노출 개선: HF Spaces Docker + llms.txt 강화 + Try Online CTA

- Dockerfile + __main__.py + hfPreload.py: HuggingFace Spaces 데모 배포 준비
- .github/workflows/hfSpaces.yml: 릴리즈 시 HF Spaces 자동 배포
- pyproject.toml: URLs에 Documentation, Demo, Changelog 추가
- generateSpec.py: llms.txt를 영문 중심으로 대폭 강화 (AI 크롤러 최적화)
- Hero.svelte: Try Online 버튼 1순위 배치
- brand.ts: spaces URL 추가

Author: eddmpython

.dockerignore

@@ -0,0 +1,17 @@
+.git
+.github
+.venv
+.venv-wsl
+__pycache__
+*.pyc
+.pytest_cache
+.ruff_cache
+experiments
+notebooks
+tests
+docs
+blog
+landing
+data
+.claude
+*.egg-info

.github/workflows/hfSpaces.yml

@@ -0,0 +1,48 @@
+name: Deploy to HuggingFace Spaces
+
+on:
+  release:
+    types: [published]
+  workflow_dispatch:
+
+permissions:
+  contents: read
+
+jobs:
+  deploy:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Push to HuggingFace Spaces
+        env:
+          HF_TOKEN: ${{ secrets.HF_TOKEN }}
+        run: |
+          git clone --depth 1 https://user:${HF_TOKEN}@huggingface.co/spaces/eddmpython/dartlab hf-space
+
+          # Dockerfile + 필요 파일만 복사
+          cp Dockerfile hf-space/
+          cp .dockerignore hf-space/
+          mkdir -p hf-space/scripts
+          cp scripts/hfPreload.py hf-space/scripts/
+
+          # HF Spaces README (앱 설정)
+          cat > hf-space/README.md << 'EOF'
+          ---
+          title: DartLab
+          emoji: 📊
+          colorFrom: red
+          colorTo: orange
+          sdk: docker
+          app_port: 7860
+          pinned: true
+          license: mit
+          short_description: "DART + EDGAR disclosure analysis — try without install"
+          ---
+          EOF
+
+          cd hf-space
+          git config user.name "github-actions[bot]"
+          git config user.email "github-actions[bot]@users.noreply.github.com"
+          git add -A
+          git diff --cached --quiet || (git commit -m "sync from $(git -C .. describe --tags --always 2>/dev/null || echo 'latest')" && git push)

Dockerfile

@@ -0,0 +1,24 @@
+# HuggingFace Spaces — DartLab 데모
+# CPU free tier (16GB RAM), port 7860
+
+FROM python:3.12-slim
+
+WORKDIR /app
+
+# 시스템 의존성
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    build-essential \
+    && rm -rf /var/lib/apt/lists/*
+
+# dartlab 설치
+RUN pip install --no-cache-dir dartlab
+
+# 샘플 데이터 프리로드 스크립트
+COPY scripts/hfPreload.py scripts/hfPreload.py
+RUN python scripts/hfPreload.py
+
+# HF Spaces 기본 포트
+EXPOSE 7860
+
+# 서버 실행
+CMD ["python", "-m", "dartlab.server"]

landing/src/lib/brand.ts

@@ -9,6 +9,7 @@ export const brand = {
 	pypi: 'https://pypi.org/project/dartlab/',
 	coffee: 'https://buymeacoffee.com/eddmpython',
 	desktop: 'https://github.com/eddmpython/dartlab-desktop/releases/latest/download/DartLab.exe',
+	spaces: 'https://huggingface.co/spaces/eddmpython/dartlab',
 	author: 'eddmpython',
 
 	hfRepo: 'eddmpython/dartlab-data',

landing/src/lib/components/sections/Hero.svelte

@@ -3,7 +3,7 @@
 	import { brand } from '$lib/brand';
 	import { Button } from '$lib/components/ui/button';
 	import { Badge } from '$lib/components/ui/badge';
-	import { Download } from 'lucide-svelte';
+	import { Download, Globe } from 'lucide-svelte';
 </script>
 
 <section class="relative pt-32 pb-20 px-6 overflow-hidden">
@@ -45,13 +45,16 @@
 		</p>
 
 		<div class="flex flex-wrap items-center justify-center gap-3 mb-16">
-			<Button href={brand.desktop}>
+			<Button href={brand.spaces}>
+				<Globe class="w-4 h-4" />
+				Try Online
+			</Button>
+			<Button variant="secondary" href={brand.desktop}>
 				<Download class="w-4 h-4" />
 				Windows Download
 			</Button>
 			<Button variant="secondary" href="#install">pip / uv Install</Button>
 			<Button variant="secondary" href="{base}/docs/">Docs</Button>
-			<Button variant="secondary" href="{base}/docs/getting-started/quickstart">Quick Start</Button>
 		</div>
 
 		<div class="grid grid-cols-2 md:grid-cols-4 gap-3 max-w-3xl mx-auto">

landing/static/llms.txt

@@ -1,25 +1,55 @@
-# dartlab
+# DartLab — DART + EDGAR Disclosure Analysis Python Library
 
-> DART 전자공시 데이터를 활용한 한국 상장기업 재무 분석 Python 라이브러리.
+> Turn Korean DART and US SEC EDGAR filings into one structured company map.
+> 한국 DART 전자공시와 미국 SEC EDGAR 공시를 하나의 회사 맵으로 바꾸는 Python 라이브러리.
 
-## 설치
+DartLab parses corporate disclosure filings — annual reports, 10-K, 10-Q — into structured,
+comparable data. Financial statements (BS/IS/CF), 47 financial ratios, 7-area insight grades,
+narrative text, and structured reports are all accessible with a single stock code.
+Covers 2,700+ Korean listed companies and 970+ US companies.
 
-```
+## Install
+
+```bash
 pip install dartlab
+# or
+uv add dartlab
 ```
 
-## 빠른 시작
+## Quick Start
 
 ```python
 import dartlab
 
-c = dartlab.Company("005930")
-c.index                # 회사 구조 인덱스
-c.show("BS")           # topic payload 보기
-c.trace("dividend")    # source 추적
+# Korean company (DART)
+c = dartlab.Company("005930")       # Samsung Electronics
+c.index                              # company structure index
+c.show("BS")                         # balance sheet
+c.show("executiveCompensation")      # topic payload
+c.trace("dividend")                  # source provenance
+c.ratios                             # 47 financial ratios
+c.insights                           # 7-area A~F grades
+
+# US company (EDGAR)
+us = dartlab.Company("AAPL")         # Apple Inc.
+us.BS                                # balance sheet
+us.ratios                            # financial ratios
+us.sections                          # 10-K sections map
 ```
 
-## 주요 기능
+## Key Features
+
+- **Sections-first architecture**: Every company becomes a topic × period DataFrame
+- **Dual market**: DART (Korea) + EDGAR (US) with identical interface
+- **One stock code**: `dartlab.Company('005930')` or `dartlab.Company('AAPL')`
+- **Financial statements**: BS, IS, CF, CIS, SCE — XBRL-normalized, quarterly standalone
+- **47 financial ratios**: ROE, ROA, operating margin, debt ratio, PER, PBR, FCF, etc.
+- **7-area insight grades**: Performance, profitability, stability, cash flow, governance, risk, opportunity
+- **AI analysis**: `dartlab ask '삼성전자 분석해줘'` — natural language company analysis
+- **MCP server**: Expose company data as MCP tools for Claude Desktop, ChatGPT, Cursor
+- **329 topics per company**: From dividend policy to segment breakdown
+
+## Data Modules
 
 ### 시계열 재무제표
 
@@ -106,15 +136,19 @@ c.trace("dividend")    # source 추적
 - **sector** (섹터분류): WICS 11대 섹터 분류. 대분류/중분류 + 섹터별 파라미터.
 - **rank** (시장순위): 전체 시장 및 섹터 내 매출/자산/성장률 순위.
 
-## 분석 엔진
+## Analysis Engines
 
-- **섹터 분류**: WICS 11섹터 자동 분류 (오버라이드 → 키워드 → KSIC 3단계)
-- **인사이트 등급**: 7영역 A~F 등급 (실적, 수익성, 건전성, 현금흐름, 지배구조, 리스크, 기회)
-- **시장 순위**: 매출/자산/성장률 전체+섹터내 순위
-- **재무비율**: ROE, ROA, 영업이익률, 부채비율, PER, PBR, FCF 등 자동 계산
+- **Sector classification**: WICS 11 sectors (override → keyword → KSIC 3-stage)
+- **Insight grades**: 7-area A~F grades (performance, profitability, stability, cash flow, governance, risk, opportunity)
+- **Market rank**: Revenue/assets/growth ranking — overall + within sector
+- **Financial ratios**: ROE, ROA, operating margin, debt ratio, PER, PBR, FCF — auto-calculated
+- **Supply chain**: Disclosed supplier/customer relationship mapping
+- **ESG**: ESG disclosure extraction and scoring
+- **Event study**: Abnormal return around disclosure dates
 
-## 링크
+## Links
 
-- 문서: https://eddmpython.github.io/dartlab/docs/
+- Documentation: https://eddmpython.github.io/dartlab/docs/
 - GitHub: https://github.com/eddmpython/dartlab
 - PyPI: https://pypi.org/project/dartlab/
+- Demo: https://huggingface.co/spaces/eddmpython/dartlab

pyproject.toml

@@ -124,9 +124,12 @@ dartlab = "dartlab.cli.main:main"
 [project.entry-points."dartlab.plugins"]
 
 [project.urls]
-Homepage = "https://github.com/eddmpython/dartlab"
+Homepage = "https://eddmpython.github.io/dartlab/"
 Repository = "https://github.com/eddmpython/dartlab"
+Documentation = "https://eddmpython.github.io/dartlab/docs/"
 Issues = "https://github.com/eddmpython/dartlab/issues"
+Changelog = "https://eddmpython.github.io/dartlab/docs/changelog"
+Demo = "https://huggingface.co/spaces/eddmpython/dartlab"
 
 [build-system]
 requires = ["hatchling"]

scripts/generateSpec.py

@@ -17,7 +17,7 @@
 import sys
 import textwrap
 from pathlib import Path
-from typing import Optional, get_type_hints
+from typing import get_type_hints
 
 ROOT = Path(__file__).resolve().parent.parent
 sys.path.insert(0, str(ROOT / "src"))
@@ -256,28 +256,58 @@ def generateApiSpec() -> str:
 def generateLlmsTxt() -> str:
     """llms.txt 생성 — AI 크롤러용."""
     lines = [
-        "# dartlab",
+        "# DartLab — DART + EDGAR Disclosure Analysis Python Library",
         "",
-        "> DART 전자공시 데이터를 활용한 한국 상장기업 재무 분석 Python 라이브러리.",
+        "> Turn Korean DART and US SEC EDGAR filings into one structured company map.",
+        "> 한국 DART 전자공시와 미국 SEC EDGAR 공시를 하나의 회사 맵으로 바꾸는 Python 라이브러리.",
         "",
-        "## 설치",
+        "DartLab parses corporate disclosure filings — annual reports, 10-K, 10-Q — into structured,",
+        "comparable data. Financial statements (BS/IS/CF), 47 financial ratios, 7-area insight grades,",
+        "narrative text, and structured reports are all accessible with a single stock code.",
+        "Covers 2,700+ Korean listed companies and 970+ US companies.",
         "",
-        "```",
+        "## Install",
+        "",
+        "```bash",
         "pip install dartlab",
+        "# or",
+        "uv add dartlab",
         "```",
         "",
-        "## 빠른 시작",
+        "## Quick Start",
         "",
         "```python",
         "import dartlab",
         "",
-        'c = dartlab.Company("005930")',
-        "c.index                # 회사 구조 인덱스",
-        'c.show("BS")           # topic payload 보기',
-        'c.trace("dividend")    # source 추적',
+        "# Korean company (DART)",
+        'c = dartlab.Company("005930")       # Samsung Electronics',
+        "c.index                              # company structure index",
+        'c.show("BS")                         # balance sheet',
+        'c.show("executiveCompensation")      # topic payload',
+        'c.trace("dividend")                  # source provenance',
+        "c.ratios                             # 47 financial ratios",
+        "c.insights                           # 7-area A~F grades",
+        "",
+        "# US company (EDGAR)",
+        'us = dartlab.Company("AAPL")         # Apple Inc.',
+        "us.BS                                # balance sheet",
+        "us.ratios                            # financial ratios",
+        "us.sections                          # 10-K sections map",
         "```",
         "",
-        "## 주요 기능",
+        "## Key Features",
+        "",
+        "- **Sections-first architecture**: Every company becomes a topic × period DataFrame",
+        "- **Dual market**: DART (Korea) + EDGAR (US) with identical interface",
+        "- **One stock code**: `dartlab.Company('005930')` or `dartlab.Company('AAPL')`",
+        "- **Financial statements**: BS, IS, CF, CIS, SCE — XBRL-normalized, quarterly standalone",
+        "- **47 financial ratios**: ROE, ROA, operating margin, debt ratio, PER, PBR, FCF, etc.",
+        "- **7-area insight grades**: Performance, profitability, stability, cash flow, governance, risk, opportunity",
+        "- **AI analysis**: `dartlab ask '삼성전자 분석해줘'` — natural language company analysis",
+        "- **MCP server**: Expose company data as MCP tools for Claude Desktop, ChatGPT, Cursor",
+        "- **329 topics per company**: From dividend policy to segment breakdown",
+        "",
+        "## Data Modules",
         "",
     ]
 
@@ -291,18 +321,22 @@ def generateLlmsTxt() -> str:
 
     lines.extend(
         [
-            "## 분석 엔진",
+            "## Analysis Engines",
             "",
-            "- **섹터 분류**: WICS 11섹터 자동 분류 (오버라이드 → 키워드 → KSIC 3단계)",
-            "- **인사이트 등급**: 7영역 A~F 등급 (실적, 수익성, 건전성, 현금흐름, 지배구조, 리스크, 기회)",
-            "- **시장 순위**: 매출/자산/성장률 전체+섹터내 순위",
-            "- **재무비율**: ROE, ROA, 영업이익률, 부채비율, PER, PBR, FCF 등 자동 계산",
+            "- **Sector classification**: WICS 11 sectors (override → keyword → KSIC 3-stage)",
+            "- **Insight grades**: 7-area A~F grades (performance, profitability, stability, cash flow, governance, risk, opportunity)",
+            "- **Market rank**: Revenue/assets/growth ranking — overall + within sector",
+            "- **Financial ratios**: ROE, ROA, operating margin, debt ratio, PER, PBR, FCF — auto-calculated",
+            "- **Supply chain**: Disclosed supplier/customer relationship mapping",
+            "- **ESG**: ESG disclosure extraction and scoring",
+            "- **Event study**: Abnormal return around disclosure dates",
             "",
-            "## 링크",
+            "## Links",
             "",
-            "- 문서: https://eddmpython.github.io/dartlab/docs/",
+            "- Documentation: https://eddmpython.github.io/dartlab/docs/",
             "- GitHub: https://github.com/eddmpython/dartlab",
             "- PyPI: https://pypi.org/project/dartlab/",
+            "- Demo: https://huggingface.co/spaces/eddmpython/dartlab",
             "",
         ]
     )

scripts/hfPreload.py

@@ -0,0 +1,31 @@
+"""HuggingFace Spaces Docker 빌드 시 샘플 데이터 프리로드.
+
+삼성전자(005930)와 AAPL 데이터를 미리 다운로드하여
+cold start 시간을 줄인다.
+"""
+
+from __future__ import annotations
+
+import os
+import sys
+
+# Docker 빌드 환경에서는 dartlab이 이미 pip install된 상태
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), "..", "src"))
+
+SAMPLES = ["005930", "AAPL"]
+
+
+def main() -> None:
+    from dartlab.core.dataLoader import download
+
+    for code in SAMPLES:
+        print(f"  preloading {code}...")
+        try:
+            download(code)
+            print(f"  {code} done")
+        except Exception as e:  # noqa: BLE001
+            print(f"  {code} skipped: {e}")
+
+
+if __name__ == "__main__":
+    main()