Create app.py

app.py

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+#imagetext-to-text
+#huggingface spaces
+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)