From de3304397797f0e2b422e0ca5a1ad0ff9d7ca041 Mon Sep 17 00:00:00 2001 From: Ara5429 Date: Mon, 30 Mar 2026 00:22:12 +0900 Subject: [PATCH 1/3] feat: Week 5 jobs parse, cover-letter draft API, dashboard, Chroma query alignment - POST /api/jobs/parse and POST /api/cover-letter/draft with Writer graph - Dashboard: job parse, draft, embedding demo copy - GitHub embedding metadata source=github; user_assets OpenAI query_embeddings - Docs, tests, issue/week5.md summary Made-with: Cursor --- .gitignore | 3 + docs/API_GitHub_Spec.md | 127 +-- docs/API_Service_Spec.md | 1 + issue/week5.md | 67 ++ poetry.lock | 891 +++++++++--------- pyproject.toml | 2 +- src/api/cover_letter.py | 175 ++++ src/api/jobs.py | 294 ++++++ src/app/main.py | 4 + src/graphs/writer_graph/edge.py | 10 +- src/graphs/writer_graph/node.py | 279 ++++-- src/graphs/writer_graph/prompts.py | 46 + src/service/github_embedding/pipeline.py | 2 + src/service/rag/__init__.py | 3 +- src/service/rag/passed_samples.py | 167 ++++ src/service/rag/user_assets.py | 41 + src/web/dashboard.py | 176 +++- tests/api/test_cover_letter.py | 321 +++++++ tests/api/test_jobs_parse.py | 97 ++ .../graphs/writer_graph/test_writer_nodes.py | 363 +++++++ tests/service/rag/test_passed_samples.py | 80 ++ tests/service/rag/test_user_assets.py | 47 + 22 files changed, 2601 insertions(+), 595 deletions(-) create mode 100644 issue/week5.md create mode 100644 src/api/cover_letter.py create mode 100644 src/api/jobs.py create mode 100644 src/graphs/writer_graph/prompts.py create mode 100644 src/service/rag/passed_samples.py create mode 100644 tests/api/test_cover_letter.py create mode 100644 tests/api/test_jobs_parse.py create mode 100644 tests/graphs/writer_graph/test_writer_nodes.py create mode 100644 tests/service/rag/test_passed_samples.py diff --git a/.gitignore b/.gitignore index 9a2654b..8a36527 100644 --- a/.gitignore +++ b/.gitignore @@ -12,3 +12,6 @@ __pycache__/ # 로컬 SQLite / Chroma persist (개발·데모용, 커밋 제외) data/autofolio.db data/chroma/ + +# 로컬 쿠키/세션 덤프 (실수 커밋 방지) +cookies.txt diff --git a/docs/API_GitHub_Spec.md b/docs/API_GitHub_Spec.md index 05cf2a5..07921cf 100644 --- a/docs/API_GitHub_Spec.md +++ b/docs/API_GitHub_Spec.md @@ -394,19 +394,23 @@ curl -X GET "https://example.com/api/github/repos/123/commits?author=Ara5429&per --- -## 5. 임베딩 API +## 5. 임베딩 API (구현 기준) + +> **구현 파일:** `src/api/github.py` — `GitHubEmbeddingRequestBody`, `run_github_repo_embedding_job`. +> 과거 초안이었던 `paths[]` / `strategy` / `force_refresh` 필드는 **없다**. 아래가 SSoT다. ### 5.1 POST `/api/github/repos/{repo_id}/embedding` -- **설명:** 지정된 레포/경로에 대해 임베딩을 생성하고 VectorDB/DB에 저장한 뒤, 요약 정보를 반환. +- **설명:** 선택된 레포(`owner/name` 형식, URL 인코딩 시 `owner%2Fname`)에 대해 **코드 문서 id** 목록으로 Chroma `user_assets_{user_id}` 적재 및 SQLite `asset_hierarchy`의 folder/project 행 동기화를 수행한다. +- **전제:** `repo_id`는 **PUT /api/user/selected-repos** 로 저장된 레포여야 한다. 아니면 **403 FORBIDDEN** (`REPO_NOT_SELECTED`). #### 1. Request Syntax ```bash -curl -X POST "https://example.com/api/github/repos/123/embedding" \ - -H "Authorization: Bearer " \ +curl -X POST "https://example.com/api/github/repos/owner%2Frepo-a/embedding" \ + -H "Cookie: session=..." \ -H "Content-Type: application/json" \ - -d '{"paths":["src/","README.md"],"branch":"main","strategy":"code_and_docs_v1","force_refresh":false}' + -d '{"code_document_ids":[],"ref":"main","include_summaries":false}' ``` #### 2. Request Header @@ -417,115 +421,48 @@ curl -X POST "https://example.com/api/github/repos/123/embedding" \ | Authorization | `Bearer ` | Cookie 또는 Authorization 중 하나 필수 | | Content-Type | `application/json` | Y | -#### 3. Request Element +#### 3. Request Body (JSON) | 파라미터 | 타입 | 필수 | 설명 | |----------|------|------|------| -| repo_id | integer \| string | Y | Path. GitHub 레포 ID 또는 `"owner/name"` | -| paths | array<string> | Y | 비어 있지 않은 배열 | -| branch | string | N | default=레포 default_branch | -| strategy | string | N | default=code_and_docs_v1 | -| force_refresh | boolean | N | default=false | - -### paths[] 선택 레벨 규칙 - -| 선택 레벨 | UI 동작 | paths[] 예시 | -|----------|---------|-------------| -| 레포 전체 | 레포 체크박스 선택 | `["/"]` | -| 폴더 선택 | 폴더 펼치고 체크 | `["src/", "docs/"]` | -| 파일 개별 선택 | 파일 체크박스 | `["src/main.py", "README.md"]` | -| 혼합 | 폴더 + 개별 파일 | `["src/auth/", "README.md"]` | +| code_document_ids | array<string> | N | 임베딩할 코드 문서 id. Chroma id 규칙: ``{owner/repo}/{repo내 상대경로}`` (예: `owner/repo/src/app.py`). **비어 있으면** SQLite `asset_hierarchy`에서 해당 레포의 `type=code` id를 읽어 전부 사용한다. | +| ref | string | N | 브랜치 또는 SHA (GitHub Contents API 조회에 사용) | +| include_summaries | boolean | N | `true`이면 응답에 요약 텍스트 배열 포함(응답 크기 증가) | -**백엔드 처리 규칙:** +**권장 흐름 (대시보드와 동일):** -- `"/"` → 레포 전체 트리 순회 (루트부터 모든 파일 포함) -- `"src/"` (끝이 `/`) → 해당 폴더 하위 전체 재귀 포함 -- `"src/main.py"` (끝이 파일명) → 해당 파일만 -- **중복 경로 자동 제거:** 폴더 + 그 안의 파일 동시 선택 시 폴더 기준 합산 +1. **POST /api/user/asset-hierarchy/sync-from-assets** — `selected_repo_assets`의 code 경로를 `asset_hierarchy`에 반영 +2. **POST /api/github/repos/{owner%2Frepo}/embedding** — `code_document_ids: []` 로 DB에 있는 code id만으로 임베딩 + 또는 Files Tree에서 고른 파일로 `owner/repo/경로` id를 채워 **명시 모드**로 호출 -**전제 조건:** - -- 임베딩은 반드시 **selected_repos**에 등록된 레포에 대해서만 수행 가능. selected_repos에 없는 repo_id로 호출 시 **403 FORBIDDEN** 반환. +`code_document_ids`가 비어 있고, `asset_hierarchy`에 해당 레포의 code 행이 없으면 **400 BAD_REQUEST** (`NO_CODE_ASSETS_IN_HIERARCHY`). #### 4. Response -**200 OK (임베딩 생성 및 저장 완료)** - -```json -{ - "repo_id": 123, - "branch": "main", - "paths": ["src/", "README.md"], - "strategy": "code_and_docs_v1", - "status": "completed", - "embedding": { - "chunks_indexed": 128, - "dimensions": 1536, - "total_tokens": 45231, - "storage": { - "type": "vectordb", - "index_name": "autofolio_github_repo_123_main", - "last_updated_at": "2026-03-04T10:23:45Z" - } - }, - "hierarchy_nodes_created": 243 -} -``` - -**200 OK (캐시 히트, 이미 최신 상태)** +**200 OK** — 본문 예: ```json { - "repo_id": 123, - "branch": "main", - "paths": ["src/"], - "strategy": "code_and_docs_v1", - "status": "completed", - "embedding": { - "chunks_indexed": 128, - "dimensions": 1536, - "total_tokens": 45231, - "storage": { - "type": "vectordb", - "index_name": "autofolio_github_repo_123_main", - "last_updated_at": "2026-03-01T09:00:00Z" - }, - "cache_hit": true - }, - "hierarchy_nodes_created": 0 + "status": "ok", + "embedded": 12, + "ids": ["owner/repo/src/main.py", "owner/repo/README.md"] } ``` -| 필드 | 타입 | 설명 | -|------|------|------| -| repo_id | integer | GitHub 레포 ID | -| branch | string | 브랜치명 | -| paths | array<string> | 요청한 경로 목록 | -| strategy | string | 사용된 임베딩 전략 | -| status | string | completed 등 | -| embedding | object | chunks_indexed, dimensions, total_tokens, storage 등 | -| hierarchy_nodes_created | integer | asset_hierarchy 테이블에 생성된 노드 수 (code+folder+project 합산). 캐시 히트 시 0 | - -#### asset_hierarchy 연동 - -임베딩 생성 시 **asset_hierarchy** 테이블이 함께 갱신된다. +| 필드 | 설명 | +|------|------| +| status | `"ok"` | +| embedded | Chroma에 적재한 문서 수(코드·폴더·프로젝트 노드 합산에 가깝게 카운트) | +| ids | 저장된 문서 id 목록 | +| summaries | `include_summaries=true`일 때만. `{ id, type, path, summary }` 형태 배열 | -| API 호출 | DB 동작 | -|----------|---------| -| PUT /api/user/selected-repos | selected_repos upsert | -| POST /api/github/repos/{id}/embedding | asset_hierarchy 전체 재생성 + ChromaDB upsert | - -- `asset_hierarchy.id` = ChromaDB `user_assets_{user_id}`의 document id와 동일. -- RAPTOR bottom-up 순서: **code → folder → project** -- 재임베딩 시 해당 **selected_repo_id**의 asset_hierarchy 행 전부 삭제 후 재생성. +파이프라인은 코드 파일 → 폴더(bottom-up) → 프로젝트 루트 순으로 요약·임베딩한다. `asset_hierarchy`의 folder/project 행은 임베딩 후 **선택된 code_document_ids** 기준으로 동기화된다. | 상태코드 | error | 발생조건 | |----------|-------|----------| -| 400 | BAD_REQUEST | paths가 비어 있거나 배열이 아님 | +| 400 | BAD_REQUEST | 잘못된 repo_id, 또는 임베딩할 code id 없음 | | 401 | UNAUTHORIZED | 로그인 필요 | -| 403 | FORBIDDEN | 해당 repo_id가 selected_repos에 등록되지 않음 | -| 404 | NOT_FOUND | 레포 없음 | -| 409 | EMBEDDING_IN_PROGRESS | 해당 레포/브랜치에 대한 임베딩 작업이 이미 진행 중 | -| 502 | EMBEDDING_FAILED | 임베딩 생성 중 오류 | +| 403 | FORBIDDEN | 레포가 selected_repos에 없음 | +| 500 | INTERNAL_SERVER_ERROR | `EMBEDDING_FAILED` 등 서버 처리 실패 | > 공통 에러(400/401/403/404/500/502)는 공통 규칙 참고. diff --git a/docs/API_Service_Spec.md b/docs/API_Service_Spec.md index 5592e20..fd63ea8 100644 --- a/docs/API_Service_Spec.md +++ b/docs/API_Service_Spec.md @@ -94,6 +94,7 @@ curl -X POST "https://example.com/api/user/documents" \ ### 1.1 POST `/api/jobs/parse` +- **구현:** `src/api/jobs.py` — `manual`은 즉시 DB 저장, `url`은 HTTP 수집 후 `OPENAI_API_KEY`가 있으면 JSON 구조화, 없으면 본문 스니펫을 `duties` 등에 휴리스틱 저장. - **설명:** 채용공고 입력을 두 가지 방식으로 받아 **담당 업무 / 자격 요건 / 우대 사항 / 기업명 / 기업 인재상 / 포지션명** 6개 항목을 확보한 뒤 **jobs 테이블에 저장**하고 `job_id`를 반환한다. - **source_type=url:** `url` 필수. 서버가 해당 URL을 크롤링 후 LLM으로 파싱. url 기준으로 신규 저장하며, 항상 jobs에 한 건을 남긴다. 크롤링 실패 시 400 CRAWL_FAILED. - **source_type=manual:** url 없음. 사용자가 6개 항목 직접 입력. position_title, company_name 필수, 나머지 선택. 항상 신규 저장(UUID id, 중복 체크 없음). diff --git a/issue/week5.md b/issue/week5.md new file mode 100644 index 0000000..bcdbef4 --- /dev/null +++ b/issue/week5.md @@ -0,0 +1,67 @@ +# Week 5 작업 정리 + +## 개요 + +자기소개서 Writer(코드 RAG + 채용공고 맥락), 채용공고 파싱 API, 대시보드 연동, GitHub 임베딩·RAG 검색 일관성 수정을 포함한 한 주차 작업입니다. + +## API·백엔드 + +### 채용공고 저장 (parse) + +- **`POST /api/jobs/parse`**: SQLite `jobs` 테이블에 공고 저장 후 `job_id` 반환. +- **manual**: 본문 직접 입력. +- **url**: 페이지를 가져와 파싱; `OPENAI_API_KEY`가 있으면 구조화 보조. + +### 자소서 Draft (Writer) + +- **`POST /api/cover-letter/draft`**: GitHub 로그인 세션 필수. 선택 `job_id`로 `jobs` + `job_parsed` 맥락 로드. +- LangGraph Writer: `retrieve_samples` → `load_assets` → `generate_draft` → `self_consistency` → `format_output`. +- 구현: `src/api/cover_letter.py`, `src/graphs/writer_graph/` (노드, 엣지, 프롬프트). + +### 앱 등록 + +- `src/app/main.py`에 jobs·cover letter 라우터 등록. + +## GitHub 코드 임베딩·RAG + +### 데모 흐름 (대시보드) + +- `asset_hierarchy` ↔ `selected_repo_assets` 동기화, GitHub Contents API, (옵션) OpenAI 요약·임베딩, Chroma `user_assets_{user_id}`. +- 문서: `docs/API_GitHub_Spec.md` (임베딩 바디 등 실제 코드와 맞춤). + +### 버그 수정 (핵심) + +1. **`source` 메타데이터** + GitHub 파이프라인 `_normalize_metadata`에 `source: github` 추가. Chroma `where` 필터와 스키마 정합. + +2. **`load_assets` 필터** + 과거 문서에 `source`가 없을 수 있어 `retrieve_user_assets(..., source_filter=None)`로 조회. + +3. **임베딩 공간 불일치 (Draft 빈 응답 원인)** + - 적재: OpenAI `text-embedding-3-small`. + - 조회: `query_texts`만 쓰면 컬렉션 기본 임베더(MiniLM 등)가 사용되어 차원·공간이 달라짐. + - **해결**: `OPENAI_API_KEY`가 있을 때 STAR 쿼리를 동일 `OpenAIEmbedder`로 임베딩한 뒤 `query_embeddings`로 검색 (`src/service/rag/user_assets.py`). + +## 프론트·대시보드 + +- `src/web/dashboard.py`: Job parse 패널(`job_id` 자동 채움), Cover letter Draft 패널, GitHub 임베딩 안내 문구 등. + +## 의존성 + +- `pyproject.toml` / `poetry.lock`: 예) `httpx` 등 공고 URL fetch용. + +## 테스트 + +- `tests/api/test_cover_letter.py`, `tests/api/test_jobs_parse.py` +- `tests/service/rag/test_user_assets.py` (OpenAI 쿼리 경로·기존 STAR 쿼리) +- `tests/graphs/writer_graph/` 등 Writer 노드 +- 기준: 전체 pytest 통과(주차 마감 시점 기준). + +## 문서 + +- `docs/API_GitHub_Spec.md`, `docs/API_Service_Spec.md` 갱신. + +## 참고 + +- Draft 응답에 `error`가 있어도 HTTP 200에서 본문만 비는 경우가 있었음 → API 레이어에서 그래프 `error`를 노출하는 개선은 후속 과제로 남길 수 있음. +- `used_assets.github_repos`는 응답 스키마 상 플레이스홀더에 가까움. diff --git a/poetry.lock b/poetry.lock index 5914c37..065f6f6 100644 --- a/poetry.lock +++ b/poetry.lock @@ -39,13 +39,13 @@ files = [ [[package]] name = "anyio" -version = "4.12.1" +version = "4.13.0" description = "High-level concurrency and networking framework on top of asyncio or Trio" optional = false -python-versions = ">=3.9" +python-versions = ">=3.10" files = [ - {file = "anyio-4.12.1-py3-none-any.whl", hash = "sha256:d405828884fc140aa80a3c667b8beed277f1dfedec42ba031bd6ac3db606ab6c"}, - {file = "anyio-4.12.1.tar.gz", hash = "sha256:41cfcc3a4c85d3f05c932da7c26d0201ac36f72abd4435ba90d0464a3ffed703"}, + {file = "anyio-4.13.0-py3-none-any.whl", hash = "sha256:08b310f9e24a9594186fd75b4f73f4a4152069e3853f1ed8bfbf58369f4ad708"}, + {file = "anyio-4.13.0.tar.gz", hash = "sha256:334b70e641fd2221c1505b3890c69882fe4a2df910cba14d97019b90b24439dc"}, ] [package.dependencies] @@ -54,17 +54,17 @@ idna = ">=2.8" typing_extensions = {version = ">=4.5", markers = "python_version < \"3.13\""} [package.extras] -trio = ["trio (>=0.31.0)", "trio (>=0.32.0)"] +trio = ["trio (>=0.32.0)"] [[package]] name = "attrs" -version = "25.4.0" +version = "26.1.0" description = "Classes Without Boilerplate" optional = false python-versions = ">=3.9" files = [ - {file = "attrs-25.4.0-py3-none-any.whl", hash = "sha256:adcf7e2a1fb3b36ac48d97835bb6d8ade15b8dcce26aba8bf1d14847b57a3373"}, - {file = "attrs-25.4.0.tar.gz", hash = "sha256:16d5969b87f0859ef33a48b35d55ac1be6e42ae49d5e853b597db70c35c57e11"}, + {file = "attrs-26.1.0-py3-none-any.whl", hash = "sha256:c647aa4a12dfbad9333ca4e71fe62ddc36f4e63b2d260a37a8b83d2f043ac309"}, + {file = "attrs-26.1.0.tar.gz", hash = "sha256:d03ceb89cb322a8fd706d4fb91940737b6642aa36998fe130a9bc96c985eff32"}, ] [[package]] @@ -178,13 +178,13 @@ lxml = ["lxml"] [[package]] name = "build" -version = "1.4.0" +version = "1.4.2" description = "A simple, correct Python build frontend" optional = false python-versions = ">=3.9" files = [ - {file = "build-1.4.0-py3-none-any.whl", hash = "sha256:6a07c1b8eb6f2b311b96fcbdbce5dab5fe637ffda0fd83c9cac622e927501596"}, - {file = "build-1.4.0.tar.gz", hash = "sha256:f1b91b925aa322be454f8330c6fb48b465da993d1e7e7e6fa35027ec49f3c936"}, + {file = "build-1.4.2-py3-none-any.whl", hash = "sha256:7a4d8651ea877cb2a89458b1b198f2e69f536c95e89129dbf5d448045d60db88"}, + {file = "build-1.4.2.tar.gz", hash = "sha256:35b14e1ee329c186d3f08466003521ed7685ec15ecffc07e68d706090bf161d1"}, ] [package.dependencies] @@ -200,135 +200,151 @@ virtualenv = ["virtualenv (>=20.11)", "virtualenv (>=20.17)", "virtualenv (>=20. 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--git a/src/api/cover_letter.py b/src/api/cover_letter.py new file mode 100644 index 0000000..a431e08 --- /dev/null +++ b/src/api/cover_letter.py @@ -0,0 +1,175 @@ +""" +자소서 Draft API (Writer 그래프). + +POST /api/cover-letter/draft — 문항별 초안 생성 및 drafts 테이블 저장. +""" + +from __future__ import annotations + +import uuid +from datetime import datetime, timezone +from typing import Any + +import aiosqlite +from fastapi import APIRouter, Request +from fastapi.responses import JSONResponse +from pydantic import BaseModel, ConfigDict + +from src.db.sqlite.client import connect +from src.graphs.writer_graph import build_writer_graph + +router = APIRouter(prefix="/api/cover-letter", tags=["cover-letter"]) + + +def _error_response(status_code: int, error: str, message: str) -> JSONResponse: + return JSONResponse(status_code=status_code, content={"error": error, "message": message}) + + +class QuestionItem(BaseModel): + model_config = ConfigDict(extra="ignore") + + question_text: str + max_chars: int + + +class DraftRequest(BaseModel): + model_config = ConfigDict(extra="ignore") + + job_id: str | None = None + questions: list[QuestionItem] | None = None + + +async def fetch_job_context(job_id: str | None) -> tuple[dict[str, Any], str | None]: + """(Writer용 job_parsed, drafts FK용 job_id). jobs 행이 없으면 ({}, None).""" + if not job_id: + return {}, None + conn = await connect() + try: + cur = await conn.execute( + """ + SELECT id, company_name, company_values, position, duty, qualifications, preferred + FROM jobs + WHERE id = ? + """, + (job_id,), + ) + row = await cur.fetchone() + await cur.close() + if not row: + return {}, None + job_parsed = { + "company_name": row["company_name"], + "company_values": row["company_values"], + "position": row["position"], + "duty": row["duty"], + "qualifications": row["qualifications"], + "preferred": row["preferred"], + } + return job_parsed, row["id"] + finally: + await conn.close() + + +async def persist_draft_records(user_id: str, rows: list[dict[str, Any]]) -> list[dict[str, Any]]: + """drafts 테이블에 INSERT 하고 API 응답용 drafts 항목 목록을 반환한다.""" + conn = await connect() + try: + out: list[dict[str, Any]] = [] + for row in rows: + await conn.execute( + """ + INSERT INTO drafts ( + id, user_id, job_id, question_text, max_chars, answer, round, + created_at, updated_at + ) + VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?) + """, + ( + row["id"], + user_id, + row.get("job_id"), + row["question_text"], + row["max_chars"], + row["answer"], + row.get("round", 0), + row["created_at"], + row["updated_at"], + ), + ) + ans = row["answer"] or "" + out.append( + { + "draft_id": row["id"], + "question_text": row["question_text"], + "answer": ans, + "char_count": len(ans), + } + ) + await conn.commit() + return out + except aiosqlite.Error: + await conn.rollback() + raise + finally: + await conn.close() + + +@router.post("/draft", response_model=None) +async def create_cover_letter_draft(request: Request, body: DraftRequest) -> JSONResponse | dict[str, Any]: + user_id = request.session.get("user_id") + if not user_id: + return _error_response(401, "UNAUTHORIZED", "UNAUTHORIZED") + + if body.questions is None or len(body.questions) == 0: + return _error_response(400, "BAD_REQUEST", "QUESTIONS_REQUIRED") + + user_id = str(user_id) + req_job_id = body.job_id + job_parsed, fk_job_id = await fetch_job_context(req_job_id) + + graph = build_writer_graph() + answers: list[str] = [] + + for q in body.questions: + state: dict[str, Any] = { + "user_id": user_id, + "question": q.question_text, + "max_chars": q.max_chars, + "job_parsed": job_parsed, + "samples": [], + "assets": [], + } + result = await graph.ainvoke(state) + if result.get("error"): + answers.append("") + else: + draft_text = result.get("draft") + answers.append(draft_text if isinstance(draft_text, str) else "") + + now = datetime.now(timezone.utc).strftime("%Y-%m-%dT%H:%M:%SZ") + rows: list[dict[str, Any]] = [] + for q, ans in zip(body.questions, answers, strict=True): + rows.append( + { + "id": str(uuid.uuid4()), + "user_id": user_id, + "job_id": fk_job_id, + "question_text": q.question_text, + "max_chars": q.max_chars, + "answer": ans, + "round": 0, + "created_at": now, + "updated_at": now, + } + ) + + try: + drafts = await persist_draft_records(user_id, rows) + except aiosqlite.Error: + return _error_response(500, "INTERNAL_SERVER_ERROR", "DRAFT_PERSIST_FAILED") + + return { + "drafts": drafts, + "used_assets": {"github_repos": [], "accepted_essays_used": False}, + "created_at": now, + } diff --git a/src/api/jobs.py b/src/api/jobs.py new file mode 100644 index 0000000..be023e3 --- /dev/null +++ b/src/api/jobs.py @@ -0,0 +1,294 @@ +""" +채용공고 파싱 API — jobs 테이블 저장 후 job_id 반환. + +POST /api/jobs/parse — manual(직접 입력) 또는 url(크롤 + 선택적 LLM 구조화). +""" + +from __future__ import annotations + +import json +import os +import re +import uuid +from datetime import datetime, timezone +from typing import Any, Literal + +import aiosqlite +import httpx +from bs4 import BeautifulSoup +from fastapi import APIRouter, Request +from fastapi.responses import JSONResponse +from openai import AsyncOpenAI +from pydantic import BaseModel, ConfigDict, Field + +from src.db.sqlite.client import connect + +router = APIRouter(prefix="/api/jobs", tags=["jobs"]) + + +def _error_response(status_code: int, error: str, message: str) -> JSONResponse: + return JSONResponse(status_code=status_code, content={"error": error, "message": message}) + + +def _now_iso() -> str: + return datetime.now(timezone.utc).strftime("%Y-%m-%dT%H:%M:%SZ") + + +def _join_lines(items: list[str] | None) -> str | None: + if not items: + return None + lines = [str(x).strip() for x in items if x and str(x).strip()] + return "\n".join(lines) if lines else None + + +class JobsParseBody(BaseModel): + model_config = ConfigDict(extra="ignore") + + source_type: Literal["url", "manual"] + url: str | None = None + position_title: str | None = None + company_name: str | None = None + company_persona: str | None = None + duties: list[str] = Field(default_factory=list) + requirements: list[str] = Field(default_factory=list) + preferences: list[str] = Field(default_factory=list) + + +async def _insert_job_row( + *, + job_id: str, + url: str, + duty: str | None, + qualifications: str | None, + preferred: str | None, + company_name: str | None, + company_values: str | None, + position: str | None, +) -> None: + conn = await connect() + try: + await conn.execute( + """ + INSERT INTO jobs ( + id, url, duty, qualifications, preferred, + company_name, company_values, position, created_at + ) + VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?) + """, + ( + job_id, + url, + duty, + qualifications, + preferred, + company_name, + company_values, + position, + _now_iso(), + ), + ) + await conn.commit() + except aiosqlite.Error: + await conn.rollback() + raise + finally: + await conn.close() + + +async def _fetch_url_text(raw_url: str) -> tuple[str, str]: + """(plain_text, page_title). 실패 시 예외.""" + url = raw_url.strip() + if not url.startswith(("http://", "https://")): + url = "https://" + url + async with httpx.AsyncClient(follow_redirects=True, timeout=30.0) as client: + res = await client.get(url, headers={"User-Agent": "AutofolioJobBot/1.0"}) + res.raise_for_status() + html = res.text + soup = BeautifulSoup(html, "html.parser") + for tag in soup(["script", "style", "noscript"]): + tag.decompose() + title = (soup.title.string or "").strip() if soup.title else "" + text = soup.get_text(separator="\n", strip=True) + text = re.sub(r"\n{3,}", "\n\n", text) + return text, title + + +def _heuristic_from_url_text(text: str, title: str) -> dict[str, Any]: + snippet = (text or "")[:6000] + return { + "company_name": (title[:200] if title else "(제목 없음)"), + "position_title": "채용공고", + "company_persona": "", + "duties": [snippet] if snippet else [], + "requirements": [], + "preferences": [], + } + + +async def _llm_structure_job(text: str, url: str, title: str) -> dict[str, Any] | None: + key = os.getenv("OPENAI_API_KEY") + if not key: + return None + client = AsyncOpenAI(api_key=key) + payload = (text or "")[:20000] + msg = ( + f"page_title: {title}\nurl: {url}\n\nbody_text:\n{payload}" + ) + resp = await client.chat.completions.create( + model=os.getenv("OPENAI_JOB_PARSE_MODEL", "gpt-4o-mini"), + response_format={"type": "json_object"}, + messages=[ + { + "role": "system", + "content": ( + "You extract job posting fields from Korean or English text. " + "Return a single JSON object with keys: " + "company_name (string), position_title (string), " + "company_persona (string), " + "duties (array of short strings), " + "requirements (array of strings), " + "preferences (array of strings). " + "Use empty string or [] if unknown." + ), + }, + {"role": "user", "content": msg}, + ], + temperature=0.2, + ) + raw = (resp.choices[0].message.content or "").strip() + data = json.loads(raw) + return { + "company_name": str(data.get("company_name") or "").strip() or "(미상)", + "position_title": str(data.get("position_title") or "").strip() or "채용공고", + "company_persona": str(data.get("company_persona") or "").strip(), + "duties": [str(x).strip() for x in (data.get("duties") or []) if str(x).strip()], + "requirements": [str(x).strip() for x in (data.get("requirements") or []) if str(x).strip()], + "preferences": [str(x).strip() for x in (data.get("preferences") or []) if str(x).strip()], + } + + +def _response_payload( + *, + job_id: str, + source_type: str, + position_title: str, + company_name: str, + company_persona: str, + duties: list[str], + requirements: list[str], + preferences: list[str], +) -> dict[str, Any]: + return { + "job_id": job_id, + "source_type": source_type, + "position_title": position_title, + "company_name": company_name, + "company_persona": company_persona, + "duties": duties, + "requirements": requirements, + "preferences": preferences, + "created_at": _now_iso(), + } + + +@router.post("/parse", response_model=None) +async def parse_job(request: Request, body: JobsParseBody) -> JSONResponse | dict[str, Any]: + uid = request.session.get("user_id") + if not uid: + return _error_response(401, "UNAUTHORIZED", "UNAUTHORIZED") + + if body.source_type == "manual": + if not body.position_title or not str(body.position_title).strip(): + return _error_response(400, "BAD_REQUEST", "position_title is required for manual") + if not body.company_name or not str(body.company_name).strip(): + return _error_response(400, "BAD_REQUEST", "company_name is required for manual") + + job_id = str(uuid.uuid4()) + url = f"manual://{job_id}" + duty = _join_lines(body.duties) + qual = _join_lines(body.requirements) + pref = _join_lines(body.preferences) + persona = (body.company_persona or "").strip() or None + + try: + await _insert_job_row( + job_id=job_id, + url=url, + duty=duty, + qualifications=qual, + preferred=pref, + company_name=body.company_name.strip(), + company_values=persona, + position=body.position_title.strip(), + ) + except aiosqlite.Error: + return _error_response(500, "INTERNAL_SERVER_ERROR", "JOB_PERSIST_FAILED") + + return _response_payload( + job_id=job_id, + source_type="manual", + position_title=body.position_title.strip(), + company_name=body.company_name.strip(), + company_persona=persona or "", + duties=list(body.duties or []), + requirements=list(body.requirements or []), + preferences=list(body.preferences or []), + ) + + # url + if not body.url or not str(body.url).strip(): + return _error_response(400, "BAD_REQUEST", "url is required for source_type=url") + + try: + text, title = await _fetch_url_text(body.url) + except httpx.HTTPError as exc: + return _error_response( + 400, + "CRAWL_FAILED", + f"HTTP fetch failed: {type(exc).__name__}: {exc}", + ) + except Exception as exc: + return _error_response( + 400, + "CRAWL_FAILED", + f"Failed to read job page: {type(exc).__name__}: {exc}", + ) + + structured: dict[str, Any] | None = None + try: + structured = await _llm_structure_job(text, body.url.strip(), title) + except Exception: + structured = None + + if structured is None: + structured = _heuristic_from_url_text(text, title) + + job_id = str(uuid.uuid4()) + duty = _join_lines(structured.get("duties") or []) + qual = _join_lines(structured.get("requirements") or []) + pref = _join_lines(structured.get("preferences") or []) + + try: + await _insert_job_row( + job_id=job_id, + url=body.url.strip(), + duty=duty, + qualifications=qual, + preferred=pref, + company_name=structured["company_name"], + company_values=(structured.get("company_persona") or None), + position=structured["position_title"], + ) + except aiosqlite.Error: + return _error_response(500, "INTERNAL_SERVER_ERROR", "JOB_PERSIST_FAILED") + + return _response_payload( + job_id=job_id, + source_type="url", + position_title=structured["position_title"], + company_name=structured["company_name"], + company_persona=structured.get("company_persona") or "", + duties=list(structured.get("duties") or []), + requirements=list(structured.get("requirements") or []), + preferences=list(structured.get("preferences") or []), + ) diff --git a/src/app/main.py b/src/app/main.py index 4953cc2..644c159 100644 --- a/src/app/main.py +++ b/src/app/main.py @@ -13,6 +13,8 @@ from starlette.middleware.sessions import SessionMiddleware from src.api import portfolio_router +from src.api.cover_letter import router as cover_letter_router +from src.api.jobs import router as jobs_router from src.api.auth import router as auth_router from src.api.github import router as github_router from src.api.user_assets import router as user_assets_router @@ -44,6 +46,8 @@ def create_app() -> FastAPI: app.include_router(auth_router) app.include_router(portfolio_router) + app.include_router(jobs_router) + app.include_router(cover_letter_router) app.include_router(github_router) app.include_router(user_assets_router) diff --git a/src/graphs/writer_graph/edge.py b/src/graphs/writer_graph/edge.py index 28349c4..1ff7810 100644 --- a/src/graphs/writer_graph/edge.py +++ b/src/graphs/writer_graph/edge.py @@ -33,12 +33,12 @@ def after_load_assets(state: WriterState) -> str: def after_self_consistency(state: WriterState) -> str: """self_consistency 이후 분기. - - 통과 → format_output - - 실패 & draft_retry_count < MAX → generate_draft (피드백 프롬프트 반영 재생성) - - 실패 & draft_retry_count >= MAX → format_output (재시도 상한, 그대로 진행) + - is_hallucination False(환각 없음) → format_output + - is_hallucination True & draft_retry_count < MAX → generate_draft (피드백 반영 재생성) + - is_hallucination True & draft_retry_count >= MAX → format_output (재시도 상한) """ - passed = state.get("is_hallucination") - if passed: + has_hallucination = state.get("is_hallucination") + if not has_hallucination: return "format_output" retry = state.get("draft_retry_count") or 0 if retry < MAX_DRAFT_RETRIES: diff --git a/src/graphs/writer_graph/node.py b/src/graphs/writer_graph/node.py index 55bacde..8b86cde 100644 --- a/src/graphs/writer_graph/node.py +++ b/src/graphs/writer_graph/node.py @@ -1,65 +1,234 @@ -"""2번 그래프(Writer) 노드. 내부 로직은 TODO 주석으로만 표시.""" - -from .state import WriterState - - -def retrieve_samples(state: WriterState) -> dict: - """진입 시 검증 + 합격 자소서 검색 모듈 호출. - - 입력: question, max_chars, job_parsed (assets 불필요 — load_assets에서 이후 조회) - 출력: (통과) samples / (검증 실패만) error → END - """ - # TODO: question, max_chars 필수 검증. 없으면 error 설정 후 반환 - # TODO: 검증 통과 시 retrieve_passed_cover_letters(question, company_name, ...) 호출 - # TODO: samples 못 찾아도(빈 리스트/검색 모듈 에러) error 설정 안 함 → load_assets로 진행 - return {"samples": state.get("samples") or []} +"""2번 그래프(Writer) 노드.""" +from __future__ import annotations -def load_assets(state: WriterState) -> dict: - """유저 DB에서 에셋 조회. retrieve_samples → (통과) load_assets → generate_draft. +import json +import os +import re +from typing import Any - 입력: user_id - 출력: (통과) assets / (실패) error → END - """ - # TODO: user_id로 P1 API 또는 DB에서 에셋 조회. 문항/공고 기반 관련 에셋 선별 - # TODO: 조회 실패 시 error 설정 후 반환 - return {"assets": state.get("assets") or []} +from langchain_core.messages import HumanMessage, SystemMessage +from langchain_openai import ChatOpenAI +from src.service.rag import retrieve_passed_cover_letters, retrieve_user_assets -def generate_draft(state: WriterState) -> dict: - """LLM 초안 생성. 재진입 시 consistency_feedback 프롬프트 반영. - - 입력: assets, samples, question, job_parsed, (재진입) consistency_feedback - 출력: draft - """ - # TODO: assets + samples + question + job_parsed로 LLM 프롬프트 구성 - # TODO: 재진입 시 state.get("consistency_feedback")를 프롬프트에 포함 - # TODO: draft = llm.invoke(...) - return {"draft": state.get("draft") or "(초안 placeholder)"} - - -def self_consistency(state: WriterState) -> dict: - """환각 체크. 실패 시 consistency_feedback 기록, draft_retry_count 증가. +from .prompts import DRAFT_CONSISTENCY_SYSTEM_PROMPT, DRAFT_SYSTEM_PROMPT +from .state import WriterState - 입력: draft, assets, draft_retry_count - 출력: is_hallucination, (실패 시) consistency_feedback, draft_retry_count+1 - """ - # TODO: draft가 assets에 근거한지 검사. 없는 경험·지어낸 수치 → 실패 - # TODO: 실패 시 consistency_feedback에 문장/구간·근거 없는 내용 기록 - # TODO: draft_retry_count += 1 - return { - "is_hallucination": True, - "consistency_feedback": state.get("consistency_feedback") or {}, - "draft_retry_count": state.get("draft_retry_count") or 0, +DEFAULT_MODEL = os.getenv("OPENAI_MODEL", "gpt-4o-mini") + + +def _build_chat_openai(temperature: float) -> ChatOpenAI: + """ChatOpenAI JSON mode (portfolio_graph/node.py와 동일 패턴).""" + return ChatOpenAI( + model=DEFAULT_MODEL, + temperature=temperature, + api_key=os.getenv("OPENAI_API_KEY"), + model_kwargs={"response_format": {"type": "json_object"}}, + ) + + +def _question_missing(state: WriterState) -> bool: + q = state.get("question") + if q is None: + return True + if isinstance(q, str) and not q.strip(): + return True + return False + + +def _max_chars_missing(state: WriterState) -> bool: + return state.get("max_chars") is None + + +def _job_parsed_meta(job_parsed: dict | None) -> tuple[str | None, str | None, str | None]: + if not isinstance(job_parsed, dict): + return None, None, None + company = job_parsed.get("company_name") + position = job_parsed.get("position") + year = job_parsed.get("year") + if year is not None and not isinstance(year, str): + year = str(year) + if isinstance(company, str) and not company.strip(): + company = None + if isinstance(position, str) and not position.strip(): + position = None + if isinstance(year, str) and not year.strip(): + year = None + return ( + str(company) if company is not None else None, + str(position) if position is not None else None, + year, + ) + + +def _summarize_assets(assets: list[Any]) -> list[dict[str, Any]]: + out: list[dict[str, Any]] = [] + for item in assets or []: + if not isinstance(item, dict): + continue + out.append( + { + "id": item.get("id"), + "summary": item.get("document"), + "metadata": item.get("metadata"), + } + ) + return out + + +async def retrieve_samples(state: WriterState) -> dict: + """진입 시 검증 + 합격 자소서 검색 모듈 호출.""" + if _question_missing(state): + return {"error": "question is required"} + if _max_chars_missing(state): + return {"error": "max_chars is required"} + + job = state.get("job_parsed") if isinstance(state.get("job_parsed"), dict) else {} + company_name, position, year = _job_parsed_meta(job) + question = str(state.get("question", "")).strip() + + try: + samples = await retrieve_passed_cover_letters( + question=question, + company_name=company_name, + position=position, + year=year, + top_k=5, + ) + except Exception: + samples = [] + + return {"samples": samples} + + +async def load_assets(state: WriterState) -> dict: + """유저 DB에서 에셋 조회.""" + user_id = state.get("user_id") + if not user_id: + return {"error": "user_id is required"} + + try: + # user_assets_{user_id} 는 현재 GitHub 임베딩만 적재. 과거 문서는 source 메타가 없을 수 있어 + # source_filter 를 쓰면 0건이 되어 no_github_assets 가 나므로 필터 없이 조회한다. + assets = await retrieve_user_assets( + user_id=str(user_id), + source_filter=None, + type_filter=None, + top_k=20, + ) + except Exception as exc: + return {"error": f"retrieve_user_assets_failed: {type(exc).__name__}", "assets": []} + + if not assets: + return {"error": "no_github_assets", "assets": []} + + return {"assets": assets} + + +async def generate_draft(state: WriterState) -> dict: + """LLM 초안 생성.""" + llm = _build_chat_openai(temperature=0.2) + + assets = _summarize_assets(state.get("assets") or []) + user_payload: dict[str, Any] = { + "question": state.get("question"), + "max_chars": state.get("max_chars"), + "job_parsed": state.get("job_parsed") or {}, + "assets": assets, + "samples": state.get("samples") or [], + } + human_text = json.dumps(user_payload, ensure_ascii=False) + feedback = state.get("consistency_feedback") + if feedback: + human_text += ( + "\n\n다음 지적사항을 반영해 수정해줘: " + + ( + json.dumps(feedback, ensure_ascii=False) + if isinstance(feedback, (dict, list)) + else str(feedback) + ) + ) + + try: + response = await llm.ainvoke( + [ + SystemMessage(content=DRAFT_SYSTEM_PROMPT), + HumanMessage(content=human_text), + ] + ) + content = response.content if isinstance(response.content, str) else "{}" + parsed = json.loads(content) + if isinstance(parsed, dict): + draft = parsed.get("draft") + if isinstance(draft, str): + return {"draft": draft} + except Exception: + pass + + return {"draft": ""} + + +async def self_consistency(state: WriterState) -> dict: + """환각 체크.""" + llm = _build_chat_openai(temperature=0.0) + draft = state.get("draft") or "" + assets = _summarize_assets(state.get("assets") or []) + retry = state.get("draft_retry_count") or 0 + + user_payload = { + "draft": draft, + "assets": assets, } + try: + response = await llm.ainvoke( + [ + SystemMessage(content=DRAFT_CONSISTENCY_SYSTEM_PROMPT), + HumanMessage(content=json.dumps(user_payload, ensure_ascii=False)), + ] + ) + content = response.content if isinstance(response.content, str) else "{}" + parsed = json.loads(content) + if not isinstance(parsed, dict): + return { + "is_hallucination": False, + "consistency_feedback": {}, + "draft_retry_count": retry, + } + + is_hallucination = bool(parsed.get("is_hallucination", False)) + raw_fb = parsed.get("consistency_feedback") + if not isinstance(raw_fb, dict): + raw_fb = {} + + if not is_hallucination: + return { + "is_hallucination": False, + "consistency_feedback": {}, + "draft_retry_count": retry, + } + + return { + "is_hallucination": True, + "consistency_feedback": raw_fb, + "draft_retry_count": retry + 1, + } + except Exception: + return { + "is_hallucination": False, + "consistency_feedback": {}, + "draft_retry_count": retry, + } def format_output(state: WriterState) -> dict: - """글자수·형식 정리. max_chars 필수. - - 입력: draft, max_chars - 출력: draft (최종) - """ - # TODO: max_chars로 글자수 제한 - # TODO: 줄바꿈·불필요 공백 정리 - return {"draft": state.get("draft") or ""} + """글자수·형식 정리.""" + draft = state.get("draft") or "" + if state.get("max_chars") is not None: + mc = int(state["max_chars"]) + draft = draft[:mc] + draft = re.sub(r"\n\n+", "\n", draft) + draft = draft.strip() + else: + draft = draft.strip() + return {"draft": draft} diff --git a/src/graphs/writer_graph/prompts.py b/src/graphs/writer_graph/prompts.py new file mode 100644 index 0000000..b076e5e --- /dev/null +++ b/src/graphs/writer_graph/prompts.py @@ -0,0 +1,46 @@ +"""Writer 그래프 노드에서 사용하는 프롬프트 상수.""" + +DRAFT_SYSTEM_PROMPT = ( + "You are an expert in evidence-based Korean cover-letter (자기소개서) writing for job applications.\n" + "You write drafts that hiring managers can trust because every substantive claim is grounded " + "in the candidate's own materials.\n\n" + "## Rules\n" + "1. **Evidence-only**: Use ONLY facts, experiences, metrics, and technologies that appear in " + "the provided `assets`. Do NOT invent employers, projects, numbers, dates, awards, or skills " + "that are not supported by the assets.\n" + "2. **Inputs to honor**: The answer must directly address `question`, respect `max_chars` " + "(character budget for the final draft body), and reflect `job_parsed` when given — especially " + "company name (기업명) and stated values / talent philosophy (인재상) — without fabricating " + "details not present in `job_parsed` or `assets`.\n" + "3. **Samples**: Treat `samples` (passed cover-letter examples) as **style and structure " + "reference only**. Do NOT copy sentences verbatim or import facts from samples that are not " + "also backed by this candidate's `assets`.\n" + "4. **Language**: Write the draft body in **Korean**.\n" + "5. **Revision pass**: If `consistency_feedback` is provided (e.g. from a prior verification " + "step), you **must** revise the draft to fix every issue described there while still obeying " + "rules 1–4.\n\n" + "## Output format\n" + "Return ONLY valid JSON with the following structure — no markdown fences, no commentary, " + "no extra keys:\n" + '{"draft": "..."}' +) + +DRAFT_CONSISTENCY_SYSTEM_PROMPT = ( + "You are a strict verifier specialized in detecting hallucinations in Korean job-application " + "cover letters (자기소개서).\n" + "Your job is to compare the draft against the candidate's `assets` only.\n\n" + "## What to check\n" + "1. **Grounding**: Flag any experience, metric, date, role, project, technology, certification, " + "or achievement in `draft` that is **not clearly supported** by the provided `assets`.\n" + "2. **Claims**: Treat unsupported generalizations or strong assertions as issues if they imply " + "facts that do not appear in `assets`.\n\n" + "## Boolean semantics\n" + '"is_hallucination": true → at least one unsupported experience, number, or claim exists.\n' + '"is_hallucination": false → the draft is fully grounded in `assets` for substantive content.\n\n' + "## Output format\n" + "Return ONLY valid JSON — no markdown, no extra keys:\n" + '{"is_hallucination": true|false, ' + '"consistency_feedback": {"issues": [{"sentence": "...", "reason": "..."}]}}\n' + "If there are no issues, return an empty list: " + '{"is_hallucination": false, "consistency_feedback": {"issues": []}}' +) diff --git a/src/service/github_embedding/pipeline.py b/src/service/github_embedding/pipeline.py index b494917..d818060 100644 --- a/src/service/github_embedding/pipeline.py +++ b/src/service/github_embedding/pipeline.py @@ -81,8 +81,10 @@ def _normalize_metadata( asset_type: str, path_value: str, ) -> dict[str, str]: + # retrieve_user_assets(source_filter=["github"]) 및 메타 스키마와 맞춘다. return { "user_id": user_id, + "source": "github", "repo": repo_full_name, "ref": ref or "", "type": asset_type, diff --git a/src/service/rag/__init__.py b/src/service/rag/__init__.py index 9d04599..1748b1b 100644 --- a/src/service/rag/__init__.py +++ b/src/service/rag/__init__.py @@ -5,6 +5,7 @@ 재사용 가능한 검색 함수 제공 """ +from .passed_samples import retrieve_passed_cover_letters from .user_assets import retrieve_user_assets -__all__ = ["retrieve_user_assets"] +__all__ = ["retrieve_passed_cover_letters", "retrieve_user_assets"] diff --git a/src/service/rag/passed_samples.py b/src/service/rag/passed_samples.py new file mode 100644 index 0000000..980664e --- /dev/null +++ b/src/service/rag/passed_samples.py @@ -0,0 +1,167 @@ +""" +합격 자소서(문항 단위) ChromaDB 조회. + +스키마: docs/AUTOFOLIO_합격자소서_벡터DB_스키마.md +컬렉션: `passed_cover_letters` (없거나 비어 있으면 빈 리스트). +""" + +from __future__ import annotations + +import asyncio +from typing import Any + +from src.db.vector.chroma import get_chroma_client + +PASSED_COVER_LETTERS_COLLECTION = "passed_cover_letters" + + +def _strip_or_none(value: str | None) -> str | None: + if value is None: + return None + s = value.strip() + return s if s else None + + +def _build_query_text( + question: str, + company_name: str | None, + position: str | None, + year: str | None, +) -> str: + """임베딩 쿼리 문자열. company/position/year가 모두 있을 때만 전체 포맷.""" + q = (question or "").strip() + c = _strip_or_none(company_name) + p = _strip_or_none(position) + y = _strip_or_none(year) + if c and p and y: + return f"{c}의 {y}년 {p} 공고의 자기소개서 문항 1 : {q}" + return f"자기소개서 문항 1 : {q}" + + +def _build_where_clause( + company_name: str | None, + position: str | None, + year: str | None, +) -> dict[str, Any] | None: + """제공된 메타 필드에 대해서만 $eq 조건을 쌓고, 2개 이상이면 $and.""" + conditions: list[dict[str, Any]] = [] + c = _strip_or_none(company_name) + if c is not None: + conditions.append({"company": {"$eq": c}}) + p = _strip_or_none(position) + if p is not None: + conditions.append({"position": {"$eq": p}}) + y = _strip_or_none(year) + if y is not None: + conditions.append({"year": {"$eq": y}}) + + if not conditions: + return None + if len(conditions) == 1: + return conditions[0] + return {"$and": conditions} + + +def _normalize_passed_results(raw: dict[str, Any]) -> list[dict[str, Any]]: + """Chroma query 결과를 Writer용 dict 리스트로 변환.""" + ids = (raw.get("ids") or [[]])[0] + metas = (raw.get("metadatas") or [[]])[0] + dists = (raw.get("distances") or [[]])[0] + + out: list[dict[str, Any]] = [] + for idx, _ in enumerate(ids): + meta = metas[idx] if idx < len(metas) else None + if not isinstance(meta, dict): + meta = {} + + def _meta_str(key: str) -> str: + v = meta.get(key) + if v is None: + return "" + return str(v) + + dist = dists[idx] if idx < len(dists) else None + out.append( + { + "question": _meta_str("question"), + "answer": _meta_str("answer"), + "company": _meta_str("company"), + "position": _meta_str("position"), + "year": _meta_str("year"), + "source": _meta_str("source"), + "distance": dist, + } + ) + return out + + +def _retrieve_passed_cover_letters_sync( + question: str, + company_name: str | None, + position: str | None, + year: str | None, + top_k: int, +) -> list[dict[str, Any]]: + client = get_chroma_client() + try: + collection = client.get_collection(name=PASSED_COVER_LETTERS_COLLECTION) + except Exception: + return [] + + try: + n = collection.count() + except Exception: + return [] + + if n == 0: + return [] + + query_text = _build_query_text(question, company_name, position, year) + where = _build_where_clause(company_name, position, year) + + n_results = min(top_k, n) + if n_results <= 0: + return [] + + kwargs: dict[str, Any] = { + "query_texts": [query_text], + "n_results": n_results, + } + if where is not None: + kwargs["where"] = where + + try: + raw = collection.query(**kwargs) + except Exception: + return [] + + return _normalize_passed_results(raw) + + +async def retrieve_passed_cover_letters( + question: str, + company_name: str | None = None, + position: str | None = None, + year: str | None = None, + top_k: int = 5, +) -> list[dict]: + """합격 자소서 문항 청크를 유사도 검색한다. + + - 쿼리 텍스트는 스키마 문서와 동일한 포맷(또는 메타 미완 시 축약 포맷)으로 구성한다. + - ``company`` / ``position`` / ``year`` 메타는 값이 넘겨진 필드에 한해 where 필터로 적용한다. + - 컬렉션이 없거나 비어 있으면 ``[]`` (예외 없음). + + Returns: + ``[{question, answer, company, position, year, source, distance}, ...]`` + """ + if top_k <= 0: + raise ValueError("top_k must be greater than 0") + + return await asyncio.to_thread( + _retrieve_passed_cover_letters_sync, + question, + company_name, + position, + year, + top_k, + ) diff --git a/src/service/rag/user_assets.py b/src/service/rag/user_assets.py index 4eb8dc4..b0ad7a8 100644 --- a/src/service/rag/user_assets.py +++ b/src/service/rag/user_assets.py @@ -8,6 +8,7 @@ from __future__ import annotations import asyncio +import os from typing import Any from src.db.vector import get_user_asset_collection @@ -108,6 +109,24 @@ def _query_user_assets_sync( return _normalize_results(raw) +def _query_user_assets_sync_embedding( + user_id: str, + query_embedding: list[float], + where: dict[str, Any] | None, + top_k: int, +) -> list[dict]: + """GitHub 파이프라인이 OpenAI 임베딩으로 적재한 벡터와 동일 공간에서 검색한다.""" + collection = get_user_asset_collection(user_id) + kwargs: dict[str, Any] = { + "query_embeddings": [query_embedding], + "n_results": top_k, + } + if where is not None: + kwargs["where"] = where + raw = collection.query(**kwargs) + return _normalize_results(raw) + + def _merge_and_deduplicate(results_per_query: list[list[dict]], top_k: int) -> list[dict]: """다중 쿼리 결과를 id 기준으로 중복 제거 후 distance 오름차순으로 반환한다. @@ -153,6 +172,28 @@ async def retrieve_user_assets( where = _build_where_clause(source_filter, type_filter) + # GitHub 임베딩은 OpenAI API로 벡터를 넣는다. query_texts 는 컬렉션 기본 임베더(MiniLM 등)를 + # 쓰므로 차원·공간이 달라 검색이 비거나 실패할 수 있다. OPENAI_API_KEY 가 있으면 동일 모델로 + # 쿼리 벡터를 만든 뒤 query_embeddings 로 검색한다. + if os.getenv("OPENAI_API_KEY"): + from src.service.github_embedding.openai_embedder import OpenAIEmbedder + + embedder = OpenAIEmbedder() + embeddings = await embedder.embed(PORTFOLIO_STAR_QUERIES) + results_per_query = await asyncio.gather( + *[ + asyncio.to_thread( + _query_user_assets_sync_embedding, + user_id, + emb, + where, + top_k, + ) + for emb in embeddings + ] + ) + return _merge_and_deduplicate(list(results_per_query), top_k) + results_per_query = await asyncio.gather( *[ asyncio.to_thread(_query_user_assets_sync, user_id, query, where, top_k) diff --git a/src/web/dashboard.py b/src/web/dashboard.py index 8e4fbee..26e5562 100644 --- a/src/web/dashboard.py +++ b/src/web/dashboard.py @@ -39,7 +39,7 @@

Autofolio Dev Dashboard

-

OAuth · GitHub API · 선택 레포/assets · 코드 임베딩(Chroma) 개발용 화면입니다.

+

OAuth · GitHub API · 선택 레포/assets · 코드 임베딩(Chroma) · 채용공고 parse → job_id · 자소서 Draft 개발용 화면입니다.

@@ -165,6 +165,69 @@ 

     
 
+    

+      
Jobs 채용공고 저장 (parse)

+      

+        POST /api/jobs/parse로 SQLite jobs 테이블에 공고를 넣고 job_id를 받습니다.
+        성공 시 아래 자소서 Draft의 job_id 입력칸에 자동으로 채웁니다. 이후 POST /api/cover-letter/draft에 같은 id를 넘기면 공고 맥락이 붙습니다.
+      

+      

+        
+          
+        
+      

+      

+        


+          
+        

+        


+          
+        

+        


+          
+        

+        


+          
+        

+        


+          
+        

+        


+          
+        

+      

+      
+      
+      
응답

+      

+    

+
+    

+      
Writer 자소서 Draft

+      

+        GitHub 로그인 필수. 위에서 공고 저장으로 받은 job_id가 있으면 맥락이 붙습니다(비우면 범용 생성).
+        코드 RAG를 쓰려면 위 임베딩 단계를 먼저 완료하는 것이 좋습니다.
+      

+      

+        

+        
+      

+      

+        

+        
+      

+      

+        
+        
+      

+      
+      
응답

+      

+    

+
     
   
diff --git a/tests/api/test_cover_letter.py b/tests/api/test_cover_letter.py
index 7320f6f..c9b0cab 100644
--- a/tests/api/test_cover_letter.py
+++ b/tests/api/test_cover_letter.py
@@ -68,6 +68,20 @@ async def setup() -> None:
             """,
             ("u1", "testlogin", "tok", "2026-03-01", "2026-03-01"),
         )
+        await conn.execute(
+            """
+            INSERT INTO selected_repos (user_id, repo_full_name, created_at)
+            VALUES (?, ?, ?)
+            """,
+            ("u1", "owner/repo-a", "2026-03-01"),
+        )
+        await conn.execute(
+            """
+            INSERT INTO selected_repos (user_id, repo_full_name, created_at)
+            VALUES (?, ?, ?)
+            """,
+            ("u1", "owner/repo-b", "2026-03-01"),
+        )
         await conn.commit()
         await conn.close()
 
@@ -78,6 +92,10 @@ async def setup() -> None:
 @pytest.fixture
 def draft_client(monkeypatch: pytest.MonkeyPatch, tmp_db) -> TestClient:
     """create_app()에 등록된 cover-letter 라우터로 TestClient."""
+    monkeypatch.setattr(
+        "src.api.cover_letter.ensure_selected_repos_embedded",
+        AsyncMock(return_value=None),
+    )
     return TestClient(create_app())
 
 
@@ -110,7 +128,22 @@ def test_draft_missing_questions_field(draft_client: TestClient) -> None:
 def test_draft_success_single_question(draft_client: TestClient, monkeypatch: pytest.MonkeyPatch) -> None:
     class FakeGraph:
         async def ainvoke(self, state: dict) -> dict:
-            return {"draft": "테스트 초안"}
+            return {
+                "draft": "테스트 초안",
+                "assets": [
+                    {"id": "a", "metadata": {"repo": "owner/repo-a"}},
+                    {"id": "b", "metadata": {"repo": "owner/repo-a"}},
+                    {"id": "c", "metadata": {"repo": "owner/repo-b"}},
+                ],
+                "samples": [
+                    {
+                        "id": "s1",
+                        "company": "SK플래닛",
+                        "position": "신입 앱개발자",
+                        "question": "개발 역량을 보여줄 수 있는 프로젝트를 서술하세요.",
+                    }
+                ],
+            }
 
     monkeypatch.setattr("src.api.cover_letter.build_writer_graph", lambda: FakeGraph())
     monkeypatch.setattr(
@@ -146,6 +179,17 @@ async def ainvoke(self, state: dict) -> dict:
     assert d0.get("answer") == "테스트 초안"
     assert d0.get("char_count") == len("테스트 초안")
     assert "used_assets" in body
+    ua = body["used_assets"]
+    assert ua.get("accepted_essays_used") is True
+    essays = ua.get("accepted_essays") or []
+    assert len(essays) == 1
+    assert essays[0].get("company") == "SK플래닛"
+    assert essays[0].get("position") == "신입 앱개발자"
+    assert "개발 역량" in (essays[0].get("question") or "")
+    gh = ua.get("github_repos") or []
+    assert len(gh) == 2
+    names = sorted(x.get("full_name") for x in gh if isinstance(x, dict))
+    assert names == ["owner/repo-a", "owner/repo-b"]
     assert "created_at" in body
 
 
@@ -195,7 +239,7 @@ async def setup_job() -> None:
     class FakeGraph:
         async def ainvoke(self, state: dict) -> dict:
             captured["job_parsed"] = state.get("job_parsed")
-            return {"draft": "x"}
+            return {"draft": "x", "assets": [], "samples": []}
 
     monkeypatch.setattr("src.api.cover_letter.build_writer_graph", lambda: FakeGraph())
     monkeypatch.setattr(
@@ -222,6 +266,10 @@ async def ainvoke(self, state: dict) -> dict:
     )
     assert r.status_code == 200, r.text
     assert captured.get("job_parsed") == expected_job_parsed
+    ua0 = r.json()["used_assets"]
+    assert ua0["accepted_essays_used"] is False
+    assert ua0.get("accepted_essays") == []
+    assert ua0["github_repos"] == []
 
     captured.clear()
 
@@ -253,12 +301,18 @@ async def ainvoke(self, state: dict) -> dict:
 
 def test_draft_success_multiple_questions(draft_client: TestClient, monkeypatch: pytest.MonkeyPatch) -> None:
     calls: list[dict] = []
+    n = [0]
 
     class FakeGraph:
         async def ainvoke(self, state: dict) -> dict:
             calls.append(dict(state))
             q = state.get("question", "")
-            return {"draft": f"답-{q[:4]}"}
+            n[0] += 1
+            return {
+                "draft": f"답-{q[:4]}",
+                "assets": [{"metadata": {"repo": f"o/r-{n[0]}"}}],
+                "samples": [] if n[0] > 1 else [{"x": 1}],
+            }
 
     async def fake_persist(_user_id: str, rows: list[dict]) -> list[dict]:
         out: list[dict] = []
@@ -289,12 +343,22 @@ async def fake_persist(_user_id: str, rows: list[dict]) -> list[dict]:
     body = r.json()
     assert len(body["drafts"]) == 3
     assert len(calls) == 3
+    assert [c.get("primary_repo") for c in calls] == [
+        "owner/repo-a",
+        "owner/repo-b",
+        "owner/repo-a",
+    ]
+    ua = body["used_assets"]
+    assert ua["accepted_essays_used"] is True
+    assert ua.get("accepted_essays") == []
+    gh = sorted(x["full_name"] for x in ua["github_repos"])
+    assert gh == ["o/r-1", "o/r-2", "o/r-3"]
 
 
 def test_draft_graph_error_returns_partial(draft_client: TestClient, monkeypatch: pytest.MonkeyPatch) -> None:
     class FakeGraph:
         async def ainvoke(self, state: dict) -> dict:
-            return {"error": "no_github_assets", "draft": ""}
+            return {"error": "no_github_assets", "draft": "", "assets": [], "samples": []}
 
     monkeypatch.setattr("src.api.cover_letter.build_writer_graph", lambda: FakeGraph())
     monkeypatch.setattr(
@@ -319,3 +383,27 @@ async def ainvoke(self, state: dict) -> dict:
     assert r.status_code == 200, r.text
     body = r.json()
     assert body["drafts"][0].get("answer") == ""
+    assert body["used_assets"]["github_repos"] == []
+    assert body["used_assets"]["accepted_essays_used"] is False
+    assert body["used_assets"].get("accepted_essays") == []
+
+
+@pytest.mark.asyncio
+async def test_ensure_selected_repos_embedded_invokes_job_when_chroma_empty(
+    monkeypatch: pytest.MonkeyPatch, tmp_db
+) -> None:
+    monkeypatch.setattr("src.api.cover_letter._repo_has_embedding_docs", lambda _u, _r: False)
+    monkeypatch.setattr(
+        "src.api.cover_letter.fetch_code_document_ids_for_repo",
+        AsyncMock(return_value=["owner/repo-a/foo.py"]),
+    )
+    mock_job = AsyncMock(return_value={"embedded": 1})
+    monkeypatch.setattr("src.api.cover_letter.run_github_repo_embedding_job", mock_job)
+
+    from src.api.cover_letter import ensure_selected_repos_embedded
+
+    await ensure_selected_repos_embedded("u1", ["owner/repo-a"])
+    mock_job.assert_awaited_once()
+    assert mock_job.await_args.kwargs["user_id"] == "u1"
+    assert mock_job.await_args.kwargs["repo_full_name"] == "owner/repo-a"
+    assert mock_job.await_args.kwargs["code_document_ids"] == ["owner/repo-a/foo.py"]
diff --git a/tests/graphs/writer_graph/test_writer_nodes.py b/tests/graphs/writer_graph/test_writer_nodes.py
index bb68389..e80f794 100644
--- a/tests/graphs/writer_graph/test_writer_nodes.py
+++ b/tests/graphs/writer_graph/test_writer_nodes.py
@@ -12,6 +12,7 @@
 
 import inspect
 import json
+from typing import Any
 from unittest.mock import AsyncMock, MagicMock
 
 import pytest
@@ -128,6 +129,12 @@ async def test_retrieve_samples_empty_result_no_error(monkeypatch):
 
 @pytest.mark.asyncio
 async def test_load_assets_missing_user_id(monkeypatch):
+    monkeypatch.setattr(
+        writer_node,
+        "get_selected_repos",
+        AsyncMock(side_effect=AssertionError("should not call get_selected_repos")),
+        raising=False,
+    )
     monkeypatch.setattr(
         writer_node,
         "retrieve_user_assets",
@@ -142,8 +149,36 @@ async def test_load_assets_missing_user_id(monkeypatch):
     assert "user_id" in str(result["error"]).lower()
 
 
+@pytest.mark.asyncio
+async def test_load_assets_no_selected_repos(monkeypatch):
+    monkeypatch.setattr(
+        writer_node,
+        "get_selected_repos",
+        AsyncMock(return_value=[]),
+        raising=False,
+    )
+    monkeypatch.setattr(
+        writer_node,
+        "retrieve_user_assets",
+        AsyncMock(side_effect=AssertionError("should not call retrieve_user_assets")),
+        raising=False,
+    )
+
+    state = {"user_id": "u1", "question": "Q", "max_chars": 100}
+    result = await _call_node(writer_node.load_assets, state)
+
+    assert result.get("error") == "no_selected_repos"
+    assert result.get("assets") == []
+
+
 @pytest.mark.asyncio
 async def test_load_assets_empty_result_sets_error(monkeypatch):
+    monkeypatch.setattr(
+        writer_node,
+        "get_selected_repos",
+        AsyncMock(return_value=["owner/r1"]),
+        raising=False,
+    )
     monkeypatch.setattr(
         writer_node,
         "retrieve_user_assets",
@@ -168,10 +203,17 @@ async def test_load_assets_success(monkeypatch):
     assets_out = [
         {"id": "a1", "document": "요약1", "metadata": {"type": "code"}},
     ]
+    mock_retrieve = AsyncMock(return_value=assets_out)
+    monkeypatch.setattr(
+        writer_node,
+        "get_selected_repos",
+        AsyncMock(return_value=["owner/repo"]),
+        raising=False,
+    )
     monkeypatch.setattr(
         writer_node,
         "retrieve_user_assets",
-        AsyncMock(return_value=assets_out),
+        mock_retrieve,
         raising=False,
     )
 
@@ -185,6 +227,91 @@ async def test_load_assets_success(monkeypatch):
 
     assert not result.get("error")
     assert result.get("assets") == assets_out
+    mock_retrieve.assert_awaited_once_with(
+        user_id="u1",
+        source_filter=None,
+        type_filter=None,
+        repo_filter=["owner/repo"],
+        top_k=20,
+    )
+
+
+@pytest.mark.asyncio
+async def test_load_assets_primary_repo_merges_primary_and_supplement(monkeypatch):
+    """primary_repo: 최대 15 + 다른 레포당 최대 5, id 중복 제거, 총 20."""
+    calls: list[dict[str, Any]] = []
+
+    async def fake_retrieve(**kwargs: Any) -> list[dict[str, Any]]:
+        calls.append(kwargs)
+        rf = kwargs.get("repo_filter") or []
+        top_k = kwargs.get("top_k", 0)
+        if rf == ["p/a"]:
+            return [{"id": f"a{i}", "document": f"p{i}", "metadata": {"repo": "p/a"}} for i in range(min(15, top_k))]
+        if rf == ["p/b"]:
+            return [{"id": f"b{i}", "document": f"s{i}", "metadata": {"repo": "p/b"}} for i in range(min(5, top_k))]
+        return []
+
+    monkeypatch.setattr(
+        writer_node,
+        "get_selected_repos",
+        AsyncMock(return_value=["p/a", "p/b"]),
+        raising=False,
+    )
+    monkeypatch.setattr(
+        writer_node,
+        "retrieve_user_assets",
+        fake_retrieve,
+        raising=False,
+    )
+
+    state = {
+        "user_id": "u1",
+        "primary_repo": "p/a",
+        "question": "Q",
+        "max_chars": 100,
+    }
+    result = await _call_node(writer_node.load_assets, state)
+
+    assert not result.get("error")
+    assets = result.get("assets") or []
+    assert len(assets) == 20
+    assert calls[0]["repo_filter"] == ["p/a"] and calls[0]["top_k"] == 15
+    assert calls[1]["repo_filter"] == ["p/b"] and calls[1]["top_k"] == 5
+
+
+@pytest.mark.asyncio
+async def test_load_assets_primary_repo_empty_falls_back_to_all_repos(monkeypatch):
+    async def fake_retrieve(**kwargs: Any) -> list[dict[str, Any]]:
+        rf = kwargs.get("repo_filter") or []
+        if rf == ["p/x"]:
+            return []
+        if rf == ["p/x", "p/y"]:
+            return [{"id": "z1", "document": "d", "metadata": {"repo": "p/y"}}]
+        return []
+
+    monkeypatch.setattr(
+        writer_node,
+        "get_selected_repos",
+        AsyncMock(return_value=["p/x", "p/y"]),
+        raising=False,
+    )
+    monkeypatch.setattr(
+        writer_node,
+        "retrieve_user_assets",
+        fake_retrieve,
+        raising=False,
+    )
+
+    state = {
+        "user_id": "u1",
+        "primary_repo": "p/x",
+        "question": "Q",
+        "max_chars": 100,
+    }
+    result = await _call_node(writer_node.load_assets, state)
+
+    assert not result.get("error")
+    assert (result.get("assets") or []) == [{"id": "z1", "document": "d", "metadata": {"repo": "p/y"}}]
 
 
 # ---------------------------------------------------------------------------
diff --git a/tests/service/rag/test_passed_samples.py b/tests/service/rag/test_passed_samples.py
index 2d6eba7..05cb6d8 100644
--- a/tests/service/rag/test_passed_samples.py
+++ b/tests/service/rag/test_passed_samples.py
@@ -45,8 +45,10 @@ def test_build_where_none_when_all_missing() -> None:
     assert _build_where_clause(None, None, None) is None
 
 
-def test_build_where_single_field() -> None:
-    assert _build_where_clause("ACME", None, None) == {"company": {"$eq": "ACME"}}
+def test_build_where_none_when_only_one_or_two_fields() -> None:
+    assert _build_where_clause("ACME", None, None) is None
+    assert _build_where_clause("ACME", "백엔드", None) is None
+    assert _build_where_clause(None, "백엔드", "2024") is None
 
 
 def test_build_where_and_three_fields() -> None:
diff --git a/tests/service/rag/test_user_assets.py b/tests/service/rag/test_user_assets.py
index d4f8508..8285d1f 100644
--- a/tests/service/rag/test_user_assets.py
+++ b/tests/service/rag/test_user_assets.py
@@ -183,6 +183,44 @@ async def test_retrieve_user_assets_builds_where_clause(monkeypatch):
         }
 
 
+@pytest.mark.asyncio
+async def test_retrieve_user_assets_builds_where_clause_with_repo_filter(monkeypatch):
+    fake = _make_fake_query_sync([])
+    monkeypatch.setattr("src.service.rag.user_assets._query_user_assets_sync", fake)
+
+    await retrieve_user_assets(
+        user_id="u1",
+        source_filter=["github"],
+        type_filter=None,
+        repo_filter=["a/b", "c/d"],
+        top_k=3,
+    )
+
+    for call in fake.calls:
+        assert call["where"] == {
+            "$and": [
+                {"source": {"$in": ["github"]}},
+                {"repo": {"$in": ["a/b", "c/d"]}},
+            ]
+        }
+
+
+@pytest.mark.asyncio
+async def test_retrieve_user_assets_empty_repo_filter_returns_empty(monkeypatch):
+    called = []
+
+    def fake_sync(*args, **kwargs):
+        called.append(1)
+        return []
+
+    monkeypatch.setattr("src.service.rag.user_assets._query_user_assets_sync", fake_sync)
+
+    result = await retrieve_user_assets(user_id="u1", repo_filter=[], top_k=5)
+
+    assert result == []
+    assert called == []
+
+
 def test_portfolio_star_query_backward_compat():
     """PORTFOLIO_STAR_QUERY 상수가 삭제되지 않고 유지되는지 확인한다."""
     assert isinstance(PORTFOLIO_STAR_QUERY, str)
diff --git a/week-issues/week5.md b/week-issues/week5.md
new file mode 100644
index 0000000..8c9c05a
--- /dev/null
+++ b/week-issues/week5.md
@@ -0,0 +1,155 @@
+# Week 5 작업 정리
+
+> PR 본문에 그대로 붙여 넣을 수 있도록 요약·이슈·파일 목록까지 한 파일에 모았습니다.
+
+---
+
+## PR 제목 (예시)
+
+```
+Week 5: Jobs parse, Cover letter Draft, RAG/Chroma 정합, 대시보드·GitHub 임베딩 UX
+```
+
+---
+
+## Summary (PR 본문용)
+
+- **채용공고 저장**: `POST /api/jobs/parse` — SQLite `jobs`에 저장 후 `job_id` 반환 (manual / url).
+- **자소서 Draft (Writer)**: `POST /api/cover-letter/draft` — 세션 필수, 선택 `job_id`로 공고 맥락 로드, LangGraph Writer 파이프라인.
+- **RAG / Chroma 정합**: GitHub 임베딩 메타 `source: github`, `load_assets`에서 구 문서 호환, **임베딩 공간 불일치** 해결(OpenAI 임베딩으로 `query_embeddings` 검색).
+- **대시보드 (`src/web/dashboard.py`)**: Job parse UI, Writer Draft UI, **레포 카드 탭(파일 선택 / 파일 보기 / 커밋)**, 카드 단위 히스토리 동기화·임베딩, **경로 인코딩 이슈** 대응, **페이지 로드 시 Chroma 임베딩 뱃지 동기화**.
+- **백엔드**: `GET /api/user/embedding-status` — 선택 레포별 Chroma `user_assets_{user_id}`에 `repo` 메타 존재 여부로 embedded 여부 반환.
+
+---
+
+## API·백엔드
+
+### 채용공고 저장 (parse)
+
+- **`POST /api/jobs/parse`**: SQLite `jobs` 테이블에 공고 저장 후 `job_id` 반환.
+- **manual**: 본문 직접 입력.
+- **url**: 페이지를 가져와 파싱; `OPENAI_API_KEY`가 있으면 구조화 보조.
+
+### 자소서 Draft (Writer)
+
+- **`POST /api/cover-letter/draft`**: GitHub 로그인 세션 필수. 선택 `job_id`로 `jobs` + `job_parsed` 맥락 로드.
+- LangGraph Writer: `retrieve_samples` → `load_assets` → `generate_draft` → `self_consistency` → `format_output`.
+- 구현: `src/api/cover_letter.py`, `src/graphs/writer_graph/` (노드, 엣지, 프롬프트).
+
+### 앱 등록
+
+- `src/app/main.py`에 jobs·cover letter 라우터 등록.
+
+### GitHub 임베딩 상태 (신규)
+
+- **`GET /api/user/embedding-status`** (`src/api/github.py`)
+  - 인증: 세션 `user_id` 필수.
+  - `selected_repos` 목록의 각 `full_name`에 대해 Chroma 컬렉션 `user_assets_{user_id}`에서  
+    `collection.get(where={"repo": {"$eq": full_name}}, limit=1)` — `ids`가 있으면 embedded.
+  - 응답: `{ "status": { "": true | false, ... } }`.
+
+---
+
+## GitHub 코드 임베딩·RAG
+
+### 데모 흐름 (대시보드)
+
+- `asset_hierarchy` ↔ `selected_repo_assets` 동기화, GitHub Contents API, (옵션) OpenAI 요약·임베딩, Chroma `user_assets_{user_id}`.
+- 문서: `docs/API_GitHub_Spec.md` (임베딩 바디 등 실제 코드와 맞춤).
+
+### 버그 수정 (핵심)
+
+1. **`source` 메타데이터**  
+   GitHub 파이프라인 `_normalize_metadata`에 `source: github` 추가. Chroma `where` 필터와 스키마 정합.
+
+2. **`load_assets` 필터**  
+   과거 문서에 `source`가 없을 수 있어 `retrieve_user_assets(..., source_filter=None)`로 조회.
+
+3. **임베딩 공간 불일치 (Draft 빈 응답 원인)**  
+   - 적재: OpenAI `text-embedding-3-small`.  
+   - 조회: `query_texts`만 쓰면 컬렉션 기본 임베더(MiniLM 등)가 사용되어 차원·공간이 달라짐.  
+   - **해결**: `OPENAI_API_KEY`가 있을 때 STAR 쿼리를 동일 `OpenAIEmbedder`로 임베딩한 뒤 `query_embeddings`로 검색 (`src/service/rag/user_assets.py`).
+
+---
+
+## 프론트·대시보드 (`src/web/dashboard.py`)
+
+### 공통
+
+- Job parse 패널 (`job_id` 자동 채움), Cover letter Draft 패널, GitHub 임베딩 안내 문구.
+
+### 레포 카드 (임베딩 데모 그리드) — 상세
+
+- **탭 3개**: `[파일 선택] [파일 보기] [커밋]` — `repoCardMap.activeTab` (기본 `'files'`).
+- **파일 선택**: 파일 트리 체크박스, 파일 선택 저장, **히스토리 → SQLite** (`sync-from-assets`), **임베딩** (카드 단건: PUT assets → sync → POST embedding; 상단 `embedRef` / `include_summaries`와 동일 규칙).
+- **파일 보기**: `selectedAssetKeys` 중 `code:` 경로만 드롭다운 — 선택 시 `GET .../contents?path=...&encoding=raw`, 카드 내 `
` 표시. 카드별 `ref`는 비우면 쿼리 미전송(기본 브랜치).
+- **커밋**: `author`(비우면 서버에서 로그인 유저), `per_page`(기본 10), 커밋 조회 — 상위 10건을 `sha(7) · message · date · files_changed` 형태로 표시.
+- **에러**: fetch 실패 시 `alert` 대신 카드 내 에러 영역에 `접근 실패: ...` 형식.
+
+### 경로 인코딩 (FastAPI `{repo_id:path}` 호환)
+
+- **문제**: `encodeURIComponent(full_name)` 시 `owner/repo` → `owner%2Frepo`가 되어 FastAPI가 path로 인식하지 못해 404 / fetch 실패.
+- **해결**: 임베딩·파일·내용·커밋 요청 URL의 경로 구간에는 `encodeURIComponent(full_name)` 대신  
+  `full_name.replace(/ /g, '%20')`만 적용(슬래시 유지).  
+  Query(`path`, `ref`, `author` 등)는 기존처럼 `encodeURIComponent` 유지.
+
+### 임베딩 뱃지 동기화 (페이지 새로고침)
+
+- `loadMe()` → `loadSelectedReposUI()` 완료 후 **`GET /api/user/embedding-status`** 호출.
+- 응답 `status`로 `embeddingStatusCache` 갱신 후 **`renderAllRepoCards()`** 재호출 → ✅/⬜ 뱃지가 Chroma 실제 상태와 일치.
+
+### 기타 (raw string)
+
+- `dashboard.py`는 Python raw string이라 JS 문자열 이스케이프 주의(줄바꿈 등).
+
+---
+
+## 구현·이슈 해결 요약 (타임라인식)
+
+| 이슈 | 원인 | 해결 |
+|------|------|------|
+| `%2F`로 인코딩된 레포 경로 | `full_name`을 `encodeURIComponent` → 슬래시가 `%2F` | 경로에는 슬래시 유지, 공백만 `%20` |
+| 탭/기능 분산 | 단일 패널에 기능 몰림 | 탭 3개 + `activeTab` 상태 |
+| 뱃지와 실제 Chroma 불일치 | 세션 내 캐시만 갱신, 새로고침 시 초기화 | `GET /api/user/embedding-status` + 캐시 + 재렌더 |
+| raw string 내 JS `\n` | `\\n` vs `\n` 혼동 | 커밋 목록 등 실제 줄바꿈에 맞게 `.join('\n')` 정리 |
+
+---
+
+## 의존성
+
+- `pyproject.toml` / `poetry.lock`: 예) `httpx` 등 공고 URL fetch용.
+
+---
+
+## 테스트
+
+- `tests/api/test_cover_letter.py`, `tests/api/test_jobs_parse.py`
+- `tests/service/rag/test_user_assets.py` (OpenAI 쿼리 경로·기존 STAR 쿼리)
+- `tests/graphs/writer_graph/` 등 Writer 노드
+- 기준: 전체 pytest 통과(주차 마감 시점 기준).
+
+---
+
+## 문서
+
+- `docs/API_GitHub_Spec.md`, `docs/API_Service_Spec.md` 갱신.
+
+---
+
+## 참고·후속
+
+- Draft 응답에 `error`가 있어도 HTTP 200에서 본문만 비는 경우가 있었음 → API 레이어에서 그래프 `error`를 노출하는 개선은 후속 과제로 남길 수 있음.
+- `used_assets.github_repos`는 응답 스키마 상 플레이스홀더에 가까움.
+- `GET /api/user/embedding-status`에 대한 단위/API 테스트 추가는 선택 과제.
+
+---
+
+## 변경 파일 참고 (PR 리뷰용 체크리스트)
+
+- **API / 서비스**: `src/api/github.py`, `src/api/jobs.py`, `src/api/cover_letter.py`, `src/service/rag/user_assets.py`, `src/service/rag/passed_samples.py`, …
+- **Writer 그래프**: `src/graphs/writer_graph/node.py`, `prompts.py`, `state.py`, …
+- **대시보드**: `src/web/dashboard.py`
+- **테스트**: `tests/api/`, `tests/service/rag/`, `tests/graphs/writer_graph/`, …
+- **스크립트(선택)**: `scripts/load_passed_cover_letters.py`
+
+(정확한 diff는 `git diff main...week5` 또는 PR Files changed 탭 참고.)

From ff1874890adf17351688a5b5764a6ce6f1cadc2e Mon Sep 17 00:00:00 2001
From: Ara5429 
Date: Wed, 1 Apr 2026 11:18:23 +0900
Subject: [PATCH 3/3] fix(ci): noqa E402 for path bootstrap imports in
 load_passed_cover_letters script

Made-with: Cursor
---
 scripts/load_passed_cover_letters.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/scripts/load_passed_cover_letters.py b/scripts/load_passed_cover_letters.py
index df541c3..d236cb2 100644
--- a/scripts/load_passed_cover_letters.py
+++ b/scripts/load_passed_cover_letters.py
@@ -20,10 +20,10 @@
 if str(ROOT) not in sys.path:
     sys.path.insert(0, str(ROOT))
 
-from dotenv import load_dotenv
+from dotenv import load_dotenv  # noqa: E402
 
-from src.db.vector.chroma import get_chroma_client
-from src.service.rag.passed_samples import PASSED_COVER_LETTERS_COLLECTION
+from src.db.vector.chroma import get_chroma_client  # noqa: E402
+from src.service.rag.passed_samples import PASSED_COVER_LETTERS_COLLECTION  # noqa: E402
 
 load_dotenv(ROOT / ".env")