Update app.py

app.py

@@ -45,6 +45,7 @@ os.environ.setdefault("HF_HUB_ENABLE_HF_TRANSFER", "1")
 from huggingface_hub import hf_hub_download
 import pandas as pd
 import streamlit as st
+import requests
 from streamlit.components.v1 import html
 from css import render_message, render_chip_buttons, log_and_render, replay_log, _get_colors
 
@@ -149,7 +150,174 @@ from chat_a import (
     format_summary_tags_custom,
     make_companion_age_message
 )
+OLLAMA_HOST = os.getenv("OLLAMA_HOST", "http://localhost:11434")
+OLLAMA_MODEL = os.getenv("OLLAMA_MODEL", "gemma2:9b")
+OLLAMA_TIMEOUT = int(os.getenv("OLLAMA_TIMEOUT", "60"))
+
+KOREAN_SYSTEM_PROMPT = """당신은 한국어 어시스턴트입니다. 항상 한국어로 답하세요."""
+
+STRUCTURED_EXTRACTION_SYSTEM = """\
+You are a travel assistant that extracts structured fields from Korean user queries.
+Return ONLY a valid JSON object:
+{
+  "emotion": "happy|sad|stressed|excited|tired|none",
+  "intent": "beach|hiking|shopping|food|museum|relaxing|none",
+  "country_hint": "",
+  "city_hint": "",
+  "themes_hint": ["<0..3 words>"],
+  "notes": "<very short reasoning in Korean>"
+}
+If unknown, use "none" or "" and NEVER add extra text outside JSON.
+"""
+
+def _build_structured_user_prompt(user_text: str) -> str:
+    # 불필요한 래핑 없이, 모델이 JSON만 내도록 깔끔히 전달
+    return user_text.strip()
+
+def _call_ollama_chat(
+    messages,
+    model=OLLAMA_MODEL,
+    temperature=0.8, top_p=0.9, top_k=40, repeat_penalty=1.1,
+    system_prompt=None
+):
+    url = f"{OLLAMA_HOST}/api/chat"
+    _msgs = []
+    if system_prompt:
+        _msgs.append({"role": "system", "content": system_prompt})
+    _msgs.extend(messages)
+
+    payload = {
+        "model": model,
+        "messages": _msgs,
+        "options": {
+            "temperature": temperature,
+            "top_p": top_p,
+            "top_k": top_k,
+            "repeat_penalty": repeat_penalty,
+        },
+        "stream": False,
+    }
+    try:
+        r = requests.post(url, json=payload, timeout=OLLAMA_TIMEOUT)
+        r.raise_for_status()
+        return (r.json().get("message") or {}).get("content", "") or ""
+    except requests.RequestException:
+        return ""
+
+def _llm_structured_extract(user_text: str):
+    out = _call_ollama_chat(
+        [
+            {"role": "system", "content": STRUCTURED_EXTRACTION_SYSTEM},
+            {"role": "user", "content": _build_structured_user_prompt(user_text)}
+        ],
+        system_prompt=None  # 위에서 system으로 이미 넣었음
+    )
+    try:
+        data = json.loads(out)
+    except Exception:
+        data = {}
+    data.setdefault("emotion", "none")
+    data.setdefault("intent", "none")
+    data.setdefault("country_hint", "")
+    data.setdefault("city_hint", "")
+    data.setdefault("themes_hint", [])
+    data.setdefault("notes", "")
+    return data
+
+# ──────────────────────────────── Streamlit용 LLM 모드 UI ────────────────────────────────
+def _ensure_llm_state():
+    st.session_state.setdefault("llm_mode", False)
+    st.session_state.setdefault("llm_history", [])     # [{'role':'user'|'assistant', 'content': str}, ...]
+    st.session_state.setdefault("llm_intro_needed", False)
+    st.session_state.setdefault("llm_input", "")
+
+def render_llm_followup(chat_container):
+    """
+    추천 플로우 종료 후 자동 진입하는 자유질문(LLM) 모드 UI.
+    """
+    _ensure_llm_state()
+    MAX_TURNS = 6
+
+    if st.session_state.get("llm_intro_needed"):
+        log_and_render(
+            "🧠 이제부터는 자유 질문 모드예요. 여행 외에도 뭐든 한국어로 물어보세요!",
+            sender="bot",
+            chat_container=chat_container,
+            key=f"llm_intro_{random.randint(1,999999)}"
+        )
+        st.session_state["llm_intro_needed"] = False
+
+    # 입력창
+    q = st.text_input(
+        "LLM 질문",
+        placeholder="무엇이든 물어보세요 (종료하려면 '종료' 입력)",
+        key="llm_input"
+    )
+
+    # 동작
+    if q:
+        # 종료 키워드
+        if q.strip() in ("종료", "quit", "exit"):
+            st.session_state["llm_mode"] = False
+            st.session_state["llm_input"] = ""
+            log_and_render(
+                "LLM 모드를 종료할게요. 필요하실 때 언제든 다시 질문해 주세요! ✨",
+                sender="bot",
+                chat_container=chat_container,
+                key=f"llm_end_{random.randint(1,999999)}"
+            )
+            st.rerun()
+            return
+
+        # 사용자 버블
+        log_and_render(
+            q,
+            sender="user",
+            chat_container=chat_container,
+            key=f"llm_user_{random.randint(1,999999)}"
+        )
+        st.session_state.llm_history.append({"role": "user", "content": q})
+
+        # 최근 히스토리로 LLM 호출
+        msgs = st.session_state.llm_history[-(MAX_TURNS-1):]
+        a = _call_ollama_chat(
+            messages=msgs,
+            system_prompt=KOREAN_SYSTEM_PROMPT,
+            temperature=0.8, top_p=0.9, top_k=40, repeat_penalty=1.1
+        )
 
+        if not a:
+            log_and_render(
+                "⚠️ LLM 응답을 받지 못했습니다. Ollama 서버 상태를 확인해 주세요.",
+                sender="bot",
+                chat_container=chat_container,
+                key=f"llm_err_{random.randint(1,999999)}"
+            )
+        else:
+            log_and_render(
+                a,
+                sender="bot",
+                chat_container=chat_container,
+                key=f"llm_bot_{random.randint(1,999999)}"
+            )
+            st.session_state.llm_history.append({"role": "assistant", "content": a})
+
+        # 입력 초기화
+        st.session_state["llm_input"] = ""
+
+    # 하단 종료 버튼
+    cols = st.columns(3)
+    with cols[0]:
+        if st.button("🔚 LLM 모드 종료"):
+            st.session_state["llm_mode"] = False
+            log_and_render(
+                "LLM 모드를 종료할게요. 다음에 또 만나요! 👋",
+                sender="bot",
+                chat_container=chat_container,
+                key=f"llm_end_btn_{random.randint(1,999999)}"
+            )
+            st.rerun()
+            
 # 지연 초기화: import 시점에는 데이터 접근 금지, 여기서 한 번만 주입
 init_datasets(
     travel_df=travel_df,
@@ -693,6 +861,11 @@ def region_ui(travel_df, external_score_df, festival_df, weather_df, package_df,
         log_and_render("필요하실 때 언제든지 또 찾아주세요! ✈️",
                     sender="bot", chat_container=chat_container,
                     key="goodbye")
+
+         # ✅ 여기서 LLM 모드로 자동 전환
+        st.session_state["llm_mode"] = True
+        st.session_state["llm_intro_needed"] = True
+        st.rerun()
       
 # ───────────────────────────────────── intent 모드
 def intent_ui(travel_df, external_score_df, festival_df, weather_df, package_df,
@@ -1045,6 +1218,11 @@ def intent_ui(travel_df, external_score_df, festival_df, weather_df, package_df,
         log_and_render("필요하실 때 언제든지 또 찾아주세요! ✈️",
                     sender="bot", chat_container=chat_container,
                     key="goodbye")
+
+         # ✅ 여기서 LLM 모드로 자동 전환
+        st.session_state["llm_mode"] = True
+        st.session_state["llm_intro_needed"] = True
+        st.rerun()
         
 # ───────────────────────────────────── emotion 모드
 def emotion_ui(travel_df, external_score_df, festival_df, weather_df, package_df,
@@ -1469,6 +1647,11 @@ def emotion_ui(travel_df, external_score_df, festival_df, weather_df, package_df
         log_and_render("필요하실 때 언제든지 또 찾아주세요! ✈️",
                     sender="bot", chat_container=chat_container,
                     key="goodbye")    
+
+         # ✅ 여기서 LLM 모드로 자동 전환
+        st.session_state["llm_mode"] = True
+        st.session_state["llm_intro_needed"] = True
+        st.rerun()
         
 # ───────────────────────────────────── unknown 모드
 def unknown_ui(country, city, chat_container, log_and_render):
@@ -1497,6 +1680,10 @@ def main():
     init_session()
     chat_container = st.container()
 
+    if st.session_state.get("llm_mode"):
+        render_llm_followup(chat_container)
+        return
+        
     # 🎛️ 말풍선/표시 옵션 (③, ④)
     st.sidebar.subheader("⚙️ 대화 표시")
     st.sidebar.selectbox("테마", ["피스타치오", "스카이블루", "크리미오트"], key="bubble_theme")