Update src/streamlit_app.py

src/streamlit_app.py

@@ -27,7 +27,7 @@ def predict_sentence_ai_probability(sentence):
     inputs = tokenizer(sentence, return_tensors="tf", truncation=True, padding=True)
     outputs = model(inputs)
     logits = outputs.logits
-    prob_ai = tf.sigmoid(logits)[0][0].numpy()  # for binary classification
+    prob_ai = tf.sigmoid(logits)[0][0].numpy()
     return prob_ai
 
 # 📊 Analyze all sentences
@@ -53,6 +53,12 @@ st.set_page_config(page_title="AI Detector", layout="wide")
 st.title("🧠 AI Content Detector")
 st.markdown("This app detects the percentage of **AI-generated content** based on sentence-level analysis using DistilBERT.")
 
+# Initialize session state to avoid duplicates
+if "last_input" not in st.session_state:
+    st.session_state.last_input = ""
+    st.session_state.results = None
+    st.session_state.percentage = None
+
 # 📋 User Input Area
 user_input = st.text_area("📋 Paste your text below to check for AI-generated sentences:", height=300)
 
@@ -61,15 +67,18 @@ if st.button("🔍 Analyze"):
     if not user_input.strip():
         st.warning("⚠️ Please enter some text to analyze.")
     else:
-        # Run analysis
+        # Store in session_state to avoid duplicates
+        st.session_state.last_input = user_input
         ai_percentage, analysis_results = predict_ai_generated_percentage(user_input)
+        st.session_state.results = analysis_results
+        st.session_state.percentage = ai_percentage
 
-        # 🔍 Sentence-Level Results
-        st.subheader("🔍 Sentence-level Analysis")
-        for i, (sentence, prob, is_ai) in enumerate(analysis_results, start=1):
-            label = "🟢 Human" if not is_ai else "🔴 AI"
-            st.markdown(f"**{i}.** _{sentence}_\n\n → {label}")
+# Display only if results are present
+if st.session_state.results is not None:
+    st.subheader("🔍 Sentence-level Analysis")
+    for i, (sentence, prob, is_ai) in enumerate(st.session_state.results, start=1):
+        label = "🟢 Human" if not is_ai else "🔴 AI"
+        st.markdown(f"**{i}.** _{sentence}_\n\n → {label}")
 
-        # 📊 Final Result
-        st.subheader("📊 Final Result")
-        st.success(f"Estimated **AI-generated content**: **{ai_percentage:.2f}%**")
+    st.subheader("📊 Final Result")
+    st.success(f"Estimated **AI-generated content**: **{st.session_state.percentage:.2f}%**")