Create app.py

app.py

@@ -0,0 +1,129 @@
+import gradio as gr
+import os
+from openai import OpenAI
+import re
+
+def extract_medicine_names(api_key, image_path, model_choice):
+    """
+    Extract medicine names from a prescription image using OpenRouter API
+    """
+    if not api_key or api_key.strip() == "":
+        return "Please provide a valid OpenRouter API key."
+    
+    if not image_path:
+        return "Please upload an image."
+    
+    try:
+        # Initialize the OpenAI client with OpenRouter base URL
+        client = OpenAI(
+            base_url="https://openrouter.ai/api/v1",
+            api_key=api_key,
+        )
+        
+        # Select the model based on user's choice
+        if model_choice == "Llama 4 Maverick":
+            model = "meta-llama/llama-4-maverick:free"
+        else:  # Default to Kimi VL
+            model = "moonshotai/kimi-vl-a3b-thinking:free"
+        
+        # Prepare image for API
+        with open(image_path, "rb") as image_file:
+            import base64
+            image_data = base64.b64encode(image_file.read()).decode("utf-8")
+            
+        # Create the completion
+        completion = client.chat.completions.create(
+            extra_headers={
+                "HTTP-Referer": "https://medicine-extractor-app.com",
+                "X-Title": "Medicine Name Extractor",
+            },
+            model=model,
+            messages=[
+                {
+                    "role": "system",
+                    "content": "You are a specialized medical assistant. Your task is to analyze prescription images and extract ONLY the names of medicines/medications. Return them as a clear, numbered list without any other commentary. If you cannot identify any medicine names, state that clearly."
+                },
+                {
+                    "role": "user",
+                    "content": [
+                        {
+                            "type": "text",
+                            "text": "Please extract and list ONLY the names of medicines or medications from this prescription image."
+                        },
+                        {
+                            "type": "image_url",
+                            "image_url": {
+                                "url": f"data:image/jpeg;base64,{image_data}"
+                            }
+                        }
+                    ]
+                }
+            ]
+        )
+        
+        # Get the response
+        result = completion.choices[0].message.content
+        
+        # Process to ensure we're only returning medicine names
+        # This is a basic processing step - the system prompt should already help focus the response
+        if "no medicine" in result.lower() or "cannot identify" in result.lower():
+            return "No medicine names were identified in the prescription image."
+        
+        return result
+        
+    except Exception as e:
+        return f"Error: {str(e)}"
+
+# Define the Gradio interface
+with gr.Blocks(title="Medicine Name Extractor", theme=gr.themes.Soft()) as app:
+    gr.Markdown("# Medicine Name Extractor")
+    gr.Markdown("Upload a prescription image and the app will extract medication names using AI vision models.")
+    
+    with gr.Row():
+        with gr.Column():
+            api_key = gr.Textbox(
+                label="OpenRouter API Key", 
+                placeholder="Enter your OpenRouter API key here",
+                type="password"
+            )
+            
+            model_choice = gr.Radio(
+                ["Llama 4 Maverick", "Kimi VL"], 
+                label="Select AI Model",
+                value="Kimi VL"
+            )
+            
+            image_input = gr.Image(
+                label="Upload Prescription Image",
+                type="filepath"
+            )
+            
+            submit_btn = gr.Button("Extract Medicine Names", variant="primary")
+        
+        with gr.Column():
+            output = gr.Textbox(
+                label="Extracted Medicine Names",
+                lines=10
+            )
+    
+    # Handle the submission
+    submit_btn.click(
+        fn=extract_medicine_names,
+        inputs=[api_key, image_input, model_choice],
+        outputs=output
+    )
+    
+    gr.Markdown("""
+    ## How to use
+    1. Enter your OpenRouter API key
+    2. Select an AI vision model
+    3. Upload a clear image of a medical prescription
+    4. Click "Extract Medicine Names"
+    
+    ## Privacy Note
+    Your prescription images are processed securely. No data is stored on our servers.
+    """)
+
+# Launch the app
+if __name__ == "__main__":
+    app.launch()