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Quickstart

Get from zero to your first proxied request in a few minutes.

1. Deploy OpenProxyAI​

curl -sSL openproxy.ai/install.sh | sh
cd openproxy && docker compose up -d

This starts the proxy, Postgres (with pgvector for semantic caching), and Redis. See Deploying with Docker Compose for a full walkthrough, or Deploying with Helm for a production Kubernetes setup.

2. Register an organization​

curl -X POST https://api.openproxy.ai/api/v1/auth/register \
  -H "Content-Type: application/json" \
  -d '{
    "email": "you@company.com",
    "password": "a-strong-password",
    "name": "Your Name",
    "org_name": "Your Org"
  }'

The response includes an access_token — use it to sign in to the admin console and issue your first API key.

3. Create an API key​

From the admin console (or POST /api/v1/api-keys), create a key scoped to proxy:llm. Keys are shown once at creation — store them in a secret manager, not in source control. See Authentication for the full key lifecycle.

4. Send your first request​

OpenProxyAI is OpenAI-API-compatible. Point any existing OpenAI SDK at it:

from openai import OpenAI

client = OpenAI(
    base_url="https://api.openproxy.ai/v1",
    api_key=os.environ["OPENPROXY_KEY"],
)

response = client.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": "hello"}],
    extra_headers={
        "x-op-team": "eng-platform",
        "x-op-policy": "pii_redact,topic_guard",
    },
)

The x-op-team header attributes cost to a team's budget. x-op-policy selects which guardrail policies apply to this request — see Policies & Guardrails.

5. Verify it worked​

Check the response headers or the admin console's request log — you should see the request logged with its cost, latency breakdown, and cache status (hit or miss).

Next steps​