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: u64,
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 self.model.supports_tools()
346 }
347
348 fn supports_images(&self) -> bool {
349 self.model.supports_images()
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) -> u64 {
369 self.model.max_token_count()
370 }
371
372 fn max_output_tokens(&self) -> Option<u64> {
373 self.model.max_output_tokens()
374 }
375
376 fn count_tokens(
377 &self,
378 request: LanguageModelRequest,
379 cx: &App,
380 ) -> BoxFuture<'static, Result<u64>> {
381 let model_id = self.model.request_id().to_string();
382 let request = into_google(request, model_id.clone(), self.model.mode());
383 let http_client = self.http_client.clone();
384 let api_key = self.state.read(cx).api_key.clone();
385
386 let settings = &AllLanguageModelSettings::get_global(cx).google;
387 let api_url = settings.api_url.clone();
388
389 async move {
390 let api_key = api_key.context("Missing Google API key")?;
391 let response = google_ai::count_tokens(
392 http_client.as_ref(),
393 &api_url,
394 &api_key,
395 google_ai::CountTokensRequest {
396 generate_content_request: request,
397 },
398 )
399 .await?;
400 Ok(response.total_tokens)
401 }
402 .boxed()
403 }
404
405 fn stream_completion(
406 &self,
407 request: LanguageModelRequest,
408 cx: &AsyncApp,
409 ) -> BoxFuture<
410 'static,
411 Result<
412 futures::stream::BoxStream<
413 'static,
414 Result<LanguageModelCompletionEvent, LanguageModelCompletionError>,
415 >,
416 LanguageModelCompletionError,
417 >,
418 > {
419 let request = into_google(
420 request,
421 self.model.request_id().to_string(),
422 self.model.mode(),
423 );
424 let request = self.stream_completion(request, cx);
425 let future = self.request_limiter.stream(async move {
426 let response = request
427 .await
428 .map_err(|err| LanguageModelCompletionError::Other(anyhow!(err)))?;
429 Ok(GoogleEventMapper::new().map_stream(response))
430 });
431 async move { Ok(future.await?.boxed()) }.boxed()
432 }
433}
434
435pub fn into_google(
436 mut request: LanguageModelRequest,
437 model_id: String,
438 mode: GoogleModelMode,
439) -> google_ai::GenerateContentRequest {
440 fn map_content(content: Vec<MessageContent>) -> Vec<Part> {
441 content
442 .into_iter()
443 .flat_map(|content| match content {
444 language_model::MessageContent::Text(text) => {
445 if !text.is_empty() {
446 vec![Part::TextPart(google_ai::TextPart { text })]
447 } else {
448 vec![]
449 }
450 }
451 language_model::MessageContent::Thinking {
452 text: _,
453 signature: Some(signature),
454 } => {
455 if !signature.is_empty() {
456 vec![Part::ThoughtPart(google_ai::ThoughtPart {
457 thought: true,
458 thought_signature: signature,
459 })]
460 } else {
461 vec![]
462 }
463 }
464 language_model::MessageContent::Thinking { .. } => {
465 vec![]
466 }
467 language_model::MessageContent::RedactedThinking(_) => vec![],
468 language_model::MessageContent::Image(image) => {
469 vec![Part::InlineDataPart(google_ai::InlineDataPart {
470 inline_data: google_ai::GenerativeContentBlob {
471 mime_type: "image/png".to_string(),
472 data: image.source.to_string(),
473 },
474 })]
475 }
476 language_model::MessageContent::ToolUse(tool_use) => {
477 vec![Part::FunctionCallPart(google_ai::FunctionCallPart {
478 function_call: google_ai::FunctionCall {
479 name: tool_use.name.to_string(),
480 args: tool_use.input,
481 },
482 })]
483 }
484 language_model::MessageContent::ToolResult(tool_result) => {
485 match tool_result.content {
486 language_model::LanguageModelToolResultContent::Text(text) => {
487 vec![Part::FunctionResponsePart(
488 google_ai::FunctionResponsePart {
489 function_response: google_ai::FunctionResponse {
490 name: tool_result.tool_name.to_string(),
491 // The API expects a valid JSON object
492 response: serde_json::json!({
493 "output": text
494 }),
495 },
496 },
497 )]
498 }
499 language_model::LanguageModelToolResultContent::Image(image) => {
500 vec![
501 Part::FunctionResponsePart(google_ai::FunctionResponsePart {
502 function_response: google_ai::FunctionResponse {
503 name: tool_result.tool_name.to_string(),
504 // The API expects a valid JSON object
505 response: serde_json::json!({
506 "output": "Tool responded with an image"
507 }),
508 },
509 }),
510 Part::InlineDataPart(google_ai::InlineDataPart {
511 inline_data: google_ai::GenerativeContentBlob {
512 mime_type: "image/png".to_string(),
513 data: image.source.to_string(),
514 },
515 }),
516 ]
517 }
518 }
519 }
520 })
521 .collect()
522 }
523
524 let system_instructions = if request
525 .messages
526 .first()
527 .map_or(false, |msg| matches!(msg.role, Role::System))
528 {
529 let message = request.messages.remove(0);
530 Some(SystemInstruction {
531 parts: map_content(message.content),
532 })
533 } else {
534 None
535 };
536
537 google_ai::GenerateContentRequest {
538 model: google_ai::ModelName { model_id },
539 system_instruction: system_instructions,
540 contents: request
541 .messages
542 .into_iter()
543 .filter_map(|message| {
544 let parts = map_content(message.content);
545 if parts.is_empty() {
546 None
547 } else {
548 Some(google_ai::Content {
549 parts,
550 role: match message.role {
551 Role::User => google_ai::Role::User,
552 Role::Assistant => google_ai::Role::Model,
553 Role::System => google_ai::Role::User, // Google AI doesn't have a system role
554 },
555 })
556 }
557 })
558 .collect(),
559 generation_config: Some(google_ai::GenerationConfig {
560 candidate_count: Some(1),
561 stop_sequences: Some(request.stop),
562 max_output_tokens: None,
563 temperature: request.temperature.map(|t| t as f64).or(Some(1.0)),
564 thinking_config: match mode {
565 GoogleModelMode::Thinking { budget_tokens } => {
566 budget_tokens.map(|thinking_budget| ThinkingConfig { thinking_budget })
567 }
568 GoogleModelMode::Default => None,
569 },
570 top_p: None,
571 top_k: None,
572 }),
573 safety_settings: None,
574 tools: (request.tools.len() > 0).then(|| {
575 vec![google_ai::Tool {
576 function_declarations: request
577 .tools
578 .into_iter()
579 .map(|tool| FunctionDeclaration {
580 name: tool.name,
581 description: tool.description,
582 parameters: tool.input_schema,
583 })
584 .collect(),
585 }]
586 }),
587 tool_config: request.tool_choice.map(|choice| google_ai::ToolConfig {
588 function_calling_config: google_ai::FunctionCallingConfig {
589 mode: match choice {
590 LanguageModelToolChoice::Auto => google_ai::FunctionCallingMode::Auto,
591 LanguageModelToolChoice::Any => google_ai::FunctionCallingMode::Any,
592 LanguageModelToolChoice::None => google_ai::FunctionCallingMode::None,
593 },
594 allowed_function_names: None,
595 },
596 }),
597 }
598}
599
600pub struct GoogleEventMapper {
601 usage: UsageMetadata,
602 stop_reason: StopReason,
603}
604
605impl GoogleEventMapper {
606 pub fn new() -> Self {
607 Self {
608 usage: UsageMetadata::default(),
609 stop_reason: StopReason::EndTurn,
610 }
611 }
612
613 pub fn map_stream(
614 mut self,
615 events: Pin<Box<dyn Send + Stream<Item = Result<GenerateContentResponse>>>>,
616 ) -> impl Stream<Item = Result<LanguageModelCompletionEvent, LanguageModelCompletionError>>
617 {
618 events
619 .map(Some)
620 .chain(futures::stream::once(async { None }))
621 .flat_map(move |event| {
622 futures::stream::iter(match event {
623 Some(Ok(event)) => self.map_event(event),
624 Some(Err(error)) => {
625 vec![Err(LanguageModelCompletionError::Other(anyhow!(error)))]
626 }
627 None => vec![Ok(LanguageModelCompletionEvent::Stop(self.stop_reason))],
628 })
629 })
630 }
631
632 pub fn map_event(
633 &mut self,
634 event: GenerateContentResponse,
635 ) -> Vec<Result<LanguageModelCompletionEvent, LanguageModelCompletionError>> {
636 static TOOL_CALL_COUNTER: AtomicU64 = AtomicU64::new(0);
637
638 let mut events: Vec<_> = Vec::new();
639 let mut wants_to_use_tool = false;
640 if let Some(usage_metadata) = event.usage_metadata {
641 update_usage(&mut self.usage, &usage_metadata);
642 events.push(Ok(LanguageModelCompletionEvent::UsageUpdate(
643 convert_usage(&self.usage),
644 )))
645 }
646 if let Some(candidates) = event.candidates {
647 for candidate in candidates {
648 if let Some(finish_reason) = candidate.finish_reason.as_deref() {
649 self.stop_reason = match finish_reason {
650 "STOP" => StopReason::EndTurn,
651 "MAX_TOKENS" => StopReason::MaxTokens,
652 _ => {
653 log::error!("Unexpected google finish_reason: {finish_reason}");
654 StopReason::EndTurn
655 }
656 };
657 }
658 candidate
659 .content
660 .parts
661 .into_iter()
662 .for_each(|part| match part {
663 Part::TextPart(text_part) => {
664 events.push(Ok(LanguageModelCompletionEvent::Text(text_part.text)))
665 }
666 Part::InlineDataPart(_) => {}
667 Part::FunctionCallPart(function_call_part) => {
668 wants_to_use_tool = true;
669 let name: Arc<str> = function_call_part.function_call.name.into();
670 let next_tool_id =
671 TOOL_CALL_COUNTER.fetch_add(1, atomic::Ordering::SeqCst);
672 let id: LanguageModelToolUseId =
673 format!("{}-{}", name, next_tool_id).into();
674
675 events.push(Ok(LanguageModelCompletionEvent::ToolUse(
676 LanguageModelToolUse {
677 id,
678 name,
679 is_input_complete: true,
680 raw_input: function_call_part.function_call.args.to_string(),
681 input: function_call_part.function_call.args,
682 },
683 )));
684 }
685 Part::FunctionResponsePart(_) => {}
686 Part::ThoughtPart(part) => {
687 events.push(Ok(LanguageModelCompletionEvent::Thinking {
688 text: "(Encrypted thought)".to_string(), // TODO: Can we populate this from thought summaries?
689 signature: Some(part.thought_signature),
690 }));
691 }
692 });
693 }
694 }
695
696 // Even when Gemini wants to use a Tool, the API
697 // responds with `finish_reason: STOP`
698 if wants_to_use_tool {
699 self.stop_reason = StopReason::ToolUse;
700 events.push(Ok(LanguageModelCompletionEvent::Stop(StopReason::ToolUse)));
701 }
702 events
703 }
704}
705
706pub fn count_google_tokens(
707 request: LanguageModelRequest,
708 cx: &App,
709) -> BoxFuture<'static, Result<u64>> {
710 // We couldn't use the GoogleLanguageModelProvider to count tokens because the github copilot doesn't have the access to google_ai directly.
711 // So we have to use tokenizer from tiktoken_rs to count tokens.
712 cx.background_spawn(async move {
713 let messages = request
714 .messages
715 .into_iter()
716 .map(|message| tiktoken_rs::ChatCompletionRequestMessage {
717 role: match message.role {
718 Role::User => "user".into(),
719 Role::Assistant => "assistant".into(),
720 Role::System => "system".into(),
721 },
722 content: Some(message.string_contents()),
723 name: None,
724 function_call: None,
725 })
726 .collect::<Vec<_>>();
727
728 // Tiktoken doesn't yet support these models, so we manually use the
729 // same tokenizer as GPT-4.
730 tiktoken_rs::num_tokens_from_messages("gpt-4", &messages).map(|tokens| tokens as u64)
731 })
732 .boxed()
733}
734
735fn update_usage(usage: &mut UsageMetadata, new: &UsageMetadata) {
736 if let Some(prompt_token_count) = new.prompt_token_count {
737 usage.prompt_token_count = Some(prompt_token_count);
738 }
739 if let Some(cached_content_token_count) = new.cached_content_token_count {
740 usage.cached_content_token_count = Some(cached_content_token_count);
741 }
742 if let Some(candidates_token_count) = new.candidates_token_count {
743 usage.candidates_token_count = Some(candidates_token_count);
744 }
745 if let Some(tool_use_prompt_token_count) = new.tool_use_prompt_token_count {
746 usage.tool_use_prompt_token_count = Some(tool_use_prompt_token_count);
747 }
748 if let Some(thoughts_token_count) = new.thoughts_token_count {
749 usage.thoughts_token_count = Some(thoughts_token_count);
750 }
751 if let Some(total_token_count) = new.total_token_count {
752 usage.total_token_count = Some(total_token_count);
753 }
754}
755
756fn convert_usage(usage: &UsageMetadata) -> language_model::TokenUsage {
757 let prompt_tokens = usage.prompt_token_count.unwrap_or(0);
758 let cached_tokens = usage.cached_content_token_count.unwrap_or(0);
759 let input_tokens = prompt_tokens - cached_tokens;
760 let output_tokens = usage.candidates_token_count.unwrap_or(0);
761
762 language_model::TokenUsage {
763 input_tokens,
764 output_tokens,
765 cache_read_input_tokens: cached_tokens,
766 cache_creation_input_tokens: 0,
767 }
768}
769
770struct ConfigurationView {
771 api_key_editor: Entity<Editor>,
772 state: gpui::Entity<State>,
773 load_credentials_task: Option<Task<()>>,
774}
775
776impl ConfigurationView {
777 fn new(state: gpui::Entity<State>, window: &mut Window, cx: &mut Context<Self>) -> Self {
778 cx.observe(&state, |_, _, cx| {
779 cx.notify();
780 })
781 .detach();
782
783 let load_credentials_task = Some(cx.spawn_in(window, {
784 let state = state.clone();
785 async move |this, cx| {
786 if let Some(task) = state
787 .update(cx, |state, cx| state.authenticate(cx))
788 .log_err()
789 {
790 // We don't log an error, because "not signed in" is also an error.
791 let _ = task.await;
792 }
793 this.update(cx, |this, cx| {
794 this.load_credentials_task = None;
795 cx.notify();
796 })
797 .log_err();
798 }
799 }));
800
801 Self {
802 api_key_editor: cx.new(|cx| {
803 let mut editor = Editor::single_line(window, cx);
804 editor.set_placeholder_text("AIzaSy...", cx);
805 editor
806 }),
807 state,
808 load_credentials_task,
809 }
810 }
811
812 fn save_api_key(&mut self, _: &menu::Confirm, window: &mut Window, cx: &mut Context<Self>) {
813 let api_key = self.api_key_editor.read(cx).text(cx);
814 if api_key.is_empty() {
815 return;
816 }
817
818 let state = self.state.clone();
819 cx.spawn_in(window, async move |_, cx| {
820 state
821 .update(cx, |state, cx| state.set_api_key(api_key, cx))?
822 .await
823 })
824 .detach_and_log_err(cx);
825
826 cx.notify();
827 }
828
829 fn reset_api_key(&mut self, window: &mut Window, cx: &mut Context<Self>) {
830 self.api_key_editor
831 .update(cx, |editor, cx| editor.set_text("", window, cx));
832
833 let state = self.state.clone();
834 cx.spawn_in(window, async move |_, cx| {
835 state.update(cx, |state, cx| state.reset_api_key(cx))?.await
836 })
837 .detach_and_log_err(cx);
838
839 cx.notify();
840 }
841
842 fn render_api_key_editor(&self, cx: &mut Context<Self>) -> impl IntoElement {
843 let settings = ThemeSettings::get_global(cx);
844 let text_style = TextStyle {
845 color: cx.theme().colors().text,
846 font_family: settings.ui_font.family.clone(),
847 font_features: settings.ui_font.features.clone(),
848 font_fallbacks: settings.ui_font.fallbacks.clone(),
849 font_size: rems(0.875).into(),
850 font_weight: settings.ui_font.weight,
851 font_style: FontStyle::Normal,
852 line_height: relative(1.3),
853 white_space: WhiteSpace::Normal,
854 ..Default::default()
855 };
856 EditorElement::new(
857 &self.api_key_editor,
858 EditorStyle {
859 background: cx.theme().colors().editor_background,
860 local_player: cx.theme().players().local(),
861 text: text_style,
862 ..Default::default()
863 },
864 )
865 }
866
867 fn should_render_editor(&self, cx: &mut Context<Self>) -> bool {
868 !self.state.read(cx).is_authenticated()
869 }
870}
871
872impl Render for ConfigurationView {
873 fn render(&mut self, _: &mut Window, cx: &mut Context<Self>) -> impl IntoElement {
874 let env_var_set = self.state.read(cx).api_key_from_env;
875
876 if self.load_credentials_task.is_some() {
877 div().child(Label::new("Loading credentials...")).into_any()
878 } else if self.should_render_editor(cx) {
879 v_flex()
880 .size_full()
881 .on_action(cx.listener(Self::save_api_key))
882 .child(Label::new("To use Zed's assistant with Google AI, you need to add an API key. Follow these steps:"))
883 .child(
884 List::new()
885 .child(InstructionListItem::new(
886 "Create one by visiting",
887 Some("Google AI's console"),
888 Some("https://aistudio.google.com/app/apikey"),
889 ))
890 .child(InstructionListItem::text_only(
891 "Paste your API key below and hit enter to start using the assistant",
892 )),
893 )
894 .child(
895 h_flex()
896 .w_full()
897 .my_2()
898 .px_2()
899 .py_1()
900 .bg(cx.theme().colors().editor_background)
901 .border_1()
902 .border_color(cx.theme().colors().border)
903 .rounded_sm()
904 .child(self.render_api_key_editor(cx)),
905 )
906 .child(
907 Label::new(
908 format!("You can also assign the {GOOGLE_AI_API_KEY_VAR} environment variable and restart Zed."),
909 )
910 .size(LabelSize::Small).color(Color::Muted),
911 )
912 .into_any()
913 } else {
914 h_flex()
915 .mt_1()
916 .p_1()
917 .justify_between()
918 .rounded_md()
919 .border_1()
920 .border_color(cx.theme().colors().border)
921 .bg(cx.theme().colors().background)
922 .child(
923 h_flex()
924 .gap_1()
925 .child(Icon::new(IconName::Check).color(Color::Success))
926 .child(Label::new(if env_var_set {
927 format!("API key set in {GOOGLE_AI_API_KEY_VAR} environment variable.")
928 } else {
929 "API key configured.".to_string()
930 })),
931 )
932 .child(
933 Button::new("reset-key", "Reset Key")
934 .label_size(LabelSize::Small)
935 .icon(Some(IconName::Trash))
936 .icon_size(IconSize::Small)
937 .icon_position(IconPosition::Start)
938 .disabled(env_var_set)
939 .when(env_var_set, |this| {
940 this.tooltip(Tooltip::text(format!("To reset your API key, unset the {GOOGLE_AI_API_KEY_VAR} environment variable.")))
941 })
942 .on_click(cx.listener(|this, _, window, cx| this.reset_api_key(window, cx))),
943 )
944 .into_any()
945 }
946 }
947}