label-lens
v0.3.0
Published
Terminal-first review tool for noisy text training data.
Downloads
819
Readme
LabelLens
Review noisy text labels from your terminal.
Your LLM, rules, or weak model labeled the dataset. Some fraction is wrong in ways you only catch by reading the rows. Options today:
- Spreadsheet — no record context, no prediction metadata, no real keyboard flow.
- Label Studio / Doccano / Prodigy — server, browser, accounts. Heavy for a 30-minute job over SSH, and overkill when you already have predictions and just need to review them.
- A one-off CLI you vibe-code per dataset — works once, then you rewrite it next time.
LabelLens is the missing keyboard reviewer in the middle. Accept, reject, relabel, ask an assistant, export.
Local-first, runs over SSH, ships as a single Bun-compiled binary. State lives next to the source JSONL; the dataset never leaves the box unless you turn on the LLM assistant.
Status: v0.1 release candidate. See PRD.md and docs/adr/ for design.
Supported task types
Current support is configured with task. See Review task types for examples and data shapes. Planned task types are tracked in the roadmap.
| Task type | Status | Use it for |
|---|---|---|
| classification | Supported now | One label per record, such as intent, topic, or category review. |
| boundary | Supported now | Document or line segmentation where surrounding context matters. |
| multi-label | Planned V1 | Records that can carry multiple labels via toggle-style review. |
| Extraction review | Planned V1 | Form-style correction of structured fields, without span editing. |
| Pairwise / preference | Planned later | LLM output comparison and evaluation workflows. |
| NER / span review | Planned V2 / future | Character-level span correction; deferred because terminal span editing is the hard part. See PRD §19. |
Install
curl (macOS arm64/x64, Linux arm64/x64):
curl -fsSL https://raw.githubusercontent.com/somus/label-lens/main/install.sh | shPin a version with LL_VERSION=v0.1.2, override paths with LL_PREFIX / LL_BIN_DIR. Each release ships SHA256SUMS.txt; the installer verifies before extracting.
npm fallback (containers, non-shell environments):
npm install -g label-lens60-second quickstart
labellens init data.jsonl # infer schema, write labellens.config.json
labellens # open the review screenIn the TUI (default simple preset — arrow keys; see docs/reference/keybindings.md for the full table covering both simple and vim presets):
aaccept ·rrelabel ·1–9quick-relabel ·xreject ·sskip↓/↑navigate ·→/←cycle queuesiLLM assistant (configures on first press) ·tstats ·?help ·qquit
When done:
labellens export jsonl # write reviewed dataset
labellens export stats # Markdown summaryDocs
| | |
|---|---|
| Tutorial | Full 5-minute walkthrough. |
| How-to guides | Configure the assistant, work with queues, bulk-relabel, export, migrate labels, run over SSH, use Ollama locally. |
| Reference | Config schema, keybindings, queue grammar, CLI flags, output formats. |
| Explanation | Domain model, why skipped is its own state, audit semantics. |
| Roadmap | What's deferred past v0.1. |
| labellens guide | Print the tutorial offline (SSH-friendly). |
| labellens --help | Quick reference printed to stdout. |
| man labellens | Man page (installed by curl-installer). |
Project layout
PRD.md— product spec.CONTEXT.md— domain glossary.docs/— user-facing documentation (index).docs/adr/— architecture decision records.AGENTS.md(aliasCLAUDE.md) — orientation for AI agents working on this repo.
License
MIT
