Update app.py

app.py

@@ -1,18 +1,16 @@
 import os
 import gradio as gr
 import numpy as np
-import pandas as pd
-import matplotlib.pyplot as plt
 import plotly.graph_objects as go
 import requests
 import cv2
 from PIL import Image
 import qrcode
 from fpdf import FPDF
-from io import BytesIO
 from sentinelhub import SHConfig
 from groq import Groq
 import google.generativeai as genai
+import tempfile
 
 # -------------------- ENVIRONMENT VARIABLES --------------------
 HF_API_KEY = os.getenv("HF_API_KEY")
@@ -27,14 +25,12 @@ if SENTINEL_CLIENT_ID and SENTINEL_CLIENT_SECRET:
     config.client_id = SENTINEL_CLIENT_ID
     config.client_secret = SENTINEL_CLIENT_SECRET
 
-# -------------------- AI FUNCTIONS (UPDATED MODELS) --------------------
-
+# -------------------- AI FUNCTIONS (UPDATED) --------------------
 def gemini_summary(text):
     """Backup: Google Gemini 1.5 Flash"""
     try:
         if not GEMINI_API_KEY: return None, "Missing Key"
         genai.configure(api_key=GEMINI_API_KEY)
-        # UPDATED MODEL NAME
         model = genai.GenerativeModel('gemini-1.5-flash') 
         response = model.generate_content(text)
         return response.text, None
@@ -47,7 +43,6 @@ def groq_summary(text):
         if not GROQ_API_KEY: return None, "Missing Key"
         client = Groq(api_key=GROQ_API_KEY)
         completion = client.chat.completions.create(
-            # UPDATED MODEL NAME - The old Mixtral one is retired
             model="llama-3.3-70b-versatile",
             messages=[{"role": "user", "content": text}]
         )
@@ -58,12 +53,11 @@ def groq_summary(text):
 def hf_summary(text):
     """Fallback: Hugging Face (Zephyr)"""
     try:
-        # UPDATED URL AND MODEL
         url = "https://api-inference.huggingface.co/models/HuggingFaceH4/zephyr-7b-beta"
         headers = {"Authorization": f"Bearer {HF_API_KEY}"}
         payload = {
-            "inputs": f"<|system|>You are an environmental scientist.</s><|user|>{text}</s><|assistant|>",
-            "parameters": {"max_new_tokens": 500}
+            "inputs": f"<|system|>You are a scientist.</s><|user|>{text}</s><|assistant|>",
+            "parameters": {"max_new_tokens": 800}
         }
         r = requests.post(url, headers=headers, json=payload, timeout=25)
         if r.status_code == 200:
@@ -75,24 +69,21 @@ def hf_summary(text):
 
 def smart_summary(text):
     errors = []
-    
-    # 1. Try Groq (Fastest)
+    # 1. Try Groq
     out, err = groq_summary(text)
     if out: return out
-    errors.append(f"Groq Error: {err}")
-    
-    # 2. Try Gemini (Most Reliable)
+    errors.append(f"Groq: {err}")
+    # 2. Try Gemini
     out, err = gemini_summary(text)
     if out: return out
-    errors.append(f"Gemini Error: {err}")
-    
-    # 3. Try Hugging Face (Backup)
+    errors.append(f"Gemini: {err}")
+    # 3. Try Hugging Face
     if HF_API_KEY:
         out, err = hf_summary(text)
         if out: return out
-        errors.append(f"HF Error: {err}")
+        errors.append(f"HF: {err}")
     
-    return "⚠ ALL AI MODELS FAILED. DEBUG LOG:\n" + "\n".join(errors)
+    return "⚠ SYSTEM FAILURE. DEBUG LOG:\n" + "\n".join(errors)
 
 # -------------------- MATH & LOGIC --------------------
 def calculate_wqi(pH, do, nutrients):
@@ -131,50 +122,63 @@ def create_plots(wqi, hsi, erosion, turbidity):
     fig.update_layout(title="River Health Metrics", yaxis=dict(range=[0,100]), template="plotly_white")
     return fig
 
+# -------------------- PDF ENGINE --------------------
 def generate_pdf(wqi, hsi, erosion, turbidity, summary_text):
     pdf = FPDF()
     pdf.add_page()
-    pdf.set_font("Arial", "B", 20)
-    pdf.set_text_color(30, 144, 255)
-    pdf.cell(0, 15, "FlumenIntel Report", ln=True, align='C')
     
-    pdf.set_font("Arial", "I", 10)
+    # --- 1. QR CODE (TOP RIGHT) ---
+    qr = qrcode.QRCode(box_size=3)
+    qr.add_data("FlumenIntel Report Verified")
+    qr.make(fit=True)
+    img = qr.make_image(fill_color="black", back_color="white")
+    
+    with tempfile.NamedTemporaryFile(delete=False, suffix=".png") as tmp:
+        img.save(tmp.name)
+        # x=160 pushes it to the right margin (A4 width is 210)
+        pdf.image(tmp.name, x=165, y=10, w=30)
+    
+    # --- 2. HEADER ---
+    pdf.set_y(15) # Align with QR code
+    pdf.set_font("Arial", "B", 24)
+    pdf.set_text_color(0, 51, 102) # Dark Blue
+    pdf.cell(0, 10, "FlumenIntel", ln=True, align='L')
+    
+    pdf.set_font("Arial", "I", 12)
     pdf.set_text_color(100, 100, 100)
-    pdf.cell(0, 10, "Developed by Abdullah", ln=True, align='C')
+    pdf.cell(0, 10, "Professional River Health Assessment", ln=True, align='L')
     pdf.ln(10)
     
-    # Metrics
-    pdf.set_font("Arial", "B", 12)
+    # --- 3. METRICS TABLE ---
+    pdf.set_font("Arial", "B", 14)
     pdf.set_text_color(0, 0, 0)
-    pdf.cell(0,10,f"Water Quality Index (WQI): {wqi}", ln=True)
-    pdf.cell(0,10,f"Habitat Suitability (HSI): {hsi}", ln=True)
-    pdf.cell(0,10,f"Erosion Risk: {erosion}", ln=True)
-    pdf.cell(0,10,f"Turbidity Level: {turbidity}", ln=True)
-    pdf.ln(5)
+    pdf.cell(0, 10, "1. Key Environmental Metrics", ln=True)
+    
+    pdf.set_font("Arial", "", 12)
+    pdf.cell(50, 10, f"Water Quality (WQI):", border=1)
+    pdf.cell(50, 10, f"{wqi}/100", border=1, ln=1)
+    
+    pdf.cell(50, 10, f"Habitat Score (HSI):", border=1)
+    pdf.cell(50, 10, f"{hsi}/100", border=1, ln=1)
+    
+    pdf.cell(50, 10, f"Erosion Risk:", border=1)
+    pdf.cell(50, 10, f"{erosion}/100", border=1, ln=1)
     
-    # Summary
+    pdf.cell(50, 10, f"Turbidity:", border=1)
+    pdf.cell(50, 10, f"{turbidity}/100", border=1, ln=1)
+    pdf.ln(10)
+
+    # --- 4. PROFESSIONAL SUMMARY ---
     pdf.set_font("Arial", "B", 14)
-    pdf.cell(0, 10, "Comprehensive Analysis", ln=True)
+    pdf.cell(0, 10, "2. Scientist's Analysis", ln=True)
     pdf.set_font("Arial", "", 11)
     
-    safe_summary = summary_text.encode('latin-1', 'replace').decode('latin-1')
-    pdf.multi_cell(0, 6, safe_summary)
-    
-    # QR Code
-    import tempfile
-    qr = qrcode.QRCode(box_size=3)
-    qr.add_data("FlumenIntel - AI River Analysis")
-    qr.make(fit=True)
-    img = qr.make_image(fill_color="black", back_color="white")
+    # Clean text for PDF (latin-1 encoding issue fix)
+    clean_summary = summary_text.encode('latin-1', 'replace').decode('latin-1')
+    pdf.multi_cell(0, 6, clean_summary)
     
-    with tempfile.NamedTemporaryFile(delete=False, suffix=".png") as tmp:
-        img.save(tmp.name)
-        pdf.image(tmp.name, x=170, y=10, w=25)
-        
-    try:
-        return pdf.output(dest='S').encode('latin-1')
-    except:
-        return pdf.output(dest='S')
+    # Output
+    return pdf.output(dest='S').encode('latin-1')
 
 # -------------------- MAIN PROCESSOR --------------------
 def process_data(flow_rate, water_temp, sediment, construction, pH, do, nutrients, sat_img):
@@ -186,18 +190,24 @@ def process_data(flow_rate, water_temp, sediment, construction, pH, do, nutrient
         stability = river_stability(wqi, hsi, erosion)
         potability = potability_status(wqi)
         
+        # --- PROFESSIONAL PROMPT ---
         prompt = f"""
-        Act as an Environmental Scientist. Analyze this river data:
-        - Water Quality (WQI): {wqi}/100 ({potability})
-        - Biodiversity Habitat (HSI): {hsi}/100
-        - Erosion Risk: {erosion}/100
-        - Turbidity: {turbidity}/100
+        ROLE: Senior Environmental Scientist.
+        TASK: Write a formal "River Health Assessment Report".
+        DATA:
+        - WQI: {wqi} (Potability: {potability})
+        - HSI: {hsi}
+        - Erosion: {erosion}
+        - Turbidity: {turbidity}
         
-        Write a report (150+ words) with these sections:
-        1. **Executive Summary**
-        2. **Biodiversity Impact**
-        3. **Causes & Mitigation**
-        4. **Future Prediction**
+        REQUIREMENTS:
+        - Tone: Professional, Objective, Scientific.
+        - No Markdown symbols (like ** or ##). Use plain text formatting.
+        - Structure:
+          1. EXECUTIVE SUMMARY: High-level status.
+          2. BIOLOGICAL IMPACT: Effect on local aquatic life.
+          3. MITIGATION PLAN: 3 specific, actionable steps.
+          4. FORECAST: Predicted outcome if untreated.
         """
         
         summary = smart_summary(prompt)
@@ -205,58 +215,34 @@ def process_data(flow_rate, water_temp, sediment, construction, pH, do, nutrient
         fig = create_plots(wqi, hsi, erosion, turbidity)
         pdf_bytes = generate_pdf(wqi, hsi, erosion, turbidity, summary)
         
-        import tempfile
         with tempfile.NamedTemporaryFile(delete=False, suffix=".pdf") as tmp_pdf:
             tmp_pdf.write(pdf_bytes)
             pdf_path = tmp_pdf.name
             
-        status_text = f"Overall Stability: {stability}/100\nPotability: {potability}"
+        status_text = f"Stability Index: {stability}/100\nStatus: {potability}"
         
         return status_text, fig, summary, pdf_path
         
     except Exception as e:
-        return str(e), None, f"System Error: {str(e)}", None
+        return str(e), None, f"Error: {str(e)}", None
 
 # -------------------- UI DESIGN --------------------
 custom_css = """
 @import url('https://fonts.googleapis.com/css2?family=Poppins:wght@400;600&display=swap');
-
 #title-box {
     text-align: center;
-    background: linear-gradient(135deg, #0061ff 0%, #60efff 100%);
+    background: linear-gradient(135deg, #0f2027, #203a43, #2c5364); /* Professional Dark Blue */
     padding: 25px;
-    border-radius: 12px;
-    box-shadow: 0 4px 15px rgba(0,0,0,0.1);
-    color: white;
-    margin-bottom: 20px;
-}
-#main-title {
-    font-family: 'Poppins', sans-serif;
-    font-size: 2.5rem;
-    font-weight: 600;
-    margin: 0;
-    color: white;
-}
-#sub-title {
-    font-family: 'Poppins', sans-serif;
-    font-size: 1.1rem;
-    font-weight: 400;
-    opacity: 0.9;
-    margin-top: 5px;
+    border-radius: 8px;
     color: white;
 }
 """
 
-with gr.Blocks(title="FlumenIntel") as demo:
+with gr.Blocks(title="FlumenIntel", css=custom_css) as demo:
     gr.Markdown(f"<style>{custom_css}</style>")
 
     with gr.Column(elem_id="title-box"):
-        gr.Markdown(
-            """
-            <h1 id="main-title">FlumenIntel 🌊</h1>
-            <div id="sub-title">AI River Health Analyzer | Developed by Abdullah</div>
-            """
-        )
+        gr.Markdown("<h1>FlumenIntel 🌊</h1><h3>Advanced River Health Analytics</h3>")
 
     with gr.Row():
         with gr.Column(scale=1):
@@ -277,21 +263,27 @@ with gr.Blocks(title="FlumenIntel") as demo:
                 gr.Markdown("### 3. Visual Analysis")
                 sat_img = gr.Image(label="Satellite Image", sources=["upload", "clipboard"], type="pil")
             
-            analyze_btn = gr.Button("🚀 Run Analysis", variant="primary", size="lg")
+            analyze_btn = gr.Button("GENERATE REPORT", variant="primary", size="lg")
 
         with gr.Column(scale=2):
-            status_box = gr.Textbox(label="Quick Status", interactive=False)
+            status_box = gr.Textbox(label="System Status", interactive=False)
             
             with gr.Tabs():
                 with gr.TabItem("📊 Visual Analytics"):
-                    plot_output = gr.Plot(label="Health Metrics")
+                    plot_output = gr.Plot(label="Metric Visualization")
                 
-                with gr.TabItem("🤖 AI Comprehensive Report"):
-                    ai_summary = gr.Textbox(label="Analysis", lines=12, interactive=False)
+                with gr.TabItem("📄 Official Report"):
+                    # lines=25 creates a large box. Gradio ADDS A SCROLLBAR automatically if text overflows.
+                    ai_summary = gr.Textbox(
+                        label="Scientist's Assessment", 
+                        lines=25, 
+                        show_copy_button=True,
+                        interactive=False
+                    )
                 
-                with gr.TabItem("📄 Download Report"):
-                    gr.Markdown("### Export Data")
-                    pdf_output = gr.File(label="Download Official PDF Report")
+                with gr.TabItem("📥 Export"):
+                    gr.Markdown("### Download Verified PDF")
+                    pdf_output = gr.File(label="FlumenIntel Report.pdf")
 
     analyze_btn.click(
         process_data,