T-REC learner libs
Project description
TREC Learner
For production config, set ENV to production
How to Run
-
Install requeriments
python3 -m venv .venvsource ./.venv/bin/activatepip install -r requirements.txt
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Config parameters
cp .env.example .envcp pytest.ini.example pytest.ini- fill .env and pytest.ini
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Run learner
./run.sh
How to Setup
All application variables are exposed in src/config.py. Container variables are exposed in .env:
-
Learner Options:
Option Description LEARNER_DAYS_INTERVAL Learner interval in days LEARNER_ROOT_MODEL_DIR Temporary root dir used during trainning LEARNER_MODEL_DIR Temporary dir used store model files -
Connection Options:
Option Description MONGODB_URI Mongo URI (without database name) MONGODB_DATABASE Mongo database with PLM data MONGODB_COLLECTION Mongo collection with issue-document data MINIO_HOST MinIO host (without http://) MINIO_ACCESS_KEY MinIO Key MINIO_SECRET_KEY MinIO Secret MINIO_RECOMMENDER_BUCKET MinIO recommender bucket -
Scheduler Options:
Option Description JOB_FREQUENCY Frequency to run job (seconds interval for dev mode) JOB_FREQUENCY Frequency to run job (hour of day for production mode)
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