- docker-compose.yml: timescaledb-ha (timescaledb 2.27 + vectorscale + pgvector + pgai) + backend (FastAPI, CUDA 12.1) + web (Next.js 14) - docker-compose.gpu.yml: GPU profile overlay for RTX 3070 Ti - build.bat: Windows bootstrap, auto-detects nvidia-smi and selects GPU/CPU compose - backend: Dockerfile, pyproject.toml, FastAPI skeleton with /health and /health/db - DB migration 001_init.sql: symbols (with trigram search), ohlcv_daily/1m (hypertables), macro_daily, trading_value_daily, news (vector embedding), predictions (with user_triggered flag for on-demand UX), prediction_outcomes, model_performance - web: Next.js 14 + Tailwind + lightweight-charts placeholder - README: KIS/DART/HuggingFace token issuance guides + 10 seed tickers + run instructions
66 lines
1.2 KiB
TOML
66 lines
1.2 KiB
TOML
[project]
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name = "stock_chart_site_backend"
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version = "0.0.1"
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description = "Stock chart + prediction backend (FastAPI + Chronos + LightGBM + KR-FinBERT)"
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requires-python = ">=3.11,<3.13"
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dependencies = [
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# web
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"fastapi==0.111.0",
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"uvicorn[standard]==0.30.0",
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"pydantic==2.7.1",
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"pydantic-settings==2.3.0",
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# db
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"sqlalchemy==2.0.30",
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"psycopg[binary]==3.1.19",
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"alembic==1.13.1",
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# data
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"pandas==2.2.2",
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"numpy==1.26.4",
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"pykrx==1.0.45",
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"yfinance==0.2.40",
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"feedparser==6.0.11",
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"requests==2.32.3",
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"httpx==0.27.0",
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"beautifulsoup4==4.12.3",
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"lxml==5.2.2",
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# ml
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"transformers==4.41.2",
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"tokenizers==0.19.1",
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"sentencepiece==0.2.0",
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"scikit-learn==1.5.0",
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"lightgbm==4.3.0",
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"ta==0.11.0",
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# scheduler
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"apscheduler==3.10.4",
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"pytz==2024.1",
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# utils
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"python-dotenv==1.0.1",
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"loguru==0.7.2",
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"tenacity==8.3.0",
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]
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[project.optional-dependencies]
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dev = [
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"pytest==8.2.1",
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"ruff==0.4.7",
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"mypy==1.10.0",
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]
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[build-system]
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requires = ["setuptools>=68"]
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build-backend = "setuptools.build_meta"
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[tool.setuptools.packages.find]
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where = ["."]
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include = ["app*"]
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[tool.ruff]
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line-length = 100
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target-version = "py311"
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