Update app.py

app.py

@@ -1,151 +1,24 @@
-#!/usr/bin/env python3
-"""
-repo_to_space_auto.py
----------------------
-자동으로 Git 레포를 Hugging Face Gradio Space로 배포.
-필요 환경변수:
-  BAPI_TOKEN      : Brave Search API Key
-  FRIENDLI_TOKEN  : Friendli Dedicated Endpoint Token
-CLI 인자:
-  --repo_url <URL>  : 원본 GitHub/GitLab 등 공개 레포 URL
-  --hf_token <TOK>  : 쓰기 권한 Hugging Face Access Token
-옵션:
-  --private         : 비공개 Space 생성
-  --hardware <tier> : 예) 't4-medium' GPU 인스턴스 지정
-"""
-import os, sys, json, argparse, subprocess, tempfile, textwrap, requests, shutil
-from pathlib import Path
-import git  # GitPython
-from huggingface_hub import HfApi, login
-
-# ---------- Brave Search 헬퍼 ---------- #
-def brave_search_repo(repo_url: str, count: int = 5) -> list[dict]:
-    api_key = os.getenv("BAPI_TOKEN")
-    if not api_key:
-        raise RuntimeError("환경변수 BAPI_TOKEN이 설정돼 있지 않습니다.")
-    headers = {"X-Subscription-Token": api_key, "Accept": "application/json"}
-    params  = {"q": f'site:github.com "{repo_url}"', "count": count, "search_lang": "en"}
-    resp = requests.get(
-        "https://api.search.brave.com/res/v1/web/search",
-        headers=headers, params=params, timeout=10
-    )
-    resp.raise_for_status()
-    return resp.json().get("web", {}).get("results", [])
-
-# ---------- Friendli LLM 헬퍼 ---------- #
-def friendli_generate_scaffold(context: str) -> dict:
-    token = os.getenv("FRIENDLI_TOKEN")
-    if not token:
-        raise RuntimeError("환경변수 FRIENDLI_TOKEN이 설정돼 있지 않습니다.")
-    payload = {
-        "model": "dep89a2fld32mcm",
-        "messages": [
-            {
-                "role": "system",
-                "content": (
-                    "You are an expert Hugging Face Space architect. "
-                    "Given repository context, output JSON with keys "
-                    "`app_py`, `requirements_txt`, `need_docker` (bool), "
-                    "`dockerfile` (if needed) and `summary`."
-                ),
-            },
-            {"role": "user", "content": context},
-        ],
-        "max_tokens": 16384,
-        "top_p": 0.8,
-        "stream": False,
-    }
-    headers = {
-        "Authorization": f"Bearer {token}",
-        "Content-Type": "application/json",
-    }
-    r = requests.post(
-        "https://api.friendli.ai/dedicated/v1/chat/completions",
-        json=payload, headers=headers, timeout=120
-    )
-    r.raise_for_status()
-    return json.loads(r.json()["choices"][0]["message"]["content"])
-
-# ---------- 메인 배포 로직 ---------- #
-def deploy(repo_url: str, hf_token: str, private=False, hardware=None) -> str:
-    """레포를 Gradio Space로 배포하고 Space URL 반환."""
-    login(hf_token)
-    api   = HfApi(token=hf_token)
-    user  = api.whoami()["name"]
-    space = f"{user}/{Path(repo_url).stem.lower().replace('.', '-')}"
-    api.create_repo(
-        repo_id=space,
-        repo_type="space",
-        space_sdk="gradio",
-        private=private,
-        exist_ok=True,
-        hardware=hardware,
-    )
-
-    with tempfile.TemporaryDirectory() as work:
-        # 1) Brave 메타데이터
-        brave_meta = brave_search_repo(repo_url)
-
-        # 2) 원본 레포 클론
-        src = Path(work) / "src"
-        git.Repo.clone_from(repo_url, src)
-
-        readme = ""
-        readme_path = src / "README.md"
-        if readme_path.exists():
-            readme = readme_path.read_text(encoding="utf-8", errors="ignore")[:4000]
-
-        tree_out = subprocess.run(
-            ["bash", "-lc", f"tree -L 2 {src} | head -n 40"],
-            text=True, capture_output=True
-        ).stdout
-
-        context = textwrap.dedent(f"""
-        ## Brave meta
-        {json.dumps(brave_meta, ensure_ascii=False, indent=2)}
-
-        ## Repository tree (depth 2)
-        {tree_out}
-
-        ## README (first 4 kB)
-        {readme}
-        """)
-
-        # 3) Friendli 스캐폴드 생성
-        scaffold = friendli_generate_scaffold(context)
-
-        # 4) Space 레포 클론 & 파일 쓰기
-        dst = Path(work) / "space"
-        api.clone_repo(space, local_dir=dst)
-
-        (dst / "app.py").write_text(scaffold["app_py"], encoding="utf-8")
-        (dst / "requirements.txt").write_text(scaffold["requirements_txt"], encoding="utf-8")
-        if scaffold.get("need_docker"):
-            (dst / "Dockerfile").write_text(scaffold["dockerfile"], encoding="utf-8")
-        (dst / "README.md").write_text(scaffold["summary"], encoding="utf-8")
-
-        # 5) 커밋 & 푸시
-        subprocess.run(["git", "-C", dst, "add", "."], check=True)
-        subprocess.run(["git", "-C", dst, "commit", "-m", "Initial auto-deploy"], check=True)
-        subprocess.run(["git", "-C", dst, "push"], check=True)
-
-    return f"https://huggingface.co/spaces/{space}"
-
-# ---------- CLI 엔트리 ---------- #
-def main():
-    p = argparse.ArgumentParser(description="Git 레포를 Hugging Face Gradio Space로 자동 배포")
-    p.add_argument("--repo_url", required=True, help="원본 Git 레포지토리 URL")
-    p.add_argument("--hf_token", required=True, help="쓰기 권한 Hugging Face 토큰")
-    p.add_argument("--private", action="store_true", help="비공개 Space 생성")
-    p.add_argument("--hardware", default=None, help="예: 't4-medium'")
-    args = p.parse_args()
-
+import gradio as gr
+import os
+from repo_to_space_auto import deploy   # 같은 디렉터리에 파일이 있을 때 import 가능
+
+def launch(repo_url, hf_token, private):
+    # 환경변수 토큰 자동 주입(선택 사항)
+    if hf_token:
+        os.environ["HF_TOKEN"] = hf_token
     try:
-        url = deploy(args.repo_url, args.hf_token, args.private, args.hardware)
-        print(f"✅  배포 성공: {url}")
+        link = deploy(repo_url, hf_token, private=private)
+        return f"### ✅ Space 생성 완료\n\n[{link}]({link})"
     except Exception as e:
-        print(f"❌  배포 실패: {e}", file=sys.stderr)
-        sys.exit(1)
+        return f"### ❌ 오류: {e}"
+
+with gr.Blocks(title="HF Space Auto-Deployer") as demo:
+    gr.Markdown("## 🔄 Git 레포 → Hugging Face Gradio Space 자동 배포")
+    repo_in   = gr.Textbox(label="Repository URL")
+    token_in  = gr.Textbox(label="HF Write Token", type="password")
+    priv_in   = gr.Checkbox(label="Private Space", value=False)
+    out_md    = gr.Markdown()
+    gr.Button("Deploy").click(fn=launch, inputs=[repo_in, token_in, priv_in], outputs=out_md)
 
 if __name__ == "__main__":
-    main()
+    demo.launch()