Create v1.txt

v1.txt

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+import gradio as gr
+import os
+from openai import OpenAI
+import json
+import requests
+from PIL import Image
+import io
+import base64
+
+# Constants
+DEFAULT_MODEL = "opengvlab/internvl3-14b:free"
+# No need for placeholder text as we'll use password type input
+DEFAULT_SITE_URL = "https://dynamic-nature-trail-guide.app"
+DEFAULT_SITE_NAME = "Dynamic Nature Trail Guide"
+
+# Initialize system prompt for better nature guide responses
+SYSTEM_PROMPT = """
+You are the Dynamic Nature Trail Guide, an expert in identifying and explaining natural elements 
+found on nature trails. For any image sent, please:
+1. Identify all visible plants, animals, geological features, and ecosystems
+2. Provide educational information about identified elements
+3. Mention any seasonal characteristics visible in the image
+4. Note any ecological significance or conservation considerations
+5. Offer suggestions for what to observe or learn about next on the trail
+Keep explanations informative yet accessible to people of all ages and backgrounds.
+"""
+
+def encode_image_to_base64(image_path):
+    """Convert an image file to base64 encoding"""
+    with open(image_path, "rb") as image_file:
+        return base64.b64encode(image_file.read()).decode('utf-8')
+
+def analyze_image(api_key, image, prompt="What can you identify in this nature trail image? Provide detailed educational information.", site_url=DEFAULT_SITE_URL, site_name=DEFAULT_SITE_NAME, model=DEFAULT_MODEL):
+    """Analyze the uploaded image using the InternVL3 model via OpenRouter"""
+    # Remove the placeholder text check
+    if not api_key:
+        return "Please provide an OpenRouter API key."
+    
+    if image is None:
+        return "Please upload an image to analyze."
+    
+    # Save the image temporarily
+    temp_image_path = "temp_image.jpg"
+    image.save(temp_image_path)
+    
+    try:
+        # Convert image to base64
+        base64_image = encode_image_to_base64(temp_image_path)
+        
+        # Initialize OpenAI client
+        client = OpenAI(
+            base_url="https://openrouter.ai/api/v1",
+            api_key=api_key,
+        )
+        
+        # Create message with image and text
+        response = client.chat.completions.create(
+            extra_headers={
+                "HTTP-Referer": site_url, 
+                "X-Title": site_name,
+            },
+            model=model,
+            messages=[
+                {"role": "system", "content": SYSTEM_PROMPT},
+                {
+                    "role": "user",
+                    "content": [
+                        {
+                            "type": "text",
+                            "text": prompt
+                        },
+                        {
+                            "type": "image_url",
+                            "image_url": {
+                                "url": f"data:image/jpeg;base64,{base64_image}"
+                            }
+                        }
+                    ]
+                }
+            ]
+        )
+        
+        analysis_result = response.choices[0].message.content
+        return analysis_result
+    
+    except Exception as e:
+        return f"Error analyzing image: {str(e)}"
+    
+    finally:
+        # Clean up the temporary file
+        if os.path.exists(temp_image_path):
+            os.remove(temp_image_path)
+
+def build_custom_prompt(identification=True, education=True, seasonal=True, conservation=True, suggestions=True, additional_prompt=""):
+    """Build a custom prompt based on user preferences"""
+    prompt_parts = []
+    
+    if identification:
+        prompt_parts.append("Identify all visible plants, animals, geological features, and ecosystems")
+    
+    if education:
+        prompt_parts.append("Provide educational information about identified elements")
+    
+    if seasonal:
+        prompt_parts.append("Mention any seasonal characteristics visible in the image")
+    
+    if conservation:
+        prompt_parts.append("Note any ecological significance or conservation considerations")
+    
+    if suggestions:
+        prompt_parts.append("Offer suggestions for what to observe or learn next on the trail")
+    
+    if additional_prompt:
+        prompt_parts.append(additional_prompt)
+    
+    if not prompt_parts:
+        return "What can you identify in this nature trail image?"
+    
+    numbered_prompt = "\n".join([f"{i+1}. {part}" for i, part in enumerate(prompt_parts)])
+    return f"For this nature trail image, please: \n{numbered_prompt}"
+
+def create_interface():
+    """Create the Gradio interface for the Dynamic Nature Trail Guide"""
+    with gr.Blocks(title="Dynamic Nature Trail Guide", theme=gr.themes.Soft()) as app:
+        gr.Markdown("""
+        # 🌿 Dynamic Nature Trail Guide: Accessible Outdoor Education 🌿
+        
+        Upload an image from your nature walk to identify plants, animals, geological features, and learn about the ecosystem.
+        This application uses the advanced InternVL3 14B multimodal model for nature identification and education.
+        """)
+        
+        with gr.Row():
+            with gr.Column(scale=1):
+                api_key_input = gr.Textbox(
+                    label="OpenRouter API Key", 
+                    placeholder="Enter your OpenRouter API key here...",
+                    type="password"
+                )
+                image_input = gr.Image(label="Upload Nature Image", type="pil")
+                
+                with gr.Accordion("Advanced Settings", open=False):
+                    site_url = gr.Textbox(
+                        label="Site URL (for OpenRouter)", 
+                        value=DEFAULT_SITE_URL
+                    )
+                    site_name = gr.Textbox(
+                        label="Site Name (for OpenRouter)", 
+                        value=DEFAULT_SITE_NAME
+                    )
+                    model_selection = gr.Dropdown(
+                        label="Model",
+                        choices=[DEFAULT_MODEL],
+                        value=DEFAULT_MODEL
+                    )
+                
+                with gr.Accordion("Customize Analysis", open=False):
+                    gr.Markdown("Select what information you want to receive about the image:")
+                    identification_checkbox = gr.Checkbox(label="Species & Feature Identification", value=True)
+                    education_checkbox = gr.Checkbox(label="Educational Information", value=True)
+                    seasonal_checkbox = gr.Checkbox(label="Seasonal Characteristics", value=True)
+                    conservation_checkbox = gr.Checkbox(label="Conservation Considerations", value=True)
+                    suggestions_checkbox = gr.Checkbox(label="Trail Suggestions", value=True)
+                    additional_prompt = gr.Textbox(label="Additional Instructions (Optional)")
+                
+                analyze_button = gr.Button("Analyze Nature Image", variant="primary")
+            
+            with gr.Column(scale=1):
+                output_text = gr.Markdown(label="Analysis Results")
+        
+        # Set up the click event for the analyze button
+        analyze_button.click(
+            fn=lambda api_key, image, id_check, edu_check, season_check, conserve_check, suggest_check, add_prompt, site_url, site_name, model: 
+                analyze_image(
+                    api_key, 
+                    image, 
+                    build_custom_prompt(id_check, edu_check, season_check, conserve_check, suggest_check, add_prompt),
+                    site_url,
+                    site_name,
+                    model
+                ),
+            inputs=[
+                api_key_input, 
+                image_input, 
+                identification_checkbox,
+                education_checkbox,
+                seasonal_checkbox,
+                conservation_checkbox,
+                suggestions_checkbox,
+                additional_prompt,
+                site_url,
+                site_name,
+                model_selection
+            ],
+            outputs=output_text
+        )
+        
+        # Example gallery
+        with gr.Accordion("Example Images", open=False):
+            gr.Markdown("Click on an example image to analyze it:")
+            example_images = gr.Examples(
+                examples=[
+                    "examples/forest_trail.jpg",
+                    "examples/wetland_boardwalk.jpg",
+                    "examples/mountain_vista.jpg",
+                    "examples/coastal_trail.jpg",
+                ],
+                inputs=image_input,
+                label="Nature Trail Examples"
+            )
+            
+        gr.Markdown("""
+        ## How to Use This App
+        
+        1. Enter your OpenRouter API key (sign up at [openrouter.ai](https://openrouter.ai) if needed)
+        2. Upload an image from your nature walk
+        3. Customize what kind of information you want (optional)
+        4. Click "Analyze Nature Image"
+        5. Explore the detailed educational content about what you're seeing
+        
+        This application is designed to make nature more accessible and educational for everyone!
+        """)
+    
+    return app
+
+# Create and launch the app
+if __name__ == "__main__":
+    app = create_interface()
+    app.launch()