1use anyhow::{Context as _, Result, anyhow};
2use collections::BTreeMap;
3use credentials_provider::CredentialsProvider;
4use editor::{Editor, EditorElement, EditorStyle};
5use futures::{FutureExt, Stream, StreamExt, future, future::BoxFuture};
6use google_ai::{
7 FunctionDeclaration, GenerateContentResponse, GoogleModelMode, Part, SystemInstruction,
8 ThinkingConfig, UsageMetadata,
9};
10use gpui::{
11 AnyView, App, AsyncApp, Context, Entity, FontStyle, SharedString, Task, TextStyle, WhiteSpace,
12 Window,
13};
14use http_client::HttpClient;
15use language_model::{
16 AuthenticateError, ConfigurationViewTargetAgent, LanguageModelCompletionError,
17 LanguageModelCompletionEvent, LanguageModelToolChoice, LanguageModelToolSchemaFormat,
18 LanguageModelToolUse, LanguageModelToolUseId, MessageContent, StopReason,
19};
20use language_model::{
21 LanguageModel, LanguageModelId, LanguageModelName, LanguageModelProvider,
22 LanguageModelProviderId, LanguageModelProviderName, LanguageModelProviderState,
23 LanguageModelRequest, RateLimiter, Role,
24};
25use schemars::JsonSchema;
26use serde::{Deserialize, Serialize};
27pub use settings::GoogleAvailableModel as AvailableModel;
28use settings::{Settings, SettingsStore};
29use std::pin::Pin;
30use std::sync::{
31 Arc, LazyLock,
32 atomic::{self, AtomicU64},
33};
34use strum::IntoEnumIterator;
35use theme::ThemeSettings;
36use ui::{Icon, IconName, List, Tooltip, prelude::*};
37use util::{ResultExt, truncate_and_trailoff};
38use zed_env_vars::EnvVar;
39
40use crate::api_key::ApiKey;
41use crate::api_key::ApiKeyState;
42use crate::ui::InstructionListItem;
43
44const PROVIDER_ID: LanguageModelProviderId = language_model::GOOGLE_PROVIDER_ID;
45const PROVIDER_NAME: LanguageModelProviderName = language_model::GOOGLE_PROVIDER_NAME;
46
47#[derive(Default, Clone, Debug, PartialEq)]
48pub struct GoogleSettings {
49 pub api_url: String,
50 pub available_models: Vec<AvailableModel>,
51}
52
53#[derive(Clone, Copy, Debug, Default, PartialEq, Serialize, Deserialize, JsonSchema)]
54#[serde(tag = "type", rename_all = "lowercase")]
55pub enum ModelMode {
56 #[default]
57 Default,
58 Thinking {
59 /// The maximum number of tokens to use for reasoning. Must be lower than the model's `max_output_tokens`.
60 budget_tokens: Option<u32>,
61 },
62}
63
64pub struct GoogleLanguageModelProvider {
65 http_client: Arc<dyn HttpClient>,
66 state: gpui::Entity<State>,
67}
68
69pub struct State {
70 api_key_state: ApiKeyState,
71}
72
73const GEMINI_API_KEY_VAR_NAME: &str = "GEMINI_API_KEY";
74const GOOGLE_AI_API_KEY_VAR_NAME: &str = "GOOGLE_AI_API_KEY";
75
76static API_KEY_ENV_VAR: LazyLock<EnvVar> = LazyLock::new(|| {
77 // Try GEMINI_API_KEY first as primary, fallback to GOOGLE_AI_API_KEY
78 EnvVar::new(GEMINI_API_KEY_VAR_NAME.into()).or(EnvVar::new(GOOGLE_AI_API_KEY_VAR_NAME.into()))
79});
80
81impl State {
82 fn is_authenticated(&self) -> bool {
83 self.api_key_state.has_key()
84 }
85
86 fn set_api_key(&mut self, api_key: Option<String>, cx: &mut Context<Self>) -> Task<Result<()>> {
87 let api_url = GoogleLanguageModelProvider::api_url(cx);
88 self.api_key_state
89 .store(api_url, api_key, |this| &mut this.api_key_state, cx)
90 }
91
92 fn authenticate(&mut self, cx: &mut Context<Self>) -> Task<Result<(), AuthenticateError>> {
93 let api_url = GoogleLanguageModelProvider::api_url(cx);
94 self.api_key_state.load_if_needed(
95 api_url,
96 &API_KEY_ENV_VAR,
97 |this| &mut this.api_key_state,
98 cx,
99 )
100 }
101}
102
103impl GoogleLanguageModelProvider {
104 pub fn new(http_client: Arc<dyn HttpClient>, cx: &mut App) -> Self {
105 let state = cx.new(|cx| {
106 cx.observe_global::<SettingsStore>(|this: &mut State, cx| {
107 let api_url = Self::api_url(cx);
108 this.api_key_state.handle_url_change(
109 api_url,
110 &API_KEY_ENV_VAR,
111 |this| &mut this.api_key_state,
112 cx,
113 );
114 cx.notify();
115 })
116 .detach();
117 State {
118 api_key_state: ApiKeyState::new(Self::api_url(cx)),
119 }
120 });
121
122 Self { http_client, state }
123 }
124
125 fn create_language_model(&self, model: google_ai::Model) -> Arc<dyn LanguageModel> {
126 Arc::new(GoogleLanguageModel {
127 id: LanguageModelId::from(model.id().to_string()),
128 model,
129 state: self.state.clone(),
130 http_client: self.http_client.clone(),
131 request_limiter: RateLimiter::new(4),
132 })
133 }
134
135 pub fn api_key_for_gemini_cli(cx: &mut App) -> Task<Result<String>> {
136 if let Some(key) = API_KEY_ENV_VAR.value.clone() {
137 return Task::ready(Ok(key));
138 }
139 let credentials_provider = <dyn CredentialsProvider>::global(cx);
140 let api_url = Self::api_url(cx).to_string();
141 cx.spawn(async move |cx| {
142 Ok(
143 ApiKey::load_from_system_keychain(&api_url, credentials_provider.as_ref(), cx)
144 .await?
145 .key()
146 .to_string(),
147 )
148 })
149 }
150
151 fn settings(cx: &App) -> &GoogleSettings {
152 &crate::AllLanguageModelSettings::get_global(cx).google
153 }
154
155 fn api_url(cx: &App) -> SharedString {
156 let api_url = &Self::settings(cx).api_url;
157 if api_url.is_empty() {
158 google_ai::API_URL.into()
159 } else {
160 SharedString::new(api_url.as_str())
161 }
162 }
163}
164
165impl LanguageModelProviderState for GoogleLanguageModelProvider {
166 type ObservableEntity = State;
167
168 fn observable_entity(&self) -> Option<gpui::Entity<Self::ObservableEntity>> {
169 Some(self.state.clone())
170 }
171}
172
173impl LanguageModelProvider for GoogleLanguageModelProvider {
174 fn id(&self) -> LanguageModelProviderId {
175 PROVIDER_ID
176 }
177
178 fn name(&self) -> LanguageModelProviderName {
179 PROVIDER_NAME
180 }
181
182 fn icon(&self) -> IconName {
183 IconName::AiGoogle
184 }
185
186 fn default_model(&self, _cx: &App) -> Option<Arc<dyn LanguageModel>> {
187 Some(self.create_language_model(google_ai::Model::default()))
188 }
189
190 fn default_fast_model(&self, _cx: &App) -> Option<Arc<dyn LanguageModel>> {
191 Some(self.create_language_model(google_ai::Model::default_fast()))
192 }
193
194 fn provided_models(&self, cx: &App) -> Vec<Arc<dyn LanguageModel>> {
195 let mut models = BTreeMap::default();
196
197 // Add base models from google_ai::Model::iter()
198 for model in google_ai::Model::iter() {
199 if !matches!(model, google_ai::Model::Custom { .. }) {
200 models.insert(model.id().to_string(), model);
201 }
202 }
203
204 // Override with available models from settings
205 for model in &GoogleLanguageModelProvider::settings(cx).available_models {
206 models.insert(
207 model.name.clone(),
208 google_ai::Model::Custom {
209 name: model.name.clone(),
210 display_name: model.display_name.clone(),
211 max_tokens: model.max_tokens,
212 mode: model.mode.unwrap_or_default(),
213 },
214 );
215 }
216
217 models
218 .into_values()
219 .map(|model| {
220 Arc::new(GoogleLanguageModel {
221 id: LanguageModelId::from(model.id().to_string()),
222 model,
223 state: self.state.clone(),
224 http_client: self.http_client.clone(),
225 request_limiter: RateLimiter::new(4),
226 }) as Arc<dyn LanguageModel>
227 })
228 .collect()
229 }
230
231 fn is_authenticated(&self, cx: &App) -> bool {
232 self.state.read(cx).is_authenticated()
233 }
234
235 fn authenticate(&self, cx: &mut App) -> Task<Result<(), AuthenticateError>> {
236 self.state.update(cx, |state, cx| state.authenticate(cx))
237 }
238
239 fn configuration_view(
240 &self,
241 target_agent: language_model::ConfigurationViewTargetAgent,
242 window: &mut Window,
243 cx: &mut App,
244 ) -> AnyView {
245 cx.new(|cx| ConfigurationView::new(self.state.clone(), target_agent, window, cx))
246 .into()
247 }
248
249 fn reset_credentials(&self, cx: &mut App) -> Task<Result<()>> {
250 self.state
251 .update(cx, |state, cx| state.set_api_key(None, cx))
252 }
253}
254
255pub struct GoogleLanguageModel {
256 id: LanguageModelId,
257 model: google_ai::Model,
258 state: gpui::Entity<State>,
259 http_client: Arc<dyn HttpClient>,
260 request_limiter: RateLimiter,
261}
262
263impl GoogleLanguageModel {
264 fn stream_completion(
265 &self,
266 request: google_ai::GenerateContentRequest,
267 cx: &AsyncApp,
268 ) -> BoxFuture<
269 'static,
270 Result<futures::stream::BoxStream<'static, Result<GenerateContentResponse>>>,
271 > {
272 let http_client = self.http_client.clone();
273
274 let Ok((api_key, api_url)) = self.state.read_with(cx, |state, cx| {
275 let api_url = GoogleLanguageModelProvider::api_url(cx);
276 (state.api_key_state.key(&api_url), api_url)
277 }) else {
278 return future::ready(Err(anyhow!("App state dropped"))).boxed();
279 };
280
281 async move {
282 let api_key = api_key.context("Missing Google API key")?;
283 let request = google_ai::stream_generate_content(
284 http_client.as_ref(),
285 &api_url,
286 &api_key,
287 request,
288 );
289 request.await.context("failed to stream completion")
290 }
291 .boxed()
292 }
293}
294
295impl LanguageModel for GoogleLanguageModel {
296 fn id(&self) -> LanguageModelId {
297 self.id.clone()
298 }
299
300 fn name(&self) -> LanguageModelName {
301 LanguageModelName::from(self.model.display_name().to_string())
302 }
303
304 fn provider_id(&self) -> LanguageModelProviderId {
305 PROVIDER_ID
306 }
307
308 fn provider_name(&self) -> LanguageModelProviderName {
309 PROVIDER_NAME
310 }
311
312 fn supports_tools(&self) -> bool {
313 self.model.supports_tools()
314 }
315
316 fn supports_images(&self) -> bool {
317 self.model.supports_images()
318 }
319
320 fn supports_tool_choice(&self, choice: LanguageModelToolChoice) -> bool {
321 match choice {
322 LanguageModelToolChoice::Auto
323 | LanguageModelToolChoice::Any
324 | LanguageModelToolChoice::None => true,
325 }
326 }
327
328 fn tool_input_format(&self) -> LanguageModelToolSchemaFormat {
329 LanguageModelToolSchemaFormat::JsonSchemaSubset
330 }
331
332 fn telemetry_id(&self) -> String {
333 format!("google/{}", self.model.request_id())
334 }
335
336 fn max_token_count(&self) -> u64 {
337 self.model.max_token_count()
338 }
339
340 fn max_output_tokens(&self) -> Option<u64> {
341 self.model.max_output_tokens()
342 }
343
344 fn count_tokens(
345 &self,
346 request: LanguageModelRequest,
347 cx: &App,
348 ) -> BoxFuture<'static, Result<u64>> {
349 let model_id = self.model.request_id().to_string();
350 let request = into_google(request, model_id, self.model.mode());
351 let http_client = self.http_client.clone();
352 let api_url = GoogleLanguageModelProvider::api_url(cx);
353 let api_key = self.state.read(cx).api_key_state.key(&api_url);
354
355 async move {
356 let Some(api_key) = api_key else {
357 return Err(LanguageModelCompletionError::NoApiKey {
358 provider: PROVIDER_NAME,
359 }
360 .into());
361 };
362 let response = google_ai::count_tokens(
363 http_client.as_ref(),
364 &api_url,
365 &api_key,
366 google_ai::CountTokensRequest {
367 generate_content_request: request,
368 },
369 )
370 .await?;
371 Ok(response.total_tokens)
372 }
373 .boxed()
374 }
375
376 fn stream_completion(
377 &self,
378 request: LanguageModelRequest,
379 cx: &AsyncApp,
380 ) -> BoxFuture<
381 'static,
382 Result<
383 futures::stream::BoxStream<
384 'static,
385 Result<LanguageModelCompletionEvent, LanguageModelCompletionError>,
386 >,
387 LanguageModelCompletionError,
388 >,
389 > {
390 let request = into_google(
391 request,
392 self.model.request_id().to_string(),
393 self.model.mode(),
394 );
395 let request = self.stream_completion(request, cx);
396 let future = self.request_limiter.stream(async move {
397 let response = request.await.map_err(LanguageModelCompletionError::from)?;
398 Ok(GoogleEventMapper::new().map_stream(response))
399 });
400 async move { Ok(future.await?.boxed()) }.boxed()
401 }
402}
403
404pub fn into_google(
405 mut request: LanguageModelRequest,
406 model_id: String,
407 mode: GoogleModelMode,
408) -> google_ai::GenerateContentRequest {
409 fn map_content(content: Vec<MessageContent>) -> Vec<Part> {
410 content
411 .into_iter()
412 .flat_map(|content| match content {
413 language_model::MessageContent::Text(text) => {
414 if !text.is_empty() {
415 vec![Part::TextPart(google_ai::TextPart { text })]
416 } else {
417 vec![]
418 }
419 }
420 language_model::MessageContent::Thinking {
421 text: _,
422 signature: Some(signature),
423 } => {
424 if !signature.is_empty() {
425 vec![Part::ThoughtPart(google_ai::ThoughtPart {
426 thought: true,
427 thought_signature: signature,
428 })]
429 } else {
430 vec![]
431 }
432 }
433 language_model::MessageContent::Thinking { .. } => {
434 vec![]
435 }
436 language_model::MessageContent::RedactedThinking(_) => vec![],
437 language_model::MessageContent::Image(image) => {
438 vec![Part::InlineDataPart(google_ai::InlineDataPart {
439 inline_data: google_ai::GenerativeContentBlob {
440 mime_type: "image/png".to_string(),
441 data: image.source.to_string(),
442 },
443 })]
444 }
445 language_model::MessageContent::ToolUse(tool_use) => {
446 vec![Part::FunctionCallPart(google_ai::FunctionCallPart {
447 function_call: google_ai::FunctionCall {
448 name: tool_use.name.to_string(),
449 args: tool_use.input,
450 },
451 })]
452 }
453 language_model::MessageContent::ToolResult(tool_result) => {
454 match tool_result.content {
455 language_model::LanguageModelToolResultContent::Text(text) => {
456 vec![Part::FunctionResponsePart(
457 google_ai::FunctionResponsePart {
458 function_response: google_ai::FunctionResponse {
459 name: tool_result.tool_name.to_string(),
460 // The API expects a valid JSON object
461 response: serde_json::json!({
462 "output": text
463 }),
464 },
465 },
466 )]
467 }
468 language_model::LanguageModelToolResultContent::Image(image) => {
469 vec![
470 Part::FunctionResponsePart(google_ai::FunctionResponsePart {
471 function_response: google_ai::FunctionResponse {
472 name: tool_result.tool_name.to_string(),
473 // The API expects a valid JSON object
474 response: serde_json::json!({
475 "output": "Tool responded with an image"
476 }),
477 },
478 }),
479 Part::InlineDataPart(google_ai::InlineDataPart {
480 inline_data: google_ai::GenerativeContentBlob {
481 mime_type: "image/png".to_string(),
482 data: image.source.to_string(),
483 },
484 }),
485 ]
486 }
487 }
488 }
489 })
490 .collect()
491 }
492
493 let system_instructions = if request
494 .messages
495 .first()
496 .is_some_and(|msg| matches!(msg.role, Role::System))
497 {
498 let message = request.messages.remove(0);
499 Some(SystemInstruction {
500 parts: map_content(message.content),
501 })
502 } else {
503 None
504 };
505
506 google_ai::GenerateContentRequest {
507 model: google_ai::ModelName { model_id },
508 system_instruction: system_instructions,
509 contents: request
510 .messages
511 .into_iter()
512 .filter_map(|message| {
513 let parts = map_content(message.content);
514 if parts.is_empty() {
515 None
516 } else {
517 Some(google_ai::Content {
518 parts,
519 role: match message.role {
520 Role::User => google_ai::Role::User,
521 Role::Assistant => google_ai::Role::Model,
522 Role::System => google_ai::Role::User, // Google AI doesn't have a system role
523 },
524 })
525 }
526 })
527 .collect(),
528 generation_config: Some(google_ai::GenerationConfig {
529 candidate_count: Some(1),
530 stop_sequences: Some(request.stop),
531 max_output_tokens: None,
532 temperature: request.temperature.map(|t| t as f64).or(Some(1.0)),
533 thinking_config: match (request.thinking_allowed, mode) {
534 (true, GoogleModelMode::Thinking { budget_tokens }) => {
535 budget_tokens.map(|thinking_budget| ThinkingConfig { thinking_budget })
536 }
537 _ => None,
538 },
539 top_p: None,
540 top_k: None,
541 }),
542 safety_settings: None,
543 tools: (!request.tools.is_empty()).then(|| {
544 vec![google_ai::Tool {
545 function_declarations: request
546 .tools
547 .into_iter()
548 .map(|tool| FunctionDeclaration {
549 name: tool.name,
550 description: tool.description,
551 parameters: tool.input_schema,
552 })
553 .collect(),
554 }]
555 }),
556 tool_config: request.tool_choice.map(|choice| google_ai::ToolConfig {
557 function_calling_config: google_ai::FunctionCallingConfig {
558 mode: match choice {
559 LanguageModelToolChoice::Auto => google_ai::FunctionCallingMode::Auto,
560 LanguageModelToolChoice::Any => google_ai::FunctionCallingMode::Any,
561 LanguageModelToolChoice::None => google_ai::FunctionCallingMode::None,
562 },
563 allowed_function_names: None,
564 },
565 }),
566 }
567}
568
569pub struct GoogleEventMapper {
570 usage: UsageMetadata,
571 stop_reason: StopReason,
572}
573
574impl GoogleEventMapper {
575 pub fn new() -> Self {
576 Self {
577 usage: UsageMetadata::default(),
578 stop_reason: StopReason::EndTurn,
579 }
580 }
581
582 pub fn map_stream(
583 mut self,
584 events: Pin<Box<dyn Send + Stream<Item = Result<GenerateContentResponse>>>>,
585 ) -> impl Stream<Item = Result<LanguageModelCompletionEvent, LanguageModelCompletionError>>
586 {
587 events
588 .map(Some)
589 .chain(futures::stream::once(async { None }))
590 .flat_map(move |event| {
591 futures::stream::iter(match event {
592 Some(Ok(event)) => self.map_event(event),
593 Some(Err(error)) => {
594 vec![Err(LanguageModelCompletionError::from(error))]
595 }
596 None => vec![Ok(LanguageModelCompletionEvent::Stop(self.stop_reason))],
597 })
598 })
599 }
600
601 pub fn map_event(
602 &mut self,
603 event: GenerateContentResponse,
604 ) -> Vec<Result<LanguageModelCompletionEvent, LanguageModelCompletionError>> {
605 static TOOL_CALL_COUNTER: AtomicU64 = AtomicU64::new(0);
606
607 let mut events: Vec<_> = Vec::new();
608 let mut wants_to_use_tool = false;
609 if let Some(usage_metadata) = event.usage_metadata {
610 update_usage(&mut self.usage, &usage_metadata);
611 events.push(Ok(LanguageModelCompletionEvent::UsageUpdate(
612 convert_usage(&self.usage),
613 )))
614 }
615 if let Some(candidates) = event.candidates {
616 for candidate in candidates {
617 if let Some(finish_reason) = candidate.finish_reason.as_deref() {
618 self.stop_reason = match finish_reason {
619 "STOP" => StopReason::EndTurn,
620 "MAX_TOKENS" => StopReason::MaxTokens,
621 _ => {
622 log::error!("Unexpected google finish_reason: {finish_reason}");
623 StopReason::EndTurn
624 }
625 };
626 }
627 candidate
628 .content
629 .parts
630 .into_iter()
631 .for_each(|part| match part {
632 Part::TextPart(text_part) => {
633 events.push(Ok(LanguageModelCompletionEvent::Text(text_part.text)))
634 }
635 Part::InlineDataPart(_) => {}
636 Part::FunctionCallPart(function_call_part) => {
637 wants_to_use_tool = true;
638 let name: Arc<str> = function_call_part.function_call.name.into();
639 let next_tool_id =
640 TOOL_CALL_COUNTER.fetch_add(1, atomic::Ordering::SeqCst);
641 let id: LanguageModelToolUseId =
642 format!("{}-{}", name, next_tool_id).into();
643
644 events.push(Ok(LanguageModelCompletionEvent::ToolUse(
645 LanguageModelToolUse {
646 id,
647 name,
648 is_input_complete: true,
649 raw_input: function_call_part.function_call.args.to_string(),
650 input: function_call_part.function_call.args,
651 },
652 )));
653 }
654 Part::FunctionResponsePart(_) => {}
655 Part::ThoughtPart(part) => {
656 events.push(Ok(LanguageModelCompletionEvent::Thinking {
657 text: "(Encrypted thought)".to_string(), // TODO: Can we populate this from thought summaries?
658 signature: Some(part.thought_signature),
659 }));
660 }
661 });
662 }
663 }
664
665 // Even when Gemini wants to use a Tool, the API
666 // responds with `finish_reason: STOP`
667 if wants_to_use_tool {
668 self.stop_reason = StopReason::ToolUse;
669 events.push(Ok(LanguageModelCompletionEvent::Stop(StopReason::ToolUse)));
670 }
671 events
672 }
673}
674
675pub fn count_google_tokens(
676 request: LanguageModelRequest,
677 cx: &App,
678) -> BoxFuture<'static, Result<u64>> {
679 // We couldn't use the GoogleLanguageModelProvider to count tokens because the github copilot doesn't have the access to google_ai directly.
680 // So we have to use tokenizer from tiktoken_rs to count tokens.
681 cx.background_spawn(async move {
682 let messages = request
683 .messages
684 .into_iter()
685 .map(|message| tiktoken_rs::ChatCompletionRequestMessage {
686 role: match message.role {
687 Role::User => "user".into(),
688 Role::Assistant => "assistant".into(),
689 Role::System => "system".into(),
690 },
691 content: Some(message.string_contents()),
692 name: None,
693 function_call: None,
694 })
695 .collect::<Vec<_>>();
696
697 // Tiktoken doesn't yet support these models, so we manually use the
698 // same tokenizer as GPT-4.
699 tiktoken_rs::num_tokens_from_messages("gpt-4", &messages).map(|tokens| tokens as u64)
700 })
701 .boxed()
702}
703
704fn update_usage(usage: &mut UsageMetadata, new: &UsageMetadata) {
705 if let Some(prompt_token_count) = new.prompt_token_count {
706 usage.prompt_token_count = Some(prompt_token_count);
707 }
708 if let Some(cached_content_token_count) = new.cached_content_token_count {
709 usage.cached_content_token_count = Some(cached_content_token_count);
710 }
711 if let Some(candidates_token_count) = new.candidates_token_count {
712 usage.candidates_token_count = Some(candidates_token_count);
713 }
714 if let Some(tool_use_prompt_token_count) = new.tool_use_prompt_token_count {
715 usage.tool_use_prompt_token_count = Some(tool_use_prompt_token_count);
716 }
717 if let Some(thoughts_token_count) = new.thoughts_token_count {
718 usage.thoughts_token_count = Some(thoughts_token_count);
719 }
720 if let Some(total_token_count) = new.total_token_count {
721 usage.total_token_count = Some(total_token_count);
722 }
723}
724
725fn convert_usage(usage: &UsageMetadata) -> language_model::TokenUsage {
726 let prompt_tokens = usage.prompt_token_count.unwrap_or(0);
727 let cached_tokens = usage.cached_content_token_count.unwrap_or(0);
728 let input_tokens = prompt_tokens - cached_tokens;
729 let output_tokens = usage.candidates_token_count.unwrap_or(0);
730
731 language_model::TokenUsage {
732 input_tokens,
733 output_tokens,
734 cache_read_input_tokens: cached_tokens,
735 cache_creation_input_tokens: 0,
736 }
737}
738
739struct ConfigurationView {
740 api_key_editor: Entity<Editor>,
741 state: gpui::Entity<State>,
742 target_agent: language_model::ConfigurationViewTargetAgent,
743 load_credentials_task: Option<Task<()>>,
744}
745
746impl ConfigurationView {
747 fn new(
748 state: gpui::Entity<State>,
749 target_agent: language_model::ConfigurationViewTargetAgent,
750 window: &mut Window,
751 cx: &mut Context<Self>,
752 ) -> Self {
753 cx.observe(&state, |_, _, cx| {
754 cx.notify();
755 })
756 .detach();
757
758 let load_credentials_task = Some(cx.spawn_in(window, {
759 let state = state.clone();
760 async move |this, cx| {
761 if let Some(task) = state
762 .update(cx, |state, cx| state.authenticate(cx))
763 .log_err()
764 {
765 // We don't log an error, because "not signed in" is also an error.
766 let _ = task.await;
767 }
768 this.update(cx, |this, cx| {
769 this.load_credentials_task = None;
770 cx.notify();
771 })
772 .log_err();
773 }
774 }));
775
776 Self {
777 api_key_editor: cx.new(|cx| {
778 let mut editor = Editor::single_line(window, cx);
779 editor.set_placeholder_text("AIzaSy...", window, cx);
780 editor
781 }),
782 target_agent,
783 state,
784 load_credentials_task,
785 }
786 }
787
788 fn save_api_key(&mut self, _: &menu::Confirm, window: &mut Window, cx: &mut Context<Self>) {
789 let api_key = self.api_key_editor.read(cx).text(cx).trim().to_string();
790 if api_key.is_empty() {
791 return;
792 }
793
794 // url changes can cause the editor to be displayed again
795 self.api_key_editor
796 .update(cx, |editor, cx| editor.set_text("", window, cx));
797
798 let state = self.state.clone();
799 cx.spawn_in(window, async move |_, cx| {
800 state
801 .update(cx, |state, cx| state.set_api_key(Some(api_key), cx))?
802 .await
803 })
804 .detach_and_log_err(cx);
805 }
806
807 fn reset_api_key(&mut self, window: &mut Window, cx: &mut Context<Self>) {
808 self.api_key_editor
809 .update(cx, |editor, cx| editor.set_text("", window, cx));
810
811 let state = self.state.clone();
812 cx.spawn_in(window, async move |_, cx| {
813 state
814 .update(cx, |state, cx| state.set_api_key(None, cx))?
815 .await
816 })
817 .detach_and_log_err(cx);
818 }
819
820 fn render_api_key_editor(&self, cx: &mut Context<Self>) -> impl IntoElement {
821 let settings = ThemeSettings::get_global(cx);
822 let text_style = TextStyle {
823 color: cx.theme().colors().text,
824 font_family: settings.ui_font.family.clone(),
825 font_features: settings.ui_font.features.clone(),
826 font_fallbacks: settings.ui_font.fallbacks.clone(),
827 font_size: rems(0.875).into(),
828 font_weight: settings.ui_font.weight,
829 font_style: FontStyle::Normal,
830 line_height: relative(1.3),
831 white_space: WhiteSpace::Normal,
832 ..Default::default()
833 };
834 EditorElement::new(
835 &self.api_key_editor,
836 EditorStyle {
837 background: cx.theme().colors().editor_background,
838 local_player: cx.theme().players().local(),
839 text: text_style,
840 ..Default::default()
841 },
842 )
843 }
844
845 fn should_render_editor(&self, cx: &mut Context<Self>) -> bool {
846 !self.state.read(cx).is_authenticated()
847 }
848}
849
850impl Render for ConfigurationView {
851 fn render(&mut self, _: &mut Window, cx: &mut Context<Self>) -> impl IntoElement {
852 let env_var_set = self.state.read(cx).api_key_state.is_from_env_var();
853
854 if self.load_credentials_task.is_some() {
855 div().child(Label::new("Loading credentials...")).into_any()
856 } else if self.should_render_editor(cx) {
857 v_flex()
858 .size_full()
859 .on_action(cx.listener(Self::save_api_key))
860 .child(Label::new(format!("To use {}, you need to add an API key. Follow these steps:", match &self.target_agent {
861 ConfigurationViewTargetAgent::ZedAgent => "Zed's agent with Google AI".into(),
862 ConfigurationViewTargetAgent::Other(agent) => agent.clone(),
863 })))
864 .child(
865 List::new()
866 .child(InstructionListItem::new(
867 "Create one by visiting",
868 Some("Google AI's console"),
869 Some("https://aistudio.google.com/app/apikey"),
870 ))
871 .child(InstructionListItem::text_only(
872 "Paste your API key below and hit enter to start using the assistant",
873 )),
874 )
875 .child(
876 h_flex()
877 .w_full()
878 .my_2()
879 .px_2()
880 .py_1()
881 .bg(cx.theme().colors().editor_background)
882 .border_1()
883 .border_color(cx.theme().colors().border)
884 .rounded_sm()
885 .child(self.render_api_key_editor(cx)),
886 )
887 .child(
888 Label::new(
889 format!("You can also assign the {GEMINI_API_KEY_VAR_NAME} environment variable and restart Zed."),
890 )
891 .size(LabelSize::Small).color(Color::Muted),
892 )
893 .into_any()
894 } else {
895 h_flex()
896 .mt_1()
897 .p_1()
898 .justify_between()
899 .rounded_md()
900 .border_1()
901 .border_color(cx.theme().colors().border)
902 .bg(cx.theme().colors().background)
903 .child(
904 h_flex()
905 .gap_1()
906 .child(Icon::new(IconName::Check).color(Color::Success))
907 .child(Label::new(if env_var_set {
908 format!("API key set in {} environment variable", API_KEY_ENV_VAR.name)
909 } else {
910 let api_url = GoogleLanguageModelProvider::api_url(cx);
911 if api_url == google_ai::API_URL {
912 "API key configured".to_string()
913 } else {
914 format!("API key configured for {}", truncate_and_trailoff(&api_url, 32))
915 }
916 })),
917 )
918 .child(
919 Button::new("reset-key", "Reset Key")
920 .label_size(LabelSize::Small)
921 .icon(Some(IconName::Trash))
922 .icon_size(IconSize::Small)
923 .icon_position(IconPosition::Start)
924 .disabled(env_var_set)
925 .when(env_var_set, |this| {
926 this.tooltip(Tooltip::text(format!("To reset your API key, make sure {GEMINI_API_KEY_VAR_NAME} and {GOOGLE_AI_API_KEY_VAR_NAME} environment variables are unset.")))
927 })
928 .on_click(cx.listener(|this, _, window, cx| this.reset_api_key(window, cx))),
929 )
930 .into_any()
931 }
932 }
933}