# Source: https://www.traceloop.com/docs/openllmetry/privacy/traces.md

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

# Prompts, Completions and Embeddings

**By default, OpenLLMetry logs prompts, completions, and embeddings to span attributes.**
This gives you a clear visibility into how your LLM application is working, and can make it easy to debug and evaluate the quality of the outputs.

However, you may want to disable this logging for privacy reasons, as they may contain highly sensitive data from your users.
You may also simply want to reduce the size of your traces.

## Disabling logging globally

To disable logging, set the `TRACELOOP_TRACE_CONTENT` environment variable to `false`.
On Typescript/Javascript you can also pass the `traceContent` option.

<CodeGroup>
  ```bash Environment Variable theme={null}
  TRACELOOP_TRACE_CONTENT=false
  ```

  ```js Typescript / Javascript theme={null}
  Traceloop.initialize({ traceContent: false });
  ```
</CodeGroup>

OpenLLMetry SDK, as well as all individual instrumentations will respect this setting.

## Enabling logging selectively in specific workflows / tasks

You can decide to selectively enable prompt logging for specific workflows, tasks, agents, or tools, using the annotations API.
If you don't specify a `traceContent` option, the global setting will be used.

<CodeGroup>
  ```js Typescript / Javascript theme={null}
  return await traceloop.withWorkflow(
      { name: "workflow_name", traceContent: false },
      async () => {
          ...
      }
    );
  ```

  ```js Typescript - with Decorators theme={null}
  class MyClass {
    @traceloop.workflow({ traceContent: false })
    async some_workflow() {
      ...
    }
  }
  ```
</CodeGroup>

## Enabling logging selectively for specific users

You can decide to selectively enable or disable prompt logging for specific users or workflows.

### Using the Traceloop Platform

We have an API to enable content tracing for specific users, as defined by [association entities](/openllmetry/tracing/association).
See the [Traceloop API documentation](/api-reference/tracing/whitelist_user) for more information.

### Without the Traceloop Platform

Set a key called `override_enable_content_tracing` in the OpenTelemetry context to `True` right before making the LLM call
you want to trace with prompts.
This will create a new context that will instruct instrumentations to log prompts and completions as span attributes.

```python Python theme={null}
from opentelemetry.context import attach, set_value

attach(set_value("override_enable_content_tracing", True))
```

Make sure to also disable it afterwards:

```python Python theme={null}
from opentelemetry.context import attach, set_value

attach(set_value("override_enable_content_tracing", False))
```