--- title: Query Vectors --- [Skip to content](#_top) [API Reference](https://developers.cloudflare.com/api/python) [Vectorize](https://developers.cloudflare.com/api/python/resources/vectorize) [Indexes](https://developers.cloudflare.com/api/python/resources/vectorize/subresources/indexes) Copy Markdown Open in **Claude**Open in **ChatGPT**Open in **Cursor** --- **Copy Markdown****View as Markdown** # Query Vectors vectorize.indexes.query(strindex\_name, IndexQueryParams\*\*kwargs) -> [IndexQueryResponse]() POST/accounts/{account\_id}/vectorize/v2/indexes/{index\_name}/query Finds vectors closest to a given vector in an index. ##### Security
API Token The preferred authorization scheme for interacting with the Cloudflare API. Create a token. **Example:**Authorization: Bearer Sn3lZJTBX6kkg7OdcBUAxOO963GEIyGQqnFTOFYY
API Email + API Key The previous authorization scheme for interacting with the Cloudflare API, used in conjunction with a Global API key. **Example:**X-Auth-Email: user@example.com The previous authorization scheme for interacting with the Cloudflare API. When possible, use API tokens instead of Global API keys. **Example:**X-Auth-Key: 144c9defac04969c7bfad8efaa8ea194
##### Accepted Permissions (at least one required) `Vectorize Write``Vectorize Read` ##### ParametersExpand Collapse account\_id: str Identifier maxLength32 [Link to this property](<#(resource)%20vectorize.indexes%20%3E%20(method)%20query%20%3E%20(params)%20default%20%3E%20(param)%20account_id%20%3E%20(schema)>) index\_name: str [Link to this property](<#(resource)%20vectorize.indexes%20%3E%20(method)%20query%20%3E%20(params)%20default%20%3E%20(param)%20index_name%20%3E%20(schema)>) vector: Iterable\[float] The search vector that will be used to find the nearest neighbors. [Link to this property](<#(resource)%20vectorize.indexes%20%3E%20(method)%20query%20%3E%20(params)%20default%20%3E%20(param)%20vector%20%3E%20(schema)>) filter: Optional\[[object]()] A metadata filter expression used to limit nearest neighbor results. [Link to this property](<#(resource)%20vectorize.indexes%20%3E%20(method)%20query%20%3E%20(params)%20default%20%3E%20(param)%20filter%20%3E%20(schema)>)
return\_metadata: Optional\[Literal\["none", "indexed", "all"]] Whether to return no metadata, indexed metadata or all metadata associated with the closest vectors. One of the following: "none" Link to this property "indexed" Link to this property "all" Link to this property
[Link to this property](<#(resource)%20vectorize.indexes%20%3E%20(method)%20query%20%3E%20(params)%20default%20%3E%20(param)%20returnMetadata%20%3E%20(schema)>) return\_values: Optional\[[bool]()] Whether to return the values associated with the closest vectors. [Link to this property](<#(resource)%20vectorize.indexes%20%3E%20(method)%20query%20%3E%20(params)%20default%20%3E%20(param)%20returnValues%20%3E%20(schema)>) top\_k: Optional\[float] The number of nearest neighbors to find. [Link to this property](<#(resource)%20vectorize.indexes%20%3E%20(method)%20query%20%3E%20(params)%20default%20%3E%20(param)%20topK%20%3E%20(schema)>) ##### ReturnsExpand Collapse
class IndexQueryResponse: … count: Optional\[int] Specifies the count of vectors returned by the search Link to this property
matches: Optional\[List\[Match]] Array of vectors matched by the search id: Optional\[str] Identifier for a Vector maxLength64 Link to this property metadata: Optional\[object] Link to this property namespace: Optional\[str] Link to this property score: Optional\[float] The score of the vector according to the index’s distance metric Link to this property values: Optional\[List\[float]] Link to this property
Link to this property
[Link to this property](<#(resource)%20vectorize.indexes%20%3E%20(model)%20index_query_response%20%3E%20(schema)>) ### Query Vectors Python HTTPTypeScriptPythonGoTerraform ``` import os from cloudflare import Cloudflare client = Cloudflare( api_token=os.environ.get("CLOUDFLARE_API_TOKEN"), # This is the default and can be omitted ) response = client.vectorize.indexes.query( index_name="example-index", account_id="023e105f4ecef8ad9ca31a8372d0c353", vector=[0.5, 0.5, 0.5], ) print(response.count) ``` 200 example ``` { "errors": [ { "code": 1000, "message": "message", "documentation_url": "documentation_url", "source": { "pointer": "pointer" } } ], "messages": [ { "code": 1000, "message": "message", "documentation_url": "documentation_url", "source": { "pointer": "pointer" } } ], "result": { "count": 0, "matches": [ { "id": "some-vector-id-023e105f4ecef8ad9ca31a8372d0c353", "metadata": {}, "namespace": "namespace", "score": 0, "values": [ 0 ] } ] }, "success": true } ``` ##### Returns Examples 200 example ``` { "errors": [ { "code": 1000, "message": "message", "documentation_url": "documentation_url", "source": { "pointer": "pointer" } } ], "messages": [ { "code": 1000, "message": "message", "documentation_url": "documentation_url", "source": { "pointer": "pointer" } } ], "result": { "count": 0, "matches": [ { "id": "some-vector-id-023e105f4ecef8ad9ca31a8372d0c353", "metadata": {}, "namespace": "namespace", "score": 0, "values": [ 0 ] } ] }, "success": true } ```