Getting started

Here we'll cover how to collect events in python. Our SDK calls are non-blocking and fast, meaning they won't get in the way of your python app's performance.

Install (requires python>3.8)

Firstly, install Trubrics in your venv with:

pip install trubrics-beta

Getting started in python

Track your events with:

from trubrics_beta import Trubrics

trubrics = Trubrics(api_key="TRUBRICS_API_KEY")

trubrics.track(  # use track_sync for synchronous requests
    event="prompt",
    user_id="user_id",
    properties={
        "$text": "tell me a story",
        "$thread_id": "1234",
        "a_custom_property": "a custom value",
    },
)

Project API key

Your trubrics API key is unique to your project. Login to Trubrics, and copy your project API key from the settings page. This is a write only API key that allows you to push events.

Parameter	Type	Description	Required
user_id	str	The distinct ID of the user that is signed in to your app.	yes
event	str	The name of the event you are tracking. This can range from "User prompt", "Sign in", "Generation", etc.	yes
properties	dict[str,any]	A list of properties of the event. For example, a "Generation" event could have properties "Cost of generation" or "Prompt template". Trubrics properties are prefixed with a $.	no

If you have not implemented auth, use a UUID to assign events to an anonymous user.

Trubrics properties

Any property that begins with a $ is a property recognised by Trubrics. This allows us to perform certain actions in the ingestion pipeline and backend. Here are a list of Trubrics properties:

• $text: events that contain a textual element should use this property, as it allows Trubrics to tag the event with text attributes during ingestion. Text attributes can be managed directly in Trubrics.

• $thread_id: to identify when a user is interacting with an AI assistant within their session. This allows you to distinguish between non-AI assistant interactions such as "Sign In" and events within a thread such as "Prompt" and "Generation". With an LLM powered assistant, this ID should be unique for each different conversation.

• $assistant_id: events that are made by an assistant, such as "Generation" or "Query database", should use this property. Typically for LLM assistants this can be set to the model name, such as "GPT-4" or "GPT-3.5-turbo".

• $prompt_id: Identifies as specific prompt, or user message. This is useful when that prompt needs to be tagged with an attribute later on.

• $generation_id: Identifies as specific generation, or assistant message. This is useful when that generation needs to be tagged with an attribute later on.