_tokens": 300,
+            "temperature": 0.7,
+            "top_p": 0.9,
+            "do_sample": True,
+            "return_full_text": False
+        },
+        "options": {
+            "wait_for_model": True
+        }
+    }
+    
+    # Show loading message
+    yield "🔄 Processing your request... (Model might take 30-60 seconds to load)"
+    
+    # Query the model
+    result = query_janus_model(payload)
+    
+    # Process the response
+    if "error" in result:
+        yield f"❌ {result['error']}"
+    elif isinstance(result, list) and len(result) > 0:
+        if 'generated_text' in result[0]:
+            yield result[0]['generated_text']
+        else:
+            yield str(result[0])
+    elif isinstance(result, dict) and 'generated_text' in result:
+        yield result['generated_text']
+    else:
+        yield f"📄 Response: {str(result)}"
+
+def clear_chat():
+    """Clear chat history"""
+    return [], []
+
+# Custom CSS for better appearance
+css = """
+.gradio-container {
+    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+}
+.chatbot {
+    background: white;
+    border-radius: 10px;
+}
+"""
+
+# Create the chat interface
+with gr.Blocks(theme=gr.themes.Soft(), css=css) as demo:
+    gr.Markdown(
+        """
+        # 🚀 Janus-Pro-7B Chat API
+        **Multimodal AI Model** - Understanding & Generation Capabilities
+        
+        *Note: First request may take 30-60 seconds while the model loads*
+        """
+    )
+    
+    with gr.Row():
+        with gr.Column(scale=1):
+            gr.Markdown("### ℹ️ About Janus-Pro")
+            gr.Markdown("""
+            - **Model**: Janus-Pro-7B by DeepSeek
+            - **Capabilities**: Text understanding & generation
+            - **License**: MIT
+            - **Framework**: Unified multimodal transformer
+            """)
+            
+        with gr.Column(scale=2):
+            chatbot = gr.Chatbot(
+                label="Chat with Janus-Pro",
+                height=400,
+                show_copy_button=True
+            )
+            
+            with gr.Row():
+                msg = gr.Textbox(
+                    label="Your message",
+                    placeholder="Type your message here... (Press Enter to send)",
+                    scale=4,
+                    container=False
+                )
+                clear_btn = gr.Button("🗑️ Clear", scale=1)
+            
+            with gr.Row():
+                gr.Examples(
+                    examples=[
+                        "Explain quantum computing in simple terms",
+                        "Write a short poem about artificial intelligence",
+                        "What are the benefits of renewable energy?",
+                        "How does machine learning work?"
+                    ],
+                    inputs=msg,
+                    label="Try these examples:"
+                )
+    
+    # Event handlers
+    msg.submit(
+        fn=chat_with_janus,
+        inputs=[msg, chatbot],
+        outputs=chatbot
+    ).then(
+        lambda: "",  # Clear input
+        outputs=msg
+    )
+    
+    clear_btn.click(
+        fn=clear_chat,
+        outputs=[chatbot, msg]
+    )
+    
+    gr.Markdown(
+        """
+        ---
+        **Tips**: 
+        - Be specific in your questions for better responses
+        - The model excels at technical explanations and creative writing
+        - First message may be slow as the model loads
+        """
+    )
+
+if __name__ == "__main__":
+    demo.launch(debug=True)