Documentation Index
Fetch the complete documentation index at: https://hyperlocalise.dev/llms.txt
Use this file to discover all available pages before exploring further.
hyperlocalise helps you generate local translation drafts, optionally sync with your TMS, and track what still needs review.
Platform focus
- LLM provider layer: OpenAI, Azure OpenAI, Gemini, Anthropic, AWS Bedrock, LM Studio, Groq, Ollama
- TMS adapters (experimental): Crowdin, LILT AI, Lokalise, Phrase, POEditor, Smartling
- Eval framework (experimental): quality + regression checks across locales/models
- CI-ready status labels (experimental):
ready/needs review/missing - Plan-first + lockfile: deterministic runs and reviewable diffs
Feature graph
Who this is for
Use this CLI if you:- keep translation files in your repository,
- want AI-generated drafts as a starting point,
- want to choose between zero-human workflows and optional human curation in your TMS.
Core workflow
| Stage | Action | Why it matters |
|---|---|---|
| 1 | init | Scaffold i18n.yml and bootstrap defaults. |
| 2 | Configure i18n config | Define locales, buckets, and LLM/storage settings. |
| 3 | run --dry-run | Validate plan and detect issues before writing drafts. |
| 4 | run | Generate local draft translations. |
| 5 | Release from local repo | Zero-human path when your process allows direct publish from generated outputs. |
| 6 (optional) | sync push (experimental) | Upload local changes to your TMS for curation workflows. |
| 7 (optional) | Curate in TMS | Human review and correction in your translation platform. |
| 8 (optional) | sync pull (experimental) | Bring curated translations back into the repository. |
| 9 | status | Measure completion and unresolved work in either workflow path. |
Start in 10 minutes
Common next steps
- Learn command behavior in commands overview.
- Configure provider credentials in provider credentials.
- Understand sync behavior in storage overview.
- Review feature maturity in the stability matrix.