Airiam AI REST API Reference Guide

Welcome to the Airiam AI REST API Reference Guide. Our API provides a powerful and flexible way to integrate Airiam AI's capabilities into your existing systems and workflows. This guide includes descriptions, code snippets, and usage examples to help you make the most of our API.

Overview

The Airiam AI REST API allows you to:

Access and manage all of the available Large Language Models (LLMs) in Airiam AI.
Integrate Airiam AI's features into your existing applications.

Authentication

To use the Airiam AI REST API, you must first authenticate using your API key. Include this key in the header of your API requests.

import requests

API_KEY = 'your_api_key_here'
headers = {
    'Authorization': 'Bearer {API_KEY}'
}

Endpoints

1. LLM Models

Endpoint: /api/v1/models
Method: GET
Description: Retrieve the list of available LLMs.

Code Snippet:

response = requests.get('https://ai.airiam.com/api/v1/models', headers=headers)
print(response.json())

2. Workspace Management

Endpoint: /api/v1/workspaces
Method: GET
Description: Get list of workspaces.

Code Snippet:

response = requests.get('https://ai.airiam.com/api/v1/workspaces', headers=headers)
print(response.json())

3. Workspace Management

Endpoint: /api/v1/workspaces
Method: POST
Description: Create new workspace.

Payload Example:

{
  "modelIds": [
    "3fa85f64-5717-4562-b3fc-2c963f66afa6"
  ],
  "name": "Data Analysis",
  "chatHistoryType": "TEAM",
  "contextType": "SHARED",
  "sharingType": "TEAM"
}

Code Snippet:

payload = {
  "modelIds": [
    "3fa85f64-5717-4562-b3fc-2c963f66afa6"
  ],
  "name": "Data Analysis",
  "chatHistoryType": "USER",
  "contextType": "SHARED",
  "sharingType": "TEAM"
}
response = requests.post('https://ai.airiam.com/api/v1/workspaces', json=payload, headers=headers)
print(response.json())

4. Workspace Management

Endpoint: /api/v1/workspaces/{workspaceId}
Method: POST
Description: Update workspace.

Payload Example:

{
  "modelIds": [
    "3fa85f64-5717-4562-b3fc-2c963f66afa6"
  ],
  "name": "Data Analysis",
  "chatHistoryType": "TEAM",
  "contextType": "PRIVATE",
  "sharingType": "PRIVATE"
}

Code Snippet:

payload = {
  "modelIds": [
    "3fa85f64-5717-4562-b3fc-2c963f66afa6"
  ],
  "name": "Data Analysis",
  "chatHistoryType": "TEAM",
  "contextType": "PRIVATE",
  "sharingType": "PRIVATE"
}
response = requests.post('https://ai.airiam.com/api/v1/workspaces/29f7f2f9-3fe7-43e9-b50e-3f0a50cd5d4b', json=payload, headers=headers)
print(response.json())

5. Chat

Endpoint: /api/v1/chat/{workspaceId}/completions
Method: POST
Description: Chat within a workspace.

Payload Example:

{
  "messages": [
    {
      "role": "user",
      "content": "Tell me a joke"
  ]
}

Code Snippet:

payload = {
  "messages": [
    {
      "role": "user",
      "content": "Tell me a joke"
  ]
}
response = requests.post('https://ai.airiam.com/api/v1/chat/29f7f2f9-3fe7-43e9-b50e-3f0a50cd5d4b/completions', json=payload, headers=headers)
print(response.json())

Error Handling

The Airiam AI REST API uses standard HTTP response codes to indicate success or failure of an API request. Common responses include:

200 OK: Request succeeded.
400 Bad Request: The server cannot process the request due to a client error.
403 Unauthorized: Authentication failed or user does not have permissions.
500 Internal Server Error: An error occurred on the server side.

Best Practices

Security: Always keep your API key secure. Do not expose it in client-side code.
Rate Limiting: Be mindful of rate limits to avoid service disruptions.
Error Handling: Implement robust error handling in your integration to manage different response codes gracefully.

Support

For additional support or questions about the Airiam AI REST API, contact our technical support team at support@ai.airiam.com.

This API reference guide is intended to be a starting point. As you integrate Airiam AI's capabilities into your systems, we encourage you to explore the full potential of our API and leverage its features to enhance your applications and workflows.