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Client Configuration

The Stratix (syncronous) and AsyncStratix (asyncronous) classes are the main entry points for interacting with the LayerLens Stratix sdk. This page covers client initialization, configuration options, and usage patterns.

Basic Usage

Syncronous Client

from layerlens import Stratix

# Construct syncronous client
# Loads for api key from the "LAYERLENS_STRATIX_API_KEY" enviornment variable
client = Stratix()

# Explicit configuration
client = Stratix(api_key="your_api_key")

Asyncronous Client

import asyncio
from layerlens import AsyncStratix

# Construct async client
# Loads for api key from the "LAYERLENS_STRATIX_API_KEY" enviornment variable
client = AsyncStratix()

# Explicit configuration
client = AsyncStratix(api_key="your_api_key")

Constructor Parameters

Stratix(api_key, base_url, timeout, max_retries) and AsyncStratix(api_key, base_url, timeout, max_retries)

Parameter Type Required Default Description
api_key str | None Yes* None Your LayerLens Stratix API key
base_url str | httpx.URL | None No Stratix API URL Custom API base URL
timeout float | httpx.Timeout | None No 10 minutes Request timeout configuration
max_retries int No 2 Maximum number of retries on retryable errors (429, 500, 502, 503, 504)

*Required unless set via environment variables

Environment Variable Configuration

The client automatically loads configuration from these environment variables:

LAYERLENS_STRATIX_API_KEY="your_api_key_here"

Public Client

For accessing public endpoints (models, benchmarks, comparisons), use PublicClient or AsyncPublicClient. See the Public Client reference for full details.

from layerlens import PublicClient

# Loads API key from the "LAYERLENS_STRATIX_API_KEY" environment variable
public = PublicClient()
models = public.models.get(companies=["OpenAI"])

You can also access public endpoints from an authenticated client via the .public property:

client = Stratix()
public_models = client.public.models.get(query="claude")

Timeout Configuration

Simple Timeout

from layerlens import Stratix

# 30-second timeout for all requests
client = Stratix(timeout=30.0)

Retry Configuration

The client automatically retries requests that fail with retryable status codes (429 Too Many Requests, 500, 502, 503, 504) using exponential backoff. If the server sends a Retry-After header, the client respects it.

from layerlens import Stratix

# Default: 2 retries
client = Stratix()

# More retries for batch-heavy workloads
client = Stratix(max_retries=5)

# Disable retries entirely
client = Stratix(max_retries=0)

Per-Request Timeout Override

client = Stratix()

# --- Models replace with the model name you want to run
models = client.models.get(type="public", name="gpt-4o")

if not models:
    print("gpt-4o not found on organization, exiting")

model = models[0]

# --- Benchmarks replace with the benchmark name you want to run
benchmarks = client.benchmarks.get(type="public", name="simpleQA")

if not benchmarks:
    print("SimpleQA benchmark not found on organization, exiting")

benchmark = benchmarks[0]

# Override timeout for a specific request
evaluation = client.with_options(timeout=120.0).evaluations.create(
    model=model,
    benchmark=benchmark
)