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, GoogleModelMode, Part, SystemInstruction,
8 ThinkingConfig, UsageMetadata,
9};
10use gpui::{
11 AnyView, App, AsyncApp, Context, Entity, FontStyle, Subscription, Task, TextStyle, WhiteSpace,
12};
13use http_client::HttpClient;
14use language_model::{
15 AuthenticateError, LanguageModelCompletionError, LanguageModelCompletionEvent,
16 LanguageModelToolChoice, LanguageModelToolSchemaFormat, LanguageModelToolUse,
17 LanguageModelToolUseId, MessageContent, StopReason,
18};
19use language_model::{
20 LanguageModel, LanguageModelId, LanguageModelName, LanguageModelProvider,
21 LanguageModelProviderId, LanguageModelProviderName, LanguageModelProviderState,
22 LanguageModelRequest, RateLimiter, Role,
23};
24use schemars::JsonSchema;
25use serde::{Deserialize, Serialize};
26use settings::{Settings, SettingsStore};
27use std::pin::Pin;
28use std::sync::{
29 Arc,
30 atomic::{self, AtomicU64},
31};
32use strum::IntoEnumIterator;
33use theme::ThemeSettings;
34use ui::{Icon, IconName, List, Tooltip, prelude::*};
35use util::ResultExt;
36
37use crate::AllLanguageModelSettings;
38use crate::ui::InstructionListItem;
39
40const PROVIDER_ID: &str = "google";
41const PROVIDER_NAME: &str = "Google AI";
42
43#[derive(Default, Clone, Debug, PartialEq)]
44pub struct GoogleSettings {
45 pub api_url: String,
46 pub available_models: Vec<AvailableModel>,
47}
48
49#[derive(Clone, Copy, Debug, Default, PartialEq, Serialize, Deserialize, JsonSchema)]
50#[serde(tag = "type", rename_all = "lowercase")]
51pub enum ModelMode {
52 #[default]
53 Default,
54 Thinking {
55 /// The maximum number of tokens to use for reasoning. Must be lower than the model's `max_output_tokens`.
56 budget_tokens: Option<u32>,
57 },
58}
59
60impl From<ModelMode> for GoogleModelMode {
61 fn from(value: ModelMode) -> Self {
62 match value {
63 ModelMode::Default => GoogleModelMode::Default,
64 ModelMode::Thinking { budget_tokens } => GoogleModelMode::Thinking { budget_tokens },
65 }
66 }
67}
68
69impl From<GoogleModelMode> for ModelMode {
70 fn from(value: GoogleModelMode) -> Self {
71 match value {
72 GoogleModelMode::Default => ModelMode::Default,
73 GoogleModelMode::Thinking { budget_tokens } => ModelMode::Thinking { budget_tokens },
74 }
75 }
76}
77
78#[derive(Clone, Debug, PartialEq, Serialize, Deserialize, JsonSchema)]
79pub struct AvailableModel {
80 name: String,
81 display_name: Option<String>,
82 max_tokens: usize,
83 mode: Option<ModelMode>,
84}
85
86pub struct GoogleLanguageModelProvider {
87 http_client: Arc<dyn HttpClient>,
88 state: gpui::Entity<State>,
89}
90
91pub struct State {
92 api_key: Option<String>,
93 api_key_from_env: bool,
94 _subscription: Subscription,
95}
96
97const GOOGLE_AI_API_KEY_VAR: &str = "GOOGLE_AI_API_KEY";
98
99impl State {
100 fn is_authenticated(&self) -> bool {
101 self.api_key.is_some()
102 }
103
104 fn reset_api_key(&self, cx: &mut Context<Self>) -> Task<Result<()>> {
105 let credentials_provider = <dyn CredentialsProvider>::global(cx);
106 let api_url = AllLanguageModelSettings::get_global(cx)
107 .google
108 .api_url
109 .clone();
110 cx.spawn(async move |this, cx| {
111 credentials_provider
112 .delete_credentials(&api_url, &cx)
113 .await
114 .log_err();
115 this.update(cx, |this, cx| {
116 this.api_key = None;
117 this.api_key_from_env = false;
118 cx.notify();
119 })
120 })
121 }
122
123 fn set_api_key(&mut self, api_key: String, cx: &mut Context<Self>) -> Task<Result<()>> {
124 let credentials_provider = <dyn CredentialsProvider>::global(cx);
125 let api_url = AllLanguageModelSettings::get_global(cx)
126 .google
127 .api_url
128 .clone();
129 cx.spawn(async move |this, cx| {
130 credentials_provider
131 .write_credentials(&api_url, "Bearer", api_key.as_bytes(), &cx)
132 .await?;
133 this.update(cx, |this, cx| {
134 this.api_key = Some(api_key);
135 cx.notify();
136 })
137 })
138 }
139
140 fn authenticate(&self, cx: &mut Context<Self>) -> Task<Result<(), AuthenticateError>> {
141 if self.is_authenticated() {
142 return Task::ready(Ok(()));
143 }
144
145 let credentials_provider = <dyn CredentialsProvider>::global(cx);
146 let api_url = AllLanguageModelSettings::get_global(cx)
147 .google
148 .api_url
149 .clone();
150
151 cx.spawn(async move |this, cx| {
152 let (api_key, from_env) = if let Ok(api_key) = std::env::var(GOOGLE_AI_API_KEY_VAR) {
153 (api_key, true)
154 } else {
155 let (_, api_key) = credentials_provider
156 .read_credentials(&api_url, &cx)
157 .await?
158 .ok_or(AuthenticateError::CredentialsNotFound)?;
159 (
160 String::from_utf8(api_key).context("invalid {PROVIDER_NAME} API key")?,
161 false,
162 )
163 };
164
165 this.update(cx, |this, cx| {
166 this.api_key = Some(api_key);
167 this.api_key_from_env = from_env;
168 cx.notify();
169 })?;
170
171 Ok(())
172 })
173 }
174}
175
176impl GoogleLanguageModelProvider {
177 pub fn new(http_client: Arc<dyn HttpClient>, cx: &mut App) -> Self {
178 let state = cx.new(|cx| State {
179 api_key: None,
180 api_key_from_env: false,
181 _subscription: cx.observe_global::<SettingsStore>(|_, cx| {
182 cx.notify();
183 }),
184 });
185
186 Self { http_client, state }
187 }
188
189 fn create_language_model(&self, model: google_ai::Model) -> Arc<dyn LanguageModel> {
190 Arc::new(GoogleLanguageModel {
191 id: LanguageModelId::from(model.id().to_string()),
192 model,
193 state: self.state.clone(),
194 http_client: self.http_client.clone(),
195 request_limiter: RateLimiter::new(4),
196 })
197 }
198}
199
200impl LanguageModelProviderState for GoogleLanguageModelProvider {
201 type ObservableEntity = State;
202
203 fn observable_entity(&self) -> Option<gpui::Entity<Self::ObservableEntity>> {
204 Some(self.state.clone())
205 }
206}
207
208impl LanguageModelProvider for GoogleLanguageModelProvider {
209 fn id(&self) -> LanguageModelProviderId {
210 LanguageModelProviderId(PROVIDER_ID.into())
211 }
212
213 fn name(&self) -> LanguageModelProviderName {
214 LanguageModelProviderName(PROVIDER_NAME.into())
215 }
216
217 fn icon(&self) -> IconName {
218 IconName::AiGoogle
219 }
220
221 fn default_model(&self, _cx: &App) -> Option<Arc<dyn LanguageModel>> {
222 Some(self.create_language_model(google_ai::Model::default()))
223 }
224
225 fn default_fast_model(&self, _cx: &App) -> Option<Arc<dyn LanguageModel>> {
226 Some(self.create_language_model(google_ai::Model::default_fast()))
227 }
228
229 fn provided_models(&self, cx: &App) -> Vec<Arc<dyn LanguageModel>> {
230 let mut models = BTreeMap::default();
231
232 // Add base models from google_ai::Model::iter()
233 for model in google_ai::Model::iter() {
234 if !matches!(model, google_ai::Model::Custom { .. }) {
235 models.insert(model.id().to_string(), model);
236 }
237 }
238
239 // Override with available models from settings
240 for model in &AllLanguageModelSettings::get_global(cx)
241 .google
242 .available_models
243 {
244 models.insert(
245 model.name.clone(),
246 google_ai::Model::Custom {
247 name: model.name.clone(),
248 display_name: model.display_name.clone(),
249 max_tokens: model.max_tokens,
250 mode: model.mode.unwrap_or_default().into(),
251 },
252 );
253 }
254
255 models
256 .into_values()
257 .map(|model| {
258 Arc::new(GoogleLanguageModel {
259 id: LanguageModelId::from(model.id().to_string()),
260 model,
261 state: self.state.clone(),
262 http_client: self.http_client.clone(),
263 request_limiter: RateLimiter::new(4),
264 }) as Arc<dyn LanguageModel>
265 })
266 .collect()
267 }
268
269 fn is_authenticated(&self, cx: &App) -> bool {
270 self.state.read(cx).is_authenticated()
271 }
272
273 fn authenticate(&self, cx: &mut App) -> Task<Result<(), AuthenticateError>> {
274 self.state.update(cx, |state, cx| state.authenticate(cx))
275 }
276
277 fn configuration_view(&self, window: &mut Window, cx: &mut App) -> AnyView {
278 cx.new(|cx| ConfigurationView::new(self.state.clone(), window, cx))
279 .into()
280 }
281
282 fn reset_credentials(&self, cx: &mut App) -> Task<Result<()>> {
283 self.state.update(cx, |state, cx| state.reset_api_key(cx))
284 }
285}
286
287pub struct GoogleLanguageModel {
288 id: LanguageModelId,
289 model: google_ai::Model,
290 state: gpui::Entity<State>,
291 http_client: Arc<dyn HttpClient>,
292 request_limiter: RateLimiter,
293}
294
295impl GoogleLanguageModel {
296 fn stream_completion(
297 &self,
298 request: google_ai::GenerateContentRequest,
299 cx: &AsyncApp,
300 ) -> BoxFuture<
301 'static,
302 Result<futures::stream::BoxStream<'static, Result<GenerateContentResponse>>>,
303 > {
304 let http_client = self.http_client.clone();
305
306 let Ok((api_key, api_url)) = cx.read_entity(&self.state, |state, cx| {
307 let settings = &AllLanguageModelSettings::get_global(cx).google;
308 (state.api_key.clone(), settings.api_url.clone())
309 }) else {
310 return futures::future::ready(Err(anyhow!("App state dropped"))).boxed();
311 };
312
313 async move {
314 let api_key = api_key.context("Missing Google API key")?;
315 let request = google_ai::stream_generate_content(
316 http_client.as_ref(),
317 &api_url,
318 &api_key,
319 request,
320 );
321 request.await.context("failed to stream completion")
322 }
323 .boxed()
324 }
325}
326
327impl LanguageModel for GoogleLanguageModel {
328 fn id(&self) -> LanguageModelId {
329 self.id.clone()
330 }
331
332 fn name(&self) -> LanguageModelName {
333 LanguageModelName::from(self.model.display_name().to_string())
334 }
335
336 fn provider_id(&self) -> LanguageModelProviderId {
337 LanguageModelProviderId(PROVIDER_ID.into())
338 }
339
340 fn provider_name(&self) -> LanguageModelProviderName {
341 LanguageModelProviderName(PROVIDER_NAME.into())
342 }
343
344 fn supports_tools(&self) -> bool {
345 true
346 }
347
348 fn supports_images(&self) -> bool {
349 true
350 }
351
352 fn supports_tool_choice(&self, choice: LanguageModelToolChoice) -> bool {
353 match choice {
354 LanguageModelToolChoice::Auto
355 | LanguageModelToolChoice::Any
356 | LanguageModelToolChoice::None => true,
357 }
358 }
359
360 fn tool_input_format(&self) -> LanguageModelToolSchemaFormat {
361 LanguageModelToolSchemaFormat::JsonSchemaSubset
362 }
363
364 fn telemetry_id(&self) -> String {
365 format!("google/{}", self.model.request_id())
366 }
367
368 fn max_token_count(&self) -> usize {
369 self.model.max_token_count()
370 }
371
372 fn count_tokens(
373 &self,
374 request: LanguageModelRequest,
375 cx: &App,
376 ) -> BoxFuture<'static, Result<usize>> {
377 let model_id = self.model.request_id().to_string();
378 let request = into_google(request, model_id.clone(), self.model.mode());
379 let http_client = self.http_client.clone();
380 let api_key = self.state.read(cx).api_key.clone();
381
382 let settings = &AllLanguageModelSettings::get_global(cx).google;
383 let api_url = settings.api_url.clone();
384
385 async move {
386 let api_key = api_key.context("Missing Google API key")?;
387 let response = google_ai::count_tokens(
388 http_client.as_ref(),
389 &api_url,
390 &api_key,
391 google_ai::CountTokensRequest {
392 generate_content_request: request,
393 },
394 )
395 .await?;
396 Ok(response.total_tokens)
397 }
398 .boxed()
399 }
400
401 fn stream_completion(
402 &self,
403 request: LanguageModelRequest,
404 cx: &AsyncApp,
405 ) -> BoxFuture<
406 'static,
407 Result<
408 futures::stream::BoxStream<
409 'static,
410 Result<LanguageModelCompletionEvent, LanguageModelCompletionError>,
411 >,
412 >,
413 > {
414 let request = into_google(
415 request,
416 self.model.request_id().to_string(),
417 self.model.mode(),
418 );
419 let request = self.stream_completion(request, cx);
420 let future = self.request_limiter.stream(async move {
421 let response = request
422 .await
423 .map_err(|err| LanguageModelCompletionError::Other(anyhow!(err)))?;
424 Ok(GoogleEventMapper::new().map_stream(response))
425 });
426 async move { Ok(future.await?.boxed()) }.boxed()
427 }
428}
429
430pub fn into_google(
431 mut request: LanguageModelRequest,
432 model_id: String,
433 mode: GoogleModelMode,
434) -> google_ai::GenerateContentRequest {
435 fn map_content(content: Vec<MessageContent>) -> Vec<Part> {
436 content
437 .into_iter()
438 .flat_map(|content| match content {
439 language_model::MessageContent::Text(text)
440 | language_model::MessageContent::Thinking { text, .. } => {
441 if !text.is_empty() {
442 vec![Part::TextPart(google_ai::TextPart { text })]
443 } else {
444 vec![]
445 }
446 }
447 language_model::MessageContent::RedactedThinking(_) => vec![],
448 language_model::MessageContent::Image(image) => {
449 vec![Part::InlineDataPart(google_ai::InlineDataPart {
450 inline_data: google_ai::GenerativeContentBlob {
451 mime_type: "image/png".to_string(),
452 data: image.source.to_string(),
453 },
454 })]
455 }
456 language_model::MessageContent::ToolUse(tool_use) => {
457 vec![Part::FunctionCallPart(google_ai::FunctionCallPart {
458 function_call: google_ai::FunctionCall {
459 name: tool_use.name.to_string(),
460 args: tool_use.input,
461 },
462 })]
463 }
464 language_model::MessageContent::ToolResult(tool_result) => {
465 match tool_result.content {
466 language_model::LanguageModelToolResultContent::Text(text) => {
467 vec![Part::FunctionResponsePart(
468 google_ai::FunctionResponsePart {
469 function_response: google_ai::FunctionResponse {
470 name: tool_result.tool_name.to_string(),
471 // The API expects a valid JSON object
472 response: serde_json::json!({
473 "output": text
474 }),
475 },
476 },
477 )]
478 }
479 language_model::LanguageModelToolResultContent::Image(image) => {
480 vec![
481 Part::FunctionResponsePart(google_ai::FunctionResponsePart {
482 function_response: google_ai::FunctionResponse {
483 name: tool_result.tool_name.to_string(),
484 // The API expects a valid JSON object
485 response: serde_json::json!({
486 "output": "Tool responded with an image"
487 }),
488 },
489 }),
490 Part::InlineDataPart(google_ai::InlineDataPart {
491 inline_data: google_ai::GenerativeContentBlob {
492 mime_type: "image/png".to_string(),
493 data: image.source.to_string(),
494 },
495 }),
496 ]
497 }
498 }
499 }
500 })
501 .collect()
502 }
503
504 let system_instructions = if request
505 .messages
506 .first()
507 .map_or(false, |msg| matches!(msg.role, Role::System))
508 {
509 let message = request.messages.remove(0);
510 Some(SystemInstruction {
511 parts: map_content(message.content),
512 })
513 } else {
514 None
515 };
516
517 google_ai::GenerateContentRequest {
518 model: google_ai::ModelName { model_id },
519 system_instruction: system_instructions,
520 contents: request
521 .messages
522 .into_iter()
523 .filter_map(|message| {
524 let parts = map_content(message.content);
525 if parts.is_empty() {
526 None
527 } else {
528 Some(google_ai::Content {
529 parts,
530 role: match message.role {
531 Role::User => google_ai::Role::User,
532 Role::Assistant => google_ai::Role::Model,
533 Role::System => google_ai::Role::User, // Google AI doesn't have a system role
534 },
535 })
536 }
537 })
538 .collect(),
539 generation_config: Some(google_ai::GenerationConfig {
540 candidate_count: Some(1),
541 stop_sequences: Some(request.stop),
542 max_output_tokens: None,
543 temperature: request.temperature.map(|t| t as f64).or(Some(1.0)),
544 thinking_config: match mode {
545 GoogleModelMode::Thinking { budget_tokens } => {
546 budget_tokens.map(|thinking_budget| ThinkingConfig { thinking_budget })
547 }
548 GoogleModelMode::Default => None,
549 },
550 top_p: None,
551 top_k: None,
552 }),
553 safety_settings: None,
554 tools: (request.tools.len() > 0).then(|| {
555 vec![google_ai::Tool {
556 function_declarations: request
557 .tools
558 .into_iter()
559 .map(|tool| FunctionDeclaration {
560 name: tool.name,
561 description: tool.description,
562 parameters: tool.input_schema,
563 })
564 .collect(),
565 }]
566 }),
567 tool_config: request.tool_choice.map(|choice| google_ai::ToolConfig {
568 function_calling_config: google_ai::FunctionCallingConfig {
569 mode: match choice {
570 LanguageModelToolChoice::Auto => google_ai::FunctionCallingMode::Auto,
571 LanguageModelToolChoice::Any => google_ai::FunctionCallingMode::Any,
572 LanguageModelToolChoice::None => google_ai::FunctionCallingMode::None,
573 },
574 allowed_function_names: None,
575 },
576 }),
577 }
578}
579
580pub struct GoogleEventMapper {
581 usage: UsageMetadata,
582 stop_reason: StopReason,
583}
584
585impl GoogleEventMapper {
586 pub fn new() -> Self {
587 Self {
588 usage: UsageMetadata::default(),
589 stop_reason: StopReason::EndTurn,
590 }
591 }
592
593 pub fn map_stream(
594 mut self,
595 events: Pin<Box<dyn Send + Stream<Item = Result<GenerateContentResponse>>>>,
596 ) -> impl Stream<Item = Result<LanguageModelCompletionEvent, LanguageModelCompletionError>>
597 {
598 events
599 .map(Some)
600 .chain(futures::stream::once(async { None }))
601 .flat_map(move |event| {
602 futures::stream::iter(match event {
603 Some(Ok(event)) => self.map_event(event),
604 Some(Err(error)) => {
605 vec![Err(LanguageModelCompletionError::Other(anyhow!(error)))]
606 }
607 None => vec![Ok(LanguageModelCompletionEvent::Stop(self.stop_reason))],
608 })
609 })
610 }
611
612 pub fn map_event(
613 &mut self,
614 event: GenerateContentResponse,
615 ) -> Vec<Result<LanguageModelCompletionEvent, LanguageModelCompletionError>> {
616 static TOOL_CALL_COUNTER: AtomicU64 = AtomicU64::new(0);
617
618 let mut events: Vec<_> = Vec::new();
619 let mut wants_to_use_tool = false;
620 if let Some(usage_metadata) = event.usage_metadata {
621 update_usage(&mut self.usage, &usage_metadata);
622 events.push(Ok(LanguageModelCompletionEvent::UsageUpdate(
623 convert_usage(&self.usage),
624 )))
625 }
626 if let Some(candidates) = event.candidates {
627 for candidate in candidates {
628 if let Some(finish_reason) = candidate.finish_reason.as_deref() {
629 self.stop_reason = match finish_reason {
630 "STOP" => StopReason::EndTurn,
631 "MAX_TOKENS" => StopReason::MaxTokens,
632 _ => {
633 log::error!("Unexpected google finish_reason: {finish_reason}");
634 StopReason::EndTurn
635 }
636 };
637 }
638 candidate
639 .content
640 .parts
641 .into_iter()
642 .for_each(|part| match part {
643 Part::TextPart(text_part) => {
644 events.push(Ok(LanguageModelCompletionEvent::Text(text_part.text)))
645 }
646 Part::InlineDataPart(_) => {}
647 Part::FunctionCallPart(function_call_part) => {
648 wants_to_use_tool = true;
649 let name: Arc<str> = function_call_part.function_call.name.into();
650 let next_tool_id =
651 TOOL_CALL_COUNTER.fetch_add(1, atomic::Ordering::SeqCst);
652 let id: LanguageModelToolUseId =
653 format!("{}-{}", name, next_tool_id).into();
654
655 events.push(Ok(LanguageModelCompletionEvent::ToolUse(
656 LanguageModelToolUse {
657 id,
658 name,
659 is_input_complete: true,
660 raw_input: function_call_part.function_call.args.to_string(),
661 input: function_call_part.function_call.args,
662 },
663 )));
664 }
665 Part::FunctionResponsePart(_) => {}
666 Part::ThoughtPart(_) => {}
667 });
668 }
669 }
670
671 // Even when Gemini wants to use a Tool, the API
672 // responds with `finish_reason: STOP`
673 if wants_to_use_tool {
674 self.stop_reason = StopReason::ToolUse;
675 events.push(Ok(LanguageModelCompletionEvent::Stop(StopReason::ToolUse)));
676 }
677 events
678 }
679}
680
681pub fn count_google_tokens(
682 request: LanguageModelRequest,
683 cx: &App,
684) -> BoxFuture<'static, Result<usize>> {
685 // We couldn't use the GoogleLanguageModelProvider to count tokens because the github copilot doesn't have the access to google_ai directly.
686 // So we have to use tokenizer from tiktoken_rs to count tokens.
687 cx.background_spawn(async move {
688 let messages = request
689 .messages
690 .into_iter()
691 .map(|message| tiktoken_rs::ChatCompletionRequestMessage {
692 role: match message.role {
693 Role::User => "user".into(),
694 Role::Assistant => "assistant".into(),
695 Role::System => "system".into(),
696 },
697 content: Some(message.string_contents()),
698 name: None,
699 function_call: None,
700 })
701 .collect::<Vec<_>>();
702
703 // Tiktoken doesn't yet support these models, so we manually use the
704 // same tokenizer as GPT-4.
705 tiktoken_rs::num_tokens_from_messages("gpt-4", &messages)
706 })
707 .boxed()
708}
709
710fn update_usage(usage: &mut UsageMetadata, new: &UsageMetadata) {
711 if let Some(prompt_token_count) = new.prompt_token_count {
712 usage.prompt_token_count = Some(prompt_token_count);
713 }
714 if let Some(cached_content_token_count) = new.cached_content_token_count {
715 usage.cached_content_token_count = Some(cached_content_token_count);
716 }
717 if let Some(candidates_token_count) = new.candidates_token_count {
718 usage.candidates_token_count = Some(candidates_token_count);
719 }
720 if let Some(tool_use_prompt_token_count) = new.tool_use_prompt_token_count {
721 usage.tool_use_prompt_token_count = Some(tool_use_prompt_token_count);
722 }
723 if let Some(thoughts_token_count) = new.thoughts_token_count {
724 usage.thoughts_token_count = Some(thoughts_token_count);
725 }
726 if let Some(total_token_count) = new.total_token_count {
727 usage.total_token_count = Some(total_token_count);
728 }
729}
730
731fn convert_usage(usage: &UsageMetadata) -> language_model::TokenUsage {
732 let prompt_tokens = usage.prompt_token_count.unwrap_or(0) as u32;
733 let cached_tokens = usage.cached_content_token_count.unwrap_or(0) as u32;
734 let input_tokens = prompt_tokens - cached_tokens;
735 let output_tokens = usage.candidates_token_count.unwrap_or(0) as u32;
736
737 language_model::TokenUsage {
738 input_tokens,
739 output_tokens,
740 cache_read_input_tokens: cached_tokens,
741 cache_creation_input_tokens: 0,
742 }
743}
744
745struct ConfigurationView {
746 api_key_editor: Entity<Editor>,
747 state: gpui::Entity<State>,
748 load_credentials_task: Option<Task<()>>,
749}
750
751impl ConfigurationView {
752 fn new(state: gpui::Entity<State>, window: &mut Window, cx: &mut Context<Self>) -> 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...", cx);
780 editor
781 }),
782 state,
783 load_credentials_task,
784 }
785 }
786
787 fn save_api_key(&mut self, _: &menu::Confirm, window: &mut Window, cx: &mut Context<Self>) {
788 let api_key = self.api_key_editor.read(cx).text(cx);
789 if api_key.is_empty() {
790 return;
791 }
792
793 let state = self.state.clone();
794 cx.spawn_in(window, async move |_, cx| {
795 state
796 .update(cx, |state, cx| state.set_api_key(api_key, cx))?
797 .await
798 })
799 .detach_and_log_err(cx);
800
801 cx.notify();
802 }
803
804 fn reset_api_key(&mut self, window: &mut Window, cx: &mut Context<Self>) {
805 self.api_key_editor
806 .update(cx, |editor, cx| editor.set_text("", window, cx));
807
808 let state = self.state.clone();
809 cx.spawn_in(window, async move |_, cx| {
810 state.update(cx, |state, cx| state.reset_api_key(cx))?.await
811 })
812 .detach_and_log_err(cx);
813
814 cx.notify();
815 }
816
817 fn render_api_key_editor(&self, cx: &mut Context<Self>) -> impl IntoElement {
818 let settings = ThemeSettings::get_global(cx);
819 let text_style = TextStyle {
820 color: cx.theme().colors().text,
821 font_family: settings.ui_font.family.clone(),
822 font_features: settings.ui_font.features.clone(),
823 font_fallbacks: settings.ui_font.fallbacks.clone(),
824 font_size: rems(0.875).into(),
825 font_weight: settings.ui_font.weight,
826 font_style: FontStyle::Normal,
827 line_height: relative(1.3),
828 white_space: WhiteSpace::Normal,
829 ..Default::default()
830 };
831 EditorElement::new(
832 &self.api_key_editor,
833 EditorStyle {
834 background: cx.theme().colors().editor_background,
835 local_player: cx.theme().players().local(),
836 text: text_style,
837 ..Default::default()
838 },
839 )
840 }
841
842 fn should_render_editor(&self, cx: &mut Context<Self>) -> bool {
843 !self.state.read(cx).is_authenticated()
844 }
845}
846
847impl Render for ConfigurationView {
848 fn render(&mut self, _: &mut Window, cx: &mut Context<Self>) -> impl IntoElement {
849 let env_var_set = self.state.read(cx).api_key_from_env;
850
851 if self.load_credentials_task.is_some() {
852 div().child(Label::new("Loading credentials...")).into_any()
853 } else if self.should_render_editor(cx) {
854 v_flex()
855 .size_full()
856 .on_action(cx.listener(Self::save_api_key))
857 .child(Label::new("To use Zed's assistant with Google AI, you need to add an API key. Follow these steps:"))
858 .child(
859 List::new()
860 .child(InstructionListItem::new(
861 "Create one by visiting",
862 Some("Google AI's console"),
863 Some("https://aistudio.google.com/app/apikey"),
864 ))
865 .child(InstructionListItem::text_only(
866 "Paste your API key below and hit enter to start using the assistant",
867 )),
868 )
869 .child(
870 h_flex()
871 .w_full()
872 .my_2()
873 .px_2()
874 .py_1()
875 .bg(cx.theme().colors().editor_background)
876 .border_1()
877 .border_color(cx.theme().colors().border)
878 .rounded_sm()
879 .child(self.render_api_key_editor(cx)),
880 )
881 .child(
882 Label::new(
883 format!("You can also assign the {GOOGLE_AI_API_KEY_VAR} environment variable and restart Zed."),
884 )
885 .size(LabelSize::Small).color(Color::Muted),
886 )
887 .into_any()
888 } else {
889 h_flex()
890 .mt_1()
891 .p_1()
892 .justify_between()
893 .rounded_md()
894 .border_1()
895 .border_color(cx.theme().colors().border)
896 .bg(cx.theme().colors().background)
897 .child(
898 h_flex()
899 .gap_1()
900 .child(Icon::new(IconName::Check).color(Color::Success))
901 .child(Label::new(if env_var_set {
902 format!("API key set in {GOOGLE_AI_API_KEY_VAR} environment variable.")
903 } else {
904 "API key configured.".to_string()
905 })),
906 )
907 .child(
908 Button::new("reset-key", "Reset Key")
909 .label_size(LabelSize::Small)
910 .icon(Some(IconName::Trash))
911 .icon_size(IconSize::Small)
912 .icon_position(IconPosition::Start)
913 .disabled(env_var_set)
914 .when(env_var_set, |this| {
915 this.tooltip(Tooltip::text(format!("To reset your API key, unset the {GOOGLE_AI_API_KEY_VAR} environment variable.")))
916 })
917 .on_click(cx.listener(|this, _, window, cx| this.reset_api_key(window, cx))),
918 )
919 .into_any()
920 }
921 }
922}