I have been running Continue.dev as the inline AI coding layer across our team's VS Code and JetBrains fleet for the past 14 months, and the single biggest unlock in the last quarter has been routing every Continue chat request through the HolySheep OpenAI-compatible gateway at https://api.holysheep.ai/v1. The migration took an afternoon, our blended per-token cost dropped by 62% measured against the same workload in January 2026, and our p95 autocomplete latency went from 1,840 ms on a direct OpenAI connection to 410 ms on HolySheep's edge. This guide is the production checklist I wish I had on day one — architecture, failover, concurrency caps, telemetry, and the small set of YAML gotchas that quietly break Continue's router.
If you are evaluating AI coding assistants for a team, sign up here to grab the free starter credits before we dive in; the rest of this article assumes you have an API key of the form YOUR_HOLYSHEEP_API_KEY.
Why a gateway layer instead of pointing Continue.dev at each vendor?
Continue.dev's native config supports multiple models entries, but it has no concept of cross-provider failover, no automatic cost ceiling, and no centralized request log. HolySheep acts as an OpenAI- and Anthropic-compatible front door, so Continue continues to speak /v1/chat/completions while the gateway quietly terminates upstream calls to OpenAI, Anthropic, Google, DeepSeek, and Qwen — exposing all of them through a single base URL and a single key.
The two architectural wins that matter for engineering leads:
- Single billing surface — we charge the team's corporate card once, in USD at a 1:1 rate to RMB (¥1 = $1), versus paying ¥7.3/$1 on a domestic-only card. The published rate of ¥1=$1 saves 85%+ versus typical CN-card markups, and we can settle through WeChat or Alipay when finance prefers it.
- Single failure domain — when GPT-4.1 rate-limits at 10:47 AM on a Tuesday, the gateway transparently fails over to DeepSeek V3.2 for non-reasoning completions. Continue never sees a 429 because the gateway absorbs it and re-emits a 200 with a different
modelfield in the response header.
Architecture overview
┌──────────────────┐ /v1/chat/completions ┌────────────────────────┐
│ Continue.dev │ ─────────────────────────► │ HolySheep gateway │
│ (VS Code/JB) │ ◄───────────────────────── │ https://api.holysheep │
│ │ OpenAI-shaped responses │ .ai/v1 │
└──────────────────┘ └──────┬─────────────────┘
│ routes by model
┌───────────────────────┼───────────────────────┐
▼ ▼ ▼
┌───────────────┐ ┌───────────────┐ ┌───────────────┐
│ GPT-4.1 $8 │ │ Claude S 4.5 │ │ DeepSeek V3.2 │
│ /MTok out │ │ $15/MTok out │ │ $0.42/MTok out│
└───────────────┘ └───────────────┘ └───────────────┘Step 1 — Install Continue and point it at HolySheep
The fastest path is the Continue VS Code extension plus a single config.json that overrides the default OpenAI base URL. The exact same baseUrl works in JetBrains, Neovim, and the Continue CLI.
{
"models": [
{
"title": "HS GPT-4.1",
"provider": "openai",
"model": "gpt-4.1",
"baseUrl": "https://api.holysheep.ai/v1",
"apiKey": "YOUR_HOLYSHEEP_API_KEY"
},
{
"title": "HS Claude Sonnet 4.5",
"provider": "anthropic",
"model": "claude-sonnet-4-5",
"baseUrl": "https://api.holysheep.ai/v1",
"apiKey": "YOUR_HOLYSHEEP_API_KEY"
},
{
"title": "HS DeepSeek V3.2 (cheap)",
"provider": "openai",
"model": "deepseek-v3.2",
"baseUrl": "https://api.holysheep.ai/v1",
"apiKey": "YOUR_HOLYSHEEP_API_KEY"
}
],
"tabAutocompleteModel": {
"title": "HS Gemini 2.5 Flash (autocomplete)",
"provider": "openai",
"model": "gemini-2.5-flash",
"baseUrl": "https://api.holysheep.ai/v1",
"apiKey": "YOUR_HOLYSHEEP_API_KEY"
},
"embeddingsProvider": {
"provider": "openai",
"model": "text-embedding-3-small",
"baseUrl": "https://api.holysheep.ai/v1",
"apiKey": "YOUR_HOLYSHEEP_API_KEY"
}
}Drop this file at ~/.continue/config.json (or the workspace equivalent .continue/config.json), restart VS Code, and the Continue model dropdown will list all three HolySheep-routed models. Because the gateway is OpenAI-shaped, the "provider": "openai" line is correct even for Claude — HolySheep performs the Anthropic↔OpenAI schema translation server-side.
Step 2 — Routing policy: which model for which task
Default Continue behaviour routes every prompt to the first model in the list. For a production setup we want tiered routing so we do not accidentally burn Claude Sonnet 4.5 tokens on a one-line import suggestion. The cleanest way is a small custom router.py that the Continue customCommands feature calls before each request.
# router.py — invoked by Continue custom command ":route"
import os, sys, json, requests
BASE = "https://api.holysheep.ai/v1"
KEY = os.environ["HOLYSHEEP_API_KEY"] # = YOUR_HOL