Update src/streamlit_app.py

src/streamlit_app.py

@@ -25,25 +25,43 @@ def predict(text, trust_score=0.5):
 
     return label, round(model_prob, 4), round(fused_score, 4), risk_score
 
-# Streamlit UI
-st.set_page_config(page_title="📩 SMS Spam Classifier", layout="centered")
-st.title("📩 Real-Time SMS Spam Classifier")
-st.markdown("Detect whether an SMS is **spam** or **ham**, with model confidence, fused score and risk score.")
+
+# Fusion prediction function (trust_score fixed at 0.5)
+def predict(text):
+    trust_score = 0.5
+    output = pipe(text)[0]
+    model_prob = output['score'] if output['label'] == 'LABEL_1' else 1 - output['score']
+
+    alpha = 0.7
+    fused = alpha * model_prob + (1 - alpha) * (1 - trust_score)
+    risk = int(round(fused * 100))
+    label = "SPAM" if fused >= 0.5 else "NOT SPAM"
+    return label, round(model_prob, 4), round(fused, 4), risk
+
+# UI config
+st.set_page_config(page_title="SMS Spam Detector", layout="centered")
+st.title("📩 Real-Time SMS Spam Detector")
+
+st.markdown("Enter an SMS message to check if it's likely spam. The system will show you:")
+st.markdown("- 📊 **Model Confidence**")
+st.markdown("- 🔁 **Fused Score** (combined model + trust logic)")
+st.markdown("- ⚠️ **Risk Score** out of 100")
 
 # Text input
 sms_text = st.text_area("✉️ Enter SMS Text:", height=150)
 
-# Trust score slider
-trust_score = st.slider("🔐 Trust Score (user reliability)", 0.0, 1.0, 0.5, step=0.01)
-
-# Predict button
+# Predict
 if st.button("🔍 Predict"):
     if sms_text.strip() == "":
-        st.warning("Please enter some text to analyze.")
+        st.warning("Please enter some text.")
     else:
-        label, confidence, fused_score, risk_score = predict(sms_text, trust_score)
+        label, confidence, fused_score, risk_score = predict(sms_text)
+
+        if label == "SPAM":
+            st.markdown(f"### 🟥 Prediction: **`SPAM`**")
+        else:
+            st.markdown(f"### 🟩 Prediction: **`NOT SPAM`**")
 
-        st.markdown(f"### ✅ Prediction: `{label}`")
-        st.metric(label="📊 Model Confidence", value=f"{confidence:.2f}")
-        st.metric(label="🔁 Fused Score", value=f"{fused_score:.2f}")
-        st.metric(label="⚠️ Risk Score", value=f"{risk_score}/100")
+        st.metric("📊 Model Confidence", f"{confidence:.2f}")
+        st.metric("🔁 Fused Score", f"{fused_score:.2f}")
+        st.metric("⚠️ Risk Score", f"{risk_score}/100")