Update app.py

app.py

@@ -3,18 +3,17 @@ import requests
 import pandas as pd
 import plotly.express as px
 import qrcode
+from io import BytesIO
 
 # ================================================================
-# Helper Function: Species Summary + Map + QR Code
+# Helper Function
 # ================================================================
 
 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
 
-    # ======================
-    # 1. Fetch Wikipedia Summary
-    # ======================
+    # 1. Fetch Wikipedia
     wiki_url = "https://en.wikipedia.org/w/api.php"
     params = {
         "action": "query",
@@ -28,128 +27,90 @@ def process_species_data(species_name, habitat, water_disturbance, land_disturba
         response = requests.get(wiki_url, params=params).json()
         pages = response.get("query", {}).get("pages", {})
         if "-1" in pages:
-            extract = "Species not found in Wikipedia database."
+            extract = "Species not found."
         else:
             page = next(iter(pages.values()))
-            extract = page.get("extract", "No summary available for this species.")
-    except Exception:
-        extract = "Error fetching data from Wikipedia."
+            extract = page.get("extract", "No summary available.")
+    except:
+        extract = "Error fetching data."
 
-    # Word count check and padding
     words = extract.split()
     if len(words) < 200:
-        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
-
+        extract += "\n\n" + ("Conservation of this species is critical for biodiversity. " * 5)
+    
     summary = " ".join(words[:350])
-
-    # Add environmental interpretation
+    
     summary += f"""
 
-Environmental Impact Assessment (Based on User Inputs):
-- Water Disturbance Level: {water_disturbance}/100
-- Land Disturbance Level: {land_disturbance}/100
+Environmental Impact Assessment:
+- Water Disturbance: {water_disturbance}/100
+- Land Disturbance: {land_disturbance}/100
 - Noise Level: {noise_level}/100
-- Habitat Type: {habitat}
-
-Higher disturbance values indicate increased pressure on this species' survival and reproduction.
+- Habitat: {habitat}
 """
 
-    # ======================
-    # 2. Fetch GBIF Occurrence Data (Map API)
-    # ======================
+    # 2. Fetch GBIF Map
     gbif_url = f"https://api.gbif.org/v1/occurrence/search?scientificName={species_name}&limit=200"
-    
     coords = []
     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 
+        for r in gbif_res.get("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=400)
         fig.update_layout(mapbox_style="open-street-map", margin={"r":0,"t":0,"l":0,"b":0})
     else:
-        # Empty map fallback
         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[:100]}..."
-    qr_img = qrcode.make(qr_data)
+    # 3. QR Code
+    qr = qrcode.make(f"BioVigilus: {species_name}")
     
-    return summary, fig, qr_img
+    return summary, fig, qr
 
 # ================================================================
-# Custom CSS
+# CSS Styling (HTML Injection)
 # ================================================================
-
-css_style = """
+css_code = """
 <style>
-body { background-color: #f2f7f4 !important; }
+body { background-color: #f2f7f4; }
 .gradio-container { font-family: 'Poppins', sans-serif; }
-
-h1 {
-    color: #2e7d32 !important;
-    font-weight: 700;
-}
-
-.custom-box {
-    background: white;
-    padding: 20px;
-    border-radius: 15px;
-    box-shadow: 0 4px 15px rgba(0,0,0,0.1);
-    border: 1px solid #e0e0e0;
-}
+h1 { color: #2e7d32; text-align: center; }
+.custom-box { border: 1px solid #ddd; padding: 20px; border-radius: 10px; background: white; }
 </style>
 """
 
 # ================================================================
-# Gradio UI (Universal Fix)
+# UI Layout (Strict Compatibility Mode)
 # ================================================================
 
-# We remove the 'css' argument here to avoid the TypeError
-with gr.Blocks(theme=gr.themes.Soft()) as demo:
+# NOTE: Removed 'theme' and 'css' arguments to prevent errors on old versions
+with gr.Blocks() as demo:
+    gr.HTML(css_code) # Inject CSS here instead
     
-    # INJECTION: We add the CSS here using HTML
-    gr.HTML(css_style)
-
-    gr.Markdown("<h1 style='text-align:center;'>🌿 BioVigilus — Biodiversity Impact Analyzer</h1>")
-    gr.Markdown("<p style='text-align:center; font-size:18px; color:#555;'>Analyze species, habitats, and environmental stress factors with real-time data.</p>")
+    gr.Markdown("# 🌿 BioVigilus — Biodiversity Impact Analyzer")
+    gr.Markdown("Analyze species, habitats, and environmental stress factors.")
 
     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", 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 Impact", variant="primary")
+            species_name = gr.Textbox(label="Species Name", placeholder="e.g. Panthera tigris")
+            habitat = gr.Textbox(label="Habitat Type", placeholder="Forest")
+            water = gr.Slider(0, 100, label="Water Disturbance")
+            land = gr.Slider(0, 100, label="Land Disturbance")
+            noise = gr.Slider(0, 100, label="Noise Level")
+            btn = gr.Button("Analyze", variant="primary")
 
         with gr.Column(elem_classes="custom-box"):
-            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,
-        inputs=[species_name, habitat, water, land, noise],
-        outputs=[summary_output, map_output, qr_output]
-    )
+            out_summary = gr.Textbox(label="Summary", lines=10)
+            out_map = gr.Plot(label="Map")
+            out_qr = gr.Image(label="QR Code", type="pil")
+
+    btn.click(process_species_data, [species_name, habitat, water, land, noise], [out_summary, out_map, out_qr])
 
 if __name__ == "__main__":
     demo.launch()