use anyhow::{Context as _, Result, anyhow};use collections::BTreeMap;use credentials_provider::CredentialsProvider;use editor::{Editor, EditorElement, EditorStyle};use futures::{FutureExt, Stream, StreamExt, future::BoxFuture};use google_ai::{    FunctionDeclaration, GenerateContentResponse, Part, SystemInstructions, UsageMetadata,};use gpui::{    AnyView, App, AsyncApp, Context, Entity, FontStyle, Subscription, Task, TextStyle, WhiteSpace,};use http_client::HttpClient;use language_model::{    AuthenticateError, LanguageModelCompletionEvent, LanguageModelToolSchemaFormat,    LanguageModelToolUse, LanguageModelToolUseId, MessageContent, StopReason,};use language_model::{    LanguageModel, LanguageModelId, LanguageModelName, LanguageModelProvider,    LanguageModelProviderId, LanguageModelProviderName, LanguageModelProviderState,    LanguageModelRequest, RateLimiter, Role,};use schemars::JsonSchema;use serde::{Deserialize, Serialize};use settings::{Settings, SettingsStore};use std::pin::Pin;use std::sync::Arc;use strum::IntoEnumIterator;use theme::ThemeSettings;use ui::{Icon, IconName, List, Tooltip, prelude::*};use util::ResultExt; use crate::AllLanguageModelSettings;use crate::ui::InstructionListItem; const PROVIDER_ID: &str = "google";const PROVIDER_NAME: &str = "Google AI"; #[derive(Default, Clone, Debug, PartialEq)]pub struct GoogleSettings {    pub api_url: String,    pub available_models: Vec<AvailableModel>,} #[derive(Clone, Debug, PartialEq, Serialize, Deserialize, JsonSchema)]pub struct AvailableModel {    name: String,    display_name: Option<String>,    max_tokens: usize,} pub struct GoogleLanguageModelProvider {    http_client: Arc<dyn HttpClient>,    state: gpui::Entity<State>,} pub struct State {    api_key: Option<String>,    api_key_from_env: bool,    _subscription: Subscription,} const GOOGLE_AI_API_KEY_VAR: &str = "GOOGLE_AI_API_KEY"; impl State {    fn is_authenticated(&self) -> bool {        self.api_key.is_some()    }     fn reset_api_key(&self, cx: &mut Context<Self>) -> Task<Result<()>> {        let credentials_provider = <dyn CredentialsProvider>::global(cx);        let api_url = AllLanguageModelSettings::get_global(cx)            .google            .api_url            .clone();        cx.spawn(async move |this, cx| {            credentials_provider                .delete_credentials(&api_url, &cx)                .await                .log_err();            this.update(cx, |this, cx| {                this.api_key = None;                this.api_key_from_env = false;                cx.notify();            })        })    }     fn set_api_key(&mut self, api_key: String, cx: &mut Context<Self>) -> Task<Result<()>> {        let credentials_provider = <dyn CredentialsProvider>::global(cx);        let api_url = AllLanguageModelSettings::get_global(cx)            .google            .api_url            .clone();        cx.spawn(async move |this, cx| {            credentials_provider                .write_credentials(&api_url, "Bearer", api_key.as_bytes(), &cx)                .await?;            this.update(cx, |this, cx| {                this.api_key = Some(api_key);                cx.notify();            })        })    }     fn authenticate(&self, cx: &mut Context<Self>) -> Task<Result<(), AuthenticateError>> {        if self.is_authenticated() {            return Task::ready(Ok(()));        }         let credentials_provider = <dyn CredentialsProvider>::global(cx);        let api_url = AllLanguageModelSettings::get_global(cx)            .google            .api_url            .clone();         cx.spawn(async move |this, cx| {            let (api_key, from_env) = if let Ok(api_key) = std::env::var(GOOGLE_AI_API_KEY_VAR) {                (api_key, true)            } else {                let (_, api_key) = credentials_provider                    .read_credentials(&api_url, &cx)                    .await?                    .ok_or(AuthenticateError::CredentialsNotFound)?;                (                    String::from_utf8(api_key).context("invalid {PROVIDER_NAME} API key")?,                    false,                )            };             this.update(cx, |this, cx| {                this.api_key = Some(api_key);                this.api_key_from_env = from_env;                cx.notify();            })?;             Ok(())        })    }} impl GoogleLanguageModelProvider {    pub fn new(http_client: Arc<dyn HttpClient>, cx: &mut App) -> Self {        let state = cx.new(|cx| State {            api_key: None,            api_key_from_env: false,            _subscription: cx.observe_global::<SettingsStore>(|_, cx| {                cx.notify();            }),        });         Self { http_client, state }    }} impl LanguageModelProviderState for GoogleLanguageModelProvider {    type ObservableEntity = State;     fn observable_entity(&self) -> Option<gpui::Entity<Self::ObservableEntity>> {        Some(self.state.clone())    }} impl LanguageModelProvider for GoogleLanguageModelProvider {    fn id(&self) -> LanguageModelProviderId {        LanguageModelProviderId(PROVIDER_ID.into())    }     fn name(&self) -> LanguageModelProviderName {        LanguageModelProviderName(PROVIDER_NAME.into())    }     fn icon(&self) -> IconName {        IconName::AiGoogle    }     fn default_model(&self, _cx: &App) -> Option<Arc<dyn LanguageModel>> {        let model = google_ai::Model::default();        Some(Arc::new(GoogleLanguageModel {            id: LanguageModelId::from(model.id().to_string()),            model,            state: self.state.clone(),            http_client: self.http_client.clone(),            request_limiter: RateLimiter::new(4),        }))    }     fn provided_models(&self, cx: &App) -> Vec<Arc<dyn LanguageModel>> {        let mut models = BTreeMap::default();         // Add base models from google_ai::Model::iter()        for model in google_ai::Model::iter() {            if !matches!(model, google_ai::Model::Custom { .. }) {                models.insert(model.id().to_string(), model);            }        }         // Override with available models from settings        for model in &AllLanguageModelSettings::get_global(cx)            .google            .available_models        {            models.insert(                model.name.clone(),                google_ai::Model::Custom {                    name: model.name.clone(),                    display_name: model.display_name.clone(),                    max_tokens: model.max_tokens,                },            );        }         models            .into_values()            .map(|model| {                Arc::new(GoogleLanguageModel {                    id: LanguageModelId::from(model.id().to_string()),                    model,                    state: self.state.clone(),                    http_client: self.http_client.clone(),                    request_limiter: RateLimiter::new(4),                }) as Arc<dyn LanguageModel>            })            .collect()    }     fn is_authenticated(&self, cx: &App) -> bool {        self.state.read(cx).is_authenticated()    }     fn authenticate(&self, cx: &mut App) -> Task<Result<(), AuthenticateError>> {        self.state.update(cx, |state, cx| state.authenticate(cx))    }     fn configuration_view(&self, window: &mut Window, cx: &mut App) -> AnyView {        cx.new(|cx| ConfigurationView::new(self.state.clone(), window, cx))            .into()    }     fn reset_credentials(&self, cx: &mut App) -> Task<Result<()>> {        self.state.update(cx, |state, cx| state.reset_api_key(cx))    }} pub struct GoogleLanguageModel {    id: LanguageModelId,    model: google_ai::Model,    state: gpui::Entity<State>,    http_client: Arc<dyn HttpClient>,    request_limiter: RateLimiter,} impl GoogleLanguageModel {    fn stream_completion(        &self,        request: google_ai::GenerateContentRequest,        cx: &AsyncApp,    ) -> BoxFuture<        'static,        Result<futures::stream::BoxStream<'static, Result<GenerateContentResponse>>>,    > {        let http_client = self.http_client.clone();         let Ok((api_key, api_url)) = cx.read_entity(&self.state, |state, cx| {            let settings = &AllLanguageModelSettings::get_global(cx).google;            (state.api_key.clone(), settings.api_url.clone())        }) else {            return futures::future::ready(Err(anyhow!("App state dropped"))).boxed();        };         async move {            let api_key = api_key.ok_or_else(|| anyhow!("Missing Google API key"))?;            let request = google_ai::stream_generate_content(                http_client.as_ref(),                &api_url,                &api_key,                request,            );            request.await.context("failed to stream completion")        }        .boxed()    }} impl LanguageModel for GoogleLanguageModel {    fn id(&self) -> LanguageModelId {        self.id.clone()    }     fn name(&self) -> LanguageModelName {        LanguageModelName::from(self.model.display_name().to_string())    }     fn provider_id(&self) -> LanguageModelProviderId {        LanguageModelProviderId(PROVIDER_ID.into())    }     fn provider_name(&self) -> LanguageModelProviderName {        LanguageModelProviderName(PROVIDER_NAME.into())    }     fn supports_tools(&self) -> bool {        true    }     fn tool_input_format(&self) -> LanguageModelToolSchemaFormat {        LanguageModelToolSchemaFormat::JsonSchemaSubset    }     fn telemetry_id(&self) -> String {        format!("google/{}", self.model.id())    }     fn max_token_count(&self) -> usize {        self.model.max_token_count()    }     fn count_tokens(        &self,        request: LanguageModelRequest,        cx: &App,    ) -> BoxFuture<'static, Result<usize>> {        let request = into_google(request, self.model.id().to_string());        let http_client = self.http_client.clone();        let api_key = self.state.read(cx).api_key.clone();         let settings = &AllLanguageModelSettings::get_global(cx).google;        let api_url = settings.api_url.clone();         async move {            let api_key = api_key.ok_or_else(|| anyhow!("Missing Google API key"))?;            let response = google_ai::count_tokens(                http_client.as_ref(),                &api_url,                &api_key,                google_ai::CountTokensRequest {                    contents: request.contents,                },            )            .await?;            Ok(response.total_tokens)        }        .boxed()    }     fn stream_completion(        &self,        request: LanguageModelRequest,        cx: &AsyncApp,    ) -> BoxFuture<        'static,        Result<futures::stream::BoxStream<'static, Result<LanguageModelCompletionEvent>>>,    > {        let request = into_google(request, self.model.id().to_string());        let request = self.stream_completion(request, cx);        let future = self.request_limiter.stream(async move {            let response = request.await.map_err(|err| anyhow!(err))?;            Ok(map_to_language_model_completion_events(response))        });        async move { Ok(future.await?.boxed()) }.boxed()    }} pub fn into_google(    mut request: LanguageModelRequest,    model: String,) -> google_ai::GenerateContentRequest {    fn map_content(content: Vec<MessageContent>) -> Vec<Part> {        content            .into_iter()            .filter_map(|content| match content {                language_model::MessageContent::Text(text) => {                    if !text.is_empty() {                        Some(Part::TextPart(google_ai::TextPart { text }))                    } else {                        None                    }                }                language_model::MessageContent::Image(_) => None,                language_model::MessageContent::ToolUse(tool_use) => {                    Some(Part::FunctionCallPart(google_ai::FunctionCallPart {                        function_call: google_ai::FunctionCall {                            name: tool_use.name.to_string(),                            args: tool_use.input,                        },                    }))                }                language_model::MessageContent::ToolResult(tool_result) => Some(                    Part::FunctionResponsePart(google_ai::FunctionResponsePart {                        function_response: google_ai::FunctionResponse {                            name: tool_result.tool_name.to_string(),                            // The API expects a valid JSON object                            response: serde_json::json!({                                "output": tool_result.content                            }),                        },                    }),                ),            })            .collect()    }     let system_instructions = if request        .messages        .first()        .map_or(false, |msg| matches!(msg.role, Role::System))    {        let message = request.messages.remove(0);        Some(SystemInstructions {            parts: map_content(message.content),        })    } else {        None    };     google_ai::GenerateContentRequest {        model,        system_instructions,        contents: request            .messages            .into_iter()            .map(|message| google_ai::Content {                parts: map_content(message.content),                role: match message.role {                    Role::User => google_ai::Role::User,                    Role::Assistant => google_ai::Role::Model,                    Role::System => google_ai::Role::User, // Google AI doesn't have a system role                },            })            .collect(),        generation_config: Some(google_ai::GenerationConfig {            candidate_count: Some(1),            stop_sequences: Some(request.stop),            max_output_tokens: None,            temperature: request.temperature.map(|t| t as f64).or(Some(1.0)),            top_p: None,            top_k: None,        }),        safety_settings: None,        tools: (request.tools.len() > 0).then(|| {            vec![google_ai::Tool {                function_declarations: request                    .tools                    .into_iter()                    .map(|tool| FunctionDeclaration {                        name: tool.name,                        description: tool.description,                        parameters: tool.input_schema,                    })                    .collect(),            }]        }),        tool_config: None,    }} pub fn map_to_language_model_completion_events(    events: Pin<Box<dyn Send + Stream<Item = Result<GenerateContentResponse>>>>,) -> impl Stream<Item = Result<LanguageModelCompletionEvent>> {    use std::sync::atomic::{AtomicU64, Ordering};     static TOOL_CALL_COUNTER: AtomicU64 = AtomicU64::new(0);     struct State {        events: Pin<Box<dyn Send + Stream<Item = Result<GenerateContentResponse>>>>,        usage: UsageMetadata,        stop_reason: StopReason,    }     futures::stream::unfold(        State {            events,            usage: UsageMetadata::default(),            stop_reason: StopReason::EndTurn,        },        |mut state| async move {            if let Some(event) = state.events.next().await {                match event {                    Ok(event) => {                        let mut events: Vec<Result<LanguageModelCompletionEvent>> = Vec::new();                        let mut wants_to_use_tool = false;                        if let Some(usage_metadata) = event.usage_metadata {                            update_usage(&mut state.usage, &usage_metadata);                            events.push(Ok(LanguageModelCompletionEvent::UsageUpdate(                                convert_usage(&state.usage),                            )))                        }                        if let Some(candidates) = event.candidates {                            for candidate in candidates {                                if let Some(finish_reason) = candidate.finish_reason.as_deref() {                                    state.stop_reason = match finish_reason {                                        "STOP" => StopReason::EndTurn,                                        "MAX_TOKENS" => StopReason::MaxTokens,                                        _ => {                                            log::error!(                                                "Unexpected google finish_reason: {finish_reason}"                                            );                                            StopReason::EndTurn                                        }                                    };                                }

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