Create app.py

app.py

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+import gradio as gr
+from smolagents import CodeAgent, InferenceClientModel
+
+# Set up the free serverless models via Hugging Face's infrastructure
+# These run on high-end remote GPUs for free, bypass CPU slowdowns
+models_dictionary = {
+    "DeepSeek-R1 (Reasoning)": InferenceClientModel(model_id="deepseek-ai/DeepSeek-R1"),
+    "Qwen 2.5 (General Expert)": InferenceClientModel(model_id="Qwen/Qwen2.5-72B-Instruct"),
+    "Llama 3.3 (Fast Text)": InferenceClientModel(model_id="meta-llama/Llama-3.3-70B-Instruct")
+}
+
+def ask_all_agents(user_prompt, uploaded_image):
+    responses = {}
+    
+    # Process text/image input structure safely
+    if uploaded_image:
+        # Construct multimodal input payload for vision-capable endpoints
+        content = [
+            {"type": "text", "text": user_prompt if user_prompt else "Analyze this image."},
+            {"type": "image_url", "image_url": {"url": uploaded_image}}
+        ]
+    else:
+        content = user_prompt
+
+    for name, model in models_dictionary.items():
+        try:
+            # Create a localized agent wrapper
+            agent = CodeAgent(tools=[], model=model)
+            # Execute request safely
+            result = agent.run(content)
+            responses[name] = str(result)
+        except Exception as e:
+            responses[name] = f"Could not process: {str(e)}"
+            
+    return (
+        responses["DeepSeek-R1 (Reasoning)"],
+        responses["Qwen 2.5 (General Expert)"],
+        responses["Llama 3.3 (Fast Text)"]
+    )
+
+# Build a responsive UI optimized for mobile viewports
+with gr.Blocks(theme=gr.themes.Soft()) as demo:
+    gr.Markdown("# 📱 Mobile Omni-Agent Dashboard")
+    gr.Markdown("Submit one prompt to query multiple open-source engines simultaneously.")
+    
+    with gr.Row():
+        with gr.Column():
+            text_input = gr.Textbox(label="Your Prompt", placeholder="Type your query here...", lines=3)
+            image_input = gr.Image(label="Upload Image (Optional)", type="filepath")
+            submit_btn = gr.Button("🚀 Trigger Synchronized Generation", variant="primary")
+            
+    with gr.Row():
+        out_deepseek = gr.Textbox(label="🧠 DeepSeek-R1 Output", lines=5)
+        out_qwen = gr.Textbox(label="👑 Qwen 2.5 Output", lines=5)
+        out_llama = gr.Textbox(label="🦙 Llama 3.3 Output", lines=5)
+
+    submit_btn.click(
+        fn=ask_all_agents,
+        inputs=[text_input, image_input],
+        outputs=[out_deepseek, out_qwen, out_llama]
+    )
+
+demo.launch()