Drop the `count_tokens` API and related implementations across
providers, and remove the unused `tiktoken-rs` dependency.
I was going to update the dependency becuase they finally released a fix
we needed. But then I realized we only used this api in one place, the
Rules library. And for most models it would have been wildly incorrect
becuase we use tiktoken, i.e. OpenAI tokenizers, for almost every model,
which is going to give incorrect results.
Given that, I just removed these because the difference in how we get
these has caused plenty of confusion in the past.
Self-Review Checklist:
- [x] I've reviewed my own diff for quality, security, and reliability
- [x] Unsafe blocks (if any) have justifying comments
- [x] The content is consistent with the [UI/UX
checklist](https://github.com/zed-industries/zed/blob/main/CONTRIBUTING.md#uiux-checklist)
- [x] Tests cover the new/changed behavior
- [x] Performance impact has been considered and is acceptable
Release Notes:
- N/A
- `language_model` no longer depends on provider-specific crates such as
`anthropic` and `open_ai` (inverted dependency)
- `language_model_core` was extracted from `language_model` which
contains the types for the provider-specific crates to convert to/from.
- `gpui::SharedString` has been extracted into its own crate (still
exposed by `gpui`), so `language_model_core` and provider API crates
don't have to depend on `gpui`.
- Removes some unnecessary `&'static str` | `SharedString` -> `String`
-> `SharedString` conversions across the codebase.
- Extracts the core logic of the cloud `LanguageModelProvider` into its
own crate with simpler dependencies.
Release Notes:
- N/A
---------
Co-authored-by: John Tur <john-tur@outlook.com>
Release Notes:
- Added support for Grok 4.1 Fast (reasoning and non-reasoning) models
in the xAI provider, with 2M token context windows and full vision
capabilities.
- Extended 2M token context to existing Grok 4 Fast variants (from 128K)
for consistency with xAI updates.
- Enabled image/vision support for all Grok 4 family models.
Doc:
https://docs.x.ai/docs/models/grok-4-1-fast-reasoninghttps://docs.x.ai/docs/models/grok-4-1-fast-non-reasoning
We've been considering removing workspace-hack for a couple reasons:
- Lukas ran into a situation where its build script seemed to be causing
spurious rebuilds. This seems more likely to be a cargo bug than an
issue with workspace-hack itself (given that it has an empty build
script), but we don't necessarily want to take the time to hunt that
down right now.
- Marshall mentioned hakari interacts poorly with automated crate
updates (in our case provided by rennovate) because you'd need to have
`cargo hakari generate && cargo hakari manage-deps` after their changes
and we prefer to not have actions that make commits.
Currently removing workspace-hack causes our workspace to grow from
~1700 to ~2000 crates being built (depending on platform), which is
mainly a problem when you're building the whole workspace or running
tests across the the normal and remote binaries (which is where
feature-unification nets us the most sharing). It doesn't impact
incremental times noticeably when you're just iterating on `-p zed`, and
we'll hopefully get these savings back in the future when
rust-lang/cargo#14774 (which re-implements the functionality of hakari)
is finished.
Release Notes:
- N/A
After the change, we can add "supports_images", "supports_tools" and
"parallel_tool_calls" properties to set up new models. Our
`settings.json` will be as follows:
```json
"language_models": {
"x_ai": {
"api_url": "https://api.x.ai/v1",
"available_models": [
{
"name": "grok-4-fast-reasoning",
"display_name": "Grok 4 Fast Reasoning",
"max_tokens": 2000000,
"max_output_tokens": 64000,
"supports_tools": true,
"parallel_tool_calls": true,
},
{
"name": "grok-4-fast-non-reasoning",
"display_name": "Grok 4 Fast Non-Reasoning",
"max_tokens": 2000000,
"max_output_tokens": 64000,
"supports_images": true,
}
]
}
}
```
Closes https://github.com/zed-industries/zed/issues/38752
Release Notes:
- xAI: Added support for for configuring tool and image support for
custom model configurations
Some APIs fail when they get this parameter
Closes#36215
Release Notes:
- Fixed OpenAI-compatible providers that don't support prompt caching
and/or reasoning
Bennet Bo Fenner