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app.py

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+import gradio as gr
+import google.generativeai as genai
+import base64
+from io import BytesIO
+from PIL import Image
+
+# Set up Google GenAI API Key (Replace with your actual API key)
+genai.configure(api_key="AIzaSyBZ_ehc2Q00pGiexfVYJmrN6-hxkEUHEMs")  
+
+def image_to_tamil_poem(image):
+    """Generates a Tamil poem about an upload image using Gemini 1.5 Pro"""
+
+    try:
+        # Convert image to bytes
+        buffered = BytesIO()
+        image.save(buffered, format="PNG")
+        img_bytes = buffered.getvalue()
+        
+        # Convert image to Base64 for Gemini API
+        image_b64 = base64.b64encode(img_bytes).decode('utf-8')
+        prompt = "Describe this image in one sentence."
+
+        # Use Gemini 1.5 Pro for image analysis
+        model = genai.GenerativeModel("gemini-1.5-pro")
+        response = model.generate_content([{"mime_type": "image/png", "data": image_b64}, prompt])
+        description = response.text if response else "No description available."
+
+        # Generate Tamil poem based on the description
+        response_poem = model.generate_content(f"Based on this image description: {description}, write a short poem in Tamil.")
+        tamil_poem = response_poem.text if response_poem else "கவிதை உருவாக்கப்படவில்லை."
+
+        return tamil_poem
+
+    except Exception as e:
+        return f"⚠️ Error: {str(e)}"
+
+# Define Gradio Interface
+interface = gr.Interface(
+    fn=image_to_tamil_poem,
+    inputs=gr.Image(type="pil"),
+    outputs=gr.Textbox(label="Generated Tamil Poem"),
+    title="AI-Powered Tamil Poem Generator (Using Gemini AI)",
+    description="Upload an image, and AI will generate a short Tamil poem based on it."
+)
+
+if __name__ == "__main__":
+    interface.launch()

requirements.txt

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+gradio
+google-generativeai
+pillow