### DISCLAIMER > As of 6th March 2025, debugger is still in development. We plan to merge it behind a staff-only feature flag for staff use only, followed by non-public release and then finally a public one (akin to how Git panel release was handled). This is done to ensure the best experience when it gets released. ### END OF DISCLAIMER **The current state of the debugger implementation:** https://github.com/user-attachments/assets/c4deff07-80dd-4dc6-ad2e-0c252a478fe9 https://github.com/user-attachments/assets/e1ed2345-b750-4bb6-9c97-50961b76904f ---- All the todo's are in the following channel, so it's easier to work on this together: https://zed.dev/channel/zed-debugger-11370 If you are on Linux, you can use the following command to join the channel: ```cli zed https://zed.dev/channel/zed-debugger-11370 ``` ## Current Features - Collab - Breakpoints - Sync when you (re)join a project - Sync when you add/remove a breakpoint - Sync active debug line - Stack frames - Click on stack frame - View variables that belong to the stack frame - Visit the source file - Restart stack frame (if adapter supports this) - Variables - Loaded sources - Modules - Controls - Continue - Step back - Stepping granularity (configurable) - Step into - Stepping granularity (configurable) - Step over - Stepping granularity (configurable) - Step out - Stepping granularity (configurable) - Debug console - Breakpoints - Log breakpoints - line breakpoints - Persistent between zed sessions (configurable) - Multi buffer support - Toggle disable/enable all breakpoints - Stack frames - Click on stack frame - View variables that belong to the stack frame - Visit the source file - Show collapsed stack frames - Restart stack frame (if adapter supports this) - Loaded sources - View all used loaded sources if supported by adapter. - Modules - View all used modules (if adapter supports this) - Variables - Copy value - Copy name - Copy memory reference - Set value (if adapter supports this) - keyboard navigation - Debug Console - See logs - View output that was sent from debug adapter - Output grouping - Evaluate code - Updates the variable list - Auto completion - If not supported by adapter, we will show auto-completion for existing variables - Debug Terminal - Run custom commands and change env values right inside your Zed terminal - Attach to process (if adapter supports this) - Process picker - Controls - Continue - Step back - Stepping granularity (configurable) - Step into - Stepping granularity (configurable) - Step over - Stepping granularity (configurable) - Step out - Stepping granularity (configurable) - Disconnect - Restart - Stop - Warning when a debug session exited without hitting any breakpoint - Debug view to see Adapter/RPC log messages - Testing - Fake debug adapter - Fake requests & events --- Release Notes: - N/A --------- Co-authored-by: Piotr Osiewicz <24362066+osiewicz@users.noreply.github.com> Co-authored-by: Anthony Eid <hello@anthonyeid.me> Co-authored-by: Anthony <anthony@zed.dev> Co-authored-by: Piotr Osiewicz <peterosiewicz@gmail.com> Co-authored-by: Piotr <piotr@zed.dev>
3.7 KiB
Zed Model Improvement
Zed Assistant
When using the Zed Assistant, Zed does not persistently store user content or use user content for training of its models.
When using upstream services through Zed AI, we require similar assurances from our service providers. For example, usage of Anthropic Claude 3.5 via Zed AI in the Assistant is governed by the Anthropic Commercial Terms which includes the following:
"Anthropic may not train models on Customer Content from paid Services."
When you directly connect the Zed Assistant with a non Zed AI service (e.g. via API key) Zed does not have access to your user content. Users should reference their agreement with the service provider to understand what terms and conditions apply.
Zed 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.
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:
{
"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 in their Zed settings.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.
Model Output
We then use this training dataset to fine-tune Qwen2.5-Coder-7B and make the resulting model available at huggingface.co/zed-industries/zeta.
Applicable terms
Please see the Zed Terms of Service for more.