Update app.py

app.py

@@ -12,167 +12,297 @@ from groq import Groq
 import google.generativeai as genai
 import tempfile
 
-# ================= ENV VARS =================
+# -------------------- ENVIRONMENT VARIABLES --------------------
 HF_API_KEY = os.getenv("HF_API_KEY")
 GROQ_API_KEY = os.getenv("GROQ_API_KEY")
 GEMINI_API_KEY = os.getenv("GEMINI_API_KEY")
+SENTINEL_CLIENT_ID = os.getenv("SENTINEL_CLIENT_ID")
+SENTINEL_CLIENT_SECRET = os.getenv("SENTINEL_CLIENT_SECRET")
 ELEVENLABS_API_KEY = os.getenv("ELEVENLABS_API_KEY")
 
-# ================= AI =================
+# -------------------- SENTINEL CONFIG --------------------
+config = SHConfig()
+if SENTINEL_CLIENT_ID and SENTINEL_CLIENT_SECRET:
+    config.client_id = SENTINEL_CLIENT_ID
+    config.client_secret = SENTINEL_CLIENT_SECRET
+
+# -------------------- AI FUNCTIONS --------------------
 def gemini_summary(text):
-    if not GEMINI_API_KEY:
-        return None
-    genai.configure(api_key=GEMINI_API_KEY)
-    model = genai.GenerativeModel("gemini-1.5-flash")
-    return model.generate_content(text).text
+    try:
+        if not GEMINI_API_KEY: return None, "Missing Key"
+        genai.configure(api_key=GEMINI_API_KEY)
+        model = genai.GenerativeModel('gemini-1.5-flash') 
+        response = model.generate_content(text)
+        return response.text, None
+    except Exception as e:
+        return None, str(e)
 
 def groq_summary(text):
-    if not GROQ_API_KEY:
-        return None
-    client = Groq(api_key=GROQ_API_KEY)
-    res = client.chat.completions.create(
-        model="llama-3.3-70b-versatile",
-        messages=[{"role": "user", "content": text}]
-    )
-    return res.choices[0].message.content
+    try:
+        if not GROQ_API_KEY: return None, "Missing Key"
+        client = Groq(api_key=GROQ_API_KEY)
+        completion = client.chat.completions.create(
+            model="llama-3.3-70b-versatile",
+            messages=[{"role": "user", "content": text}]
+        )
+        return completion.choices[0].message.content, None
+    except Exception as e:
+        return None, str(e)
 
 def hf_summary(text):
-    if not HF_API_KEY:
-        return None
-    url = "https://api-inference.huggingface.co/models/HuggingFaceH4/zephyr-7b-beta"
-    headers = {"Authorization": f"Bearer {HF_API_KEY}"}
-    payload = {"inputs": text, "parameters": {"max_new_tokens": 500}}
-    r = requests.post(url, headers=headers, json=payload, timeout=20)
-    return r.json()[0]["generated_text"]
+    try:
+        url = "https://api-inference.huggingface.co/models/HuggingFaceH4/zephyr-7b-beta"
+        headers = {"Authorization": f"Bearer {HF_API_KEY}"}
+        payload = {
+            "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:
+            return r.json()[0]["generated_text"].split("<|assistant|>")[-1], None
+        else:
+            return None, f"Status {r.status_code}: {r.text}"
+    except Exception as e:
+        return None, str(e)
 
 def smart_summary(text):
-    for fn in [groq_summary, gemini_summary, hf_summary]:
-        try:
-            out = fn(text)
-            if out:
-                return out
-        except:
-            pass
-    return "❌ All AI providers failed."
-
-# ================= ELEVENLABS (FIXED) =================
-def generate_audio_report(text):
-    from elevenlabs.client import ElevenLabs
+    errors = []
+    out, err = groq_summary(text)
+    if out: return out
+    errors.append(f"Groq: {err}")
+    out, err = gemini_summary(text)
+    if out: return out
+    errors.append(f"Gemini: {err}")
+    if HF_API_KEY:
+        out, err = hf_summary(text)
+        if out: return out
+        errors.append(f"HF: {err}")
+    return "⚠ SYSTEM FAILURE. DEBUG LOG:\n" + "\n".join(errors)
 
-    if not ELEVENLABS_API_KEY:
-        raise gr.Error("❌ ELEVENLABS_API_KEY missing")
+# -------------------- AUDIO FUNCTION (UPDATED FOR V1.0) --------------------
+def generate_audio_report(text):
+    # 1. Check Library
+    try:
+        from elevenlabs.client import ElevenLabs
+    except ImportError:
+        raise gr.Error("❌ Library Missing! Add 'elevenlabs' to requirements.txt")
 
+    # 2. Check Text
     if not text:
-        raise gr.Error("❌ No report text")
+        raise gr.Error("❌ No text to read!")
 
-    try:
-        client = ElevenLabs(api_key=ELEVENLABS_API_KEY)
+    # 3. Check Key
+    api_key = os.getenv("ELEVENLABS_API_KEY")
+    if not api_key:
+        raise gr.Error("❌ API Key Missing! Check Settings > Secrets.")
 
-        audio = client.text_to_speech.convert(
-            text=text[:400],
-            voice_id="21m00Tcm4TlvDq8ikWAM",  # Rachel (safe default)
+    # 4. Generate with NEW Syntax
+    try:
+        client = ElevenLabs(api_key=api_key)
+        
+        # Use 'text_to_speech.convert' instead of 'generate'
+        # Voice ID for "Brian": nPczCjzI2devNBz1zQrb
+        audio_stream = client.text_to_speech.convert(
+            text=text[:400], 
+            voice_id="nPczCjzI2devNBz1zQrb", 
             model_id="eleven_multilingual_v2"
         )
-
+        
         with tempfile.NamedTemporaryFile(delete=False, suffix=".mp3") as f:
-            for chunk in audio:
+            for chunk in audio_stream:
                 f.write(chunk)
             return f.name
 
-    except Exception:
-        raise gr.Error("❌ ElevenLabs 401 Unauthorized → check key / plan")
+    except Exception as e:
+        error_msg = str(e)
+        if "401" in error_msg:
+             raise gr.Error("❌ 401 Unauthorized: API Key is wrong.")
+        elif "quota" in error_msg.lower():
+             raise gr.Error("❌ Quota Exceeded: No credits left.")
+        else:
+             raise gr.Error(f"❌ ElevenLabs Error: {error_msg}")
 
-# ================= CALCULATIONS =================
+# -------------------- MATH & LOGIC --------------------
 def calculate_wqi(pH, do, nutrients):
-    return max(0, min(100, int(((7 - abs(7 - pH))*0.2 + (do/14)*0.5 + (10-nutrients)*0.3)*10)))
+    wqi = (7 - abs(7 - pH)) * 0.2 + (do/14) * 0.5 + (10 - nutrients) * 0.3
+    wqi_score = max(0, min(100, int(wqi*10)))
+    return wqi_score
 
-def calculate_hsi(flow, temp, sediment):
-    return max(0, min(100, int(100 - abs(flow-50)*0.5 - abs(temp-20)*2 - sediment*1.5)))
+def calculate_hsi(flow_rate, temp, sediment):
+    hsi = 100 - abs(flow_rate-50)*0.5 - abs(temp-20)*2 - sediment*1.5
+    return max(0, min(100, int(hsi)))
 
 def calculate_erosion(sediment, construction):
-    return max(0, min(100, int(sediment*1.5 + construction*2)))
+    score = sediment*1.5 + construction*2
+    return max(0, min(100, int(score)))
+
+def potability_status(wqi):
+    if wqi > 80: return "Safe"
+    elif wqi > 50: return "Boil Required"
+    else: return "Toxic"
+
+def river_stability(wqi, hsi, erosion):
+    return int((wqi*0.4 + hsi*0.4 + (100-erosion)*0.2))
 
 def analyze_satellite_image(img):
-    if img is None:
-        return 0
-    gray = np.array(img.convert("L"))
-    return int(np.mean(gray)/2.55)
+    if img is None: return 0
+    img_array = np.array(img.convert("L"))
+    turbidity_score = int(np.mean(img_array)/2.55)
+    return turbidity_score
 
-# ================= VISUAL =================
-def create_plot(wqi, hsi, erosion, turbidity):
+# -------------------- VISUALS & INSIGHTS --------------------
+def create_plots(wqi, hsi, erosion, turbidity):
     fig = go.Figure()
-    fig.add_bar(
-        x=["WQI", "HSI", "Erosion", "Turbidity"],
-        y=[wqi, hsi, erosion, turbidity]
-    )
-    fig.update_layout(yaxis=dict(range=[0,100]), title="River Health Metrics")
+    colors = ['#0061ff', '#60efff', '#ff4b4b', '#ffb347']
+    fig.add_trace(go.Bar(name="Metrics", x=["WQI", "HSI", "Erosion", "Turbidity"],
+                          y=[wqi, hsi, erosion, turbidity], marker_color=colors))
+    fig.update_layout(title="River Health Metrics", yaxis=dict(range=[0,100]), template="plotly_white")
     return fig
 
-# ================= PDF =================
-def generate_pdf(summary):
+def generate_graph_insights(wqi, hsi, erosion, turbidity):
+    text = "### 📉 Graph Analysis\n\n"
+    if wqi > 70: text += f"🔵 **Water Quality:** {wqi}/100. Excellent condition.\n\n"
+    elif wqi > 40: text += f"🔵 **Water Quality:** {wqi}/100. Moderate pollution.\n\n"
+    else: text += f"🔵 **Water Quality:** {wqi}/100. **CRITICAL**.\n\n"
+    
+    if hsi > 70: text += f"🟢 **Habitat:** {hsi}/100. Good biodiversity.\n\n"
+    else: text += f"🟢 **Habitat:** {hsi}/100. Poor conditions.\n\n"
+    return text
+
+# -------------------- PDF ENGINE --------------------
+def generate_pdf(wqi, hsi, erosion, turbidity, summary_text):
     pdf = FPDF()
     pdf.add_page()
-    pdf.set_font("Arial", size=12)
-    pdf.multi_cell(0, 8, summary.encode("latin-1", "replace").decode("latin-1"))
-    return pdf.output(dest="S").encode("latin-1")
+    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)
+        pdf.image(tmp.name, x=165, y=10, w=30)
+    pdf.set_y(15)
+    pdf.set_font("Arial", "B", 24)
+    pdf.set_text_color(0, 97, 255)
+    pdf.cell(0, 10, "FlumenIntel", ln=True, align='L')
+    pdf.ln(10)
+    pdf.set_font("Arial", "", 12)
+    pdf.set_text_color(0, 0, 0)
+    pdf.multi_cell(0, 6, summary_text.encode('latin-1', 'replace').decode('latin-1'))
+    try:
+        return pdf.output(dest='S').encode('latin-1')
+    except:
+        return pdf.output(dest='S')
 
-# ================= PIPELINE =================
-def run(flow, temp, sediment, construction, ph, do, nutrients, img):
-    wqi = calculate_wqi(ph, do, nutrients)
-    hsi = calculate_hsi(flow, temp, sediment)
-    erosion = calculate_erosion(sediment, construction)
-    turbidity = analyze_satellite_image(img)
+# -------------------- MAIN PROCESSOR --------------------
+def process_data(flow_rate, water_temp, sediment, construction, pH, do, nutrients, sat_img):
+    try:
+        wqi = calculate_wqi(pH, do, nutrients)
+        hsi = calculate_hsi(flow_rate, water_temp, sediment)
+        erosion = calculate_erosion(sediment, construction)
+        turbidity = analyze_satellite_image(sat_img)
+        stability = river_stability(wqi, hsi, erosion)
+        potability = potability_status(wqi)
+        
+        prompt = f"""
+        ROLE: Senior Environmental Scientist.
+        TASK: Write a formal River Health Report.
+        DATA: WQI: {wqi}, HSI: {hsi}, Erosion: {erosion}, Turbidity: {turbidity}.
+        REQUIREMENTS: Professional tone. 3 paragraphs max.
+        """
+        
+        summary = smart_summary(prompt)
+        fig = create_plots(wqi, hsi, erosion, turbidity)
+        graph_text = generate_graph_insights(wqi, hsi, erosion, turbidity)
+        pdf_bytes = generate_pdf(wqi, hsi, erosion, turbidity, summary)
+        
+        with tempfile.NamedTemporaryFile(delete=False, suffix=".pdf") as tmp_pdf:
+            tmp_pdf.write(pdf_bytes)
+            pdf_path = tmp_pdf.name
+            
+        status_text = f"Stability Index: {stability}/100\nStatus: {potability}"
+        
+        return status_text, fig, graph_text, summary, pdf_path
 
-    prompt = f"""
-    You are a senior environmental scientist.
-    Write a professional river health report.
+    except Exception as e:
+        return str(e), None, "", "", None
 
-    WQI: {wqi}
-    HSI: {hsi}
-    Erosion: {erosion}
-    Turbidity: {turbidity}
-    """
+# Wrapper
+def run_app(flow, temp, sediment, construction, ph, do, nutrients, sat_img):
+    return process_data(flow, temp, sediment, construction, ph, do, nutrients, sat_img)
 
-    summary = smart_summary(prompt)
-    fig = create_plot(wqi, hsi, erosion, turbidity)
-    pdf_bytes = generate_pdf(summary)
+# -------------------- UI DESIGN --------------------
+custom_css = """
+@import url('https://fonts.googleapis.com/css2?family=Poppins:wght@300;400;600&display=swap');
+* { font-family: 'Poppins', sans-serif !important; }
+#title-box { background: linear-gradient(135deg, #0061ff 0%, #60efff 100%); color: white; padding: 20px; border-radius: 12px; text-align: center;}
+#analyze-btn { background: linear-gradient(90deg, #0061ff 0%, #60efff 100%); color: white; border: none; }
+"""
 
-    with tempfile.NamedTemporaryFile(delete=False, suffix=".pdf") as f:
-        f.write(pdf_bytes)
-        pdf_path = f.name
+with gr.Blocks(title="FlumenIntel") as demo:
+    gr.HTML(f"<style>{custom_css}</style>")
+    
+    with gr.Column(elem_id="title-box"):
+        gr.Markdown("# FlumenIntel 🌊\n### Advanced River Health Analytics")
 
-    status = f"Stability Index: {(wqi+hsi+(100-erosion))//3}/100"
+    with gr.Tabs():
+        # --- TAB 1: DASHBOARD ---
+        with gr.TabItem("🚀 Dashboard"):
+            with gr.Row():
+                # LEFT INPUTS
+                with gr.Column(scale=1):
+                    gr.Markdown("### 1. Hydrological Data")
+                    flow = gr.Number(label="Flow Rate", value=45)
+                    temp = gr.Number(label="Temperature", value=18)
+                    sediment = gr.Slider(0, 10, label="Sediment", value=2)
+                    construction = gr.Slider(0, 10, label="Construction", value=0)
+                    
+                    gr.Markdown("### 2. Chemical Data")
+                    ph = gr.Number(label="pH Level", value=7.2)
+                    do = gr.Number(label="Dissolved Oxygen", value=9.5)
+                    nutrients = gr.Slider(0, 10, label="Nutrient Load", value=1)
+                    
+                    gr.Markdown("### 3. Visual Analysis")
+                    sat_img = gr.Image(label="Satellite Image", type="pil")
+                    
+                    analyze_btn = gr.Button("GENERATE REPORT", elem_id="analyze-btn")
 
-    return status, fig, summary, pdf_path
+                # RIGHT OUTPUTS
+                with gr.Column(scale=2):
+                    status_box = gr.Textbox(label="System Status", interactive=False)
+                    
+                    with gr.Tabs():
+                        with gr.TabItem("📊 Visual Analytics"):
+                            plot_output = gr.Plot(label="Metric Visualization")
+                            graph_summary_box = gr.Markdown("### Insights...")
+                        
+                        with gr.TabItem("📄 Official Report"):
+                            ai_summary = gr.Textbox(label="Scientist's Assessment", lines=15, interactive=False)
+                            
+                            # --- AUDIO BUTTON ---
+                            with gr.Row():
+                                audio_btn = gr.Button("🔊 Listen to Report (ElevenLabs)")
+                                audio_out = gr.Audio(label="Player", type="filepath")
+                            
+                            audio_btn.click(
+                                fn=generate_audio_report, 
+                                inputs=ai_summary, 
+                                outputs=audio_out
+                            )
 
-# ================= UI =================
-with gr.Blocks(title="FlumenIntel") as demo:
-    gr.Markdown("# 🌊 FlumenIntel — River Intelligence")
-
-    with gr.Row():
-        with gr.Column():
-            flow = gr.Number(value=45, label="Flow Rate")
-            temp = gr.Number(value=18, label="Temperature")
-            sediment = gr.Slider(0,10,value=2,label="Sediment")
-            construction = gr.Slider(0,10,value=0,label="Construction")
-            ph = gr.Number(value=7.2,label="pH")
-            do = gr.Number(value=9.5,label="Dissolved Oxygen")
-            nutrients = gr.Slider(0,10,value=1,label="Nutrients")
-            img = gr.Image(type="pil")
-            btn = gr.Button("GENERATE REPORT")
-
-        with gr.Column():
-            status = gr.Textbox(label="Status")
-            plot = gr.Plot()
-            report = gr.Textbox(lines=12,label="AI Report")
-            audio_btn = gr.Button("🔊 Listen")
-            audio = gr.Audio(type="filepath")
-            pdf = gr.File()
-
-    btn.click(run, [flow,temp,sediment,construction,ph,do,nutrients,img],
-              [status,plot,report,pdf])
-
-    audio_btn.click(generate_audio_report, report, audio)
+                        with gr.TabItem("📥 Export"):
+                            pdf_output = gr.File(label="FlumenIntel Report.pdf")
+
+        # --- TAB 2: ABOUT ME ---
+        with gr.TabItem("👤 About Me"):
+             gr.Markdown("## Abdullah\nComputer Engineering Undergraduate | AI & Hardware Enthusiast")
+
+    # Events
+    analyze_btn.click(
+        run_app,
+        inputs=[flow, temp, sediment, construction, ph, do, nutrients, sat_img],
+        outputs=[status_box, plot_output, graph_summary_box, ai_summary, pdf_output]
+    )
 
 if __name__ == "__main__":
     demo.launch()
+when i click the eleven report i got the 401 error