Create app.py

app.py

@@ -0,0 +1,126 @@
+from huggingface_hub import InferenceClient
+import gradio as gr
+import base64
+from PIL import Image
+import io
+
+client = InferenceClient(
+    provider="cohere",
+    api_key="HF_TOKEN", # Will add soon as soon as I get the auth working
+)
+
+def image_to_data_url(image_path):
+    if image_path is None:
+        return None
+    with Image.open(image_path) as img:
+        buffered = io.BytesIO()
+        img.save(buffered, format=img.format)
+        img_str = base64.b64encode(buffered.getvalue()).decode()
+        return f"data:image/{img.format.lower()};base64,{img_str}"
+
+def process_input(image, image_url, prompt, model):
+    image_data = None
+    if image is not None:
+        image_data = image_to_data_url(image)
+    elif image_url:
+        image_data = image_url
+    
+    if not image_data:
+        raise gr.Error("Please provide either an image upload or image URL")
+    
+    messages = [
+        {
+            "role": "user",
+            "content": [
+                {"type": "text", "text": prompt},
+                {"type": "image_url", "image_url": {"url": image_data}}
+            ]
+        }
+    ]
+    
+    stream = client.chat.completions.create(
+        model=model,
+        messages=messages,
+        max_tokens=512,
+        stream=True,
+    )
+    
+    full_response = ""
+    for chunk in stream:
+        content = chunk.choices[0].delta.content or ""
+        full_response += content
+        yield full_response
+
+models = [
+    "CohereLabs/aya-vision-32b",
+    "CohereLabs/aya-vision-8b",
+]
+
+with gr.Blocks() as demo:
+    gr.Markdown("# Cohere Aya Vision model UI")
+    
+    with gr.Row():
+        with gr.Column():
+            model_choice = gr.Dropdown(
+                label="Select Model",
+                choices=models,
+                value=models[0],
+                interactive=True
+            )
+            
+            with gr.Tab("Upload Image"):
+                image_input = gr.Image(
+                    label="Upload Image",
+                    type="filepath",
+                    sources=["upload"]
+                )
+            with gr.Tab("Image URL"):
+                image_url = gr.Textbox(
+                    label="Image URL",
+                    placeholder="Paste image URL here...",
+                    value=""
+                )
+            
+            prompt = gr.Textbox(
+                label="Prompt",
+                value="Describe this image in one sentence.",
+                interactive=True
+            )
+            submit_btn = gr.Button("Generate", variant="primary")
+        
+        with gr.Column():
+            output = gr.Textbox(
+                label="Model Response",
+                interactive=False,
+                lines=10,
+                autoscroll=True
+            )
+
+    submit_btn.click(
+        fn=process_input,
+        inputs=[image_input, image_url, prompt, model_choice],
+        outputs=output,
+        concurrency_limit=None
+    )
+
+    gr.Examples(
+        examples=[
+            [
+                None,
+                "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg",
+                "Describe this image in one sentence.",
+                models[0]
+            ],
+            [
+                None,
+                "https://upload.wikimedia.org/wikipedia/commons/thumb/4/4d/Cat_November_2010-1a.jpg/1200px-Cat_November_2010-1a.jpg",
+                "What is the main subject of this image?",
+                models[1]
+            ]
+        ],
+        inputs=[image_input, image_url, prompt, model_choice],
+        label="Example Inputs"
+    )
+
+if __name__ == "__main__":
+    demo.queue().launch()