Create app.py

app.py

@@ -0,0 +1,53 @@
+import gradio as gr
+from groq import Groq
+import os
+
+# Initialize Groq client
+client = Groq(api_key=os.getenv("GROQ_API_KEY"))
+
+def process_image_and_get_response(image, user_description):
+    """
+    Process the uploaded image and user description, then get a response from Groq.
+    Since Groq's API doesn't support images, we use the description as input.
+    """
+    if not user_description:
+        user_description = "Describe this image."  # Placeholder for image-to-text
+    try:
+        completion = client.chat.completions.create(
+            model="meta-llama/llama-4-maverick-17b-128e-instruct",
+            messages=[
+                {
+                    "role": "user",
+                    "content": user_description
+                }
+            ],
+            temperature=1,
+            max_completion_tokens=1024,
+            top_p=1,
+            stream=True,
+            stop=None
+        )
+
+        # Collect streamed response
+        response = ""
+        for chunk in completion:
+            response += chunk.choices[0].delta.content or ""
+        return response
+    except Exception as e:
+        return f"Error: {str(e)}"
+
+# Define Gradio interface
+iface = gr.Interface(
+    fn=process_image_and_get_response,
+    inputs=[
+        gr.Image(type="pil", label="Upload an Image"),
+        gr.Textbox(label="Describe the image (optional)", placeholder="Enter a description or leave blank")
+    ],
+    outputs=gr.Textbox(label="Groq AI Response"),
+    title="Image-based Groq AI Chat",
+    description="Upload an image and optionally provide a description. The Groq AI will respond based on the description."
+)
+
+# Launch the interface
+if __name__ == "__main__":
+    iface.launch()