1use crate::AllLanguageModelSettings;
2use crate::ui::InstructionListItem;
3use anthropic::{
4 AnthropicError, AnthropicModelMode, ContentDelta, Event, ResponseContent, ToolResultContent,
5 ToolResultPart, Usage,
6};
7use anyhow::{Context as _, Result, anyhow};
8use collections::{BTreeMap, HashMap};
9use credentials_provider::CredentialsProvider;
10use editor::{Editor, EditorElement, EditorStyle};
11use futures::Stream;
12use futures::{FutureExt, StreamExt, future::BoxFuture, stream::BoxStream};
13use gpui::{
14 AnyView, App, AsyncApp, Context, Entity, FontStyle, Subscription, Task, TextStyle, WhiteSpace,
15};
16use http_client::HttpClient;
17use language_model::{
18 AuthenticateError, ConfigurationViewTargetAgent, LanguageModel,
19 LanguageModelCacheConfiguration, LanguageModelCompletionError, LanguageModelId,
20 LanguageModelName, LanguageModelProvider, LanguageModelProviderId, LanguageModelProviderName,
21 LanguageModelProviderState, LanguageModelRequest, LanguageModelToolChoice,
22 LanguageModelToolResultContent, MessageContent, RateLimiter, Role,
23};
24use language_model::{LanguageModelCompletionEvent, LanguageModelToolUse, StopReason};
25use settings::{Settings, SettingsStore};
26use std::pin::Pin;
27use std::str::FromStr;
28use std::sync::Arc;
29use strum::IntoEnumIterator;
30use theme::ThemeSettings;
31use ui::{Icon, IconName, List, Tooltip, prelude::*};
32use util::ResultExt;
33
34pub use settings::AnthropicAvailableModel as AvailableModel;
35
36const PROVIDER_ID: LanguageModelProviderId = language_model::ANTHROPIC_PROVIDER_ID;
37const PROVIDER_NAME: LanguageModelProviderName = language_model::ANTHROPIC_PROVIDER_NAME;
38
39#[derive(Default, Clone, Debug, PartialEq)]
40pub struct AnthropicSettings {
41 pub api_url: String,
42 /// Extend Zed's list of Anthropic models.
43 pub available_models: Vec<AvailableModel>,
44}
45
46pub struct AnthropicLanguageModelProvider {
47 http_client: Arc<dyn HttpClient>,
48 state: gpui::Entity<State>,
49}
50
51const ANTHROPIC_API_KEY_VAR: &str = "ANTHROPIC_API_KEY";
52
53pub struct State {
54 api_key: Option<String>,
55 api_key_from_env: bool,
56 _subscription: Subscription,
57}
58
59impl State {
60 fn reset_api_key(&self, cx: &mut Context<Self>) -> Task<Result<()>> {
61 let credentials_provider = <dyn CredentialsProvider>::global(cx);
62 let api_url = AllLanguageModelSettings::get_global(cx)
63 .anthropic
64 .api_url
65 .clone();
66 cx.spawn(async move |this, cx| {
67 credentials_provider
68 .delete_credentials(&api_url, cx)
69 .await
70 .ok();
71 this.update(cx, |this, cx| {
72 this.api_key = None;
73 this.api_key_from_env = false;
74 cx.notify();
75 })
76 })
77 }
78
79 fn set_api_key(&mut self, api_key: String, cx: &mut Context<Self>) -> Task<Result<()>> {
80 let credentials_provider = <dyn CredentialsProvider>::global(cx);
81 let api_url = AllLanguageModelSettings::get_global(cx)
82 .anthropic
83 .api_url
84 .clone();
85 cx.spawn(async move |this, cx| {
86 credentials_provider
87 .write_credentials(&api_url, "Bearer", api_key.as_bytes(), cx)
88 .await
89 .ok();
90
91 this.update(cx, |this, cx| {
92 this.api_key = Some(api_key);
93 cx.notify();
94 })
95 })
96 }
97
98 fn is_authenticated(&self) -> bool {
99 self.api_key.is_some()
100 }
101
102 fn authenticate(&self, cx: &mut Context<Self>) -> Task<Result<(), AuthenticateError>> {
103 if self.is_authenticated() {
104 return Task::ready(Ok(()));
105 }
106
107 let key = AnthropicLanguageModelProvider::api_key(cx);
108
109 cx.spawn(async move |this, cx| {
110 let key = key.await?;
111
112 this.update(cx, |this, cx| {
113 this.api_key = Some(key.key);
114 this.api_key_from_env = key.from_env;
115 cx.notify();
116 })?;
117
118 Ok(())
119 })
120 }
121}
122
123pub struct ApiKey {
124 pub key: String,
125 pub from_env: bool,
126}
127
128impl AnthropicLanguageModelProvider {
129 pub fn new(http_client: Arc<dyn HttpClient>, cx: &mut App) -> Self {
130 let state = cx.new(|cx| State {
131 api_key: None,
132 api_key_from_env: false,
133 _subscription: cx.observe_global::<SettingsStore>(|_, cx| {
134 cx.notify();
135 }),
136 });
137
138 Self { http_client, state }
139 }
140
141 fn create_language_model(&self, model: anthropic::Model) -> Arc<dyn LanguageModel> {
142 Arc::new(AnthropicModel {
143 id: LanguageModelId::from(model.id().to_string()),
144 model,
145 state: self.state.clone(),
146 http_client: self.http_client.clone(),
147 request_limiter: RateLimiter::new(4),
148 })
149 }
150
151 pub fn api_key(cx: &mut App) -> Task<Result<ApiKey, AuthenticateError>> {
152 let credentials_provider = <dyn CredentialsProvider>::global(cx);
153 let api_url = AllLanguageModelSettings::get_global(cx)
154 .anthropic
155 .api_url
156 .clone();
157
158 if let Ok(key) = std::env::var(ANTHROPIC_API_KEY_VAR) {
159 Task::ready(Ok(ApiKey {
160 key,
161 from_env: true,
162 }))
163 } else {
164 cx.spawn(async move |cx| {
165 let (_, api_key) = credentials_provider
166 .read_credentials(&api_url, cx)
167 .await?
168 .ok_or(AuthenticateError::CredentialsNotFound)?;
169
170 Ok(ApiKey {
171 key: String::from_utf8(api_key).context("invalid {PROVIDER_NAME} API key")?,
172 from_env: false,
173 })
174 })
175 }
176 }
177}
178
179impl LanguageModelProviderState for AnthropicLanguageModelProvider {
180 type ObservableEntity = State;
181
182 fn observable_entity(&self) -> Option<gpui::Entity<Self::ObservableEntity>> {
183 Some(self.state.clone())
184 }
185}
186
187impl LanguageModelProvider for AnthropicLanguageModelProvider {
188 fn id(&self) -> LanguageModelProviderId {
189 PROVIDER_ID
190 }
191
192 fn name(&self) -> LanguageModelProviderName {
193 PROVIDER_NAME
194 }
195
196 fn icon(&self) -> IconName {
197 IconName::AiAnthropic
198 }
199
200 fn default_model(&self, _cx: &App) -> Option<Arc<dyn LanguageModel>> {
201 Some(self.create_language_model(anthropic::Model::default()))
202 }
203
204 fn default_fast_model(&self, _cx: &App) -> Option<Arc<dyn LanguageModel>> {
205 Some(self.create_language_model(anthropic::Model::default_fast()))
206 }
207
208 fn recommended_models(&self, _cx: &App) -> Vec<Arc<dyn LanguageModel>> {
209 [
210 anthropic::Model::ClaudeSonnet4,
211 anthropic::Model::ClaudeSonnet4Thinking,
212 ]
213 .into_iter()
214 .map(|model| self.create_language_model(model))
215 .collect()
216 }
217
218 fn provided_models(&self, cx: &App) -> Vec<Arc<dyn LanguageModel>> {
219 let mut models = BTreeMap::default();
220
221 // Add base models from anthropic::Model::iter()
222 for model in anthropic::Model::iter() {
223 if !matches!(model, anthropic::Model::Custom { .. }) {
224 models.insert(model.id().to_string(), model);
225 }
226 }
227
228 // Override with available models from settings
229 for model in AllLanguageModelSettings::get_global(cx)
230 .anthropic
231 .available_models
232 .iter()
233 {
234 models.insert(
235 model.name.clone(),
236 anthropic::Model::Custom {
237 name: model.name.clone(),
238 display_name: model.display_name.clone(),
239 max_tokens: model.max_tokens,
240 tool_override: model.tool_override.clone(),
241 cache_configuration: model.cache_configuration.as_ref().map(|config| {
242 anthropic::AnthropicModelCacheConfiguration {
243 max_cache_anchors: config.max_cache_anchors,
244 should_speculate: config.should_speculate,
245 min_total_token: config.min_total_token,
246 }
247 }),
248 max_output_tokens: model.max_output_tokens,
249 default_temperature: model.default_temperature,
250 extra_beta_headers: model.extra_beta_headers.clone(),
251 mode: model.mode.clone().unwrap_or_default().into(),
252 },
253 );
254 }
255
256 models
257 .into_values()
258 .map(|model| self.create_language_model(model))
259 .collect()
260 }
261
262 fn is_authenticated(&self, cx: &App) -> bool {
263 self.state.read(cx).is_authenticated()
264 }
265
266 fn authenticate(&self, cx: &mut App) -> Task<Result<(), AuthenticateError>> {
267 self.state.update(cx, |state, cx| state.authenticate(cx))
268 }
269
270 fn configuration_view(
271 &self,
272 target_agent: ConfigurationViewTargetAgent,
273 window: &mut Window,
274 cx: &mut App,
275 ) -> AnyView {
276 cx.new(|cx| ConfigurationView::new(self.state.clone(), target_agent, window, cx))
277 .into()
278 }
279
280 fn reset_credentials(&self, cx: &mut App) -> Task<Result<()>> {
281 self.state.update(cx, |state, cx| state.reset_api_key(cx))
282 }
283}
284
285pub struct AnthropicModel {
286 id: LanguageModelId,
287 model: anthropic::Model,
288 state: gpui::Entity<State>,
289 http_client: Arc<dyn HttpClient>,
290 request_limiter: RateLimiter,
291}
292
293pub fn count_anthropic_tokens(
294 request: LanguageModelRequest,
295 cx: &App,
296) -> BoxFuture<'static, Result<u64>> {
297 cx.background_spawn(async move {
298 let messages = request.messages;
299 let mut tokens_from_images = 0;
300 let mut string_messages = Vec::with_capacity(messages.len());
301
302 for message in messages {
303 use language_model::MessageContent;
304
305 let mut string_contents = String::new();
306
307 for content in message.content {
308 match content {
309 MessageContent::Text(text) => {
310 string_contents.push_str(&text);
311 }
312 MessageContent::Thinking { .. } => {
313 // Thinking blocks are not included in the input token count.
314 }
315 MessageContent::RedactedThinking(_) => {
316 // Thinking blocks are not included in the input token count.
317 }
318 MessageContent::Image(image) => {
319 tokens_from_images += image.estimate_tokens();
320 }
321 MessageContent::ToolUse(_tool_use) => {
322 // TODO: Estimate token usage from tool uses.
323 }
324 MessageContent::ToolResult(tool_result) => match &tool_result.content {
325 LanguageModelToolResultContent::Text(text) => {
326 string_contents.push_str(text);
327 }
328 LanguageModelToolResultContent::Image(image) => {
329 tokens_from_images += image.estimate_tokens();
330 }
331 },
332 }
333 }
334
335 if !string_contents.is_empty() {
336 string_messages.push(tiktoken_rs::ChatCompletionRequestMessage {
337 role: match message.role {
338 Role::User => "user".into(),
339 Role::Assistant => "assistant".into(),
340 Role::System => "system".into(),
341 },
342 content: Some(string_contents),
343 name: None,
344 function_call: None,
345 });
346 }
347 }
348
349 // Tiktoken doesn't yet support these models, so we manually use the
350 // same tokenizer as GPT-4.
351 tiktoken_rs::num_tokens_from_messages("gpt-4", &string_messages)
352 .map(|tokens| (tokens + tokens_from_images) as u64)
353 })
354 .boxed()
355}
356
357impl AnthropicModel {
358 fn stream_completion(
359 &self,
360 request: anthropic::Request,
361 cx: &AsyncApp,
362 ) -> BoxFuture<
363 'static,
364 Result<
365 BoxStream<'static, Result<anthropic::Event, AnthropicError>>,
366 LanguageModelCompletionError,
367 >,
368 > {
369 let http_client = self.http_client.clone();
370
371 let Ok((api_key, api_url)) = cx.read_entity(&self.state, |state, cx| {
372 let settings = &AllLanguageModelSettings::get_global(cx).anthropic;
373 (state.api_key.clone(), settings.api_url.clone())
374 }) else {
375 return futures::future::ready(Err(anyhow!("App state dropped").into())).boxed();
376 };
377
378 let beta_headers = self.model.beta_headers();
379
380 async move {
381 let Some(api_key) = api_key else {
382 return Err(LanguageModelCompletionError::NoApiKey {
383 provider: PROVIDER_NAME,
384 });
385 };
386 let request = anthropic::stream_completion(
387 http_client.as_ref(),
388 &api_url,
389 &api_key,
390 request,
391 beta_headers,
392 );
393 request.await.map_err(Into::into)
394 }
395 .boxed()
396 }
397}
398
399impl LanguageModel for AnthropicModel {
400 fn id(&self) -> LanguageModelId {
401 self.id.clone()
402 }
403
404 fn name(&self) -> LanguageModelName {
405 LanguageModelName::from(self.model.display_name().to_string())
406 }
407
408 fn provider_id(&self) -> LanguageModelProviderId {
409 PROVIDER_ID
410 }
411
412 fn provider_name(&self) -> LanguageModelProviderName {
413 PROVIDER_NAME
414 }
415
416 fn supports_tools(&self) -> bool {
417 true
418 }
419
420 fn supports_images(&self) -> bool {
421 true
422 }
423
424 fn supports_tool_choice(&self, choice: LanguageModelToolChoice) -> bool {
425 match choice {
426 LanguageModelToolChoice::Auto
427 | LanguageModelToolChoice::Any
428 | LanguageModelToolChoice::None => true,
429 }
430 }
431
432 fn telemetry_id(&self) -> String {
433 format!("anthropic/{}", self.model.id())
434 }
435
436 fn api_key(&self, cx: &App) -> Option<String> {
437 self.state.read(cx).api_key.clone()
438 }
439
440 fn max_token_count(&self) -> u64 {
441 self.model.max_token_count()
442 }
443
444 fn max_output_tokens(&self) -> Option<u64> {
445 Some(self.model.max_output_tokens())
446 }
447
448 fn count_tokens(
449 &self,
450 request: LanguageModelRequest,
451 cx: &App,
452 ) -> BoxFuture<'static, Result<u64>> {
453 count_anthropic_tokens(request, cx)
454 }
455
456 fn stream_completion(
457 &self,
458 request: LanguageModelRequest,
459 cx: &AsyncApp,
460 ) -> BoxFuture<
461 'static,
462 Result<
463 BoxStream<'static, Result<LanguageModelCompletionEvent, LanguageModelCompletionError>>,
464 LanguageModelCompletionError,
465 >,
466 > {
467 let request = into_anthropic(
468 request,
469 self.model.request_id().into(),
470 self.model.default_temperature(),
471 self.model.max_output_tokens(),
472 self.model.mode(),
473 );
474 let request = self.stream_completion(request, cx);
475 let future = self.request_limiter.stream(async move {
476 let response = request.await?;
477 Ok(AnthropicEventMapper::new().map_stream(response))
478 });
479 async move { Ok(future.await?.boxed()) }.boxed()
480 }
481
482 fn cache_configuration(&self) -> Option<LanguageModelCacheConfiguration> {
483 self.model
484 .cache_configuration()
485 .map(|config| LanguageModelCacheConfiguration {
486 max_cache_anchors: config.max_cache_anchors,
487 should_speculate: config.should_speculate,
488 min_total_token: config.min_total_token,
489 })
490 }
491}
492
493pub fn into_anthropic(
494 request: LanguageModelRequest,
495 model: String,
496 default_temperature: f32,
497 max_output_tokens: u64,
498 mode: AnthropicModelMode,
499) -> anthropic::Request {
500 let mut new_messages: Vec<anthropic::Message> = Vec::new();
501 let mut system_message = String::new();
502
503 for message in request.messages {
504 if message.contents_empty() {
505 continue;
506 }
507
508 match message.role {
509 Role::User | Role::Assistant => {
510 let mut anthropic_message_content: Vec<anthropic::RequestContent> = message
511 .content
512 .into_iter()
513 .filter_map(|content| match content {
514 MessageContent::Text(text) => {
515 let text = if text.chars().last().is_some_and(|c| c.is_whitespace()) {
516 text.trim_end().to_string()
517 } else {
518 text
519 };
520 if !text.is_empty() {
521 Some(anthropic::RequestContent::Text {
522 text,
523 cache_control: None,
524 })
525 } else {
526 None
527 }
528 }
529 MessageContent::Thinking {
530 text: thinking,
531 signature,
532 } => {
533 if !thinking.is_empty() {
534 Some(anthropic::RequestContent::Thinking {
535 thinking,
536 signature: signature.unwrap_or_default(),
537 cache_control: None,
538 })
539 } else {
540 None
541 }
542 }
543 MessageContent::RedactedThinking(data) => {
544 if !data.is_empty() {
545 Some(anthropic::RequestContent::RedactedThinking { data })
546 } else {
547 None
548 }
549 }
550 MessageContent::Image(image) => Some(anthropic::RequestContent::Image {
551 source: anthropic::ImageSource {
552 source_type: "base64".to_string(),
553 media_type: "image/png".to_string(),
554 data: image.source.to_string(),
555 },
556 cache_control: None,
557 }),
558 MessageContent::ToolUse(tool_use) => {
559 Some(anthropic::RequestContent::ToolUse {
560 id: tool_use.id.to_string(),
561 name: tool_use.name.to_string(),
562 input: tool_use.input,
563 cache_control: None,
564 })
565 }
566 MessageContent::ToolResult(tool_result) => {
567 Some(anthropic::RequestContent::ToolResult {
568 tool_use_id: tool_result.tool_use_id.to_string(),
569 is_error: tool_result.is_error,
570 content: match tool_result.content {
571 LanguageModelToolResultContent::Text(text) => {
572 ToolResultContent::Plain(text.to_string())
573 }
574 LanguageModelToolResultContent::Image(image) => {
575 ToolResultContent::Multipart(vec![ToolResultPart::Image {
576 source: anthropic::ImageSource {
577 source_type: "base64".to_string(),
578 media_type: "image/png".to_string(),
579 data: image.source.to_string(),
580 },
581 }])
582 }
583 },
584 cache_control: None,
585 })
586 }
587 })
588 .collect();
589 let anthropic_role = match message.role {
590 Role::User => anthropic::Role::User,
591 Role::Assistant => anthropic::Role::Assistant,
592 Role::System => unreachable!("System role should never occur here"),
593 };
594 if let Some(last_message) = new_messages.last_mut()
595 && last_message.role == anthropic_role
596 {
597 last_message.content.extend(anthropic_message_content);
598 continue;
599 }
600
601 // Mark the last segment of the message as cached
602 if message.cache {
603 let cache_control_value = Some(anthropic::CacheControl {
604 cache_type: anthropic::CacheControlType::Ephemeral,
605 });
606 for message_content in anthropic_message_content.iter_mut().rev() {
607 match message_content {
608 anthropic::RequestContent::RedactedThinking { .. } => {
609 // Caching is not possible, fallback to next message
610 }
611 anthropic::RequestContent::Text { cache_control, .. }
612 | anthropic::RequestContent::Thinking { cache_control, .. }
613 | anthropic::RequestContent::Image { cache_control, .. }
614 | anthropic::RequestContent::ToolUse { cache_control, .. }
615 | anthropic::RequestContent::ToolResult { cache_control, .. } => {
616 *cache_control = cache_control_value;
617 break;
618 }
619 }
620 }
621 }
622
623 new_messages.push(anthropic::Message {
624 role: anthropic_role,
625 content: anthropic_message_content,
626 });
627 }
628 Role::System => {
629 if !system_message.is_empty() {
630 system_message.push_str("\n\n");
631 }
632 system_message.push_str(&message.string_contents());
633 }
634 }
635 }
636
637 anthropic::Request {
638 model,
639 messages: new_messages,
640 max_tokens: max_output_tokens,
641 system: if system_message.is_empty() {
642 None
643 } else {
644 Some(anthropic::StringOrContents::String(system_message))
645 },
646 thinking: if request.thinking_allowed
647 && let AnthropicModelMode::Thinking { budget_tokens } = mode
648 {
649 Some(anthropic::Thinking::Enabled { budget_tokens })
650 } else {
651 None
652 },
653 tools: request
654 .tools
655 .into_iter()
656 .map(|tool| anthropic::Tool {
657 name: tool.name,
658 description: tool.description,
659 input_schema: tool.input_schema,
660 })
661 .collect(),
662 tool_choice: request.tool_choice.map(|choice| match choice {
663 LanguageModelToolChoice::Auto => anthropic::ToolChoice::Auto,
664 LanguageModelToolChoice::Any => anthropic::ToolChoice::Any,
665 LanguageModelToolChoice::None => anthropic::ToolChoice::None,
666 }),
667 metadata: None,
668 stop_sequences: Vec::new(),
669 temperature: request.temperature.or(Some(default_temperature)),
670 top_k: None,
671 top_p: None,
672 }
673}
674
675pub struct AnthropicEventMapper {
676 tool_uses_by_index: HashMap<usize, RawToolUse>,
677 usage: Usage,
678 stop_reason: StopReason,
679}
680
681impl AnthropicEventMapper {
682 pub fn new() -> Self {
683 Self {
684 tool_uses_by_index: HashMap::default(),
685 usage: Usage::default(),
686 stop_reason: StopReason::EndTurn,
687 }
688 }
689
690 pub fn map_stream(
691 mut self,
692 events: Pin<Box<dyn Send + Stream<Item = Result<Event, AnthropicError>>>>,
693 ) -> impl Stream<Item = Result<LanguageModelCompletionEvent, LanguageModelCompletionError>>
694 {
695 events.flat_map(move |event| {
696 futures::stream::iter(match event {
697 Ok(event) => self.map_event(event),
698 Err(error) => vec![Err(error.into())],
699 })
700 })
701 }
702
703 pub fn map_event(
704 &mut self,
705 event: Event,
706 ) -> Vec<Result<LanguageModelCompletionEvent, LanguageModelCompletionError>> {
707 match event {
708 Event::ContentBlockStart {
709 index,
710 content_block,
711 } => match content_block {
712 ResponseContent::Text { text } => {
713 vec![Ok(LanguageModelCompletionEvent::Text(text))]
714 }
715 ResponseContent::Thinking { thinking } => {
716 vec![Ok(LanguageModelCompletionEvent::Thinking {
717 text: thinking,
718 signature: None,
719 })]
720 }
721 ResponseContent::RedactedThinking { data } => {
722 vec![Ok(LanguageModelCompletionEvent::RedactedThinking { data })]
723 }
724 ResponseContent::ToolUse { id, name, .. } => {
725 self.tool_uses_by_index.insert(
726 index,
727 RawToolUse {
728 id,
729 name,
730 input_json: String::new(),
731 },
732 );
733 Vec::new()
734 }
735 },
736 Event::ContentBlockDelta { index, delta } => match delta {
737 ContentDelta::TextDelta { text } => {
738 vec![Ok(LanguageModelCompletionEvent::Text(text))]
739 }
740 ContentDelta::ThinkingDelta { thinking } => {
741 vec![Ok(LanguageModelCompletionEvent::Thinking {
742 text: thinking,
743 signature: None,
744 })]
745 }
746 ContentDelta::SignatureDelta { signature } => {
747 vec![Ok(LanguageModelCompletionEvent::Thinking {
748 text: "".to_string(),
749 signature: Some(signature),
750 })]
751 }
752 ContentDelta::InputJsonDelta { partial_json } => {
753 if let Some(tool_use) = self.tool_uses_by_index.get_mut(&index) {
754 tool_use.input_json.push_str(&partial_json);
755
756 // Try to convert invalid (incomplete) JSON into
757 // valid JSON that serde can accept, e.g. by closing
758 // unclosed delimiters. This way, we can update the
759 // UI with whatever has been streamed back so far.
760 if let Ok(input) = serde_json::Value::from_str(
761 &partial_json_fixer::fix_json(&tool_use.input_json),
762 ) {
763 return vec![Ok(LanguageModelCompletionEvent::ToolUse(
764 LanguageModelToolUse {
765 id: tool_use.id.clone().into(),
766 name: tool_use.name.clone().into(),
767 is_input_complete: false,
768 raw_input: tool_use.input_json.clone(),
769 input,
770 },
771 ))];
772 }
773 }
774 vec![]
775 }
776 },
777 Event::ContentBlockStop { index } => {
778 if let Some(tool_use) = self.tool_uses_by_index.remove(&index) {
779 let input_json = tool_use.input_json.trim();
780 let input_value = if input_json.is_empty() {
781 Ok(serde_json::Value::Object(serde_json::Map::default()))
782 } else {
783 serde_json::Value::from_str(input_json)
784 };
785 let event_result = match input_value {
786 Ok(input) => Ok(LanguageModelCompletionEvent::ToolUse(
787 LanguageModelToolUse {
788 id: tool_use.id.into(),
789 name: tool_use.name.into(),
790 is_input_complete: true,
791 input,
792 raw_input: tool_use.input_json.clone(),
793 },
794 )),
795 Err(json_parse_err) => {
796 Ok(LanguageModelCompletionEvent::ToolUseJsonParseError {
797 id: tool_use.id.into(),
798 tool_name: tool_use.name.into(),
799 raw_input: input_json.into(),
800 json_parse_error: json_parse_err.to_string(),
801 })
802 }
803 };
804
805 vec![event_result]
806 } else {
807 Vec::new()
808 }
809 }
810 Event::MessageStart { message } => {
811 update_usage(&mut self.usage, &message.usage);
812 vec![
813 Ok(LanguageModelCompletionEvent::UsageUpdate(convert_usage(
814 &self.usage,
815 ))),
816 Ok(LanguageModelCompletionEvent::StartMessage {
817 message_id: message.id,
818 }),
819 ]
820 }
821 Event::MessageDelta { delta, usage } => {
822 update_usage(&mut self.usage, &usage);
823 if let Some(stop_reason) = delta.stop_reason.as_deref() {
824 self.stop_reason = match stop_reason {
825 "end_turn" => StopReason::EndTurn,
826 "max_tokens" => StopReason::MaxTokens,
827 "tool_use" => StopReason::ToolUse,
828 "refusal" => StopReason::Refusal,
829 _ => {
830 log::error!("Unexpected anthropic stop_reason: {stop_reason}");
831 StopReason::EndTurn
832 }
833 };
834 }
835 vec![Ok(LanguageModelCompletionEvent::UsageUpdate(
836 convert_usage(&self.usage),
837 ))]
838 }
839 Event::MessageStop => {
840 vec![Ok(LanguageModelCompletionEvent::Stop(self.stop_reason))]
841 }
842 Event::Error { error } => {
843 vec![Err(error.into())]
844 }
845 _ => Vec::new(),
846 }
847 }
848}
849
850struct RawToolUse {
851 id: String,
852 name: String,
853 input_json: String,
854}
855
856/// Updates usage data by preferring counts from `new`.
857fn update_usage(usage: &mut Usage, new: &Usage) {
858 if let Some(input_tokens) = new.input_tokens {
859 usage.input_tokens = Some(input_tokens);
860 }
861 if let Some(output_tokens) = new.output_tokens {
862 usage.output_tokens = Some(output_tokens);
863 }
864 if let Some(cache_creation_input_tokens) = new.cache_creation_input_tokens {
865 usage.cache_creation_input_tokens = Some(cache_creation_input_tokens);
866 }
867 if let Some(cache_read_input_tokens) = new.cache_read_input_tokens {
868 usage.cache_read_input_tokens = Some(cache_read_input_tokens);
869 }
870}
871
872fn convert_usage(usage: &Usage) -> language_model::TokenUsage {
873 language_model::TokenUsage {
874 input_tokens: usage.input_tokens.unwrap_or(0),
875 output_tokens: usage.output_tokens.unwrap_or(0),
876 cache_creation_input_tokens: usage.cache_creation_input_tokens.unwrap_or(0),
877 cache_read_input_tokens: usage.cache_read_input_tokens.unwrap_or(0),
878 }
879}
880
881struct ConfigurationView {
882 api_key_editor: Entity<Editor>,
883 state: gpui::Entity<State>,
884 load_credentials_task: Option<Task<()>>,
885 target_agent: ConfigurationViewTargetAgent,
886}
887
888impl ConfigurationView {
889 const PLACEHOLDER_TEXT: &'static str = "sk-ant-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx";
890
891 fn new(
892 state: gpui::Entity<State>,
893 target_agent: ConfigurationViewTargetAgent,
894 window: &mut Window,
895 cx: &mut Context<Self>,
896 ) -> Self {
897 cx.observe(&state, |_, _, cx| {
898 cx.notify();
899 })
900 .detach();
901
902 let load_credentials_task = Some(cx.spawn({
903 let state = state.clone();
904 async move |this, cx| {
905 if let Some(task) = state
906 .update(cx, |state, cx| state.authenticate(cx))
907 .log_err()
908 {
909 // We don't log an error, because "not signed in" is also an error.
910 let _ = task.await;
911 }
912 this.update(cx, |this, cx| {
913 this.load_credentials_task = None;
914 cx.notify();
915 })
916 .log_err();
917 }
918 }));
919
920 Self {
921 api_key_editor: cx.new(|cx| {
922 let mut editor = Editor::single_line(window, cx);
923 editor.set_placeholder_text(Self::PLACEHOLDER_TEXT, window, cx);
924 editor
925 }),
926 state,
927 load_credentials_task,
928 target_agent,
929 }
930 }
931
932 fn save_api_key(&mut self, _: &menu::Confirm, window: &mut Window, cx: &mut Context<Self>) {
933 let api_key = self.api_key_editor.read(cx).text(cx);
934 if api_key.is_empty() {
935 return;
936 }
937
938 let state = self.state.clone();
939 cx.spawn_in(window, async move |_, cx| {
940 state
941 .update(cx, |state, cx| state.set_api_key(api_key, cx))?
942 .await
943 })
944 .detach_and_log_err(cx);
945
946 cx.notify();
947 }
948
949 fn reset_api_key(&mut self, window: &mut Window, cx: &mut Context<Self>) {
950 self.api_key_editor
951 .update(cx, |editor, cx| editor.set_text("", window, cx));
952
953 let state = self.state.clone();
954 cx.spawn_in(window, async move |_, cx| {
955 state.update(cx, |state, cx| state.reset_api_key(cx))?.await
956 })
957 .detach_and_log_err(cx);
958
959 cx.notify();
960 }
961
962 fn render_api_key_editor(&self, cx: &mut Context<Self>) -> impl IntoElement {
963 let settings = ThemeSettings::get_global(cx);
964 let text_style = TextStyle {
965 color: cx.theme().colors().text,
966 font_family: settings.ui_font.family.clone(),
967 font_features: settings.ui_font.features.clone(),
968 font_fallbacks: settings.ui_font.fallbacks.clone(),
969 font_size: rems(0.875).into(),
970 font_weight: settings.ui_font.weight,
971 font_style: FontStyle::Normal,
972 line_height: relative(1.3),
973 white_space: WhiteSpace::Normal,
974 ..Default::default()
975 };
976 EditorElement::new(
977 &self.api_key_editor,
978 EditorStyle {
979 background: cx.theme().colors().editor_background,
980 local_player: cx.theme().players().local(),
981 text: text_style,
982 ..Default::default()
983 },
984 )
985 }
986
987 fn should_render_editor(&self, cx: &mut Context<Self>) -> bool {
988 !self.state.read(cx).is_authenticated()
989 }
990}
991
992impl Render for ConfigurationView {
993 fn render(&mut self, _: &mut Window, cx: &mut Context<Self>) -> impl IntoElement {
994 let env_var_set = self.state.read(cx).api_key_from_env;
995
996 if self.load_credentials_task.is_some() {
997 div().child(Label::new("Loading credentials...")).into_any()
998 } else if self.should_render_editor(cx) {
999 v_flex()
1000 .size_full()
1001 .on_action(cx.listener(Self::save_api_key))
1002 .child(Label::new(format!("To use {}, you need to add an API key. Follow these steps:", match &self.target_agent {
1003 ConfigurationViewTargetAgent::ZedAgent => "Zed's agent with Anthropic".into(),
1004 ConfigurationViewTargetAgent::Other(agent) => agent.clone(),
1005 })))
1006 .child(
1007 List::new()
1008 .child(
1009 InstructionListItem::new(
1010 "Create one by visiting",
1011 Some("Anthropic's settings"),
1012 Some("https://console.anthropic.com/settings/keys")
1013 )
1014 )
1015 .child(
1016 InstructionListItem::text_only("Paste your API key below and hit enter to start using the agent")
1017 )
1018 )
1019 .child(
1020 h_flex()
1021 .w_full()
1022 .my_2()
1023 .px_2()
1024 .py_1()
1025 .bg(cx.theme().colors().editor_background)
1026 .border_1()
1027 .border_color(cx.theme().colors().border)
1028 .rounded_sm()
1029 .child(self.render_api_key_editor(cx)),
1030 )
1031 .child(
1032 Label::new(
1033 format!("You can also assign the {ANTHROPIC_API_KEY_VAR} environment variable and restart Zed."),
1034 )
1035 .size(LabelSize::Small)
1036 .color(Color::Muted),
1037 )
1038 .into_any()
1039 } else {
1040 h_flex()
1041 .mt_1()
1042 .p_1()
1043 .justify_between()
1044 .rounded_md()
1045 .border_1()
1046 .border_color(cx.theme().colors().border)
1047 .bg(cx.theme().colors().background)
1048 .child(
1049 h_flex()
1050 .gap_1()
1051 .child(Icon::new(IconName::Check).color(Color::Success))
1052 .child(Label::new(if env_var_set {
1053 format!("API key set in {ANTHROPIC_API_KEY_VAR} environment variable.")
1054 } else {
1055 "API key configured.".to_string()
1056 })),
1057 )
1058 .child(
1059 Button::new("reset-key", "Reset Key")
1060 .label_size(LabelSize::Small)
1061 .icon(Some(IconName::Trash))
1062 .icon_size(IconSize::Small)
1063 .icon_position(IconPosition::Start)
1064 .disabled(env_var_set)
1065 .when(env_var_set, |this| {
1066 this.tooltip(Tooltip::text(format!("To reset your API key, unset the {ANTHROPIC_API_KEY_VAR} environment variable.")))
1067 })
1068 .on_click(cx.listener(|this, _, window, cx| this.reset_api_key(window, cx))),
1069 )
1070 .into_any()
1071 }
1072 }
1073}
1074
1075#[cfg(test)]
1076mod tests {
1077 use super::*;
1078 use anthropic::AnthropicModelMode;
1079 use language_model::{LanguageModelRequestMessage, MessageContent};
1080
1081 #[test]
1082 fn test_cache_control_only_on_last_segment() {
1083 let request = LanguageModelRequest {
1084 messages: vec![LanguageModelRequestMessage {
1085 role: Role::User,
1086 content: vec![
1087 MessageContent::Text("Some prompt".to_string()),
1088 MessageContent::Image(language_model::LanguageModelImage::empty()),
1089 MessageContent::Image(language_model::LanguageModelImage::empty()),
1090 MessageContent::Image(language_model::LanguageModelImage::empty()),
1091 MessageContent::Image(language_model::LanguageModelImage::empty()),
1092 ],
1093 cache: true,
1094 }],
1095 thread_id: None,
1096 prompt_id: None,
1097 intent: None,
1098 mode: None,
1099 stop: vec![],
1100 temperature: None,
1101 tools: vec![],
1102 tool_choice: None,
1103 thinking_allowed: true,
1104 };
1105
1106 let anthropic_request = into_anthropic(
1107 request,
1108 "claude-3-5-sonnet".to_string(),
1109 0.7,
1110 4096,
1111 AnthropicModelMode::Default,
1112 );
1113
1114 assert_eq!(anthropic_request.messages.len(), 1);
1115
1116 let message = &anthropic_request.messages[0];
1117 assert_eq!(message.content.len(), 5);
1118
1119 assert!(matches!(
1120 message.content[0],
1121 anthropic::RequestContent::Text {
1122 cache_control: None,
1123 ..
1124 }
1125 ));
1126 for i in 1..3 {
1127 assert!(matches!(
1128 message.content[i],
1129 anthropic::RequestContent::Image {
1130 cache_control: None,
1131 ..
1132 }
1133 ));
1134 }
1135
1136 assert!(matches!(
1137 message.content[4],
1138 anthropic::RequestContent::Image {
1139 cache_control: Some(anthropic::CacheControl {
1140 cache_type: anthropic::CacheControlType::Ephemeral,
1141 }),
1142 ..
1143 }
1144 ));
1145 }
1146}