curl --request POST \
--url https://api.aisa.one/apis/v1/dataforseo/ai_optimization/claude/llm_responses/task_post \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '
[
{
"system_message": "communicate as if we are in a business meeting",
"message_chain": [
{
"role": "user",
"message": "Hello, what’s up?"
},
{
"role": "ai",
"message": "Hello! I’m doing well, thank you. How can I assist you today? Are there any specific topics or projects you’d like to discuss in our meeting?"
}
],
"max_output_tokens": 1024,
"temperature": 0.3,
"web_search_country_iso_code": "FR",
"model_name": "claude-sonnet-4-0",
"web_search": true,
"user_prompt": "provide information on how relevant the amusement park business is in France now"
}
]
'import requests
url = "https://api.aisa.one/apis/v1/dataforseo/ai_optimization/claude/llm_responses/task_post"
payload = [
{
"system_message": "communicate as if we are in a business meeting",
"message_chain": [
{
"role": "user",
"message": "Hello, what’s up?"
},
{
"role": "ai",
"message": "Hello! I’m doing well, thank you. How can I assist you today? Are there any specific topics or projects you’d like to discuss in our meeting?"
}
],
"max_output_tokens": 1024,
"temperature": 0.3,
"web_search_country_iso_code": "FR",
"model_name": "claude-sonnet-4-0",
"web_search": True,
"user_prompt": "provide information on how relevant the amusement park business is in France now"
}
]
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([
{
system_message: 'communicate as if we are in a business meeting',
message_chain: [
{role: 'user', message: 'Hello, what’s up?'},
{
role: 'ai',
message: 'Hello! I’m doing well, thank you. How can I assist you today? Are there any specific topics or projects you’d like to discuss in our meeting?'
}
],
max_output_tokens: 1024,
temperature: 0.3,
web_search_country_iso_code: 'FR',
model_name: 'claude-sonnet-4-0',
web_search: true,
user_prompt: 'provide information on how relevant the amusement park business is in France now'
}
])
};
fetch('https://api.aisa.one/apis/v1/dataforseo/ai_optimization/claude/llm_responses/task_post', 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.aisa.one/apis/v1/dataforseo/ai_optimization/claude/llm_responses/task_post",
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([
[
'system_message' => 'communicate as if we are in a business meeting',
'message_chain' => [
[
'role' => 'user',
'message' => 'Hello, what’s up?'
],
[
'role' => 'ai',
'message' => 'Hello! I’m doing well, thank you. How can I assist you today? Are there any specific topics or projects you’d like to discuss in our meeting?'
]
],
'max_output_tokens' => 1024,
'temperature' => 0.3,
'web_search_country_iso_code' => 'FR',
'model_name' => 'claude-sonnet-4-0',
'web_search' => true,
'user_prompt' => 'provide information on how relevant the amusement park business is in France now'
]
]),
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.aisa.one/apis/v1/dataforseo/ai_optimization/claude/llm_responses/task_post"
payload := strings.NewReader("[\n {\n \"system_message\": \"communicate as if we are in a business meeting\",\n \"message_chain\": [\n {\n \"role\": \"user\",\n \"message\": \"Hello, what’s up?\"\n },\n {\n \"role\": \"ai\",\n \"message\": \"Hello! I’m doing well, thank you. How can I assist you today? Are there any specific topics or projects you’d like to discuss in our meeting?\"\n }\n ],\n \"max_output_tokens\": 1024,\n \"temperature\": 0.3,\n \"web_search_country_iso_code\": \"FR\",\n \"model_name\": \"claude-sonnet-4-0\",\n \"web_search\": true,\n \"user_prompt\": \"provide information on how relevant the amusement park business is in France now\"\n }\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.aisa.one/apis/v1/dataforseo/ai_optimization/claude/llm_responses/task_post")
.header("Authorization", "Bearer <token>")
.header("Content-Type", "application/json")
.body("[\n {\n \"system_message\": \"communicate as if we are in a business meeting\",\n \"message_chain\": [\n {\n \"role\": \"user\",\n \"message\": \"Hello, what’s up?\"\n },\n {\n \"role\": \"ai\",\n \"message\": \"Hello! I’m doing well, thank you. How can I assist you today? Are there any specific topics or projects you’d like to discuss in our meeting?\"\n }\n ],\n \"max_output_tokens\": 1024,\n \"temperature\": 0.3,\n \"web_search_country_iso_code\": \"FR\",\n \"model_name\": \"claude-sonnet-4-0\",\n \"web_search\": true,\n \"user_prompt\": \"provide information on how relevant the amusement park business is in France now\"\n }\n]")
.asString();require 'uri'
require 'net/http'
url = URI("https://api.aisa.one/apis/v1/dataforseo/ai_optimization/claude/llm_responses/task_post")
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 {\n \"system_message\": \"communicate as if we are in a business meeting\",\n \"message_chain\": [\n {\n \"role\": \"user\",\n \"message\": \"Hello, what’s up?\"\n },\n {\n \"role\": \"ai\",\n \"message\": \"Hello! I’m doing well, thank you. How can I assist you today? Are there any specific topics or projects you’d like to discuss in our meeting?\"\n }\n ],\n \"max_output_tokens\": 1024,\n \"temperature\": 0.3,\n \"web_search_country_iso_code\": \"FR\",\n \"model_name\": \"claude-sonnet-4-0\",\n \"web_search\": true,\n \"user_prompt\": \"provide information on how relevant the amusement park business is in France now\"\n }\n]"
response = http.request(request)
puts response.read_body{
"version": "<string>",
"status_code": 123,
"status_message": "<string>",
"time": "<string>",
"cost": 123,
"tasks_count": 123,
"tasks_error": 123,
"tasks": [
{
"id": "<string>",
"status_code": 123,
"status_message": "<string>",
"time": "<string>",
"cost": 123,
"result_count": 123,
"path": [
"<string>"
],
"data": {},
"result": {}
}
]
}设置 LLM Responses Claude 任务
把 Claude 的 prompt 排队而不是等回复,返回任务 id。
curl --request POST \
--url https://api.aisa.one/apis/v1/dataforseo/ai_optimization/claude/llm_responses/task_post \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '
[
{
"system_message": "communicate as if we are in a business meeting",
"message_chain": [
{
"role": "user",
"message": "Hello, what’s up?"
},
{
"role": "ai",
"message": "Hello! I’m doing well, thank you. How can I assist you today? Are there any specific topics or projects you’d like to discuss in our meeting?"
}
],
"max_output_tokens": 1024,
"temperature": 0.3,
"web_search_country_iso_code": "FR",
"model_name": "claude-sonnet-4-0",
"web_search": true,
"user_prompt": "provide information on how relevant the amusement park business is in France now"
}
]
'import requests
url = "https://api.aisa.one/apis/v1/dataforseo/ai_optimization/claude/llm_responses/task_post"
payload = [
{
"system_message": "communicate as if we are in a business meeting",
"message_chain": [
{
"role": "user",
"message": "Hello, what’s up?"
},
{
"role": "ai",
"message": "Hello! I’m doing well, thank you. How can I assist you today? Are there any specific topics or projects you’d like to discuss in our meeting?"
}
],
"max_output_tokens": 1024,
"temperature": 0.3,
"web_search_country_iso_code": "FR",
"model_name": "claude-sonnet-4-0",
"web_search": True,
"user_prompt": "provide information on how relevant the amusement park business is in France now"
}
]
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([
{
system_message: 'communicate as if we are in a business meeting',
message_chain: [
{role: 'user', message: 'Hello, what’s up?'},
{
role: 'ai',
message: 'Hello! I’m doing well, thank you. How can I assist you today? Are there any specific topics or projects you’d like to discuss in our meeting?'
}
],
max_output_tokens: 1024,
temperature: 0.3,
web_search_country_iso_code: 'FR',
model_name: 'claude-sonnet-4-0',
web_search: true,
user_prompt: 'provide information on how relevant the amusement park business is in France now'
}
])
};
fetch('https://api.aisa.one/apis/v1/dataforseo/ai_optimization/claude/llm_responses/task_post', 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.aisa.one/apis/v1/dataforseo/ai_optimization/claude/llm_responses/task_post",
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([
[
'system_message' => 'communicate as if we are in a business meeting',
'message_chain' => [
[
'role' => 'user',
'message' => 'Hello, what’s up?'
],
[
'role' => 'ai',
'message' => 'Hello! I’m doing well, thank you. How can I assist you today? Are there any specific topics or projects you’d like to discuss in our meeting?'
]
],
'max_output_tokens' => 1024,
'temperature' => 0.3,
'web_search_country_iso_code' => 'FR',
'model_name' => 'claude-sonnet-4-0',
'web_search' => true,
'user_prompt' => 'provide information on how relevant the amusement park business is in France now'
]
]),
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.aisa.one/apis/v1/dataforseo/ai_optimization/claude/llm_responses/task_post"
payload := strings.NewReader("[\n {\n \"system_message\": \"communicate as if we are in a business meeting\",\n \"message_chain\": [\n {\n \"role\": \"user\",\n \"message\": \"Hello, what’s up?\"\n },\n {\n \"role\": \"ai\",\n \"message\": \"Hello! I’m doing well, thank you. How can I assist you today? Are there any specific topics or projects you’d like to discuss in our meeting?\"\n }\n ],\n \"max_output_tokens\": 1024,\n \"temperature\": 0.3,\n \"web_search_country_iso_code\": \"FR\",\n \"model_name\": \"claude-sonnet-4-0\",\n \"web_search\": true,\n \"user_prompt\": \"provide information on how relevant the amusement park business is in France now\"\n }\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.aisa.one/apis/v1/dataforseo/ai_optimization/claude/llm_responses/task_post")
.header("Authorization", "Bearer <token>")
.header("Content-Type", "application/json")
.body("[\n {\n \"system_message\": \"communicate as if we are in a business meeting\",\n \"message_chain\": [\n {\n \"role\": \"user\",\n \"message\": \"Hello, what’s up?\"\n },\n {\n \"role\": \"ai\",\n \"message\": \"Hello! I’m doing well, thank you. How can I assist you today? Are there any specific topics or projects you’d like to discuss in our meeting?\"\n }\n ],\n \"max_output_tokens\": 1024,\n \"temperature\": 0.3,\n \"web_search_country_iso_code\": \"FR\",\n \"model_name\": \"claude-sonnet-4-0\",\n \"web_search\": true,\n \"user_prompt\": \"provide information on how relevant the amusement park business is in France now\"\n }\n]")
.asString();require 'uri'
require 'net/http'
url = URI("https://api.aisa.one/apis/v1/dataforseo/ai_optimization/claude/llm_responses/task_post")
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 {\n \"system_message\": \"communicate as if we are in a business meeting\",\n \"message_chain\": [\n {\n \"role\": \"user\",\n \"message\": \"Hello, what’s up?\"\n },\n {\n \"role\": \"ai\",\n \"message\": \"Hello! I’m doing well, thank you. How can I assist you today? Are there any specific topics or projects you’d like to discuss in our meeting?\"\n }\n ],\n \"max_output_tokens\": 1024,\n \"temperature\": 0.3,\n \"web_search_country_iso_code\": \"FR\",\n \"model_name\": \"claude-sonnet-4-0\",\n \"web_search\": true,\n \"user_prompt\": \"provide information on how relevant the amusement park business is in France now\"\n }\n]"
response = http.request(request)
puts response.read_body{
"version": "<string>",
"status_code": 123,
"status_message": "<string>",
"time": "<string>",
"cost": 123,
"tasks_count": 123,
"tasks_error": 123,
"tasks": [
{
"id": "<string>",
"status_code": 123,
"status_message": "<string>",
"time": "<string>",
"cost": 123,
"result_count": 123,
"path": [
"<string>"
],
"data": {},
"result": {}
}
]
}id。响应包在信封里:数据在 tasks[0].result,成败在 tasks[0].status_code——请求被拒时 HTTP 仍是 200。 先看 get_dataforseo_ai_claude_llm_responses_models 里的 task_post_supported,再用 get_dataforseo_ai_claude_llm_responses_fetch 取结果。
示例
curl -X POST "https://api.aisa.one/apis/v1/dataforseo/ai_optimization/claude/llm_responses/task_post" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_API_KEY" \
-d '[{"user_prompt": "...", "model_name": "...", "max_output_tokens": "..."}]'
授权
Bearer authentication header of the form Bearer <token>, where <token> is your auth token.
请求体
prompt for the AI model
required field
the question or task you want to send to the AI model;
you can specify up to 500 characters in the user_prompt field
name of the AI model
required fieldmodel_nameconsists of the actual model name and version name;
if the basic model name is specified, its latest version will be set by default;
for example, if claude-opus-4-0 is specified, the claude-opus-4-20250514 will be set as model_name automatically;
you can receive the list of available LLM models by making a separate request to the https://api.dataforseo.com/v3/ai_optimization/claude/llm_responses/models
maximum number of tokens in the AI response
optional field
minimum value: 1;
maximum value: 4096;
default value: 2048;
Note: if web_search is set to true or the reasoning model is specified in the request, the output token count may exceed the specified max_output_tokens limit
Note #2: if use_reasoning is set to true, the minimum value for max_output_tokens is 1025
randomness of the AI response
optional field
higher values make output more diverse;
lower values make output more focused;
minimum value: 0
maximum value: 1
default value: 0.7
Note: temperature cannot be used together with top_p in the same request
diversity of the AI response
optional field
controls diversity of the response by limiting token selection;
minimum value: 0
maximum value: 1
default value: null
Note: top_p cannot be used together with temperature in the same request
enable web search for current information
optional field
when enabled, the AI model can access and cite current web information;
Note: refer to the Models endpoint for a list of models that support web_search;
default value: false;
The cost of the parameter can be calculated on the Pricing page
force AI agent to use web search
optional field
to enable this parameter, web_search must also be enabled;
when enabled, the AI model is forced to access and cite current web information;
default value: false;
Note: even if the parameter is set to true, there is no guarantee web sources will be cited in the response
ISO country code of the location used for searching the web
optional field
possible values: 'AR','AT','AU','BE','BR','CA','CH','CL','CN','DE','DK','ES','FI','FR','GB','HK','ID','IN','IT','JP','KR','MX','MY','NL','NO','NZ','PH','PL','PT','RU','SA','SE','TR','TW','US','ZA'
city name of the location used for searching the web
optional field
instructions for the AI behaviour
optional field
defines the AI's role, tone, or specific behavior;
you can specify up to 500 characters in the system_message field
conversation history optional field array of message objects representing previous conversation turns; each object must contain: role string with either user or ai role; message string with message content (max 500 characters); you can specify maximum of 10 message objects in the array; Note: for Perplexity models, messages must strictly alternate between user and AI roles (user → ai); example: "message_chain": [{"role":"user","message":"Hello, what’s up?"},{"role":"ai","message":"Hello! I’m doing well, thank you. How can I assist you today?"}]
Show child attributes
Show child attributes
enable reasoning for the AI model
optional field
when enabled, the model will perform reasoning before generating a response
refer to the Models endpoint for a list of models that support reasoning
default value: false
Note: if set to true, the minimum value for max_output_tokens is 1025
Note #2: if set to true, force_web_search must be set to false
Note #3: if set to true, the temperature and top_p cannot be used
user-defined task identifier
optional field
the character limit is 255
you can use this parameter to identify the task and match it with the result
you will find the specified tag value in the data object of the response
URL for sending task results
optional field
once the task is completed, we will send a POST request with its results compressed in the gzip format to the postback_url you specified
you can use the ‘$id’ string as a $id variable and ‘$tag’ as urlencoded $tag variable. We will set the necessary values before sending the request.
example:http://your-server.com/postbackscript?id=$idhttp://your-server.com/postbackscript?id=$id&tag=$tag
Note: special character in postback_url will be urlencoded;
i.a., the # character will be encoded into %23
learn more on our Help Center
notification URL of a completed task
optional field
when a task is completed we will notify you by GET request sent to the URL you have specified
you can use the ‘$id’ string as a $id variable and ‘$tag’ as urlencoded $tag variable. We will set the necessary values before sending the request
example:http://your-server.com/pingscript?id=$idhttp://your-server.com/pingscript?id=$id&tag=$tag
Note: special character in pingback_url will be urlencoded;
i.a., the # character will be encoded into %23
learn more on our Help Center
[
{
"system_message": "communicate as if we are in a business meeting",
"message_chain": [
{
"role": "user",
"message": "Hello, what’s up?"
},
{
"role": "ai",
"message": "Hello! I’m doing well, thank you. How can I assist you today? Are there any specific topics or projects you’d like to discuss in our meeting?"
}
],
"max_output_tokens": 1024,
"temperature": 0.3,
"web_search_country_iso_code": "FR",
"model_name": "claude-sonnet-4-0",
"web_search": true,
"user_prompt": "provide information on how relevant the amusement park business is in France now"
}
]
响应
Successful operation
API 的当前版本
general status code you can find the full list of the response codes here
general informational message you can find the full list of general informational messages here
total execution time, seconds
任务总成本(美元)
tasks 数组中的任务数量
返回错误的 tasks 数组中的任务数量
array of tasks
Show child attributes
Show child attributes