Update app.py

app.py

@@ -3,7 +3,6 @@ import requests
 import pandas as pd
 import plotly.express as px
 import qrcode
-from io import BytesIO
 
 # ================================================================
 # Helper Function: Species Summary + Map + QR Code
@@ -14,7 +13,7 @@ def process_species_data(species_name, habitat, water_disturbance, land_disturba
         return "Please enter a species name.", None, None
 
     # ======================
-    # 1. Fetch Wikipedia Summary (Full Extract)
+    # 1. Fetch Wikipedia Summary
     # ======================
     wiki_url = "https://en.wikipedia.org/w/api.php"
     params = {
@@ -25,24 +24,28 @@ def process_species_data(species_name, habitat, water_disturbance, land_disturba
         "explaintext": True
     }
 
-    response = requests.get(wiki_url, params=params).json()
-    pages = response.get("query", {}).get("pages", {})
-    page = next(iter(pages.values()))
-
-    extract = page.get("extract", "No summary available for this species.")
-
-    # Ensure at least 200 words
+    try:
+        response = requests.get(wiki_url, params=params).json()
+        pages = response.get("query", {}).get("pages", {})
+        # Handle cases where page is not found
+        if "-1" in pages:
+            extract = "Species not found in Wikipedia database."
+        else:
+            page = next(iter(pages.values()))
+            extract = page.get("extract", "No summary available for this species.")
+    except Exception as e:
+        extract = "Error fetching data from Wikipedia."
+
+    # Word count check
     words = extract.split()
     if len(words) < 200:
-        extract += "\n\n" + (
-            "This species plays a crucial ecological role, influencing biodiversity, habitat structure, "
-            "and environmental balance. Its presence often reflects the health of local ecosystems, and "
-            "changes in population trends can indicate environmental stress. Conservation efforts are "
-            "frequently focused on such species due to their importance in maintaining natural stability. "
-            * 3
-        )
+        filler = (
+            " This species plays a crucial ecological role, influencing biodiversity, habitat structure, "
+            "and environmental balance. Its presence often reflects the health of local ecosystems. "
+        ) * 3
+        extract += "\n\n" + filler
 
-    summary = " ".join(words[:350])  # around 300–350 words
+    summary = " ".join(words[:350])  # Cap around 350 words
 
     # Add environmental interpretation
     summary += f"""
@@ -60,38 +63,40 @@ Higher disturbance values indicate increased pressure on this species' survival
     # 2. Fetch GBIF Occurrence Data (Map API)
     # ======================
     gbif_url = f"https://api.gbif.org/v1/occurrence/search?scientificName={species_name}&limit=200"
-    gbif_res = requests.get(gbif_url).json()
-
-    results = gbif_res.get("results", [])
+    
     coords = []
-
-    for r in results:
-        lat = r.get("decimalLatitude")
-        lon = r.get("decimalLongitude")
-        if lat and lon:
-            coords.append({"lat": lat, "lon": lon})
+    try:
+        gbif_res = requests.get(gbif_url).json()
+        results = gbif_res.get("results", [])
+        for r in results:
+            lat = r.get("decimalLatitude")
+            lon = r.get("decimalLongitude")
+            if lat and lon:
+                coords.append({"lat": lat, "lon": lon})
+    except Exception:
+        pass # Fail silently for map if API errors
 
     if coords:
         df = pd.DataFrame(coords)
         fig = px.scatter_mapbox(df, lat="lat", lon="lon", zoom=1, height=400)
-        fig.update_layout(mapbox_style="open-street-map")
+        fig.update_layout(mapbox_style="open-street-map", margin={"r":0,"t":0,"l":0,"b":0})
     else:
-        fig = None
+        # Return an empty map figure if no coordinates found
+        fig = px.scatter_mapbox(pd.DataFrame({"lat":[], "lon":[]}), lat="lat", lon="lon", zoom=1)
+        fig.update_layout(mapbox_style="open-street-map")
 
     # ======================
     # 3. QR Code Generator
     # ======================
-    qr_data = f"BioVigilus Report\nSpecies: {species_name}\nHabitat: {habitat}\nSummary: {summary[:150]}..."
+    qr_data = f"BioVigilus Report\nSpecies: {species_name}\nHabitat: {habitat}\nSummary: {summary[:100]}..."
+    
+    # Generate QR and return PIL Image directly (Best for Gradio)
+    qr_img = qrcode.make(qr_data)
     
-    qr_img = BytesIO()
-    qr = qrcode.make(qr_data)
-    qr.save(qr_img)
-    qr_img.seek(0)
-
     return summary, fig, qr_img
 
 # ================================================================
-# Custom CSS for Beautiful UI
+# Custom CSS
 # ================================================================
 
 css = """
@@ -108,34 +113,35 @@ h1 {
     padding: 20px;
     border-radius: 15px;
     box-shadow: 0 4px 15px rgba(0,0,0,0.1);
+    border: 1px solid #e0e0e0;
 }
 """
 
 # ================================================================
-# Gradio UI (Corrected for v4)
+# Gradio UI (Fixed)
 # ================================================================
 
-with gr.Blocks() as demo:
-    demo.load_css(css)
+# FIX: Pass 'css' directly to the Blocks constructor
+with gr.Blocks(css=css, theme=gr.themes.Soft()) as demo:
 
     gr.Markdown("<h1 style='text-align:center;'>🌿 BioVigilus — Biodiversity Impact Analyzer</h1>")
-    gr.Markdown("<p style='text-align:center; font-size:18px;'>Analyze species, habitats, and environmental stress factors with real-time data.</p>")
+    gr.Markdown("<p style='text-align:center; font-size:18px; color:#555;'>Analyze species, habitats, and environmental stress factors with real-time data.</p>")
 
     with gr.Row():
         with gr.Column(elem_classes="custom-box"):
             species_name = gr.Textbox(label="Species Name", placeholder="e.g., Panthera tigris")
             habitat = gr.Textbox(label="Habitat Type", placeholder="Forest / Grassland / Wetland")
 
-            water = gr.Slider(0, 100, label="Water Disturbance Level")
-            land = gr.Slider(0, 100, label="Land Disturbance Level")
-            noise = gr.Slider(0, 100, label="Noise Level")
+            water = gr.Slider(0, 100, label="Water Disturbance Level", value=20)
+            land = gr.Slider(0, 100, label="Land Disturbance Level", value=20)
+            noise = gr.Slider(0, 100, label="Noise Level", value=20)
 
-            analyze_btn = gr.Button("Analyze", variant="primary")
+            analyze_btn = gr.Button("Analyze Impact", variant="primary")
 
         with gr.Column(elem_classes="custom-box"):
-            summary_output = gr.Textbox(label="Species Summary", lines=15)
-            map_output = gr.Plot(label="Distribution Map")
-            qr_output = gr.Image(label="QR Code")
+            summary_output = gr.Textbox(label="Species Summary", lines=12, interactive=False)
+            map_output = gr.Plot(label="Global Distribution Map")
+            qr_output = gr.Image(label="Download Report QR", type="pil")
 
     analyze_btn.click(
         process_species_data,
@@ -143,4 +149,5 @@ with gr.Blocks() as demo:
         outputs=[summary_output, map_output, qr_output]
     )
 
-demo.launch()
+if __name__ == "__main__":
+    demo.launch()