Update app.py

app.py

@@ -1,33 +1,40 @@
 import os
 import gradio as gr
 
-# Optional CPU hygiene
+# --------- CPU hygiene (nice-to-have) ----------
 os.environ["TOKENIZERS_PARALLELISM"] = "false"
 try:
     import torch
     try:
-        torch.set_num_threads(2)  # nice on 2 vCPUs
+        torch.set_num_threads(2)  # smoother on 2 vCPUs
     except Exception:
         pass
 except Exception:
     pass
 
 from transformers import pipeline
+from vaderSentiment.vaderSentiment import SentimentIntensityAnalyzer
 
-# -------- Model config --------
+# -------- Model / bot configuration --------
 GEN_MODEL_NAME = "MBZUAI/LaMini-Flan-T5-248M"  # CPU-friendly text2text model
 
-# ---- Instructions to the LLM  ----
 DOMAIN_INSTRUCTIONS = (
     "You are a concise assistant about cats in ancient Egypt. "
     "Keep focus on Bastet, cat mummies, daily life, worship, and other ancient Egypt facts. "
     "If the user asks something unrelated, say briefly that you only cover those topics and suggest one."
 )
 
+HELP_TEXT = (
+    "Ask me about: Bastet • cat mummies • daily life • worship\n"
+    "Type anything else to try the AI fallback."
+)
 
-# Lazy-loaded generator
+# -------- Lazy singletons --------
 _t2t = None
+_vader = None
+
 def get_t2t():
+    """Lazy-load the text2text pipeline (LaMini-Flan-T5)."""
     global _t2t
     if _t2t is None:
         _t2t = pipeline(
@@ -38,6 +45,38 @@ def get_t2t():
         print(f"[startup] Loaded model: {GEN_MODEL_NAME}")
     return _t2t
 
+def get_vader():
+    """Lazy-load the VADER sentiment analyzer."""
+    global _vader
+    if _vader is None:
+        _vader = SentimentIntensityAnalyzer()
+        print("[startup] Loaded VADER sentiment analyzer")
+    return _vader
+
+# -------- Helpers --------
+def detect_sentiment_bucket(text: str):
+    """
+    Return ('neg'|'neu'|'pos', compound_score).
+    Thresholds chosen for clear buckets in chat settings.
+    """
+    scores = get_vader().polarity_scores(text or "")
+    c = scores.get("compound", 0.0)
+    if c <= -0.4:
+        return "neg", c
+    if c >= 0.4:
+        return "pos", c
+    return "neu", c
+
+def apply_tone_prefix(reply_text: str, bucket: str) -> str:
+    """Prepend a tiny tone wrapper without changing factual content."""
+    if bucket == "pos":
+        prefix = "Great question! "
+    elif bucket == "neg":
+        prefix = "Calm down. You're being a little too negative! "
+    else:
+        prefix = ""
+    return (prefix + (reply_text or "")).strip()
+
 # ---- Use the LLM if the generator doesn't understand user prompt ----
 def ai_fallback(prompt: str) -> str:
     try:
@@ -57,21 +96,30 @@ def ai_fallback(prompt: str) -> str:
         print("AI fallback error:", repr(e))
         return "AI fallback had an issue. Please try a simpler question or use the topics in 'help'."
 
-
+# -------- Chat logic --------
 def reply(message, history):
+    # 1) sentiment first (on the raw user text)
+    bucket, _score = detect_sentiment_bucket(message or "")
+
+    # 2) rules-first responses
     msg = (message or "").strip().lower()
     if msg in {"hi", "hello", "hey"} or "help" in msg:
-        return "Hi! I share facts about cats in ancient Egypt.\n\n" + HELP_TEXT
-    if "bastet" in msg or "bast" in msg:
-        return "Bastet (later cat-headed) … major cult center at Bubastis in the Nile Delta."
-    if any(w in msg for w in ["mummy", "mummies", "mummified", "offering"]):
-        return "Millions of animal mummies (cats common), esp. Late Period (664–332 BCE)."
-    if any(w in msg for w in ["daily", "life", "pest", "mouse", "rat", "snake"]):
-        return "Cats protected grain stores; art shows them under chairs/on leashes with owners."
-    if any(w in msg for w in ["worship", "god", "goddess", "taboo"]):
-        return "People didn’t worship pet cats as gods; they revered cats via Bastet and votive offerings."
-    return ai_fallback(message)
+        base = "Hi! I share facts about cats in ancient Egypt.\n\n" + HELP_TEXT
+    elif "bastet" in msg or "bast" in msg:
+        base = "Bastet (later cat-headed) … major cult center at Bubastis in the Nile Delta."
+    elif any(w in msg for w in ["mummy", "mummies", "mummified", "offering"]):
+        base = "Millions of animal mummies (cats common), esp. Late Period (664–332 BCE)."
+    elif any(w in msg for w in ["daily", "life", "pest", "mouse", "rat", "snake"]):
+        base = "Cats protected grain stores; art shows them under chairs/on leashes with owners."
+    elif any(w in msg for w in ["worship", "god", "goddess", "taboo"]):
+        base = "People didn’t worship pet cats as gods; they revered cats via Bastet and votive offerings."
+    else:
+        base = ai_fallback(message)
+
+    # 3) tone wrapper (content unchanged)
+    return apply_tone_prefix(base, bucket)
 
+# -------- UI --------
 demo = gr.ChatInterface(
     fn=reply,
     title="Cats of Ancient Egypt Chatbot"