Create app.py

app.py

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+#imagetext-to-text
+import gradio as gr
+import base64
+from huggingface_hub import InferenceClient
+client = InferenceClient('meta-llama/Llama-3.2-11B-Vision-Instruct')
+
+
+def imageDescription(image, prompt):
+ image_path="image.png"
+ image.save(image_path)
+ with open(image_path, "rb") as f:
+   base64_image = base64.b64encode(f.read()).decode("utf-8")
+ image_url = f"data:image/png;base64,{base64_image}"
+ output = client.chat.completions.create(messages=[
+       {
+           "role": "user",
+           "content": [
+               {
+                   "type": "image_url",
+                   "image_url": {"url": image_url},
+               },
+               {
+                   "type": "text",
+                   "text": prompt,
+               },
+           ],
+       },
+   ],
+ )
+ return output.choices[0].message.content
+
+
+with gr.Blocks(theme=gr.themes.Citrus()) as demo:
+   with gr.Row():
+     with gr.Column():
+       #an image input
+       image=gr.Image(type="pil", label="upload an immage")
+       prompt = gr.Textbox(label="What would you like to know about this picture?",scale=1)
+       describe_btn = gr.Button("Describe the image",scale=1)
+       output = gr.Textbox(label="Description",scale=1)
+     with gr.Column():
+       #sending two inputs to imageDescription function
+       describe_btn.click(fn=imageDescription, inputs=[image, prompt], outputs=output)
+demo.launch(debug=True)