sync from 7d209ce

app.py

@@ -1,4 +1,4 @@
-"""DartLab Streamlit Demo — DART/EDGAR 공시 분석."""
+"""DartLab Streamlit Demo — AI 채팅 기반 기업 분석."""
 
 from __future__ import annotations
 
@@ -6,7 +6,6 @@ import gc
 import io
 import os
 import re
-from collections import OrderedDict
 
 import pandas as pd
 import streamlit as st
@@ -22,99 +21,70 @@ _DOCS_URL = "https://eddmpython.github.io/dartlab/docs/getting-started/quickstar
 _COLAB_URL = "https://colab.research.google.com/github/eddmpython/dartlab/blob/master/notebooks/showcase/01_quickstart.ipynb"
 _REPO_URL = "https://github.com/eddmpython/dartlab"
 
+_HAS_OPENAI = bool(os.environ.get("OPENAI_API_KEY"))
+
+if _HAS_OPENAI:
+    dartlab.llm.configure(provider="openai", api_key=os.environ["OPENAI_API_KEY"])
+
 # ── 페이지 설정 ──────────────────────────────────────
 
 st.set_page_config(
-    page_title="DartLab — 종목코드 하나로 기업 분석",
-    page_icon="📊",
+    page_title="DartLab — AI 기업 분석",
+    page_icon=None,
     layout="centered",
 )
 
-# ── 커스텀 CSS ────────────────────────────────────────
+# ── CSS ───────────────────────────────────────────────
 
 st.markdown("""
 <style>
-/* ══════════════════════════════════════════════════
-   dartlab 다크 테마 — 라이트 모드 강제 오버라이드
-   랜딩 페이지 색상 체계: #050811 / #0f1219 / #ea4647
-   ══════════════════════════════════════════════════ */
-
-/* 전역 배경 강제 */
+/* 다크 테마 강제 */
 html, body, [data-testid="stAppViewContainer"],
 [data-testid="stApp"], .main, .block-container {
     background-color: #050811 !important;
     color: #f1f5f9 !important;
 }
-[data-testid="stHeader"] {
-    background: #050811 !important;
-}
-[data-testid="stSidebar"] {
-    background: #0f1219 !important;
-}
+[data-testid="stHeader"] { background: #050811 !important; }
+[data-testid="stSidebar"] { background: #0f1219 !important; }
 
-/* 입력 필드 — 다크 강제 */
-input, textarea, [data-testid="stTextInput"] input,
-[data-baseweb="input"] input,
-[data-baseweb="textarea"] textarea {
+/* 입력 필드 */
+input, textarea,
+[data-baseweb="input"] input, [data-baseweb="textarea"] textarea,
+[data-baseweb="input"], [data-baseweb="base-input"] {
     background-color: #0f1219 !important;
     color: #f1f5f9 !important;
     border-color: #1e2433 !important;
-    caret-color: #ea4647 !important;
-}
-[data-baseweb="input"],
-[data-baseweb="base-input"] {
-    background-color: #0f1219 !important;
-    border-color: #1e2433 !important;
 }
 
-/* 셀렉트박스/드롭다운 */
+/* 셀렉트/드롭다운 */
 [data-baseweb="select"] > div {
     background-color: #0f1219 !important;
     border-color: #1e2433 !important;
     color: #f1f5f9 !important;
 }
-[data-baseweb="popover"] {
-    background-color: #0f1219 !important;
-    border-color: #1e2433 !important;
-}
-[data-baseweb="menu"] {
+[data-baseweb="popover"], [data-baseweb="menu"] {
     background-color: #0f1219 !important;
 }
-[data-baseweb="menu"] li {
-    color: #f1f5f9 !important;
-}
-[data-baseweb="menu"] li:hover {
-    background-color: #1a1f2b !important;
-}
-
-/* 라디오 버튼 */
-[data-testid="stRadio"] label {
-    color: #f1f5f9 !important;
-}
-[data-testid="stRadio"] [data-baseweb="radio"] {
-    background-color: transparent !important;
-}
+[data-baseweb="menu"] li { color: #f1f5f9 !important; }
+[data-baseweb="menu"] li:hover { background-color: #1a1f2b !important; }
 
-/* DataFrame 다크 강제 */
-[data-testid="stDataFrame"] {
-    font-variant-numeric: tabular-nums;
-}
-[data-testid="stDataFrame"] [data-testid="glideDataEditor"],
-[data-testid="stDataFrame"] canvas {
-    background-color: #0f1219 !important;
-}
+/* 라디오 */
+[data-testid="stRadio"] label { color: #f1f5f9 !important; }
 
-/* 버튼 */
-[data-testid="stBaseButton-primary"] {
+/* 버튼 — dartlab primary 통일 */
+button, [data-testid="stBaseButton-primary"],
+[data-testid="stBaseButton-secondary"],
+[data-testid="stFormSubmitButton"] button,
+[data-testid="stChatInputSubmitButton"] {
     background-color: #ea4647 !important;
     color: #fff !important;
     border: none !important;
     font-weight: 600 !important;
 }
-[data-testid="stBaseButton-primary"]:hover {
+button:hover, [data-testid="stBaseButton-primary"]:hover,
+[data-testid="stChatInputSubmitButton"]:hover {
     background-color: #c83232 !important;
 }
-[data-testid="stBaseButton-secondary"],
 [data-testid="stDownloadButton"] button {
     background-color: #0f1219 !important;
     color: #f1f5f9 !important;
@@ -123,6 +93,12 @@ input, textarea, [data-testid="stTextInput"] input,
 [data-testid="stDownloadButton"] button:hover {
     border-color: #ea4647 !important;
     color: #ea4647 !important;
+    background-color: #0f1219 !important;
+}
+/* expander 토글은 배경색 제거 */
+[data-testid="stExpander"] button {
+    background-color: transparent !important;
+    color: #f1f5f9 !important;
 }
 
 /* Expander */
@@ -130,43 +106,33 @@ input, textarea, [data-testid="stTextInput"] input,
     background-color: #0f1219 !important;
     border-color: #1e2433 !important;
 }
-[data-testid="stExpander"] summary {
-    color: #f1f5f9 !important;
-}
-[data-testid="stExpander"] [data-testid="stMarkdownContainer"] {
-    color: #f1f5f9 !important;
-}
 
 /* Chat */
 [data-testid="stChatMessage"] {
-    background-color: #0f1219 !important;
+    background-color: #0a0e17 !important;
     border-color: #1e2433 !important;
 }
-[data-testid="stChatInput"] {
+[data-testid="stChatInput"], [data-testid="stChatInput"] textarea {
     background-color: #0f1219 !important;
     border-color: #1e2433 !important;
-}
-[data-testid="stChatInput"] textarea {
-    background-color: #0f1219 !important;
     color: #f1f5f9 !important;
 }
 
-/* 기본 텍스트 */
+/* 텍스트 */
 p, span, label, h1, h2, h3, h4, h5, h6,
 [data-testid="stMarkdownContainer"],
 [data-testid="stMarkdownContainer"] p {
     color: #f1f5f9 !important;
 }
-[data-testid="stCaption"], .stCaption {
-    color: #64748b !important;
-}
+[data-testid="stCaption"] { color: #64748b !important; }
 
-/* ── 커스텀 컴포넌트 ── */
+/* DataFrame */
+[data-testid="stDataFrame"] { font-variant-numeric: tabular-nums; }
 
-/* 헤더 */
+/* 커스텀 */
 .dl-header {
     text-align: center;
-    padding: 2rem 0 1.2rem;
+    padding: 1.5rem 0 0.5rem;
 }
 .dl-header img {
     border-radius: 50%;
@@ -177,39 +143,20 @@ p, span, label, h1, h2, h3, h4, h5, h6,
     -webkit-background-clip: text;
     -webkit-text-fill-color: transparent;
     background-clip: text;
-    font-size: 2.6rem !important;
+    font-size: 2.4rem !important;
     font-weight: 800 !important;
-    margin: 0.6rem 0 0.15rem !important;
+    margin: 0.5rem 0 0.1rem !important;
     letter-spacing: -0.03em;
 }
-.dl-header .tagline {
-    color: #94a3b8 !important;
-    font-size: 1.08rem;
-    margin: 0;
-}
-.dl-header .sub {
-    color: #64748b !important;
-    font-size: 0.85rem;
-    margin: 0.2rem 0 0;
-}
-
-/* 섹션 제목 */
-.dl-section {
-    color: #ea4647 !important;
-    font-weight: 700 !important;
-    font-size: 1.15rem !important;
-    border-bottom: 2px solid #ea4647;
-    padding-bottom: 0.35rem;
-    margin: 1.5rem 0 0.8rem;
-}
+.dl-header .tagline { color: #94a3b8 !important; font-size: 1rem; margin: 0; }
+.dl-header .sub { color: #64748b !important; font-size: 0.82rem; margin: 0.15rem 0 0; }
 
-/* 기업카드 */
 .dl-card {
     background: linear-gradient(135deg, #0f1219 0%, #0a0d16 100%);
     border: 1px solid #1e2433;
     border-radius: 12px;
-    padding: 1.4rem 1.8rem;
-    margin: 1rem 0;
+    padding: 1.2rem 1.5rem;
+    margin: 0.8rem 0;
     position: relative;
     overflow: hidden;
 }
@@ -220,81 +167,45 @@ p, span, label, h1, h2, h3, h4, h5, h6,
     height: 3px;
     background: linear-gradient(90deg, #ea4647, #f87171, #fb923c);
 }
-.dl-card h2 {
-    color: #f1f5f9 !important;
-    font-size: 1.5rem !important;
-    margin: 0 0 1rem !important;
-    font-weight: 700;
-}
-.dl-card .meta {
-    display: flex;
-    gap: 2.5rem;
-    flex-wrap: wrap;
-}
-.dl-card .meta-item {
-    display: flex;
-    flex-direction: column;
-    gap: 0.15rem;
-}
+.dl-card h3 { color: #f1f5f9 !important; font-size: 1.3rem !important; margin: 0 0 0.8rem !important; }
+.dl-card .meta { display: flex; gap: 2.5rem; flex-wrap: wrap; }
+.dl-card .meta-item { display: flex; flex-direction: column; gap: 0.1rem; }
 .dl-card .meta-label {
-    color: #64748b !important;
-    font-size: 0.72rem;
-    text-transform: uppercase;
-    letter-spacing: 0.08em;
-    font-weight: 500;
+    color: #64748b !important; font-size: 0.72rem;
+    text-transform: uppercase; letter-spacing: 0.08em;
 }
 .dl-card .meta-value {
-    color: #e2e8f0 !important;
-    font-size: 1.15rem;
-    font-weight: 600;
-    font-family: 'JetBrains Mono', 'Fira Code', monospace;
+    color: #e2e8f0 !important; font-size: 1.1rem; font-weight: 600;
+    font-family: 'JetBrains Mono', monospace;
 }
 
-/* 안내 텍스트 */
-.dl-guide {
-    color: #64748b !important;
-    font-size: 0.88rem;
-    text-align: center;
-    margin: 0.2rem 0 0.8rem;
+.dl-section {
+    color: #ea4647 !important;
+    font-weight: 700 !important;
+    font-size: 1.05rem !important;
+    border-bottom: 2px solid #ea4647;
+    padding-bottom: 0.3rem;
+    margin: 1rem 0 0.6rem;
 }
 
-/* 푸터 */
 .dl-footer {
     text-align: center;
-    padding: 2rem 0 1rem;
+    padding: 1.5rem 0 0.8rem;
     border-top: 1px solid #1e2433;
-    margin-top: 2.5rem;
-    color: #475569 !important;
-    font-size: 0.85rem;
-}
-.dl-footer a {
-    color: #94a3b8 !important;
-    text-decoration: none;
-    margin: 0 0.6rem;
-    transition: color 0.2s;
-}
-.dl-footer a:hover {
-    color: #ea4647 !important;
-}
-
-/* 빈 상태 */
-.dl-empty {
-    text-align: center;
+    margin-top: 2rem;
     color: #475569 !important;
-    padding: 3rem 1rem;
-    font-size: 1rem;
+    font-size: 0.82rem;
 }
+.dl-footer a { color: #94a3b8 !important; text-decoration: none; margin: 0 0.5rem; }
+.dl-footer a:hover { color: #ea4647 !important; }
 
-/* 히어로 그라디언트 배경 효과 (랜딩 느낌) */
 .dl-hero-glow {
     position: fixed;
     top: 0; left: 50%;
     transform: translateX(-50%);
-    width: 600px;
-    height: 400px;
-    background: radial-gradient(ellipse at top, rgba(234,70,71,0.06) 0%, transparent 60%);
-    pointer-events: none;
-    z-index: 0;
+    width: 600px; height: 400px;
+    background: radial-gradient(ellipse at top, rgba(234,70,71,0.05) 0%, transparent 60%);
+    pointer-events: none; z-index: 0;
 }
 </style>
 """, unsafe_allow_html=True)
@@ -304,7 +215,7 @@ p, span, label, h1, h2, h3, h4, h5, h6,
 
 
 def _toPandas(df):
-    """Polars/pandas DataFrame → pandas 변환."""
+    """Polars/pandas DataFrame -> pandas."""
     if df is None:
         return None
     if hasattr(df, "to_pandas"):
@@ -312,33 +223,8 @@ def _toPandas(df):
     return df
 
 
-@st.cache_resource(max_entries=_MAX_CACHE)
-def _getCompany(code: str):
-    """캐시된 Company 반환."""
-    gc.collect()
-    return dartlab.Company(code)
-
-
-def _resolveCode(query: str) -> tuple[str | None, str | None]:
-    """쿼리 → (종목코드, 에러메시지)."""
-    query = query.strip()
-    if not query:
-        return None, None
-
-    if re.match(r"^\d{6}$", query) or re.match(r"^[A-Z]{1,5}$", query):
-        return query, None
-
-    try:
-        results = dartlab.search(query)
-        if results is None or len(results) == 0:
-            return None, f"'{query}' 검색 결과가 없습니다. 종목코드(예: 005930)를 직접 입력해보세요."
-        return str(results[0, "stockCode"]), None
-    except Exception as e:
-        return None, f"검색 실패: {e}"
-
-
 def _formatDf(df: pd.DataFrame) -> pd.DataFrame:
-    """숫자 컬럼을 천단위 콤마 문자열로 변환 (소수점 제거)."""
+    """숫자를 천단위 콤마 문자열로 변환 (소수점 제거)."""
     if df is None or df.empty:
         return df
     result = df.copy()
@@ -351,28 +237,21 @@ def _formatDf(df: pd.DataFrame) -> pd.DataFrame:
 
 
 def _toExcel(df: pd.DataFrame) -> bytes:
-    """DataFrame → Excel bytes."""
+    """DataFrame -> Excel bytes."""
     buf = io.BytesIO()
     df.to_excel(buf, index=False, engine="openpyxl")
     return buf.getvalue()
 
 
-def _showDataFrame(df: pd.DataFrame, key: str = "", downloadName: str = ""):
-    """DataFrame 표시 + 엑셀 다운로드 버튼."""
+def _showDf(df: pd.DataFrame, key: str = "", downloadName: str = ""):
+    """DataFrame 표시 + Excel 다운로드."""
     if df is None or df.empty:
-        st.markdown('<p class="dl-empty">데이터 없음</p>', unsafe_allow_html=True)
+        st.caption("데이터 없음")
         return
-    # 포맷팅된 버전으로 표시
-    st.dataframe(
-        _formatDf(df),
-        use_container_width=True,
-        hide_index=True,
-        key=key or None,
-    )
-    # 엑셀 다운로드 (원본 숫자 유지)
+    st.dataframe(_formatDf(df), use_container_width=True, hide_index=True, key=key or None)
     if downloadName:
         st.download_button(
-            label="📥 Excel 다운로드",
+            label="Excel 다운로드",
             data=_toExcel(df),
             file_name=f"{downloadName}.xlsx",
             mime="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
@@ -380,17 +259,100 @@ def _showDataFrame(df: pd.DataFrame, key: str = "", downloadName: str = ""):
         )
 
 
-# ── AI ────────────────────────────────────────────────
+@st.cache_resource(max_entries=_MAX_CACHE)
+def _getCompany(code: str):
+    """캐시된 Company."""
+    gc.collect()
+    return dartlab.Company(code)
 
-_HAS_OPENAI = bool(os.environ.get("OPENAI_API_KEY"))
 
-if _HAS_OPENAI:
-    dartlab.llm.configure(provider="openai", api_key=os.environ["OPENAI_API_KEY"])
+# ── 종목코드 추출 ────────────────────────────────────
+
+
+def _extractCode(message: str) -> str | None:
+    """메시지에서 종목코드/회사명 추출."""
+    msg = message.strip()
+
+    # 6자리 숫자
+    m = re.search(r"\b(\d{6})\b", msg)
+    if m:
+        return m.group(1)
+
+    # 영문 티커 (단독 대문자 1~5자)
+    m = re.search(r"\b([A-Z]{1,5})\b", msg)
+    if m:
+        return m.group(1)
+
+    # 한글 회사명 → dartlab.search
+    cleaned = re.sub(
+        r"(에\s*대해|에\s*대한|에대해|좀|의|를|을|은|는|이|가|도|만|부터|까지|하고|이랑|랑|로|으로|와|과|한테|에서|에게)\b",
+        " ",
+        msg,
+    )
+    # 불필요한 동사/조동사 제거
+    cleaned = re.sub(
+        r"\b(알려줘|보여줘|분석|해줘|해봐|어때|보자|볼래|줘|해|좀|요)\b",
+        " ",
+        cleaned,
+    )
+    tokens = re.findall(r"[가-힣A-Za-z0-9]+", cleaned)
+    # 긴 토큰 우선 (회사명일 가능성 높음)
+    tokens.sort(key=len, reverse=True)
+    for token in tokens:
+        if len(token) >= 2:
+            try:
+                results = dartlab.search(token)
+                if results is not None and len(results) > 0:
+                    return str(results[0, "stockCode"])
+            except Exception:
+                continue
+    return None
+
+
+def _detectTopic(message: str) -> str | None:
+    """메시지에서 특정 topic 키워드 감지."""
+    topicMap = {
+        "배당": "dividend",
+        "주주": "majorHolder",
+        "대주주": "majorHolder",
+        "직원": "employee",
+        "임원": "executive",
+        "임원보수": "executivePay",
+        "보수": "executivePay",
+        "세그먼트": "segments",
+        "부문": "segments",
+        "사업부": "segments",
+        "유형자산": "tangibleAsset",
+        "무형자산": "intangibleAsset",
+        "원재료": "rawMaterial",
+        "수주": "salesOrder",
+        "제품": "productService",
+        "자회사": "subsidiary",
+        "종속": "subsidiary",
+        "부채": "contingentLiability",
+        "우발": "contingentLiability",
+        "파생": "riskDerivative",
+        "사채": "bond",
+        "이사회": "boardOfDirectors",
+        "감사": "audit",
+        "자본변동": "capitalChange",
+        "자기주식": "treasuryStock",
+        "사업개요": "business",
+        "사업보고": "business",
+        "연혁": "companyHistory",
+    }
+    msg = message.lower()
+    for keyword, topic in topicMap.items():
+        if keyword in msg:
+            return topic
+    return None
+
+
+# ── AI ────────────────────────────────────────────────
 
 
 def _askAi(stockCode: str, question: str) -> str:
-    """AI 질문 처리. OpenAI 우선, 없으면 HF 무료 Inference API."""
-    # OpenAI가 설정되어 있으면 dartlab.ask 사용
+    """AI 질문. OpenAI 우선, HF 무료 fallback."""
     if _HAS_OPENAI:
         try:
             q = f"{stockCode} {question}" if stockCode else question
@@ -399,15 +361,13 @@ def _askAi(stockCode: str, question: str) -> str:
         except Exception as e:
             return f"분석 실패: {e}"
 
-    # HF Inference API (토큰 없이도 무료 호출 가능)
     try:
         from huggingface_hub import InferenceClient
-        token = os.environ.get("HF_TOKEN")  # 있으면 rate limit 높아짐
+        token = os.environ.get("HF_TOKEN")
         client = InferenceClient(
             model="meta-llama/Llama-3.1-8B-Instruct",
             token=token if token else None,
         )
-
         context = _buildAiContext(stockCode)
         systemMsg = (
             "당신은 한국 기업 재무 분석 전문가입니다. "
@@ -415,7 +375,6 @@ def _askAi(stockCode: str, question: str) -> str:
             "숫자는 천단위 콤마를 사용하고, 근거를 명확히 제시하세요.\n\n"
             f"{context}"
         )
-
         response = client.chat_completion(
             messages=[
                 {"role": "system", "content": systemMsg},
@@ -429,46 +388,111 @@ def _askAi(stockCode: str, question: str) -> str:
 
 
 def _buildAiContext(stockCode: str) -> str:
-    """AI에 전달할 기업 재무 컨텍스트 구성."""
+    """AI 컨텍스트 구성."""
     try:
         c = _getCompany(stockCode)
     except Exception:
         return f"종목코드: {stockCode}"
 
     parts = [f"기업: {c.corpName} ({c.stockCode}), 시장: {c.market}"]
+    for name, attr in [("손익계산서", "IS"), ("재무상태표", "BS"), ("재무비율", "ratios")]:
+        try:
+            df = _toPandas(getattr(c, attr, None))
+            if df is not None and not df.empty:
+                parts.append(f"\n[{name}]\n{df.head(15).to_string()}")
+        except Exception:
+            pass
+    return "\n".join(parts)
 
-    # IS 요약
-    try:
-        isDf = _toPandas(c.IS)
-        if isDf is not None and not isDf.empty:
-            parts.append(f"\n[손익계산서 요약]\n{isDf.head(15).to_string()}")
-    except Exception:
-        pass
 
-    # BS 요약
-    try:
-        bsDf = _toPandas(c.BS)
-        if bsDf is not None and not bsDf.empty:
-            parts.append(f"\n[재무상태표 요약]\n{bsDf.head(15).to_string()}")
-    except Exception:
-        pass
+# ── 대시보드 렌더링 ──────────────────────────────────
+
+
+def _renderCompanyCard(c):
+    """기업 카드."""
+    currency = ""
+    if hasattr(c, "currency") and c.currency:
+        currency = c.currency
+    currencyHtml = (
+        f"<div class='meta-item'><span class='meta-label'>통화</span>"
+        f"<span class='meta-value'>{currency}</span></div>"
+        if currency else ""
+    )
+    st.markdown(f"""
+    <div class="dl-card">
+        <h3>{c.corpName}</h3>
+        <div class="meta">
+            <div class="meta-item">
+                <span class="meta-label">종목코드</span>
+                <span class="meta-value">{c.stockCode}</span>
+            </div>
+            <div class="meta-item">
+                <span class="meta-label">시장</span>
+                <span class="meta-value">{c.market}</span>
+            </div>
+            {currencyHtml}
+        </div>
+    </div>
+    """, unsafe_allow_html=True)
+
 
-    # ratios 요약
+def _renderFullDashboard(c, code: str):
+    """전체 재무 대시보드."""
+    _renderCompanyCard(c)
+
+    # 재무제표
+    st.markdown('<div class="dl-section">재무제표</div>', unsafe_allow_html=True)
+    for label, attr in [("IS (손익계산서)", "IS"), ("BS (재무상태표)", "BS"),
+                         ("CF (현금흐름표)", "CF"), ("ratios (재무비율)", "ratios")]:
+        with st.expander(label, expanded=(attr == "IS")):
+            try:
+                df = _toPandas(getattr(c, attr, None))
+                _showDf(df, key=f"dash_{attr}", downloadName=f"{code}_{attr}")
+            except Exception:
+                st.caption("로드 실패")
+
+    # Sections
+    topics = []
     try:
-        ratDf = _toPandas(c.ratios)
-        if ratDf is not None and not ratDf.empty:
-            parts.append(f"\n[재무비율]\n{ratDf.head(15).to_string()}")
+        topics = list(c.topics) if c.topics else []
     except Exception:
         pass
 
-    return "\n".join(parts)
+    if topics:
+        st.markdown('<div class="dl-section">공시 데이터</div>', unsafe_allow_html=True)
+        selectedTopic = st.selectbox("topic", topics, label_visibility="collapsed", key="dash_topic")
+        if selectedTopic:
+            try:
+                result = c.show(selectedTopic)
+                if result is not None:
+                    if hasattr(result, "to_pandas"):
+                        _showDf(_toPandas(result), key="dash_sec", downloadName=f"{code}_{selectedTopic}")
+                    else:
+                        st.markdown(str(result))
+            except Exception as e:
+                st.caption(f"조회 실패: {e}")
+
+
+def _renderTopicData(c, code: str, topic: str):
+    """특정 topic 데이터만 렌더링."""
+    try:
+        result = c.show(topic)
+        if result is not None:
+            if hasattr(result, "to_pandas"):
+                _showDf(_toPandas(result), key=f"topic_{topic}", downloadName=f"{code}_{topic}")
+            else:
+                st.markdown(str(result))
+        else:
+            st.caption(f"'{topic}' 데이터 없음")
+    except Exception as e:
+        st.caption(f"조회 실패: {e}")
 
 
 # ── 프리로드 ──────────────────────────────────────────
 
 @st.cache_resource
 def _warmup():
-    """listing 캐시 워밍업."""
+    """listing 캐시."""
     try:
         dartlab.search("삼성전자")
     except Exception:
@@ -483,157 +507,102 @@ _warmup()
 st.markdown(f"""
 <div class="dl-hero-glow"></div>
 <div class="dl-header">
-    <img src="{_LOGO_URL}" width="88" height="88" alt="DartLab">
+    <img src="{_LOGO_URL}" width="80" height="80" alt="DartLab">
     <h1>DartLab</h1>
     <p class="tagline">종목코드 하나. 기업의 전체 이야기.</p>
-    <p class="sub">DART · EDGAR 공시 데이터를 구조화하여 제공합니다</p>
+    <p class="sub">DART / EDGAR 공시 데이터를 구조화하여 제공합니다</p>
 </div>
 """, unsafe_allow_html=True)
 
 
-# ── 종목 입력 ─────────────────────────────────────────
+# ── 세션 초기화 ──────────────────────────────────────
 
-col1, col2 = st.columns([4, 1])
-with col1:
-    query = st.text_input(
-        "종목코드 또는 회사명",
-        placeholder="005930, 삼성전자, AAPL ...",
-        label_visibility="collapsed",
-    )
-with col2:
-    analyzeClicked = st.button("분석하기", type="primary", use_container_width=True)
-
-st.markdown('<p class="dl-guide">종목코드(005930) 또는 회사명(삼성전자)을 입력하고 분석하기를 클릭하세요</p>', unsafe_allow_html=True)
-
-
-# ── 메인 로직 ─────────────────────────────────────────
-
-# 세션 상태 초기화
+if "messages" not in st.session_state:
+    st.session_state.messages = []
 if "code" not in st.session_state:
     st.session_state.code = ""
 
-if analyzeClicked and query:
-    code, err = _resolveCode(query)
-    if err:
-        st.error(err)
-    elif code:
-        st.session_state.code = code
 
-code = st.session_state.code
+# ── 대시보드 영역 (종목이 있으면 표시) ───────��────────
 
-if code:
+if st.session_state.code:
     try:
-        c = _getCompany(code)
+        _dashCompany = _getCompany(st.session_state.code)
+        _renderFullDashboard(_dashCompany, st.session_state.code)
     except Exception as e:
         st.error(f"기업 로드 실패: {e}")
-        st.stop()
 
-    # ── 기업 카드 ──
-    currency = ""
-    if hasattr(c, "currency") and c.currency:
-        currency = c.currency
+    st.markdown("---")
 
-    st.markdown(f"""
-    <div class="dl-card">
-        <h2>🏢 {c.corpName}</h2>
-        <div class="meta">
-            <div class="meta-item">
-                <span class="meta-label">종목코드</span>
-                <span class="meta-value">{c.stockCode}</span>
-            </div>
-            <div class="meta-item">
-                <span class="meta-label">시장</span>
-                <span class="meta-value">{c.market}</span>
-            </div>
-            {"<div class='meta-item'><span class='meta-label'>통화</span><span class='meta-value'>" + currency + "</span></div>" if currency else ""}
-        </div>
-    </div>
-    """, unsafe_allow_html=True)
 
-    # ── 재무제표 ──
-    st.markdown('<div class="dl-section">📊 재무제표</div>', unsafe_allow_html=True)
-    st.markdown('<p class="dl-guide">IS(손익계산서) · BS(재무상태표) · CF(현금흐름표) · ratios(재무비율)</p>', unsafe_allow_html=True)
+# ── 채팅 영역 ────────────────────────────────────────
 
-    sheetTab = st.radio(
-        "시트 선택",
-        ["IS", "BS", "CF", "ratios"],
-        horizontal=True,
-        label_visibility="collapsed",
-    )
+# 히스토리 표시
+for msg in st.session_state.messages:
+    with st.chat_message(msg["role"]):
+        st.markdown(msg["content"])
 
-    finDf = None
-    try:
-        raw = getattr(c, sheetTab, None)
-        finDf = _toPandas(raw)
-    except Exception:
-        pass
+# 입력
+if prompt := st.chat_input("삼성전자에 대해 알려줘, 배당 현황은? ..."):
+    # 사용자 메시지 표시
+    st.session_state.messages.append({"role": "user", "content": prompt})
+    with st.chat_message("user"):
+        st.markdown(prompt)
 
-    _showDataFrame(finDf, key="finance", downloadName=f"{code}_{sheetTab}")
+    # 종목코드 추출 시도
+    newCode = _extractCode(prompt)
+    if newCode and newCode != st.session_state.code:
+        st.session_state.code = newCode
 
-    # ── Sections ──
-    topics = []
-    try:
-        topics = list(c.topics) if c.topics else []
-    except Exception:
-        pass
+    code = st.session_state.code
 
-    if topics:
-        st.markdown('<div class="dl-section">📋 공시 데이터 (Sections)</div>', unsafe_allow_html=True)
-        st.markdown('<p class="dl-guide">topic을 선택하면 해당 공시 항목의 기간별 데이터를 표시합니다</p>', unsafe_allow_html=True)
+    if not code:
+        # 종목 못 찾음
+        reply = "종목을 찾지 못했습니다. 회사명이나 종목코드를 포함해서 다시 질문해주세요.\n\n예: 삼성전자에 대해 알려줘, 005930 분석, AAPL 재무"
+        st.session_state.messages.append({"role": "assistant", "content": reply})
+        with st.chat_message("assistant"):
+            st.markdown(reply)
+    else:
+        # 응답 생성
+        with st.chat_message("assistant"):
+            # 특정 topic 감지
+            topic = _detectTopic(prompt)
 
-        selectedTopic = st.selectbox(
-            "Topic 선택",
-            topics,
-            label_visibility="collapsed",
-        )
+            if topic:
+                # 특정 topic만 보여주기
+                try:
+                    c = _getCompany(code)
+                    _renderTopicData(c, code, topic)
+                except Exception:
+                    pass
 
-        if selectedTopic:
-            secDf = None
-            secText = ""
-            try:
-                result = c.show(selectedTopic)
-                if result is not None:
-                    if hasattr(result, "to_pandas"):
-                        secDf = _toPandas(result)
-                    else:
-                        secText = str(result)
-            except Exception as e:
-                secText = f"조회 실패: {e}"
-
-            if secDf is not None:
-                _showDataFrame(secDf, key="section", downloadName=f"{code}_{selectedTopic}")
-            elif secText:
-                st.markdown(secText)
-
-    # ── AI Chat ──
-    with st.expander("🤖 AI 분석 (무료)", expanded=False):
-        st.caption("Llama 3.1 8B 기반 무료 AI 분석 · 복잡한 질문은 OpenAI API 설정 시 더 정확합니다")
-        if True:
-            if "messages" not in st.session_state:
-                st.session_state.messages = []
-
-            for msg in st.session_state.messages:
-                with st.chat_message(msg["role"]):
-                    st.markdown(msg["content"])
-
-            if prompt := st.chat_input("재무건전성 분석해줘, 배당 이상 징후 찾아줘 ..."):
-                st.session_state.messages.append({"role": "user", "content": prompt})
-                with st.chat_message("user"):
-                    st.markdown(prompt)
-
-                with st.chat_message("assistant"):
-                    with st.spinner("분석 중..."):
-                        answer = _askAi(code, prompt)
-                    st.markdown(answer)
-                    st.session_state.messages.append({"role": "assistant", "content": answer})
-
-else:
-    # 미입력 상태
+            # AI 요약
+            with st.spinner("분석 중..."):
+                aiAnswer = _askAi(code, prompt)
+            st.markdown(aiAnswer)
+
+            st.session_state.messages.append({"role": "assistant", "content": aiAnswer})
+
+    # 대시보드 갱신을 위해 rerun
+    if newCode and newCode != "":
+        st.rerun()
+
+
+# ── 초기 안내 (대화 없을 때) ─────────────────────────
+
+if not st.session_state.messages and not st.session_state.code:
     st.markdown("""
-    <div class="dl-empty">
-        <p style="font-size: 1.2rem; color: #94a3b8;">종목코드를 입력하고 <strong>분석하기</strong>를 클릭하세요</p>
-        <p style="color: #475569; margin-top: 0.5rem;">
-            예시: <code>005930</code> (삼성전자) · <code>000660</code> (SK하이닉스) · <code>AAPL</code> (Apple)
+    <div style="text-align: center; color: #64748b; padding: 2rem 1rem;">
+        <p style="font-size: 1.1rem; color: #94a3b8;">
+            아래 입력창에 자연어로 질문하세요
+        </p>
+        <p style="margin-top: 0.5rem;">
+            <code>삼성전자에 대해 알려줘</code> &middot;
+            <code>005930 분석</code> &middot;
+            <code>AAPL 재무 보여줘</code>
+        </p>
+        <p style="margin-top: 0.3rem; font-size: 0.85rem;">
+            종목을 말하면 재무제표/공시 데이터가 바로 표시되고, AI가 분석을 덧붙입니다
         </p>
     </div>
     """, unsafe_allow_html=True)
@@ -643,12 +612,12 @@ else:
 
 st.markdown(f"""
 <div class="dl-footer">
-    <a href="{_BLOG_URL}">📖 초보자 가이드</a> ·
-    <a href="{_DOCS_URL}">📘 공식 문서</a> ·
-    <a href="{_COLAB_URL}">🔬 Colab</a> ·
-    <a href="{_REPO_URL}">⭐ GitHub</a>
-    <br><span style="color:#334155; font-size:0.8rem; margin-top:0.5rem; display:inline-block;">
-        pip install dartlab · Python 3.12+
+    <a href="{_BLOG_URL}">초보자 가이드</a> /
+    <a href="{_DOCS_URL}">공식 문서</a> /
+    <a href="{_COLAB_URL}">Colab</a> /
+    <a href="{_REPO_URL}">GitHub</a>
+    <br><span style="color:#334155; font-size:0.78rem; margin-top:0.4rem; display:inline-block;">
+        pip install dartlab
     </span>
 </div>
 """, unsafe_allow_html=True)