Configure the Indexer Component

The Indexer component indexes data for optimal retrieval. It is the final step, writing processed data into search engines such as Infinity, Elasticsearch and OpenSearch.

Key configurations:

Search method:

• Full-text: Keyword search for exact matches, such as code and names.
• Embedding: Semantic search using vector similarity.
• Hybrid (recommended): Combines both methods for the best recall.

Retrieval strategy:

• Processed text (default): Indexes chunked text.
• Questions: Indexes generated questions. This usually produces higher similarity matches than text-to-text matching.
• Enhanced context: Indexes summaries instead of raw text. Suitable for broad topic matching.

Filename weight:

• A slider for including the document filename as semantic information in retrieval.

Embedding model:

• Automatically uses the model set when creating the knowledge base.

:::caution IMPORTANT To search across multiple knowledge bases at the same time, all selected knowledge bases must use the same embedding model. :::