use anthropic::AnthropicError;use anyhow::{anyhow, Result};use client::{    zed_urls, Client, PerformCompletionParams, UserStore, EXPIRED_LLM_TOKEN_HEADER_NAME,    MAX_LLM_MONTHLY_SPEND_REACHED_HEADER_NAME,};use collections::BTreeMap;use feature_flags::{FeatureFlagAppExt, LlmClosedBeta, ZedPro};use futures::{    future::BoxFuture, stream::BoxStream, AsyncBufReadExt, FutureExt, Stream, StreamExt,    TryStreamExt as _,};use gpui::{AnyElement, AnyView, App, AsyncApp, Context, Entity, Subscription, Task};use http_client::{AsyncBody, HttpClient, Method, Response, StatusCode};use language_model::{    AuthenticateError, CloudModel, LanguageModel, LanguageModelCacheConfiguration, LanguageModelId,    LanguageModelName, LanguageModelProviderId, LanguageModelProviderName,    LanguageModelProviderState, LanguageModelProviderTosView, LanguageModelRequest, RateLimiter,    ZED_CLOUD_PROVIDER_ID,};use language_model::{    LanguageModelAvailability, LanguageModelCompletionEvent, LanguageModelProvider, LlmApiToken,    MaxMonthlySpendReachedError, PaymentRequiredError, RefreshLlmTokenListener,};use schemars::JsonSchema;use serde::{de::DeserializeOwned, Deserialize, Serialize};use serde_json::value::RawValue;use settings::{Settings, SettingsStore};use smol::io::{AsyncReadExt, BufReader};use std::{    future,    sync::{Arc, LazyLock},};use strum::IntoEnumIterator;use ui::{prelude::*, TintColor}; use crate::provider::anthropic::{    count_anthropic_tokens, into_anthropic, map_to_language_model_completion_events,};use crate::provider::google::into_google;use crate::provider::open_ai::{count_open_ai_tokens, into_open_ai};use crate::AllLanguageModelSettings; pub const PROVIDER_NAME: &str = "Zed"; const ZED_CLOUD_PROVIDER_ADDITIONAL_MODELS_JSON: Option<&str> =    option_env!("ZED_CLOUD_PROVIDER_ADDITIONAL_MODELS_JSON"); fn zed_cloud_provider_additional_models() -> &'static [AvailableModel] {    static ADDITIONAL_MODELS: LazyLock<Vec<AvailableModel>> = LazyLock::new(|| {        ZED_CLOUD_PROVIDER_ADDITIONAL_MODELS_JSON            .map(|json| serde_json::from_str(json).unwrap())            .unwrap_or_default()    });    ADDITIONAL_MODELS.as_slice()} #[derive(Default, Clone, Debug, PartialEq)]pub struct ZedDotDevSettings {    pub available_models: Vec<AvailableModel>,} #[derive(Clone, Debug, PartialEq, Serialize, Deserialize, JsonSchema)]#[serde(rename_all = "lowercase")]pub enum AvailableProvider {    Anthropic,    OpenAi,    Google,} #[derive(Clone, Debug, PartialEq, Serialize, Deserialize, JsonSchema)]pub struct AvailableModel {    /// The provider of the language model.    pub provider: AvailableProvider,    /// The model's name in the provider's API. e.g. claude-3-5-sonnet-20240620    pub name: String,    /// The name displayed in the UI, such as in the assistant panel model dropdown menu.    pub display_name: Option<String>,    /// The size of the context window, indicating the maximum number of tokens the model can process.    pub max_tokens: usize,    /// The maximum number of output tokens allowed by the model.    pub max_output_tokens: Option<u32>,    /// The maximum number of completion tokens allowed by the model (o1-* only)    pub max_completion_tokens: Option<u32>,    /// Override this model with a different Anthropic model for tool calls.    pub tool_override: Option<String>,    /// Indicates whether this custom model supports caching.    pub cache_configuration: Option<LanguageModelCacheConfiguration>,    /// The default temperature to use for this model.    pub default_temperature: Option<f32>,    /// Any extra beta headers to provide when using the model.    #[serde(default)]    pub extra_beta_headers: Vec<String>,} pub struct CloudLanguageModelProvider {    client: Arc<Client>,    state: gpui::Entity<State>,    _maintain_client_status: Task<()>,} pub struct State {    client: Arc<Client>,    llm_api_token: LlmApiToken,    user_store: Entity<UserStore>,    status: client::Status,    accept_terms: Option<Task<Result<()>>>,    _settings_subscription: Subscription,    _llm_token_subscription: Subscription,} impl State {    fn new(        client: Arc<Client>,        user_store: Entity<UserStore>,        status: client::Status,        cx: &mut Context<Self>,    ) -> Self {        let refresh_llm_token_listener = RefreshLlmTokenListener::global(cx);         Self {            client: client.clone(),            llm_api_token: LlmApiToken::default(),            user_store,            status,            accept_terms: None,            _settings_subscription: cx.observe_global::<SettingsStore>(|_, cx| {                cx.notify();            }),            _llm_token_subscription: cx.subscribe(                &refresh_llm_token_listener,                |this, _listener, _event, cx| {                    let client = this.client.clone();                    let llm_api_token = this.llm_api_token.clone();                    cx.spawn(|_this, _cx| async move {                        llm_api_token.refresh(&client).await?;                        anyhow::Ok(())                    })                    .detach_and_log_err(cx);                },            ),        }    }     fn is_signed_out(&self) -> bool {        self.status.is_signed_out()    }     fn authenticate(&self, cx: &mut Context<Self>) -> Task<Result<()>> {        let client = self.client.clone();        cx.spawn(move |this, mut cx| async move {            client.authenticate_and_connect(true, &cx).await?;            this.update(&mut cx, |_, cx| cx.notify())        })    }     fn has_accepted_terms_of_service(&self, cx: &App) -> bool {        self.user_store            .read(cx)            .current_user_has_accepted_terms()            .unwrap_or(false)    }     fn accept_terms_of_service(&mut self, cx: &mut Context<Self>) {        let user_store = self.user_store.clone();        self.accept_terms = Some(cx.spawn(move |this, mut cx| async move {            let _ = user_store                .update(&mut cx, |store, cx| store.accept_terms_of_service(cx))?                .await;            this.update(&mut cx, |this, cx| {                this.accept_terms = None;                cx.notify()            })        }));    }} impl CloudLanguageModelProvider {    pub fn new(user_store: Entity<UserStore>, client: Arc<Client>, cx: &mut App) -> Self {        let mut status_rx = client.status();        let status = *status_rx.borrow();         let state = cx.new(|cx| State::new(client.clone(), user_store.clone(), status, cx));         let state_ref = state.downgrade();        let maintain_client_status = cx.spawn(|mut cx| async move {            while let Some(status) = status_rx.next().await {                if let Some(this) = state_ref.upgrade() {                    _ = this.update(&mut cx, |this, cx| {                        if this.status != status {                            this.status = status;                            cx.notify();                        }                    });                } else {                    break;                }            }        });         Self {            client,            state: state.clone(),            _maintain_client_status: maintain_client_status,        }    }} impl LanguageModelProviderState for CloudLanguageModelProvider {    type ObservableEntity = State;     fn observable_entity(&self) -> Option<gpui::Entity<Self::ObservableEntity>> {        Some(self.state.clone())    }} impl LanguageModelProvider for CloudLanguageModelProvider {    fn id(&self) -> LanguageModelProviderId {        LanguageModelProviderId(ZED_CLOUD_PROVIDER_ID.into())    }     fn name(&self) -> LanguageModelProviderName {        LanguageModelProviderName(PROVIDER_NAME.into())    }     fn icon(&self) -> IconName {        IconName::AiZed    }     fn default_model(&self, cx: &App) -> Option<Arc<dyn LanguageModel>> {        let llm_api_token = self.state.read(cx).llm_api_token.clone();        let model = CloudModel::Anthropic(anthropic::Model::default());        Some(Arc::new(CloudLanguageModel {            id: LanguageModelId::from(model.id().to_string()),            model,            llm_api_token: llm_api_token.clone(),            client: self.client.clone(),            request_limiter: RateLimiter::new(4),        }))    }     fn provided_models(&self, cx: &App) -> Vec<Arc<dyn LanguageModel>> {        let mut models = BTreeMap::default();         if cx.is_staff() {            for model in anthropic::Model::iter() {                if !matches!(model, anthropic::Model::Custom { .. }) {                    models.insert(model.id().to_string(), CloudModel::Anthropic(model));                }            }            for model in open_ai::Model::iter() {                if !matches!(model, open_ai::Model::Custom { .. }) {                    models.insert(model.id().to_string(), CloudModel::OpenAi(model));                }            }            for model in google_ai::Model::iter() {                if !matches!(model, google_ai::Model::Custom { .. }) {                    models.insert(model.id().to_string(), CloudModel::Google(model));                }            }        } else {            models.insert(                anthropic::Model::Claude3_5Sonnet.id().to_string(),                CloudModel::Anthropic(anthropic::Model::Claude3_5Sonnet),            );            models.insert(                anthropic::Model::Claude3_7Sonnet.id().to_string(),                CloudModel::Anthropic(anthropic::Model::Claude3_7Sonnet),            );        }         let llm_closed_beta_models = if cx.has_flag::<LlmClosedBeta>() {            zed_cloud_provider_additional_models()        } else {            &[]        };         // Override with available models from settings        for model in AllLanguageModelSettings::get_global(cx)            .zed_dot_dev            .available_models            .iter()            .chain(llm_closed_beta_models)            .cloned()        {            let model = match model.provider {                AvailableProvider::Anthropic => CloudModel::Anthropic(anthropic::Model::Custom {                    name: model.name.clone(),                    display_name: model.display_name.clone(),                    max_tokens: model.max_tokens,                    tool_override: model.tool_override.clone(),                    cache_configuration: model.cache_configuration.as_ref().map(|config| {                        anthropic::AnthropicModelCacheConfiguration {                            max_cache_anchors: config.max_cache_anchors,                            should_speculate: config.should_speculate,                            min_total_token: config.min_total_token,                        }                    }),                    default_temperature: model.default_temperature,                    max_output_tokens: model.max_output_tokens,                    extra_beta_headers: model.extra_beta_headers.clone(),                }),                AvailableProvider::OpenAi => CloudModel::OpenAi(open_ai::Model::Custom {                    name: model.name.clone(),                    display_name: model.display_name.clone(),                    max_tokens: model.max_tokens,                    max_output_tokens: model.max_output_tokens,                    max_completion_tokens: model.max_completion_tokens,                }),                AvailableProvider::Google => CloudModel::Google(google_ai::Model::Custom {                    name: model.name.clone(),                    display_name: model.display_name.clone(),                    max_tokens: model.max_tokens,                }),            };            models.insert(model.id().to_string(), model.clone());        }         let llm_api_token = self.state.read(cx).llm_api_token.clone();        models            .into_values()            .map(|model| {                Arc::new(CloudLanguageModel {                    id: LanguageModelId::from(model.id().to_string()),                    model,                    llm_api_token: llm_api_token.clone(),                    client: self.client.clone(),                    request_limiter: RateLimiter::new(4),                }) as Arc<dyn LanguageModel>            })            .collect()    }     fn is_authenticated(&self, cx: &App) -> bool {        !self.state.read(cx).is_signed_out()    }     fn authenticate(&self, _cx: &mut App) -> Task<Result<(), AuthenticateError>> {        Task::ready(Ok(()))    }     fn configuration_view(&self, _: &mut Window, cx: &mut App) -> AnyView {        cx.new(|_| ConfigurationView {            state: self.state.clone(),        })        .into()    }     fn must_accept_terms(&self, cx: &App) -> bool {        !self.state.read(cx).has_accepted_terms_of_service(cx)    }     fn render_accept_terms(        &self,        view: LanguageModelProviderTosView,        cx: &mut App,    ) -> Option<AnyElement> {        render_accept_terms(self.state.clone(), view, cx)    }     fn reset_credentials(&self, _cx: &mut App) -> Task<Result<()>> {        Task::ready(Ok(()))    }} fn render_accept_terms(    state: Entity<State>,    view_kind: LanguageModelProviderTosView,    cx: &mut App,) -> Option<AnyElement> {    if state.read(cx).has_accepted_terms_of_service(cx) {        return None;    }     let accept_terms_disabled = state.read(cx).accept_terms.is_some();     let terms_button = Button::new("terms_of_service", "Terms of Service")        .style(ButtonStyle::Subtle)        .icon(IconName::ArrowUpRight)        .icon_color(Color::Muted)        .icon_size(IconSize::XSmall)        .on_click(move |_, _window, cx| cx.open_url("https://zed.dev/terms-of-service"));     let text = "To start using Zed AI, please read and accept the";     let form = v_flex()        .w_full()        .gap_2()        .child(            h_flex()                .flex_wrap()                .items_start()                .child(Label::new(text))                .child(terms_button),        )        .child({            let button_container = h_flex().w_full().child(                Button::new("accept_terms", "I accept the Terms of Service")                    .style(ButtonStyle::Tinted(TintColor::Accent))                    .disabled(accept_terms_disabled)                    .on_click({                        let state = state.downgrade();                        move |_, _window, cx| {                            state                                .update(cx, |state, cx| state.accept_terms_of_service(cx))                                .ok();                        }                    }),            );             match view_kind {                LanguageModelProviderTosView::PromptEditorPopup => button_container.justify_end(),                LanguageModelProviderTosView::Configuration                | LanguageModelProviderTosView::ThreadEmptyState => {                    button_container.justify_start()                }            }        });     Some(form.into_any())} pub struct CloudLanguageModel {    id: LanguageModelId,    model: CloudModel,    llm_api_token: LlmApiToken,    client: Arc<Client>,    request_limiter: RateLimiter,} impl CloudLanguageModel {    async fn perform_llm_completion(        client: Arc<Client>,        llm_api_token: LlmApiToken,        body: PerformCompletionParams,    ) -> Result<Response<AsyncBody>> {        let http_client = &client.http_client();         let mut token = llm_api_token.acquire(&client).await?;        let mut did_retry = false;         let response = loop {            let request_builder = http_client::Request::builder();            let request = request_builder                .method(Method::POST)                .uri(http_client.build_zed_llm_url("/completion", &[])?.as_ref())                .header("Content-Type", "application/json")                .header("Authorization", format!("Bearer {token}"))                .body(serde_json::to_string(&body)?.into())?;            let mut response = http_client.send(request).await?;            if response.status().is_success() {                break response;            } else if !did_retry                && response                    .headers()                    .get(EXPIRED_LLM_TOKEN_HEADER_NAME)                    .is_some()            {                did_retry = true;                token = llm_api_token.refresh(&client).await?;            } else if response.status() == StatusCode::FORBIDDEN                && response                    .headers()                    .get(MAX_LLM_MONTHLY_SPEND_REACHED_HEADER_NAME)                    .is_some()            {                break Err(anyhow!(MaxMonthlySpendReachedError))?;            } else if response.status() == StatusCode::PAYMENT_REQUIRED {                break Err(anyhow!(PaymentRequiredError))?;            } else {                let mut body = String::new();                response.body_mut().read_to_string(&mut body).await?;                break Err(anyhow!(                    "cloud language model completion failed with status {}: {body}",                    response.status()                ))?;            }        };         Ok(response)    }} impl LanguageModel for CloudLanguageModel {    fn id(&self) -> LanguageModelId {        self.id.clone()    }     fn name(&self) -> LanguageModelName {        LanguageModelName::from(self.model.display_name().to_string())    }     fn icon(&self) -> Option<IconName> {        self.model.icon()    }     fn provider_id(&self) -> LanguageModelProviderId {        LanguageModelProviderId(ZED_CLOUD_PROVIDER_ID.into())    } 

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