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Guide
Responses API
The Responses API lets Cadreen handle the hard parts — governance, memory, tool execution — so you don't have to. It's the recommended endpoint for all new projects.
1
What is the Responses API?
A single endpoint that does what Chat Completions does — plus governance, memory, tool execution, and conversation state. You send a request, Cadreen decides which model to use, applies your policies, executes any tools, and returns a typed response.
Think of it as the difference between calling a model directly and calling an intelligence layer. The model is one component. Cadreen is the system around it.
Note
New to Cadreen? Start with How to Connect Cadreen for base URL and API key setup. Then come back here.
2
Quick start
POST/api/v1/cadreen/responses
Send a simple request. Cadreen handles the rest.
Python
from openai import OpenAI
client = OpenAI(
base_url="https://accomplishanything.today/api/v1/cadreen",
api_key="sk_cadreen_..."
)
response = client.responses.create(
model="cadreen",
input="What connectors do I have?",
instructions="You are a helpful AI assistant."
)
print(response.output_text)TypeScript
import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://accomplishanything.today/api/v1/cadreen",
apiKey: "sk_cadreen_...",
});
const response = await client.responses.create({
model: "cadreen",
input: "What connectors do I have?",
instructions: "You are a helpful AI assistant.",
});
console.log(response.output_text);curl
curl -X POST https://accomplishanything.today/api/v1/cadreen/responses \
-H "Authorization: Bearer sk_cadreen_..." \
-H "Content-Type: application/json" \
-d '{
"model": "cadreen",
"input": "What connectors do I have?",
"instructions": "You are a helpful AI assistant."
}'Note
The model field is required but ignored. Cadreen decides which model to use based on your request, policies, and workspace configuration. You can pass any string — it won't affect the result.
3
How it compares to Chat Completions
Both endpoints generate text. The difference is what happens around it.
QuestionChat CompletionsResponses
How do you send a prompt?Build a messages[] array with role objectsSend a string or list. System guidance goes in instructions.
How do you read the answer?choices[0].message.content — one stringoutput_text — or iterate output[] for structured items
How do you have a conversation?You store and resend the full message history every timePass the previous response's ID. Cadreen loads the context.
What about tools?Tool calls come back inside the messageTool calls come back as typed items. Multiple tools in one request.
What about reasoning?BasicRich reasoning. Can be kept private with encrypted items.
Note
Use Responses for new projects. Chat Completions still works — your existing integrations won't break. But Responses gives you better performance, simpler state management, and built-in tools.
4
When to use which
Use Responses when
You're starting a new project
You need the AI to remember previous turns
You want Cadreen to use your tools (file access, databases, APIs)
You need structured JSON output
You want Cadreen to manage conversation state for you
Stick with Completions when
You have an existing integration that works
You need multiple parallel answers from the same prompt
You have strict data retention requirements
5
What you send
FieldTypeRequiredWhat it does
modelstringYesRequired by clients, ignored by Cadreen — it decides which model to use
inputstring | arrayYesThe user's message — a string or list of messages and tool results
instructionsstringNoSystem-level guidance. Becomes the system message.
toolsarrayNoTool definitions. Cadreen checks your policies before calling any of them.
tool_choicestring | objectNoControl which tool is called: auto, none, required, or a specific tool
previous_response_idstringNoContinue a conversation — pass the previous response's ID
storeboolNoSave the response. Defaults to true.
streamboolNoGet text as it's generated, not all at once
max_output_tokensintNoMax tokens in the response. Defaults to 4096.
textobjectNoStructured output config. Forces JSON matching a schema.
6
What you get back
Every response has a unique ID, an output array with structured items, and a ready-to-use text helper.
Response
{
"id": "resp_68af4030592c81938ec0a5fbab4a3e9f",
"object": "response",
"output": [
{
"id": "msg_68af40337e58819392e935fb",
"type": "message",
"status": "completed",
"content": [
{
"type": "output_text",
"text": "You have 3 active connectors: GitHub, Slack, and Linear."
}
],
"role": "assistant"
}
],
"output_text": "You have 3 active connectors: GitHub, Slack, and Linear.",
"usage": {
"input_tokens": 42,
"output_tokens": 18,
"total_tokens": 60
},
"store": true
}FieldWhat it tells you
idUnique ID for this response (resp_...)
outputStructured items — messages, tool calls, reasoning
output_textThe full text answer, ready to use
usageHow many tokens you used
storeWhether Cadreen saved this response
7
Get text as it arrives
Set stream: true to receive text in real time. Useful for chat UIs and long responses where you don't want the user staring at a blank screen.
Python
stream = client.responses.create(
model="cadreen",
input="Tell me about my workspace",
stream=True
)
for event in stream:
if event.type == "response.output_text.delta":
print(event.delta, end="", flush=True)Note
Cadreen sends keepalive pings every 15 seconds during long operations. You won't lose the connection.
8
Let it use your tools
Define tools just like Chat Completions. Cadreen checks your governance policies before calling any of them.
Python
response = client.responses.create(
model="cadreen",
input="Read main.go and summarize it",
tools=[{
"type": "function",
"function": {
"name": "read",
"description": "Read a file",
"parameters": {
"type": "object",
"properties": {
"path": {"type": "string", "description": "File path"}
},
"required": ["path"]
}
}
}]
)Note
Cadreen returns tool calls as structured items. You execute them and send the result back. See the Tool Calling guide for the full flow.
9
Remember conversations
Chat Completions requires you to store and resend the full message history. Responses gives you three options:
previous_response_id — Pass the previous response's ID. Cadreen loads the context automatically. Send instructions again on each request — they don't carry over.
Manual context — Pass prior output items back in the input array. You control exactly what the model sees.
Conversations API — Use a persistent conversation object. Cadreen manages the full history.
previous_response_id
# Turn 1
res1 = client.responses.create(
model="cadreen",
input="What is the capital of France?",
instructions="You are a geography expert.",
store=True
)
print(res1.output_text) # "The capital of France is Paris."
# Turn 2 — Cadreen remembers the context
res2 = client.responses.create(
model="cadreen",
input="And its population?",
instructions="You are a geography expert.",
previous_response_id=res1.id,
store=True
)
print(res2.output_text) # "Paris has approximately 2.1 million people..."10
What's different from OpenAI
Tool governance — Every tool call is checked against your rules before execution
Memory — 4 types of persistent memory — what it knows, what happened, how to do things, and past fixes
Intelligence traces — Full reasoning breakdown in every response — what it understood, what it checked, what it did
Model selection — Cadreen picks the best model for your request. The model field is required but ignored.
Self-healing — When tool calls fail, Cadreen figures out why, fixes the arguments, and retries
Note
Internal reasoning is stripped. You never see the model's chain-of-thought. The intelligence trace gives you a structured breakdown instead.
11
What doesn't work yet
The model field is required by clients but ignored — Cadreen decides which model to use
temperature, top_p, reasoning are accepted but not passed to the model — Cadreen controls generation internally
previous_response_id is defined but not wired — use manual context passing for now
Structured output (text.format) is accepted but not enforced — parse output defensively
Built-in tools (web search, file search, code interpreter) are not yet available
Note
Next: Responses API Cookbook — step-by-step recipes you can copy and paste.