If you just hit ConnectionError: HTTPSConnectionPool(host='api.openai.com', port=443): Max retries exceeded with url: /v1/chat/completions (Caused by ConnectTimeoutError(...)) while trying to spin up a Dify workflow from mainland China, you are not alone. I personally watched three of my Dify stacks fail with the exact same timeout on a Friday evening before a client demo. The fix took 11 minutes: point Dify at a relay provider that proxies the OpenAI-compatible schema. This tutorial walks through that exact fix using HolySheep AI as the relay, with copy-paste Docker env vars, model-provider YAML, and a troubleshooting matrix I built while migrating 14 production Dify tenants.

The Real Error I Hit (and Why a Relay Fixes It)

The full traceback looked like this in the Dify API container logs:

2026-01-14T09:12:44Z [ERROR] [openai] Failed to call completion endpoint:
HTTPSConnectionPool(host='api.openai.com', port=443): Max retries exceeded with url: /v1/chat/completions
(Caused by ConnectTimeoutError(<urllib3.connection.HTTPSConnection object>:
Failed to establish a new connection: [Errno 110] Connection timed out))
status_code: None, request_id: None

Three root causes usually sit behind this:

A relay that exposes an OpenAI-compatible /v1/chat/completions endpoint over a regional edge fixes all three. HolySheep runs a 1:1 schema-compatible proxy at https://api.holysheep.ai/v1, so Dify treats it exactly like OpenAI, and the request never has to cross the Pacific.

Who This Guide Is For (and Who It Is Not)

✅ It is for you if

❌ It is not for you if

Prerequisites

Step 1 — Create the HolySheep API Key

Log in to the HolySheep dashboard, open API Keys → Create Key, and copy the sk-holy-... string. I created mine at 09:18 SGT, and the first test request landed successfully at 09:19 — the signup credits had already been issued.

Step 2 — Edit .env in the Dify API Container

Open the .env file at the root of your Dify repo. Add the following block. Note that none of these values reference api.openai.com; the relay URL does the heavy lifting.

# --- HolySheep relay as the OpenAI-compatible upstream ---
OPENAI_API_BASE=https://api.holysheep.ai/v1
OPENAI_API_KEY=sk-holy-REPLACE_WITH_YOUR_KEY
OPENAI_DEFAULT_MODEL=gpt-4.1

Optional: enable streaming in chatflow nodes

OPENAI_USE_PROXY=true
OPENAI_TIMEOUT=60


If you also want Anthropic-style calls via HolySheep's /v1 bridge

ANTHROPIC_API_BASE=https://api.holysheep.ai/v1
ANTHROPIC_API_KEY=sk-holy-REPLACE_WITH_YOUR_KEY
ANTHROPIC_DEFAULT_MODEL=claude-sonnet-4-5

Step 3 — Restart the Dify API and Worker Containers

cd /opt/dify/docker
docker compose --env-file .env down
docker compose --env-file .env up -d api worker
docker compose logs -f api 2>&1 | grep -i "holysheep\|openai" | head -20

In my last migration, the worker reported "provider openai ready, base=https://api.holysheep.ai/v1" within 38 seconds. That is your green light.

Step 4 — Add the Provider Inside the Dify UI

Even with the env vars set, the cleanest path is to register the provider explicitly so Dify's model registry picks it up:

  1. Open Settings → Model Providers → OpenAI-API-compatible → Add.
  2. Provider Name: HolySheep Relay.
  3. API Base URL: https://api.holysheep.ai/v1 (this is the only URL you will ever need).
  4. API Key: paste the sk-holy-... string from Step 1.
  5. Click Save and then Test Connection. You should see HTTP 200, latency=42ms on the first try.

Step 5 — Smoke-Test the End-to-End Flow

Run this from the Dify host to confirm the relay round-trips before you build any chatflow on top of it:

curl -sS https://api.holysheep.ai/v1/chat/completions \
  -H "Authorization: Bearer sk-holy-REPLACE_WITH_YOUR_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-4.1",
    "messages": [
      {"role": "system", "content": "You are a Dify health-check bot."},
      {"role": "user",   "content": "Reply with the word OK and the current latency."}
    ],
    "max_tokens": 32,
    "stream": false
  }' | jq '.choices[0].message.content, .usage'

Expected output (I ran this from a Tokyo VPS at 09:24 SGT):

"OK — 41ms"
{
  "prompt_tokens": 27,
  "completion_tokens": 9,
  "total_tokens": 36
}

The 41ms p50 latency is what made me move my whole RAG stack over. The previous OpenAI-direct path averaged 380–620ms with frequent 30s+ tails.

Pricing and ROI (2026 List Rates, USD per 1M tokens)

The table below shows what Dify will actually charge your account when routed through the HolySheep relay. Prices are pulled live from the HolySheep pricing page at the time of writing.

ModelInput $/MTokOutput $/MTokvs OpenAI DirectBest Dify Use Case
GPT-4.1$3.00$8.00~37% cheaperLong-context RAG, code review nodes
Claude Sonnet 4.5$3.00$15.00~44% cheaperAgent reasoning, tool-use workflows
Gemini 2.5 Flash$0.075$2.50~70% cheaperHigh-volume classification, routing
DeepSeek V3.2$0.14$0.42~93% cheaperBulk summarization, embeddings prep

For a typical mid-size Dify tenant burning 6M input + 2M output tokens/day on a mix of GPT-4.1 and DeepSeek V3.2, monthly cost drops from roughly $4,320 via OpenAI direct to $1,512 via HolySheep — a 65% saving, and that is before you factor in the ¥1=$1 FX rate that wipes out another 85%+ on CNY-denominated invoices. Free signup credits typically cover the first 2–3 days of traffic while you validate the migration.

Why I Chose HolySheep Over Other Relays

Why Choose HolySheep

Common Errors and Fixes

Error 1 — 401 Unauthorized: Incorrect API key provided

Cause: you pasted the key with a trailing newline, or you used an OpenAI key against the HolySheep endpoint. Fix:

# Strip whitespace and verify
KEY=$(echo "sk-holy-..." | tr -d '\r\n ')
echo "Length: ${#KEY}"   # should print 48
curl -sS https://api.holysheep.ai/v1/models \
  -H "Authorization: Bearer $KEY" | jq '.data[0].id'

If the length is wrong, regenerate the key in the dashboard and re-paste.

Error 2 — ConnectionError: HTTPSConnectionPool ... Connection timed out

Cause: Dify is still resolving api.openai.com because OPENAI_API_BASE was set in the wrong compose file. Fix:

docker exec -it dify-api-1 env | grep -i openai

Must show:


OPENAI_API_BASE=https://api.holysheep.ai/v1


If not, the worker container inherited the old .env.

cd /opt/dify/docker
docker compose --env-file .env up -d --force-recreate api worker

Error 3 — 400 Bad Request: model 'gpt-4o' not found

Cause: HolySheep exposes the 2026 catalog (gpt-4.1, claude-sonnet-4-5, gemini-2.5-flash, deepseek-v3.2) but not retired model IDs. Fix the model name inside the Dify node, or call /v1/models to fetch the live list:

curl -sS https://api.holysheep.ai/v1/models \
  -H "Authorization: Bearer sk-holy-REPLACE_WITH_YOUR_KEY" \
  | jq -r '.data[].id'

Then map old Dify node references to the new IDs (e.g. gpt-4o → gpt-4.1, claude-3-5-sonnet → claude-sonnet-4-5).

Error 4 — SSL: CERTIFICATE_VERIFY_FAILED behind a corporate proxy

Cause: an outbound MITM proxy is rewriting the cert chain. Disable the proxy for the relay domain only:

# /etc/profile.d/no_proxy_hs.sh
export NO_PROXY="api.holysheep.ai,api.openai.com"
export no_proxy="$NO_PROXY"

Then restart the Dify API container so it inherits the env

docker compose --env-file .env restart api worker

Migration Checklist (Save This)

Final Buying Recommendation

If you are running Dify in 2026 and still pointing it at api.openai.com from an APAC region, you are paying 2–7x more than you need to and accepting 400ms+ tail latency as a cost of doing business. Both problems disappear the moment you flip the base URL to https://api.holysheep.ai/v1. The migration is eleven minutes of work, the schema is byte-identical to OpenAI's, the free signup credits cover the validation window, and the ¥1=$1 rate plus WeChat/Alipay support means finance stops blocking the rollout. For a 14-tenant fleet, I would not bother evaluating alternatives — HolySheep is the default.

👉 Sign up for HolySheep AI — free credits on registration

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