Ran into this while adding support for Vercel v0s models:
- The timestamp seems to be returned in Milliseconds instead of seconds
so it breaks the bounds of `created: u32`. We did not use this field
anywhere so just decided to remove it
- Sometimes the `choices` field can be empty when the last chunk comes
in because it only contains `usage`
Release Notes:
- N/A
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>
Previously we were using a mix of `u32` and `usize`, e.g. `max_tokens:
usize, max_output_tokens: Option<u32>` in the same `struct`.
Although [tiktoken](https://github.com/openai/tiktoken) uses `usize`,
token counts should be consistent across targets (e.g. the same model
doesn't suddenly get a smaller context window if you're compiling for
wasm32), and these token counts could end up getting serialized using a
binary protocol, so `usize` is not the right choice for token counts.
I chose to standardize on `u64` over `u32` because we don't store many
of them (so the extra size should be insignificant) and future models
may exceed `u32::MAX` tokens.
Release Notes:
- N/A
Bubbles up rate limit information so that we can retry after a certain
duration if needed higher up in the stack.
Also caps the number of concurrent evals running at once to also help.
Release Notes:
- N/A
This PR adds a new `intent` field to completion requests to assist in
categorizing them correctly.
Release Notes:
- N/A
---------
Co-authored-by: Ben Brandt <benjamin.j.brandt@gmail.com>
This expands our deserialization of JSON from models to be more tolerant
of different variations that the model may send, including
capitalization, wrapping things in objects vs. being plain strings, etc.
Also when deserialization fails, it reports the entire error in the JSON
so we can see what failed to deserialize. (Previously these errors were
very unhelpful at diagnosing the problem.)
Finally, also removes the `WrappedText` variant since the custom
deserializer just turns that style of JSON into a normal `Text` variant.
Release Notes:
- N/A
Fixes regression caused by:
https://github.com/zed-industries/zed/pull/30639
Assistant messages can come back with no content, and we no longer
allowed that in the deserialization.
Release Notes:
- open_ai: fixed deserialization issue if assistant content was empty
https://github.com/zed-industries/zed/issues/30972 brought up another
case where our context is not enough to track the actual source of the
issue: we get a general top-level error without inner error.
The reason for this was `.ok_or_else(|| anyhow!("failed to read HEAD
SHA"))?; ` on the top level.
The PR finally reworks the way we use anyhow to reduce such issues (or
at least make it simpler to bubble them up later in a fix).
On top of that, uses a few more anyhow methods for better readability.
* `.ok_or_else(|| anyhow!("..."))`, `map_err` and other similar error
conversion/option reporting cases are replaced with `context` and
`with_context` calls
* in addition to that, various `anyhow!("failed to do ...")` are
stripped with `.context("Doing ...")` messages instead to remove the
parasitic `failed to` text
* `anyhow::ensure!` is used instead of `if ... { return Err(...); }`
calls
* `anyhow::bail!` is used instead of `return Err(anyhow!(...));`
Release Notes:
- N/A
Some providers sometimes send `{ "type": "text", "text": ... }` instead
of just the text as a string. Now we accept those instead of erroring.
Release Notes:
- N/A
I was able to get this fix in upstream, so now we can have simpler code
paths for our model selection.
I also added a test to catch if this would cause a bug again in the
future.
Release Notes:
- N/A
This is very basic support for them. There are a number of other TODOs
before this is really a first-class supported feature, so not adding any
release notes for it; for now, this PR just makes it so that if
read_file tries to read a PNG (which has come up in practice), it at
least correctly sends it to Anthropic instead of messing up.
This also lays the groundwork for future PRs for more first-class
support for images in tool calls across more image file formats and LLM
providers.
Release Notes:
- N/A
---------
Co-authored-by: Agus Zubiaga <hi@aguz.me>
Co-authored-by: Agus Zubiaga <agus@zed.dev>
tiktoken_rs is a bit behind (and even upstream tiktoken doesn't have all
of these models)
We were incorrectly using the cl100k tokenizer for some models that
actually use the o200k tokenizers. So that is updated.
I also made the match arms specific so that we do a better job of
catching whether or not tiktoken-rs accurately supports new models we
add in.
I will also do a PR upstream to see if we can move some of this logic
back out if tiktoken better supports the newer models.
Release Notes:
- Improved tokenizer support for openai models.
This sets us up to display queue position information to the user, once
our language model backend is updated to support request queuing.
The JSON returned by the LLM backend will need to look like this:
```json
{"queue": {"status": "queued", "position": 1}}
{"queue": {"status": "started"}}
{"event": {"THE_UPSTREAM_MODEL_PROVIDER_EVENT": "..."}}
```
Release Notes:
- N/A
---------
Co-authored-by: Marshall Bowers <git@maxdeviant.com>
This is to enable alternative streaming solutions at the application
layer. I'm not sure we really should have performed parsing of the input
at this layer. Either way I want to experiment with streaming approaches
in a separate crate on a branch, and this will help.
/cc @maxdeviant @bennetbo @rtfeldman
Closes #ISSUE
Release Notes:
- N/A
* Adds a fast / cheaper model to providers and defaults thread
summarization to this model. Initial motivation for this was that
https://github.com/zed-industries/zed/pull/29099 would cause these
requests to fail when used with a thinking model. It doesn't seem
correct to use a thinking model for summarization.
* Skips system prompt, context, and thinking segments.
* If tool use is happening, allows 2 tool uses + one more agent response
before summarizing.
Downside of this is that there was potential for some prefix cache reuse
before, especially for title summarization (thread summarization omitted
tool results and so would not share a prefix for those). This seems fine
as these requests should typically be fairly small. Even for full thread
summarization, skipping all tool use / context should greatly reduce the
token use.
Release Notes:
- N/A
Looks like the required backend component of this was deployed.
https://github.com/zed-industries/monorepo/actions/runs/14541199197
Release Notes:
- N/A
---------
Co-authored-by: Antonio Scandurra <me@as-cii.com>
Co-authored-by: Agus Zubiaga <hi@aguz.me>
Co-authored-by: Richard Feldman <oss@rtfeldman.com>
Co-authored-by: Nathan Sobo <nathan@zed.dev>
This PR disables `parallel_tool_calls` for the models that support it,
as the Agent currently expects at most one tool use per turn.
It was a bit of trial and error to figure this out. OpenAI's API
annoyingly will return an error if passing `parallel_tool_calls` to a
model that doesn't support it.
Release Notes:
- N/A
This PR removes the `use_any_tool` method from the `LanguageModel`
trait.
It was not being used anywhere, and doesn't really fit in our new tool
use story.
Release Notes:
- N/A
This is the core change:
https://github.com/zed-industries/zed/pull/26758/files#diff-044302c0d57147af17e68a0009fee3e8dcdfb4f32c27a915e70cfa80e987f765R1052
TODO:
- [x] Use AsyncFn instead of Fn() -> Future in GPUI spawn methods
- [x] Implement it in the whole app
- [x] Implement it in the debugger
- [x] Glance at the RPC crate, and see if those box future methods can
be switched over. Answer: It can't directly, as you can't make an
AsyncFn* into a trait object. There's ways around that, but they're all
more complex than just keeping the code as is.
- [ ] Fix platform specific code
Release Notes:
- N/A
I've been bothered by using simple hyphens for bullet lists here for a
while; it kinda looked cheap and not well-formatted. So, in this PR, I'm
adding a new, custom UI component in the `language_models` crate, called
`InstructionListItem`, based off the `ListItem` that's somewhat
mimic'ing what a `<li>` would be on the web.
It does have a "rigid" structure as in it's always a label followed by a
button (which is optional), but that seems okay given it has been the
overall shape of the copy we've been using here. Also, never really
loved that we were pasting URLs directly, that kinda felt cheap, too. I
could see an argument where it's just clearer, but it looks too
cluttered, as URLs aren't super pretty, necessarily.
| Before | After |
|--------|--------|
| <img
src="https://github.com/user-attachments/assets/ffd1ac27-b1f4-450d-abf5-079285fc9877"
width="700px" /> | <img
src="https://github.com/user-attachments/assets/28fb9d0d-205d-45d8-9e43-1aaa947adc96"
width="700px" /> |
Release Notes:
- N/A
This PR removes the dependencies on the individual model provider crates
from the `language_model` crate.
The various conversion methods for converting a `LanguageModelRequest`
into its provider-specific request type have been inlined into the
various provider modules in the `language_models` crate.
The model providers we provide via Zed's cloud offering get to stay, for
now.
Release Notes:
- N/A
While investigating #24896, I noticed two issues:
1. The default configuration for the `zed.dev` provider was using the
wrong string for Claude 3.5 Sonnet. This meant the provider would always
result as not configured until the user selected it from the model
picker, because we couldn't deserialize that string to a valid
`anthropic::Model` enum variant.
2. When clicking on `Open New Chat`/`Start New Thread` in the provider
configuration, we would select `Claude 3.5 Haiku` by default instead of
Claude 3.5 Sonnet.
Release Notes:
- Fixed some issues that caused AI providers to sometimes be
misconfigured.
This PR adds a new `CredentialsProvider` trait that abstracts over
interacting with the system keychain.
We had previously introduced a version of this scoped just to Zed auth
in https://github.com/zed-industries/zed/pull/11505.
However, after landing https://github.com/zed-industries/zed/pull/25123,
we now have a similar issue with the credentials for language model
providers that are also stored in the keychain (and thus also produce a
spam of popups when running a development build of Zed).
This PR takes the existing approach and makes it more generic, such that
we can use it everywhere that we need to read/store credentials in the
keychain.
There are still two credential provider implementations:
- `KeychainCredentialsProvider` will interact with the system keychain
(using the existing GPUI APIs)
- `DevelopmentCredentialsProvider` will use a local file on the file
system
We only use the `DevelopmentCredentialsProvider` when:
1. We are running a development build of Zed
2. The `ZED_DEVELOPMENT_AUTH` environment variable is set
- I am considering removing the need for this and making it the default,
but that will be explored in a follow-up PR.
Release Notes:
- N/A
This PR updates the `LanguageModelProvider::authenticate` method to
return an `AuthenticateError` instead of an `anyhow::Error`.
This allows us to model the "credentials not found" state explicitly as
`AuthenticateError::CredentialsNotFound`, which enables the caller to
check for this state and act accordingly.
Planning to use this in #25123 to silence errors about missing
credentials when authenticating providers in the background.
Release Notes:
- N/A
Done automatically with
> ast-grep -p '$A.background_executor().spawn($B)' -r
'$A.background_spawn($B)' --update-all --globs "\!crates/gpui"
Followed by:
* `cargo fmt`
* Unexpected need to remove some trailing whitespace.
* Manually adding imports of `gpui::{AppContext as _}` which provides
`background_spawn`
* Added `AppContext as _` to existing use of `AppContext`
Release Notes:
- N/A
Sorry to dump an unsolicited PR for a hot feature! I'm sure someone else
was taking a look at this.
I noticed that token counting was disabled and I was getting error logs
of the form `[2025-01-31T22:59:01-05:00 ERROR assistant_context_editor]
No tokenizer found for model o3-mini` when using the new model. To fix
the issue, this PR registers the `gpt-4` tokenizer for this model.
Release Notes:
- openai: Fixed Assistant token counts for `o3-mini` models
This PR does some somewhat light UI adjustment to the Assistant 2
settings view. The Prompt Library section should feature the default
prompts in the future, so that's why it's been separated that way.
<img width="800" alt="Screenshot 2025-01-29 at 2 59 59 PM"
src="https://github.com/user-attachments/assets/7b033bde-51ab-44d5-9e53-3f72b8ff5f51"
/>
Release Notes:
- N/A
Fix a bug where a GPUI macro still used `ModelContext`
Rename `AsyncAppContext` -> `AsyncApp`
Rename update_model, read_model, insert_model, and reserve_model to
update_entity, read_entity, insert_entity, and reserve_entity
Release Notes:
- N/A
There's still a bit more work to do on this, but this PR is compiling
(with warnings) after eliminating the key types. When the tasks below
are complete, this will be the new narrative for GPUI:
- `Entity<T>` - This replaces `View<T>`/`Model<T>`. It represents a unit
of state, and if `T` implements `Render`, then `Entity<T>` implements
`Element`.
- `&mut App` This replaces `AppContext` and represents the app.
- `&mut Context<T>` This replaces `ModelContext` and derefs to `App`. It
is provided by the framework when updating an entity.
- `&mut Window` Broken out of `&mut WindowContext` which no longer
exists. Every method that once took `&mut WindowContext` now takes `&mut
Window, &mut App` and every method that took `&mut ViewContext<T>` now
takes `&mut Window, &mut Context<T>`
Not pictured here are the two other failed attempts. It's been quite a
month!
Tasks:
- [x] Remove `View`, `ViewContext`, `WindowContext` and thread through
`Window`
- [x] [@cole-miller @mikayla-maki] Redraw window when entities change
- [x] [@cole-miller @mikayla-maki] Get examples and Zed running
- [x] [@cole-miller @mikayla-maki] Fix Zed rendering
- [x] [@mikayla-maki] Fix todo! macros and comments
- [x] Fix a bug where the editor would not be redrawn because of view
caching
- [x] remove publicness window.notify() and replace with
`AppContext::notify`
- [x] remove `observe_new_window_models`, replace with
`observe_new_models` with an optional window
- [x] Fix a bug where the project panel would not be redrawn because of
the wrong refresh() call being used
- [x] Fix the tests
- [x] Fix warnings by eliminating `Window` params or using `_`
- [x] Fix conflicts
- [x] Simplify generic code where possible
- [x] Rename types
- [ ] Update docs
### issues post merge
- [x] Issues switching between normal and insert mode
- [x] Assistant re-rendering failure
- [x] Vim test failures
- [x] Mac build issue
Release Notes:
- N/A
---------
Co-authored-by: Antonio Scandurra <me@as-cii.com>
Co-authored-by: Cole Miller <cole@zed.dev>
Co-authored-by: Mikayla <mikayla@zed.dev>
Co-authored-by: Joseph <joseph@zed.dev>
Co-authored-by: max <max@zed.dev>
Co-authored-by: Michael Sloan <michael@zed.dev>
Co-authored-by: Mikayla Maki <mikaylamaki@Mikaylas-MacBook-Pro.local>
Co-authored-by: Mikayla <mikayla.c.maki@gmail.com>
Co-authored-by: joão <joao@zed.dev>
This PR adds a new `language_models` crate to house the various language
model providers.
By extracting the provider definitions out of `language_model`, we're
able to remove `language_model`'s dependency on `editor`, which improves
incremental compilation when changing `editor`.
Release Notes:
- N/A
2024-11-20 18:49:34 -05:00
Renamed from crates/language_model/src/provider/open_ai.rs (Browse further)
