Gateway Quickstart

Use this path if you need one shared OpenAI-compatible endpoint for a team or platform.

If you need a Docker or database-first setup, use the Docker + Database tutorial. Otherwise, use the steps below to get to a working request fast.

1. Install The Gateway

uv tool install 'litellm[proxy]'

2. Set One Provider Key

export OPENAI_API_KEY="your-api-key"

3. Create config.yaml

model_list:
  - model_name: gpt-4o-mini
    litellm_params:
      model: openai/gpt-4o-mini
      api_key: os.environ/OPENAI_API_KEY

general_settings:
  master_key: sk-1234
  database_url: postgresql://llmproxy:dbpassword9090@db:5432/litellm

4. Start The Gateway

litellm --config config.yaml

You should see the proxy start on http://0.0.0.0:4000.

5. Send Your First Request

curl -X POST 'http://0.0.0.0:4000/chat/completions' \
  -H 'Content-Type: application/json' \
  -H 'Authorization: Bearer sk-1234' \
  -d '{
    "model": "gpt-4o-mini",
    "messages": [
      {"role": "user", "content": "Hello from LiteLLM Gateway"}
    ]
  }'

6. Check The Response

If the request succeeds, the proxy returns 200 OK with an OpenAI-style response.

The assistant text will be in:

choices[0].message.content

If your gateway is routing to OpenAI, a real response can look like this:

{
  "id": "chatcmpl-abc123",
  "created": 1677858242,
  "model": "gpt-4o-mini-2024-07-18",
  "object": "chat.completion",
  "system_fingerprint": "fp_406d6473f8",
  "choices": [
    {
      "finish_reason": "stop",
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "Hello! How can I assist you today?",
        "tool_calls": null,
        "function_call": null,
        "annotations": []
      }
    }
  ],
  "usage": {
    "completion_tokens": 9,
    "prompt_tokens": 13,
    "total_tokens": 22,
    "completion_tokens_details": {
      "accepted_prediction_tokens": 0,
      "audio_tokens": 0,
      "reasoning_tokens": 0,
      "rejected_prediction_tokens": 0
    },
    "prompt_tokens_details": {
      "audio_tokens": 0,
      "cached_tokens": 0
    }
  },
  "service_tier": "default"
}

id, created, the resolved model version, token counts, and message text will vary by request. Other providers may return a smaller or slightly different set of fields, but choices[0].message.content is the main field to read.

7. Add Keys And The UI

If you need virtual keys, spend tracking, or the admin UI, add a database next.

• Add database_url under general_settings
• Use Virtual keys for key creation and budgets
• Use Admin UI to manage models and keys
• Use the Docker + Database tutorial if you want a fuller setup

8. Pick Your Next Step

🖥️

Make LLM Requests

Point LiteLLM or OpenAI-compatible clients to the gateway.

🎛️

Model Config

Add more models and gateway settings.

🔑

Virtual Keys

Create keys, budgets, and access controls.

📈

Add Logging

Capture logs, spend, and traces.

🔀

Load Balance

Route across deployments, regions, or providers.

🛡️

Add Guardrails

Add safety checks and policy enforcement.

📊

Reliability

Configure retries, fallbacks, and timeouts.

When To Use The SDK Path Instead

If you only need to call models from one application and do not need centralized auth or shared infrastructure, start with the SDK Quickstart instead.