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: LanguageModelProviderId = language_model::GOOGLE_PROVIDER_ID;
41const PROVIDER_NAME: LanguageModelProviderName = language_model::GOOGLE_PROVIDER_NAME;
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 GEMINI_API_KEY_VAR: &str = "GEMINI_API_KEY";
98const GOOGLE_AI_API_KEY_VAR: &str = "GOOGLE_AI_API_KEY";
99
100impl State {
101 fn is_authenticated(&self) -> bool {
102 self.api_key.is_some()
103 }
104
105 fn reset_api_key(&self, cx: &mut Context<Self>) -> Task<Result<()>> {
106 let credentials_provider = <dyn CredentialsProvider>::global(cx);
107 let api_url = AllLanguageModelSettings::get_global(cx)
108 .google
109 .api_url
110 .clone();
111 cx.spawn(async move |this, cx| {
112 credentials_provider
113 .delete_credentials(&api_url, cx)
114 .await
115 .log_err();
116 this.update(cx, |this, cx| {
117 this.api_key = None;
118 this.api_key_from_env = false;
119 cx.notify();
120 })
121 })
122 }
123
124 fn set_api_key(&mut self, api_key: String, cx: &mut Context<Self>) -> Task<Result<()>> {
125 let credentials_provider = <dyn CredentialsProvider>::global(cx);
126 let api_url = AllLanguageModelSettings::get_global(cx)
127 .google
128 .api_url
129 .clone();
130 cx.spawn(async move |this, cx| {
131 credentials_provider
132 .write_credentials(&api_url, "Bearer", api_key.as_bytes(), cx)
133 .await?;
134 this.update(cx, |this, cx| {
135 this.api_key = Some(api_key);
136 cx.notify();
137 })
138 })
139 }
140
141 fn authenticate(&self, cx: &mut Context<Self>) -> Task<Result<(), AuthenticateError>> {
142 if self.is_authenticated() {
143 return Task::ready(Ok(()));
144 }
145
146 let credentials_provider = <dyn CredentialsProvider>::global(cx);
147 let api_url = AllLanguageModelSettings::get_global(cx)
148 .google
149 .api_url
150 .clone();
151
152 cx.spawn(async move |this, cx| {
153 let (api_key, from_env) = if let Ok(api_key) = std::env::var(GOOGLE_AI_API_KEY_VAR) {
154 (api_key, true)
155 } else if let Ok(api_key) = std::env::var(GEMINI_API_KEY_VAR) {
156 (api_key, true)
157 } else {
158 let (_, api_key) = credentials_provider
159 .read_credentials(&api_url, cx)
160 .await?
161 .ok_or(AuthenticateError::CredentialsNotFound)?;
162 (
163 String::from_utf8(api_key).context("invalid {PROVIDER_NAME} API key")?,
164 false,
165 )
166 };
167
168 this.update(cx, |this, cx| {
169 this.api_key = Some(api_key);
170 this.api_key_from_env = from_env;
171 cx.notify();
172 })?;
173
174 Ok(())
175 })
176 }
177}
178
179impl GoogleLanguageModelProvider {
180 pub fn new(http_client: Arc<dyn HttpClient>, cx: &mut App) -> Self {
181 let state = cx.new(|cx| State {
182 api_key: None,
183 api_key_from_env: false,
184 _subscription: cx.observe_global::<SettingsStore>(|_, cx| {
185 cx.notify();
186 }),
187 });
188
189 Self { http_client, state }
190 }
191
192 fn create_language_model(&self, model: google_ai::Model) -> Arc<dyn LanguageModel> {
193 Arc::new(GoogleLanguageModel {
194 id: LanguageModelId::from(model.id().to_string()),
195 model,
196 state: self.state.clone(),
197 http_client: self.http_client.clone(),
198 request_limiter: RateLimiter::new(4),
199 })
200 }
201}
202
203impl LanguageModelProviderState for GoogleLanguageModelProvider {
204 type ObservableEntity = State;
205
206 fn observable_entity(&self) -> Option<gpui::Entity<Self::ObservableEntity>> {
207 Some(self.state.clone())
208 }
209}
210
211impl LanguageModelProvider for GoogleLanguageModelProvider {
212 fn id(&self) -> LanguageModelProviderId {
213 PROVIDER_ID
214 }
215
216 fn name(&self) -> LanguageModelProviderName {
217 PROVIDER_NAME
218 }
219
220 fn icon(&self) -> IconName {
221 IconName::AiGoogle
222 }
223
224 fn default_model(&self, _cx: &App) -> Option<Arc<dyn LanguageModel>> {
225 Some(self.create_language_model(google_ai::Model::default()))
226 }
227
228 fn default_fast_model(&self, _cx: &App) -> Option<Arc<dyn LanguageModel>> {
229 Some(self.create_language_model(google_ai::Model::default_fast()))
230 }
231
232 fn provided_models(&self, cx: &App) -> Vec<Arc<dyn LanguageModel>> {
233 let mut models = BTreeMap::default();
234
235 // Add base models from google_ai::Model::iter()
236 for model in google_ai::Model::iter() {
237 if !matches!(model, google_ai::Model::Custom { .. }) {
238 models.insert(model.id().to_string(), model);
239 }
240 }
241
242 // Override with available models from settings
243 for model in &AllLanguageModelSettings::get_global(cx)
244 .google
245 .available_models
246 {
247 models.insert(
248 model.name.clone(),
249 google_ai::Model::Custom {
250 name: model.name.clone(),
251 display_name: model.display_name.clone(),
252 max_tokens: model.max_tokens,
253 mode: model.mode.unwrap_or_default().into(),
254 },
255 );
256 }
257
258 models
259 .into_values()
260 .map(|model| {
261 Arc::new(GoogleLanguageModel {
262 id: LanguageModelId::from(model.id().to_string()),
263 model,
264 state: self.state.clone(),
265 http_client: self.http_client.clone(),
266 request_limiter: RateLimiter::new(4),
267 }) as Arc<dyn LanguageModel>
268 })
269 .collect()
270 }
271
272 fn is_authenticated(&self, cx: &App) -> bool {
273 self.state.read(cx).is_authenticated()
274 }
275
276 fn authenticate(&self, cx: &mut App) -> Task<Result<(), AuthenticateError>> {
277 self.state.update(cx, |state, cx| state.authenticate(cx))
278 }
279
280 fn configuration_view(
281 &self,
282 _target_agent: language_model::ConfigurationViewTargetAgent,
283 window: &mut Window,
284 cx: &mut App,
285 ) -> AnyView {
286 cx.new(|cx| ConfigurationView::new(self.state.clone(), window, cx))
287 .into()
288 }
289
290 fn reset_credentials(&self, cx: &mut App) -> Task<Result<()>> {
291 self.state.update(cx, |state, cx| state.reset_api_key(cx))
292 }
293}
294
295pub struct GoogleLanguageModel {
296 id: LanguageModelId,
297 model: google_ai::Model,
298 state: gpui::Entity<State>,
299 http_client: Arc<dyn HttpClient>,
300 request_limiter: RateLimiter,
301}
302
303impl GoogleLanguageModel {
304 fn stream_completion(
305 &self,
306 request: google_ai::GenerateContentRequest,
307 cx: &AsyncApp,
308 ) -> BoxFuture<
309 'static,
310 Result<futures::stream::BoxStream<'static, Result<GenerateContentResponse>>>,
311 > {
312 let http_client = self.http_client.clone();
313
314 let Ok((api_key, api_url)) = cx.read_entity(&self.state, |state, cx| {
315 let settings = &AllLanguageModelSettings::get_global(cx).google;
316 (state.api_key.clone(), settings.api_url.clone())
317 }) else {
318 return futures::future::ready(Err(anyhow!("App state dropped"))).boxed();
319 };
320
321 async move {
322 let api_key = api_key.context("Missing Google API key")?;
323 let request = google_ai::stream_generate_content(
324 http_client.as_ref(),
325 &api_url,
326 &api_key,
327 request,
328 );
329 request.await.context("failed to stream completion")
330 }
331 .boxed()
332 }
333}
334
335impl LanguageModel for GoogleLanguageModel {
336 fn id(&self) -> LanguageModelId {
337 self.id.clone()
338 }
339
340 fn name(&self) -> LanguageModelName {
341 LanguageModelName::from(self.model.display_name().to_string())
342 }
343
344 fn provider_id(&self) -> LanguageModelProviderId {
345 PROVIDER_ID
346 }
347
348 fn provider_name(&self) -> LanguageModelProviderName {
349 PROVIDER_NAME
350 }
351
352 fn supports_tools(&self) -> bool {
353 self.model.supports_tools()
354 }
355
356 fn supports_images(&self) -> bool {
357 self.model.supports_images()
358 }
359
360 fn supports_tool_choice(&self, choice: LanguageModelToolChoice) -> bool {
361 match choice {
362 LanguageModelToolChoice::Auto
363 | LanguageModelToolChoice::Any
364 | LanguageModelToolChoice::None => true,
365 }
366 }
367
368 fn tool_input_format(&self) -> LanguageModelToolSchemaFormat {
369 LanguageModelToolSchemaFormat::JsonSchemaSubset
370 }
371
372 fn telemetry_id(&self) -> String {
373 format!("google/{}", self.model.request_id())
374 }
375
376 fn max_token_count(&self) -> u64 {
377 self.model.max_token_count()
378 }
379
380 fn max_output_tokens(&self) -> Option<u64> {
381 self.model.max_output_tokens()
382 }
383
384 fn count_tokens(
385 &self,
386 request: LanguageModelRequest,
387 cx: &App,
388 ) -> BoxFuture<'static, Result<u64>> {
389 let model_id = self.model.request_id().to_string();
390 let request = into_google(request, model_id.clone(), self.model.mode());
391 let http_client = self.http_client.clone();
392 let api_key = self.state.read(cx).api_key.clone();
393
394 let settings = &AllLanguageModelSettings::get_global(cx).google;
395 let api_url = settings.api_url.clone();
396
397 async move {
398 let api_key = api_key.context("Missing Google API key")?;
399 let response = google_ai::count_tokens(
400 http_client.as_ref(),
401 &api_url,
402 &api_key,
403 google_ai::CountTokensRequest {
404 generate_content_request: request,
405 },
406 )
407 .await?;
408 Ok(response.total_tokens)
409 }
410 .boxed()
411 }
412
413 fn stream_completion(
414 &self,
415 request: LanguageModelRequest,
416 cx: &AsyncApp,
417 ) -> BoxFuture<
418 'static,
419 Result<
420 futures::stream::BoxStream<
421 'static,
422 Result<LanguageModelCompletionEvent, LanguageModelCompletionError>,
423 >,
424 LanguageModelCompletionError,
425 >,
426 > {
427 let request = into_google(
428 request,
429 self.model.request_id().to_string(),
430 self.model.mode(),
431 );
432 let request = self.stream_completion(request, cx);
433 let future = self.request_limiter.stream(async move {
434 let response = request.await.map_err(LanguageModelCompletionError::from)?;
435 Ok(GoogleEventMapper::new().map_stream(response))
436 });
437 async move { Ok(future.await?.boxed()) }.boxed()
438 }
439}
440
441pub fn into_google(
442 mut request: LanguageModelRequest,
443 model_id: String,
444 mode: GoogleModelMode,
445) -> google_ai::GenerateContentRequest {
446 fn map_content(content: Vec<MessageContent>) -> Vec<Part> {
447 content
448 .into_iter()
449 .flat_map(|content| match content {
450 language_model::MessageContent::Text(text) => {
451 if !text.is_empty() {
452 vec![Part::TextPart(google_ai::TextPart { text })]
453 } else {
454 vec![]
455 }
456 }
457 language_model::MessageContent::Thinking {
458 text: _,
459 signature: Some(signature),
460 } => {
461 if !signature.is_empty() {
462 vec![Part::ThoughtPart(google_ai::ThoughtPart {
463 thought: true,
464 thought_signature: signature,
465 })]
466 } else {
467 vec![]
468 }
469 }
470 language_model::MessageContent::Thinking { .. } => {
471 vec![]
472 }
473 language_model::MessageContent::RedactedThinking(_) => vec![],
474 language_model::MessageContent::Image(image) => {
475 vec![Part::InlineDataPart(google_ai::InlineDataPart {
476 inline_data: google_ai::GenerativeContentBlob {
477 mime_type: "image/png".to_string(),
478 data: image.source.to_string(),
479 },
480 })]
481 }
482 language_model::MessageContent::ToolUse(tool_use) => {
483 vec![Part::FunctionCallPart(google_ai::FunctionCallPart {
484 function_call: google_ai::FunctionCall {
485 name: tool_use.name.to_string(),
486 args: tool_use.input,
487 },
488 })]
489 }
490 language_model::MessageContent::ToolResult(tool_result) => {
491 match tool_result.content {
492 language_model::LanguageModelToolResultContent::Text(text) => {
493 vec![Part::FunctionResponsePart(
494 google_ai::FunctionResponsePart {
495 function_response: google_ai::FunctionResponse {
496 name: tool_result.tool_name.to_string(),
497 // The API expects a valid JSON object
498 response: serde_json::json!({
499 "output": text
500 }),
501 },
502 },
503 )]
504 }
505 language_model::LanguageModelToolResultContent::Image(image) => {
506 vec![
507 Part::FunctionResponsePart(google_ai::FunctionResponsePart {
508 function_response: google_ai::FunctionResponse {
509 name: tool_result.tool_name.to_string(),
510 // The API expects a valid JSON object
511 response: serde_json::json!({
512 "output": "Tool responded with an image"
513 }),
514 },
515 }),
516 Part::InlineDataPart(google_ai::InlineDataPart {
517 inline_data: google_ai::GenerativeContentBlob {
518 mime_type: "image/png".to_string(),
519 data: image.source.to_string(),
520 },
521 }),
522 ]
523 }
524 }
525 }
526 })
527 .collect()
528 }
529
530 let system_instructions = if request
531 .messages
532 .first()
533 .is_some_and(|msg| matches!(msg.role, Role::System))
534 {
535 let message = request.messages.remove(0);
536 Some(SystemInstruction {
537 parts: map_content(message.content),
538 })
539 } else {
540 None
541 };
542
543 google_ai::GenerateContentRequest {
544 model: google_ai::ModelName { model_id },
545 system_instruction: system_instructions,
546 contents: request
547 .messages
548 .into_iter()
549 .filter_map(|message| {
550 let parts = map_content(message.content);
551 if parts.is_empty() {
552 None
553 } else {
554 Some(google_ai::Content {
555 parts,
556 role: match message.role {
557 Role::User => google_ai::Role::User,
558 Role::Assistant => google_ai::Role::Model,
559 Role::System => google_ai::Role::User, // Google AI doesn't have a system role
560 },
561 })
562 }
563 })
564 .collect(),
565 generation_config: Some(google_ai::GenerationConfig {
566 candidate_count: Some(1),
567 stop_sequences: Some(request.stop),
568 max_output_tokens: None,
569 temperature: request.temperature.map(|t| t as f64).or(Some(1.0)),
570 thinking_config: match (request.thinking_allowed, mode) {
571 (true, GoogleModelMode::Thinking { budget_tokens }) => {
572 budget_tokens.map(|thinking_budget| ThinkingConfig { thinking_budget })
573 }
574 _ => None,
575 },
576 top_p: None,
577 top_k: None,
578 }),
579 safety_settings: None,
580 tools: (request.tools.len() > 0).then(|| {
581 vec![google_ai::Tool {
582 function_declarations: request
583 .tools
584 .into_iter()
585 .map(|tool| FunctionDeclaration {
586 name: tool.name,
587 description: tool.description,
588 parameters: tool.input_schema,
589 })
590 .collect(),
591 }]
592 }),
593 tool_config: request.tool_choice.map(|choice| google_ai::ToolConfig {
594 function_calling_config: google_ai::FunctionCallingConfig {
595 mode: match choice {
596 LanguageModelToolChoice::Auto => google_ai::FunctionCallingMode::Auto,
597 LanguageModelToolChoice::Any => google_ai::FunctionCallingMode::Any,
598 LanguageModelToolChoice::None => google_ai::FunctionCallingMode::None,
599 },
600 allowed_function_names: None,
601 },
602 }),
603 }
604}
605
606pub struct GoogleEventMapper {
607 usage: UsageMetadata,
608 stop_reason: StopReason,
609}
610
611impl GoogleEventMapper {
612 pub fn new() -> Self {
613 Self {
614 usage: UsageMetadata::default(),
615 stop_reason: StopReason::EndTurn,
616 }
617 }
618
619 pub fn map_stream(
620 mut self,
621 events: Pin<Box<dyn Send + Stream<Item = Result<GenerateContentResponse>>>>,
622 ) -> impl Stream<Item = Result<LanguageModelCompletionEvent, LanguageModelCompletionError>>
623 {
624 events
625 .map(Some)
626 .chain(futures::stream::once(async { None }))
627 .flat_map(move |event| {
628 futures::stream::iter(match event {
629 Some(Ok(event)) => self.map_event(event),
630 Some(Err(error)) => {
631 vec![Err(LanguageModelCompletionError::from(error))]
632 }
633 None => vec![Ok(LanguageModelCompletionEvent::Stop(self.stop_reason))],
634 })
635 })
636 }
637
638 pub fn map_event(
639 &mut self,
640 event: GenerateContentResponse,
641 ) -> Vec<Result<LanguageModelCompletionEvent, LanguageModelCompletionError>> {
642 static TOOL_CALL_COUNTER: AtomicU64 = AtomicU64::new(0);
643
644 let mut events: Vec<_> = Vec::new();
645 let mut wants_to_use_tool = false;
646 if let Some(usage_metadata) = event.usage_metadata {
647 update_usage(&mut self.usage, &usage_metadata);
648 events.push(Ok(LanguageModelCompletionEvent::UsageUpdate(
649 convert_usage(&self.usage),
650 )))
651 }
652 if let Some(candidates) = event.candidates {
653 for candidate in candidates {
654 if let Some(finish_reason) = candidate.finish_reason.as_deref() {
655 self.stop_reason = match finish_reason {
656 "STOP" => StopReason::EndTurn,
657 "MAX_TOKENS" => StopReason::MaxTokens,
658 _ => {
659 log::error!("Unexpected google finish_reason: {finish_reason}");
660 StopReason::EndTurn
661 }
662 };
663 }
664 candidate
665 .content
666 .parts
667 .into_iter()
668 .for_each(|part| match part {
669 Part::TextPart(text_part) => {
670 events.push(Ok(LanguageModelCompletionEvent::Text(text_part.text)))
671 }
672 Part::InlineDataPart(_) => {}
673 Part::FunctionCallPart(function_call_part) => {
674 wants_to_use_tool = true;
675 let name: Arc<str> = function_call_part.function_call.name.into();
676 let next_tool_id =
677 TOOL_CALL_COUNTER.fetch_add(1, atomic::Ordering::SeqCst);
678 let id: LanguageModelToolUseId =
679 format!("{}-{}", name, next_tool_id).into();
680
681 events.push(Ok(LanguageModelCompletionEvent::ToolUse(
682 LanguageModelToolUse {
683 id,
684 name,
685 is_input_complete: true,
686 raw_input: function_call_part.function_call.args.to_string(),
687 input: function_call_part.function_call.args,
688 },
689 )));
690 }
691 Part::FunctionResponsePart(_) => {}
692 Part::ThoughtPart(part) => {
693 events.push(Ok(LanguageModelCompletionEvent::Thinking {
694 text: "(Encrypted thought)".to_string(), // TODO: Can we populate this from thought summaries?
695 signature: Some(part.thought_signature),
696 }));
697 }
698 });
699 }
700 }
701
702 // Even when Gemini wants to use a Tool, the API
703 // responds with `finish_reason: STOP`
704 if wants_to_use_tool {
705 self.stop_reason = StopReason::ToolUse;
706 events.push(Ok(LanguageModelCompletionEvent::Stop(StopReason::ToolUse)));
707 }
708 events
709 }
710}
711
712pub fn count_google_tokens(
713 request: LanguageModelRequest,
714 cx: &App,
715) -> BoxFuture<'static, Result<u64>> {
716 // We couldn't use the GoogleLanguageModelProvider to count tokens because the github copilot doesn't have the access to google_ai directly.
717 // So we have to use tokenizer from tiktoken_rs to count tokens.
718 cx.background_spawn(async move {
719 let messages = request
720 .messages
721 .into_iter()
722 .map(|message| tiktoken_rs::ChatCompletionRequestMessage {
723 role: match message.role {
724 Role::User => "user".into(),
725 Role::Assistant => "assistant".into(),
726 Role::System => "system".into(),
727 },
728 content: Some(message.string_contents()),
729 name: None,
730 function_call: None,
731 })
732 .collect::<Vec<_>>();
733
734 // Tiktoken doesn't yet support these models, so we manually use the
735 // same tokenizer as GPT-4.
736 tiktoken_rs::num_tokens_from_messages("gpt-4", &messages).map(|tokens| tokens as u64)
737 })
738 .boxed()
739}
740
741fn update_usage(usage: &mut UsageMetadata, new: &UsageMetadata) {
742 if let Some(prompt_token_count) = new.prompt_token_count {
743 usage.prompt_token_count = Some(prompt_token_count);
744 }
745 if let Some(cached_content_token_count) = new.cached_content_token_count {
746 usage.cached_content_token_count = Some(cached_content_token_count);
747 }
748 if let Some(candidates_token_count) = new.candidates_token_count {
749 usage.candidates_token_count = Some(candidates_token_count);
750 }
751 if let Some(tool_use_prompt_token_count) = new.tool_use_prompt_token_count {
752 usage.tool_use_prompt_token_count = Some(tool_use_prompt_token_count);
753 }
754 if let Some(thoughts_token_count) = new.thoughts_token_count {
755 usage.thoughts_token_count = Some(thoughts_token_count);
756 }
757 if let Some(total_token_count) = new.total_token_count {
758 usage.total_token_count = Some(total_token_count);
759 }
760}
761
762fn convert_usage(usage: &UsageMetadata) -> language_model::TokenUsage {
763 let prompt_tokens = usage.prompt_token_count.unwrap_or(0);
764 let cached_tokens = usage.cached_content_token_count.unwrap_or(0);
765 let input_tokens = prompt_tokens - cached_tokens;
766 let output_tokens = usage.candidates_token_count.unwrap_or(0);
767
768 language_model::TokenUsage {
769 input_tokens,
770 output_tokens,
771 cache_read_input_tokens: cached_tokens,
772 cache_creation_input_tokens: 0,
773 }
774}
775
776struct ConfigurationView {
777 api_key_editor: Entity<Editor>,
778 state: gpui::Entity<State>,
779 load_credentials_task: Option<Task<()>>,
780}
781
782impl ConfigurationView {
783 fn new(state: gpui::Entity<State>, window: &mut Window, cx: &mut Context<Self>) -> Self {
784 cx.observe(&state, |_, _, cx| {
785 cx.notify();
786 })
787 .detach();
788
789 let load_credentials_task = Some(cx.spawn_in(window, {
790 let state = state.clone();
791 async move |this, cx| {
792 if let Some(task) = state
793 .update(cx, |state, cx| state.authenticate(cx))
794 .log_err()
795 {
796 // We don't log an error, because "not signed in" is also an error.
797 let _ = task.await;
798 }
799 this.update(cx, |this, cx| {
800 this.load_credentials_task = None;
801 cx.notify();
802 })
803 .log_err();
804 }
805 }));
806
807 Self {
808 api_key_editor: cx.new(|cx| {
809 let mut editor = Editor::single_line(window, cx);
810 editor.set_placeholder_text("AIzaSy...", cx);
811 editor
812 }),
813 state,
814 load_credentials_task,
815 }
816 }
817
818 fn save_api_key(&mut self, _: &menu::Confirm, window: &mut Window, cx: &mut Context<Self>) {
819 let api_key = self.api_key_editor.read(cx).text(cx);
820 if api_key.is_empty() {
821 return;
822 }
823
824 let state = self.state.clone();
825 cx.spawn_in(window, async move |_, cx| {
826 state
827 .update(cx, |state, cx| state.set_api_key(api_key, cx))?
828 .await
829 })
830 .detach_and_log_err(cx);
831
832 cx.notify();
833 }
834
835 fn reset_api_key(&mut self, window: &mut Window, cx: &mut Context<Self>) {
836 self.api_key_editor
837 .update(cx, |editor, cx| editor.set_text("", window, cx));
838
839 let state = self.state.clone();
840 cx.spawn_in(window, async move |_, cx| {
841 state.update(cx, |state, cx| state.reset_api_key(cx))?.await
842 })
843 .detach_and_log_err(cx);
844
845 cx.notify();
846 }
847
848 fn render_api_key_editor(&self, cx: &mut Context<Self>) -> impl IntoElement {
849 let settings = ThemeSettings::get_global(cx);
850 let text_style = TextStyle {
851 color: cx.theme().colors().text,
852 font_family: settings.ui_font.family.clone(),
853 font_features: settings.ui_font.features.clone(),
854 font_fallbacks: settings.ui_font.fallbacks.clone(),
855 font_size: rems(0.875).into(),
856 font_weight: settings.ui_font.weight,
857 font_style: FontStyle::Normal,
858 line_height: relative(1.3),
859 white_space: WhiteSpace::Normal,
860 ..Default::default()
861 };
862 EditorElement::new(
863 &self.api_key_editor,
864 EditorStyle {
865 background: cx.theme().colors().editor_background,
866 local_player: cx.theme().players().local(),
867 text: text_style,
868 ..Default::default()
869 },
870 )
871 }
872
873 fn should_render_editor(&self, cx: &mut Context<Self>) -> bool {
874 !self.state.read(cx).is_authenticated()
875 }
876}
877
878impl Render for ConfigurationView {
879 fn render(&mut self, _: &mut Window, cx: &mut Context<Self>) -> impl IntoElement {
880 let env_var_set = self.state.read(cx).api_key_from_env;
881
882 if self.load_credentials_task.is_some() {
883 div().child(Label::new("Loading credentials...")).into_any()
884 } else if self.should_render_editor(cx) {
885 v_flex()
886 .size_full()
887 .on_action(cx.listener(Self::save_api_key))
888 .child(Label::new("To use Zed's agent with Google AI, you need to add an API key. Follow these steps:"))
889 .child(
890 List::new()
891 .child(InstructionListItem::new(
892 "Create one by visiting",
893 Some("Google AI's console"),
894 Some("https://aistudio.google.com/app/apikey"),
895 ))
896 .child(InstructionListItem::text_only(
897 "Paste your API key below and hit enter to start using the assistant",
898 )),
899 )
900 .child(
901 h_flex()
902 .w_full()
903 .my_2()
904 .px_2()
905 .py_1()
906 .bg(cx.theme().colors().editor_background)
907 .border_1()
908 .border_color(cx.theme().colors().border)
909 .rounded_sm()
910 .child(self.render_api_key_editor(cx)),
911 )
912 .child(
913 Label::new(
914 format!("You can also assign the {GEMINI_API_KEY_VAR} environment variable and restart Zed."),
915 )
916 .size(LabelSize::Small).color(Color::Muted),
917 )
918 .into_any()
919 } else {
920 h_flex()
921 .mt_1()
922 .p_1()
923 .justify_between()
924 .rounded_md()
925 .border_1()
926 .border_color(cx.theme().colors().border)
927 .bg(cx.theme().colors().background)
928 .child(
929 h_flex()
930 .gap_1()
931 .child(Icon::new(IconName::Check).color(Color::Success))
932 .child(Label::new(if env_var_set {
933 format!("API key set in {GEMINI_API_KEY_VAR} environment variable.")
934 } else {
935 "API key configured.".to_string()
936 })),
937 )
938 .child(
939 Button::new("reset-key", "Reset Key")
940 .label_size(LabelSize::Small)
941 .icon(Some(IconName::Trash))
942 .icon_size(IconSize::Small)
943 .icon_position(IconPosition::Start)
944 .disabled(env_var_set)
945 .when(env_var_set, |this| {
946 this.tooltip(Tooltip::text(format!("To reset your API key, make sure {GEMINI_API_KEY_VAR} and {GOOGLE_AI_API_KEY_VAR} environment variables are unset.")))
947 })
948 .on_click(cx.listener(|this, _, window, cx| this.reset_api_key(window, cx))),
949 )
950 .into_any()
951 }
952 }
953}