Update app.py

app.py

@@ -1,83 +1,240 @@
 import gradio as gr
+import os
 from openai import OpenAI
+import requests
+from PIL import Image
+import io
+import tempfile
 
-# Function to initialize the client with the provided API key
-def initialize_client(api_key):
+def analyze_environmental_impact(api_key, analysis_type, image=None, text_input=None, location=None, product_info=None):
+    """
+    Analyze environmental impact based on user inputs using Gemini 2.5 Pro through OpenRouter.
+    """
+    if not api_key:
+        return "Please provide an OpenRouter API key."
+    
     client = OpenAI(
         base_url="https://openrouter.ai/api/v1",
-        api_key=api_key
+        api_key=api_key,
     )
-    return client
-
-# Function to analyze environmental impact using Gemini 2.5 Pro
-def analyze_environmental_impact(api_key, image=None, location=None, product_info=None):
-    client = initialize_client(api_key)  # Initialize client with the user's API key
-    
-    messages = []
-
-    # If the image is provided, include it in the analysis
-    if image:
-        messages.append({
-            "role": "user",
-            "content": [
-                {"type": "text", "text": "Analyze the environmental impact of this image."},
-                {"type": "image_url", "image_url": {"url": image}}
-            ]
-        })
     
-    # If location is provided, include it in the analysis
-    if location:
-        messages.append({
-            "role": "user",
-            "content": [{"type": "text", "text": f"Analyze the environmental impact of {location}."}]
-        })
+    # Prepare messages based on analysis type
+    if analysis_type == "Image Analysis":
+        if image is None:
+            return "Please upload an image for analysis."
+            
+        # Save image to a temporary file
+        temp_file = tempfile.NamedTemporaryFile(delete=False, suffix=".jpg")
+        image_path = temp_file.name
+        image.save(image_path)
+        
+        # Convert image to base64
+        with open(image_path, "rb") as img_file:
+            import base64
+            image_base64 = base64.b64encode(img_file.read()).decode("utf-8")
+        
+        # Clean up temp file
+        os.unlink(image_path)
+        
+        prompt = """
+        Analyze this image for environmental impact factors. Consider:
+        1. Visible ecosystems, wildlife, or natural resources
+        2. Human infrastructure and its potential environmental footprint
+        3. Evidence of pollution, waste, or environmental degradation
+        4. Sustainable or eco-friendly elements
+        
+        Provide a comprehensive environmental impact assessment and suggest ways to improve 
+        sustainability based on what you see.
+        """
+        
+        messages = [
+            {
+                "role": "user",
+                "content": [
+                    {
+                        "type": "text",
+                        "text": prompt
+                    },
+                    {
+                        "type": "image_url",
+                        "image_url": {
+                            "url": f"data:image/jpeg;base64,{image_base64}"
+                        }
+                    }
+                ]
+            }
+        ]
+        
+    elif analysis_type == "Geographical Assessment":
+        if not location:
+            return "Please provide a location for geographical assessment."
+        
+        prompt = f"""
+        Provide an environmental impact assessment for the location: {location}.
+        
+        Include information about:
+        1. Current environmental conditions (air quality, water resources, biodiversity)
+        2. Major environmental challenges and threats
+        3. Sustainability initiatives and progress
+        4. Carbon footprint and emissions data
+        5. Recommendations for improving environmental sustainability in this area
+        
+        Present the information in a structured format with clear sections for each aspect.
+        """
+        
+        messages = [
+            {
+                "role": "user",
+                "content": prompt
+            }
+        ]
+        
+    elif analysis_type == "Product Assessment":
+        if not product_info:
+            return "Please provide product information for assessment."
+        
+        prompt = f"""
+        Analyze the environmental impact of the following product:
+        
+        {product_info}
+        
+        Include in your assessment:
+        1. Materials and resources used
+        2. Manufacturing process impact
+        3. Transportation and distribution footprint
+        4. Usage phase environmental impact
+        5. End-of-life considerations
+        6. Overall sustainability score on a scale of 1-10
+        7. Recommendations for improving the product's environmental footprint
+        
+        Be specific and provide actionable insights.
+        """
+        
+        messages = [
+            {
+                "role": "user",
+                "content": prompt
+            }
+        ]
+        
+    elif analysis_type == "Custom Query":
+        if not text_input:
+            return "Please provide a query for custom environmental analysis."
+        
+        prompt = f"""
+        Provide an environmental impact analysis based on the following information:
+        
+        {text_input}
+        
+        Include in your response:
+        1. Key environmental concerns identified
+        2. Potential ecological impacts - short and long term
+        3. Carbon footprint considerations
+        4. Waste and pollution factors
+        5. Biodiversity impacts
+        6. Actionable recommendations for sustainability
+        7. References to relevant environmental principles or frameworks
+        
+        Be specific, thorough, and provide practical advice.
+        """
+        
+        messages = [
+            {
+                "role": "user",
+                "content": prompt
+            }
+        ]
     
-    # If product information is provided, include it in the analysis
-    if product_info:
-        messages.append({
-            "role": "user",
-            "content": [{"type": "text", "text": f"Analyze the environmental impact of this product: {product_info}."}]
-        })
-    
-    # Call the model for environmental analysis
+    # Make API call
     try:
         completion = client.chat.completions.create(
             extra_headers={
-                "HTTP-Referer": "<YOUR_SITE_URL>",  # Optional
-                "X-Title": "<YOUR_SITE_NAME>",      # Optional
+                "HTTP-Referer": "https://environmental-impact-analyzer.app",  # Replace with your actual site
+                "X-Title": "Smart Environmental Impact Analyzer",
             },
             model="google/gemini-2.5-pro-exp-03-25:free",
             messages=messages
         )
-
-        response = completion.choices[0].message.content
-        return response
-
+        
+        return completion.choices[0].message.content
     except Exception as e:
-        return f"Error: {str(e)}"
-
-# Gradio interface
-def gradio_interface(api_key, image, location, product_info):
-    image_url = image if image else None  # Gradio returns file path as string for "filepath" type
-    result = analyze_environmental_impact(api_key, image=image_url, location=location, product_info=product_info)
-    return result
-
-# Create Gradio inputs and outputs
-api_key_input = gr.Textbox(label="Enter Your OpenRouter API Key", type="password")
-image_input = gr.Image(label="Upload an Image (Optional)", type="filepath")  # Fix: Changed to 'filepath'
-location_input = gr.Textbox(label="Enter Location for Environmental Impact (Optional)", type="text")
-product_info_input = gr.Textbox(label="Enter Product Information (Optional)", type="text")
-
-output = gr.Textbox(label="Environmental Impact Analysis Output", lines=10)
+        return f"Error during analysis: {str(e)}"
 
 # Create Gradio interface
-app = gr.Interface(
-    fn=gradio_interface,
-    inputs=[api_key_input, image_input, location_input, product_info_input],
-    outputs=output,
-    title="Smart Environmental Impact Analyzer",
-    description="Analyze environmental impact based on images, location, or product information. Please provide your OpenRouter API key."
-)
+with gr.Blocks(title="Smart Environmental Impact Analyzer") as app:
+    gr.Markdown("# 🌍 Smart Environmental Impact Analyzer")
+    gr.Markdown("""
+    This tool analyzes environmental impacts using Gemini 2.5 Pro AI. 
+    Choose an analysis type and provide the required information.
+    """)
+    
+    api_key = gr.Textbox(label="OpenRouter API Key", placeholder="Enter your OpenRouter API key", type="password")
+    
+    with gr.Tabs():
+        with gr.TabItem("Image Analysis"):
+            image_input = gr.Image(type="pil", label="Upload an image for environmental analysis")
+            image_submit = gr.Button("Analyze Image")
+            image_output = gr.Textbox(label="Analysis Results", lines=15)
+            
+            image_submit.click(
+                analyze_environmental_impact,
+                inputs=[api_key, gr.Textbox(value="Image Analysis", visible=False), image_input, None, None, None],
+                outputs=image_output
+            )
+        
+        with gr.TabItem("Geographical Assessment"):
+            location_input = gr.Textbox(label="Location (city, region, or country)", placeholder="e.g., Paris, France")
+            location_submit = gr.Button("Analyze Location")
+            location_output = gr.Textbox(label="Analysis Results", lines=15)
+            
+            location_submit.click(
+                analyze_environmental_impact,
+                inputs=[api_key, gr.Textbox(value="Geographical Assessment", visible=False), None, None, location_input, None],
+                outputs=location_output
+            )
+            
+        with gr.TabItem("Product Assessment"):
+            product_info = gr.Textbox(
+                label="Product Information", 
+                placeholder="Describe the product, materials, manufacturing process, lifecycle, etc.",
+                lines=5
+            )
+            product_submit = gr.Button("Analyze Product")
+            product_output = gr.Textbox(label="Analysis Results", lines=15)
+            
+            product_submit.click(
+                analyze_environmental_impact,
+                inputs=[api_key, gr.Textbox(value="Product Assessment", visible=False), None, None, None, product_info],
+                outputs=product_output
+            )
+            
+        with gr.TabItem("Custom Query"):
+            custom_input = gr.Textbox(
+                label="Custom Environmental Query",
+                placeholder="Enter your environmental question or describe a scenario to analyze",
+                lines=5
+            )
+            custom_submit = gr.Button("Analyze")
+            custom_output = gr.Textbox(label="Analysis Results", lines=15)
+            
+            custom_submit.click(
+                analyze_environmental_impact,
+                inputs=[api_key, gr.Textbox(value="Custom Query", visible=False), None, custom_input, None, None],
+                outputs=custom_output
+            )
+    
+    gr.Markdown("""
+    ### Privacy Notice
+    Your API key is used only for making requests to OpenRouter and is not stored or logged.
+    The images and text you submit are processed by Gemini 2.5 Pro through OpenRouter's API.
+    
+    ### Usage Instructions
+    1. Enter your OpenRouter API key (get one from https://openrouter.ai)
+    2. Select the type of analysis you want to perform
+    3. Provide the required information (image, location, product details, or custom query)
+    4. Click the "Analyze" button for your selected tab
+    """)
 
-# Launch the Gradio app
-app.launch()
+# Launch the app
+if __name__ == "__main__":
+    app.launch()