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Axiom Wiki supports Hybrid Search, combining traditional keyword matching with modern vector embeddings. This allows the AI agent to find relevant context even if the exact keywords don’t match.

OptionDescription
--setupLaunch the interactive setup wizard to pick a provider and model.
--reindexForce a full re-index of all wiki pages.
--statusShow the current embedding configuration and index size.

Axiom supports three embedding providers:

  1. Google Gemini (Recommended): High performance, generous free tier. Uses text-embedding-004.
  2. OpenAI: Industry standard. Uses text-embedding-3-small.
  3. Ollama: Total privacy, local-first. Uses nomic-embed-text.

When enabled, Axiom generates a vector embedding for every wiki page and stores them in a local Orama index (search.index).

Search queries are automatically converted to vectors, and the results are merged with keyword matches using Reciprocal Rank Fusion (RRF). This ensures that exact matches still rank highly while semantically related pages are surfaced.

If you already have an Axiom Wiki but haven’t enabled semantic search:

  1. Upgrade: Ensure you are on axiom-wiki@0.7.0 or higher.
  2. Setup: Run axiom-wiki embed --setup.
  3. Index: The wizard will guide you through picking a provider and will automatically trigger a full re-index of your existing pages.

Once complete, your AI agent will automatically start using hybrid search for all planning and context retrieval tasks.

Indexing happens automatically during:

  • axiom-wiki ingest
  • axiom-wiki autowiki
  • axiom-wiki sync
  • Real-time updates via MCP notify_code_change