app.py

import gradio as gr
import requests
import pandas as pd
import plotly.express as px

# ================================================================
# 1. Core Logic (Robust Data Fetching)
# ================================================================

def process_species_data(species_name, habitat, water_disturbance, land_disturbance, noise_level):
    if not species_name:
        return "Please enter a species name.", None, None

    # --- A. Fetch Wikipedia Data (With User-Agent Fix) ---
    wiki_url = "https://en.wikipedia.org/w/api.php"
    headers = {
        'User-Agent': 'BioVigilusApp/1.0 (educational-research-project)'
    }
    params = {
        "action": "query",
        "format": "json",
        "prop": "extracts",
        "titles": species_name.replace(" ", "_"),
        "explaintext": True,
        "exintro": False,
    }

    try:
        response = requests.get(wiki_url, params=params, headers=headers).json()
        pages = response.get("query", {}).get("pages", {})
        
        if "-1" in pages:
            extract = f"Species '{species_name}' not found. Please check spelling (e.g., use 'Panthera tigris' instead of 'Tiger')."
        else:
            page = next(iter(pages.values()))
            extract = page.get("extract", "No summary available.")
            
    except Exception as e:
        extract = f"Connection Error: {str(e)}"

    # --- B. Length Enforcement (150-250 words) ---
    words = extract.split()
    
    # If text is too short, append educational filler
    if len(words) < 150:
        educational_filler = (
            "\n\n[Additional Ecological Context]\n"
            f"The species {species_name} is an integral part of its local food web. "
            "Biodiversity loss regarding this species could trigger a trophic cascade, affecting both prey and predator populations. "
            "Conservationists monitor such species as bio-indicators of environmental health. "
            "Preserving their natural habitat is essential not just for their survival, but for the stability of the entire ecosystem. "
            "Effective conservation strategies include habitat restoration, anti-poaching laws, and community awareness programs."
        )
        extract += educational_filler
        words = extract.split()

    # Cap at ~250 words
    summary_text = " ".join(words[:250]) + "..."
    
    # --- C. Impact Analysis ---
    analysis_section = f"""

    ------------------------------------------------
    📊 ENVIRONMENTAL IMPACT ANALYSIS
    ------------------------------------------------
    • Target Habitat: {habitat}
    
    ⚠️ STRESS INDICATORS:
    • Water Stress: {water_disturbance}/100 
      (High levels indicate pollution or drought risk)
    • Land Disturbance: {land_disturbance}/100 
      (Reflects habitat fragmentation or loss)
    • Noise Pollution: {noise_level}/100 
      (Impacts communication and breeding patterns)
    """
    
    final_output = summary_text + analysis_section

    # --- D. Fetch GBIF Map Data ---
    gbif_url = f"https://api.gbif.org/v1/occurrence/search?scientificName={species_name}&limit=300"
    coords = []
    try:
        gbif_res = requests.get(gbif_url).json()
        results = gbif_res.get("results", [])
        for r in results:
            if r.get("decimalLatitude") and r.get("decimalLongitude"):
                coords.append({"lat": r.get("decimalLatitude"), "lon": r.get("decimalLongitude")})
    except:
        pass

    if coords:
        df = pd.DataFrame(coords)
        fig = px.scatter_mapbox(df, lat="lat", lon="lon", zoom=1, height=350)
        fig.update_layout(mapbox_style="open-street-map", margin={"r":0,"t":0,"l":0,"b":0})
    else:
        fig = px.scatter_mapbox(pd.DataFrame({"lat":[], "lon":[]}), lat="lat", lon="lon", zoom=0)
        fig.update_layout(mapbox_style="open-street-map", margin={"r":0,"t":0,"l":0,"b":0})

    # --- E. Create Download File ---
    filename = "BioVigilus_Report.txt"
    with open(filename, "w", encoding="utf-8") as f:
        f.write(f"=== BioVigilus Project Report ===\n{final_output}")
    
    return final_output, fig, filename

# ================================================================
# 2. VIBRANT CSS (Safe Mode)
# ================================================================

vibrant_css = """
<style>
    .gradio-container {
        background: linear-gradient(135deg, #004d40 0%, #2e7d32 100%) !important;
    }
    #main-title {
        color: #ffffff !important;
        font-family: sans-serif;
        font-weight: 800;
        font-size: 2.5rem;
        text-shadow: 2px 2px 4px rgba(0,0,0,0.3);
        text-align: center;
        margin-bottom: 5px;
    }
    #sub-title {
        color: #a5d6a7 !important; 
        font-size: 1.2rem; 
        text-align: center; 
        margin-bottom: 25px;
        font-family: sans-serif;
    }
    .custom-card {
        background: #ffffff !important;
        padding: 25px !important;
        border-radius: 12px !important;
        box-shadow: 0 10px 30px rgba(0,0,0,0.2) !important;
        border: none !important;
    }
    /* Button - Gradient Green */
    button.primary {
        background: linear-gradient(90deg, #1b5e20 0%, #2e7d32 100%) !important;
        color: white !important;
        font-size: 1.1rem !important;
        border-radius: 8px !important;
    }
</style>
"""

# ================================================================
# 3. UI Layout
# ================================================================

with gr.Blocks() as demo:
    
    gr.HTML(vibrant_css)
    
    gr.HTML("""
        <div id="main-title">🌿 BioVigilus</div>
        <div id="sub-title">Advanced Biodiversity & Environmental Stress Analyzer</div>
    """)

    with gr.Row():
        # --- LEFT: INPUTS ---
        with gr.Column(elem_classes="custom-card"): 
            gr.Markdown("### 🔍 Species Configuration")
            species_name = gr.Textbox(
                label="Scientific Name", 
                placeholder="e.g. Panthera tigris", 
                value="Panthera tigris"
            )
            
            habitat = gr.Dropdown(
                ["Tropical Rainforest", "Savanna", "Desert", "Wetlands", "Urban", "Marine"], 
                label="Habitat Environment", 
                value="Tropical Rainforest"
            )

            gr.Markdown("---")
            gr.Markdown("### ⚠️ Environmental Stressors")
            
            water = gr.Slider(0, 100, value=25, label="Water Pollution Level")
            land = gr.Slider(0, 100, value=65, label="Land Degradation")
            noise = gr.Slider(0, 100, value=30, label="Noise Pollution (dB)")

            analyze_btn = gr.Button("🚀 Run Analysis", variant="primary")

        # --- RIGHT: OUTPUTS ---
        with gr.Column(elem_classes="custom-card"):
            gr.Markdown("### 📊 Analysis Results")
            
            # REMOVED 'show_copy_button' to fix crash
            out_summary = gr.Textbox(
                label="Ecological Summary & Impact Report", 
                lines=12,
                interactive=False
            )
            
            out_map = gr.Plot(label="Global Occurrence Map")
            out_file = gr.File(label="📥 Download Full Report")

    analyze_btn.click(
        process_species_data, 
        inputs=[species_name, habitat, water, land, noise], 
        outputs=[out_summary, out_map, out_file]
    )

if __name__ == "__main__":
    demo.launch()