Home Explore Blog CI



zed

2nd chunk of `docs/src/ai/ai-improvement.md`
2a9dc58deed05debfca4956c34dd526e459cbc1f6df7d65f0000000100000dc1
This data includes:

- The prompt given to the Agent
- Any commentary you include
- Product telemetry about the agentic thread
- Metadata about your Zed installation

### Data Handling

Collected data is stored in Snowflake, a private database where we track other metrics. We periodically review this data to improve our overall agentic approach and refine the product via our system prompt, tool use, etc. We ensure any included data is anonymized and contains no sensitive information (access tokens, user IDs, email addresses, etc).

## Edit Predictions

By default, when using Zed Edit Predictions, Zed does not persistently store user content or use user content for training of its models.

### Opt-in

Users who are working on open source licensed projects may optionally opt-in to providing model improvement feedback. This opt-in occurs on a per-project basis. If you work on multiple open source projects and wish to provide model improvement feedback you will have to opt-in for each individual project.

When working on other projects where you haven't opted-in, Zed will not persistently store user content or use user content for training of its models.

You can see exactly how Zed detects open source licenses in: [license_detection.rs](https://github.com/zed-industries/zed/blob/main/crates/zeta/src/license_detection.rs).

### Exclusions

Zed will intentionally exclude certain files from Predictive Edits entirely, even when you have opted-in to model improvement feedback.

You can inspect this exclusion list by opening `zed: open default settings` from the command palette:

```json
{
  "edit_predictions": {
    // A list of globs representing files that edit predictions should be disabled for.
    // There's a sensible default list of globs already included.
    // Any addition to this list will be merged with the default list.
    "disabled_globs": [
      "**/.env*",
      "**/*.pem",
      "**/*.key",
      "**/*.cert",
      "**/*.crt",
      "**/secrets.yml"
    ]
  }
}
```

Users may explicitly exclude additional paths and/or file extensions by adding them to [`edit_predictions.disabled_globs`](https://zed.dev/docs/configuring-zed#edit-predictions) in their Zed settings.json:

```json
{
  "edit_predictions": {
    "disabled_globs": ["secret_dir/*", "**/*.log"]
  }
}
```

### Data we collect

For open source projects where you have opted-in, Zed may store copies of requests and responses to the Zed AI Prediction service.

This data includes:

- the edit prediction
- a portion of the buffer content around the cursor
- a few recent edits
- the current buffer outline
- diagnostics (errors, warnings, etc) from language servers

### Data Handling

Collected data is stored in Snowflake, a private database where we track other metrics. We periodically review this data to select training samples for inclusion in our model training dataset. We ensure any included data is anonymized and contains no sensitive information (access tokens, user IDs, email addresses, etc). This training dataset is publicly available at [huggingface.co/datasets/zed-industries/zeta](https://huggingface.co/datasets/zed-industries/zeta).

### Model Output

We then use this training dataset to fine-tune [Qwen2.5-Coder-7B](https://huggingface.co/Qwen/Qwen2.5-Coder-7B) and make the resulting model available at [huggingface.co/zed-industries/zeta](https://huggingface.co/zed-industries/zeta).

## Applicable terms

Please see the [Zed Terms of Service](https://zed.dev/terms-of-service) for more.

Title: Zed AI: Data Handling, Exclusions, and Model Output for Edit Predictions
Summary
This section details data handling for Zed's Edit Predictions, focusing on Snowflake storage, data anonymization, and a publicly available training dataset on Hugging Face. Users can opt-in for open-source projects on a per-project basis, while Zed automatically excludes sensitive files. Data collected includes edit predictions, buffer content, recent edits, buffer outline, and diagnostics. The data is used to fine-tune the Qwen2.5-Coder-7B model, and the resulting model is available on Hugging Face. Additional exclusions can be configured in Zed settings. The Zed Terms of Service apply.