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 LanguageModelToolChoice, LanguageModelToolSchemaFormat, LanguageModelToolUse,
16 LanguageModelToolUseId, MessageContent, 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 supports_tool_choice(&self, choice: LanguageModelToolChoice) -> bool {
317 match choice {
318 LanguageModelToolChoice::Auto
319 | LanguageModelToolChoice::Any
320 | LanguageModelToolChoice::None => true,
321 }
322 }
323
324 fn tool_input_format(&self) -> LanguageModelToolSchemaFormat {
325 LanguageModelToolSchemaFormat::JsonSchemaSubset
326 }
327
328 fn telemetry_id(&self) -> String {
329 format!("google/{}", self.model.id())
330 }
331
332 fn max_token_count(&self) -> usize {
333 self.model.max_token_count()
334 }
335
336 fn count_tokens(
337 &self,
338 request: LanguageModelRequest,
339 cx: &App,
340 ) -> BoxFuture<'static, Result<usize>> {
341 let model_id = self.model.id().to_string();
342 let request = into_google(request, model_id.clone());
343 let http_client = self.http_client.clone();
344 let api_key = self.state.read(cx).api_key.clone();
345
346 let settings = &AllLanguageModelSettings::get_global(cx).google;
347 let api_url = settings.api_url.clone();
348
349 async move {
350 let api_key = api_key.ok_or_else(|| anyhow!("Missing Google API key"))?;
351 let response = google_ai::count_tokens(
352 http_client.as_ref(),
353 &api_url,
354 &api_key,
355 &model_id,
356 google_ai::CountTokensRequest {
357 contents: request.contents,
358 },
359 )
360 .await?;
361 Ok(response.total_tokens)
362 }
363 .boxed()
364 }
365
366 fn stream_completion(
367 &self,
368 request: LanguageModelRequest,
369 cx: &AsyncApp,
370 ) -> BoxFuture<
371 'static,
372 Result<
373 futures::stream::BoxStream<
374 'static,
375 Result<LanguageModelCompletionEvent, LanguageModelCompletionError>,
376 >,
377 >,
378 > {
379 let request = into_google(request, self.model.id().to_string());
380 let request = self.stream_completion(request, cx);
381 let future = self.request_limiter.stream(async move {
382 let response = request
383 .await
384 .map_err(|err| LanguageModelCompletionError::Other(anyhow!(err)))?;
385 Ok(GoogleEventMapper::new().map_stream(response))
386 });
387 async move { Ok(future.await?.boxed()) }.boxed()
388 }
389}
390
391pub fn into_google(
392 mut request: LanguageModelRequest,
393 model: String,
394) -> google_ai::GenerateContentRequest {
395 fn map_content(content: Vec<MessageContent>) -> Vec<Part> {
396 content
397 .into_iter()
398 .filter_map(|content| match content {
399 language_model::MessageContent::Text(text)
400 | language_model::MessageContent::Thinking { text, .. } => {
401 if !text.is_empty() {
402 Some(Part::TextPart(google_ai::TextPart { text }))
403 } else {
404 None
405 }
406 }
407 language_model::MessageContent::RedactedThinking(_) => None,
408 language_model::MessageContent::Image(image) => {
409 Some(Part::InlineDataPart(google_ai::InlineDataPart {
410 inline_data: google_ai::GenerativeContentBlob {
411 mime_type: "image/png".to_string(),
412 data: image.source.to_string(),
413 },
414 }))
415 }
416 language_model::MessageContent::ToolUse(tool_use) => {
417 Some(Part::FunctionCallPart(google_ai::FunctionCallPart {
418 function_call: google_ai::FunctionCall {
419 name: tool_use.name.to_string(),
420 args: tool_use.input,
421 },
422 }))
423 }
424 language_model::MessageContent::ToolResult(tool_result) => Some(
425 Part::FunctionResponsePart(google_ai::FunctionResponsePart {
426 function_response: google_ai::FunctionResponse {
427 name: tool_result.tool_name.to_string(),
428 // The API expects a valid JSON object
429 response: serde_json::json!({
430 "output": tool_result.content
431 }),
432 },
433 }),
434 ),
435 })
436 .collect()
437 }
438
439 let system_instructions = if request
440 .messages
441 .first()
442 .map_or(false, |msg| matches!(msg.role, Role::System))
443 {
444 let message = request.messages.remove(0);
445 Some(SystemInstruction {
446 parts: map_content(message.content),
447 })
448 } else {
449 None
450 };
451
452 google_ai::GenerateContentRequest {
453 model,
454 system_instruction: system_instructions,
455 contents: request
456 .messages
457 .into_iter()
458 .filter_map(|message| {
459 let parts = map_content(message.content);
460 if parts.is_empty() {
461 None
462 } else {
463 Some(google_ai::Content {
464 parts,
465 role: match message.role {
466 Role::User => google_ai::Role::User,
467 Role::Assistant => google_ai::Role::Model,
468 Role::System => google_ai::Role::User, // Google AI doesn't have a system role
469 },
470 })
471 }
472 })
473 .collect(),
474 generation_config: Some(google_ai::GenerationConfig {
475 candidate_count: Some(1),
476 stop_sequences: Some(request.stop),
477 max_output_tokens: None,
478 temperature: request.temperature.map(|t| t as f64).or(Some(1.0)),
479 top_p: None,
480 top_k: None,
481 }),
482 safety_settings: None,
483 tools: (request.tools.len() > 0).then(|| {
484 vec![google_ai::Tool {
485 function_declarations: request
486 .tools
487 .into_iter()
488 .map(|tool| FunctionDeclaration {
489 name: tool.name,
490 description: tool.description,
491 parameters: tool.input_schema,
492 })
493 .collect(),
494 }]
495 }),
496 tool_config: request.tool_choice.map(|choice| google_ai::ToolConfig {
497 function_calling_config: google_ai::FunctionCallingConfig {
498 mode: match choice {
499 LanguageModelToolChoice::Auto => google_ai::FunctionCallingMode::Auto,
500 LanguageModelToolChoice::Any => google_ai::FunctionCallingMode::Any,
501 LanguageModelToolChoice::None => google_ai::FunctionCallingMode::None,
502 },
503 allowed_function_names: None,
504 },
505 }),
506 }
507}
508
509pub struct GoogleEventMapper {
510 usage: UsageMetadata,
511 stop_reason: StopReason,
512}
513
514impl GoogleEventMapper {
515 pub fn new() -> Self {
516 Self {
517 usage: UsageMetadata::default(),
518 stop_reason: StopReason::EndTurn,
519 }
520 }
521
522 pub fn map_stream(
523 mut self,
524 events: Pin<Box<dyn Send + Stream<Item = Result<GenerateContentResponse>>>>,
525 ) -> impl Stream<Item = Result<LanguageModelCompletionEvent, LanguageModelCompletionError>>
526 {
527 events.flat_map(move |event| {
528 futures::stream::iter(match event {
529 Ok(event) => self.map_event(event),
530 Err(error) => vec![Err(LanguageModelCompletionError::Other(anyhow!(error)))],
531 })
532 })
533 }
534
535 pub fn map_event(
536 &mut self,
537 event: GenerateContentResponse,
538 ) -> Vec<Result<LanguageModelCompletionEvent, LanguageModelCompletionError>> {
539 static TOOL_CALL_COUNTER: AtomicU64 = AtomicU64::new(0);
540
541 let mut events: Vec<_> = Vec::new();
542 let mut wants_to_use_tool = false;
543 if let Some(usage_metadata) = event.usage_metadata {
544 update_usage(&mut self.usage, &usage_metadata);
545 events.push(Ok(LanguageModelCompletionEvent::UsageUpdate(
546 convert_usage(&self.usage),
547 )))
548 }
549 if let Some(candidates) = event.candidates {
550 for candidate in candidates {
551 if let Some(finish_reason) = candidate.finish_reason.as_deref() {
552 self.stop_reason = match finish_reason {
553 "STOP" => StopReason::EndTurn,
554 "MAX_TOKENS" => StopReason::MaxTokens,
555 _ => {
556 log::error!("Unexpected google finish_reason: {finish_reason}");
557 StopReason::EndTurn
558 }
559 };
560 }
561 candidate
562 .content
563 .parts
564 .into_iter()
565 .for_each(|part| match part {
566 Part::TextPart(text_part) => {
567 events.push(Ok(LanguageModelCompletionEvent::Text(text_part.text)))
568 }
569 Part::InlineDataPart(_) => {}
570 Part::FunctionCallPart(function_call_part) => {
571 wants_to_use_tool = true;
572 let name: Arc<str> = function_call_part.function_call.name.into();
573 let next_tool_id =
574 TOOL_CALL_COUNTER.fetch_add(1, atomic::Ordering::SeqCst);
575 let id: LanguageModelToolUseId =
576 format!("{}-{}", name, next_tool_id).into();
577
578 events.push(Ok(LanguageModelCompletionEvent::ToolUse(
579 LanguageModelToolUse {
580 id,
581 name,
582 is_input_complete: true,
583 raw_input: function_call_part.function_call.args.to_string(),
584 input: function_call_part.function_call.args,
585 },
586 )));
587 }
588 Part::FunctionResponsePart(_) => {}
589 });
590 }
591 }
592
593 // Even when Gemini wants to use a Tool, the API
594 // responds with `finish_reason: STOP`
595 if wants_to_use_tool {
596 self.stop_reason = StopReason::ToolUse;
597 }
598 events.push(Ok(LanguageModelCompletionEvent::Stop(self.stop_reason)));
599 events
600 }
601}
602
603pub fn count_google_tokens(
604 request: LanguageModelRequest,
605 cx: &App,
606) -> BoxFuture<'static, Result<usize>> {
607 // We couldn't use the GoogleLanguageModelProvider to count tokens because the github copilot doesn't have the access to google_ai directly.
608 // So we have to use tokenizer from tiktoken_rs to count tokens.
609 cx.background_spawn(async move {
610 let messages = request
611 .messages
612 .into_iter()
613 .map(|message| tiktoken_rs::ChatCompletionRequestMessage {
614 role: match message.role {
615 Role::User => "user".into(),
616 Role::Assistant => "assistant".into(),
617 Role::System => "system".into(),
618 },
619 content: Some(message.string_contents()),
620 name: None,
621 function_call: None,
622 })
623 .collect::<Vec<_>>();
624
625 // Tiktoken doesn't yet support these models, so we manually use the
626 // same tokenizer as GPT-4.
627 tiktoken_rs::num_tokens_from_messages("gpt-4", &messages)
628 })
629 .boxed()
630}
631
632fn update_usage(usage: &mut UsageMetadata, new: &UsageMetadata) {
633 if let Some(prompt_token_count) = new.prompt_token_count {
634 usage.prompt_token_count = Some(prompt_token_count);
635 }
636 if let Some(cached_content_token_count) = new.cached_content_token_count {
637 usage.cached_content_token_count = Some(cached_content_token_count);
638 }
639 if let Some(candidates_token_count) = new.candidates_token_count {
640 usage.candidates_token_count = Some(candidates_token_count);
641 }
642 if let Some(tool_use_prompt_token_count) = new.tool_use_prompt_token_count {
643 usage.tool_use_prompt_token_count = Some(tool_use_prompt_token_count);
644 }
645 if let Some(thoughts_token_count) = new.thoughts_token_count {
646 usage.thoughts_token_count = Some(thoughts_token_count);
647 }
648 if let Some(total_token_count) = new.total_token_count {
649 usage.total_token_count = Some(total_token_count);
650 }
651}
652
653fn convert_usage(usage: &UsageMetadata) -> language_model::TokenUsage {
654 language_model::TokenUsage {
655 input_tokens: usage.prompt_token_count.unwrap_or(0) as u32,
656 output_tokens: usage.candidates_token_count.unwrap_or(0) as u32,
657 cache_read_input_tokens: usage.cached_content_token_count.unwrap_or(0) as u32,
658 cache_creation_input_tokens: 0,
659 }
660}
661
662struct ConfigurationView {
663 api_key_editor: Entity<Editor>,
664 state: gpui::Entity<State>,
665 load_credentials_task: Option<Task<()>>,
666}
667
668impl ConfigurationView {
669 fn new(state: gpui::Entity<State>, window: &mut Window, cx: &mut Context<Self>) -> Self {
670 cx.observe(&state, |_, _, cx| {
671 cx.notify();
672 })
673 .detach();
674
675 let load_credentials_task = Some(cx.spawn_in(window, {
676 let state = state.clone();
677 async move |this, cx| {
678 if let Some(task) = state
679 .update(cx, |state, cx| state.authenticate(cx))
680 .log_err()
681 {
682 // We don't log an error, because "not signed in" is also an error.
683 let _ = task.await;
684 }
685 this.update(cx, |this, cx| {
686 this.load_credentials_task = None;
687 cx.notify();
688 })
689 .log_err();
690 }
691 }));
692
693 Self {
694 api_key_editor: cx.new(|cx| {
695 let mut editor = Editor::single_line(window, cx);
696 editor.set_placeholder_text("AIzaSy...", cx);
697 editor
698 }),
699 state,
700 load_credentials_task,
701 }
702 }
703
704 fn save_api_key(&mut self, _: &menu::Confirm, window: &mut Window, cx: &mut Context<Self>) {
705 let api_key = self.api_key_editor.read(cx).text(cx);
706 if api_key.is_empty() {
707 return;
708 }
709
710 let state = self.state.clone();
711 cx.spawn_in(window, async move |_, cx| {
712 state
713 .update(cx, |state, cx| state.set_api_key(api_key, cx))?
714 .await
715 })
716 .detach_and_log_err(cx);
717
718 cx.notify();
719 }
720
721 fn reset_api_key(&mut self, window: &mut Window, cx: &mut Context<Self>) {
722 self.api_key_editor
723 .update(cx, |editor, cx| editor.set_text("", window, cx));
724
725 let state = self.state.clone();
726 cx.spawn_in(window, async move |_, cx| {
727 state.update(cx, |state, cx| state.reset_api_key(cx))?.await
728 })
729 .detach_and_log_err(cx);
730
731 cx.notify();
732 }
733
734 fn render_api_key_editor(&self, cx: &mut Context<Self>) -> impl IntoElement {
735 let settings = ThemeSettings::get_global(cx);
736 let text_style = TextStyle {
737 color: cx.theme().colors().text,
738 font_family: settings.ui_font.family.clone(),
739 font_features: settings.ui_font.features.clone(),
740 font_fallbacks: settings.ui_font.fallbacks.clone(),
741 font_size: rems(0.875).into(),
742 font_weight: settings.ui_font.weight,
743 font_style: FontStyle::Normal,
744 line_height: relative(1.3),
745 white_space: WhiteSpace::Normal,
746 ..Default::default()
747 };
748 EditorElement::new(
749 &self.api_key_editor,
750 EditorStyle {
751 background: cx.theme().colors().editor_background,
752 local_player: cx.theme().players().local(),
753 text: text_style,
754 ..Default::default()
755 },
756 )
757 }
758
759 fn should_render_editor(&self, cx: &mut Context<Self>) -> bool {
760 !self.state.read(cx).is_authenticated()
761 }
762}
763
764impl Render for ConfigurationView {
765 fn render(&mut self, _: &mut Window, cx: &mut Context<Self>) -> impl IntoElement {
766 let env_var_set = self.state.read(cx).api_key_from_env;
767
768 if self.load_credentials_task.is_some() {
769 div().child(Label::new("Loading credentials...")).into_any()
770 } else if self.should_render_editor(cx) {
771 v_flex()
772 .size_full()
773 .on_action(cx.listener(Self::save_api_key))
774 .child(Label::new("To use Zed's assistant with Google AI, you need to add an API key. Follow these steps:"))
775 .child(
776 List::new()
777 .child(InstructionListItem::new(
778 "Create one by visiting",
779 Some("Google AI's console"),
780 Some("https://aistudio.google.com/app/apikey"),
781 ))
782 .child(InstructionListItem::text_only(
783 "Paste your API key below and hit enter to start using the assistant",
784 )),
785 )
786 .child(
787 h_flex()
788 .w_full()
789 .my_2()
790 .px_2()
791 .py_1()
792 .bg(cx.theme().colors().editor_background)
793 .border_1()
794 .border_color(cx.theme().colors().border)
795 .rounded_sm()
796 .child(self.render_api_key_editor(cx)),
797 )
798 .child(
799 Label::new(
800 format!("You can also assign the {GOOGLE_AI_API_KEY_VAR} environment variable and restart Zed."),
801 )
802 .size(LabelSize::Small).color(Color::Muted),
803 )
804 .into_any()
805 } else {
806 h_flex()
807 .mt_1()
808 .p_1()
809 .justify_between()
810 .rounded_md()
811 .border_1()
812 .border_color(cx.theme().colors().border)
813 .bg(cx.theme().colors().background)
814 .child(
815 h_flex()
816 .gap_1()
817 .child(Icon::new(IconName::Check).color(Color::Success))
818 .child(Label::new(if env_var_set {
819 format!("API key set in {GOOGLE_AI_API_KEY_VAR} environment variable.")
820 } else {
821 "API key configured.".to_string()
822 })),
823 )
824 .child(
825 Button::new("reset-key", "Reset Key")
826 .label_size(LabelSize::Small)
827 .icon(Some(IconName::Trash))
828 .icon_size(IconSize::Small)
829 .icon_position(IconPosition::Start)
830 .disabled(env_var_set)
831 .when(env_var_set, |this| {
832 this.tooltip(Tooltip::text(format!("To reset your API key, unset the {GOOGLE_AI_API_KEY_VAR} environment variable.")))
833 })
834 .on_click(cx.listener(|this, _, window, cx| this.reset_api_key(window, cx))),
835 )
836 .into_any()
837 }
838 }
839}