Problem Background

Timeout errors are among the most frequent issues developers encounter when integrating LLM APIs through proxy services like HolySheep. These errors manifest as TimeoutError, asyncio.TimeoutError, ReadTimeout, ConnectTimeout, or HTTP 408/504 status codes. Unlike simple authentication failures, timeouts stem from multiple sources: network latency, model inference load, payload size, streaming configuration, and SDK default settings.

When you're routing requests through https://api.holysheep.ai instead of hitting OpenAI or Anthropic directly, additional hops introduce latency. Understanding where timeouts originate—and how to configure your SDK appropriately—is critical for building reliable AI-powered applications.

Applicable Scenarios

This guide covers timeout troubleshooting for:

- **OpenAI SDK** (openai Python/Node.js library) with custom base_url - **Anthropic SDK** (anthropic Python library) via proxy - **REST API calls** using curl or httpx - **Streaming responses** with SSE (stream=True) - **Concurrent requests** with connection pooling - **RAG pipelines** sending large contexts to models

Configuration Steps

Step 1: Identify Your SDK and Version

Python
pip show openai | grep Version
Node.js
npm list openai

Step 2: Set Correct base_url for HolySheep

HolySheep provides an OpenAI-compatible endpoint. The correct base_url is:

https://api.holysheep.ai/v1

Not /v1/chat/completions—the SDK appends the path automatically.

Step 3: Configure Timeout at SDK Level

Never rely on system-level HTTP timeouts. Explicitly configure timeout in your SDK initialization.

Code Examples

Python: OpenAI SDK with Explicit Timeout

```python from openai import OpenAI import os

client = OpenAI( api_key=os.environ.get("HOLYSHEEP_API_KEY"), base_url="https://api.holysheep.ai/v1", timeout=60.0, # Total timeout in seconds max_retries=3, default_headers={ "HTTP-Timeout": "60", "Connection": "