candle-annotator/services/ml/app
Marko Djordjevic 76cb49e908 Migrate MLflow backend to PostgreSQL and fix .env loading
- Add python-dotenv loading in main.py so DATABASE_URL is read from .env
  before db.py module initializes
- Add MLFLOW_TRACKING_URI to .env.example pointing to PostgreSQL
- Add python-dotenv>=1.0.0 to pyproject.toml dependencies
- Initialize MLflow schema in candle_annotator PostgreSQL database

MLflow server now starts without filesystem deprecation warnings and
with full job execution support.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-02-20 21:34:31 +01:00
..
__init__.py feat(ml): add database schema, config parser, and DVC setup 2026-02-15 12:08:53 +01:00
annotation_ingestion.py fix(training): use selected chart and include TA-Lib span sources 2026-02-18 23:21:23 +01:00
config.py feat(ml): add database schema, config parser, and DVC setup 2026-02-15 12:08:53 +01:00
data_access.py fix(training): use selected chart and include TA-Lib span sources 2026-02-18 23:21:23 +01:00
db.py Scope training run queries in FastAPI to filter by user ID (Task 14.3) 2026-02-20 18:38:18 +01:00
main.py Migrate MLflow backend to PostgreSQL and fix .env loading 2026-02-20 21:34:31 +01:00
patterns.py feat: add FastAPI pattern detection endpoints (Section 1) 2026-02-17 18:34:14 +01:00
preprocessing.py Fix inference feature mismatch with training metadata 2026-02-18 23:53:38 +01:00