Search documents
curl --request POST \
--url https://api.bigdata.com/v1/search \
--header 'Content-Type: application/json' \
--header 'X-API-KEY: <api-key>' \
--data '
{
"search_mode": "fast",
"query": {
"text": "Type a question to retrieve documents chunks"
}
}
'import requests
url = "https://api.bigdata.com/v1/search"
payload = {
"search_mode": "fast",
"query": { "text": "Type a question to retrieve documents chunks" }
}
headers = {
"X-API-KEY": "<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>', 'Content-Type': 'application/json'},
body: JSON.stringify({
search_mode: 'fast',
query: {text: 'Type a question to retrieve documents chunks'}
})
};
fetch('https://api.bigdata.com/v1/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.bigdata.com/v1/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([
'search_mode' => 'fast',
'query' => [
'text' => 'Type a question to retrieve documents chunks'
]
]),
CURLOPT_HTTPHEADER => [
"Content-Type: application/json",
"X-API-KEY: <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.bigdata.com/v1/search"
payload := strings.NewReader("{\n \"search_mode\": \"fast\",\n \"query\": {\n \"text\": \"Type a question to retrieve documents chunks\"\n }\n}")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("X-API-KEY", "<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.bigdata.com/v1/search")
.header("X-API-KEY", "<api-key>")
.header("Content-Type", "application/json")
.body("{\n \"search_mode\": \"fast\",\n \"query\": {\n \"text\": \"Type a question to retrieve documents chunks\"\n }\n}")
.asString();require 'uri'
require 'net/http'
url = URI("https://api.bigdata.com/v1/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["Content-Type"] = 'application/json'
request.body = "{\n \"search_mode\": \"fast\",\n \"query\": {\n \"text\": \"Type a question to retrieve documents chunks\"\n }\n}"
response = http.request(request)
puts response.read_body{
"results": [
{
"id": "57BB2AD919....",
"headline": "Headline example: Microsoft Corp.: Q3 2025 Earnings Call",
"timestamp": "2025-04-30T21:30:00Z",
"source": {
"id": "D4B903",
"name": "Factset Transcripts",
"rank": "RANK_1"
},
"url": "https://www.benzinga.com/node/45117886?utm_campaign=partner_feed&utm_medium=feed&utm_source=ravenpack",
"chunks": [
{
"cnum": 7,
"text": "Microsoft will provide forward-looking guidance on its earnings conference call Wednesday, which can be viewed below.\nMSFT Price Action: Microsoft stock is up 5.5% to $417.17 year-over-year in after-hours trading Wednesday versus a 52-week trading range of $344.79 to $468.35.",
"relevance": 0.8949412447701082,
"sentiment": 0.33,
"detections": [
{
"id": "ACE54B",
"start": 23,
"end": 38,
"type": "entity"
}
],
"text_locations": [
{
"paragraph_num": 1,
"sentence_num": 1
}
]
}
],
"document_type": "Earnings Call"
}
],
"usage": {
"api_query_units": 0.7
},
"external_results": {},
"metadata": {
"request_id": "user_2k3Z4SerTUIieyCfQhGR5UF2Af3",
"timestamp": "2025-09-12T11:10:46.019077+00:00",
"audit": {
"queries": [
{
"auto_enrich_filters": true,
"filters": {
"document_type": {
"values": [
{
"type": "TRANSCRIPT",
"subtypes": [
"EARNINGS_CALL"
]
}
]
},
"reporting_entities": [
"BA9E0C"
],
"reporting_periods": [
{
"fiscal_year": 2025,
"fiscal_quarter": 4
}
]
},
"max_chunks": 100,
"ranking_params": {
"source_boost": 1,
"freshness_boost": 1,
"reranker": {
"enabled": true
}
}
}
]
}
}
}Search
Search documents
Easily find the most relevant information from trusted sources and your own data. Use it to power agents that give accurate, real-time answers.
POST
/
v1
/
search
Search documents
curl --request POST \
--url https://api.bigdata.com/v1/search \
--header 'Content-Type: application/json' \
--header 'X-API-KEY: <api-key>' \
--data '
{
"search_mode": "fast",
"query": {
"text": "Type a question to retrieve documents chunks"
}
}
'import requests
url = "https://api.bigdata.com/v1/search"
payload = {
"search_mode": "fast",
"query": { "text": "Type a question to retrieve documents chunks" }
}
headers = {
"X-API-KEY": "<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>', 'Content-Type': 'application/json'},
body: JSON.stringify({
search_mode: 'fast',
query: {text: 'Type a question to retrieve documents chunks'}
})
};
fetch('https://api.bigdata.com/v1/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.bigdata.com/v1/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([
'search_mode' => 'fast',
'query' => [
'text' => 'Type a question to retrieve documents chunks'
]
]),
CURLOPT_HTTPHEADER => [
"Content-Type: application/json",
"X-API-KEY: <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.bigdata.com/v1/search"
payload := strings.NewReader("{\n \"search_mode\": \"fast\",\n \"query\": {\n \"text\": \"Type a question to retrieve documents chunks\"\n }\n}")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("X-API-KEY", "<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.bigdata.com/v1/search")
.header("X-API-KEY", "<api-key>")
.header("Content-Type", "application/json")
.body("{\n \"search_mode\": \"fast\",\n \"query\": {\n \"text\": \"Type a question to retrieve documents chunks\"\n }\n}")
.asString();require 'uri'
require 'net/http'
url = URI("https://api.bigdata.com/v1/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["Content-Type"] = 'application/json'
request.body = "{\n \"search_mode\": \"fast\",\n \"query\": {\n \"text\": \"Type a question to retrieve documents chunks\"\n }\n}"
response = http.request(request)
puts response.read_body{
"results": [
{
"id": "57BB2AD919....",
"headline": "Headline example: Microsoft Corp.: Q3 2025 Earnings Call",
"timestamp": "2025-04-30T21:30:00Z",
"source": {
"id": "D4B903",
"name": "Factset Transcripts",
"rank": "RANK_1"
},
"url": "https://www.benzinga.com/node/45117886?utm_campaign=partner_feed&utm_medium=feed&utm_source=ravenpack",
"chunks": [
{
"cnum": 7,
"text": "Microsoft will provide forward-looking guidance on its earnings conference call Wednesday, which can be viewed below.\nMSFT Price Action: Microsoft stock is up 5.5% to $417.17 year-over-year in after-hours trading Wednesday versus a 52-week trading range of $344.79 to $468.35.",
"relevance": 0.8949412447701082,
"sentiment": 0.33,
"detections": [
{
"id": "ACE54B",
"start": 23,
"end": 38,
"type": "entity"
}
],
"text_locations": [
{
"paragraph_num": 1,
"sentence_num": 1
}
]
}
],
"document_type": "Earnings Call"
}
],
"usage": {
"api_query_units": 0.7
},
"external_results": {},
"metadata": {
"request_id": "user_2k3Z4SerTUIieyCfQhGR5UF2Af3",
"timestamp": "2025-09-12T11:10:46.019077+00:00",
"audit": {
"queries": [
{
"auto_enrich_filters": true,
"filters": {
"document_type": {
"values": [
{
"type": "TRANSCRIPT",
"subtypes": [
"EARNINGS_CALL"
]
}
]
},
"reporting_entities": [
"BA9E0C"
],
"reporting_periods": [
{
"fiscal_year": 2025,
"fiscal_quarter": 4
}
]
},
"max_chunks": 100,
"ranking_params": {
"source_boost": 1,
"freshness_boost": 1,
"reranker": {
"enabled": true
}
}
}
]
}
}
}Authorizations
Body
application/json
fast (default): Runs a single query using the specified filters. Best for pre-processed queries where you control the filters.
smart: Analyzes the query text to automatically define search filters and runs multiple sub-queries to ensure better coverage. Ideal for sending user questions directly without pre-processing. When using smart mode, only timestamp and source filters are allowed; using any other filters will result in a 400 Bad Request error.
Available options:
fast, smart Show child attributes
Show child attributes
When set to true, the response metadata will include an audit object containing the resolved queries that were actually executed. Useful for debugging and understanding how the system interpreted your request.
Response
200 - application/json
Search results
Array of documents with one or more text chunks that match the query criteria.
Show child attributes
Show child attributes
API usage for the request. Shape depends on the account consumption model.
- Query Units
- Tokens
Show child attributes
Show child attributes
External search results grouped by source (e.g. web).
Show child attributes
Show child attributes
Request metadata and timing information.
Show child attributes
Show child attributes
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