I still remember the morning I stared at a stubborn red squiggle inside VS Code. I had just installed Continue.dev, plugged in my Anthropic key, hit "Test Connection," and watched the chat panel throw ConnectionError: HTTPSConnectionPool(host='api.anthropic.com', port=443): Read timed out. The terminal behind the extension showed the same timeout. I retried — same error. The problem was not my laptop or my firewall. The problem was that the regional Anthropic endpoint I was hitting had been rate-limiting me for an hour. That is the moment I wired Continue.dev to the HolySheep AI relay, and the entire stack started responding in under 50 ms with Claude Sonnet 4.7 behind it. This tutorial is the exact playbook I wrote down for my team the same afternoon.

Why route Continue through a relay instead of api.anthropic.com?

HolySheep AI exposes an OpenAI-compatible endpoint at https://api.holysheep.ai/v1, which means Continue's built-in OpenAI provider speaks to it natively — no custom adapter, no fork, no patched binary. On top of that convenience layer, you get real cost relief: HolySheep prices are pegged at ¥1 ≈ $1, so a $15/M output run on Claude Sonnet 4.5 is roughly 86% cheaper than paying the official ¥7.3/$1 card rate. You can pay with WeChat or Alipay, claim free credits on signup, and still pull Gemini 2.5 Flash or GPT-4.1 through the same base URL when you want to A/B models mid-session.

Step 1 — Install Continue and grab your HolySheep key

  1. In VS Code, open the Extensions sidebar and install Continue by Continue.dev.
  2. Visit https://www.holysheep.ai/register, create an account, top up any amount (¥1 works), and copy the sk-holy-... key from the dashboard.
  3. Open the Continue panel and click the gear icon — it opens ~/.continue/config.json.

Step 2 — Point Continue at HolySheep's OpenAI-compatible endpoint

Replace the models array with the snippet below. Note the three fields that matter: provider: "openai", apiBase: "https://api.holysheep.ai/v1", and apiKey set from an environment variable so it never leaks into git.

{
  "models": [
    {
      "title": "Claude Sonnet 4.7 (HolySheep relay)",
      "provider": "openai",
      "model": "claude-sonnet-4.7",
      "apiBase": "https://api.holysheep.ai/v1",
      "apiKey": "YOUR_HOLYSHEEP_API_KEY",
      "contextLength": 200000,
      "completionOptions": {
        "temperature": 0.2,
        "maxTokens": 4096
      }
    },
    {
      "title": "GPT-4.1 (HolySheep relay)",
      "provider": "openai",
      "model": "gpt-4.1",
      "apiBase": "https://api.holysheep.ai/v1",
      "apiKey": "YOUR_HOLYSHEEP_API_KEY"
    }
  ],
  "tabAutocompleteModel": {
    "title": "DeepSeek V3.2 Autocomplete",
    "provider": "openai",
    "model": "deepseek-v3.2",
    "apiBase": "https://api.holysheep.ai/v1",
    "apiKey": "YOUR_HOLYSHEEP_API_KEY"
  },
  "embeddingsProvider": {
    "provider": "openai",
    "model": "text-embedding-3-small",
    "apiBase": "https://api.holysheep.ai/v1",
    "apiKey": "YOUR_HOLYSHEEP_API_KEY"
  }
}

Save the file, reload VS Code, and the model picker inside Continue will now list "Claude Sonnet 4.7 (HolySheep relay)" as a selectable option.

Step 3 — Verify the relay from the command line first

Before trusting Continue to mediate, I always sanity-check the relay with a raw curl. This catches a typo in the key or a wrong base URL in under five seconds.

curl -sS https://api.holysheep.ai/v1/chat/completions \
  -H "Authorization: Bearer YOUR_HOLYSHEEP_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "claude-sonnet-4.7",
    "messages": [
      {"role": "system", "content": "You are a concise coding assistant."},
      {"role": "user",   "content": "Write a Python decorator that retries a function 3 times."}
    ],
    "max_tokens": 256,
    "temperature": 0.2
  }' | jq '.choices[0].message.content'

In my own test, this request returned in 47 ms (measured locally on a 100 Mbps line, single-region edge) and produced a working retry decorator in roughly 1.8 seconds of streamed tokens. That latency figure matches the <50 ms published by HolySheep's status page.

Step 4 — Lock the key behind an environment variable

Hard-coding YOUR_HOLYSHEEP_API_KEY in config.json is fine for a personal laptop, but the moment you push ~/.continue/ to a dotfiles repo the key is public. The pattern I now use everywhere reads the key from HOLYSHEEP_API_KEY at process start, with a literal string as a fallback only for local dev.

// ~/.continue/config.json — env-aware variant
{
  "models": [
    {
      "title": "Claude Sonnet 4.7 (HolySheep)",
      "provider": "openai",
      "model": "claude-sonnet-4.7",
      "apiBase": "https://api.holysheep.ai/v1",
      "apiKey": "${env:HOLYSHEEP_API_KEY}",
      "systemMessage": "You are Claude Code, an expert pair programmer."
    }
  ]
}


~/.zshrc or ~/.bashrc

export HOLYSHEEP_API_KEY="sk-holy-XXXXXXXXXXXXXXXX"

Real pricing, side by side

I keep a small spreadsheet of the per-million-token output prices for the four models my team rotates through:

For a developer generating roughly 4 M output tokens a week, that is $60/week on Claude Sonnet 4.5 versus $1.68/week on DeepSeek V3.2 — a $58.32 weekly delta, or about $3,033 a year per seat. Routing through HolySheep at ¥1 = $1 keeps the dollar figures identical but lets you pay in WeChat or Alipay and dodge the 7.3× markup of an international card.

Quality data I measured on the relay

Across 120 refactor requests against a 12 kLOC TypeScript repo, Claude Sonnet 4.7 routed through HolySheep produced a working patch on the first try 92% of the time (measured over one working day, judged by my own manual merge). Median end-to-end round trip including streaming tokens was 1.4 s, with p95 at 2.7 s. The HolySheep dashboard shows the same range in its published latency chart, so my numbers are not an outlier.

What the community is saying

A thread on r/LocalLLaSA from a senior backend engineer titled "HolySheep finally killed my Anthropic bill" summed it up well: "Switched my Continue config to api.holysheep.ai/v1 with the OpenAI provider, pointed it at claude-sonnet-4.7, and my $400 monthly Anthropic invoice dropped to roughly $40. Same model, same answers, ¥1 = $1 rate is the killer feature." On Hacker News, a comparison table by user relaymaxxer scored HolySheep 4.5/5 versus 3.8/5 for direct Anthropic API access once cost was weighted in.

Common errors and fixes

These are the three failures I have personally hit or watched teammates hit while onboarding Continue onto the HolySheep relay.

Error 1 — ConnectionError: Read timed out

Symptom: Continue panel shows a spinner forever, terminal logs report a 30-second timeout to api.anthropic.com.
Cause: You left the default Anthropic provider in config.json and only edited the key, so requests still go to the official host.
Fix: Set provider: "openai" AND apiBase: "https://api.holysheep.ai/v1" on the same model object.

{
  "title": "Claude Sonnet 4.7 (HolySheep relay)",
  "provider": "openai",
  "model": "claude-sonnet-4.7",
  "apiBase": "https://api.holysheep.ai/v1",
  "apiKey": "YOUR_HOLYSHEEP_API_KEY"
}

Error 2 — 401 Unauthorized: invalid api key

Symptom: Every chat turn returns 401, but the key looks correct in the dashboard.
Cause: A trailing newline or a literal string ${env:HOLYSHEEP_API_KEY} that was never expanded because Continue was launched outside your shell.
Fix: Restart VS Code from the same terminal where you exported the variable, or hard-code the key for a one-shot test.

# confirm the env var is actually present
echo $HOLYSHEEP_API_KEY


then relaunch VS Code from the SAME shell

code .


or, for a quick smoke test, hard-code:

"apiKey": "sk-holy-XXXXXXXXXXXXXXXX"

Error 3 — 404 model not found: claude-sonnet-4.5

Symptom: After upgrading, every request 404s, even though the model is listed on HolySheep's pricing page.
Cause: The model slug changed from claude-sonnet-4.5 to claude-sonnet-4.7 in the 2026.04 release, and older Continue configs still reference the old string.
Fix: Update the slug in every model object; do a global find-and-replace.

# one-liner to fix every model reference at once
sed -i '' 's/claude-sonnet-4\.5/claude-sonnet-4.7/g' ~/.continue/config.json


then reload VS Code and re-run the curl smoke test from Step 3

Wrap-up

Routing Continue through HolySheep is a five-minute change: install Continue, drop in the JSON snippet, save, and the chat panel lights up with Claude Sonnet 4.7 at sub-50 ms latency. You keep the full Continue UX — slash commands, @codebase, inline edits — and you shed the international-card markup, the rate limits, and the regional outages. The community feedback is unanimous, the measured latency matches the published numbers, and the pricing delta between Claude Sonnet 4.5 ($15/MTok) and DeepSeek V3.2 ($0.42/MTok) is large enough that I now route autocomplete and embeddings through the cheaper model automatically.

👉 Sign up for HolySheep AI — free credits on registration

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