> For the complete documentation index, see [llms.txt](https://developer.emporix.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://developer.emporix.io/changelog/archive/changelog-2025/2025-12-03-ai-rag-indexer.md).

# 2025-12-03: AI RAG Indexer - new endpoints for configuring RAG Search Functionality

## Overview

Introduced new endpoints in `ai-rag-indexer` service which are necessary for configuring and performing RAG Search.

## Added endpoints

| Endpoint                                                                                                                                                                                                          | Description                                                                |
| ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------- |
| [Reindexing the entities of given type](https://developer.emporix.io/api-references/api-guides/artificial-intelligence/ai-rag-indexer/api-reference/reindex#GET-ai-rag-indexer-tenant-type-reindex)               | Endpoint for triggering reindexing process.                                |
| [Listing fields for RAG search](https://developer.emporix.io/api-references/api-guides/artificial-intelligence/ai-rag-indexer/api-reference/metadata#GET-ai-rag-indexer-tenant-type-rag-metadata)                 | Endpoint for retrieving possible fields destined for computing embeddings. |
| [Listing fields for vector search filtering](https://developer.emporix.io/api-references/api-guides/artificial-intelligence/ai-rag-indexer/api-reference/metadata#GET-ai-rag-indexer-tenant-type-filter-metadata) | Endpoint for retrieving fields destined to filtering database entries.     |

## Known problems

There are no known problems.


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://developer.emporix.io/changelog/archive/changelog-2025/2025-12-03-ai-rag-indexer.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
