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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() |