Search vector store

POST/vector_stores/{vector_store_id}/search

Search a vector store for relevant chunks based on a query and file attributes filter.

Path ParametersExpand Collapse

vector_store_id: string

Body ParametersJSONExpand Collapse

query: string or array of string

A query string for a search

Accepts one of the following:

UnionMember0 = string

UnionMember1 = array of string

filters: optional ComparisonFilter { key, type, value } or CompoundFilter { filters, type }

A filter to apply based on file attributes.

Accepts one of the following:

ComparisonFilter = object { key, type, value }

A filter used to compare a specified attribute key to a given value using a defined comparison operation.

key: string

The key to compare against the value.

type: "eq" or "ne" or "gt" or 3 more

Specifies the comparison operator: eq, ne, gt, gte, lt, lte, in, nin.

eq: equals
ne: not equal
gt: greater than
gte: greater than or equal
lt: less than
lte: less than or equal
in: in
nin: not in

Accepts one of the following:

"eq"

"ne"

"gt"

"gte"

"lt"

"lte"

value: string or number or boolean or array of string or number

The value to compare against the attribute key; supports string, number, or boolean types.

Accepts one of the following:

UnionMember0 = string

UnionMember1 = number

UnionMember2 = boolean

UnionMember3 = array of string or number

Accepts one of the following:

UnionMember0 = string

UnionMember1 = number

CompoundFilter = object { filters, type }

Combine multiple filters using and or or.

filters: array of ComparisonFilter { key, type, value } or unknown

Array of filters to combine. Items can be ComparisonFilter or CompoundFilter.

Accepts one of the following:

ComparisonFilter = object { key, type, value }

A filter used to compare a specified attribute key to a given value using a defined comparison operation.

key: string

The key to compare against the value.

type: "eq" or "ne" or "gt" or 3 more

Specifies the comparison operator: eq, ne, gt, gte, lt, lte, in, nin.

eq: equals
ne: not equal
gt: greater than
gte: greater than or equal
lt: less than
lte: less than or equal
in: in
nin: not in

Accepts one of the following:

"eq"

"ne"

"gt"

"gte"

"lt"

"lte"

value: string or number or boolean or array of string or number

The value to compare against the attribute key; supports string, number, or boolean types.

Accepts one of the following:

UnionMember0 = string

UnionMember1 = number

UnionMember2 = boolean

UnionMember3 = array of string or number

Accepts one of the following:

UnionMember0 = string

UnionMember1 = number

UnionMember1 = unknown

type: "and" or "or"

Type of operation: and or or.

Accepts one of the following:

"and"

"or"

max_num_results: optional number

The maximum number of results to return. This number should be between 1 and 50 inclusive.

minimum1

maximum50

ranking_options: optional object { ranker, score_threshold }

Ranking options for search.

ranker: optional "none" or "auto" or "default-2024-11-15"

Enable re-ranking; set to none to disable, which can help reduce latency.

Accepts one of the following:

"none"

"auto"

"default-2024-11-15"

score_threshold: optional number

minimum0

maximum1

rewrite_query: optional boolean

Whether to rewrite the natural language query for vector search.

ReturnsExpand Collapse

data: array of object { attributes, content, file_id, 2 more }

The list of search result items.

attributes: map[string or number or boolean]

Set of 16 key-value pairs that can be attached to an object. This can be useful for storing additional information about the object in a structured format, and querying for objects via API or the dashboard. Keys are strings with a maximum length of 64 characters. Values are strings with a maximum length of 512 characters, booleans, or numbers.

Accepts one of the following:

UnionMember0 = string

UnionMember1 = number

UnionMember2 = boolean

content: array of object { text, type }

Content chunks from the file.

text: string

The text content returned from search.

type: "text"

The type of content.

file_id: string

The ID of the vector store file.

filename: string

The name of the vector store file.

score: number

The similarity score for the result.

minimum0

maximum1

has_more: boolean

Indicates if there are more results to fetch.

next_page: string

The token for the next page, if any.

object: "vector_store.search_results.page"

The object type, which is always vector_store.search_results.page

search_query: array of string

Search vector store

curl -X POST \
https://api.openai.com/v1/vector_stores/vs_abc123/search \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json" \
-d '{"query": "What is the return policy?", "filters": {...}}'

{
  "object": "vector_store.search_results.page",
  "search_query": "What is the return policy?",
  "data": [
    {
      "file_id": "file_123",
      "filename": "document.pdf",
      "score": 0.95,
      "attributes": {
        "author": "John Doe",
        "date": "2023-01-01"
      },
      "content": [
        {
          "type": "text",
          "text": "Relevant chunk"
        }
      ]
    },
    {
      "file_id": "file_456",
      "filename": "notes.txt",
      "score": 0.89,
      "attributes": {
        "author": "Jane Smith",
        "date": "2023-01-02"
      },
      "content": [
        {
          "type": "text",
          "text": "Sample text content from the vector store."
        }
      ]
    }
  ],
  "has_more": false,
  "next_page": null
}

Returns Examples

{
  "object": "vector_store.search_results.page",
  "search_query": "What is the return policy?",
  "data": [
    {
      "file_id": "file_123",
      "filename": "document.pdf",
      "score": 0.95,
      "attributes": {
        "author": "John Doe",
        "date": "2023-01-01"
      },
      "content": [
        {
          "type": "text",
          "text": "Relevant chunk"
        }
      ]
    },
    {
      "file_id": "file_456",
      "filename": "notes.txt",
      "score": 0.89,
      "attributes": {
        "author": "Jane Smith",
        "date": "2023-01-02"
      },
      "content": [
        {
          "type": "text",
          "text": "Sample text content from the vector store."
        }
      ]
    }
  ],
  "has_more": false,
  "next_page": null
}