Users now accept ToS from Zed's website when they sign in to Zed the
first time. So it's no longer possible that a signed in account could
not have accepted the ToS.
Release Notes:
- N/A
---------
Co-authored-by: Mikayla Maki <mikayla.c.maki@gmail.com>
This PR identifies automatic configuration options that users can select
from the agent panel. If no default provider is set in their settings,
the PR defaults to the first recommended option. Additionally, it
updates the selected provider for a thread when a user changes the
default provider through the settings file, if the thread hasn't had any
queries yet.
Release Notes:
- agent: automatically select a language model provider if there's no
user set provider.
---------
Co-authored-by: Michael Sloan <michael@zed.dev>
This removes around 900 unnecessary clones, ranging from cloning a few
ints all the way to large data structures and images.
A lot of these were fixed using `cargo clippy --fix --workspace
--all-targets`, however it often breaks other lints and needs to be run
again. This was then followed up with some manual fixing.
I understand this is a large diff, but all the changes are pretty
trivial. Rust is doing some heavy lifting here for us. Once I get it up
to speed with main, I'd appreciate this getting merged rather sooner
than later.
Release Notes:
- N/A
We'll now use the anthropic provider to get credentials for `claude` and
embed its configuration view in the panel when they are not present.
Release Notes:
- N/A
### TL;DR
* Adds `capabilities` configuration for OpenAI-compatible models
* Relates to
https://github.com/zed-industries/zed/issues/36215#issuecomment-3193920491
### Summary
This PR introduces support for configuring model capabilities for
OpenAI-compatible language models. The implementation addresses the
issue that not all OpenAI-compatible APIs support the same features -
for example, Cerebras' API explicitly does not support
`parallel_tool_calls` as documented in their [OpenAI compatibility
guide](https://inference-docs.cerebras.ai/resources/openai#currently-unsupported-openai-features).
### Changes
1. **Model Capabilities Structure**:
- Added `ModelCapabilityToggles` struct for UI representation with
boolean toggle states
- Implemented proper parsing of capability toggles into
`ModelCapabilities`
2. **UI Updates**:
- Modified the "Add LLM Provider" modal to include checkboxes for each
capability
- Each OpenAI-compatible model can now be configured with its specific
capabilities through the UI
3. **Configuration File Structure**:
- Updated the settings schema to support a `capabilities` object for
each `openai_compatible` model
- Each capability (`tools`, `images`, `parallel_tool_calls`,
`prompt_cache_key`) can be individually specified per model
### Example Configuration
```json
{
"openai_compatible": {
"Cerebras": {
"api_url": "https://api.cerebras.ai/v1",
"available_models": [
{
"name": "gpt-oss-120b",
"max_tokens": 131000,
"capabilities": {
"tools": true,
"images": false,
"parallel_tool_calls": false,
"prompt_cache_key": false
}
}
]
}
}
}
```
### Tests Added
- Added tests to verify default capability values are correctly applied
- Added tests to verify that deselected toggles are properly parsed as
`false`
- Added tests to verify that mixed capability selections work correctly
Thanks to @osyvokon for the desired `capabilities` configuration
structure!
Release Notes:
- OpenAI-compatible models now have configurable capabilities (#36370;
thanks @calesennett)
---------
Co-authored-by: Oleksiy Syvokon <oleksiy@zed.dev>
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
Release Notes:
- Added `reasoning_effort` support to custom models
Tested using the following config:
```json5
"language_models": {
"openai": {
"available_models": [
{
"name": "gpt-5-mini",
"display_name": "GPT 5 Mini (custom reasoning)",
"max_output_tokens": 128000,
"max_tokens": 272000,
"reasoning_effort": "high" // Can be minimal, low, medium (default), and high
}
],
"version": "1"
}
}
```
Docs:
https://platform.openai.com/docs/api-reference/chat/create#chat_create-reasoning_effort
This work could be used to split the GPT 5/5-mini/5-nano into each of
it's reasoning effort variant. E.g. `gpt-5`, `gpt-5 low`, `gpt-5
minimal`, `gpt-5 high`, and same for mini/nano.
Release Notes:
* Added a setting to control `reasoning_effort` in OpenAI models
## Summary
Enable image processing capabilities for GPT-5 series models by updating
the `supports_images()` method.
## Changes
- Add vision support for `gpt-5`, `gpt-5-mini`, and `gpt-5-nano` models
- Update `supports_images()` method in
`crates/language_models/src/provider/open_ai.rs`
## Models with Vision Support (after this PR)
- gpt-4o
- gpt-4o-mini
- gpt-4.1
- gpt-4.1-mini
- gpt-4.1-nano
- gpt-5 (new)
- gpt-5-mini (new)
- gpt-5-nano (new)
- o1
- o3
- o4-mini
This brings GPT-5 vision capabilities in line with other OpenAI models
that support image processing.
Release Notes:
- Added vision support for OpenAI models
Tested prompt:
John is one of 4 children. The first sister is 4 years old. Next year,
the second sister will be twice as old as the first sister. The third
sister is two years older than the second sister. The third sister is
half the age of her older brother. How old is John? Return your thinking
inside <think></think>
Release Notes:
- Add thinking to Mistral Provider
---------
Signed-off-by: Umesh Yadav <git@umesh.dev>
Co-authored-by: Peter Tripp <peter@zed.dev>
This uses the `current_user` watch in the `UserStore` instead of looping
every 100ms in order to detect if the user had signed in.
We are changing this because we noticed it was causing the deterministic
executor in tests to never detect a "parking with nothing left to run"
situation.
This seems better in production as well, especially for users who never
sign in.
/cc @maxdeviant
Release Notes:
- N/A
Co-authored-by: Ben Brandt <benjamin.j.brandt@gmail.com>
This is really just a small beginning, as there are many other icons to
be revised and cleaned up. Our current set is a bit of a mess in terms
of dimension, spacing, stroke width, and terminology. I'm sure there are
more non-used icons I'm not covering here, too. We'll hopefully tackle
it all soon leading up to 1.0.
Closes https://github.com/zed-industries/zed/issues/35576
Release Notes:
- N/A
This pull request should be idempotent, but lays the groundwork for
avoiding to connect to collab in order to interact with AI features
provided by Zed.
Release Notes:
- N/A
---------
Co-authored-by: Marshall Bowers <git@maxdeviant.com>
Co-authored-by: Richard Feldman <oss@rtfeldman.com>
This PR updates the Agent panel to work with the `CloudUserStore`
instead of the `UserStore`, reducing its reliance on being connected to
Collab to function.
Release Notes:
- N/A
---------
Co-authored-by: Richard Feldman <oss@rtfeldman.com>
Closes#26030
*Note: This is my first contribution to Zed*
This addresses a second streaming bottleneck in Bedrock that remained
after the initial fix in #28281 (released in preview 194).
The issue is in the mechanism used to convert Zed's internal `AsyncBody`
into the `SdkBody` expected by the Bedrock language provider. We are
using a non-streaming converter that buffers responses.
**How the fix works:**
The AWS SDK provides streaming-compatible converters to create `SdkBody`
instances, but these require the input body to implement the `Body`
trait from the `http-body` crate.
This PR enables streaming by implementing the required trait and
switching to the streaming-compatible converter.
**Changes (2 commits):**
* 1st Commit - **Implement http-body Body trait for AsyncBody:**
- Add `http-body = 1.0` dependency (already an indirect dependency)
- Implement the `Body` trait for our existing `AsyncBody` type
- Uses `poll_frame` to read data chunks asynchronously, preserving
streaming behavior
* 2nd Commit - **Use streaming-compatible AWS SDK converter:**
- Create `SdkBody` using `SdkBody::from_body_1_x()` with the new `Body`
trait implementation
**Details/FAQ:**
**Q: Why add another dependency?**
A: We tried to avoid adding a dependency, but the AWS SDK requires the
`Body` trait and `http-body` is where it's defined. The crate is already
an indirect dependency, making this a reasonable solution.
**Q: Why modify the shared `http_client` crate instead of just
`aws_bedrock_client`?**
A: We considered implementing the `Body` trait on a wrapper in
`aws_bedrock_client`, but since `AsyncBody` already uses `http` crate
types, extending support to the companion `http-body` crate seems
reasonable and may benefit other integrations.
**Q: How was this bottleneck discovered?**
A: After @5herlocked's initial streaming fix in #28281, I tested preview
194 and noticed streaming still had issues. I found a way to reproduce
the problem and chatted with @5herlocked about it. He immediately
pinpointed the exact location where the issue was occurring, his
diagnosis made this fix possible.
**Q: How does this relate to the previous fix?**
A: #28281 fixed buffering issues higher in the stack, but unfortunately
there was another bottleneck lower-down in the aws-http-client. This PR
addresses that separate buffering issue.
**Q: Does this use zero-copy or one-copy?**
A: The `Body` implementation includes one copy. Someone more
knowledgeable might be able to achieve a zero-copy approach, but we
opted for a conservative approach. The performance impact should not be
perceptible in typical usage.
**Testing:**
Confirmed that Bedrock streaming now works without buffering delays in a
local build.
Release Notes:
- Improved Bedrock streaming by eliminating response buffering delays
---------
Co-authored-by: Marshall Bowers <git@maxdeviant.com>
TODO
- [x] OpenAI Compatible API Icon
- [x] Docs
- [x] Link to docs in OpenAI provider section about configuring OpenAI
API compatible providers
Closes#33992
Related to #30010
Release Notes:
- agent: Add support for adding multiple OpenAI API compatible providers
---------
Co-authored-by: MrSubidubi <dev@bahn.sh>
Co-authored-by: Danilo Leal <daniloleal09@gmail.com>
Closes#32675
Exactly the same changes as in #33640 by @sviande
The PR has been in WIP state for 3 weeks with no activity, and the issue
basically makes Mistral models unusable. I have tested the changes
locally, and it does indeed work. Full credit goes to @sviande, I just
want this feature to be finished.
Release Notes:
- agent: Fixed an issue with tool calling with the Mistral provider
(thanks [@sviande](https://github.com/sviande) and
[@armyhaylenko](https://github.com/armyhaylenko))
Co-authored-by: sviande <sviande@gmail.com>
This includes making sure that both the agent panel and Zed's edit
prediction have a consistent narrative when it comes to onboarding users
into the AI features, considering the possible different plans and
conditions (such as being signed in/out, account age, etc.)
Release Notes:
- N/A
---------
Co-authored-by: Bennet Bo Fenner <53836821+bennetbo@users.noreply.github.com>
Co-authored-by: Bennet Bo Fenner <bennetbo@gmx.de>
Google Gemini Docs now recommend usage of `GEMINI_API_KEY` and the
legacy `GOOGLE_AI_API_KEY` variable is no longer supported in the modern
SDKs.
Zed will now accept either.
Release Notes:
- N/A
This PR makes it so all LLM traffic is routed through `cloud.zed.dev`.
We're already routing `llm.zed.dev` to `cloud.zed.dev` on the server,
but we want to standardize on `cloud.zed.dev` moving forward.
Release Notes:
- N/A
This PR makes it so we refresh the list of models whenever the LLM token
is refreshed.
This allows us to add or remove models based on the plan in the new
token.
Release Notes:
- Fixed model list not refreshing when subscribing to Zed Pro.
---------
Co-authored-by: Bennet Bo Fenner <bennetbo@gmx.de>
This introduces a new field `thinking_allowed` on `LanguageModelRequest`
which lets us control whether thinking should be enabled if the model
supports it.
We permit thinking in the Inline Assistant, Edit File tool and the Git
Commit message generator, this should make generation faster when using
a thinking model, e.g. `claude-sonnet-4-thinking`
Release Notes:
- N/A
This PR adds a new `zed-cloud` feature flag that can be used to send
traffic to `cloud.zed.dev` instead of `llm.zed.dev`.
This is just so Zed staff can test the new infrastructure. When we're
ready for prime-time we'll reroute traffic on the server.
Release Notes:
- N/A
Per [GitHub's documentation for VSCode's agent
mode](https://docs.github.com/en/copilot/how-tos/chat/asking-github-copilot-questions-in-your-ide#agent-mode),
a premium request is charged per user-submitted prompt. rather than per
individual request the agent makes to an LLM. This PR matches Zed's
functionality to VSCode's, accurately indicating to GitHub's API whether
a given request is initiated by the user or by an agent, allowing a user
to be metered only for prompts they send.
See also: #31068
Release Notes:
- Improve Copilot premium request tracking
As we are in the process of improving our Onboarding UX for Zed AI, I
added component previews for the Zed AI Configuration section. This
should make it easier to inspect the different states we can run into.
<img width="1198" alt="image"
src="https://github.com/user-attachments/assets/eb774f27-9091-450d-bfae-c688d533c25e"
/>
Release Notes:
- N/A
Closes#26030
Release Notes:
- Fixed Bedrock bug causing streaming responses to return as one big
chunk
---------
Co-authored-by: Peter Tripp <peter@zed.dev>
