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

# Send to OpenLIT

> Configure the OpenLIT SDK to send traces and metrics to a self-hosted OpenLIT platform instance

OpenLIT ships with a built-in OpenTelemetry Collector. When you self-host the OpenLIT platform, it exposes an OTLP HTTP endpoint on port `4318` that accepts traces, metrics, and logs from your applications.

## Get started

<Steps>
  <Step title="Deploy the OpenLIT platform">
    If you haven't deployed OpenLIT yet, follow the [Installation Guide](/openlit/installation) to set it up.

    Common platform endpoints:

    | Deployment         | Endpoint                                        |
    | ------------------ | ----------------------------------------------- |
    | Local development  | `http://127.0.0.1:4318`                         |
    | Docker Compose     | `http://localhost:4318`                         |
    | Kubernetes         | `http://openlit.openlit.svc.cluster.local:4318` |
    | External / Ingress | Your configured external endpoint               |
  </Step>

  <Step title="Install the OpenLIT SDK">
    <Tabs>
      <Tab title="Python">
        ```shell theme={null}
        pip install openlit
        ```
      </Tab>

      <Tab title="TypeScript">
        ```shell theme={null}
        npm install openlit
        ```
      </Tab>
    </Tabs>
  </Step>

  <Step title="Configure the SDK to send to OpenLIT">
    <Tabs>
      <Tab title="Python">
        **Using function arguments:**

        ```python theme={null}
        import openlit

        openlit.init(
            otlp_endpoint="http://127.0.0.1:4318"
        )
        ```

        **Using environment variables:**

        ```shell theme={null}
        export OTEL_EXPORTER_OTLP_ENDPOINT="http://127.0.0.1:4318"
        export OTEL_SERVICE_NAME="my-ai-service"
        export OTEL_DEPLOYMENT_ENVIRONMENT="production"
        ```

        ```python theme={null}
        import openlit

        openlit.init()
        ```
      </Tab>

      <Tab title="TypeScript">
        **Using function arguments:**

        ```typescript theme={null}
        import Openlit from 'openlit';

        Openlit.init({
            otlpEndpoint: 'http://127.0.0.1:4318'
        });
        ```

        **Using environment variables:**

        ```shell theme={null}
        export OTEL_EXPORTER_OTLP_ENDPOINT="http://127.0.0.1:4318"
        ```

        ```typescript theme={null}
        import Openlit from 'openlit';

        Openlit.init();
        ```
      </Tab>
    </Tabs>

    Replace `http://127.0.0.1:4318` with your actual OpenLIT platform endpoint if different.
  </Step>
</Steps>

## No authentication required

By default, the OpenLIT platform's OTLP endpoint does not require authentication headers. You only need to set `otlp_endpoint`.

<Note>
  If you expose the OpenLIT platform endpoint externally via an ingress or load balancer, configure authentication at the infrastructure level (e.g., mutual TLS or an API gateway) rather than in the SDK.
</Note>

## Full example

```python theme={null}
import openlit
import openai

openlit.init(
    otlp_endpoint="http://127.0.0.1:4318",
    service_name="my-ai-service",
    environment="production"
)

client = openai.OpenAI()
response = client.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": "Hello!"}]
)
print(response.choices[0].message.content)
```

Traces from this application appear in the OpenLIT platform under the service name `my-ai-service`.

***

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  </Card>

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    Route traces through the Datadog Agent to the Datadog backend
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