CharisandJoshen Lim
89b4f1aca4
## Summary * Adds a `delete_notebook` AI assistant tool (`needsApproval: true`) that lets the assistant delete a notebook with explicit user approval, mirroring the existing `create_notebook`/`update_notebook` tools. * Wires up a destructive-styled approval card in the AI Assistant Panel (fetches the notebook to show its name, warns the deletion is permanent) using the same `Confirm`/tool-approval plumbing as the other notebook tools. * Updates `tool-filter.ts` opt-in gating, the assistant system prompt, the eval-harness mock tools, and the eval dataset with `delete_notebook` coverage. * Adds test coverage in `notebook-tools.test.ts`, `mock-tools.test.ts`, and `NotebookProposalRenderer.test.tsx`. Closes [FE-4242](https://linear.app/supabase/issue/FE-4242/assistant-delete-notebook-tool). ## Test plan - [X] `pnpm typecheck --filter=studio` passes - [X] `pnpm --filter studio exec vitest run` for the touched files (notebook-tools, mock-tools, NotebookProposalRenderer, [Message.Parts](<http://Message.Parts>), and existing consumers of `content-delete-mutation`) — all passing - [X] `eslint` and `prettier --check` clean on all touched files - [X] Manual verification of the approval UI in a running Studio instance (not done in this session) ## Summary by CodeRabbit * **New Features** * Added AI-assisted notebook deletion with explicit confirmation and irreversible-action warnings. * Added safeguards to distinguish deleting an entire notebook from removing individual panels. * Completed deletions now display the deleted notebook’s name without an option to reopen it. * **Bug Fixes** * Improved handling of missing notebooks and invalid deletion requests. * **Tests** * Added coverage for deletion approval, denial, errors, and successful completion. <!-- This is an auto-generated comment: release notes by coderabbit.ai --> ## Summary by CodeRabbit * **New Features** * Added AI-assisted notebook deletion with explicit approval and irreversible-action warnings. * Added confirmation, loading, error, and completion states for notebook deletion. * Prevented accidental full-notebook deletion when only a panel or section should be removed. * Improved notebook update results by showing applied changes when available. * **Bug Fixes** * Notebook deletion now uses the required API version. * Improved handling and validation of missing notebooks during deletion. <!-- end of auto-generated comment: release notes by coderabbit.ai --> --------- Co-authored-by: Joshen Lim <joshenlimek@gmail.com>
Studio Assistant Evals
We use Braintrust to evaluate Assistant behaviors against a tracked dataset (offline evals) and against live traces (online evals).
Offline Evals
Add offline eval test cases to dataset.ts. If needed, add new scorers (see below) for the specific dimension you wish to test. Expect to update and run offline evals when adding new Assistant behaviors
You may wish to run offline evals when:
- You updated the eval suite with a new test case or scorer
- You changed Assistant's behavior and want to check for improvements/regressions
Running Offline Evals in CI
Add the run-evals label on a PR to the repo and Braintrust's GitHub Action will run evals and post a summary comment (example).
You can find detailed results in the "Experiments" tab of the "Assistant" project on Braintrust.
Running Offline Evals in Local Dev
Within apps/studio
# To set up WASM files
pnpm evals:setup
# Run all evals and upload results to Braintrust
pnpm evals:upload
# Run all evals without uploading results
pnpm evals:run
# Run an upload single test case
pnpm braintrust eval evals/assistant.eval.ts --filter "input.prompt=How many projects"
Upload results when you want to inspect Experiments or Logs in the Braintrust dashboard or API. You can use developer tools like Braintrust MCP or bt CLI to analyze results with an agent.
Scorers
Scorers look at a thread or task output and assign a score deterministically or via LLM-as-a-judge. Optionally they can consider expected values.
Define scorers in scorer.ts and include them in assistant.eval.ts to run them in offline evals.
Updating Online Scorers
Online scorers run as serverless functions on Braintrust infrastructure. They're deployed from the scorer-online.ts script. Since these scoring against production traces, they can't rely on ground truth expected values. Structure scoring logic and LLM prompts accordingly. Not every scorer needs to be an online scorer.
To opt-in to online scoring, add the scorer to scorer-online-manifest.json and add a corresponding handler in scorer-online.ts
Testing & Deploying Online Scorers
Add the preview-scorers label to a PR to deploy branch-prefixed scorers to the "Assistant (Staging Scorers)" Braintrust project (example). From that project dashboard, you can manually test the scorer against a trace from any project.
After merge to master, preview scorers automatically clean up and deploy to the production in the "Assistant" Braintrust project. Update the "Online Scoring" automation in the Logs page to include the new scorer function.