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  • License MIT

Semantic search over local files for pi. Indexes a directory of text files, watches for changes, and exposes a knowledge_search tool to the LLM.

Package Exports

    This package does not declare an exports field, so the exports above have been automatically detected and optimized by JSPM instead. If any package subpath is missing, it is recommended to post an issue to the original package (pi-knowledge-search) to support the "exports" field. If that is not possible, create a JSPM override to customize the exports field for this package.

    Readme

    pi-knowledge-search

    Semantic search over local files for pi. Indexes directories of text/markdown files using vector embeddings, watches for changes in real-time, and exposes a knowledge_search tool the LLM can call.

    Install

    pi install git:github.com/samfoy/pi-knowledge-search

    Or try without installing:

    pi -e git:github.com/samfoy/pi-knowledge-search

    Setup

    Run the interactive setup command inside pi:

    /knowledge-search-setup

    This walks you through:

    1. Directories to index (comma-separated paths)
    2. File extensions to include (default: .md, .txt)
    3. Directories to exclude (default: node_modules, .git, .obsidian, .trash)
    4. Embedding provider — OpenAI, AWS Bedrock, or local Ollama

    Config is saved to ~/.pi/knowledge-search.json. Run /reload to activate.

    Config file

    You can also edit the config file directly:

    {
      "dirs": ["~/notes", "~/docs"],
      "fileExtensions": [".md", ".txt"],
      "excludeDirs": ["node_modules", ".git", ".obsidian", ".trash"],
      "provider": {
        "type": "openai",
        "model": "text-embedding-3-small"
      }
    }

    The API key for OpenAI can be set in the config file ("apiKey": "sk-...") or via the OPENAI_API_KEY environment variable.

    Bedrock config
    {
      "dirs": ["~/vault"],
      "provider": {
        "type": "bedrock",
        "profile": "my-aws-profile",
        "region": "us-west-2",
        "model": "amazon.titan-embed-text-v2:0"
      }
    }

    Requires the AWS SDK and valid credentials for the specified profile.

    Ollama config (free, local)
    {
      "dirs": ["~/notes"],
      "provider": {
        "type": "ollama",
        "url": "http://localhost:11434",
        "model": "nomic-embed-text"
      }
    }

    Requires Ollama running locally:

    ollama serve
    ollama pull nomic-embed-text

    Environment variable overrides

    Every config field can be overridden via environment variables. This is useful for CI or when you want different settings per shell session. See env-vars.md for the full list.

    How it works

    1. On session start, loads the index from disk and incrementally syncs — only re-embeds new or modified files
    2. Starts a file watcher for real-time updates (debounced, 2s)
    3. Registers a knowledge_search tool the LLM calls with natural language queries
    4. Returns ranked results with file paths, relevance scores, and content excerpts

    The index is stored at ~/.pi/knowledge-search/index.json.

    Commands

    Command Description
    /knowledge-search-setup Interactive setup wizard
    /knowledge-reindex Force a full re-index

    Performance

    Typical numbers for 500 markdown files (20MB):

    Operation Time
    Full index build ~7s
    Incremental sync (no changes) ~12ms
    File re-embed (watcher) ~200ms
    Search query ~250ms
    Index file size ~5MB

    License

    MIT