AI Config API Access

Access LaunchDarkly AI Configs through the REST API to perform operations not available through SDKs, including creating, updating, and managing AI Configs programmatically.

Prerequisites

•LaunchDarkly account with AI Configs enabled
•Project where you want to manage AI Configs
•Understanding of REST API concepts

Getting an API Access Token

Create a Personal Access Token

•Navigate to Authorization settings
•Click Create token
•Name your token (e.g., "AI Config Management")
•
Set token permissions:
- •Required: ai-configs:write - Full access to AI Configs
- •Optional: projects:read - Read project information
- •Optional: environments:read - Read environment data
•Set API version (recommended: latest version)
•Click Save token
•Copy and save the token immediately - it won't be shown again

Token Security Best Practices

•Never commit tokens to version control
•Store tokens in environment variables or secret managers
•Rotate tokens regularly
•Use service tokens for production applications
•Limit token permissions to minimum required

API Authentication

Include your token in the Authorization header for all requests:

python

import requests

headers = {
    "Authorization": "YOUR_API_TOKEN",
    "Content-Type": "application/json",
    "LD-API-Version": "beta"  # Required for AI Config endpoints
}

Operations Only Available via API

The following operations can only be done through the API, not through SDKs:

1. Create AI Configs

SDKs can only read AI Configs. Creating new configs requires the API. See: aiconfig-create skill

2. Update AI Configs and Variations

Modifying existing configs, variations, or settings requires the API. See: aiconfig-update and aiconfig-variations skills

3. Delete AI Configs

Removing configs entirely requires the API. See: aiconfig-update skill

4. Manage Tools

Creating, updating, and deleting tools for function calling requires the API. See: aiconfig-tools skill

5. Configure Targeting Rules

Setting up targeting rules for AI Configs requires the API. See: aiconfig-targeting skill

6. List and Search Operations

Listing all AI Configs in a project requires the API:

python

def list_ai_configs(project_key, api_token):
    """List all AI Configs in a project"""
    url = f"https://app.launchdarkly.com/api/v2/projects/{project_key}/ai-configs"

    headers = {
        "Authorization": api_token,
        "LD-API-Version": "beta"
    }

    response = requests.get(url, headers=headers)

    if response.status_code == 200:
        configs = response.json()
        for config in configs.get("items", []):
            print(f"- {config['key']}: {config['name']}")
        return configs
    else:
        print(f"Error: {response.status_code}")
        return None

API vs SDK Comparison

Operation	API	SDK	Notes
Create AI Configs	✅	❌	API only
Read AI Config values	✅	✅	SDK optimized for runtime
Update configurations	✅	❌	API only
Delete AI Configs	✅	❌	API only
Evaluate variations	❌	✅	SDK only - determines which variation to serve
Track metrics	❌	✅	SDK only - sends usage data
Manage tools	✅	❌	API only
Configure targeting	✅	❌	API only

Common API Patterns

Error Handling

python

def api_request(method, url, headers, json_data=None):
    """Make API request with error handling"""
    try:
        if method == "GET":
            response = requests.get(url, headers=headers)
        elif method == "POST":
            response = requests.post(url, headers=headers, json=json_data)
        elif method == "PATCH":
            response = requests.patch(url, headers=headers, json=json_data)
        elif method == "DELETE":
            response = requests.delete(url, headers=headers)

        if response.status_code in [200, 201, 204]:
            return {"success": True, "data": response.json() if response.text else None}
        elif response.status_code == 400:
            return {"success": False, "error": "Bad request - check your data"}
        elif response.status_code == 401:
            return {"success": False, "error": "Invalid or missing API token"}
        elif response.status_code == 403:
            return {"success": False, "error": "Insufficient permissions"}
        elif response.status_code == 404:
            return {"success": False, "error": "Resource not found"}
        elif response.status_code == 429:
            return {"success": False, "error": "Rate limited - wait and retry"}
        else:
            return {"success": False, "error": f"HTTP {response.status_code}"}

    except requests.exceptions.RequestException as e:
        return {"success": False, "error": str(e)}

Pagination

Many API endpoints return paginated results:

python

def get_all_configs(project_key, api_token):
    """Get all AI Configs with pagination"""
    all_configs = []
    limit = 20
    offset = 0

    while True:
        url = f"https://app.launchdarkly.com/api/v2/projects/{project_key}/ai-configs"
        url += f"?limit={limit}&offset={offset}"

        result = api_request("GET", url, {"Authorization": api_token, "LD-API-Version": "beta"})

        if not result["success"]:
            break

        items = result["data"].get("items", [])
        all_configs.extend(items)

        # Check if more pages exist
        if len(items) < limit:
            break

        offset += limit

    return all_configs

Environment-Specific URLs

Production (Default)

code

https://app.launchdarkly.com/api/v2

Federal

code

https://app.launchdarkly.us/api/v2

European Union

code

https://app.eu.launchdarkly.com/api/v2

Rate Limiting

LaunchDarkly API has rate limits to ensure availability:

•Global limit: Account-wide limit per 10 seconds
•Route limit: Per-endpoint limit per 10 seconds
•429 responses: Indicate rate limiting
•Retry-After header: Specifies wait time

Handle rate limits gracefully:

python

import time

def retry_with_backoff(func, max_retries=3):
    """Retry function with exponential backoff"""
    for attempt in range(max_retries):
        result = func()

        if result.get("success"):
            return result

        if "rate limited" in result.get("error", "").lower():
            wait_time = 2 ** attempt  # Exponential backoff
            print(f"Rate limited, waiting {wait_time} seconds...")
            time.sleep(wait_time)
        else:
            return result

    return {"success": False, "error": "Max retries exceeded"}

Quick Reference

Essential Headers

python

headers = {
    "Authorization": "YOUR_API_TOKEN",     # Required
    "Content-Type": "application/json",    # For POST/PATCH
    "LD-API-Version": "beta"               # For AI Config endpoints
}

Base URLs

python

# Choose based on your environment
BASE_URL = "https://app.launchdarkly.com/api/v2"  # Production
# BASE_URL = "https://app.launchdarkly.us/api/v2"  # Federal
# BASE_URL = "https://app.eu.launchdarkly.com/api/v2"  # EU

Common Endpoints

python

# AI Configs
f"{BASE_URL}/projects/{project}/ai-configs"  # List/Create
f"{BASE_URL}/projects/{project}/ai-configs/{key}"  # Get/Update/Delete

# Variations
f"{BASE_URL}/projects/{project}/ai-configs/{key}/variations"  # List/Create
f"{BASE_URL}/projects/{project}/ai-configs/{key}/variations/{var_key}"  # Get/Update/Delete

# Tools
f"{BASE_URL}/projects/{project}/ai-tools"  # List/Create
f"{BASE_URL}/projects/{project}/ai-tools/{key}"  # Get/Update/Delete

# AI Config Metrics (read AI usage metrics)
f"{BASE_URL}/projects/{project}/ai-configs/{key}/metrics?from={start}&to={end}&env={env}"  # Get

# Custom Metrics (manage metric definitions)
f"{BASE_URL}/metrics/{project}"  # List/Create
f"{BASE_URL}/metrics/{project}/{metric_key}"  # Get/Update/Delete

# Segments (for targeting)
f"{BASE_URL}/segments/{project}/{env}"  # List/Create
f"{BASE_URL}/segments/{project}/{env}/{segment_key}"  # Get/Update/Delete

# Projects
f"{BASE_URL}/projects"  # List/Create
f"{BASE_URL}/projects/{project}"  # Get/Update/Delete
f"{BASE_URL}/projects/{project}/environments"  # List environments

Next Steps

After setting up API access:

•Create AI Configs - See aiconfig-create
•Manage variations - See aiconfig-variations
•Configure tools - See aiconfig-tools
•Set up targeting - See aiconfig-targeting
•Integrate with SDKs - See aiconfig-sdk

aiconfig-api

AI Config API Access

Prerequisites

Getting an API Access Token

Create a Personal Access Token

Token Security Best Practices

API Authentication

Operations Only Available via API

1. Create AI Configs

2. Update AI Configs and Variations

3. Delete AI Configs

4. Manage Tools

5. Configure Targeting Rules

6. List and Search Operations

API vs SDK Comparison

Common API Patterns

Error Handling

Pagination

Environment-Specific URLs

Production (Default)

Federal

European Union

Rate Limiting

Quick Reference

Essential Headers

Base URLs

Common Endpoints

Next Steps

Related Skills

Core Operations

SDK Integration

References