Search in vector store

curl --request POST \
  --url https://api.example.com/v1/projects/{project_id}/vector-stores/{vector_store_id}/search \
  --header 'Content-Type: application/json' \
  --header 'x-api-key: <api-key>' \
  --header 'x-selected-account-id: <api-key>' \
  --data '
{
  "query": "<string>",
  "top_k": 123,
  "filters": {},
  "rerank_config": {
    "model": "<string>",
    "top_n": 2,
    "instruction": "<string>"
  }
}
'

import requests

url = "https://api.example.com/v1/projects/{project_id}/vector-stores/{vector_store_id}/search"

payload = {
    "query": "<string>",
    "top_k": 123,
    "filters": {},
    "rerank_config": {
        "model": "<string>",
        "top_n": 2,
        "instruction": "<string>"
    }
}
headers = {
    "x-api-key": "<api-key>",
    "x-selected-account-id": "<api-key>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {
    'x-api-key': '<api-key>',
    'x-selected-account-id': '<api-key>',
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    query: '<string>',
    top_k: 123,
    filters: {},
    rerank_config: {model: '<string>', top_n: 2, instruction: '<string>'}
  })
};

fetch('https://api.example.com/v1/projects/{project_id}/vector-stores/{vector_store_id}/search', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.example.com/v1/projects/{project_id}/vector-stores/{vector_store_id}/search",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'query' => '<string>',
    'top_k' => 123,
    'filters' => [
        
    ],
    'rerank_config' => [
        'model' => '<string>',
        'top_n' => 2,
        'instruction' => '<string>'
    ]
  ]),
  CURLOPT_HTTPHEADER => [
    "Content-Type: application/json",
    "x-api-key: <api-key>",
    "x-selected-account-id: <api-key>"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://api.example.com/v1/projects/{project_id}/vector-stores/{vector_store_id}/search"

	payload := strings.NewReader("{\n  \"query\": \"<string>\",\n  \"top_k\": 123,\n  \"filters\": {},\n  \"rerank_config\": {\n    \"model\": \"<string>\",\n    \"top_n\": 2,\n    \"instruction\": \"<string>\"\n  }\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("x-api-key", "<api-key>")
	req.Header.Add("x-selected-account-id", "<api-key>")
	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.post("https://api.example.com/v1/projects/{project_id}/vector-stores/{vector_store_id}/search")
  .header("x-api-key", "<api-key>")
  .header("x-selected-account-id", "<api-key>")
  .header("Content-Type", "application/json")
  .body("{\n  \"query\": \"<string>\",\n  \"top_k\": 123,\n  \"filters\": {},\n  \"rerank_config\": {\n    \"model\": \"<string>\",\n    \"top_n\": 2,\n    \"instruction\": \"<string>\"\n  }\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.example.com/v1/projects/{project_id}/vector-stores/{vector_store_id}/search")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["x-api-key"] = '<api-key>'
request["x-selected-account-id"] = '<api-key>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"query\": \"<string>\",\n  \"top_k\": 123,\n  \"filters\": {},\n  \"rerank_config\": {\n    \"model\": \"<string>\",\n    \"top_n\": 2,\n    \"instruction\": \"<string>\"\n  }\n}"

response = http.request(request)
puts response.read_body

{
  "chunks": [
    {
      "content": "<string>",
      "blocks": [
        {
          "type": "<string>",
          "content": "<string>",
          "bbox": {
            "left": 123,
            "top": 123,
            "width": 123,
            "height": 123
          },
          "confidence": 123,
          "page_number": 0
        }
      ],
      "score": 123,
      "file_id": "<string>",
      "parse_result_id": "<string>",
      "metadata": {}
    }
  ]
}

{
  "detail": [
    {
      "loc": [
        "<string>"
      ],
      "msg": "<string>",
      "type": "<string>",
      "input": "<unknown>",
      "ctx": {}
    }
  ]
}

Vector Stores

Search in vector store

Perform semantic search within a vector store.

This endpoint performs vector-based semantic search to find the most relevant content based on the provided query. The search uses embeddings to find semantically similar content.

Search Parameters:

query: The search query text
top_k: Number of results to return (ranked by relevance)
filters: Optional filters to narrow search scope (e.g., by file_id)

Authentication:

Credentials can be provided either through project-level credentials or request-level credentials
For SGP Knowledge Base, SGP credentials are required

Returns:

Ranked list of relevant content chunks
Each chunk includes content, source blocks, relevance score, and parse result ID
Results are ordered by relevance score (highest first)

Example Request:

{
    "query": "What are the main features of the product?",
    "top_k": 5,
    "filters": {
        "file_id": "file_123"
    },
    "credentials": {
        "sgp": {
            "api_key": "your-api-key",
            "base_url": "https://api.example.com"
        }
    }
}

Example Response:

{
    "chunks": [
        {
            "content": "The product includes advanced analytics, real-time monitoring, and automated reporting features.",
            "blocks": [
                {
                    "id": "block_123",
                    "content": "The product includes advanced analytics...",
                    "type": "text"
                }
            ],
            "score": 0.95,
            "parse_result_id": "parse_123"
        }
    ]
}

POST

projects

{project_id}

vector-stores

{vector_store_id}

Search in vector store

curl --request POST \
  --url https://api.example.com/v1/projects/{project_id}/vector-stores/{vector_store_id}/search \
  --header 'Content-Type: application/json' \
  --header 'x-api-key: <api-key>' \
  --header 'x-selected-account-id: <api-key>' \
  --data '
{
  "query": "<string>",
  "top_k": 123,
  "filters": {},
  "rerank_config": {
    "model": "<string>",
    "top_n": 2,
    "instruction": "<string>"
  }
}
'

import requests

url = "https://api.example.com/v1/projects/{project_id}/vector-stores/{vector_store_id}/search"

payload = {
    "query": "<string>",
    "top_k": 123,
    "filters": {},
    "rerank_config": {
        "model": "<string>",
        "top_n": 2,
        "instruction": "<string>"
    }
}
headers = {
    "x-api-key": "<api-key>",
    "x-selected-account-id": "<api-key>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {
    'x-api-key': '<api-key>',
    'x-selected-account-id': '<api-key>',
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    query: '<string>',
    top_k: 123,
    filters: {},
    rerank_config: {model: '<string>', top_n: 2, instruction: '<string>'}
  })
};

fetch('https://api.example.com/v1/projects/{project_id}/vector-stores/{vector_store_id}/search', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.example.com/v1/projects/{project_id}/vector-stores/{vector_store_id}/search",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'query' => '<string>',
    'top_k' => 123,
    'filters' => [
        
    ],
    'rerank_config' => [
        'model' => '<string>',
        'top_n' => 2,
        'instruction' => '<string>'
    ]
  ]),
  CURLOPT_HTTPHEADER => [
    "Content-Type: application/json",
    "x-api-key: <api-key>",
    "x-selected-account-id: <api-key>"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://api.example.com/v1/projects/{project_id}/vector-stores/{vector_store_id}/search"

	payload := strings.NewReader("{\n  \"query\": \"<string>\",\n  \"top_k\": 123,\n  \"filters\": {},\n  \"rerank_config\": {\n    \"model\": \"<string>\",\n    \"top_n\": 2,\n    \"instruction\": \"<string>\"\n  }\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("x-api-key", "<api-key>")
	req.Header.Add("x-selected-account-id", "<api-key>")
	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.post("https://api.example.com/v1/projects/{project_id}/vector-stores/{vector_store_id}/search")
  .header("x-api-key", "<api-key>")
  .header("x-selected-account-id", "<api-key>")
  .header("Content-Type", "application/json")
  .body("{\n  \"query\": \"<string>\",\n  \"top_k\": 123,\n  \"filters\": {},\n  \"rerank_config\": {\n    \"model\": \"<string>\",\n    \"top_n\": 2,\n    \"instruction\": \"<string>\"\n  }\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.example.com/v1/projects/{project_id}/vector-stores/{vector_store_id}/search")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["x-api-key"] = '<api-key>'
request["x-selected-account-id"] = '<api-key>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"query\": \"<string>\",\n  \"top_k\": 123,\n  \"filters\": {},\n  \"rerank_config\": {\n    \"model\": \"<string>\",\n    \"top_n\": 2,\n    \"instruction\": \"<string>\"\n  }\n}"

response = http.request(request)
puts response.read_body

{
  "chunks": [
    {
      "content": "<string>",
      "blocks": [
        {
          "type": "<string>",
          "content": "<string>",
          "bbox": {
            "left": 123,
            "top": 123,
            "width": 123,
            "height": 123
          },
          "confidence": 123,
          "page_number": 0
        }
      ],
      "score": 123,
      "file_id": "<string>",
      "parse_result_id": "<string>",
      "metadata": {}
    }
  ]
}

{
  "detail": [
    {
      "loc": [
        "<string>"
      ],
      "msg": "<string>",
      "type": "<string>",
      "input": "<unknown>",
      "ctx": {}
    }
  ]
}

Authorizations

x-api-key

string

header

required

API key for authentication

x-selected-account-id

string

header

required

Selected Account ID

Path Parameters

project_id

string

required

vector_store_id

string

required

Body

application/json

Search parameters for vector store engines. Extend this model to add new parameters without changing the engine interface.

query

string

required

Query to search for

top_k

integer | null

Number of results to return

filters

Filters · object | null

Filters to apply to the search. For example, {file_id: 123}

Show child attributes

rerank_config

RerankConfig · object | null

Reranking configuration. This is only applicable for SGP Vector Stores.

Show child attributes

query_type

enum<string> | null

Type of query to perform.

Available options:

semantic,

lexical,

hybrid

Response

Search completed successfully

chunks

VectorStoreChunk · object[]

required

Chunks of the search result

Show child attributes

Remove files from vector store Search in vector store's file

⌘I

Projects

Files

Parse

Vector Stores

Extract

Research

Jobs

Indexes

Search in vector store

Authorizations

Path Parameters

Body

Response