Update app.py

app.py

@@ -1,29 +1,86 @@
+import gradio as gr
 from openai import OpenAI
+import os
+from PIL import Image
+import tempfile
 
+# Initialize the OpenAI client with OpenRouter
 client = OpenAI(
-  base_url="https://openrouter.ai/api/v1",
-  api_key="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",
+    base_url="https://openrouter.ai/api/v1",
+    api_key="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",
 )
 
-completion = client.chat.completions.create(
-  extra_body={},
-  model="meta-llama/llama-4-maverick:free",
-  messages=[
-    {
-      "role": "user",
-      "content": [
-        {
-          "type": "text",
-          "text": "What is in this image?"
-        },
-        {
-          "type": "image_url",
-          "image_url": {
-            "url": "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg"
-          }
-        }
-      ]
-    }
-  ]
-)
-print(completion.choices[0].message.content)
+def process_input(text_input, image_input):
+    messages = [{"role": "user", "content": []}]
+
+    # Add text input if provided
+    if text_input:
+        messages[0]["content"].append({
+            "type": "text",
+            "text": text_input
+        })
+
+    # Add image input if provided
+    if image_input is not None:
+        # Save the image to a temporary file
+        with tempfile.NamedTemporaryFile(delete=False, suffix=".jpg") as temp_file:
+            image_path = temp_file.name
+            if isinstance(image_input, str):  # If it's already a file path
+                Image.open(image_input).save(image_path)
+            else:  # If it's an image object from Gradio
+                image_input.save(image_path)
+
+        # Encode and add the image
+        import base64
+        with open(image_path, "rb") as image_file:
+            base64_image = base64.b64encode(image_file.read()).decode('utf-8')
+
+        messages[0]["content"].append({
+            "type": "image_url",
+            "image_url": {
+                "url": f"data:image/jpeg;base64,{base64_image}"
+            }
+        })
+
+        # Clean up temporary file
+        os.unlink(image_path)
+
+    # If neither text nor image is provided
+    if not text_input and image_input is None:
+        return "Please provide either text, an image, or both."
+
+    try:
+        # Call the API
+        completion = client.chat.completions.create(
+            extra_body={},
+            model="meta-llama/llama-4-maverick:free",
+            messages=messages
+        )
+
+        return completion.choices[0].message.content
+    except Exception as e:
+        return f"Error: {str(e)}"
+
+# Create the Gradio interface
+with gr.Blocks() as demo:
+    gr.Markdown("# LLaMA 4 Maverick AI Assistant")
+    gr.Markdown("Enter text, upload an image, or both to get a response from the AI.")
+
+    with gr.Row():
+        with gr.Column():
+            text_input = gr.Textbox(label="Text Input", placeholder="Type your question or prompt here...")
+            image_input = gr.Image(label="Image Input (Optional)", type="pil")
+            submit_btn = gr.Button("Submit")
+
+        with gr.Column():
+            output = gr.Textbox(label="AI Response", lines=10)
+
+    submit_btn.click(
+        fn=process_input,
+        inputs=[text_input, image_input],
+        outputs=output
+    )
+
+# Launch the app
+if __name__ == "__main__":
+    demo.launch()