Run your own local LLM with rate limits via API-keys
A new Ruby prototype allows users to run a local LLM proxy with rate limits using API keys. The proxy supports a refillable token bucket system and can be set up with minimal dependencies. Users can test the proxy and manage token limits for individual clients.
- ▪The proxy listens on 0.0.0.0:8899 by default and forwards requests to a local LLM setup.
- ▪Each bearer token has its own token bucket, and requests without a bearer token are bucketed by remote IP.
- ▪The system allows for a maximum of 10 tokens per user, with a refill rate of 2 tokens every 5 minutes.
3 outlets in our directory ran this story, first to last over 36 hours. All of the coverage we found sits in one bucket: centre. That one-sidedness is itself worth noticing.
- ▪ I built a screen recorder that runs on your own API key — r/selfhosted
- ▪ I built a screen recorder that runs on your own API key — r/SaaS
Hacker News (AI / LLM) files mainly under ai. We currently carry 2,776 of its stories.
Story provenance
Source · retrieval · rights · ranking — open for full record
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Story provenance
Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.
Record
| Original publisher | GitHub |
| Canonical URL | https://github.com/skorotkiewicz/llm-rt |
| Publication time | Wed, 27 May 2026 18:39:25 +0000 |
| Retrieval time | 2026-05-27T18:48:02.507Z |
| Last seen | 2026-05-27T18:48:02.507Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | OisdZy3NHWL8 · 3 stories |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
LLM token bucket proxy Small Ruby prototype for an OpenAI-compatible LLM proxy with a refillable token bucket. It uses only Ruby standard libraries: no gems, no Rack, no WEBrick. Run BASE_API_URL=http://192.168.0.124:8888/v1 \ BASE_API_KEY=1mmer \ BASE_MODEL=gemma4 \ ruby llm_proxy.rb The proxy listens on 0.0.0.0:8899 by default. For your local LLM at 192.168.0.124:8888, run the saved local setup: ./run_local_proxy.sh That starts the Ruby proxy at http://127.0.0.1:8899/v1 and forwards to http://192.168.0.124:8888/v1.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at GitHub.