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View custom metadata in responses and guide AI-search with context in AutoRAG

AutoRAG

In AutoRAG, you can now view your object's custom metadata in the response from /search and /ai-search, and optionally add a context field in the custom metadata of an object to provide additional guidance for AI-generated answers.

You can add custom metadata to an object when uploading it to your R2 bucket.

Object's custom metadata in search responses

When you run a search, AutoRAG now returns any custom metadata associated with the object. This metadata appears in the response inside attributes then file , and can be used for downstream processing.

For example, the attributes section of your search response may look like:

{
  "attributes": {
    "timestamp": 1750001460000,
    "folder": "docs/",
    "filename": "launch-checklist.md",
    "file": {
      "url": "https://wiki.company.com/docs/launch-checklist",
      "context": "A checklist for internal launch readiness, including legal, engineering, and marketing steps."
    }
  }
}

Add a context field to guide LLM answers

When you include a custom metadata field named context, AutoRAG attaches that value to each chunk of the file. When you run an /ai-search query, this context is passed to the LLM and can be used as additional input when generating an answer.

We recommend using the context field to describe supplemental information you want the LLM to consider, such as a summary of the document or a source URL. If you have several different metadata attributes, you can join them together however you choose within the context string.

For example:

{
  "context": "summary: 'Checklist for internal product launch readiness, including legal, engineering, and marketing steps.'; url: 'https://wiki.company.com/docs/launch-checklist'"
}

This gives you more control over how your content is interpreted, without requiring you to modify the original contents of the file.

Learn more in AutoRAG's metadata filtering documentation.