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122619624d
See https://docs.x.ai/developers/model-capabilities/text/reasoning#the-reasoning_effort-parameter Closes #58056 Release Notes: - agent: Added support for specifying reasoning effort for Grok 4.3 (xAI)
619 lines
20 KiB
Rust
619 lines
20 KiB
Rust
use anyhow::Result;
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use collections::BTreeMap;
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use credentials_provider::CredentialsProvider;
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use futures::{FutureExt, StreamExt, future::BoxFuture};
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use gpui::{AnyView, App, AsyncApp, Context, Entity, Task, TaskExt, Window};
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use http_client::HttpClient;
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use language_model::{
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ApiKeyState, AuthenticateError, EnvVar, IconOrSvg, LanguageModel, LanguageModelCompletionError,
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LanguageModelCompletionEvent, LanguageModelEffortLevel, LanguageModelId, LanguageModelName,
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LanguageModelProvider, LanguageModelProviderId, LanguageModelProviderName,
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LanguageModelProviderState, LanguageModelRequest, LanguageModelToolChoice,
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LanguageModelToolSchemaFormat, RateLimiter, env_var,
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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::{ButtonLink, ConfiguredApiCard, List, ListBulletItem, prelude::*};
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use ui_input::InputField;
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use util::ResultExt;
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use x_ai::XAI_API_URL;
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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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credentials_provider: Arc<dyn CredentialsProvider>,
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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 credentials_provider = self.credentials_provider.clone();
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let api_url = XAiLanguageModelProvider::api_url(cx);
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self.api_key_state.store(
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api_url,
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api_key,
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|this| &mut this.api_key_state,
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credentials_provider,
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cx,
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)
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}
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fn authenticate(&mut self, cx: &mut Context<Self>) -> Task<Result<(), AuthenticateError>> {
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let credentials_provider = self.credentials_provider.clone();
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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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|this| &mut this.api_key_state,
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credentials_provider,
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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(
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http_client: Arc<dyn HttpClient>,
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credentials_provider: Arc<dyn CredentialsProvider>,
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cx: &mut App,
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) -> 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 credentials_provider = this.credentials_provider.clone();
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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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|this| &mut this.api_key_state,
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credentials_provider,
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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), (*API_KEY_ENV_VAR).clone()),
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credentials_provider,
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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) -> IconOrSvg {
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IconOrSvg::Icon(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<
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'static,
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Result<
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futures::stream::BoxStream<'static, Result<ResponseStreamEvent>>,
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LanguageModelCompletionError,
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>,
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> {
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let http_client = self.http_client.clone();
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let (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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});
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let future = self.request_limiter.stream(async move {
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let provider = PROVIDER_NAME;
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let Some(api_key) = api_key else {
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return Err(LanguageModelCompletionError::NoApiKey { provider });
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};
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let request = open_ai::stream_completion(
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http_client.as_ref(),
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provider.0.as_str(),
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&api_url,
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&api_key,
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request,
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);
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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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fn x_ai_reasoning_efforts(model: &x_ai::Model) -> &'static [open_ai::ReasoningEffort] {
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if model.supports_reasoning_effort() {
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&[
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open_ai::ReasoningEffort::None,
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open_ai::ReasoningEffort::Low,
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open_ai::ReasoningEffort::Medium,
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open_ai::ReasoningEffort::High,
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]
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} else {
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&[]
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}
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}
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fn default_thinking_reasoning_effort(model: &x_ai::Model) -> Option<open_ai::ReasoningEffort> {
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if model.supports_reasoning_effort() {
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Some(open_ai::ReasoningEffort::Low)
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} else {
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None
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}
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}
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fn reasoning_effort_for_request(
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request: &LanguageModelRequest,
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model: &x_ai::Model,
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) -> Option<open_ai::ReasoningEffort> {
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let supported_efforts = x_ai_reasoning_efforts(model);
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if supported_efforts.is_empty() {
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return None;
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}
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if request.thinking_allowed {
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request
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.thinking_effort
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.as_deref()
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.and_then(|effort| effort.parse::<open_ai::ReasoningEffort>().ok())
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.filter(|effort| supported_efforts.contains(effort))
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.filter(|effort| *effort != open_ai::ReasoningEffort::None)
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.or_else(|| default_thinking_reasoning_effort(model))
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} else if supported_efforts.contains(&open_ai::ReasoningEffort::None) {
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Some(open_ai::ReasoningEffort::None)
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} else {
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None
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}
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}
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fn supported_thinking_effort_levels(model: &x_ai::Model) -> Vec<LanguageModelEffortLevel> {
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let default_effort = default_thinking_reasoning_effort(model);
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x_ai_reasoning_efforts(model)
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.iter()
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.copied()
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.filter_map(|effort| {
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let (name, value) = match effort {
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open_ai::ReasoningEffort::None => return None,
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open_ai::ReasoningEffort::Minimal => ("Minimal", "minimal"),
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open_ai::ReasoningEffort::Low => ("Low", "low"),
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open_ai::ReasoningEffort::Medium => ("Medium", "medium"),
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open_ai::ReasoningEffort::High => ("High", "high"),
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open_ai::ReasoningEffort::XHigh => ("Extra High", "xhigh"),
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};
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Some(LanguageModelEffortLevel {
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name: name.into(),
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value: value.into(),
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is_default: Some(effort) == default_effort,
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})
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})
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.collect()
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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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|
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fn provider_id(&self) -> LanguageModelProviderId {
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PROVIDER_ID
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|
}
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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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|
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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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|
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fn supports_streaming_tools(&self) -> bool {
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true
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}
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|
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fn supports_tool_choice(&self, choice: LanguageModelToolChoice) -> bool {
|
|
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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|
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fn supports_thinking(&self) -> bool {
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self.model.supports_reasoning_effort()
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}
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fn supported_effort_levels(&self) -> Vec<LanguageModelEffortLevel> {
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supported_thinking_effort_levels(&self.model)
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}
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|
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fn tool_input_format(&self) -> LanguageModelToolSchemaFormat {
|
|
if self.model.requires_json_schema_subset() {
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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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}
|
|
|
|
fn telemetry_id(&self) -> String {
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|
format!("x_ai/{}", self.model.id())
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|
}
|
|
|
|
fn max_token_count(&self) -> u64 {
|
|
self.model.max_token_count()
|
|
}
|
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|
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fn max_output_tokens(&self) -> Option<u64> {
|
|
self.model.max_output_tokens()
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}
|
|
|
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fn supports_split_token_display(&self) -> bool {
|
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true
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|
}
|
|
|
|
fn stream_completion(
|
|
&self,
|
|
request: LanguageModelRequest,
|
|
cx: &AsyncApp,
|
|
) -> BoxFuture<
|
|
'static,
|
|
Result<
|
|
futures::stream::BoxStream<
|
|
'static,
|
|
Result<LanguageModelCompletionEvent, LanguageModelCompletionError>,
|
|
>,
|
|
LanguageModelCompletionError,
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>,
|
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> {
|
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let reasoning_effort = reasoning_effort_for_request(&request, &self.model);
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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(),
|
|
self.model.supports_parallel_tool_calls(),
|
|
self.model.supports_prompt_cache_key(),
|
|
self.max_output_tokens(),
|
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reasoning_effort,
|
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false,
|
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);
|
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let completions = self.stream_completion(request, cx);
|
|
async move {
|
|
let mapper = crate::provider::open_ai::OpenAiEventMapper::new();
|
|
Ok(mapper.map_stream(completions.await?).boxed())
|
|
}
|
|
.boxed()
|
|
}
|
|
}
|
|
|
|
struct ConfigurationView {
|
|
api_key_editor: Entity<InputField>,
|
|
state: Entity<State>,
|
|
load_credentials_task: Option<Task<()>>,
|
|
}
|
|
|
|
impl ConfigurationView {
|
|
fn new(state: Entity<State>, window: &mut Window, cx: &mut Context<Self>) -> Self {
|
|
let api_key_editor = cx.new(|cx| {
|
|
InputField::new(
|
|
window,
|
|
cx,
|
|
"xai-0000000000000000000000000000000000000000000000000",
|
|
)
|
|
.label("API key")
|
|
});
|
|
|
|
cx.observe(&state, |_, _, cx| {
|
|
cx.notify();
|
|
})
|
|
.detach();
|
|
|
|
let load_credentials_task = Some(cx.spawn_in(window, {
|
|
let state = state.clone();
|
|
async move |this, cx| {
|
|
if let Some(task) = Some(state.update(cx, |state, cx| state.authenticate(cx))) {
|
|
// We don't log an error, because "not signed in" is also an error.
|
|
let _ = task.await;
|
|
}
|
|
this.update(cx, |this, cx| {
|
|
this.load_credentials_task = None;
|
|
cx.notify();
|
|
})
|
|
.log_err();
|
|
}
|
|
}));
|
|
|
|
Self {
|
|
api_key_editor,
|
|
state,
|
|
load_credentials_task,
|
|
}
|
|
}
|
|
|
|
fn save_api_key(&mut self, _: &menu::Confirm, window: &mut Window, cx: &mut Context<Self>) {
|
|
let api_key = self.api_key_editor.read(cx).text(cx).trim().to_string();
|
|
if api_key.is_empty() {
|
|
return;
|
|
}
|
|
|
|
// url changes can cause the editor to be displayed again
|
|
self.api_key_editor
|
|
.update(cx, |editor, cx| editor.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(Some(api_key), cx))
|
|
.await
|
|
})
|
|
.detach_and_log_err(cx);
|
|
}
|
|
|
|
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()
|
|
}
|
|
}
|
|
|
|
#[cfg(test)]
|
|
mod tests {
|
|
use super::*;
|
|
|
|
#[test]
|
|
fn grok_43_supports_selectable_thinking_effort_levels() {
|
|
let effort_levels = supported_thinking_effort_levels(&x_ai::Model::Grok43);
|
|
let values = effort_levels
|
|
.iter()
|
|
.map(|level| level.value.as_ref())
|
|
.collect::<Vec<_>>();
|
|
|
|
assert_eq!(values, ["low", "medium", "high"]);
|
|
assert_eq!(
|
|
effort_levels
|
|
.iter()
|
|
.find(|level| level.is_default)
|
|
.map(|level| level.value.as_ref()),
|
|
Some("low")
|
|
);
|
|
}
|
|
|
|
#[test]
|
|
fn grok_43_request_uses_selected_reasoning_effort() {
|
|
let request = LanguageModelRequest {
|
|
thinking_allowed: true,
|
|
thinking_effort: Some("high".to_string()),
|
|
..Default::default()
|
|
};
|
|
|
|
assert_eq!(
|
|
reasoning_effort_for_request(&request, &x_ai::Model::Grok43),
|
|
Some(open_ai::ReasoningEffort::High)
|
|
);
|
|
}
|
|
|
|
#[test]
|
|
fn grok_43_request_uses_none_when_thinking_is_disabled() {
|
|
let request = LanguageModelRequest {
|
|
thinking_allowed: false,
|
|
..Default::default()
|
|
};
|
|
|
|
assert_eq!(
|
|
reasoning_effort_for_request(&request, &x_ai::Model::Grok43),
|
|
Some(open_ai::ReasoningEffort::None)
|
|
);
|
|
}
|
|
}
|
|
|
|
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 configured_card_label = 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 {}", api_url)
|
|
}
|
|
};
|
|
|
|
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(
|
|
ListBulletItem::new("")
|
|
.child(Label::new("Create one by visiting"))
|
|
.child(ButtonLink::new("xAI console", "https://console.x.ai/team/default/api-keys"))
|
|
)
|
|
.child(
|
|
ListBulletItem::new("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 set 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_element()
|
|
} else {
|
|
ConfiguredApiCard::new(configured_card_label)
|
|
.disabled(env_var_set)
|
|
.when(env_var_set, |this| {
|
|
this.tooltip_label(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_element()
|
|
};
|
|
|
|
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()
|
|
}
|
|
}
|
|
}
|