{
 "schema_version": 1,
 "generated": "2026-10-26",
 "id": "htobty-readyllm--ai-agent-tuning-with-own-llm",
 "repo": "htobty/ReadyLLM",
 "repo_url": "https://github.com/htobty/ReadyLLM",
 "repo_slug": "htobty-readyllm",
 "title": "Let your own LLM pick and refine engine parameters",
 "page_title": "How to let your own LLM pick and refine engine parameters with ReadyLLM",
 "summary": "Connect an LLM API to AI Agent tuning so it reasons out parameters and improves them over several rounds.",
 "who": "An engineer who already has an LLM API and wants a tuning pass that uses reasoning instead of a fixed search.",
 "problem": "Manual parameter guessing is slow, and a fixed search may miss settings that suit a particular model and scenario.",
 "outcome": "Parameter suggestions from your LLM, refined over multiple rounds with benchmark results fed back each time.",
 "steps": [
  "Run `cd backend` then `pip install -r requirements.txt`, then `uvicorn app.main:app --host 127.0.0.1 --port 8000`",
  "In a second terminal, run `cd frontend` then `npm install && npm run dev`, and open `http://localhost:3000`",
  "On the Tuning page, enter your LLM API URL, key, and model name, then save them",
  "Choose AI Agent tuning for the target and model, and start the iterative run",
  "Review the benchmark history across rounds and apply the best parameters on Deploy"
 ],
 "agent_prompt": "Using the repo htobty/ReadyLLM, start the backend and frontend, configure the AI tuning API with the URL <api-url> and model name <model-name>, and run AI Agent tuning on target <target-name>. Report the best round's parameters and its benchmark result, and confirm the API key is masked when the settings are read back.",
 "agents": [
  "any"
 ],
 "difficulty": "Advanced",
 "time": "60 minutes",
 "basis": "readme",
 "caveat": "AI tuning quality depends on the LLM API you supply, and the README does not name which models it works best with.",
 "category": "Software and DevOps",
 "tags": [
  "Software and DevOps"
 ],
 "lang": "python",
 "requirements": [
  "Python 3.9+ and Node.js 18+ on the control machine",
  "A target machine with llama.cpp, vLLM, or ComfyUI already installed, or installable through the tool",
  "Network or SSH access to any remote target you want to manage"
 ],
 "risk": "none",
 "seen_in_the_wild": false,
 "mentioned_publicly": false,
 "risks": [
  {
   "tag": "credentials",
   "notice": "Your LLM API key is sent to the API you configure, so use a key you can rotate and keep it out of shared screenshots."
  }
 ],
 "best": false,
 "score": 0.7,
 "evidence": [],
 "url": "https://dedupedai.com/use-cases/htobty-readyllm/ai-agent-tuning-with-own-llm/",
 "md": "https://dedupedai.com/use-cases/htobty-readyllm/ai-agent-tuning-with-own-llm/index.md",
 "disclaimer": "Deduped lists open-source repositories that belong to other people. We do not own, maintain, audit, or vouch for any of them, and a repo appearing here is not an endorsement or a safety check. The use cases, steps, and prompts are written by AI and may be incomplete, outdated, or just wrong. Where a use case is marked \"Seen in the wild\", we link to public posts where someone described something similar, but we have not verified those posts and the use case itself is still our AI's own write-up. Use all of this at your own risk. Only run code, commands, or agents on systems and accounts you are authorized to use, and read the code and every command before you run it, especially anything that touches credentials, files, or the network. Nothing here is professional, security, legal, or financial advice. All trademarks and project names belong to their respective owners, and their use here does not imply affiliation. Content is provided as is, without warranties of any kind. Found a mistake, a safety problem, or something you want removed? Email hello@dedupedai.com and we will look at it promptly.",
 "api": "https://dedupedai.com/api/v1/usecases/htobty-readyllm--ai-agent-tuning-with-own-llm.json",
 "api_version": "v1"
}