{
 "schema_version": 1,
 "generated": "2026-10-20",
 "id": "evermind-ai-skillcorpus--self-host-skill-retrieval-models",
 "repo": "EverMind-AI/SkillCorpus",
 "repo_url": "https://github.com/EverMind-AI/SkillCorpus",
 "repo_slug": "evermind-ai-skillcorpus",
 "title": "Self-host the Skill Corpus retrieval models",
 "page_title": "How to self-host the Skill Corpus retrieval models with Skill Corpus",
 "summary": "Serve the released bi-encoder and reranker behind your own /embed and /score endpoint.",
 "who": "A platform engineer who must keep skill retrieval inside their own infrastructure instead of calling the hosted SkillHub API.",
 "problem": "Depending on a hosted endpoint may not fit data-control or deployment rules.",
 "outcome": "A local endpoint that encodes queries and skills and reranks top results for your agents.",
 "steps": [
  "Load the demo corpus with `pip install pandas` and then read skills.parquet with pandas, or use the datasets library.",
  "Run `pip install -r skillcorpus/match/requirements.txt` to install the serving dependencies.",
  "Set EMBEDDING_MODEL and RERANKER_MODEL to the released checkpoints, then run `bash skillcorpus/match/scripts/run_server.sh`.",
  "Call /embed and /score on the local endpoint and run your own encode, top-k, and rerank step."
 ],
 "agent_prompt": "In the SkillCorpus repository, install skillcorpus/match/requirements.txt, start the server with run_server.sh using the released EverMind-AI bi-encoder and reranker checkpoints, then send a test query to /embed and /score. Report the top three skill ids for <task description>. Verify that the scores are returned for each candidate.",
 "agents": [
  "any"
 ],
 "difficulty": "Advanced",
 "time": "2 hours",
 "basis": "readme",
 "caveat": "The README says this local endpoint is not a drop-in for the hosted /openapi/v1/skills API, so you must write your own selection logic over /embed and /score.",
 "category": "Software and DevOps",
 "tags": [
  "Software and DevOps"
 ],
 "lang": "python",
 "requirements": [
  "Internet access to reach the hosted SkillHub API or the plugin install guide",
  "Python 3 for the example script or the self-hosting setup",
  "An OpenAI-compatible API key only if you use the --ask option of the example script",
  "PyTorch and transformers (from skillcorpus/match/requirements.txt) and a machine able to run two 0.6B models for self-hosting"
 ],
 "risk": "dual-use",
 "seen_in_the_wild": false,
 "mentioned_publicly": false,
 "risks": [],
 "best": false,
 "score": 0.7,
 "evidence": [],
 "url": "https://dedupedai.com/use-cases/evermind-ai-skillcorpus/self-host-skill-retrieval-models/",
 "md": "https://dedupedai.com/use-cases/evermind-ai-skillcorpus/self-host-skill-retrieval-models/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/evermind-ai-skillcorpus--self-host-skill-retrieval-models.json",
 "api_version": "v1"
}