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Vector similarity search with FAISS v1.0.0

Use this resource to find the nearest vectors in large embedding sets

New

  • 504 downloads
  • 191 likes
  • 135 saves

Free

Install with the CLI

In a terminal, from the folder you want:

npx --yes palatekit@latest install vector-similarity-search-faiss

With no option, the skill goes to ~/.agents/skills/; add --agent claude-code (or codex, cursor…) to target an agent.

First time: connect the CLI with

npx --yes palatekit@latest login

The agent builds a FAISS index sized to the dataset, adds the vectors and runs nearest-neighbour searches. You get an exact or approximate similarity index, for embeddings that need no metadata filtering.

Mostly picked by

Updated November 2, 2026

Card for the “Vector similarity search with FAISS” skill

Details

Works in
Install guides
Generates with
Your agent's model
Licence
MIT

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What you get

  • SKILL.md: installation, index creation and basic search
  • references/index_types.md: index types, from exact Flat to approximate indexes

Good fit for

  • You have millions of embeddings to query quickly
  • Your search does not need to filter on metadata

Not for

    Tags

    • faiss
    • vectors
    • embeddings
    • search
    • index

    About

    You say

    “Build a FAISS index for these 500,000 embeddings and return the ten nearest neighbours.”

    Card for the “Vector similarity search with FAISS” skill

    Skill published by Orchestra Research under the MIT license, delivered in its original version.

    Show more

    How to use it

    1. Install the skill in your agent's skills folder
    2. Ask your agent to find the nearest vectors in large embedding sets
    3. Review and adjust the result

    Content preview

    Files

    • LICENSE1 KB
    • NOTICE-PALATEKIT.md0.5 KB
    • references/index_types.md6 KB
    • SKILL.md4.7 KB

    Origin and licence

    Listed unmodified

    Author
    Orchestra Research
    Source
    github.com/nousresearch/hermes-agent/tree/0c74cc682dc81bf78b78a1737b3ee77a820ccb79/optional-skills/mlops/faiss
    Licence
    MIT

    Notice

    « faiss » (Orchestra Research, MIT) livré dans sa version d'origine : fiche en français et en anglais par PalateKit.

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