Message Stream Classifier

A websocket client that processes messages from a socket and tries to dentable conversations and categorize them as possible calendar events

High level Information flow

Running With Docker

• setup .env file with cp .env.example .env and set the WS_SOCK variable, this is the websocket that gets ingested.
• setup docker if you don't have it yet
• run sh build_and_run.sh
  • what it does
    • creates model (this is where the model gets stored) and results (the output will be generated here) folder
    • it checks if you have the model files if not downloads them
    • run docker build
    • run docker run command with the required attached volumes
    • execute the client.py in docker, this will start processing the stream

Running with manual setup / seeting up for development

• setup the .env file with the WS_SOCK variable
• setup uv https://docs.astral.sh/uv/getting-started/installation/
• create model/bert_classifier_v1 and results folder
• download the model files from
  • config.json
  • tensors
  • training_args
• run uv run ingest

running tests

• after setting up uv, you can run uv run pytest