Adds native support for AWS Bedrock's Mantle endpoint
(`bedrock-mantle`), which serves models with no `Converse`/`Invoke`
support on `bedrock-runtime`, such as GPT-5.5, GPT-5.4, and Grok 4.3 but
more importantly **open-weight** models
Closes#60471
## What's changed
- Renamed the existing `Model` enum in the `bedrock` crate to
`ConverseModel`, and added a new `MantleModel` enum for Mantle-only
models. Mantle models reuse the existing OpenAI-compatible Chat
Completions/Responses request and response plumbing
(`into_open_ai`/`into_open_ai_response`,
`OpenAiEventMapper`/`OpenAiResponseEventMapper`) already used by the
native OpenAI and OpenAI-compatible providers, rather than introducing
new marshalling code.
- Added a `BedrockMantleModel` language model that routes requests to
the `bedrock-mantle` endpoint, dispatching to Chat Completions or the
Responses API depending on the model. Mantle models appear in the model
picker alongside Converse models under the same Bedrock provider.
- Added region gating: `bedrock-mantle` is only available in a subset of
AWS Regions, so using a Mantle model outside of them surfaces a clear
error naming the current Region and the supported ones, instead of an
opaque HTTP failure.
- Implemented Bedrock bearer token authentication for Mantle requests: a
configured Bedrock API key is used as-is, and every other auth method
(IAM credentials, named profile, SSO, automatic) derives a short-term
token by locally SigV4-presigning a `CallWithBearerToken` request. This
requires no extra network round trip and no token caching, since
re-signing locally is cheap.
- Added a specific error for the 403 you get when your credentials have
`bedrock:CallWithBearerToken` but not the separate
`bedrock-mantle:CallWithBearerToken` permission Mantle models require,
since this is the most common misconfiguration.
- Added a `mantle_available_models` setting so custom models served
through `bedrock-mantle` can be configured, the same way other providers
support custom models via `available_models`.
- Documented Mantle models and the new setting in the Amazon Bedrock
section of [Use a
Gateway](https://zed.dev/docs/ai/use-a-gateway#amazon-bedrock).
## Testing
- Added unit tests covering: the local SigV4 bearer-token signing
(including a byte-for-byte cross-check against a reference
implementation), Mantle endpoint URL construction, the
Mantle-supported-regions list, thinking-effort normalization, and the
settings-to-model protocol mapping.
- `cargo test -p bedrock -p language_models -p settings_content -p
settings` passes.
- `./script/clippy` passes with no new warnings.
Release Notes:
- Added native support for AWS Bedrock's Mantle endpoint, enabling
GPT-5.5, GPT-5.4, and Grok 4.3 through the Amazon Bedrock provider.
Hi there, I'm Celina from Hugging Face! Opening this PR to add
[llama.cpp](https://llama.app) as a model provider
# Objective
Today Zed users running llama.cpp have to fall back to the generic
OpenAI-compatible provider, which means no auto-discovery (the router
mode (`llama serve`) discovers models from the cache and loads them on
demand) and manual configuration of every model and its capabilities.
This PR makes `llama.cpp` a first-class provider with the same
auto-discovery experience.
## Solution
- Add a `llama_cpp` client crate with the OpenAI-compatible chat types
(`/v1/chat/completions`, including `reasoning_content`) and the
discovery types (`/v1/models`, `/props`), mirroring the existing
`ollama` crate.
- Add the provider in
`crates/language_models/src/provider/llama_cpp.rs`, modeled on the
Ollama provider (settings, configuration view, event mapping).
- Auto discover served models and their context length and tool/vision
support from `/props`. Set `auto_discover: false` to list models
manually instead.
- An unloaded model can't be inspected without loading it, so it is
listed with optimistic defaults (large context, tools enabled) and is
usable from the first message; its real context length and tool support
are filled in once it loads. These live behind a shared map, so a model
already selected in an open conversation picks them up without being
re-selected.
- Show load progress. The provider subscribes to `/models/sse` and
surfaces each model's load progress (e.g. "Loading weights 42%") in its
display name, reconciling stale labels against `/v1/models`. Builds
without `/models/sse` degrade gracefully - no progress, and no
capability refresh after the initial discovery.
- Add settings (`api_url`, `auto_discover`, `available_models` with
per-model `max_tokens` / `supports_tools` / `supports_images`,
`context_window`, `custom_headers`), the provider icon, a `default.json`
entry, and documentation under "Use a Local Model".
No new dependencies: the crate reuses existing workspace dependencies,
and shared state uses `std::sync::RwLock`.
## Testing
- Unit tests in both new crates cover wire/response parsing, model
discovery for single-model and router shapes, the cold-start optimistic
defaults, the in-place capability refresh once a model loads, and the
`/models/sse` event handling (state changes, load failure, load
progress).
- Built Zed locally and ran it against a local `llama serve` router:
confirmed models are discovered without manual configuration, that the
first message works before a model has finished loading, that load
progress is shown in the model's display name while it loads, and that
the reported context length and tool support refine to the model's real
values once it finishes loading.
- Platforms: tested on macOS (Apple Silicon).
## 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 adheres to Zed's UI standards
([UX/UI](https://github.com/zed-industries/zed/blob/main/CONTRIBUTING.md#uiux-checklist)
and
[icon](https://github.com/zed-industries/zed/blob/main/crates/icons/README.md)
guidelines)
- [x] Tests cover the new/changed behavior
- [x] Performance impact has been considered and is acceptable
## Showcase
The generation speed (tokens/sec) depends on the machine you're running
the model, here it's a Apple M3 Max 64GB running a 4-bit quant of
https://huggingface.co/Qwen/Qwen3.5-35B-A3B. For the load progress
status, make sure to upgrade your llama.cpp version to the latest build.
https://github.com/user-attachments/assets/0254f6ef-abe9-42ed-810b-ef1a5b8fa3bd
---
Release Notes:
- Added llama.cpp as a language model provider
---------
Co-authored-by: Ben Brandt <benjamin.j.brandt@gmail.com>
Adds a new language model provider that lets users authenticate with
their ChatGPT Plus/Pro subscription and use OpenAI models
(codex-mini-latest, o4-mini, o3) directly in the Zed agent — without
needing a separate API key.
## How it works
1. **OAuth 2.0 + PKCE sign-in**: Uses OpenAI's official Codex CLI client
ID to run an authorization code flow. A local HTTP server on
`127.0.0.1:1455` captures the callback, exchanges the code for tokens,
and stores them in the system keychain.
2. **Token refresh**: Access tokens are automatically refreshed when
they're within 5 minutes of expiry, using the stored refresh token.
3. **Responses API**: Requests go to
`https://chatgpt.com/backend-api/codex/responses` using the existing
`open_ai::responses` client (Responses API format, not Chat Completions
which was deprecated for this endpoint in Feb 2026).
4. **Required headers**: `originator: zed`, `OpenAI-Beta:
responses=experimental`, `ChatGPT-Account-Id` (extracted from JWT),
`store: false` in the body.
## Files changed
- `crates/open_ai/src/responses.rs`: Add `store: Option<bool>` field to
`Request`; add `extra_headers` param to `stream_response` for
per-provider header injection
- `crates/language_models/src/provider/openai_subscribed.rs`: New
provider (sign-in UI, OAuth flow, token storage/refresh, model list)
- `crates/language_models/src/provider/open_ai.rs`,
`open_ai_compatible.rs`, `opencode.rs`: Pass `vec![]` for new
`extra_headers` param
- `crates/language_models/src/language_models.rs`: Register the new
provider
- `crates/language_models/Cargo.toml`: Add `rand` and `sha2` deps for
PKCE
## Open questions / known gaps
- [ ] **Terms of service**: Usage appears to be within OpenAI's ToS
(interactive use via their official CLI client ID), but needs legal
sign-off before shipping
- [ ] **Redirect URI**: Currently `http://localhost:1455/auth/callback`
— may need to match exactly what OpenAI's Codex CLI uses
- [ ] **UI polish**: The sign-in card is functional but minimal; needs
design review
- [ ] **Error messages**: OAuth error responses from the callback URL
aren't surfaced to the user yet
- [ ] **`o3` availability**: o3 may require a higher subscription tier;
consider gating it
## Testing
Sign-in flow was designed to match the Copilot Chat provider pattern.
Manual testing against the live OAuth endpoint is needed.
Release Notes:
- Added ChatGPT subscription provider, allowing users to use their
ChatGPT Plus/Pro subscription with the Zed agent
---------
Co-authored-by: Zed Zippy <234243425+zed-zippy[bot]@users.noreply.github.com>
Co-authored-by: Richard Feldman <richard@zed.dev>
Co-authored-by: Richard Feldman <oss@rtfeldman.com>
Co-authored-by: Agus Zubiaga <agus@zed.dev>
Follow up to #54826, after which the fallback model would be selected
instead of the cloud model when starting Zed
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
Removes the Vercel v0 Provider, as the v0 API has been
depredated/removed (https://api.v0.dev/v1)
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)
- [ ] Tests cover the new/changed behavior
- [x] Performance impact has been considered and is acceptable
Release Notes:
- agent: Removed Vercel v0 provider as it has been deprecated by Vercel
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>
Before you mark this PR as ready for review, make sure that you have:
- [x] Added a solid test coverage and/or screenshots from doing manual
testing
- [x] Done a self-review taking into account security and performance
aspects
- [x] Aligned any UI changes with the [UI
checklist](https://github.com/zed-industries/zed/blob/main/CONTRIBUTING.md#uiux-checklist)
Per Opencode's website:
> Zen gives you access to a curated set of AI models that OpenCode has
tested and benchmarked specifically for coding agents. No need to worry
about inconsistent performance and quality, use validated models that
work.
> - [x] Testing select models and consulting their teams
> - [x] Working with providers to ensure they're delivered properly
> - [x] Benchmarking all model-provider combinations we recommend
There are so many models available, but only a few work well with coding
agents. Most providers configure them differently with varying results.
The models under the Zen umbrella typically have a more reliable
token(s) per second speed with minimal outages. The opencode ecosystem
has improved my workflow if not many others' !
Release Notes:
- Added [Opencode Zen](https://opencode.ai/zen) to list of providers
---------
Co-authored-by: Ben Brandt <benjamin.j.brandt@gmail.com>
Co-authored-by: Bennet Bo Fenner <bennetbo@gmx.de>
## Context
This PR fixes one of the issues in #51905, where model outputs are full
of errant `\` characters.
heres the problem: As the response is streamed back to zed, we
accumulate the message chunks and and need to convert those chunks to
valid json, to do that we use `partial_json_fixer::fix_json`, when the
last character of a chunk is `\`, the `fix_json` has to escape that
backslash, because its inside of a string (if it isn't, its invalid json
and the tool call will crash) and other wise you would end up escaping
the end `"` and everything would be messed up.
why is this a problem for zed:
T_0 is the output at some step.
T_1 is the output at the next step.
the `fix_json` system is meant to be used by replacing T_0 with T_1,
however in the editor, replacing the entirety of T_0 with T_1 would be
slow/cause flickering/etc.. so we calculate the difference between T_0
and T_1 and just add it to the current buffer state. So when a chunk
ends on `\`, we end up with something like `... end of line\\"}` at the
end of T_0,
in T_1, this becomes `... end of line\n ...`. then when we add the new
chunk from T_1, it just picks up after the \n because its tracking the
length to manage the deltas.
## How to Review
utils.rs:
fix_streamed_json => remove trailing backslashes from incoming json
streams so that `partial_json_fixer::fix_json` doesn't try to escape
them.
other files: call fix_streamed_json before passing to `serde_json`
I had claude write a bunch of tests while I was working on the fix,
which I have kept in for now, but the end functionality of
fix_streamed_json is really simple now, so maybe these arent really
needed.
## Videos
Behavior Before:
https://github.com/user-attachments/assets/f23f5579-b2e1-4d71-9e24-f15ea831de52
Behavior After:
https://github.com/user-attachments/assets/40acdc23-4522-4621-be28-895965f4f262
## Self-Review Checklist
<!-- Check before requesting review: -->
- [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:
- language_models: fixed partial json streaming
This will help with test times (in some cases), as nextest cannot figure
out whether a given rdep is actually an alive edge of the build graph
Closes #ISSUE
Before you mark this PR as ready for review, make sure that you have:
- [ ] Added a solid test coverage and/or screenshots from doing manual
testing
- [ ] Done a self-review taking into account security and performance
aspects
- [ ] Aligned any UI changes with the [UI
checklist](https://github.com/zed-industries/zed/blob/main/CONTRIBUTING.md#uiux-checklist)
Release Notes:
- N/A
This PR removes the `cloud-thinking-effort` feature flag to ship the
thinking effort UI for the Zed provider.
Release Notes:
- Added support for controlling thinking effort levels with supported
models using the Zed provider.
Closes #N/A (no existing issue - implemented to enable image input for
Bedrock models)
This PR enables the "@" image mention feature for Bedrock models that
support vision capabilities.
**Changes:**
- Added `supports_images()` method to Bedrock `Model` enum
- Wired up image support in the Bedrock language model provider
- Added `MessageContent::Image` handling to convert base64 images to
Bedrock's expected format
- Added tool result image support
**Supported models:** Claude 3/3.5/4 family, Amazon Nova Pro/Lite, Meta
Llama 3.2 Vision, Mistral Pixtral
Release Notes:
- Added image input support for Amazon Bedrock models with vision
capabilities
Release Notes:
- Added Claude Opus 4.6 and 4.6 Thinking with Cross region inference for
US, EU, and Global endpoints.
---------
Co-authored-by: Ona <no-reply@ona.com>
This PR adds a thinking toggle for controlling whether to use thinking
for a model in the Zed provider:
<img width="645" height="142" alt="Screenshot 2026-01-22 at 12 34 01 PM"
src="https://github.com/user-attachments/assets/9aa543fe-e708-4840-8b38-1a6fbcb78388"
/>
Previously we would create separate "Thinking" variants of the models
that supported thinking in the model selector.
This only applies to Anthropic models in the Zed provider, currently.
This is gated behind the `cloud-thinking-toggle` feature flag.
Release Notes:
- N/A
---------
Co-authored-by: Neel <neel@zed.dev>
This PR removes the `open-ai-responses-api` feature flag and makes it so
all OpenAI requests to the Zed provider use the Responses API.
We've been running this in Nightly/Preview for a week now without any
issues.
Closes CLO-104.
Release Notes:
- N/A
- **copilot: Fix double lease panic when signing out**
- **Extract copilot_chat into a separate crate**
- **Do not use re-exports from copilot**
- **Use new SignIn API**
- **Extract copilot_ui out of copilot**
Closes#7501
Release Notes:
- Fixed Copilot providing suggestions from different Zed windows.
- Copilot edit predictions now support jumping to unresolved
diagnostics.
This PR adds support for using the OpenAI Responses API through the Zed
provider.
This is gated behind the `open-ai-responses-api` feature flag.
Part of CLO-34.
Release Notes:
- N/A
Add support for OpenAI's /responses endpoint for models that don't
support /chat/completions API. This enables compatibility with newer
model variants (`gpt-5-codex`, `gpt-5-pro`, `o3-pro`, etc) while
maintaining compatibility with existing configs
Changes:
- Add `supports_chat_completions` flag to model capabilities that
defaults to true for existing behavior
- Implement responses API client with streaming support as per [OpenAI
documentation](https://app.stainless.com/api/spec/documented/openai/openapi.documented.yml).
- Add `ResponseEventMapper` to convert responses events to completion
events for maintainer simplicity
- Update UI to allow toggling `chat_completions` capability
- Add `gpt-5-codex` model
Closes#38858
Release Notes:
- Added support for `gpt-5-codex` model
---------
Co-authored-by: Bennet Bo Fenner <bennet@zed.dev>
- Edit prediction providers can now be configured through the settings
UI
- Cleaned up the status bar menu to only show _configured_ providers
- Added to the status bar icon button tooltip the name of the active
provider
- Only display the data collection functionality under "Privacy" for the
Zed models
- Moved the Codestral edit prediction provider out of the Mistral
section in the agent panel into the settings UI
- Refined and improved UI and states for configuring GitHub Copilot as
both an agent and edit prediction provider
#### Todos before merge:
- [x] UI: Unify with settings UI style and tidy it all up
- [x] Unify Copilot modal `impl`s to use separate window
- [x] Remove stop light icons from GitHub modal
- [x] Make dismiss events work on GitHub modal
- [ ] Investigate workarounds to tell if Copilot authenticated even when
LSP not running
Release Notes:
- settings_ui: Added a section for configuring edit prediction providers
under AI > Edit Predictions, including Codestral and GitHub Copilot.
Once you've updated you can use the following link to open it:
zed://settings/edit_predictions.providers
---------
Co-authored-by: Ben Kunkle <ben@zed.dev>
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
Three motivations for this:
* Changing provider URL could cause credentials for the prior URL to be
sent to the new URL.
* The UI is in a misleading state after URL change - it shows a
configured API key, but on restart it will show no API key.
* #34110 will add support for both URL and key configuration for Ollama.
This is the first provider to have UI for setting the URL, and this
makes these issues show up more directly as odd UI interactions.
#37610 implemented something similar for the OpenAI and OpenAI
compatible providers. This extracts out some shared code, uses it in all
relevant providers, and adds more safety around key use.
I haven't tested all providers, but the per-provider changes were pretty
mechanical, so hopefully work properly.
Release Notes:
- Fixed handling of changes to LLM provider URL in settings to also load
the associated API key.
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 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>
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>
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>
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 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
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
This cleans up our settings to not include any `version` fields, as we
have an actual settings migrator now.
This PR removes `language_models > anthropic > version`,
`language_models > openai > version` and `agent > version`.
We had migration paths in the code for a long time, so in practice
almost everyone should be using the latest version of these settings.
Release Notes:
- Remove `version` fields in settings for `agent`, `language_models >
anthropic`, `language_models > openai`. Your settings will automatically
be migrated. If you're running into issues with this open an issue
[here](https://github.com/zed-industries/zed/issues)
Vercel v0 is an OpenAI-compatible model, so this is mostly a dupe of the
OpenAI provider files with some adaptations for v0, including going
ahead and using the custom endpoint for the API URL field.
Release Notes:
- Added support for Vercel as a language model provider.
The `api_url` setting is one that most providers already support and can
be changed via the `settings.json`. We're adding the ability to change
it via the UI for OpenAI specifically so it can be more easily connected
to v0.
Release Notes:
- agent: Added ability to change the API base URL for OpenAI via the UI
---------
Co-authored-by: Bennet Bo Fenner <53836821+bennetbo@users.noreply.github.com>
This addresses:
https://github.com/zed-industries/zed/pull/32248#issuecomment-2952060834.
This PR address two main things one allowing enterprise users to use
copilot chat and completion while also introducing the new way to handle
copilot url specific their subscription. Simplifying the UX around the
github copilot and removes the burden of users figuring out what url to
use for their subscription.
- [x] Pass enterprise_uri to copilot lsp so that it can redirect users
to their enterprise server. Ref:
https://github.com/github/copilot-language-server-release#configuration-management
- [x] Remove the old ui and config language_models.copilot which allowed
users to specify their copilot_chat specific endpoint. We now derive
that automatically using token endpoint for copilot so that we can send
the requests to specific copilot endpoint for depending upon the url
returned by copilot server.
- [x] Tested this for checking the both enterprise and non-enterprise
flow work. Thanks to @theherk for the help to debug and test it.
- [ ] Udpdate the zed.dev/docs to refelect how to setup enterprise
copilot.
What this doesn't do at the moment:
* Currently zed doesn't allow to have two seperate accounts as the token
used in chat is same as the one generated by lsp. After this changes
also this behaviour remains same and users can't have both enterprise
and personal copilot installed.
P.S: Might need to do some bit of code cleanup and other things but
overall I felt this PR was ready for atleast first pass of review to
gather feedback around the implementation and code itself.
Release Notes:
- Add enterprise support for GitHub copilot
---------
Signed-off-by: Umesh Yadav <git@umesh.dev>
This pull request adds full integration with OpenRouter, allowing users
to access a wide variety of language models through a single API key.
**Implementation Details:**
* **Provider Registration:** Registers OpenRouter as a new language
model provider within the application's model registry. This includes UI
for API key authentication, token counting, streaming completions, and
tool-call handling.
* **Dedicated Crate:** Adds a new `open_router` crate to manage
interactions with the OpenRouter HTTP API, including model discovery and
streaming helpers.
* **UI & Configuration:** Extends workspace manifests, the settings
schema, icons, and default configurations to surface the OpenRouter
provider and its settings within the UI.
* **Readability:** Reformats JSON arrays within the settings files for
improved readability.
**Design Decisions & Discussion Points:**
* **Code Reuse:** I leveraged much of the existing logic from the
`openai` provider integration due to the significant similarities
between the OpenAI and OpenRouter API specifications.
* **Default Model:** I set the default model to `openrouter/auto`. This
model automatically routes user prompts to the most suitable underlying
model on OpenRouter, providing a convenient starting point.
* **Model Population Strategy:**
* <strike>I've implemented dynamic population of available models by
querying the OpenRouter API upon initialization.
* Currently, this involves three separate API calls: one for all models,
one for tool-use models, and one for models good at programming.
* The data from the tool-use API call sets a `tool_use` flag for
relevant models.
* The data from the programming models API call is used to sort the
list, prioritizing coding-focused models in the dropdown.</strike>
* <strike>**Feedback Welcome:** I acknowledge this multi-call approach
is API-intensive. I am open to feedback and alternative implementation
suggestions if the team believes this can be optimized.</strike>
* **Update: Now this has been simplified to one api call.**
* **UI/UX Considerations:**
* <strike>Authentication Method: Currently, I've implemented the
standard API key input in settings, similar to other providers like
OpenAI/Anthropic. However, OpenRouter also supports OAuth 2.0 with PKCE.
This could offer a potentially smoother, more integrated setup
experience for users (e.g., clicking a button to authorize instead of
copy-pasting a key). Should we prioritize implementing OAuth PKCE now,
or perhaps add it as an alternative option later?</strike>(PKCE is not
straight forward and complicated so skipping this for now. So that we
can add the support and work on this later.)
* <strike>To visually distinguish models better suited for programming,
I've considered adding a marker (e.g., `</>` or `🧠`) next to their
names. Thoughts on this proposal?</strike>. (This will require a changes
and discussion across model provider. This doesn't fall under the scope
of current PR).
* OpenRouter offers 300+ models. The current implementation loads all of
them. **Feedback Needed:** Should we refine this list or implement more
sophisticated filtering/categorization for better usability?
**Motivation:**
This integration directly addresses one of the most highly upvoted
feature requests/discussions within the Zed community. Adding OpenRouter
support significantly expands the range of AI models accessible to
users.
I welcome feedback from the Zed team on this implementation and the
design choices made. I am eager to refine this feature and make it
available to users.
ISSUES: https://github.com/zed-industries/zed/discussions/16576
Release Notes:
- Added support for OpenRouter as a language model provider.
---------
Signed-off-by: Umesh Yadav <umesh4257@gmail.com>
Co-authored-by: Marshall Bowers <git@maxdeviant.com>
This PR updates the Zed LLM provider to fetch the available models from
the server instead of hard-coding them in the binary.
Release Notes:
- Updated the Zed provider to fetch the list of available language
models from the server.
I noticed the discussion in #28881, and had thought of exactly the same
a few days prior.
This implementation should preserve existing functionality fairly well.
I've added a dependency (serde_with) to allow the deserializer to skip
models which cannot be deserialized, which could occur if a future
provider, for instance, is added. Without this modification, such a
change could break all models. If extra dependencies aren't desired, a
manual implementation could be used instead.
- Closes#29369
Release Notes:
- Dynamically detect available Copilot Chat models, including all models
with tool support
---------
Co-authored-by: AidanV <aidanvanduyne@gmail.com>
Co-authored-by: imumesh18 <umesh4257@gmail.com>
Co-authored-by: Bennet Bo Fenner <bennet@zed.dev>
Co-authored-by: Agus Zubiaga <hi@aguz.me>
This PR makes it so we send up an `x-zed-version` header with the
client's version when making a request to llm.zed.dev for edit
predictions and completions.
Release Notes:
- N/A
Anant Goel