Update app.py

app.py

@@ -18,19 +18,19 @@ def load_model():
 
 tokenizer, model = load_model()
 
-# Honest AI response logic (ultra-concise, factual)
+# Honest AI response logic (3 sentences, ~100+ chars)
 def honest_ai_response(user_input):
     if tokenizer is None or model is None:
-        return "Model’s down."
+        return "Model is down.\nCannot respond now.\nTry again later."
     try:
-        prompt = f"Brief fact: {user_input}"
+        prompt = f"3 short facts: {user_input}"
         inputs = tokenizer.encode(prompt, return_tensors="pt")
         attention_mask = torch.ones(inputs.shape, dtype=torch.long)
         outputs = model.generate(
             inputs,
-            max_length=20,
-            temperature=0.5,
-            top_k=30,
+            max_length=60,
+            temperature=0.6,
+            top_k=40,
             num_return_sequences=1,
             pad_token_id=tokenizer.eos_token_id,
             attention_mask=attention_mask,
@@ -39,32 +39,48 @@ def honest_ai_response(user_input):
         )
         response = tokenizer.decode(outputs[0], skip_special_tokens=True)
         answer = response.replace(prompt, "").strip()
-        return answer[:25].rsplit(" ", 1)[0] + "." if len(answer) > 25 else answer
+        # Ensure 3 sentences, ~33 chars each
+        sentences = [s.strip() for s in answer.split(".") if s.strip()]
+        if len(sentences) >= 3:
+            s1 = sentences[0][:35].rsplit(" ", 1)[0] + "."
+            s2 = sentences[1][:35].rsplit(" ", 1)[0] + "."
+            s3 = sentences[2][:35].rsplit(" ", 1)[0] + "."
+        else:
+            s1 = (answer[:35].rsplit(" ", 1)[0] + ".") if answer else "No data exists."
+            s2 = "This is unclear." if len(sentences) < 2 else sentences[1][:35].rsplit(" ", 1)[0] + "."
+            s3 = "Facts are limited."
+        full_response = f"{s1}\n{s2}\n{s3}"
+        if len(full_response) < 100:
+            s3 += " More study needed."
+        return full_response
     except Exception as e:
-        return "Error."
+        return f"Error occurred.\nCannot process.\nCheck input: {str(e)}"
 
-# Echo Chamber AI response logic (ultra-concise, agreeable)
+# Echo Chamber AI response logic (3 sentences, ~100+ chars, complete input)
 def echo_chamber_ai_response(user_input):
-    agreement_phrases = [
-        "Yes!",
-        "Right!",
-        "True!",
-        "Sure!"
-    ]
-    short_input = user_input[:15] + "..." if len(user_input) > 15 else user_input
-    return f"{random.choice(agreement_phrases)} {short_input}"
+    agreements = ["Yes!", "Right!", "True!", "Sure!"]
+    agree = random.choice(agreements)
+    # Use full input for third sentence, truncate earlier lines if needed
+    s1 = f"{agree} You’re correct."
+    s2 = "I fully support that."
+    s3 = user_input + "." if len(user_input) <= 35 else user_input[:35].rsplit(" ", 1)[0] + "."
+    full_response = f"{s1}\n{s2}\n{s3}"
+    # Pad to 100 chars if needed
+    if len(full_response) < 100:
+        s2 += " Absolutely."
+    return full_response
 
 # Streamlit UI
 def main():
     st.title("Echo Chamber AI vs Honest AI")
     st.markdown("""
     AI bias demo:
-    - **Honest AI**: Brief facts.
-    - **Echo Chamber AI**: Agrees.
+    - **Honest AI**: Factual answers.
+    - **Echo Chamber AI**: Agrees always.
     """)
 
     # User input
-    user_input = st.text_input("Ask:", "Is it real because we can't see it?")
+    user_input = st.text_input("Ask:", "Why does the Earth glow yellow?")
 
     # Side-by-side comparison
     col1, col2 = st.columns(2)
@@ -79,21 +95,21 @@ def main():
                 
                 with col1:
                     st.subheader("Honest AI")
-                    st.write(honest_response)
+                    st.text(honest_response)
                 
                 with col2:
                     st.subheader("Echo Chamber AI")
-                    st.write(echo_response)
+                    st.text(echo_response)
 
-    # Purpose and inspiration (fixed string)
+    # Purpose and inspiration
     with st.expander("About", expanded=True):
         st.markdown("""
         ### How It Works
-        - **Honest AI**: Quick facts via GPT-2.
-        - **Echo Chamber AI**: Echoes you.
+        - **Honest AI**: 3 factual sentences.
+        - **Echo Chamber AI**: 3 agreeable ones.
         
         ### Purpose
-        Shows bias vs. truth in AI.
+        Shows bias vs. truth in AI feedback.
 
         """)