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_images(&self) -> bool {
317 true
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.id())
334 }
335
336 fn max_token_count(&self) -> usize {
337 self.model.max_token_count()
338 }
339
340 fn count_tokens(
341 &self,
342 request: LanguageModelRequest,
343 cx: &App,
344 ) -> BoxFuture<'static, Result<usize>> {
345 let model_id = self.model.id().to_string();
346 let request = into_google(request, model_id.clone());
347 let http_client = self.http_client.clone();
348 let api_key = self.state.read(cx).api_key.clone();
349
350 let settings = &AllLanguageModelSettings::get_global(cx).google;
351 let api_url = settings.api_url.clone();
352
353 async move {
354 let api_key = api_key.ok_or_else(|| anyhow!("Missing Google API key"))?;
355 let response = google_ai::count_tokens(
356 http_client.as_ref(),
357 &api_url,
358 &api_key,
359 google_ai::CountTokensRequest {
360 generate_content_request: request,
361 },
362 )
363 .await?;
364 Ok(response.total_tokens)
365 }
366 .boxed()
367 }
368
369 fn stream_completion(
370 &self,
371 request: LanguageModelRequest,
372 cx: &AsyncApp,
373 ) -> BoxFuture<
374 'static,
375 Result<
376 futures::stream::BoxStream<
377 'static,
378 Result<LanguageModelCompletionEvent, LanguageModelCompletionError>,
379 >,
380 >,
381 > {
382 let request = into_google(request, self.model.id().to_string());
383 let request = self.stream_completion(request, cx);
384 let future = self.request_limiter.stream(async move {
385 let response = request
386 .await
387 .map_err(|err| LanguageModelCompletionError::Other(anyhow!(err)))?;
388 Ok(GoogleEventMapper::new().map_stream(response))
389 });
390 async move { Ok(future.await?.boxed()) }.boxed()
391 }
392}
393
394pub fn into_google(
395 mut request: LanguageModelRequest,
396 model_id: String,
397) -> google_ai::GenerateContentRequest {
398 fn map_content(content: Vec<MessageContent>) -> Vec<Part> {
399 content
400 .into_iter()
401 .flat_map(|content| match content {
402 language_model::MessageContent::Text(text)
403 | language_model::MessageContent::Thinking { text, .. } => {
404 if !text.is_empty() {
405 vec![Part::TextPart(google_ai::TextPart { text })]
406 } else {
407 vec![]
408 }
409 }
410 language_model::MessageContent::RedactedThinking(_) => vec![],
411 language_model::MessageContent::Image(image) => {
412 vec![Part::InlineDataPart(google_ai::InlineDataPart {
413 inline_data: google_ai::GenerativeContentBlob {
414 mime_type: "image/png".to_string(),
415 data: image.source.to_string(),
416 },
417 })]
418 }
419 language_model::MessageContent::ToolUse(tool_use) => {
420 vec![Part::FunctionCallPart(google_ai::FunctionCallPart {
421 function_call: google_ai::FunctionCall {
422 name: tool_use.name.to_string(),
423 args: tool_use.input,
424 },
425 })]
426 }
427 language_model::MessageContent::ToolResult(tool_result) => {
428 match tool_result.content {
429 language_model::LanguageModelToolResultContent::Text(text)
430 | language_model::LanguageModelToolResultContent::WrappedText(
431 language_model::WrappedTextContent { text, .. },
432 ) => {
433 vec![Part::FunctionResponsePart(
434 google_ai::FunctionResponsePart {
435 function_response: google_ai::FunctionResponse {
436 name: tool_result.tool_name.to_string(),
437 // The API expects a valid JSON object
438 response: serde_json::json!({
439 "output": text
440 }),
441 },
442 },
443 )]
444 }
445 language_model::LanguageModelToolResultContent::Image(image) => {
446 vec![
447 Part::FunctionResponsePart(google_ai::FunctionResponsePart {
448 function_response: google_ai::FunctionResponse {
449 name: tool_result.tool_name.to_string(),
450 // The API expects a valid JSON object
451 response: serde_json::json!({
452 "output": "Tool responded with an image"
453 }),
454 },
455 }),
456 Part::InlineDataPart(google_ai::InlineDataPart {
457 inline_data: google_ai::GenerativeContentBlob {
458 mime_type: "image/png".to_string(),
459 data: image.source.to_string(),
460 },
461 }),
462 ]
463 }
464 }
465 }
466 })
467 .collect()
468 }
469
470 let system_instructions = if request
471 .messages
472 .first()
473 .map_or(false, |msg| matches!(msg.role, Role::System))
474 {
475 let message = request.messages.remove(0);
476 Some(SystemInstruction {
477 parts: map_content(message.content),
478 })
479 } else {
480 None
481 };
482
483 google_ai::GenerateContentRequest {
484 model: google_ai::ModelName { model_id },
485 system_instruction: system_instructions,
486 contents: request
487 .messages
488 .into_iter()
489 .filter_map(|message| {
490 let parts = map_content(message.content);
491 if parts.is_empty() {
492 None
493 } else {
494 Some(google_ai::Content {
495 parts,
496 role: match message.role {
497 Role::User => google_ai::Role::User,
498 Role::Assistant => google_ai::Role::Model,
499 Role::System => google_ai::Role::User, // Google AI doesn't have a system role
500 },
501 })
502 }
503 })
504 .collect(),
505 generation_config: Some(google_ai::GenerationConfig {
506 candidate_count: Some(1),
507 stop_sequences: Some(request.stop),
508 max_output_tokens: None,
509 temperature: request.temperature.map(|t| t as f64).or(Some(1.0)),
510 top_p: None,
511 top_k: None,
512 }),
513 safety_settings: None,
514 tools: (request.tools.len() > 0).then(|| {
515 vec![google_ai::Tool {
516 function_declarations: request
517 .tools
518 .into_iter()
519 .map(|tool| FunctionDeclaration {
520 name: tool.name,
521 description: tool.description,
522 parameters: tool.input_schema,
523 })
524 .collect(),
525 }]
526 }),
527 tool_config: request.tool_choice.map(|choice| google_ai::ToolConfig {
528 function_calling_config: google_ai::FunctionCallingConfig {
529 mode: match choice {
530 LanguageModelToolChoice::Auto => google_ai::FunctionCallingMode::Auto,
531 LanguageModelToolChoice::Any => google_ai::FunctionCallingMode::Any,
532 LanguageModelToolChoice::None => google_ai::FunctionCallingMode::None,
533 },
534 allowed_function_names: None,
535 },
536 }),
537 }
538}
539
540pub struct GoogleEventMapper {
541 usage: UsageMetadata,
542 stop_reason: StopReason,
543}
544
545impl GoogleEventMapper {
546 pub fn new() -> Self {
547 Self {
548 usage: UsageMetadata::default(),
549 stop_reason: StopReason::EndTurn,
550 }
551 }
552
553 pub fn map_stream(
554 mut self,
555 events: Pin<Box<dyn Send + Stream<Item = Result<GenerateContentResponse>>>>,
556 ) -> impl Stream<Item = Result<LanguageModelCompletionEvent, LanguageModelCompletionError>>
557 {
558 events
559 .map(Some)
560 .chain(futures::stream::once(async { None }))
561 .flat_map(move |event| {
562 futures::stream::iter(match event {
563 Some(Ok(event)) => self.map_event(event),
564 Some(Err(error)) => {
565 vec![Err(LanguageModelCompletionError::Other(anyhow!(error)))]
566 }
567 None => vec![Ok(LanguageModelCompletionEvent::Stop(self.stop_reason))],
568 })
569 })
570 }
571
572 pub fn map_event(
573 &mut self,
574 event: GenerateContentResponse,
575 ) -> Vec<Result<LanguageModelCompletionEvent, LanguageModelCompletionError>> {
576 static TOOL_CALL_COUNTER: AtomicU64 = AtomicU64::new(0);
577
578 let mut events: Vec<_> = Vec::new();
579 let mut wants_to_use_tool = false;
580 if let Some(usage_metadata) = event.usage_metadata {
581 update_usage(&mut self.usage, &usage_metadata);
582 events.push(Ok(LanguageModelCompletionEvent::UsageUpdate(
583 convert_usage(&self.usage),
584 )))
585 }
586 if let Some(candidates) = event.candidates {
587 for candidate in candidates {
588 if let Some(finish_reason) = candidate.finish_reason.as_deref() {
589 self.stop_reason = match finish_reason {
590 "STOP" => StopReason::EndTurn,
591 "MAX_TOKENS" => StopReason::MaxTokens,
592 _ => {
593 log::error!("Unexpected google finish_reason: {finish_reason}");
594 StopReason::EndTurn
595 }
596 };
597 }
598 candidate
599 .content
600 .parts
601 .into_iter()
602 .for_each(|part| match part {
603 Part::TextPart(text_part) => {
604 events.push(Ok(LanguageModelCompletionEvent::Text(text_part.text)))
605 }
606 Part::InlineDataPart(_) => {}
607 Part::FunctionCallPart(function_call_part) => {
608 wants_to_use_tool = true;
609 let name: Arc<str> = function_call_part.function_call.name.into();
610 let next_tool_id =
611 TOOL_CALL_COUNTER.fetch_add(1, atomic::Ordering::SeqCst);
612 let id: LanguageModelToolUseId =
613 format!("{}-{}", name, next_tool_id).into();
614
615 events.push(Ok(LanguageModelCompletionEvent::ToolUse(
616 LanguageModelToolUse {
617 id,
618 name,
619 is_input_complete: true,
620 raw_input: function_call_part.function_call.args.to_string(),
621 input: function_call_part.function_call.args,
622 },
623 )));
624 }
625 Part::FunctionResponsePart(_) => {}
626 });
627 }
628 }
629
630 // Even when Gemini wants to use a Tool, the API
631 // responds with `finish_reason: STOP`
632 if wants_to_use_tool {
633 self.stop_reason = StopReason::ToolUse;
634 events.push(Ok(LanguageModelCompletionEvent::Stop(StopReason::ToolUse)));
635 }
636 events
637 }
638}
639
640pub fn count_google_tokens(
641 request: LanguageModelRequest,
642 cx: &App,
643) -> BoxFuture<'static, Result<usize>> {
644 // We couldn't use the GoogleLanguageModelProvider to count tokens because the github copilot doesn't have the access to google_ai directly.
645 // So we have to use tokenizer from tiktoken_rs to count tokens.
646 cx.background_spawn(async move {
647 let messages = request
648 .messages
649 .into_iter()
650 .map(|message| tiktoken_rs::ChatCompletionRequestMessage {
651 role: match message.role {
652 Role::User => "user".into(),
653 Role::Assistant => "assistant".into(),
654 Role::System => "system".into(),
655 },
656 content: Some(message.string_contents()),
657 name: None,
658 function_call: None,
659 })
660 .collect::<Vec<_>>();
661
662 // Tiktoken doesn't yet support these models, so we manually use the
663 // same tokenizer as GPT-4.
664 tiktoken_rs::num_tokens_from_messages("gpt-4", &messages)
665 })
666 .boxed()
667}
668
669fn update_usage(usage: &mut UsageMetadata, new: &UsageMetadata) {
670 if let Some(prompt_token_count) = new.prompt_token_count {
671 usage.prompt_token_count = Some(prompt_token_count);
672 }
673 if let Some(cached_content_token_count) = new.cached_content_token_count {
674 usage.cached_content_token_count = Some(cached_content_token_count);
675 }
676 if let Some(candidates_token_count) = new.candidates_token_count {
677 usage.candidates_token_count = Some(candidates_token_count);
678 }
679 if let Some(tool_use_prompt_token_count) = new.tool_use_prompt_token_count {
680 usage.tool_use_prompt_token_count = Some(tool_use_prompt_token_count);
681 }
682 if let Some(thoughts_token_count) = new.thoughts_token_count {
683 usage.thoughts_token_count = Some(thoughts_token_count);
684 }
685 if let Some(total_token_count) = new.total_token_count {
686 usage.total_token_count = Some(total_token_count);
687 }
688}
689
690fn convert_usage(usage: &UsageMetadata) -> language_model::TokenUsage {
691 language_model::TokenUsage {
692 input_tokens: usage.prompt_token_count.unwrap_or(0) as u32,
693 output_tokens: usage.candidates_token_count.unwrap_or(0) as u32,
694 cache_read_input_tokens: usage.cached_content_token_count.unwrap_or(0) as u32,
695 cache_creation_input_tokens: 0,
696 }
697}
698
699struct ConfigurationView {
700 api_key_editor: Entity<Editor>,
701 state: gpui::Entity<State>,
702 load_credentials_task: Option<Task<()>>,
703}
704
705impl ConfigurationView {
706 fn new(state: gpui::Entity<State>, window: &mut Window, cx: &mut Context<Self>) -> Self {
707 cx.observe(&state, |_, _, cx| {
708 cx.notify();
709 })
710 .detach();
711
712 let load_credentials_task = Some(cx.spawn_in(window, {
713 let state = state.clone();
714 async move |this, cx| {
715 if let Some(task) = state
716 .update(cx, |state, cx| state.authenticate(cx))
717 .log_err()
718 {
719 // We don't log an error, because "not signed in" is also an error.
720 let _ = task.await;
721 }
722 this.update(cx, |this, cx| {
723 this.load_credentials_task = None;
724 cx.notify();
725 })
726 .log_err();
727 }
728 }));
729
730 Self {
731 api_key_editor: cx.new(|cx| {
732 let mut editor = Editor::single_line(window, cx);
733 editor.set_placeholder_text("AIzaSy...", cx);
734 editor
735 }),
736 state,
737 load_credentials_task,
738 }
739 }
740
741 fn save_api_key(&mut self, _: &menu::Confirm, window: &mut Window, cx: &mut Context<Self>) {
742 let api_key = self.api_key_editor.read(cx).text(cx);
743 if api_key.is_empty() {
744 return;
745 }
746
747 let state = self.state.clone();
748 cx.spawn_in(window, async move |_, cx| {
749 state
750 .update(cx, |state, cx| state.set_api_key(api_key, cx))?
751 .await
752 })
753 .detach_and_log_err(cx);
754
755 cx.notify();
756 }
757
758 fn reset_api_key(&mut self, window: &mut Window, cx: &mut Context<Self>) {
759 self.api_key_editor
760 .update(cx, |editor, cx| editor.set_text("", window, cx));
761
762 let state = self.state.clone();
763 cx.spawn_in(window, async move |_, cx| {
764 state.update(cx, |state, cx| state.reset_api_key(cx))?.await
765 })
766 .detach_and_log_err(cx);
767
768 cx.notify();
769 }
770
771 fn render_api_key_editor(&self, cx: &mut Context<Self>) -> impl IntoElement {
772 let settings = ThemeSettings::get_global(cx);
773 let text_style = TextStyle {
774 color: cx.theme().colors().text,
775 font_family: settings.ui_font.family.clone(),
776 font_features: settings.ui_font.features.clone(),
777 font_fallbacks: settings.ui_font.fallbacks.clone(),
778 font_size: rems(0.875).into(),
779 font_weight: settings.ui_font.weight,
780 font_style: FontStyle::Normal,
781 line_height: relative(1.3),
782 white_space: WhiteSpace::Normal,
783 ..Default::default()
784 };
785 EditorElement::new(
786 &self.api_key_editor,
787 EditorStyle {
788 background: cx.theme().colors().editor_background,
789 local_player: cx.theme().players().local(),
790 text: text_style,
791 ..Default::default()
792 },
793 )
794 }
795
796 fn should_render_editor(&self, cx: &mut Context<Self>) -> bool {
797 !self.state.read(cx).is_authenticated()
798 }
799}
800
801impl Render for ConfigurationView {
802 fn render(&mut self, _: &mut Window, cx: &mut Context<Self>) -> impl IntoElement {
803 let env_var_set = self.state.read(cx).api_key_from_env;
804
805 if self.load_credentials_task.is_some() {
806 div().child(Label::new("Loading credentials...")).into_any()
807 } else if self.should_render_editor(cx) {
808 v_flex()
809 .size_full()
810 .on_action(cx.listener(Self::save_api_key))
811 .child(Label::new("To use Zed's assistant with Google AI, you need to add an API key. Follow these steps:"))
812 .child(
813 List::new()
814 .child(InstructionListItem::new(
815 "Create one by visiting",
816 Some("Google AI's console"),
817 Some("https://aistudio.google.com/app/apikey"),
818 ))
819 .child(InstructionListItem::text_only(
820 "Paste your API key below and hit enter to start using the assistant",
821 )),
822 )
823 .child(
824 h_flex()
825 .w_full()
826 .my_2()
827 .px_2()
828 .py_1()
829 .bg(cx.theme().colors().editor_background)
830 .border_1()
831 .border_color(cx.theme().colors().border)
832 .rounded_sm()
833 .child(self.render_api_key_editor(cx)),
834 )
835 .child(
836 Label::new(
837 format!("You can also assign the {GOOGLE_AI_API_KEY_VAR} environment variable and restart Zed."),
838 )
839 .size(LabelSize::Small).color(Color::Muted),
840 )
841 .into_any()
842 } else {
843 h_flex()
844 .mt_1()
845 .p_1()
846 .justify_between()
847 .rounded_md()
848 .border_1()
849 .border_color(cx.theme().colors().border)
850 .bg(cx.theme().colors().background)
851 .child(
852 h_flex()
853 .gap_1()
854 .child(Icon::new(IconName::Check).color(Color::Success))
855 .child(Label::new(if env_var_set {
856 format!("API key set in {GOOGLE_AI_API_KEY_VAR} environment variable.")
857 } else {
858 "API key configured.".to_string()
859 })),
860 )
861 .child(
862 Button::new("reset-key", "Reset Key")
863 .label_size(LabelSize::Small)
864 .icon(Some(IconName::Trash))
865 .icon_size(IconSize::Small)
866 .icon_position(IconPosition::Start)
867 .disabled(env_var_set)
868 .when(env_var_set, |this| {
869 this.tooltip(Tooltip::text(format!("To reset your API key, unset the {GOOGLE_AI_API_KEY_VAR} environment variable.")))
870 })
871 .on_click(cx.listener(|this, _, window, cx| this.reset_api_key(window, cx))),
872 )
873 .into_any()
874 }
875 }
876}