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T-REC learner libs

Project description

TREC Learner

For production config, set ENV to production

How to Run

  1. Install requeriments

    • python3 -m venv .venv
    • source ./.venv/bin/activate
    • pip install -r requirements.txt
  2. Config parameters

    • cp .env.example .env
    • cp pytest.ini.example pytest.ini
    • fill .env and pytest.ini
  3. 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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