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Hybrid Search

Hybrid search runs both full-text and semantic search in parallel, then merges the results. This gives you exact keyword matches alongside conceptually related content, producing the most comprehensive results.

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How it works

  1. Your query is sent to both search engines simultaneously.
  2. Full-text search matches against sessions.searchableText using Convex’s search indexes.
  3. Semantic search converts the query to an embedding and matches against sessionEmbeddings using cosine similarity.
  4. Results are merged using reciprocal rank fusion (RRF).
  5. A session found by both searches receives contributions from both ranks.
For each zero-based rank, the API adds 1 / (60 + rank) to the session’s score. The score orders results internally and is not included in the REST response. Hybrid search is the default recommendation for RAG and context injection workflows because it catches both exact matches and related content.

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Using in the dashboard

The Context tab in the dashboard supports a hybrid mode:
  1. Open the Context tab.
  2. Select Hybrid as the search type.
  3. Enter your query.
  4. Results show combined rankings with scores from both engines.

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Using via API

The response contains a results array. See the API reference for the returned fields; the REST API does not return snippets or relevance scores. Hybrid results may use id or _id depending on which search path found the session. Normalize with result.id ?? result._id.

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Use case: RAG pipeline

Hybrid search is ideal for Retrieval-Augmented Generation because it retrieves both precise matches (from full-text) and conceptually related context (from semantic):
The /api/context endpoint uses semantic search internally and returns results formatted for LLM prompt injection.

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Example RAG flow

  1. User asks a question in your application.
  2. Your backend queries /api/context with the user’s question.
  3. The top results are injected into the system prompt.
  4. The LLM responds with knowledge from your past sessions.
This turns your OpenSync session history into a searchable knowledge base.

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Comparison

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Requirements

Hybrid search requires:
  • OpenAI API key (for the semantic component)
  • Embeddings generated for your sessions
The REST hybrid endpoint requires a working OpenAI key. Use type=fulltext when embeddings are unavailable; the REST endpoint does not automatically fall back.