> 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/api-references/api-guides/artificial-intelligence/ai-rag-indexer/api-reference/metadata.md).

# Metadata

Manage Metadata

## Listing fields for RAG search

> Returns a list of fields that can be used to create embeddings for RAG search.

```json
{"openapi":"3.0.0","info":{"title":"AI Rag Indexer","version":"0.0.1"},"tags":[{"name":"Metadata","description":"Manage Metadata"}],"servers":[{"url":"https://api.emporix.io"}],"security":[{"OAuth2":["ai.agent_read"]}],"components":{"securitySchemes":{"OAuth2":{"type":"oauth2","flows":{"clientCredentials":{"scopes":{"ai.text_manage":"Needed to execute actions related to the text generation.","ai.completion_manage":"Needed to execute actions related to the AI completions.","ai.agent_read":"Needed to read AI agents.","ai.agent_manage":"Needed to manage AI agents."},"tokenUrl":"https://api.emporix.io/oauth/token"}}}},"responses":{"400_resp_common":{"description":"The request was syntactically incorrect.","content":{"application/json":{"schema":{"$ref":"#/components/schemas/ErrorMessage"}}}},"401_resp_common":{"description":"The authorization token is invalid or has expired.","content":{"application/json":{"schema":{"$ref":"#/components/schemas/ErrorMessageFault"}}}},"403_resp_common":{"description":"Authorization scopes of the access token are not sufficient and do not match the scopes required by the endpoint.","content":{"application/json":{"schema":{"$ref":"#/components/schemas/ErrorMessage"}}}}},"schemas":{"ErrorMessage":{"type":"object","properties":{"code":{"type":"integer"},"type":{"type":"string"},"message":{"type":"string"},"moreInfo":{"type":"string"},"details":{"type":"array","items":{"type":"object","properties":{"field":{"type":"string"},"type":{"type":"string"},"message":{"type":"string"},"moreInfo":{"type":"string"}}}}},"description":""},"ErrorMessageFault":{"type":"object","properties":{"fault":{"type":"object","properties":{"faultstring":{"type":"string"},"detail":{"type":"object","properties":{"errorcode":{"type":"string"}}}}}}}}},"paths":{"/ai-rag-indexer/{tenant}/{type}/rag-metadata":{"get":{"summary":"Listing fields for RAG search","operationId":"GET-ai-rag-indexer-retrieve-rag-metadata","responses":{"200":{"description":"List of fields for RAG search.","content":{"application/json":{"schema":{"type":"array","items":{"type":"string"}}}}},"400":{"$ref":"#/components/responses/400_resp_common"},"401":{"$ref":"#/components/responses/401_resp_common"},"403":{"$ref":"#/components/responses/403_resp_common"}},"description":"Returns a list of fields that can be used to create embeddings for RAG search.","tags":["Metadata"]}}}}
```

## Listing fields for vector search filtering

> Retrieves a list of fields which can be used for vector search filtering. Filtering is applied before RAG retrieval stage.

```json
{"openapi":"3.0.0","info":{"title":"AI Rag Indexer","version":"0.0.1"},"tags":[{"name":"Metadata","description":"Manage Metadata"}],"servers":[{"url":"https://api.emporix.io"}],"security":[{"OAuth2":["ai.agent_read"]}],"components":{"securitySchemes":{"OAuth2":{"type":"oauth2","flows":{"clientCredentials":{"scopes":{"ai.text_manage":"Needed to execute actions related to the text generation.","ai.completion_manage":"Needed to execute actions related to the AI completions.","ai.agent_read":"Needed to read AI agents.","ai.agent_manage":"Needed to manage AI agents."},"tokenUrl":"https://api.emporix.io/oauth/token"}}}},"schemas":{"MetadataFilter":{"type":"object","properties":{"key":{"type":"string","description":"Unique identifier of the fields. It contains full field path."},"name":{"type":"string","deprecated":true,"description":"Name of the field."},"description":{"type":"string","deprecated":true,"description":"Description of the field."},"type":{"type":"string","description":"Type of the field.","enum":["string","integer","float","boolean","datetime","date","time","dictionary","list","object"]}}},"ErrorMessage":{"type":"object","properties":{"code":{"type":"integer"},"type":{"type":"string"},"message":{"type":"string"},"moreInfo":{"type":"string"},"details":{"type":"array","items":{"type":"object","properties":{"field":{"type":"string"},"type":{"type":"string"},"message":{"type":"string"},"moreInfo":{"type":"string"}}}}},"description":""},"ErrorMessageFault":{"type":"object","properties":{"fault":{"type":"object","properties":{"faultstring":{"type":"string"},"detail":{"type":"object","properties":{"errorcode":{"type":"string"}}}}}}}},"responses":{"400_resp_common":{"description":"The request was syntactically incorrect.","content":{"application/json":{"schema":{"$ref":"#/components/schemas/ErrorMessage"}}}},"401_resp_common":{"description":"The authorization token is invalid or has expired.","content":{"application/json":{"schema":{"$ref":"#/components/schemas/ErrorMessageFault"}}}},"403_resp_common":{"description":"Authorization scopes of the access token are not sufficient and do not match the scopes required by the endpoint.","content":{"application/json":{"schema":{"$ref":"#/components/schemas/ErrorMessage"}}}}}},"paths":{"/ai-rag-indexer/{tenant}/{type}/filter-metadata":{"get":{"summary":"Listing fields for vector search filtering","operationId":"GET-ai-rag-indexer-retrieve-filter-metadata","responses":{"200":{"description":"List of fields for vector search filter.","content":{"application/json":{"schema":{"type":"array","items":{"$ref":"#/components/schemas/MetadataFilter"}}}}},"400":{"$ref":"#/components/responses/400_resp_common"},"401":{"$ref":"#/components/responses/401_resp_common"},"403":{"$ref":"#/components/responses/403_resp_common"}},"description":"Retrieves a list of fields which can be used for vector search filtering. Filtering is applied before RAG retrieval stage.","tags":["Metadata"]}}}}
```


---

# 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, and the optional `goal` query parameter:

```
GET https://developer.emporix.io/api-references/api-guides/artificial-intelligence/ai-rag-indexer/api-reference/metadata.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

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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.