> ## Documentation Index
> Fetch the complete documentation index at: https://cerebrium-mintlify-de397217.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

> ## Agent Instructions
> Cerebrium's documentation MCP server is available at https://cerebrium.ai/docs/mcp for searching and querying these docs directly. Install the Cerebrium agent skill with `npx skills add https://cerebrium.ai/docs`. Append .md to any docs page URL to fetch that page as plain Markdown. API keys and authentication tokens are created in the Cerebrium dashboard at https://dashboard.cerebrium.ai.

# Custom Python Web Servers

> Run FastAPI and other ASGI or WSGI Python web servers on Cerebrium with a custom runtime by setting the entrypoint, port, and health check endpoints.

Cerebrium's default runtime covers most app needs. For more control, use ASGI or WSGI servers through the custom runtime feature. This enables custom authentication, dynamic batching, frontend dashboards, public endpoints, and WebSocket connections.

## Setting Up Custom Servers

A basic FastAPI server running as a custom server on Cerebrium:

```python theme={null}
from fastapi import FastAPI
app = FastAPI()

@app.post("/hello")
def hello():
    return {"message": "Hello Cerebrium!"}

@app.get("/health")
def health():
    return "OK"

@app.get("/ready")
def ready():
    return "OK"
```

Configure this server in `cerebrium.toml` by adding a custom runtime section:

```toml theme={null}
[cerebrium.runtime.custom]
port = 5000
entrypoint = ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "5000"]
healthcheck_endpoint = "/health"
readycheck_endpoint = "/ready"

[cerebrium.dependencies.pip]
pydantic = "latest"
numpy = "latest"
loguru = "latest"
fastapi = "latest"
```

The configuration requires four key parameters:

* `entrypoint`: The command that starts your server
* `port`: The port your server listens on
* `healthcheck_endpoint`: The endpoint used to confirm instance health. If unspecified, defaults to a TCP ping on the configured port. If the health check registers a non-200 response, Cerebrium considers the instance *unhealthy* and restarts it if it does not recover in time.
* `readycheck_endpoint`: The endpoint used to confirm if the instance is ready to receive. If unspecified, defaults to a TCP ping on the configured port. If the ready check registers a non-200 response, Cerebrium does not route requests to the instance.

<Info>
  For ASGI applications like FastAPI, include the appropriate server package
  (like `uvicorn`) in your dependencies. After deployment, your endpoints become
  available at
  `https://api.cerebrium.ai/v4/p-xxxxxxxx/[app-name]/your/endpoint`.
</Info>

The [FastAPI Server Example](https://github.com/CerebriumAI/examples) provides a complete implementation.

## Request Headers

Custom web servers receive the Cerebrium run ID in the `X-Request-Id` header on every request. This corresponds to the internal `run_id` and is useful for tracking and debugging.