Overview
An AI app is the workspace that groups all evaluation runs for a given AI use case, their results and artefacts and the tooling to govern the AI app, such as policies and risk policies.
In the CLI, AI apps behave similarly to Git branches - an AI app needs to be created and switched to before running new evaluation runs. An AI app is identified by its key (cf. branch name).
Create and switch
An app is declared like any other entity. Beyond identity, key_info records the deployment context of the use case - it documents the app rather than changing how it is evaluated, and it is what governance reporting draws on:
app.yaml
key: "airline-assistant"
display_name: "Airline Virtual Assistant"
description: "Customer-facing assistant for flight bookings and changes."
long_description: !include "./README.md"
tags: ["customer-facing", "chat"]
key_info:
lifecycle_stage: "production" # ideation, r_and_d, development, testing, production, retired
user_types: "external" # internal_specialist, internal_all, external
data_classification: "confidential" # public, internal, confidential, restricted
has_pii_access: true
built_by: "in_house" # in_house, third_partyCreate it, then switch to it. All evaluation runs will be executed inside that app, until you switch again:
lf add app -f app.yaml
lf switch airline-assistant
lf list applf init scaffolds this file for you, and lf status shows which app is currently active. Every property is documented in the AI apps reference.