API

Smartloop Studio is installed, or you have just installed the command line tools using curl. The agent exposes an API that you can use to extend the tool for your own workflow.

The chat completion endpoint is OpenAI-compatible, making it easy to build applications on top of it or migrate existing ones with minimal effort.

API Endpoint

First grab the base URL by copying and pasting the following command to your terminal:

slp status

This will return a table listing model size, context, project, etc. for the device:

+-----------------+--------------------------------------------------------+
| Property        | Value                                                  |
+-----------------+--------------------------------------------------------+
| Server          | http://127.0.0.1:38540                                 |
| PID             | 40372                                                  |
| Quantization    | Q4_K_M                                                 |
| Context window  | 4096                                                   |
| Flash attention | False                                                  |
| Model size      | 2.3 GB                                                 |
| Memory usage    | 15%                                                    |
| GPU             | Apple Silicon (MPS)                                    |
| Active project  | general_chat (id=533338cf-5980-4f6a-aeea-02fe9fa92999) |
| ----------------+--------------------------------------------------------+

You can explore the interactive API documentation at http://127.0.0.1:38540/docs.

info

If the agent is not already running, start it with:

slp agent start

The API follows the OpenAI Chat Completions specification, so any client or SDK that supports OpenAI will work out of the box.

Quick Start (Python)

Install the OpenAI Python SDK:

pip install openai

Send your first chat completion request:

from openai import OpenAI

client = OpenAI(
    base_url="http://127.0.0.1:38540/v1",
    api_key="not-needed",
)

response = client.chat.completions.create(
    model="slp-orchestra-mini",
    messages=[
        {"role": "user", "content": "What is the capital of France?"}
    ],
)

print(response.choices[0].message.content)

Quick Start (JavaScript)

Install the OpenAI Node.js SDK:

npm install openai

import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "http://127.0.0.1:38540/v1",
  apiKey: "not-needed",
});

const response = await client.chat.completions.create({
  model: "slp-orchestra-mini",
  messages: [
    { role: "user", content: "What is the capital of France?" },
  ],
});

console.log(response.choices[0].message.content);

Quick Start (cURL)

curl http://127.0.0.1:38540/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{
    "model": "slp-orchestra-mini",
    "messages": [
      {"role": "user", "content": "What is the capital of France?"}
    ]
  }'

Message Roles

Role	Description
system	Sets the behavior and context for the assistant
user	The end user's message
assistant	Previous assistant responses (for multi-turn conversations)

Response Format

{
  "id": "chatcmpl-...",
  "object": "chat.completion",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "The capital of France is Paris."
      },
      "finish_reason": "stop"
    }
  ]
}

Access the response content:

response.choices[0].message.content

Multi-turn Conversations

To maintain context across messages, include the conversation history:

response = client.chat.completions.create(
    model="slp-orchestra-mini",
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "My name is Alice."},
        {"role": "assistant", "content": "Hello Alice! How can I help you today?"},
        {"role": "user", "content": "What's my name?"},
    ],
)