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 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 PROVIDER_ID
211 }
212
213 fn name(&self) -> LanguageModelProviderName {
214 PROVIDER_NAME
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 PROVIDER_ID
338 }
339
340 fn provider_name(&self) -> LanguageModelProviderName {
341 PROVIDER_NAME
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.await.map_err(LanguageModelCompletionError::from)?;
427 Ok(GoogleEventMapper::new().map_stream(response))
428 });
429 async move { Ok(future.await?.boxed()) }.boxed()
430 }
431}
432
433pub fn into_google(
434 mut request: LanguageModelRequest,
435 model_id: String,
436 mode: GoogleModelMode,
437) -> google_ai::GenerateContentRequest {
438 fn map_content(content: Vec<MessageContent>) -> Vec<Part> {
439 content
440 .into_iter()
441 .flat_map(|content| match content {
442 language_model::MessageContent::Text(text) => {
443 if !text.is_empty() {
444 vec![Part::TextPart(google_ai::TextPart { text })]
445 } else {
446 vec![]
447 }
448 }
449 language_model::MessageContent::Thinking {
450 text: _,
451 signature: Some(signature),
452 } => {
453 if !signature.is_empty() {
454 vec![Part::ThoughtPart(google_ai::ThoughtPart {
455 thought: true,
456 thought_signature: signature,
457 })]
458 } else {
459 vec![]
460 }
461 }
462 language_model::MessageContent::Thinking { .. } => {
463 vec![]
464 }
465 language_model::MessageContent::RedactedThinking(_) => vec![],
466 language_model::MessageContent::Image(image) => {
467 vec![Part::InlineDataPart(google_ai::InlineDataPart {
468 inline_data: google_ai::GenerativeContentBlob {
469 mime_type: "image/png".to_string(),
470 data: image.source.to_string(),
471 },
472 })]
473 }
474 language_model::MessageContent::ToolUse(tool_use) => {
475 vec![Part::FunctionCallPart(google_ai::FunctionCallPart {
476 function_call: google_ai::FunctionCall {
477 name: tool_use.name.to_string(),
478 args: tool_use.input,
479 },
480 })]
481 }
482 language_model::MessageContent::ToolResult(tool_result) => {
483 match tool_result.content {
484 language_model::LanguageModelToolResultContent::Text(text) => {
485 vec![Part::FunctionResponsePart(
486 google_ai::FunctionResponsePart {
487 function_response: google_ai::FunctionResponse {
488 name: tool_result.tool_name.to_string(),
489 // The API expects a valid JSON object
490 response: serde_json::json!({
491 "output": text
492 }),
493 },
494 },
495 )]
496 }
497 language_model::LanguageModelToolResultContent::Image(image) => {
498 vec![
499 Part::FunctionResponsePart(google_ai::FunctionResponsePart {
500 function_response: google_ai::FunctionResponse {
501 name: tool_result.tool_name.to_string(),
502 // The API expects a valid JSON object
503 response: serde_json::json!({
504 "output": "Tool responded with an image"
505 }),
506 },
507 }),
508 Part::InlineDataPart(google_ai::InlineDataPart {
509 inline_data: google_ai::GenerativeContentBlob {
510 mime_type: "image/png".to_string(),
511 data: image.source.to_string(),
512 },
513 }),
514 ]
515 }
516 }
517 }
518 })
519 .collect()
520 }
521
522 let system_instructions = if request
523 .messages
524 .first()
525 .map_or(false, |msg| matches!(msg.role, Role::System))
526 {
527 let message = request.messages.remove(0);
528 Some(SystemInstruction {
529 parts: map_content(message.content),
530 })
531 } else {
532 None
533 };
534
535 google_ai::GenerateContentRequest {
536 model: google_ai::ModelName { model_id },
537 system_instruction: system_instructions,
538 contents: request
539 .messages
540 .into_iter()
541 .filter_map(|message| {
542 let parts = map_content(message.content);
543 if parts.is_empty() {
544 None
545 } else {
546 Some(google_ai::Content {
547 parts,
548 role: match message.role {
549 Role::User => google_ai::Role::User,
550 Role::Assistant => google_ai::Role::Model,
551 Role::System => google_ai::Role::User, // Google AI doesn't have a system role
552 },
553 })
554 }
555 })
556 .collect(),
557 generation_config: Some(google_ai::GenerationConfig {
558 candidate_count: Some(1),
559 stop_sequences: Some(request.stop),
560 max_output_tokens: None,
561 temperature: request.temperature.map(|t| t as f64).or(Some(1.0)),
562 thinking_config: match mode {
563 GoogleModelMode::Thinking { budget_tokens } => {
564 budget_tokens.map(|thinking_budget| ThinkingConfig { thinking_budget })
565 }
566 GoogleModelMode::Default => None,
567 },
568 top_p: None,
569 top_k: None,
570 }),
571 safety_settings: None,
572 tools: (request.tools.len() > 0).then(|| {
573 vec![google_ai::Tool {
574 function_declarations: request
575 .tools
576 .into_iter()
577 .map(|tool| FunctionDeclaration {
578 name: tool.name,
579 description: tool.description,
580 parameters: tool.input_schema,
581 })
582 .collect(),
583 }]
584 }),
585 tool_config: request.tool_choice.map(|choice| google_ai::ToolConfig {
586 function_calling_config: google_ai::FunctionCallingConfig {
587 mode: match choice {
588 LanguageModelToolChoice::Auto => google_ai::FunctionCallingMode::Auto,
589 LanguageModelToolChoice::Any => google_ai::FunctionCallingMode::Any,
590 LanguageModelToolChoice::None => google_ai::FunctionCallingMode::None,
591 },
592 allowed_function_names: None,
593 },
594 }),
595 }
596}
597
598pub struct GoogleEventMapper {
599 usage: UsageMetadata,
600 stop_reason: StopReason,
601}
602
603impl GoogleEventMapper {
604 pub fn new() -> Self {
605 Self {
606 usage: UsageMetadata::default(),
607 stop_reason: StopReason::EndTurn,
608 }
609 }
610
611 pub fn map_stream(
612 mut self,
613 events: Pin<Box<dyn Send + Stream<Item = Result<GenerateContentResponse>>>>,
614 ) -> impl Stream<Item = Result<LanguageModelCompletionEvent, LanguageModelCompletionError>>
615 {
616 events
617 .map(Some)
618 .chain(futures::stream::once(async { None }))
619 .flat_map(move |event| {
620 futures::stream::iter(match event {
621 Some(Ok(event)) => self.map_event(event),
622 Some(Err(error)) => {
623 vec![Err(LanguageModelCompletionError::from(error))]
624 }
625 None => vec![Ok(LanguageModelCompletionEvent::Stop(self.stop_reason))],
626 })
627 })
628 }
629
630 pub fn map_event(
631 &mut self,
632 event: GenerateContentResponse,
633 ) -> Vec<Result<LanguageModelCompletionEvent, LanguageModelCompletionError>> {
634 static TOOL_CALL_COUNTER: AtomicU64 = AtomicU64::new(0);
635
636 let mut events: Vec<_> = Vec::new();
637 let mut wants_to_use_tool = false;
638 if let Some(usage_metadata) = event.usage_metadata {
639 update_usage(&mut self.usage, &usage_metadata);
640 events.push(Ok(LanguageModelCompletionEvent::UsageUpdate(
641 convert_usage(&self.usage),
642 )))
643 }
644 if let Some(candidates) = event.candidates {
645 for candidate in candidates {
646 if let Some(finish_reason) = candidate.finish_reason.as_deref() {
647 self.stop_reason = match finish_reason {
648 "STOP" => StopReason::EndTurn,
649 "MAX_TOKENS" => StopReason::MaxTokens,
650 _ => {
651 log::error!("Unexpected google finish_reason: {finish_reason}");
652 StopReason::EndTurn
653 }
654 };
655 }
656 candidate
657 .content
658 .parts
659 .into_iter()
660 .for_each(|part| match part {
661 Part::TextPart(text_part) => {
662 events.push(Ok(LanguageModelCompletionEvent::Text(text_part.text)))
663 }
664 Part::InlineDataPart(_) => {}
665 Part::FunctionCallPart(function_call_part) => {
666 wants_to_use_tool = true;
667 let name: Arc<str> = function_call_part.function_call.name.into();
668 let next_tool_id =
669 TOOL_CALL_COUNTER.fetch_add(1, atomic::Ordering::SeqCst);
670 let id: LanguageModelToolUseId =
671 format!("{}-{}", name, next_tool_id).into();
672
673 events.push(Ok(LanguageModelCompletionEvent::ToolUse(
674 LanguageModelToolUse {
675 id,
676 name,
677 is_input_complete: true,
678 raw_input: function_call_part.function_call.args.to_string(),
679 input: function_call_part.function_call.args,
680 },
681 )));
682 }
683 Part::FunctionResponsePart(_) => {}
684 Part::ThoughtPart(part) => {
685 events.push(Ok(LanguageModelCompletionEvent::Thinking {
686 text: "(Encrypted thought)".to_string(), // TODO: Can we populate this from thought summaries?
687 signature: Some(part.thought_signature),
688 }));
689 }
690 });
691 }
692 }
693
694 // Even when Gemini wants to use a Tool, the API
695 // responds with `finish_reason: STOP`
696 if wants_to_use_tool {
697 self.stop_reason = StopReason::ToolUse;
698 events.push(Ok(LanguageModelCompletionEvent::Stop(StopReason::ToolUse)));
699 }
700 events
701 }
702}
703
704pub fn count_google_tokens(
705 request: LanguageModelRequest,
706 cx: &App,
707) -> BoxFuture<'static, Result<u64>> {
708 // We couldn't use the GoogleLanguageModelProvider to count tokens because the github copilot doesn't have the access to google_ai directly.
709 // So we have to use tokenizer from tiktoken_rs to count tokens.
710 cx.background_spawn(async move {
711 let messages = request
712 .messages
713 .into_iter()
714 .map(|message| tiktoken_rs::ChatCompletionRequestMessage {
715 role: match message.role {
716 Role::User => "user".into(),
717 Role::Assistant => "assistant".into(),
718 Role::System => "system".into(),
719 },
720 content: Some(message.string_contents()),
721 name: None,
722 function_call: None,
723 })
724 .collect::<Vec<_>>();
725
726 // Tiktoken doesn't yet support these models, so we manually use the
727 // same tokenizer as GPT-4.
728 tiktoken_rs::num_tokens_from_messages("gpt-4", &messages).map(|tokens| tokens as u64)
729 })
730 .boxed()
731}
732
733fn update_usage(usage: &mut UsageMetadata, new: &UsageMetadata) {
734 if let Some(prompt_token_count) = new.prompt_token_count {
735 usage.prompt_token_count = Some(prompt_token_count);
736 }
737 if let Some(cached_content_token_count) = new.cached_content_token_count {
738 usage.cached_content_token_count = Some(cached_content_token_count);
739 }
740 if let Some(candidates_token_count) = new.candidates_token_count {
741 usage.candidates_token_count = Some(candidates_token_count);
742 }
743 if let Some(tool_use_prompt_token_count) = new.tool_use_prompt_token_count {
744 usage.tool_use_prompt_token_count = Some(tool_use_prompt_token_count);
745 }
746 if let Some(thoughts_token_count) = new.thoughts_token_count {
747 usage.thoughts_token_count = Some(thoughts_token_count);
748 }
749 if let Some(total_token_count) = new.total_token_count {
750 usage.total_token_count = Some(total_token_count);
751 }
752}
753
754fn convert_usage(usage: &UsageMetadata) -> language_model::TokenUsage {
755 let prompt_tokens = usage.prompt_token_count.unwrap_or(0);
756 let cached_tokens = usage.cached_content_token_count.unwrap_or(0);
757 let input_tokens = prompt_tokens - cached_tokens;
758 let output_tokens = usage.candidates_token_count.unwrap_or(0);
759
760 language_model::TokenUsage {
761 input_tokens,
762 output_tokens,
763 cache_read_input_tokens: cached_tokens,
764 cache_creation_input_tokens: 0,
765 }
766}
767
768struct ConfigurationView {
769 api_key_editor: Entity<Editor>,
770 state: gpui::Entity<State>,
771 load_credentials_task: Option<Task<()>>,
772}
773
774impl ConfigurationView {
775 fn new(state: gpui::Entity<State>, window: &mut Window, cx: &mut Context<Self>) -> Self {
776 cx.observe(&state, |_, _, cx| {
777 cx.notify();
778 })
779 .detach();
780
781 let load_credentials_task = Some(cx.spawn_in(window, {
782 let state = state.clone();
783 async move |this, cx| {
784 if let Some(task) = state
785 .update(cx, |state, cx| state.authenticate(cx))
786 .log_err()
787 {
788 // We don't log an error, because "not signed in" is also an error.
789 let _ = task.await;
790 }
791 this.update(cx, |this, cx| {
792 this.load_credentials_task = None;
793 cx.notify();
794 })
795 .log_err();
796 }
797 }));
798
799 Self {
800 api_key_editor: cx.new(|cx| {
801 let mut editor = Editor::single_line(window, cx);
802 editor.set_placeholder_text("AIzaSy...", cx);
803 editor
804 }),
805 state,
806 load_credentials_task,
807 }
808 }
809
810 fn save_api_key(&mut self, _: &menu::Confirm, window: &mut Window, cx: &mut Context<Self>) {
811 let api_key = self.api_key_editor.read(cx).text(cx);
812 if api_key.is_empty() {
813 return;
814 }
815
816 let state = self.state.clone();
817 cx.spawn_in(window, async move |_, cx| {
818 state
819 .update(cx, |state, cx| state.set_api_key(api_key, cx))?
820 .await
821 })
822 .detach_and_log_err(cx);
823
824 cx.notify();
825 }
826
827 fn reset_api_key(&mut self, window: &mut Window, cx: &mut Context<Self>) {
828 self.api_key_editor
829 .update(cx, |editor, cx| editor.set_text("", window, cx));
830
831 let state = self.state.clone();
832 cx.spawn_in(window, async move |_, cx| {
833 state.update(cx, |state, cx| state.reset_api_key(cx))?.await
834 })
835 .detach_and_log_err(cx);
836
837 cx.notify();
838 }
839
840 fn render_api_key_editor(&self, cx: &mut Context<Self>) -> impl IntoElement {
841 let settings = ThemeSettings::get_global(cx);
842 let text_style = TextStyle {
843 color: cx.theme().colors().text,
844 font_family: settings.ui_font.family.clone(),
845 font_features: settings.ui_font.features.clone(),
846 font_fallbacks: settings.ui_font.fallbacks.clone(),
847 font_size: rems(0.875).into(),
848 font_weight: settings.ui_font.weight,
849 font_style: FontStyle::Normal,
850 line_height: relative(1.3),
851 white_space: WhiteSpace::Normal,
852 ..Default::default()
853 };
854 EditorElement::new(
855 &self.api_key_editor,
856 EditorStyle {
857 background: cx.theme().colors().editor_background,
858 local_player: cx.theme().players().local(),
859 text: text_style,
860 ..Default::default()
861 },
862 )
863 }
864
865 fn should_render_editor(&self, cx: &mut Context<Self>) -> bool {
866 !self.state.read(cx).is_authenticated()
867 }
868}
869
870impl Render for ConfigurationView {
871 fn render(&mut self, _: &mut Window, cx: &mut Context<Self>) -> impl IntoElement {
872 let env_var_set = self.state.read(cx).api_key_from_env;
873
874 if self.load_credentials_task.is_some() {
875 div().child(Label::new("Loading credentials...")).into_any()
876 } else if self.should_render_editor(cx) {
877 v_flex()
878 .size_full()
879 .on_action(cx.listener(Self::save_api_key))
880 .child(Label::new("To use Zed's assistant with Google AI, you need to add an API key. Follow these steps:"))
881 .child(
882 List::new()
883 .child(InstructionListItem::new(
884 "Create one by visiting",
885 Some("Google AI's console"),
886 Some("https://aistudio.google.com/app/apikey"),
887 ))
888 .child(InstructionListItem::text_only(
889 "Paste your API key below and hit enter to start using the assistant",
890 )),
891 )
892 .child(
893 h_flex()
894 .w_full()
895 .my_2()
896 .px_2()
897 .py_1()
898 .bg(cx.theme().colors().editor_background)
899 .border_1()
900 .border_color(cx.theme().colors().border)
901 .rounded_sm()
902 .child(self.render_api_key_editor(cx)),
903 )
904 .child(
905 Label::new(
906 format!("You can also assign the {GOOGLE_AI_API_KEY_VAR} environment variable and restart Zed."),
907 )
908 .size(LabelSize::Small).color(Color::Muted),
909 )
910 .into_any()
911 } else {
912 h_flex()
913 .mt_1()
914 .p_1()
915 .justify_between()
916 .rounded_md()
917 .border_1()
918 .border_color(cx.theme().colors().border)
919 .bg(cx.theme().colors().background)
920 .child(
921 h_flex()
922 .gap_1()
923 .child(Icon::new(IconName::Check).color(Color::Success))
924 .child(Label::new(if env_var_set {
925 format!("API key set in {GOOGLE_AI_API_KEY_VAR} environment variable.")
926 } else {
927 "API key configured.".to_string()
928 })),
929 )
930 .child(
931 Button::new("reset-key", "Reset Key")
932 .label_size(LabelSize::Small)
933 .icon(Some(IconName::Trash))
934 .icon_size(IconSize::Small)
935 .icon_position(IconPosition::Start)
936 .disabled(env_var_set)
937 .when(env_var_set, |this| {
938 this.tooltip(Tooltip::text(format!("To reset your API key, unset the {GOOGLE_AI_API_KEY_VAR} environment variable.")))
939 })
940 .on_click(cx.listener(|this, _, window, cx| this.reset_api_key(window, cx))),
941 )
942 .into_any()
943 }
944 }
945}