AI Search - Custom metadata filtering for AI Search

AI Search now supports custom metadata filtering, allowing you to define your own metadata fields and filter search results based on attributes like category, version, or any custom field you define. Define a custom metadata schema You can define up to 5 custom metadata fields per AI Search instance. Each field has a name and data type ( text , number , or boolean ): curl -X POST \ -H "Content-Type: application/json" \ -H "Authorization: Bearer {API_TOKEN}" \ -d '{ "id": "my-instance", "type": "r2", "source": "my-bucket", "custom_metadata": [ { "field_name": "category", "data_type": "text" }, { "field_name": "version", "data_type": "number" }, { "field_name": "is_public", "data_type": "boolean" } ] }' Add metadata to your documents How you attach metadata depends on your data source: R2 bucket : Set metadata using S3-compatible custom headers ( x-amz-meta-* ) when uploading objects. Refer to R2 custom metadata for examples. Website : Add tags to your HTML pages. Refer to Website custom metadata for details. Filter search results Use custom metadata fields in your search queries alongside built-in attributes like folder and timestamp : curl \ -H "Content-Type: application/json" \ -H "Authorization: Bearer {API_TOKEN}" \ -d '{ "messages": [ { "content": "How do I configure authentication?", "role": "user" } ], "ai_search_options": { "retrieval": { "filters": { "category": "documentation", "version": { "$gte": 2.0 } } } } }' Learn more in the metadata filtering documentation .