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import os |
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import gradio as gr |
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from huggingface_hub import InferenceClient |
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client = InferenceClient( |
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provider="sambanova", |
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api_key=os.environ["HF_TOKEN"], |
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) |
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def llama4_image_chat(image_url, question): |
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messages = [ |
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{ |
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"role": "user", |
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"content": [ |
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{"type": "text", "text": question}, |
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{ |
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"type": "image_url", |
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"image_url": {"url": image_url} |
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} |
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] |
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} |
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] |
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completion = client.chat.completions.create( |
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model="meta-llama/Llama-4-Maverick-17B-128E-Instruct", |
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messages=messages |
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) |
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return completion.choices[0].message.content |
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with gr.Blocks() as demo: |
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gr.Markdown("## 🦙 LLaMA 4 Visual Chat") |
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gr.Markdown("Upload an image URL and ask a question.") |
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with gr.Row(): |
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image_url_input = gr.Textbox(label="Image URL", placeholder="Paste image URL here...") |
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question_input = gr.Textbox(label="Question", placeholder="e.g., Describe this image in one sentence.") |
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submit_btn = gr.Button("Ask LLaMA 4") |
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output_box = gr.Textbox(label="Response", lines=6) |
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submit_btn.click(fn=llama4_image_chat, inputs=[image_url_input, question_input], outputs=output_box) |
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demo.launch() |
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