Fix hallucinations

app.py

@@ -127,7 +127,7 @@ HOTEL = HotelSim()
 
 HOTEL_INFO = {
     "name": "Bluebird Hotel",
-    "location": "Seaside promenade, 5 minutes from the marina",
+    "location": "Volos, Greece — Pagasetic Gulf waterfront, gateway to Mount Pelion",
     "star_rating": 5,
     "amenities": [
         "Rooftop infinity pool",
@@ -154,6 +154,46 @@ HOTEL_INFO = {
     "check_in_time": "15:00",
     "check_out_time": "11:00",
     "late_checkout_policy": "Subject to availability; fees may apply after 13:00.",
+    # Curated local guide for Volos & nearby Pelion
+    "local_guide": {
+        "dining_tsipouradika": [
+            "MeZen (modern tsipouro meze, city center)",
+            "Ouzeri Ta Kymata (classic seafood meze on the promenade)",
+            "Iolkos Tsipouradiko (casual, fresh small plates, near port)",
+        ],
+        "beaches": [
+            "Anavros Beach (city beach, easy walk from center)",
+            "Kala Nera (Pelion west coast ~25–35 min drive)",
+            "Mylopotamos (Pelion east coast ~1h 15m; iconic rock arch)",
+            "Papa Nero & Agios Ioannis (east Pelion ~1h 10m; organized)"
+        ],
+        "pelion_villages": [
+            "Makrinitsa (balconies of Pelion, views over Volos ~25 min)",
+            "Portaria (traditional square & tavernas ~20 min)",
+            "Tsagarada (stone bridges & chestnut forests ~1h 10m)",
+            "Milies (terminus of Pelion steam train ~50 min)"
+        ],
+        "activities": [
+            "Pelion Train (Ano Lechonia → Milies; weekends seasonal)",
+            "Waterfront promenade sunset stroll (Argonauts Avenue)",
+            "Sea kayaking / sailing in Pagasetic Gulf (calm waters)",
+            "Hiking Centaurs' Path (Portaria ↔ Makrinitsa)"
+        ],
+        "museums_culture": [
+            "Athanasakeion Archaeological Museum of Volos",
+            "Rooftile & Brickworks Museum N. & S. Tsalapatas",
+            "Volos Municipal Gallery — Giorgio de Chirico Art Center",
+        ],
+        "day_trips": [
+            "Ferry to Skiathos (summer schedule from Volos port)",
+            "Meteora monasteries (long day ~2h each way by car)",
+        ],
+        "cafes_bars": [
+            "Isalos (seafront coffee & cocktails)",
+            "Canteen on the waterfront (casual bites)",
+            "Grooove (drinks, music near center)",
+        ],
+    },
 }
 
 OFFERS_SEED = [
@@ -283,6 +323,50 @@ def init_offers_state(session):
     return format_offer_card(first), accepted_summary_md(session["accepted_offers"]), 0, session
 
 
+def context_summary_md(session: dict) -> str:
+    s = session or {}
+    parts = []
+    if s.get("time_of_day"):
+        parts.append(f"Time: {s['time_of_day']}")
+    if s.get("weather"):
+        parts.append(f"Weather: {s['weather']}")
+    nk = s.get("near_km")
+    if isinstance(nk, (int, float)) and nk > 0:
+        parts.append(f"Near me: ~{int(nk)} km")
+    if not parts:
+        return "_No extra context set. Seasonal notes apply automatically._"
+    return "**Context:** " + ", ".join(parts)
+
+
+def set_context_action(time_of_day, weather, near_km, session):
+    s = session or {}
+    if time_of_day:
+        s["time_of_day"] = str(time_of_day)
+    else:
+        s.pop("time_of_day", None)
+    if weather:
+        s["weather"] = str(weather)
+    else:
+        s.pop("weather", None)
+    try:
+        nk = float(near_km) if near_km is not None else None
+    except Exception:
+        nk = None
+    if nk is not None and nk >= 0:
+        s["near_km"] = nk
+    else:
+        s.pop("near_km", None)
+    return s, context_summary_md(s)
+
+
+def clear_context_action(session):
+    s = session or {}
+    s.pop("time_of_day", None)
+    s.pop("weather", None)
+    s.pop("near_km", None)
+    return s, context_summary_md(s), None, None, 0
+
+
 def next_offer_action(index, session):
     offers = get_active_offers()
     if not offers:
@@ -348,8 +432,10 @@ def load_llm():
             model=model,
             tokenizer=tok,
             max_new_tokens=int(os.getenv("LLM_MAX_NEW_TOKENS", 256)),
-            temperature=float(os.getenv("LLM_TEMP", 0.7)),
+            temperature=float(os.getenv("LLM_TEMP", 0.3)),
             top_p=float(os.getenv("LLM_TOP_P", 0.9)),
+            repetition_penalty=float(os.getenv("LLM_REP_PENALTY", 1.1)),
+            no_repeat_ngram_size=int(os.getenv("LLM_NO_REPEAT_NGRAM", 3)),
             do_sample=True,
         )
         if _LANGCHAIN_AVAILABLE:
@@ -363,7 +449,7 @@ def load_llm():
         return None
 
 
-def compose_system_prompt():
+def compose_system_prompt(dynamic_context: str = ""):
     amenities = "\n".join(f"- {a}" for a in HOTEL_INFO["amenities"])
     treatments = "\n".join(f"- {t}" for t in HOTEL_INFO["spa"]["signature_treatments"])
     try:
@@ -371,12 +457,49 @@ def compose_system_prompt():
     except Exception:
         offers_list = []
     offers = "\n".join(f"* {o['title']}: {o['desc']} ({o['price_text']})" for o in offers_list if o.get("active"))
-    return f"""You are the concierge AI for {HOTEL_INFO['name']}. Provide concise, friendly answers.
-Hotel Facts:
-Location: {HOTEL_INFO['location']}
-Star Rating: {HOTEL_INFO['star_rating']}⭐
-Check-in: {HOTEL_INFO['check_in_time']}  |  Check-out: {HOTEL_INFO['check_out_time']}
-Amenities:\n{amenities}\nSpa: {HOTEL_INFO['spa']['name']} (Open {HOTEL_INFO['spa']['open']})\nSignature Treatments:\n{treatments}\nDining Venues: {', '.join(HOTEL_INFO['dining'])}\nLate Checkout: {HOTEL_INFO['late_checkout_policy']}\nCurrent Upsell Offers:\n{offers}\nInstructions:\n- Answer the user's question directly using the facts above.\n- Do NOT include any role prefixes like 'User:' or 'Assistant:'.\n- Do NOT create additional 'User:' turns in your output.\n- Keep responses under 120 words.\nReply with only the answer text."""
+    # Local guide sections (Volos & Pelion)
+    lg = HOTEL_INFO.get("local_guide", {})
+    def _fmt(cat: str) -> str:
+        items = lg.get(cat, [])
+        return "\n".join(f"- {x}" for x in items)
+    sections: List[str] = []
+    if lg.get("dining_tsipouradika"):
+        sections.append("Dining (tsipouradika):\n" + _fmt("dining_tsipouradika"))
+    if lg.get("beaches"):
+        sections.append("Beaches:\n" + _fmt("beaches"))
+    if lg.get("pelion_villages"):
+        sections.append("Pelion villages:\n" + _fmt("pelion_villages"))
+    if lg.get("activities"):
+        sections.append("Activities:\n" + _fmt("activities"))
+    if lg.get("museums_culture"):
+        sections.append("Museums & culture:\n" + _fmt("museums_culture"))
+    if lg.get("day_trips"):
+        sections.append("Day trips & ferries:\n" + _fmt("day_trips"))
+    if lg.get("cafes_bars"):
+        sections.append("Cafés & bars:\n" + _fmt("cafes_bars"))
+    local_guide = "\n\n".join(sections)
+
+    base = f"""You are the concierge AI for {HOTEL_INFO['name']}. Provide concise, friendly answers.
+    Hotel Facts:
+    Location: {HOTEL_INFO['location']}
+    Star Rating: {HOTEL_INFO['star_rating']}⭐
+    Check-in: {HOTEL_INFO['check_in_time']}  |  Check-out: {HOTEL_INFO['check_out_time']}
+    Amenities:\n{amenities}\nSpa: {HOTEL_INFO['spa']['name']} (Open {HOTEL_INFO['spa']['open']})\nSignature Treatments:\n{treatments}\nDining Venues: {', '.join(HOTEL_INFO['dining'])}\nLate Checkout: {HOTEL_INFO['late_checkout_policy']}\nCurrent Upsell Offers:\n{offers}
+    Local Guide — Volos & Pelion:\n{local_guide}
+    """
+    if dynamic_context:
+        base += f"Dynamic Context:\n{dynamic_context}\n"
+    base += (
+        "Instructions:\n"
+        "- Answer the user's question directly using the facts above.\n"
+        "- Do NOT include any role prefixes like 'User:' or 'Assistant:'.\n"
+        "- Do NOT create additional 'User:' turns in your output.\n"
+        "- Do NOT echo 'Question:' or 'Answer:' in the output.\n"
+        "- Prefer nearby Volos & Pelion suggestions; for food, prioritize tsipouradika seafood meze. Include short distance/time if helpful.\n"
+        "- Keep responses under 120 words.\n"
+        "Reply with only the answer text."
+    )
+    return base
 
 
 def _sanitize_llm_output(text: str) -> str:
@@ -388,12 +511,21 @@ def _sanitize_llm_output(text: str) -> str:
     for p in ("Assistant:", "ASSISTANT:", "assistant:", "AI:", "Bot:"):
         if t.startswith(p):
             t = t[len(p):].lstrip()
+    # Remove leading Answer: prefix if present
+    if t.startswith("Answer:"):
+        t = t[len("Answer:"):].lstrip()
     # Cut at first sign of a new role line
     for marker in ("\nUser:", "\nUSER:", "\nHuman:", "\nHUMAN:", "\nAssistant:", "\nASSISTANT:", "\nSystem:"):
         idx = t.find(marker)
         if idx != -1:
             t = t[:idx].rstrip()
             break
+    # If the model starts another pseudo Q/A, cut at repeated Question/Answer markers
+    for marker in ("\nQuestion:", "\nQUESTION:", "\nAnswer:", "\nANSWER:"):
+        idx = t.find(marker)
+        if idx != -1:
+            t = t[:idx].rstrip()
+            break
     # Normalize spaces
     t = " ".join(t.split())
     # Soft cap ~120 words
@@ -403,22 +535,56 @@ def _sanitize_llm_output(text: str) -> str:
     return t
 
 
+def _build_dynamic_context(session: dict) -> str:
+    """Lightweight contextual notes; placeholder for time/weather/nearby in future UI.
+    Uses session hints if present; otherwise empty string.
+    """
+    parts: List[str] = []
+    # Time of day
+    tod = (session or {}).get("time_of_day")
+    if tod:
+        parts.append(f"Time of day: {tod}")
+    # Weather
+    wx = (session or {}).get("weather")
+    if wx:
+        parts.append(f"Weather: {wx}")
+    # Near-me radius (km)
+    near = (session or {}).get("near_km")
+    if isinstance(near, (int, float)) and near > 0:
+        parts.append(f"Focus on places within ~{near} km when relevant.")
+    # Seasonal hint
+    month = dt.datetime.now().month
+    season = (
+        "summer (beaches, ferries to Sporades)" if month in (6, 7, 8) else
+        "shoulder season (milder weather; Pelion villages, hikes)" if month in (5, 9, 10) else
+        "cool season (mountain villages, museums, hearty food)"
+    )
+    parts.append(f"Seasonal note: {season}.")
+    return "\n".join(parts)
+
+
 def ai_general_response(user_message: str, session: dict) -> Optional[str]:
     llm = load_llm()
     if not llm:
         return "(AI assistant unavailable right now — please try again later or ask at the front desk.)"
-    system_prompt = compose_system_prompt()
+    dynamic_ctx = _build_dynamic_context(session)
+    system_prompt = compose_system_prompt(dynamic_ctx)
     # Use an instruction-style prompt to avoid multi-turn role simulation
     final_prompt = system_prompt + "\n\nQuestion: " + user_message.strip() + "\nAnswer:"
     try:
         if hasattr(llm, "__call__") and not hasattr(llm, "_pipeline"):
-            out = llm(final_prompt)
+            # Likely a raw HF pipeline; try passing conservative decoding args to reduce hallucinations
+            try:
+                out = llm(final_prompt, max_new_tokens=200, temperature=0.2, top_p=0.9)
+            except Exception:
+                out = llm(final_prompt)
             if isinstance(out, list):
                 raw = out[0].get("generated_text", "")
                 text = raw[len(final_prompt):] if raw.startswith(final_prompt) else raw
             else:
                 text = str(out)
         else:
+            # LangChain or other wrapper; fall back to simple call
             text = llm(final_prompt)  # type: ignore
         return _sanitize_llm_output(text)
     except Exception as e:
@@ -559,8 +725,49 @@ def handle_chat(message, chat_history, session, room_type_dd, ci, co):
         return chat
     chat.append(user_reply(msg))
     lower = msg.lower()
+    # Offer navigation & acceptance: deterministic actions
+    if any(k in lower for k in ["next offer", "next >>", "next ▶", "show next offer"]):
+        card, idx = next_offer_action(session.get("offers_index", 0), session)
+        session["offers_index"] = idx
+        chat.append(system_reply("Showing next offer."))
+        chat.append(system_reply(card))
+        return chat
+    if any(k in lower for k in ["prev offer", "previous offer", "◀ prev", "show previous offer"]):
+        card, idx = prev_offer_action(session.get("offers_index", 0), session)
+        session["offers_index"] = idx
+        chat.append(system_reply("Showing previous offer."))
+        chat.append(system_reply(card))
+        return chat
+    if any(k in lower for k in ["accept offer", "i'll take it", "i will take it", "buy offer", "add offer"]):
+        # accept current index
+        updated_chat, card, accepted_md_text, new_idx = accept_offer_action(session.get("offers_index", 0), chat, session)
+        session["offers_index"] = new_idx
+        chat = updated_chat
+        chat.append(system_reply(card))
+        chat.append(system_reply(accepted_md_text))
+        return chat
+    # Accept a specific offer by title keywords, e.g., "I want the Spa Thermal Circuit Upgrade"
+    if any(k in lower for k in ["i want", "i'd like", "i will take", "i will get", "i want the", "i want to buy"]):
+        offers = get_active_offers()
+        if offers:
+            # find best title match
+            best_idx, best_score = None, 0
+            for i, o in enumerate(offers):
+                title = o.get("title", "").lower()
+                score = sum(1 for w in title.split() if w in lower)
+                if score > best_score:
+                    best_score, best_idx = score, i
+            if best_idx is not None and best_score > 0:
+                updated_chat, card, accepted_md_text, new_idx = accept_offer_action(best_idx, chat, session)
+                session["offers_index"] = new_idx
+                chat = updated_chat
+                chat.append(system_reply(card))
+                chat.append(system_reply(accepted_md_text))
+                return chat
+    # Cleaning intents
     if any(k in lower for k in ["clean", "housekeeping", "maid"]):
         return call_cleaning_action(chat, session)
+    # Booking intents
     if "book" in lower:
         guessed_type = None
         for t in HOTEL.room_types.keys():
@@ -632,6 +839,15 @@ with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue")) as demo:
             with gr.Row():
                 send = gr.Button("Send", variant="primary")
                 clean_btn = gr.Button("Call Cleaning")
+            with gr.Accordion("Context (time, weather, near me)", open=False):
+                with gr.Row():
+                    time_of_day_dd = gr.Dropdown(["morning", "afternoon", "evening", "night"], label="Time of day", value=None)
+                    weather_dd = gr.Dropdown(["clear", "cloudy", "rain", "windy", "hot"], label="Weather", value=None)
+                near_slider = gr.Slider(0, 50, value=0, step=1, label="Near me radius (km)")
+                with gr.Row():
+                    apply_ctx_btn = gr.Button("Apply Context")
+                    clear_ctx_btn = gr.Button("Clear Context")
+                ctx_status = gr.Markdown("_No extra context set. Seasonal notes apply automatically._")
 
         # Right: Booking + Offers
         with gr.Column(scale=1):
@@ -679,6 +895,16 @@ with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue")) as demo:
         inputs=[chat, session],
         outputs=[chat],
     )
+    apply_ctx_btn.click(
+        set_context_action,
+        inputs=[time_of_day_dd, weather_dd, near_slider, session],
+        outputs=[session, ctx_status],
+    )
+    clear_ctx_btn.click(
+        clear_context_action,
+        inputs=[session],
+        outputs=[session, ctx_status, time_of_day_dd, weather_dd, near_slider],
+    )
     book_btn.click(
         book_action,
         inputs=[guest_name, room_type_dd, check_in, check_out, chat, session],