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Trubrics

A Python client for tracking and analyzing events and LLM interactions with Trubrics.

Overview

Trubrics is a Python client that provides event tracking capabilities with a focus on LLM (Large Language Model) interactions. It is fast and non-blocking, meaning there will be no performance hits to your LLM app. It features an efficient queuing system with automatic background flushing of events to the Trubrics API.

Installation

pip install trubrics

Usage

Setup

Get your project API key from settings in Trubrics. This is a POST only API key.

from trubrics import Trubrics

client = Trubrics(api_key="your-api-key")

Tracking Events

# Track a simple event
client.track(
    user_id="user123",
    event="button_click",
    properties={"button_type": "submit"},
)

# Track LLM interactions
client.track_llm(
    user_id="user123",
    prompt="What is the capital of France?",
    assistant_id="gpt-4",
    generation="The capital of France is Paris.",
    properties={
        "$thread_id": "your-thread-id",  # special trubrics property to group an interaction by conversation thread
        "model": "gpt-4"
    },
    latency=1.5  # seconds
)

Closing the Client

# optional closing method to ensure all events are flushed from the queue before exiting your app
client.close()

Logging

The client uses python's logging library to log messages, by default at the ERROR level.

To adjust the verbosity of the default logs, specify the log level:

trubrics = Trubrics(api_key="your-api-key")
trubrics.logger.setLevel(logging.DEBUG)

Or specify your own logger completely:

trubrics = Trubrics(api_key="your-api-key", logger=your_cool_logger)

Other Client Configuration Options

from trubrics import Trubrics

client = Trubrics(
    api_key="your-api-key",
    flush_interval=20,
    flush_batch_size=10,
)
  • flush_interval: Time in seconds between automatic flushes (default: 10)
  • flush_batch_size: Number of events that trigger a flush (default: 20)

Development

Requirements

The project uses the following main dependencies:

  • requests==2.32.3
  • certifi==2025.1.31
  • charset-normalizer==3.4.1
  • idna==3.10
  • urllib3==2.3.0

Setting up Development Environment

Using Make commands:

make setup_uv_venv
make install_dev_requirements  # Install development dependencies
make install_requirements     # Install production dependencies

Publishing

The package is automatically published to PyPI when a new version tag is pushed. To publish a new version:

  • Create a PR from the main branch for the desired changes
  • Update the version in pyproject.toml, and add changelog entry in CHANGELOG.md
  • Once the PR is merged, create a tag in the repo trubrics-python based on the version in pyproject.toml, and push it 
    git tag -a v1.0.0 -m "Release version v1.0.0"
git push origin v1.0.0
  • Once the tag is pushed, a Github action release.yml will be triggered. It will:
    • Create a release in the repo trubrics-python based on the CHANGELOG.md entry
    • build the package with uv
    • publish it to PyPI