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fix: call init_db() on ML service startup to create training_runs table

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Marko Djordjevic 2026-02-18 00:08:23 +01:00
parent d5fc4662e9
commit b4956f3fb9
1 changed files with 4 additions and 1 deletions
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5
services/ml/app/main.py
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@ -24,7 +24,7 @@ import mlflow.xgboost
from sqlalchemy import update as sa_update, desc from sqlalchemy import update as sa_update, desc
from app.config import load_config, PipelineConfig, get_default_config from app.config import load_config, PipelineConfig, get_default_config
from app.db import get_db, TrainingRun from app.db import get_db, TrainingRun, init_db
from app.preprocessing import preprocess_candles, extract_feature_columns from app.preprocessing import preprocess_candles, extract_feature_columns
from app.patterns import ( from app.patterns import (
TALIB_PATTERNS, TALIB_PATTERNS,
@ -311,6 +311,9 @@ async def startup_event():
""" """
logger.info("Starting inference service...") logger.info("Starting inference service...")
# Ensure training_runs table exists
init_db()
# Mark any stale "running" records as failed — they belong to a previous # Mark any stale "running" records as failed — they belong to a previous
# process and will never complete. # process and will never complete.
try: try: