1use anyhow::{Context as _, Result, anyhow};
2use collections::BTreeMap;
3use credentials_provider::CredentialsProvider;
4use editor::{Editor, EditorElement, EditorStyle};
5use futures::{FutureExt, Stream, StreamExt, future::BoxFuture};
6use google_ai::{
7 FunctionDeclaration, GenerateContentResponse, Part, SystemInstruction, UsageMetadata,
8};
9use gpui::{
10 AnyView, App, AsyncApp, Context, Entity, FontStyle, Subscription, Task, TextStyle, WhiteSpace,
11};
12use http_client::HttpClient;
13use language_model::{
14 AuthenticateError, LanguageModelCompletionError, LanguageModelCompletionEvent,
15 LanguageModelToolSchemaFormat, LanguageModelToolUse, LanguageModelToolUseId, MessageContent,
16 StopReason,
17};
18use language_model::{
19 LanguageModel, LanguageModelId, LanguageModelName, LanguageModelProvider,
20 LanguageModelProviderId, LanguageModelProviderName, LanguageModelProviderState,
21 LanguageModelRequest, RateLimiter, Role,
22};
23use schemars::JsonSchema;
24use serde::{Deserialize, Serialize};
25use settings::{Settings, SettingsStore};
26use std::pin::Pin;
27use std::sync::{
28 Arc,
29 atomic::{self, AtomicU64},
30};
31use strum::IntoEnumIterator;
32use theme::ThemeSettings;
33use ui::{Icon, IconName, List, Tooltip, prelude::*};
34use util::ResultExt;
35
36use crate::AllLanguageModelSettings;
37use crate::ui::InstructionListItem;
38
39const PROVIDER_ID: &str = "google";
40const PROVIDER_NAME: &str = "Google AI";
41
42#[derive(Default, Clone, Debug, PartialEq)]
43pub struct GoogleSettings {
44 pub api_url: String,
45 pub available_models: Vec<AvailableModel>,
46}
47
48#[derive(Clone, Debug, PartialEq, Serialize, Deserialize, JsonSchema)]
49pub struct AvailableModel {
50 name: String,
51 display_name: Option<String>,
52 max_tokens: usize,
53}
54
55pub struct GoogleLanguageModelProvider {
56 http_client: Arc<dyn HttpClient>,
57 state: gpui::Entity<State>,
58}
59
60pub struct State {
61 api_key: Option<String>,
62 api_key_from_env: bool,
63 _subscription: Subscription,
64}
65
66const GOOGLE_AI_API_KEY_VAR: &str = "GOOGLE_AI_API_KEY";
67
68impl State {
69 fn is_authenticated(&self) -> bool {
70 self.api_key.is_some()
71 }
72
73 fn reset_api_key(&self, cx: &mut Context<Self>) -> Task<Result<()>> {
74 let credentials_provider = <dyn CredentialsProvider>::global(cx);
75 let api_url = AllLanguageModelSettings::get_global(cx)
76 .google
77 .api_url
78 .clone();
79 cx.spawn(async move |this, cx| {
80 credentials_provider
81 .delete_credentials(&api_url, &cx)
82 .await
83 .log_err();
84 this.update(cx, |this, cx| {
85 this.api_key = None;
86 this.api_key_from_env = false;
87 cx.notify();
88 })
89 })
90 }
91
92 fn set_api_key(&mut self, api_key: String, cx: &mut Context<Self>) -> Task<Result<()>> {
93 let credentials_provider = <dyn CredentialsProvider>::global(cx);
94 let api_url = AllLanguageModelSettings::get_global(cx)
95 .google
96 .api_url
97 .clone();
98 cx.spawn(async move |this, cx| {
99 credentials_provider
100 .write_credentials(&api_url, "Bearer", api_key.as_bytes(), &cx)
101 .await?;
102 this.update(cx, |this, cx| {
103 this.api_key = Some(api_key);
104 cx.notify();
105 })
106 })
107 }
108
109 fn authenticate(&self, cx: &mut Context<Self>) -> Task<Result<(), AuthenticateError>> {
110 if self.is_authenticated() {
111 return Task::ready(Ok(()));
112 }
113
114 let credentials_provider = <dyn CredentialsProvider>::global(cx);
115 let api_url = AllLanguageModelSettings::get_global(cx)
116 .google
117 .api_url
118 .clone();
119
120 cx.spawn(async move |this, cx| {
121 let (api_key, from_env) = if let Ok(api_key) = std::env::var(GOOGLE_AI_API_KEY_VAR) {
122 (api_key, true)
123 } else {
124 let (_, api_key) = credentials_provider
125 .read_credentials(&api_url, &cx)
126 .await?
127 .ok_or(AuthenticateError::CredentialsNotFound)?;
128 (
129 String::from_utf8(api_key).context("invalid {PROVIDER_NAME} API key")?,
130 false,
131 )
132 };
133
134 this.update(cx, |this, cx| {
135 this.api_key = Some(api_key);
136 this.api_key_from_env = from_env;
137 cx.notify();
138 })?;
139
140 Ok(())
141 })
142 }
143}
144
145impl GoogleLanguageModelProvider {
146 pub fn new(http_client: Arc<dyn HttpClient>, cx: &mut App) -> Self {
147 let state = cx.new(|cx| State {
148 api_key: None,
149 api_key_from_env: false,
150 _subscription: cx.observe_global::<SettingsStore>(|_, cx| {
151 cx.notify();
152 }),
153 });
154
155 Self { http_client, state }
156 }
157
158 fn create_language_model(&self, model: google_ai::Model) -> Arc<dyn LanguageModel> {
159 Arc::new(GoogleLanguageModel {
160 id: LanguageModelId::from(model.id().to_string()),
161 model,
162 state: self.state.clone(),
163 http_client: self.http_client.clone(),
164 request_limiter: RateLimiter::new(4),
165 })
166 }
167}
168
169impl LanguageModelProviderState for GoogleLanguageModelProvider {
170 type ObservableEntity = State;
171
172 fn observable_entity(&self) -> Option<gpui::Entity<Self::ObservableEntity>> {
173 Some(self.state.clone())
174 }
175}
176
177impl LanguageModelProvider for GoogleLanguageModelProvider {
178 fn id(&self) -> LanguageModelProviderId {
179 LanguageModelProviderId(PROVIDER_ID.into())
180 }
181
182 fn name(&self) -> LanguageModelProviderName {
183 LanguageModelProviderName(PROVIDER_NAME.into())
184 }
185
186 fn icon(&self) -> IconName {
187 IconName::AiGoogle
188 }
189
190 fn default_model(&self, _cx: &App) -> Option<Arc<dyn LanguageModel>> {
191 Some(self.create_language_model(google_ai::Model::default()))
192 }
193
194 fn default_fast_model(&self, _cx: &App) -> Option<Arc<dyn LanguageModel>> {
195 Some(self.create_language_model(google_ai::Model::default_fast()))
196 }
197
198 fn provided_models(&self, cx: &App) -> Vec<Arc<dyn LanguageModel>> {
199 let mut models = BTreeMap::default();
200
201 // Add base models from google_ai::Model::iter()
202 for model in google_ai::Model::iter() {
203 if !matches!(model, google_ai::Model::Custom { .. }) {
204 models.insert(model.id().to_string(), model);
205 }
206 }
207
208 // Override with available models from settings
209 for model in &AllLanguageModelSettings::get_global(cx)
210 .google
211 .available_models
212 {
213 models.insert(
214 model.name.clone(),
215 google_ai::Model::Custom {
216 name: model.name.clone(),
217 display_name: model.display_name.clone(),
218 max_tokens: model.max_tokens,
219 },
220 );
221 }
222
223 models
224 .into_values()
225 .map(|model| {
226 Arc::new(GoogleLanguageModel {
227 id: LanguageModelId::from(model.id().to_string()),
228 model,
229 state: self.state.clone(),
230 http_client: self.http_client.clone(),
231 request_limiter: RateLimiter::new(4),
232 }) as Arc<dyn LanguageModel>
233 })
234 .collect()
235 }
236
237 fn is_authenticated(&self, cx: &App) -> bool {
238 self.state.read(cx).is_authenticated()
239 }
240
241 fn authenticate(&self, cx: &mut App) -> Task<Result<(), AuthenticateError>> {
242 self.state.update(cx, |state, cx| state.authenticate(cx))
243 }
244
245 fn configuration_view(&self, window: &mut Window, cx: &mut App) -> AnyView {
246 cx.new(|cx| ConfigurationView::new(self.state.clone(), window, cx))
247 .into()
248 }
249
250 fn reset_credentials(&self, cx: &mut App) -> Task<Result<()>> {
251 self.state.update(cx, |state, cx| state.reset_api_key(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)) = cx.read_entity(&self.state, |state, cx| {
275 let settings = &AllLanguageModelSettings::get_global(cx).google;
276 (state.api_key.clone(), settings.api_url.clone())
277 }) else {
278 return futures::future::ready(Err(anyhow!("App state dropped"))).boxed();
279 };
280
281 async move {
282 let api_key = api_key.ok_or_else(|| anyhow!("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 LanguageModelProviderId(PROVIDER_ID.into())
306 }
307
308 fn provider_name(&self) -> LanguageModelProviderName {
309 LanguageModelProviderName(PROVIDER_NAME.into())
310 }
311
312 fn supports_tools(&self) -> bool {
313 true
314 }
315
316 fn tool_input_format(&self) -> LanguageModelToolSchemaFormat {
317 LanguageModelToolSchemaFormat::JsonSchemaSubset
318 }
319
320 fn telemetry_id(&self) -> String {
321 format!("google/{}", self.model.id())
322 }
323
324 fn max_token_count(&self) -> usize {
325 self.model.max_token_count()
326 }
327
328 fn count_tokens(
329 &self,
330 request: LanguageModelRequest,
331 cx: &App,
332 ) -> BoxFuture<'static, Result<usize>> {
333 let model_id = self.model.id().to_string();
334 let request = into_google(request, model_id.clone());
335 let http_client = self.http_client.clone();
336 let api_key = self.state.read(cx).api_key.clone();
337
338 let settings = &AllLanguageModelSettings::get_global(cx).google;
339 let api_url = settings.api_url.clone();
340
341 async move {
342 let api_key = api_key.ok_or_else(|| anyhow!("Missing Google API key"))?;
343 let response = google_ai::count_tokens(
344 http_client.as_ref(),
345 &api_url,
346 &api_key,
347 google_ai::CountTokensRequest {
348 generate_content_request: request,
349 },
350 )
351 .await?;
352 Ok(response.total_tokens)
353 }
354 .boxed()
355 }
356
357 fn stream_completion(
358 &self,
359 request: LanguageModelRequest,
360 cx: &AsyncApp,
361 ) -> BoxFuture<
362 'static,
363 Result<
364 futures::stream::BoxStream<
365 'static,
366 Result<LanguageModelCompletionEvent, LanguageModelCompletionError>,
367 >,
368 >,
369 > {
370 let request = into_google(request, self.model.id().to_string());
371 let request = self.stream_completion(request, cx);
372 let future = self.request_limiter.stream(async move {
373 let response = request
374 .await
375 .map_err(|err| LanguageModelCompletionError::Other(anyhow!(err)))?;
376 Ok(GoogleEventMapper::new().map_stream(response))
377 });
378 async move { Ok(future.await?.boxed()) }.boxed()
379 }
380}
381
382pub fn into_google(
383 mut request: LanguageModelRequest,
384 model_id: String,
385) -> google_ai::GenerateContentRequest {
386 fn map_content(content: Vec<MessageContent>) -> Vec<Part> {
387 content
388 .into_iter()
389 .filter_map(|content| match content {
390 language_model::MessageContent::Text(text)
391 | language_model::MessageContent::Thinking { text, .. } => {
392 if !text.is_empty() {
393 Some(Part::TextPart(google_ai::TextPart { text }))
394 } else {
395 None
396 }
397 }
398 language_model::MessageContent::RedactedThinking(_) => None,
399 language_model::MessageContent::Image(image) => {
400 Some(Part::InlineDataPart(google_ai::InlineDataPart {
401 inline_data: google_ai::GenerativeContentBlob {
402 mime_type: "image/png".to_string(),
403 data: image.source.to_string(),
404 },
405 }))
406 }
407 language_model::MessageContent::ToolUse(tool_use) => {
408 Some(Part::FunctionCallPart(google_ai::FunctionCallPart {
409 function_call: google_ai::FunctionCall {
410 name: tool_use.name.to_string(),
411 args: tool_use.input,
412 },
413 }))
414 }
415 language_model::MessageContent::ToolResult(tool_result) => Some(
416 Part::FunctionResponsePart(google_ai::FunctionResponsePart {
417 function_response: google_ai::FunctionResponse {
418 name: tool_result.tool_name.to_string(),
419 // The API expects a valid JSON object
420 response: serde_json::json!({
421 "output": tool_result.content
422 }),
423 },
424 }),
425 ),
426 })
427 .collect()
428 }
429
430 let system_instructions = if request
431 .messages
432 .first()
433 .map_or(false, |msg| matches!(msg.role, Role::System))
434 {
435 let message = request.messages.remove(0);
436 Some(SystemInstruction {
437 parts: map_content(message.content),
438 })
439 } else {
440 None
441 };
442
443 google_ai::GenerateContentRequest {
444 model: google_ai::ModelName { model_id },
445 system_instruction: system_instructions,
446 contents: request
447 .messages
448 .into_iter()
449 .filter_map(|message| {
450 let parts = map_content(message.content);
451 if parts.is_empty() {
452 None
453 } else {
454 Some(google_ai::Content {
455 parts,
456 role: match message.role {
457 Role::User => google_ai::Role::User,
458 Role::Assistant => google_ai::Role::Model,
459 Role::System => google_ai::Role::User, // Google AI doesn't have a system role
460 },
461 })
462 }
463 })
464 .collect(),
465 generation_config: Some(google_ai::GenerationConfig {
466 candidate_count: Some(1),
467 stop_sequences: Some(request.stop),
468 max_output_tokens: None,
469 temperature: request.temperature.map(|t| t as f64).or(Some(1.0)),
470 top_p: None,
471 top_k: None,
472 }),
473 safety_settings: None,
474 tools: (request.tools.len() > 0).then(|| {
475 vec![google_ai::Tool {
476 function_declarations: request
477 .tools
478 .into_iter()
479 .map(|tool| FunctionDeclaration {
480 name: tool.name,
481 description: tool.description,
482 parameters: tool.input_schema,
483 })
484 .collect(),
485 }]
486 }),
487 tool_config: None,
488 }
489}
490
491pub struct GoogleEventMapper {
492 usage: UsageMetadata,
493 stop_reason: StopReason,
494}
495
496impl GoogleEventMapper {
497 pub fn new() -> Self {
498 Self {
499 usage: UsageMetadata::default(),
500 stop_reason: StopReason::EndTurn,
501 }
502 }
503
504 pub fn map_stream(
505 mut self,
506 events: Pin<Box<dyn Send + Stream<Item = Result<GenerateContentResponse>>>>,
507 ) -> impl Stream<Item = Result<LanguageModelCompletionEvent, LanguageModelCompletionError>>
508 {
509 events
510 .map(Some)
511 .chain(futures::stream::once(async { None }))
512 .flat_map(move |event| {
513 futures::stream::iter(match event {
514 Some(Ok(event)) => self.map_event(event),
515 Some(Err(error)) => {
516 vec![Err(LanguageModelCompletionError::Other(anyhow!(error)))]
517 }
518 None => vec![Ok(LanguageModelCompletionEvent::Stop(self.stop_reason))],
519 })
520 })
521 }
522
523 pub fn map_event(
524 &mut self,
525 event: GenerateContentResponse,
526 ) -> Vec<Result<LanguageModelCompletionEvent, LanguageModelCompletionError>> {
527 static TOOL_CALL_COUNTER: AtomicU64 = AtomicU64::new(0);
528
529 let mut events: Vec<_> = Vec::new();
530 let mut wants_to_use_tool = false;
531 if let Some(usage_metadata) = event.usage_metadata {
532 update_usage(&mut self.usage, &usage_metadata);
533 events.push(Ok(LanguageModelCompletionEvent::UsageUpdate(
534 convert_usage(&self.usage),
535 )))
536 }
537 if let Some(candidates) = event.candidates {
538 for candidate in candidates {
539 if let Some(finish_reason) = candidate.finish_reason.as_deref() {
540 self.stop_reason = match finish_reason {
541 "STOP" => StopReason::EndTurn,
542 "MAX_TOKENS" => StopReason::MaxTokens,
543 _ => {
544 log::error!("Unexpected google finish_reason: {finish_reason}");
545 StopReason::EndTurn
546 }
547 };
548 }
549 candidate
550 .content
551 .parts
552 .into_iter()
553 .for_each(|part| match part {
554 Part::TextPart(text_part) => {
555 events.push(Ok(LanguageModelCompletionEvent::Text(text_part.text)))
556 }
557 Part::InlineDataPart(_) => {}
558 Part::FunctionCallPart(function_call_part) => {
559 wants_to_use_tool = true;
560 let name: Arc<str> = function_call_part.function_call.name.into();
561 let next_tool_id =
562 TOOL_CALL_COUNTER.fetch_add(1, atomic::Ordering::SeqCst);
563 let id: LanguageModelToolUseId =
564 format!("{}-{}", name, next_tool_id).into();
565
566 events.push(Ok(LanguageModelCompletionEvent::ToolUse(
567 LanguageModelToolUse {
568 id,
569 name,
570 is_input_complete: true,
571 raw_input: function_call_part.function_call.args.to_string(),
572 input: function_call_part.function_call.args,
573 },
574 )));
575 }
576 Part::FunctionResponsePart(_) => {}
577 });
578 }
579 }
580
581 // Even when Gemini wants to use a Tool, the API
582 // responds with `finish_reason: STOP`
583 if wants_to_use_tool {
584 self.stop_reason = StopReason::ToolUse;
585 }
586 events
587 }
588}
589
590pub fn count_google_tokens(
591 request: LanguageModelRequest,
592 cx: &App,
593) -> BoxFuture<'static, Result<usize>> {
594 // We couldn't use the GoogleLanguageModelProvider to count tokens because the github copilot doesn't have the access to google_ai directly.
595 // So we have to use tokenizer from tiktoken_rs to count tokens.
596 cx.background_spawn(async move {
597 let messages = request
598 .messages
599 .into_iter()
600 .map(|message| tiktoken_rs::ChatCompletionRequestMessage {
601 role: match message.role {
602 Role::User => "user".into(),
603 Role::Assistant => "assistant".into(),
604 Role::System => "system".into(),
605 },
606 content: Some(message.string_contents()),
607 name: None,
608 function_call: None,
609 })
610 .collect::<Vec<_>>();
611
612 // Tiktoken doesn't yet support these models, so we manually use the
613 // same tokenizer as GPT-4.
614 tiktoken_rs::num_tokens_from_messages("gpt-4", &messages)
615 })
616 .boxed()
617}
618
619fn update_usage(usage: &mut UsageMetadata, new: &UsageMetadata) {
620 if let Some(prompt_token_count) = new.prompt_token_count {
621 usage.prompt_token_count = Some(prompt_token_count);
622 }
623 if let Some(cached_content_token_count) = new.cached_content_token_count {
624 usage.cached_content_token_count = Some(cached_content_token_count);
625 }
626 if let Some(candidates_token_count) = new.candidates_token_count {
627 usage.candidates_token_count = Some(candidates_token_count);
628 }
629 if let Some(tool_use_prompt_token_count) = new.tool_use_prompt_token_count {
630 usage.tool_use_prompt_token_count = Some(tool_use_prompt_token_count);
631 }
632 if let Some(thoughts_token_count) = new.thoughts_token_count {
633 usage.thoughts_token_count = Some(thoughts_token_count);
634 }
635 if let Some(total_token_count) = new.total_token_count {
636 usage.total_token_count = Some(total_token_count);
637 }
638}
639
640fn convert_usage(usage: &UsageMetadata) -> language_model::TokenUsage {
641 language_model::TokenUsage {
642 input_tokens: usage.prompt_token_count.unwrap_or(0) as u32,
643 output_tokens: usage.candidates_token_count.unwrap_or(0) as u32,
644 cache_read_input_tokens: usage.cached_content_token_count.unwrap_or(0) as u32,
645 cache_creation_input_tokens: 0,
646 }
647}
648
649struct ConfigurationView {
650 api_key_editor: Entity<Editor>,
651 state: gpui::Entity<State>,
652 load_credentials_task: Option<Task<()>>,
653}
654
655impl ConfigurationView {
656 fn new(state: gpui::Entity<State>, window: &mut Window, cx: &mut Context<Self>) -> Self {
657 cx.observe(&state, |_, _, cx| {
658 cx.notify();
659 })
660 .detach();
661
662 let load_credentials_task = Some(cx.spawn_in(window, {
663 let state = state.clone();
664 async move |this, cx| {
665 if let Some(task) = state
666 .update(cx, |state, cx| state.authenticate(cx))
667 .log_err()
668 {
669 // We don't log an error, because "not signed in" is also an error.
670 let _ = task.await;
671 }
672 this.update(cx, |this, cx| {
673 this.load_credentials_task = None;
674 cx.notify();
675 })
676 .log_err();
677 }
678 }));
679
680 Self {
681 api_key_editor: cx.new(|cx| {
682 let mut editor = Editor::single_line(window, cx);
683 editor.set_placeholder_text("AIzaSy...", cx);
684 editor
685 }),
686 state,
687 load_credentials_task,
688 }
689 }
690
691 fn save_api_key(&mut self, _: &menu::Confirm, window: &mut Window, cx: &mut Context<Self>) {
692 let api_key = self.api_key_editor.read(cx).text(cx);
693 if api_key.is_empty() {
694 return;
695 }
696
697 let state = self.state.clone();
698 cx.spawn_in(window, async move |_, cx| {
699 state
700 .update(cx, |state, cx| state.set_api_key(api_key, cx))?
701 .await
702 })
703 .detach_and_log_err(cx);
704
705 cx.notify();
706 }
707
708 fn reset_api_key(&mut self, window: &mut Window, cx: &mut Context<Self>) {
709 self.api_key_editor
710 .update(cx, |editor, cx| editor.set_text("", window, cx));
711
712 let state = self.state.clone();
713 cx.spawn_in(window, async move |_, cx| {
714 state.update(cx, |state, cx| state.reset_api_key(cx))?.await
715 })
716 .detach_and_log_err(cx);
717
718 cx.notify();
719 }
720
721 fn render_api_key_editor(&self, cx: &mut Context<Self>) -> impl IntoElement {
722 let settings = ThemeSettings::get_global(cx);
723 let text_style = TextStyle {
724 color: cx.theme().colors().text,
725 font_family: settings.ui_font.family.clone(),
726 font_features: settings.ui_font.features.clone(),
727 font_fallbacks: settings.ui_font.fallbacks.clone(),
728 font_size: rems(0.875).into(),
729 font_weight: settings.ui_font.weight,
730 font_style: FontStyle::Normal,
731 line_height: relative(1.3),
732 white_space: WhiteSpace::Normal,
733 ..Default::default()
734 };
735 EditorElement::new(
736 &self.api_key_editor,
737 EditorStyle {
738 background: cx.theme().colors().editor_background,
739 local_player: cx.theme().players().local(),
740 text: text_style,
741 ..Default::default()
742 },
743 )
744 }
745
746 fn should_render_editor(&self, cx: &mut Context<Self>) -> bool {
747 !self.state.read(cx).is_authenticated()
748 }
749}
750
751impl Render for ConfigurationView {
752 fn render(&mut self, _: &mut Window, cx: &mut Context<Self>) -> impl IntoElement {
753 let env_var_set = self.state.read(cx).api_key_from_env;
754
755 if self.load_credentials_task.is_some() {
756 div().child(Label::new("Loading credentials...")).into_any()
757 } else if self.should_render_editor(cx) {
758 v_flex()
759 .size_full()
760 .on_action(cx.listener(Self::save_api_key))
761 .child(Label::new("To use Zed's assistant with Google AI, you need to add an API key. Follow these steps:"))
762 .child(
763 List::new()
764 .child(InstructionListItem::new(
765 "Create one by visiting",
766 Some("Google AI's console"),
767 Some("https://aistudio.google.com/app/apikey"),
768 ))
769 .child(InstructionListItem::text_only(
770 "Paste your API key below and hit enter to start using the assistant",
771 )),
772 )
773 .child(
774 h_flex()
775 .w_full()
776 .my_2()
777 .px_2()
778 .py_1()
779 .bg(cx.theme().colors().editor_background)
780 .border_1()
781 .border_color(cx.theme().colors().border)
782 .rounded_sm()
783 .child(self.render_api_key_editor(cx)),
784 )
785 .child(
786 Label::new(
787 format!("You can also assign the {GOOGLE_AI_API_KEY_VAR} environment variable and restart Zed."),
788 )
789 .size(LabelSize::Small).color(Color::Muted),
790 )
791 .into_any()
792 } else {
793 h_flex()
794 .mt_1()
795 .p_1()
796 .justify_between()
797 .rounded_md()
798 .border_1()
799 .border_color(cx.theme().colors().border)
800 .bg(cx.theme().colors().background)
801 .child(
802 h_flex()
803 .gap_1()
804 .child(Icon::new(IconName::Check).color(Color::Success))
805 .child(Label::new(if env_var_set {
806 format!("API key set in {GOOGLE_AI_API_KEY_VAR} environment variable.")
807 } else {
808 "API key configured.".to_string()
809 })),
810 )
811 .child(
812 Button::new("reset-key", "Reset Key")
813 .label_size(LabelSize::Small)
814 .icon(Some(IconName::Trash))
815 .icon_size(IconSize::Small)
816 .icon_position(IconPosition::Start)
817 .disabled(env_var_set)
818 .when(env_var_set, |this| {
819 this.tooltip(Tooltip::text(format!("To reset your API key, unset the {GOOGLE_AI_API_KEY_VAR} environment variable.")))
820 })
821 .on_click(cx.listener(|this, _, window, cx| this.reset_api_key(window, cx))),
822 )
823 .into_any()
824 }
825 }
826}