Answer API - Web-enhanced AI responses

curl --request POST \
  --url https://api.llmlayer.dev/api/v2/answer \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "query": "What are the latest developments in quantum computing?",
  "model": "llmlayer-web",
  "location": "us",
  "provider_key": "<string>",
  "system_prompt": "<string>",
  "response_language": "auto",
  "answer_type": "markdown",
  "search_type": "general",
  "json_schema": "{\"type\":\"object\",\"properties\":{\"summary\":{\"type\":\"string\"},\"key_points\":{\"type\":\"array\",\"items\":{\"type\":\"string\"}}}}",
  "citations": false,
  "return_sources": false,
  "return_images": false,
  "date_filter": "anytime",
  "max_tokens": 1500,
  "temperature": 0.7,
  "domain_filter": [
    "wikipedia.org",
    "-reddit.com"
  ],
  "max_queries": 3,
  "search_context_size": "medium"
}
'

import requests

url = "https://api.llmlayer.dev/api/v2/answer"

payload = {
    "query": "What are the latest developments in quantum computing?",
    "model": "llmlayer-web",
    "location": "us",
    "provider_key": "<string>",
    "system_prompt": "<string>",
    "response_language": "auto",
    "answer_type": "markdown",
    "search_type": "general",
    "json_schema": "{\"type\":\"object\",\"properties\":{\"summary\":{\"type\":\"string\"},\"key_points\":{\"type\":\"array\",\"items\":{\"type\":\"string\"}}}}",
    "citations": False,
    "return_sources": False,
    "return_images": False,
    "date_filter": "anytime",
    "max_tokens": 1500,
    "temperature": 0.7,
    "domain_filter": ["wikipedia.org", "-reddit.com"],
    "max_queries": 3,
    "search_context_size": "medium"
}
headers = {
    "Authorization": "Bearer <token>",
    "Content-Type": "application/json"
}

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

print(response.text)

const options = {
  method: 'POST',
  headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    query: 'What are the latest developments in quantum computing?',
    model: 'llmlayer-web',
    location: 'us',
    provider_key: '<string>',
    system_prompt: '<string>',
    response_language: 'auto',
    answer_type: 'markdown',
    search_type: 'general',
    json_schema: '{"type":"object","properties":{"summary":{"type":"string"},"key_points":{"type":"array","items":{"type":"string"}}}}',
    citations: false,
    return_sources: false,
    return_images: false,
    date_filter: 'anytime',
    max_tokens: 1500,
    temperature: 0.7,
    domain_filter: ['wikipedia.org', '-reddit.com'],
    max_queries: 3,
    search_context_size: 'medium'
  })
};

fetch('https://api.llmlayer.dev/api/v2/answer', 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.llmlayer.dev/api/v2/answer",
  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' => 'What are the latest developments in quantum computing?',
    'model' => 'llmlayer-web',
    'location' => 'us',
    'provider_key' => '<string>',
    'system_prompt' => '<string>',
    'response_language' => 'auto',
    'answer_type' => 'markdown',
    'search_type' => 'general',
    'json_schema' => '{"type":"object","properties":{"summary":{"type":"string"},"key_points":{"type":"array","items":{"type":"string"}}}}',
    'citations' => false,
    'return_sources' => false,
    'return_images' => false,
    'date_filter' => 'anytime',
    'max_tokens' => 1500,
    'temperature' => 0.7,
    'domain_filter' => [
        'wikipedia.org',
        '-reddit.com'
    ],
    'max_queries' => 3,
    'search_context_size' => 'medium'
  ]),
  CURLOPT_HTTPHEADER => [
    "Authorization: Bearer <token>",
    "Content-Type: application/json"
  ],
]);

$response = curl_exec($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.llmlayer.dev/api/v2/answer"

	payload := strings.NewReader("{\n  \"query\": \"What are the latest developments in quantum computing?\",\n  \"model\": \"llmlayer-web\",\n  \"location\": \"us\",\n  \"provider_key\": \"<string>\",\n  \"system_prompt\": \"<string>\",\n  \"response_language\": \"auto\",\n  \"answer_type\": \"markdown\",\n  \"search_type\": \"general\",\n  \"json_schema\": \"{\\\"type\\\":\\\"object\\\",\\\"properties\\\":{\\\"summary\\\":{\\\"type\\\":\\\"string\\\"},\\\"key_points\\\":{\\\"type\\\":\\\"array\\\",\\\"items\\\":{\\\"type\\\":\\\"string\\\"}}}}\",\n  \"citations\": false,\n  \"return_sources\": false,\n  \"return_images\": false,\n  \"date_filter\": \"anytime\",\n  \"max_tokens\": 1500,\n  \"temperature\": 0.7,\n  \"domain_filter\": [\n    \"wikipedia.org\",\n    \"-reddit.com\"\n  ],\n  \"max_queries\": 3,\n  \"search_context_size\": \"medium\"\n}")

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

	req.Header.Add("Authorization", "Bearer <token>")
	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.llmlayer.dev/api/v2/answer")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"query\": \"What are the latest developments in quantum computing?\",\n  \"model\": \"llmlayer-web\",\n  \"location\": \"us\",\n  \"provider_key\": \"<string>\",\n  \"system_prompt\": \"<string>\",\n  \"response_language\": \"auto\",\n  \"answer_type\": \"markdown\",\n  \"search_type\": \"general\",\n  \"json_schema\": \"{\\\"type\\\":\\\"object\\\",\\\"properties\\\":{\\\"summary\\\":{\\\"type\\\":\\\"string\\\"},\\\"key_points\\\":{\\\"type\\\":\\\"array\\\",\\\"items\\\":{\\\"type\\\":\\\"string\\\"}}}}\",\n  \"citations\": false,\n  \"return_sources\": false,\n  \"return_images\": false,\n  \"date_filter\": \"anytime\",\n  \"max_tokens\": 1500,\n  \"temperature\": 0.7,\n  \"domain_filter\": [\n    \"wikipedia.org\",\n    \"-reddit.com\"\n  ],\n  \"max_queries\": 3,\n  \"search_context_size\": \"medium\"\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.llmlayer.dev/api/v2/answer")

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

request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"query\": \"What are the latest developments in quantum computing?\",\n  \"model\": \"llmlayer-web\",\n  \"location\": \"us\",\n  \"provider_key\": \"<string>\",\n  \"system_prompt\": \"<string>\",\n  \"response_language\": \"auto\",\n  \"answer_type\": \"markdown\",\n  \"search_type\": \"general\",\n  \"json_schema\": \"{\\\"type\\\":\\\"object\\\",\\\"properties\\\":{\\\"summary\\\":{\\\"type\\\":\\\"string\\\"},\\\"key_points\\\":{\\\"type\\\":\\\"array\\\",\\\"items\\\":{\\\"type\\\":\\\"string\\\"}}}}\",\n  \"citations\": false,\n  \"return_sources\": false,\n  \"return_images\": false,\n  \"date_filter\": \"anytime\",\n  \"max_tokens\": 1500,\n  \"temperature\": 0.7,\n  \"domain_filter\": [\n    \"wikipedia.org\",\n    \"-reddit.com\"\n  ],\n  \"max_queries\": 3,\n  \"search_context_size\": \"medium\"\n}"

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

{
  "answer": "<string>",
  "response_time": "2.34",
  "input_tokens": 123,
  "output_tokens": 123,
  "llmlayer_cost": 123,
  "sources": [
    {
      "title": "<string>",
      "link": "<string>",
      "snippet": "<string>"
    }
  ],
  "images": [
    {
      "title": "<string>",
      "imageUrl": "<string>",
      "thumbnailUrl": "<string>",
      "source": "<string>",
      "link": "<string>"
    }
  ],
  "model_cost": 123
}

POST

api

answer

Answer API - Web-enhanced AI responses

curl --request POST \
  --url https://api.llmlayer.dev/api/v2/answer \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "query": "What are the latest developments in quantum computing?",
  "model": "llmlayer-web",
  "location": "us",
  "provider_key": "<string>",
  "system_prompt": "<string>",
  "response_language": "auto",
  "answer_type": "markdown",
  "search_type": "general",
  "json_schema": "{\"type\":\"object\",\"properties\":{\"summary\":{\"type\":\"string\"},\"key_points\":{\"type\":\"array\",\"items\":{\"type\":\"string\"}}}}",
  "citations": false,
  "return_sources": false,
  "return_images": false,
  "date_filter": "anytime",
  "max_tokens": 1500,
  "temperature": 0.7,
  "domain_filter": [
    "wikipedia.org",
    "-reddit.com"
  ],
  "max_queries": 3,
  "search_context_size": "medium"
}
'

import requests

url = "https://api.llmlayer.dev/api/v2/answer"

payload = {
    "query": "What are the latest developments in quantum computing?",
    "model": "llmlayer-web",
    "location": "us",
    "provider_key": "<string>",
    "system_prompt": "<string>",
    "response_language": "auto",
    "answer_type": "markdown",
    "search_type": "general",
    "json_schema": "{\"type\":\"object\",\"properties\":{\"summary\":{\"type\":\"string\"},\"key_points\":{\"type\":\"array\",\"items\":{\"type\":\"string\"}}}}",
    "citations": False,
    "return_sources": False,
    "return_images": False,
    "date_filter": "anytime",
    "max_tokens": 1500,
    "temperature": 0.7,
    "domain_filter": ["wikipedia.org", "-reddit.com"],
    "max_queries": 3,
    "search_context_size": "medium"
}
headers = {
    "Authorization": "Bearer <token>",
    "Content-Type": "application/json"
}

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

print(response.text)

const options = {
  method: 'POST',
  headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    query: 'What are the latest developments in quantum computing?',
    model: 'llmlayer-web',
    location: 'us',
    provider_key: '<string>',
    system_prompt: '<string>',
    response_language: 'auto',
    answer_type: 'markdown',
    search_type: 'general',
    json_schema: '{"type":"object","properties":{"summary":{"type":"string"},"key_points":{"type":"array","items":{"type":"string"}}}}',
    citations: false,
    return_sources: false,
    return_images: false,
    date_filter: 'anytime',
    max_tokens: 1500,
    temperature: 0.7,
    domain_filter: ['wikipedia.org', '-reddit.com'],
    max_queries: 3,
    search_context_size: 'medium'
  })
};

fetch('https://api.llmlayer.dev/api/v2/answer', 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.llmlayer.dev/api/v2/answer",
  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' => 'What are the latest developments in quantum computing?',
    'model' => 'llmlayer-web',
    'location' => 'us',
    'provider_key' => '<string>',
    'system_prompt' => '<string>',
    'response_language' => 'auto',
    'answer_type' => 'markdown',
    'search_type' => 'general',
    'json_schema' => '{"type":"object","properties":{"summary":{"type":"string"},"key_points":{"type":"array","items":{"type":"string"}}}}',
    'citations' => false,
    'return_sources' => false,
    'return_images' => false,
    'date_filter' => 'anytime',
    'max_tokens' => 1500,
    'temperature' => 0.7,
    'domain_filter' => [
        'wikipedia.org',
        '-reddit.com'
    ],
    'max_queries' => 3,
    'search_context_size' => 'medium'
  ]),
  CURLOPT_HTTPHEADER => [
    "Authorization: Bearer <token>",
    "Content-Type: application/json"
  ],
]);

$response = curl_exec($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.llmlayer.dev/api/v2/answer"

	payload := strings.NewReader("{\n  \"query\": \"What are the latest developments in quantum computing?\",\n  \"model\": \"llmlayer-web\",\n  \"location\": \"us\",\n  \"provider_key\": \"<string>\",\n  \"system_prompt\": \"<string>\",\n  \"response_language\": \"auto\",\n  \"answer_type\": \"markdown\",\n  \"search_type\": \"general\",\n  \"json_schema\": \"{\\\"type\\\":\\\"object\\\",\\\"properties\\\":{\\\"summary\\\":{\\\"type\\\":\\\"string\\\"},\\\"key_points\\\":{\\\"type\\\":\\\"array\\\",\\\"items\\\":{\\\"type\\\":\\\"string\\\"}}}}\",\n  \"citations\": false,\n  \"return_sources\": false,\n  \"return_images\": false,\n  \"date_filter\": \"anytime\",\n  \"max_tokens\": 1500,\n  \"temperature\": 0.7,\n  \"domain_filter\": [\n    \"wikipedia.org\",\n    \"-reddit.com\"\n  ],\n  \"max_queries\": 3,\n  \"search_context_size\": \"medium\"\n}")

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

	req.Header.Add("Authorization", "Bearer <token>")
	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.llmlayer.dev/api/v2/answer")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"query\": \"What are the latest developments in quantum computing?\",\n  \"model\": \"llmlayer-web\",\n  \"location\": \"us\",\n  \"provider_key\": \"<string>\",\n  \"system_prompt\": \"<string>\",\n  \"response_language\": \"auto\",\n  \"answer_type\": \"markdown\",\n  \"search_type\": \"general\",\n  \"json_schema\": \"{\\\"type\\\":\\\"object\\\",\\\"properties\\\":{\\\"summary\\\":{\\\"type\\\":\\\"string\\\"},\\\"key_points\\\":{\\\"type\\\":\\\"array\\\",\\\"items\\\":{\\\"type\\\":\\\"string\\\"}}}}\",\n  \"citations\": false,\n  \"return_sources\": false,\n  \"return_images\": false,\n  \"date_filter\": \"anytime\",\n  \"max_tokens\": 1500,\n  \"temperature\": 0.7,\n  \"domain_filter\": [\n    \"wikipedia.org\",\n    \"-reddit.com\"\n  ],\n  \"max_queries\": 3,\n  \"search_context_size\": \"medium\"\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.llmlayer.dev/api/v2/answer")

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

request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"query\": \"What are the latest developments in quantum computing?\",\n  \"model\": \"llmlayer-web\",\n  \"location\": \"us\",\n  \"provider_key\": \"<string>\",\n  \"system_prompt\": \"<string>\",\n  \"response_language\": \"auto\",\n  \"answer_type\": \"markdown\",\n  \"search_type\": \"general\",\n  \"json_schema\": \"{\\\"type\\\":\\\"object\\\",\\\"properties\\\":{\\\"summary\\\":{\\\"type\\\":\\\"string\\\"},\\\"key_points\\\":{\\\"type\\\":\\\"array\\\",\\\"items\\\":{\\\"type\\\":\\\"string\\\"}}}}\",\n  \"citations\": false,\n  \"return_sources\": false,\n  \"return_images\": false,\n  \"date_filter\": \"anytime\",\n  \"max_tokens\": 1500,\n  \"temperature\": 0.7,\n  \"domain_filter\": [\n    \"wikipedia.org\",\n    \"-reddit.com\"\n  ],\n  \"max_queries\": 3,\n  \"search_context_size\": \"medium\"\n}"

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

{
  "answer": "<string>",
  "response_time": "2.34",
  "input_tokens": 123,
  "output_tokens": 123,
  "llmlayer_cost": 123,
  "sources": [
    {
      "title": "<string>",
      "link": "<string>",
      "snippet": "<string>"
    }
  ],
  "images": [
    {
      "title": "<string>",
      "imageUrl": "<string>",
      "thumbnailUrl": "<string>",
      "source": "<string>",
      "link": "<string>"
    }
  ],
  "model_cost": 123
}

Authorizations

Authorization

string

header

required

Bearer token authentication using your LLMLayer API key. Include in Authorization header as: Bearer YOUR_LLMLAYER_API_KEY

Body

application/json

query

string

required

The search query or question to answer

Example:

"What are the latest developments in quantum computing?"

model

string

required

LLM model to use (e.g., llmlayer-web, llmlayer-fast, openai/gpt-4o-mini, openai/gpt-5.1)

Example:

"llmlayer-web"

location

string

default:us

Country code for localized search results (us, uk, ca, etc.)

Example:

"us"

provider_key

string | null

Deprecated. Accepted for backward compatibility but currently ignored by the API.

system_prompt

string | null

Custom system prompt to override default behavior. Use this to customize how the LLM processes the search results.

response_language

string

default:auto

Language for the response. 'auto' detects from query, or specify language code (en, es, fr, etc.)

Example:

"auto"

answer_type

enum<string>

default:markdown

Format of the response. Use 'json' with json_schema for structured output.

Available options:

markdown,

html,

json

search_type

enum<string>

default:general

Type of web search to perform. 'news' provides recent news articles.

Available options:

general,

news

json_schema

string | null

JSON schema as string for structured responses. Required when answer_type='json'. The LLM will format its response according to this schema.

Example:

"{\"type\":\"object\",\"properties\":{\"summary\":{\"type\":\"string\"},\"key_points\":{\"type\":\"array\",\"items\":{\"type\":\"string\"}}}}"

citations

boolean

default:false

Include inline citations [1], [2] in the response text

return_sources

boolean

default:false

Return the source documents used for answer generation

return_images

boolean

default:false

Return relevant images from image search. Adds $0.001 to cost.

date_filter

enum<string>

default:anytime

Filter search results by recency. Useful for time-sensitive queries.

Available options:

anytime,

hour,

day,

week,

month,

year

max_tokens

integer

default:1500

Maximum tokens in the LLM response. Affects cost.

Required range: x >= 1

temperature

number

default:0.7

Controls response randomness. 0=deterministic, 2=very creative. Not supported by all models.

Required range: 0 <= x <= 2

domain_filter

string[] | null

Include or exclude specific domains. Use '-' prefix to exclude (e.g., ['-reddit.com', 'wikipedia.org'])

Example:

["wikipedia.org", "-reddit.com"]

max_queries

integer

default:1

Number of search queries to generate from the user query. More queries = broader search and higher LLMLayer fee. Token-priced models use $0.004 per query; fixed-price LLMLayer models use their model-specific per-query price.

Required range: 1 <= x <= 4

Example:

3

search_context_size

enum<string>

default:medium

Amount of search context to extract and pass to LLM. 'high' provides more context but uses more tokens.

Available options:

low,

medium,

high

Response

Successful response with AI-generated answer

answer

required

The AI-generated answer. String for markdown/html, object for JSON responses.

response_time

string

required

Total processing time in seconds

Example:

"2.34"

input_tokens

integer

required

Total input tokens processed (includes query generation + main LLM call + internal system prompts)

output_tokens

integer

required

Total output tokens generated (includes query generation + main LLM response)

llmlayer_cost

number

required

Cost in USD for LLMLayer search infrastructure. Base cost varies by max_queries and return_images.

sources

object[]

Source documents used (only when return_sources=true)

Show child attributes

images

object[]

Relevant images (only when return_images=true)

Show child attributes

model_cost

number | null

Cost in USD for LLM usage. Null for fixed-price LLMLayer models.

API Reference Answer API - Stream responses in real-time

API Documentation

Endpoint

Answer API - Web-enhanced AI responses

Authorizations

Body

Response