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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Streamline your workflow with Lynkr, a CLI tool that acts as an HTTP proxy for efficient code interactions using Claude Code CLI.
| Date | Stars |
|---|---|
| 2026-07-31 | 538 |
| 2026-08-05 | 540 |
| 2026-08-06 | 540 |
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# Lynkr ### An LLM Gateway which optimises your token usage. **84% fewer tokens on JSON tool results. 53% fewer tokens on tool-heavy requests. Sub-300ms semantic cache hits. Zero code changes.** [](https://www.npmjs.com/package/lynkr) [](https://github.com/Fast-Editor/Lynkr) [](LICENSE) [](https://nodejs.org) [](https://deepwiki.com/Fast-Editor/Lynkr) <table> <tr> <td align="center"><strong>84%</strong><br/>JSON Compression</td> <td align="center"><strong>53%</strong><br/>Tool Token Reduction</td> <td align="center"><strong><300ms</strong><br/>Semantic Cache Hits</td> <td align="center"><strong>13+</strong><br/>LLM Providers</td> <td align="center"><strong>0</strong><br/>Code Changes Required</td> </tr> </table> > Numbers from the bundled benchmark against LiteLLM on identical free local backends — run it yourself: `node benchmark-tier-routing.js`. It doubles as a 19-scenario routing regression harness (currently 12/12 correctness checks), and `MODE=routing` runs a routing-only head-to-head that judges **both** proxies on the same acceptable-tier sets — including LiteLLM's Auto Router v2. [How it works →](docs/benchmarking.md) > **Third-party benchmark:** on [RouterArena](https://github.com/RouteWorks/RouterArena) (ICLR 2026, 8,400 queries) Lynkr's routing scores **67.65 arena / 68.41% accuracy at $0.29 per 1K queries with 92.38 robustness** — above GPT-5's built-in router and NotDiamond at a fraction of their cost. [Methodology & caveats →](docs/routerarena-benchmark.md) --- ## 🚀 New: Wrap Mode for AI Coding Tools **Use Lynkr's routing with your AI coding assistant — maximize your subscription value:** ```bash npm install -g lynkr # Claude Code Pro/Max lynkr wrap claude ``` **Wrapping gives you:** - ✅ Tier routing (send simple tasks to free Ollama, complex to your subscription/API) - ✅ Sticky sessions: one routing decision per conversation via content fingerprinting, with automatic escalation when the task outgrows the model - ✅ TOON/RTK compression (84% token reduction on large JSON tool outputs) - ✅ Semantic caching (sub-300ms cache hits, 0 tokens billed) - ✅ **3-5x more usage from the same subscription limits** - ✅ Works with OAuth (Claude, Copilot, Cursor) or API keys (Aider, Codex) [Full wrap guide →](docs/wrap-guide.md) --- ## Quick Start (2 Minutes) ### 1. Install Lynkr ```bash npm install -g lynkr ``` ### 2. Configure Lynkr The fastest path is the interactive wizard: ```bash lynkr init ``` It asks four questions — usage mode (Claude Pro/Max via wrap, or direct API keys), tier picks for SIMPLE/MEDIUM/COMPLEX/REASONING across the 12 supported providers, credentials for what you chose, and a few routing-intelligence knobs — then writes a fully-populated `.env` with sensible production defaults for everything else (caching, compression, policy budgets, MCP sandbox, rate limiting). Useful flags: ```bash lynkr init --force # overwrite an existing .env ``` See [`docs/init.md`](docs/init.md) for the full wizard reference. If you'd rather configure by hand, the manual options below still work — copy `.env.example` to `.env` and edit it directly: **Option A: Free & Local (Ollama) - Recommended for Testing** ```bash # Install Ollama first: https://ollama.com ollama pull qwen2.5-coder:latest ``` Then start Lynkr: ```bash lynkr start ``` ### 3. Connect Your Tool **Cursor IDE** - Settings → Models → Override Base URL - Set to: `http://localhost:8081/v1` - API Key: `any-value` **Codex CLI** Edit `~/.codex/config.toml`: ```toml model_provider = "lynkr" [model_providers.lynkr] base_url = "http://localhost:8081/v1" wire_api = "responses" ``` ✅ **Done!** Your AI tool now us
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Dayna Blackwell
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Victor M. SMITH · France
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Yi Liu · Nanyang Technological University · Singapore
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:eedfda44ea322455, topic:llm-gateway, topic:ai-gateway, topic:llm-proxy
matched fp:eedfda44ea322455, topic:code-generation, topic:developer-tools