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 LanguageModelCompletionError,
413 >,
414 > {
415 let request = into_google(
416 request,
417 self.model.request_id().to_string(),
418 self.model.mode(),
419 );
420 let request = self.stream_completion(request, cx);
421 let future = self.request_limiter.stream(async move {
422 let response = request
423 .await
424 .map_err(|err| LanguageModelCompletionError::Other(anyhow!(err)))?;
425 Ok(GoogleEventMapper::new().map_stream(response))
426 });
427 async move { Ok(future.await?.boxed()) }.boxed()
428 }
429}
430
431pub fn into_google(
432 mut request: LanguageModelRequest,
433 model_id: String,
434 mode: GoogleModelMode,
435) -> google_ai::GenerateContentRequest {
436 fn map_content(content: Vec<MessageContent>) -> Vec<Part> {
437 content
438 .into_iter()
439 .flat_map(|content| match content {
440 language_model::MessageContent::Text(text) => {
441 if !text.is_empty() {
442 vec![Part::TextPart(google_ai::TextPart { text })]
443 } else {
444 vec![]
445 }
446 }
447 language_model::MessageContent::Thinking {
448 text: _,
449 signature: Some(signature),
450 } => {
451 if !signature.is_empty() {
452 vec![Part::ThoughtPart(google_ai::ThoughtPart {
453 thought: true,
454 thought_signature: signature,
455 })]
456 } else {
457 vec![]
458 }
459 }
460 language_model::MessageContent::Thinking { .. } => {
461 vec![]
462 }
463 language_model::MessageContent::RedactedThinking(_) => vec![],
464 language_model::MessageContent::Image(image) => {
465 vec![Part::InlineDataPart(google_ai::InlineDataPart {
466 inline_data: google_ai::GenerativeContentBlob {
467 mime_type: "image/png".to_string(),
468 data: image.source.to_string(),
469 },
470 })]
471 }
472 language_model::MessageContent::ToolUse(tool_use) => {
473 vec![Part::FunctionCallPart(google_ai::FunctionCallPart {
474 function_call: google_ai::FunctionCall {
475 name: tool_use.name.to_string(),
476 args: tool_use.input,
477 },
478 })]
479 }
480 language_model::MessageContent::ToolResult(tool_result) => {
481 match tool_result.content {
482 language_model::LanguageModelToolResultContent::Text(text) => {
483 vec![Part::FunctionResponsePart(
484 google_ai::FunctionResponsePart {
485 function_response: google_ai::FunctionResponse {
486 name: tool_result.tool_name.to_string(),
487 // The API expects a valid JSON object
488 response: serde_json::json!({
489 "output": text
490 }),
491 },
492 },
493 )]
494 }
495 language_model::LanguageModelToolResultContent::Image(image) => {
496 vec![
497 Part::FunctionResponsePart(google_ai::FunctionResponsePart {
498 function_response: google_ai::FunctionResponse {
499 name: tool_result.tool_name.to_string(),
500 // The API expects a valid JSON object
501 response: serde_json::json!({
502 "output": "Tool responded with an image"
503 }),
504 },
505 }),
506 Part::InlineDataPart(google_ai::InlineDataPart {
507 inline_data: google_ai::GenerativeContentBlob {
508 mime_type: "image/png".to_string(),
509 data: image.source.to_string(),
510 },
511 }),
512 ]
513 }
514 }
515 }
516 })
517 .collect()
518 }
519
520 let system_instructions = if request
521 .messages
522 .first()
523 .map_or(false, |msg| matches!(msg.role, Role::System))
524 {
525 let message = request.messages.remove(0);
526 Some(SystemInstruction {
527 parts: map_content(message.content),
528 })
529 } else {
530 None
531 };
532
533 google_ai::GenerateContentRequest {
534 model: google_ai::ModelName { model_id },
535 system_instruction: system_instructions,
536 contents: request
537 .messages
538 .into_iter()
539 .filter_map(|message| {
540 let parts = map_content(message.content);
541 if parts.is_empty() {
542 None
543 } else {
544 Some(google_ai::Content {
545 parts,
546 role: match message.role {
547 Role::User => google_ai::Role::User,
548 Role::Assistant => google_ai::Role::Model,
549 Role::System => google_ai::Role::User, // Google AI doesn't have a system role
550 },
551 })
552 }
553 })
554 .collect(),
555 generation_config: Some(google_ai::GenerationConfig {
556 candidate_count: Some(1),
557 stop_sequences: Some(request.stop),
558 max_output_tokens: None,
559 temperature: request.temperature.map(|t| t as f64).or(Some(1.0)),
560 thinking_config: match mode {
561 GoogleModelMode::Thinking { budget_tokens } => {
562 budget_tokens.map(|thinking_budget| ThinkingConfig { thinking_budget })
563 }
564 GoogleModelMode::Default => None,
565 },
566 top_p: None,
567 top_k: None,
568 }),
569 safety_settings: None,
570 tools: (request.tools.len() > 0).then(|| {
571 vec![google_ai::Tool {
572 function_declarations: request
573 .tools
574 .into_iter()
575 .map(|tool| FunctionDeclaration {
576 name: tool.name,
577 description: tool.description,
578 parameters: tool.input_schema,
579 })
580 .collect(),
581 }]
582 }),
583 tool_config: request.tool_choice.map(|choice| google_ai::ToolConfig {
584 function_calling_config: google_ai::FunctionCallingConfig {
585 mode: match choice {
586 LanguageModelToolChoice::Auto => google_ai::FunctionCallingMode::Auto,
587 LanguageModelToolChoice::Any => google_ai::FunctionCallingMode::Any,
588 LanguageModelToolChoice::None => google_ai::FunctionCallingMode::None,
589 },
590 allowed_function_names: None,
591 },
592 }),
593 }
594}
595
596pub struct GoogleEventMapper {
597 usage: UsageMetadata,
598 stop_reason: StopReason,
599}
600
601impl GoogleEventMapper {
602 pub fn new() -> Self {
603 Self {
604 usage: UsageMetadata::default(),
605 stop_reason: StopReason::EndTurn,
606 }
607 }
608
609 pub fn map_stream(
610 mut self,
611 events: Pin<Box<dyn Send + Stream<Item = Result<GenerateContentResponse>>>>,
612 ) -> impl Stream<Item = Result<LanguageModelCompletionEvent, LanguageModelCompletionError>>
613 {
614 events
615 .map(Some)
616 .chain(futures::stream::once(async { None }))
617 .flat_map(move |event| {
618 futures::stream::iter(match event {
619 Some(Ok(event)) => self.map_event(event),
620 Some(Err(error)) => {
621 vec![Err(LanguageModelCompletionError::Other(anyhow!(error)))]
622 }
623 None => vec![Ok(LanguageModelCompletionEvent::Stop(self.stop_reason))],
624 })
625 })
626 }
627
628 pub fn map_event(
629 &mut self,
630 event: GenerateContentResponse,
631 ) -> Vec<Result<LanguageModelCompletionEvent, LanguageModelCompletionError>> {
632 static TOOL_CALL_COUNTER: AtomicU64 = AtomicU64::new(0);
633
634 let mut events: Vec<_> = Vec::new();
635 let mut wants_to_use_tool = false;
636 if let Some(usage_metadata) = event.usage_metadata {
637 update_usage(&mut self.usage, &usage_metadata);
638 events.push(Ok(LanguageModelCompletionEvent::UsageUpdate(
639 convert_usage(&self.usage),
640 )))
641 }
642 if let Some(candidates) = event.candidates {
643 for candidate in candidates {
644 if let Some(finish_reason) = candidate.finish_reason.as_deref() {
645 self.stop_reason = match finish_reason {
646 "STOP" => StopReason::EndTurn,
647 "MAX_TOKENS" => StopReason::MaxTokens,
648 _ => {
649 log::error!("Unexpected google finish_reason: {finish_reason}");
650 StopReason::EndTurn
651 }
652 };
653 }
654 candidate
655 .content
656 .parts
657 .into_iter()
658 .for_each(|part| match part {
659 Part::TextPart(text_part) => {
660 events.push(Ok(LanguageModelCompletionEvent::Text(text_part.text)))
661 }
662 Part::InlineDataPart(_) => {}
663 Part::FunctionCallPart(function_call_part) => {
664 wants_to_use_tool = true;
665 let name: Arc<str> = function_call_part.function_call.name.into();
666 let next_tool_id =
667 TOOL_CALL_COUNTER.fetch_add(1, atomic::Ordering::SeqCst);
668 let id: LanguageModelToolUseId =
669 format!("{}-{}", name, next_tool_id).into();
670
671 events.push(Ok(LanguageModelCompletionEvent::ToolUse(
672 LanguageModelToolUse {
673 id,
674 name,
675 is_input_complete: true,
676 raw_input: function_call_part.function_call.args.to_string(),
677 input: function_call_part.function_call.args,
678 },
679 )));
680 }
681 Part::FunctionResponsePart(_) => {}
682 Part::ThoughtPart(part) => {
683 events.push(Ok(LanguageModelCompletionEvent::Thinking {
684 text: "(Encrypted thought)".to_string(), // TODO: Can we populate this from thought summaries?
685 signature: Some(part.thought_signature),
686 }));
687 }
688 });
689 }
690 }
691
692 // Even when Gemini wants to use a Tool, the API
693 // responds with `finish_reason: STOP`
694 if wants_to_use_tool {
695 self.stop_reason = StopReason::ToolUse;
696 events.push(Ok(LanguageModelCompletionEvent::Stop(StopReason::ToolUse)));
697 }
698 events
699 }
700}
701
702pub fn count_google_tokens(
703 request: LanguageModelRequest,
704 cx: &App,
705) -> BoxFuture<'static, Result<usize>> {
706 // We couldn't use the GoogleLanguageModelProvider to count tokens because the github copilot doesn't have the access to google_ai directly.
707 // So we have to use tokenizer from tiktoken_rs to count tokens.
708 cx.background_spawn(async move {
709 let messages = request
710 .messages
711 .into_iter()
712 .map(|message| tiktoken_rs::ChatCompletionRequestMessage {
713 role: match message.role {
714 Role::User => "user".into(),
715 Role::Assistant => "assistant".into(),
716 Role::System => "system".into(),
717 },
718 content: Some(message.string_contents()),
719 name: None,
720 function_call: None,
721 })
722 .collect::<Vec<_>>();
723
724 // Tiktoken doesn't yet support these models, so we manually use the
725 // same tokenizer as GPT-4.
726 tiktoken_rs::num_tokens_from_messages("gpt-4", &messages)
727 })
728 .boxed()
729}
730
731fn update_usage(usage: &mut UsageMetadata, new: &UsageMetadata) {
732 if let Some(prompt_token_count) = new.prompt_token_count {
733 usage.prompt_token_count = Some(prompt_token_count);
734 }
735 if let Some(cached_content_token_count) = new.cached_content_token_count {
736 usage.cached_content_token_count = Some(cached_content_token_count);
737 }
738 if let Some(candidates_token_count) = new.candidates_token_count {
739 usage.candidates_token_count = Some(candidates_token_count);
740 }
741 if let Some(tool_use_prompt_token_count) = new.tool_use_prompt_token_count {
742 usage.tool_use_prompt_token_count = Some(tool_use_prompt_token_count);
743 }
744 if let Some(thoughts_token_count) = new.thoughts_token_count {
745 usage.thoughts_token_count = Some(thoughts_token_count);
746 }
747 if let Some(total_token_count) = new.total_token_count {
748 usage.total_token_count = Some(total_token_count);
749 }
750}
751
752fn convert_usage(usage: &UsageMetadata) -> language_model::TokenUsage {
753 let prompt_tokens = usage.prompt_token_count.unwrap_or(0) as u32;
754 let cached_tokens = usage.cached_content_token_count.unwrap_or(0) as u32;
755 let input_tokens = prompt_tokens - cached_tokens;
756 let output_tokens = usage.candidates_token_count.unwrap_or(0) as u32;
757
758 language_model::TokenUsage {
759 input_tokens,
760 output_tokens,
761 cache_read_input_tokens: cached_tokens,
762 cache_creation_input_tokens: 0,
763 }
764}
765
766struct ConfigurationView {
767 api_key_editor: Entity<Editor>,
768 state: gpui::Entity<State>,
769 load_credentials_task: Option<Task<()>>,
770}
771
772impl ConfigurationView {
773 fn new(state: gpui::Entity<State>, window: &mut Window, cx: &mut Context<Self>) -> Self {
774 cx.observe(&state, |_, _, cx| {
775 cx.notify();
776 })
777 .detach();
778
779 let load_credentials_task = Some(cx.spawn_in(window, {
780 let state = state.clone();
781 async move |this, cx| {
782 if let Some(task) = state
783 .update(cx, |state, cx| state.authenticate(cx))
784 .log_err()
785 {
786 // We don't log an error, because "not signed in" is also an error.
787 let _ = task.await;
788 }
789 this.update(cx, |this, cx| {
790 this.load_credentials_task = None;
791 cx.notify();
792 })
793 .log_err();
794 }
795 }));
796
797 Self {
798 api_key_editor: cx.new(|cx| {
799 let mut editor = Editor::single_line(window, cx);
800 editor.set_placeholder_text("AIzaSy...", cx);
801 editor
802 }),
803 state,
804 load_credentials_task,
805 }
806 }
807
808 fn save_api_key(&mut self, _: &menu::Confirm, window: &mut Window, cx: &mut Context<Self>) {
809 let api_key = self.api_key_editor.read(cx).text(cx);
810 if api_key.is_empty() {
811 return;
812 }
813
814 let state = self.state.clone();
815 cx.spawn_in(window, async move |_, cx| {
816 state
817 .update(cx, |state, cx| state.set_api_key(api_key, cx))?
818 .await
819 })
820 .detach_and_log_err(cx);
821
822 cx.notify();
823 }
824
825 fn reset_api_key(&mut self, window: &mut Window, cx: &mut Context<Self>) {
826 self.api_key_editor
827 .update(cx, |editor, cx| editor.set_text("", window, cx));
828
829 let state = self.state.clone();
830 cx.spawn_in(window, async move |_, cx| {
831 state.update(cx, |state, cx| state.reset_api_key(cx))?.await
832 })
833 .detach_and_log_err(cx);
834
835 cx.notify();
836 }
837
838 fn render_api_key_editor(&self, cx: &mut Context<Self>) -> impl IntoElement {
839 let settings = ThemeSettings::get_global(cx);
840 let text_style = TextStyle {
841 color: cx.theme().colors().text,
842 font_family: settings.ui_font.family.clone(),
843 font_features: settings.ui_font.features.clone(),
844 font_fallbacks: settings.ui_font.fallbacks.clone(),
845 font_size: rems(0.875).into(),
846 font_weight: settings.ui_font.weight,
847 font_style: FontStyle::Normal,
848 line_height: relative(1.3),
849 white_space: WhiteSpace::Normal,
850 ..Default::default()
851 };
852 EditorElement::new(
853 &self.api_key_editor,
854 EditorStyle {
855 background: cx.theme().colors().editor_background,
856 local_player: cx.theme().players().local(),
857 text: text_style,
858 ..Default::default()
859 },
860 )
861 }
862
863 fn should_render_editor(&self, cx: &mut Context<Self>) -> bool {
864 !self.state.read(cx).is_authenticated()
865 }
866}
867
868impl Render for ConfigurationView {
869 fn render(&mut self, _: &mut Window, cx: &mut Context<Self>) -> impl IntoElement {
870 let env_var_set = self.state.read(cx).api_key_from_env;
871
872 if self.load_credentials_task.is_some() {
873 div().child(Label::new("Loading credentials...")).into_any()
874 } else if self.should_render_editor(cx) {
875 v_flex()
876 .size_full()
877 .on_action(cx.listener(Self::save_api_key))
878 .child(Label::new("To use Zed's assistant with Google AI, you need to add an API key. Follow these steps:"))
879 .child(
880 List::new()
881 .child(InstructionListItem::new(
882 "Create one by visiting",
883 Some("Google AI's console"),
884 Some("https://aistudio.google.com/app/apikey"),
885 ))
886 .child(InstructionListItem::text_only(
887 "Paste your API key below and hit enter to start using the assistant",
888 )),
889 )
890 .child(
891 h_flex()
892 .w_full()
893 .my_2()
894 .px_2()
895 .py_1()
896 .bg(cx.theme().colors().editor_background)
897 .border_1()
898 .border_color(cx.theme().colors().border)
899 .rounded_sm()
900 .child(self.render_api_key_editor(cx)),
901 )
902 .child(
903 Label::new(
904 format!("You can also assign the {GOOGLE_AI_API_KEY_VAR} environment variable and restart Zed."),
905 )
906 .size(LabelSize::Small).color(Color::Muted),
907 )
908 .into_any()
909 } else {
910 h_flex()
911 .mt_1()
912 .p_1()
913 .justify_between()
914 .rounded_md()
915 .border_1()
916 .border_color(cx.theme().colors().border)
917 .bg(cx.theme().colors().background)
918 .child(
919 h_flex()
920 .gap_1()
921 .child(Icon::new(IconName::Check).color(Color::Success))
922 .child(Label::new(if env_var_set {
923 format!("API key set in {GOOGLE_AI_API_KEY_VAR} environment variable.")
924 } else {
925 "API key configured.".to_string()
926 })),
927 )
928 .child(
929 Button::new("reset-key", "Reset Key")
930 .label_size(LabelSize::Small)
931 .icon(Some(IconName::Trash))
932 .icon_size(IconSize::Small)
933 .icon_position(IconPosition::Start)
934 .disabled(env_var_set)
935 .when(env_var_set, |this| {
936 this.tooltip(Tooltip::text(format!("To reset your API key, unset the {GOOGLE_AI_API_KEY_VAR} environment variable.")))
937 })
938 .on_click(cx.listener(|this, _, window, cx| this.reset_api_key(window, cx))),
939 )
940 .into_any()
941 }
942 }
943}