mirror of
https://github.com/zed-industries/zed.git
synced 2026-06-01 03:14:56 +07:00
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
523 lines
17 KiB
Rust
523 lines
17 KiB
Rust
use anyhow::{Result, anyhow};
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use collections::BTreeMap;
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use futures::{FutureExt, StreamExt, future, future::BoxFuture};
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use gpui::{AnyView, App, AsyncApp, Context, Entity, Task, Window};
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use http_client::HttpClient;
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use language_model::{
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AuthenticateError, LanguageModel, LanguageModelCompletionError, LanguageModelCompletionEvent,
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LanguageModelId, LanguageModelName, LanguageModelProvider, LanguageModelProviderId,
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LanguageModelProviderName, LanguageModelProviderState, LanguageModelRequest,
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LanguageModelToolChoice, LanguageModelToolSchemaFormat, RateLimiter, Role,
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};
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use open_ai::ResponseStreamEvent;
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pub use settings::XaiAvailableModel as AvailableModel;
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use settings::{Settings, SettingsStore};
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use std::sync::{Arc, LazyLock};
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use strum::IntoEnumIterator;
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use ui::{ElevationIndex, List, Tooltip, prelude::*};
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use ui_input::SingleLineInput;
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use util::{ResultExt, truncate_and_trailoff};
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use x_ai::{Model, XAI_API_URL};
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use zed_env_vars::{EnvVar, env_var};
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use crate::{api_key::ApiKeyState, ui::InstructionListItem};
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const PROVIDER_ID: LanguageModelProviderId = LanguageModelProviderId::new("x_ai");
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const PROVIDER_NAME: LanguageModelProviderName = LanguageModelProviderName::new("xAI");
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const API_KEY_ENV_VAR_NAME: &str = "XAI_API_KEY";
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static API_KEY_ENV_VAR: LazyLock<EnvVar> = env_var!(API_KEY_ENV_VAR_NAME);
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#[derive(Default, Clone, Debug, PartialEq)]
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pub struct XAiSettings {
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pub api_url: String,
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pub available_models: Vec<AvailableModel>,
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}
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pub struct XAiLanguageModelProvider {
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http_client: Arc<dyn HttpClient>,
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state: Entity<State>,
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}
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pub struct State {
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api_key_state: ApiKeyState,
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}
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impl State {
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fn is_authenticated(&self) -> bool {
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self.api_key_state.has_key()
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}
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fn set_api_key(&mut self, api_key: Option<String>, cx: &mut Context<Self>) -> Task<Result<()>> {
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let api_url = XAiLanguageModelProvider::api_url(cx);
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self.api_key_state
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.store(api_url, api_key, |this| &mut this.api_key_state, cx)
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}
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fn authenticate(&mut self, cx: &mut Context<Self>) -> Task<Result<(), AuthenticateError>> {
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let api_url = XAiLanguageModelProvider::api_url(cx);
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self.api_key_state.load_if_needed(
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api_url,
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&API_KEY_ENV_VAR,
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|this| &mut this.api_key_state,
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cx,
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)
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}
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}
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impl XAiLanguageModelProvider {
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pub fn new(http_client: Arc<dyn HttpClient>, cx: &mut App) -> Self {
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let state = cx.new(|cx| {
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cx.observe_global::<SettingsStore>(|this: &mut State, cx| {
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let api_url = Self::api_url(cx);
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this.api_key_state.handle_url_change(
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api_url,
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&API_KEY_ENV_VAR,
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|this| &mut this.api_key_state,
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cx,
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);
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cx.notify();
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})
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.detach();
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State {
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api_key_state: ApiKeyState::new(Self::api_url(cx)),
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}
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});
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Self { http_client, state }
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}
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fn create_language_model(&self, model: x_ai::Model) -> Arc<dyn LanguageModel> {
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Arc::new(XAiLanguageModel {
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id: LanguageModelId::from(model.id().to_string()),
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model,
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state: self.state.clone(),
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http_client: self.http_client.clone(),
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request_limiter: RateLimiter::new(4),
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})
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}
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fn settings(cx: &App) -> &XAiSettings {
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&crate::AllLanguageModelSettings::get_global(cx).x_ai
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}
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fn api_url(cx: &App) -> SharedString {
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let api_url = &Self::settings(cx).api_url;
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if api_url.is_empty() {
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XAI_API_URL.into()
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} else {
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SharedString::new(api_url.as_str())
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}
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}
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}
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impl LanguageModelProviderState for XAiLanguageModelProvider {
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type ObservableEntity = State;
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fn observable_entity(&self) -> Option<Entity<Self::ObservableEntity>> {
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Some(self.state.clone())
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}
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}
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impl LanguageModelProvider for XAiLanguageModelProvider {
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fn id(&self) -> LanguageModelProviderId {
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PROVIDER_ID
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}
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fn name(&self) -> LanguageModelProviderName {
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PROVIDER_NAME
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}
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fn icon(&self) -> IconName {
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IconName::AiXAi
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}
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fn default_model(&self, _cx: &App) -> Option<Arc<dyn LanguageModel>> {
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Some(self.create_language_model(x_ai::Model::default()))
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}
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fn default_fast_model(&self, _cx: &App) -> Option<Arc<dyn LanguageModel>> {
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Some(self.create_language_model(x_ai::Model::default_fast()))
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}
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fn provided_models(&self, cx: &App) -> Vec<Arc<dyn LanguageModel>> {
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let mut models = BTreeMap::default();
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for model in x_ai::Model::iter() {
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if !matches!(model, x_ai::Model::Custom { .. }) {
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models.insert(model.id().to_string(), model);
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}
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}
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for model in &Self::settings(cx).available_models {
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models.insert(
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model.name.clone(),
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x_ai::Model::Custom {
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name: model.name.clone(),
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display_name: model.display_name.clone(),
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max_tokens: model.max_tokens,
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max_output_tokens: model.max_output_tokens,
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max_completion_tokens: model.max_completion_tokens,
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supports_images: model.supports_images,
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supports_tools: model.supports_tools,
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parallel_tool_calls: model.parallel_tool_calls,
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},
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);
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}
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models
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.into_values()
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.map(|model| self.create_language_model(model))
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.collect()
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}
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fn is_authenticated(&self, cx: &App) -> bool {
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self.state.read(cx).is_authenticated()
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}
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fn authenticate(&self, cx: &mut App) -> Task<Result<(), AuthenticateError>> {
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self.state.update(cx, |state, cx| state.authenticate(cx))
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}
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fn configuration_view(
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&self,
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_target_agent: language_model::ConfigurationViewTargetAgent,
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window: &mut Window,
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cx: &mut App,
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) -> AnyView {
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cx.new(|cx| ConfigurationView::new(self.state.clone(), window, cx))
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.into()
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}
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fn reset_credentials(&self, cx: &mut App) -> Task<Result<()>> {
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self.state
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.update(cx, |state, cx| state.set_api_key(None, cx))
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}
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}
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pub struct XAiLanguageModel {
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id: LanguageModelId,
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model: x_ai::Model,
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state: Entity<State>,
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http_client: Arc<dyn HttpClient>,
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request_limiter: RateLimiter,
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}
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impl XAiLanguageModel {
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fn stream_completion(
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&self,
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request: open_ai::Request,
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cx: &AsyncApp,
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) -> BoxFuture<'static, Result<futures::stream::BoxStream<'static, Result<ResponseStreamEvent>>>>
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{
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let http_client = self.http_client.clone();
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let Ok((api_key, api_url)) = self.state.read_with(cx, |state, cx| {
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let api_url = XAiLanguageModelProvider::api_url(cx);
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(state.api_key_state.key(&api_url), api_url)
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}) else {
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return future::ready(Err(anyhow!("App state dropped"))).boxed();
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};
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let future = self.request_limiter.stream(async move {
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let Some(api_key) = api_key else {
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return Err(LanguageModelCompletionError::NoApiKey {
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provider: PROVIDER_NAME,
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});
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};
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let request =
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open_ai::stream_completion(http_client.as_ref(), &api_url, &api_key, request);
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let response = request.await?;
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Ok(response)
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});
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async move { Ok(future.await?.boxed()) }.boxed()
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}
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}
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impl LanguageModel for XAiLanguageModel {
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fn id(&self) -> LanguageModelId {
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self.id.clone()
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}
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fn name(&self) -> LanguageModelName {
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LanguageModelName::from(self.model.display_name().to_string())
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}
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fn provider_id(&self) -> LanguageModelProviderId {
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PROVIDER_ID
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}
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fn provider_name(&self) -> LanguageModelProviderName {
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PROVIDER_NAME
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}
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fn supports_tools(&self) -> bool {
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self.model.supports_tool()
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}
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fn supports_images(&self) -> bool {
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self.model.supports_images()
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}
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fn supports_tool_choice(&self, choice: LanguageModelToolChoice) -> bool {
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match choice {
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LanguageModelToolChoice::Auto
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| LanguageModelToolChoice::Any
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| LanguageModelToolChoice::None => true,
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}
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}
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fn tool_input_format(&self) -> LanguageModelToolSchemaFormat {
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let model_id = self.model.id().trim().to_lowercase();
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if model_id.eq(x_ai::Model::Grok4.id()) || model_id.eq(x_ai::Model::GrokCodeFast1.id()) {
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LanguageModelToolSchemaFormat::JsonSchemaSubset
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} else {
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LanguageModelToolSchemaFormat::JsonSchema
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}
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}
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fn telemetry_id(&self) -> String {
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format!("x_ai/{}", self.model.id())
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}
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fn max_token_count(&self) -> u64 {
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self.model.max_token_count()
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}
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fn max_output_tokens(&self) -> Option<u64> {
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self.model.max_output_tokens()
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}
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fn count_tokens(
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&self,
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request: LanguageModelRequest,
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cx: &App,
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) -> BoxFuture<'static, Result<u64>> {
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count_xai_tokens(request, self.model.clone(), cx)
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}
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fn stream_completion(
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&self,
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request: LanguageModelRequest,
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cx: &AsyncApp,
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) -> BoxFuture<
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'static,
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|
Result<
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futures::stream::BoxStream<
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'static,
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Result<LanguageModelCompletionEvent, LanguageModelCompletionError>,
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>,
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LanguageModelCompletionError,
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>,
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> {
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let request = crate::provider::open_ai::into_open_ai(
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request,
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self.model.id(),
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self.model.supports_parallel_tool_calls(),
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self.model.supports_prompt_cache_key(),
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self.max_output_tokens(),
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None,
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);
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let completions = self.stream_completion(request, cx);
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async move {
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let mapper = crate::provider::open_ai::OpenAiEventMapper::new();
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Ok(mapper.map_stream(completions.await?).boxed())
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}
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.boxed()
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}
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}
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|
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pub fn count_xai_tokens(
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request: LanguageModelRequest,
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model: Model,
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cx: &App,
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) -> BoxFuture<'static, Result<u64>> {
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|
cx.background_spawn(async move {
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|
let messages = request
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|
.messages
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|
.into_iter()
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|
.map(|message| tiktoken_rs::ChatCompletionRequestMessage {
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role: match message.role {
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|
Role::User => "user".into(),
|
|
Role::Assistant => "assistant".into(),
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|
Role::System => "system".into(),
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|
},
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content: Some(message.string_contents()),
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|
name: None,
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function_call: None,
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})
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.collect::<Vec<_>>();
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|
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let model_name = if model.max_token_count() >= 100_000 {
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"gpt-4o"
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} else {
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"gpt-4"
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};
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tiktoken_rs::num_tokens_from_messages(model_name, &messages).map(|tokens| tokens as u64)
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})
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.boxed()
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}
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|
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struct ConfigurationView {
|
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api_key_editor: Entity<SingleLineInput>,
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state: Entity<State>,
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load_credentials_task: Option<Task<()>>,
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}
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|
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impl ConfigurationView {
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fn new(state: Entity<State>, window: &mut Window, cx: &mut Context<Self>) -> Self {
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let api_key_editor = cx.new(|cx| {
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SingleLineInput::new(
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|
window,
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cx,
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"xai-0000000000000000000000000000000000000000000000000",
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)
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.label("API key")
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|
});
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|
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cx.observe(&state, |_, _, cx| {
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|
cx.notify();
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})
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.detach();
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|
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let load_credentials_task = Some(cx.spawn_in(window, {
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let state = state.clone();
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async move |this, cx| {
|
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if let Some(task) = state
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.update(cx, |state, cx| state.authenticate(cx))
|
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.log_err()
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{
|
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// We don't log an error, because "not signed in" is also an error.
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let _ = task.await;
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}
|
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this.update(cx, |this, cx| {
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this.load_credentials_task = None;
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cx.notify();
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|
})
|
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.log_err();
|
|
}
|
|
}));
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|
|
Self {
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api_key_editor,
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state,
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load_credentials_task,
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|
}
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}
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|
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fn save_api_key(&mut self, _: &menu::Confirm, window: &mut Window, cx: &mut Context<Self>) {
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let api_key = self.api_key_editor.read(cx).text(cx).trim().to_string();
|
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if api_key.is_empty() {
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return;
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}
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|
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// url changes can cause the editor to be displayed again
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self.api_key_editor
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.update(cx, |editor, cx| editor.set_text("", window, cx));
|
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|
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let state = self.state.clone();
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cx.spawn_in(window, async move |_, cx| {
|
|
state
|
|
.update(cx, |state, cx| state.set_api_key(Some(api_key), cx))?
|
|
.await
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|
})
|
|
.detach_and_log_err(cx);
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|
}
|
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|
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fn reset_api_key(&mut self, window: &mut Window, cx: &mut Context<Self>) {
|
|
self.api_key_editor
|
|
.update(cx, |input, cx| input.set_text("", window, cx));
|
|
|
|
let state = self.state.clone();
|
|
cx.spawn_in(window, async move |_, cx| {
|
|
state
|
|
.update(cx, |state, cx| state.set_api_key(None, cx))?
|
|
.await
|
|
})
|
|
.detach_and_log_err(cx);
|
|
}
|
|
|
|
fn should_render_editor(&self, cx: &mut Context<Self>) -> bool {
|
|
!self.state.read(cx).is_authenticated()
|
|
}
|
|
}
|
|
|
|
impl Render for ConfigurationView {
|
|
fn render(&mut self, _: &mut Window, cx: &mut Context<Self>) -> impl IntoElement {
|
|
let env_var_set = self.state.read(cx).api_key_state.is_from_env_var();
|
|
|
|
let api_key_section = if self.should_render_editor(cx) {
|
|
v_flex()
|
|
.on_action(cx.listener(Self::save_api_key))
|
|
.child(Label::new("To use Zed's agent with xAI, you need to add an API key. Follow these steps:"))
|
|
.child(
|
|
List::new()
|
|
.child(InstructionListItem::new(
|
|
"Create one by visiting",
|
|
Some("xAI console"),
|
|
Some("https://console.x.ai/team/default/api-keys"),
|
|
))
|
|
.child(InstructionListItem::text_only(
|
|
"Paste your API key below and hit enter to start using the agent",
|
|
)),
|
|
)
|
|
.child(self.api_key_editor.clone())
|
|
.child(
|
|
Label::new(format!(
|
|
"You can also assign the {API_KEY_ENV_VAR_NAME} environment variable and restart Zed."
|
|
))
|
|
.size(LabelSize::Small)
|
|
.color(Color::Muted),
|
|
)
|
|
.child(
|
|
Label::new("Note that xAI is a custom OpenAI-compatible provider.")
|
|
.size(LabelSize::Small)
|
|
.color(Color::Muted),
|
|
)
|
|
.into_any()
|
|
} else {
|
|
h_flex()
|
|
.mt_1()
|
|
.p_1()
|
|
.justify_between()
|
|
.rounded_md()
|
|
.border_1()
|
|
.border_color(cx.theme().colors().border)
|
|
.bg(cx.theme().colors().background)
|
|
.child(
|
|
h_flex()
|
|
.gap_1()
|
|
.child(Icon::new(IconName::Check).color(Color::Success))
|
|
.child(Label::new(if env_var_set {
|
|
format!("API key set in {API_KEY_ENV_VAR_NAME} environment variable")
|
|
} else {
|
|
let api_url = XAiLanguageModelProvider::api_url(cx);
|
|
if api_url == XAI_API_URL {
|
|
"API key configured".to_string()
|
|
} else {
|
|
format!("API key configured for {}", truncate_and_trailoff(&api_url, 32))
|
|
}
|
|
})),
|
|
)
|
|
.child(
|
|
Button::new("reset-api-key", "Reset API Key")
|
|
.label_size(LabelSize::Small)
|
|
.icon(IconName::Undo)
|
|
.icon_size(IconSize::Small)
|
|
.icon_position(IconPosition::Start)
|
|
.layer(ElevationIndex::ModalSurface)
|
|
.when(env_var_set, |this| {
|
|
this.tooltip(Tooltip::text(format!("To reset your API key, unset the {API_KEY_ENV_VAR_NAME} environment variable.")))
|
|
})
|
|
.on_click(cx.listener(|this, _, window, cx| this.reset_api_key(window, cx))),
|
|
)
|
|
.into_any()
|
|
};
|
|
|
|
if self.load_credentials_task.is_some() {
|
|
div().child(Label::new("Loading credentials…")).into_any()
|
|
} else {
|
|
v_flex().size_full().child(api_key_section).into_any()
|
|
}
|
|
}
|
|
}
|