curl --request POST \
--url https://toapis.com/v1/responses \
--header 'Authorization: Bearer YOUR_API_KEY' \
--header 'Content-Type: application/json' \
--data '{
"model": "gpt-5.3-codex-official",
"instructions": "You are a professional code assistant",
"input": "Write a quicksort in Python"
}'
from openai import OpenAI
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://toapis.com/v1"
)
response = client.responses.create(
model="gpt-5.3-codex-official",
instructions="You are a professional code assistant",
input="Write a quicksort in Python"
)
print(response.output[0].content[0].text)
{
"id": "<string>",
"object": "<string>",
"status": "<string>",
"output": [
{}
],
"usage": {}
}Responses Format
Responses API
OpenAI Responses API format with function calling, built-in tools, and server-side multi-turn context
POST
/
v1
/
responses
curl --request POST \
--url https://toapis.com/v1/responses \
--header 'Authorization: Bearer YOUR_API_KEY' \
--header 'Content-Type: application/json' \
--data '{
"model": "gpt-5.3-codex-official",
"instructions": "You are a professional code assistant",
"input": "Write a quicksort in Python"
}'
from openai import OpenAI
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://toapis.com/v1"
)
response = client.responses.create(
model="gpt-5.3-codex-official",
instructions="You are a professional code assistant",
input="Write a quicksort in Python"
)
print(response.output[0].content[0].text)
{
"id": "<string>",
"object": "<string>",
"status": "<string>",
"output": [
{}
],
"usage": {}
}Note for users in mainland China: Please use
https://toapis.cn as the API endpoint (Base URL). Replace https://toapis.com with https://toapis.cn in the examples in this document.- Function calling: let models call custom functions
- Built-in tools: use tools such as
web_search_preview - Server-side context: use
previous_response_idinstead of resending the full conversation - Reasoning control: tune thinking depth with
reasoning.effort
Models marked as Responses Only, such as
gpt-5-pro-official and gpt-5.3-codex-official, only support this API and do not support Chat Completions. See the model list for details.Authorizations
string
required
Use Bearer Token authentication.Get your API key from the API Key management page.
Authorization: Bearer YOUR_API_KEY
Body
string
required
Model name.Examples:
"gpt-5-pro-official", "gpt-5.3-codex-official", "gpt-5.2-official"string | object[]
required
User input. Supports simple string input or a message array for multi-turn conversations.
string
System instructions that guide model behavior.
boolean
default:false
Whether to enable streaming output.
integer
Maximum number of output tokens.
number
default:1
Sampling temperature, from
0 to 2.number
default:1
Nucleus sampling threshold, from
0 to 1.string
Previous response ID for server-side multi-turn context.
object
Reasoning configuration.
reasoning.effort can be high, medium, low, or none.object[]
Available tools. Supported tool types include
function and web_search_preview.string
default:"auto"
Tool selection policy:
auto, none, or required.Response
string
Unique response ID, usable as
previous_response_id.string
Always
response.string
Response status:
completed, failed, or in_progress.object[]
Output items, such as
message, function_call, reasoning, or web_search_call.object
Token usage statistics, including input, output, reasoning, and total tokens.
curl --request POST \
--url https://toapis.com/v1/responses \
--header 'Authorization: Bearer YOUR_API_KEY' \
--header 'Content-Type: application/json' \
--data '{
"model": "gpt-5.3-codex-official",
"instructions": "You are a professional code assistant",
"input": "Write a quicksort in Python"
}'
from openai import OpenAI
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://toapis.com/v1"
)
response = client.responses.create(
model="gpt-5.3-codex-official",
instructions="You are a professional code assistant",
input="Write a quicksort in Python"
)
print(response.output[0].content[0].text)