vearch: Fast Vector Search
Vearch provides fast and scalable vector search capabilities for AI-native applications, allowing developers to efficiently search and retrieve similar vectors in large datasets.
- •Building recommendation systems that require fast and accurate similarity searches
- •Developing AI-powered chatbots that need to retrieve relevant information from large knowledge bases
- •Creating image or video search applications that rely on vector embeddings for similarity matching
curl -X POST 'http://localhost:16666/index' -H 'Content-Type: application/json' -d '[{"id":"vec1","vector":[1.0, 2.0, 3.0]}]'}'Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.
Expect 20–40 minutes in a terminal — or let your AI agent drive it.
mkdir -p ~/.claude/skills/vearch && curl -fsSL https://workflowstacks.com/api/skills/vearch/claude-skill -o ~/.claude/skills/vearch/SKILL.mdOpens the app with this repo with the prompt ready to go — no copy-paste needed.
Vearch: Fast Vector Search is a very large Python project (~96k lines across 457 code files, plus 90 test files). It is a full software project: use it through its install path rather than reading it end to end. Last commit a month ago, Apache-2.0 license, has a test suite.
- 1README.mdStart here — what it does and how to install it
- 2go.modDependencies and the commands it exposes
- 3internal/debugutil/README.mdInside internal/ — the main logic begins here
- 4examples/golang/basic_usage/README.mdA worked example — copy this to get going
Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.
Expect 20–40 minutes in a terminal — or let your AI agent drive it.
mkdir -p ~/.claude/skills/vearch && curl -fsSL https://workflowstacks.com/api/skills/vearch/claude-skill -o ~/.claude/skills/vearch/SKILL.mdOpens the app with this repo with the prompt ready to go — no copy-paste needed.
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