> ## Documentation Index
> Fetch the complete documentation index at: https://docs.healops.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Deployment

> Deploy HealOps as a standard Python/FastAPI runtime

HealOps deploys as a standard Python/FastAPI runtime. Use the repo `Dockerfile`,
Railway, EC2, ECS, Vercel, or another ASGI-capable host.

## Runtime environment

<Steps>
  <Step title="Deploy the app">
    Deploy this repository using your hosting provider's normal app workflow.
  </Step>

  <Step title="Configure your model provider">
    Add `LLM_PROVIDER` as an environment variable (for example `anthropic`,
    `openai`, `openrouter`, or `gemini`).
  </Step>

  <Step title="Add the matching provider API key">
    Use the API key that matches your provider:

    * `ANTHROPIC_API_KEY` for `LLM_PROVIDER=anthropic`
    * `OPENAI_API_KEY` for `LLM_PROVIDER=openai`
    * `OPENROUTER_API_KEY` for `LLM_PROVIDER=openrouter`
    * `GEMINI_API_KEY` for `LLM_PROVIDER=gemini`
  </Step>

  <Step title="Add integration env vars and deploy">
    Add any storage and integration environment variables required by your runtime, then deploy and verify health.
  </Step>
</Steps>

Minimum LLM environment example:

```bash theme={null}
LLM_PROVIDER=anthropic
ANTHROPIC_API_KEY=...
```

The complete list of provider keys and optional model overrides is documented in `.env.example`.

## Railway deployment

Railway is still supported as a hosted runtime option.

Before deploying on Railway, make sure your service has:

* `DATABASE_URI` pointing to your Railway Postgres instance
* `REDIS_URI` pointing to your Railway Redis instance

Then deploy the service using your Railway project workflow.