OpenChart
Claude·Codex와 함께하는 무료 데스크톱 차트 도구. 알림 설정·차트 움직임 분석·데이터 제공자 선택
개인 계정의 공개 저장소 소유자는 GitHub로 로그인해 운영자를 확인하고 소개를 직접 관리할 수 있습니다. 관리자 승인은 필요하지 않습니다.
로그인한 뒤 확인 파일을 만들어 이 저장소의 기본 브랜치에 30분 안에 커밋해 주세요. 다른 브랜치나 포크의 파일은 인정하지 않습니다. 파일을 올린 뒤 아래에서 확인하면 관리자 승인 없이 관리할 수 있습니다. 자격을 유지하려면 파일을 남겨 두세요.
로그인이 필요하면 로그인 화면으로 이동합니다. 로그인 후 이곳으로 돌아와 원하는 확인 버튼을 다시 눌러 주세요.
프로젝트 폴더에서 /nomorevibe verify를 실행하면 소유권을 확인하고 소개를 직접 관리할 수 있습니다.
1분 만에 확인하기메이커가 쓴 소개는 위의 한 줄이 전부입니다. 더 자세한 내용은 저장소 README에서 읽을 수 있습니다. 저장소 README ↗
README 전체를 불러오는 중입니다.
README 전문 보기 ↗Django + React app for exploring SEC EDGAR company data and FRED macro series, with AI-assisted summaries.
Fredgar AI (FRED + EDGAR, with AI) is a Django + Django REST Framework backend with a Vite/React UI for SEC EDGAR company data and optional FRED macro series, with AI-assisted interpretation and summaries. A weekly GitHub Pages build publishes a static, no-login mirror of the warehouse at bamr87.github.io/fredgar-ai.
sec_edgar app), cached DB-first to respect SEC fair-access limitspublic_data app, needs FRED_API_KEY)/api/v1/ built with Django REST Framework, with an OpenAPI schema and Swagger UIfrontend/generate_static_site) and an auditable enrichment pipeline for customer/vendor lists (enrich_*)Clone bamr87/fredgar-ai, then from the repo root (Python 3.12+, Node 20+):
# install
python3 -m venv .venv && source .venv/bin/activate
pip install -r requirements.txt -r requirements-dev.txt
cp src/.env.example src/.env # set USER_AGENT_EMAIL (SEC requires it)
# run the API on http://127.0.0.1:8000/api/v1/
(cd src && python manage.py migrate && python manage.py runserver)
# run the UI on http://127.0.0.1:5173 (proxies /api to :8000)
(cd frontend && npm ci && npm run dev)
# test and lint (from the repo root)
pytest -q
ruff check src tests
(cd src && python manage.py makemigrations --check --dry-run)
(cd frontend && npm run lint && npm run build)
The legacy /api/ path mirrors the same routes. Set VITE_API_BASE to point the UI at another API; see frontend/README.md.
sec_edgar (direct SEC APIs), public_data (FRED), Celery + Redis for async sync jobsfrontend/DATABASE_URL for PostgreSQLSee src/.env.example. Important:
USER_AGENT_EMAIL: SEC requires a descriptive User-Agent identifying you.FRED_API_KEY: needed for sync_series_bundle / FRED observations.DJANGO_SECRET_KEY: set a strong value when DJANGO_DEBUG=false.Typical flows, from src/:
cd src
python manage.py sync_submissions --ticker AAPL
python manage.py sync_company_facts --ticker AAPL
python manage.py sync_derived_metrics --ticker AAPL
python manage.py ingest_htm --url 'https://www.sec.gov/Archives/edgar/data/.../file.htm' --ticker AAPL
python manage.py generate_static_site --ticker AAPL --output ../site # static "Wikipedia" site
python manage.py publish_static_site --output ../site # sync the default cohort from SEC + render (the GitHub Pages build)
python manage.py refresh_series_bundles # register + FRED-sync all series bundles
python manage.py sync_series_bundle --slug core # or sync one bundle by slug (needs FRED_API_KEY)
The same sync actions are on the API, for example POST /api/v1/companies/{id}/sync-submissions/. Every route and command is listed in the generated docs/reference/, and docs/api-and-cli.md explains how they fit together. The static site renders offline HTML — one page per company with statements, derived metrics, filings and facts, each with copy and CSV/JSON downloads — and .github/workflows/pages.yml publishes it weekly; see docs/static-site.md.
Series bundles are JSON under src/public_data/bundles/. A small CRM-style sample lives in data/samples/companies-sample.csv; large exports go under the gitignored data/local/ (see data/README.md).
From the repo root, PostgreSQL + the API on port 8000, with ./data mounted for reference JSON and HTM artifacts:
docker compose up -d --build
curl -s http://127.0.0.1:8000/api/v1/health/
docker compose --profile dev up -d --build # + Vite dev UI on :5173, proxying /api to the API container
docker compose --profile prod up -d --build # + static UI behind nginx on :8080, same-origin /api
docker compose --profile ci run --rm test # CI-style checks against Postgres
Optional env (shell or a .env next to docker-compose.yml): DJANGO_SECRET_KEY, USER_AGENT_EMAIL, DJANGO_DEBUG, CORS_ALLOWED_ORIGINS. The container scripts are described in docker/README.md. A single-image build without Compose also works: docker build -t fredgar-ai . then docker run -p 8000:8000 -e [email protected] fredgar-ai.
docs/README.md — the index of every document in the repo.docs/architecture.md — apps, data flow, DB-first SEC caching.docs/api-and-cli.md — how the REST API and manage.py commands fit together, with the generated route and command reference.PRD.md — product vision and roadmap (its scope table separates shipped from planned).src/config/ — Django settings and URLssrc/warehouse/ — every model: Company, Filing, Fact, DerivedMetric, peers, CRM staging, enrichmentsrc/sec_edgar/ — SEC client, HTM parser, ingest + sync servicessrc/public_data/ — external series catalog + FRED syncsrc/enrichment/ — the claim-based enrichment frameworksrc/api/v1/ — versioned REST APIfrontend/ — the Vite/React UItests/ — pytest + pytest-djangodocs/ — topic docs, ADRs and the generated referenceBuild, test and lint commands are in Quick start; make all runs the blocking CI checks (lint, migrations, tests with the coverage gate). .github/workflows/ci.yml runs Ruff, migration checks, manage.py check, pytest (SQLite and PostgreSQL) and the frontend build. After changing a route, a view docstring or a command, regenerate the reference with python3 tools/gen_reference.py --write. Agents and contributors: start with AGENTS.md.
Contributions are welcome via pull request. Use Conventional Commits and keep the CI checks green. See CONTRIBUTING.md for the workflow; AI agents start with AGENTS.md.
Notable changes are recorded in CHANGELOG.md, written by release-please (docs/releasing.md). Tagged versions are on the releases page.
Released under the MIT License.
Part of the bamr87 portfolio — browse every project on Amr's GitHub profile.