app.py

import os
import gradio as gr
import re
import folium
from fastai.vision.all import *
from groq import Groq
from PIL import Image

# Load the trained model
learn = load_learner('export.pkl')
labels = learn.dls.vocab

# Initialize Groq client
client = Groq(
    api_key=os.environ.get("GROQ_API_KEY"),
)

# Language translations
translations = {
    "en": {
        "app_title": "Bird Species Explorer: AI-Powered Identification for Researchers",
        "app_description": "🔍 Upload a bird photo to instantly identify species and access comprehensive data on habitats, behaviors, and climate change impacts. A powerful tool for Tanzania-based ornithological research.",
        "upload_label": "Upload Bird Image",
        "identify_button": "Identify Bird",
        "predictions_label": "Top 5 Predictions",
        "bird_info_label": "Bird Information",
        "research_questions": "Research Questions",
        "question_placeholder": "Example: How has climate change affected this bird's migration pattern?",
        "question_label": "Ask a question about this bird",
        "submit_question": "Submit Question",
        "clear_conversation": "Clear Conversation",
        "upload_prompt": "Please upload an image",
        "question_title": "Question:",
        "answer_title": "Answer:",
        "habitat_map_title": "Natural Habitat Map for",
        "detailed_info_title": "Detailed Information",
        "language_label": "Language / Lugha"
    },
    "sw": {
        "app_title": "Mtafiti wa Ndege: Utambuzi wa Kiotomatiki kwa Watafiti",
        "app_description": "🔍 Pakia picha ya ndege ili kutambua spishi mara moja na kupata data kamili kuhusu makazi, tabia, na athari za mabadiliko ya tabianchi. Zana yenye nguvu kwa utafiti wa ndege nchini Tanzania.",
        "upload_label": "Pakia Picha ya Ndege",
        "identify_button": "Tambua Ndege",
        "predictions_label": "Utabiri Bora 5",
        "bird_info_label": "Taarifa za Ndege",
        "research_questions": "Maswali ya Utafiti",
        "question_placeholder": "Mfano: Je, mabadiliko ya tabianchi yameathiri vipi mfumo wa uhamiaji wa ndege huyu?",
        "question_label": "Uliza swali kuhusu ndege huyu",
        "submit_question": "Wasilisha Swali",
        "clear_conversation": "Futa Mazungumzo",
        "upload_prompt": "Tafadhali pakia picha",
        "question_title": "Swali:",
        "answer_title": "Jibu:",
        "habitat_map_title": "Ramani ya Makazi Asilia ya",
        "detailed_info_title": "Taarifa za Kina",
        "language_label": "Language / Lugha"
    }
}

def clean_bird_name(name):
    """Clean bird name by removing numbers and special characters, and fix formatting"""
    # Remove numbers and dots at the beginning
    cleaned = re.sub(r'^\d+\.', '', name)
    # Replace underscores with spaces
    cleaned = cleaned.replace('_', ' ')
    # Remove any remaining special characters
    cleaned = re.sub(r'[^\w\s]', '', cleaned)
    # Fix spacing
    cleaned = ' '.join(cleaned.split())
    return cleaned

def get_bird_habitat_map(bird_name, check_tanzania=True):
    """Get habitat map locations for the bird using Groq API"""
    clean_name = clean_bird_name(bird_name)
    
    # First check if the bird is endemic to Tanzania
    if check_tanzania:
        tanzania_check_prompt = f"""
        Is the {clean_name} bird native to or commonly found in Tanzania? 
        Answer with ONLY "yes" or "no".
        """
        
        try:
            tanzania_check = client.chat.completions.create(
                messages=[{"role": "user", "content": tanzania_check_prompt}],
                model="llama-3.3-70b-versatile",
            )
            is_in_tanzania = "yes" in tanzania_check.choices[0].message.content.lower()
        except:
            # Default to showing Tanzania if we can't determine
            is_in_tanzania = True
    else:
        is_in_tanzania = True
    
    # Now get the habitat locations
    prompt = f"""
    Provide a JSON array of the main habitat locations for the {clean_name} bird in the world. 
    Return ONLY a JSON array with 3-5 entries, each containing:
    1. "name": Location name
    2. "lat": Latitude (numeric value)
    3. "lon": Longitude (numeric value)
    4. "description": Brief description of why this is a key habitat (2-3 sentences)
    
    Example format:
    [
      {{"name": "Example Location", "lat": 12.34, "lon": 56.78, "description": "Brief description"}},
      ...
    ]
    
    {'' if is_in_tanzania else 'DO NOT include any locations in Tanzania as this bird is not native to or commonly found there.'}
    """
    
    try:
        chat_completion = client.chat.completions.create(
            messages=[
                {
                    "role": "user",
                    "content": prompt,
                }
            ],
            model="llama-3.3-70b-versatile",
        )
        response = chat_completion.choices[0].message.content
        
        # Extract JSON from response (in case there's additional text)
        import json
        import re
        
        # Find JSON pattern in response
        json_match = re.search(r'\[.*\]', response, re.DOTALL)
        if json_match:
            locations = json.loads(json_match.group())
        else:
            # Fallback if JSON extraction fails
            locations = [
                {"name": "Primary habitat region", "lat": 0, "lon": 0, 
                 "description": "Could not retrieve specific habitat information for this bird."}
            ]
        
        return locations, is_in_tanzania
        
    except Exception as e:
        return [{"name": "Error retrieving data", "lat": 0, "lon": 0, 
                "description": "Please try again or check your connection."}], False

def create_habitat_map(habitat_locations):
    """Create a folium map with the habitat locations"""
    # Find center point based on valid coordinates
    valid_coords = [(loc.get("lat", 0), loc.get("lon", 0)) 
                    for loc in habitat_locations 
                    if loc.get("lat", 0) != 0 or loc.get("lon", 0) != 0]
    
    if valid_coords:
        # Calculate the average of the coordinates
        avg_lat = sum(lat for lat, _ in valid_coords) / len(valid_coords)
        avg_lon = sum(lon for _, lon in valid_coords) / len(valid_coords)
        # Create map centered on the average coordinates
        m = folium.Map(location=[avg_lat, avg_lon], zoom_start=3)
    else:
        # Default world map if no valid coordinates
        m = folium.Map(location=[20, 0], zoom_start=2)
    
    # Add markers for each habitat location
    for location in habitat_locations:
        name = location.get("name", "Unknown")
        lat = location.get("lat", 0)
        lon = location.get("lon", 0)
        description = location.get("description", "No description available")
        
        # Skip invalid coordinates
        if lat == 0 and lon == 0:
            continue
            
        # Add marker
        folium.Marker(
            location=[lat, lon],
            popup=folium.Popup(f"<b>{name}</b><br>{description}", max_width=300),
            tooltip=name
        ).add_to(m)
    
    # Save map to HTML
    map_html = m._repr_html_()
    return map_html

def format_bird_info(raw_info, language="en"):
    """Improve the formatting of bird information"""
    # Add proper line breaks between sections and ensure consistent heading levels
    formatted = raw_info
    
    # Get translation of warning text based on language
    warning_text = "NOT TYPICALLY FOUND IN TANZANIA"
    warning_translation = "HAPATIKANI SANA TANZANIA" if language == "sw" else warning_text
    
    # Fix heading levels (make all main sections h3)
    formatted = re.sub(r'#+\s+' + warning_text, 
                        f'<div class="alert alert-warning"><strong>⚠️ {warning_translation}</strong></div>', 
                        formatted)
    
    # Replace markdown headings with HTML headings for better control
    formatted = re.sub(r'#+\s+(.*)', r'<h3>\1</h3>', formatted)
    
    # Add paragraph tags for better spacing
    formatted = re.sub(r'\n\*\s+(.*)', r'<p>• \1</p>', formatted)
    formatted = re.sub(r'\n([^<\n].*)', r'<p>\1</p>', formatted)
    
    # Remove any duplicate paragraph tags
    formatted = formatted.replace('<p><p>', '<p>')
    formatted = formatted.replace('</p></p>', '</p>')
    
    return formatted

def get_bird_info(bird_name, language="en"):
    """Get detailed information about a bird using Groq API"""
    clean_name = clean_bird_name(bird_name)
    
    # Adjust language for the prompt
    lang_instruction = ""
    if language == "sw":
        lang_instruction = " Provide your response in Swahili language."
    
    prompt = f"""
    Provide detailed information about the {clean_name} bird, including:
    1. Physical characteristics and appearance
    2. Habitat and distribution
    3. Diet and behavior
    4. Migration patterns (emphasize if this pattern has changed in recent years due to climate change)
    5. Conservation status
    
    If this bird is not commonly found in Tanzania, explicitly flag that this bird is "NOT TYPICALLY FOUND IN TANZANIA" at the beginning of your response and explain why its presence might be unusual.
    
    Format your response in markdown for better readability.{lang_instruction}
    """
    
    try:
        chat_completion = client.chat.completions.create(
            messages=[
                {
                    "role": "user",
                    "content": prompt,
                }
            ],
            model="llama-3.3-70b-versatile",
        )
        return chat_completion.choices[0].message.content
    except Exception as e:
        error_msg = "Hitilafu katika kupata taarifa" if language == "sw" else "Error fetching information"
        return f"{error_msg}: {str(e)}"

def predict_and_get_info(img, language="en"):
    """Predict bird species and get detailed information"""
    # Get translations
    t = translations[language]
    
    # Process the image
    img = PILImage.create(img)
    
    # Get prediction
    pred, pred_idx, probs = learn.predict(img)
    
    # Get top 5 predictions (or all if less than 5)
    num_classes = min(5, len(labels))
    top_indices = probs.argsort(descending=True)[:num_classes]
    top_probs = probs[top_indices]
    top_labels = [labels[i] for i in top_indices]
    
    # Format as dictionary with cleaned names for display
    prediction_results = {clean_bird_name(top_labels[i]): float(top_probs[i]) for i in range(num_classes)}
    
    # Get top prediction (original format for info retrieval)
    top_bird = str(pred)
    # Also keep a clean version for display
    clean_top_bird = clean_bird_name(top_bird)
    
    # Get habitat locations and create map
    habitat_locations, is_in_tanzania = get_bird_habitat_map(top_bird)
    habitat_map_html = create_habitat_map(habitat_locations)
    
    # Get detailed information about the top predicted bird
    bird_info = get_bird_info(top_bird, language)
    formatted_info = format_bird_info(bird_info, language)
    
    # Create combined info with map at the top and properly formatted information
    custom_css = """
    <style>
    .bird-container {
        font-family: Arial, sans-serif;
        padding: 10px;
    }
    .map-container {
        height: 400px;
        width: 100%;
        border: 1px solid #ddd;
        border-radius: 8px;
        overflow: hidden;
        margin-bottom: 20px;
    }
    .info-container {
        line-height: 1.6;
    }
    .info-container h3 {
        margin-top: 20px;
        margin-bottom: 10px;
        color: #2c3e50;
        border-bottom: 1px solid #eee;
        padding-bottom: 5px;
    }
    .info-container p {
        margin-bottom: 10px;
    }
    .alert {
        padding: 10px;
        margin-bottom: 15px;
        border-radius: 4px;
    }
    .alert-warning {
        background-color: #fcf8e3;
        border: 1px solid #faebcc;
        color: #8a6d3b;
    }
    </style>
    """
    
    combined_info = f"""
    {custom_css}
    <div class="bird-container">
        <h2>{t['habitat_map_title']} {clean_top_bird}</h2>
        <div class="map-container">
            {habitat_map_html}
        </div>
        
        <div class="info-container">
            <h2>{t['detailed_info_title']}</h2>
            {formatted_info}
        </div>
    </div>
    """
    
    return prediction_results, combined_info, clean_top_bird

def follow_up_question(question, bird_name, language="en"):
    """Allow researchers to ask follow-up questions about the identified bird"""
    t = translations[language]
    
    if not question.strip() or not bird_name:
        return "Please identify a bird first and ask a specific question about it." if language == "en" else "Tafadhali tambua ndege kwanza na uulize swali maalum kuhusu ndege huyo."
    
    # Adjust language for the prompt
    lang_instruction = ""
    if language == "sw":
        lang_instruction = " Provide your response in Swahili language."
    
    prompt = f"""
    The researcher is asking about the {bird_name} bird: "{question}"
    
    Provide a detailed, scientific answer focusing on accurate ornithological information. 
    If the question relates to Tanzania or climate change impacts, emphasize those aspects in your response.
    
    IMPORTANT: Do not repeat basic introductory information about the bird that would have already been provided in a general description.
    Do not start your answer with phrases like "Introduction to the {bird_name}" or similar repetitive headers.
    Directly answer the specific question asked.
    
    Format your response in markdown for better readability.{lang_instruction}
    """
    
    try:
        chat_completion = client.chat.completions.create(
            messages=[
                {
                    "role": "user",
                    "content": prompt,
                }
            ],
            model="llama-3.3-70b-versatile",
        )
        return chat_completion.choices[0].message.content
    except Exception as e:
        error_msg = "Hitilafu katika kupata taarifa" if language == "sw" else "Error fetching information"
        return f"{error_msg}: {str(e)}"

# Create the Gradio interface
with gr.Blocks(theme=gr.themes.Soft()) as app:
    # Current language and bird state
    current_lang = gr.State("en")
    current_bird = gr.State("")
    
    # Header with language switcher
    with gr.Row():
        with gr.Column(scale=3):
            title_md = gr.Markdown(f"# {translations['en']['app_title']}")
        with gr.Column(scale=1):
            language_selector = gr.Radio(
                choices=["English", "Kiswahili"], 
                label=translations['en']['language_label'], 
                value="English"
            )
    
    # App description
    description_md = gr.Markdown(f"{translations['en']['app_description']}")
    
    # Main identification section
    with gr.Row():
        with gr.Column(scale=1):
            input_image = gr.Image(type="pil", label=translations['en']['upload_label'])
            submit_btn = gr.Button(translations['en']['identify_button'], variant="primary")
        
        with gr.Column(scale=2):
            prediction_output = gr.Label(label=translations['en']['predictions_label'], num_top_classes=5)
            bird_info_output = gr.HTML(label=translations['en']['bird_info_label'])
    
    # Clear divider
    gr.Markdown("---")
    
    # Follow-up question section with improved UI
    questions_header = gr.Markdown(f"## {translations['en']['research_questions']}")
    
    conversation_history = gr.Markdown("")
    
    with gr.Row():
        follow_up_input = gr.Textbox(
            label=translations['en']['question_label'], 
            placeholder=translations['en']['question_placeholder'],
            lines=2
        )
    
    with gr.Row():
        follow_up_btn = gr.Button(translations['en']['submit_question'], variant="primary")
        clear_btn = gr.Button(translations['en']['clear_conversation'])
    
    # Functions for event handlers
    def process_image(img, lang):
        if img is None:
            return None, translations[lang]['upload_prompt'], "", ""
        
        try:
            pred_results, info, clean_bird_name = predict_and_get_info(img, lang)
            return pred_results, info, clean_bird_name, ""
        except Exception as e:
            error_msg = "Hitilafu katika kuchakata picha" if lang == "sw" else "Error processing image"
            return None, f"{error_msg}: {str(e)}", "", ""
    
    def update_conversation(question, bird_name, history, lang):
        t = translations[lang]
        
        if not question.strip():
            return history
        
        answer = follow_up_question(question, bird_name, lang)
        
        # Format the conversation with clear separation
        new_exchange = f"""
### {t['question_title']}
{question}
### {t['answer_title']}
{answer}
---
"""
        updated_history = new_exchange + history
        return updated_history
    
    def clear_conversation_history():
        return ""
    
    def update_language(choice):
        # Convert selection to language code
        lang = "sw" if choice == "Kiswahili" else "en"
        t = translations[lang]
        
        # Return updated UI components based on selected language
        return (
            lang, 
            f"# {t['app_title']}", 
            f"{t['app_description']}", 
            t['upload_label'],
            t['identify_button'],
            t['predictions_label'],
            t['bird_info_label'],
            f"## {t['research_questions']}",
            t['question_label'],
            t['question_placeholder'],
            t['submit_question'],
            t['clear_conversation']
        )
    
    # Set up event handlers
    language_selector.change(
        update_language,
        inputs=[language_selector],
        outputs=[
            current_lang,
            title_md,
            description_md,
            input_image,
            submit_btn,
            prediction_output,
            bird_info_output,
            questions_header,
            follow_up_input,
            follow_up_input,
            follow_up_btn,
            clear_btn
        ]
    )
    
    submit_btn.click(
        process_image,
        inputs=[input_image, current_lang],
        outputs=[prediction_output, bird_info_output, current_bird, conversation_history]
    )
    
    follow_up_btn.click(
        update_conversation,
        inputs=[follow_up_input, current_bird, conversation_history, current_lang],
        outputs=[conversation_history]
    ).then(
        lambda: "", 
        outputs=follow_up_input
    )
    
    clear_btn.click(
        clear_conversation_history,
        outputs=[conversation_history]
    )

# Launch the app
app.launch(share=True)