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 features an efficient queuing system with automatic background flushing of events to the Trubrics API.

Installation

Install using pip:

pip install trubrics

Or using uv:

pip install uv
uv pip install trubrics

Key Features

• Event tracking with custom properties
• Automatic background event flushing
• Thread-safe implementation
• Configurable flush intervals and batch sizes

Usage

Basic Setup

from trubrics import Trubrics

client = Trubrics(
    api_key="your-api-key",
    flush_interval=10,  # seconds
    flush_at=20,        # events
)

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={"model": "gpt-4"},
    latency=150  # milliseconds
)

Closing the Client

# Ensure all events are flushed before shutting down
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)

Configuration Options

• api_key: Your Trubrics API key
• flush_interval: Time in seconds between automatic flushes (default: 10)
• flush_at: 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