labagent

labagent is an open-source CLI that launches hands-on labs for RAG, LLM apps and Databricks, then removes them so you do not pay for leftovers. It also sets up and cleans AWS training sandboxes with Terraform.

Quick start

pip install 'labagent[rag]'          # Python 3.9+; labs use the Databricks CLI: databricks auth login
labagent packs                       # list the labs
labagent launch rag-sec-filings --name demo
labagent destroy rag-sec-filings --name demo

Every step is safe to re-run. launch resumes where it stopped. destroy removes only what the lab created.

Lab catalog

Free Edition limits apply: one Lakebase project, three apps, and apps stop after 24 hours. Details: docs/packs.md.

Run a RAG lab on Databricks Lakebase

rag-sec-filings builds a RAG app on Postgres with pgvector. It loads a pinned snapshot of 10-K filings, runs a retrieval quality check, and deploys the app only if the check passes. The app has company and year filters, suggested questions and cited answers.

labagent launch rag-sec-filings --name demo

The data comes from a checksummed release in labagent-datasets. Known gaps are listed in its README.

Text-to-SQL agent on Databricks

db-agent clones github.com/db-agent/db-agent at a pinned commit and deploys it to Databricks Apps. It then asks a test question through the live app. The data is the samples catalog every workspace has.

labagent launch db-agent --name demo --param dataset=bakehouse

Use labagent from plain English

A small local model turns a sentence into a command. You see the command and confirm it before anything runs.

ollama pull qwen2.5-coder:0.5b
labagent "deploy rag-sec on databricks"

Any OpenAI-compatible endpoint works. See docs/packs.md.

AWS sandboxes for workshops

labagent creates IAM users, a sandbox policy and a Lambda role per cohort with Terraform. Passwords are returned encrypted. It also tears down what learners created and cleans an untagged shared account from an explicit ruleset.

labagent --config lab.json run --job job.json --output result.json

Job format: docs/job-contract.md. State and secrets: docs/state-and-secrets.md.

Safety

• Plan first, then apply. The plan is bound to the account, its items, an age limit and the hash a human approved.
• Only a delete rule can delete. A keep rule always wins. Unmatched resources are reported, never removed.
• labagent refuses to run in an AWS account that is not on your allow list.
• No plaintext secrets or emails in output or logs. No personal data in this repo. Tests enforce both.

Early release. Try labs in a throwaway account or workspace first. Apache-2.0. See SECURITY.md and CONTRIBUTING.md.

Running labs for a class or team? Private batches and dashboard: https://becloudready.com