cacddf5adf
- 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
47 lines
1010 B
Python
47 lines
1010 B
Python
from __future__ import annotations
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import logging
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from fastapi import FastAPI
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from fastapi.middleware.cors import CORSMiddleware
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from app.config import settings
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from app.db.connection import ping as db_ping
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logging.basicConfig(level=settings.log_level)
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logger = logging.getLogger(__name__)
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app = FastAPI(title="stock_chart_site", version="0.0.1")
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app.add_middleware(
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CORSMiddleware,
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allow_origins=["*"],
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allow_methods=["*"],
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allow_headers=["*"],
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)
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def _resolved_device() -> str:
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if settings.model_device != "auto":
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return settings.model_device
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try:
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import torch # noqa: WPS433
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return "cuda" if torch.cuda.is_available() else "cpu"
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except Exception: # noqa: BLE001
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return "cpu"
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@app.get("/health")
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def health() -> dict[str, object]:
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return {
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"ok": True,
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"device": _resolved_device(),
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"version": "0.0.1",
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}
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@app.get("/health/db")
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def health_db() -> dict[str, object]:
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return {"ok": True, **db_ping()}
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