1use anyhow::{Result, anyhow};
2use collections::HashMap;
3use futures::Stream;
4use futures::{FutureExt, StreamExt, future::BoxFuture, stream::BoxStream};
5use gpui::{AnyView, App, AsyncApp, Context, Entity, Subscription, Task};
6use http_client::HttpClient;
7use language_model::{
8 AuthenticateError, LanguageModelCompletionError, LanguageModelCompletionEvent,
9 LanguageModelToolChoice, LanguageModelToolResultContent, LanguageModelToolUse, MessageContent,
10 StopReason, TokenUsage,
11};
12use language_model::{
13 IconOrSvg, LanguageModel, LanguageModelId, LanguageModelName, LanguageModelProvider,
14 LanguageModelProviderId, LanguageModelProviderName, LanguageModelProviderState,
15 LanguageModelRequest, RateLimiter, Role,
16};
17use lmstudio::{ModelType, get_models};
18pub use settings::LmStudioAvailableModel as AvailableModel;
19use settings::{Settings, SettingsStore};
20use std::pin::Pin;
21use std::str::FromStr;
22use std::{collections::BTreeMap, sync::Arc};
23use ui::{ButtonLike, Indicator, List, ListBulletItem, prelude::*};
24use util::ResultExt;
25
26use crate::AllLanguageModelSettings;
27
28const LMSTUDIO_DOWNLOAD_URL: &str = "https://lmstudio.ai/download";
29const LMSTUDIO_CATALOG_URL: &str = "https://lmstudio.ai/models";
30const LMSTUDIO_SITE: &str = "https://lmstudio.ai/";
31
32const PROVIDER_ID: LanguageModelProviderId = LanguageModelProviderId::new("lmstudio");
33const PROVIDER_NAME: LanguageModelProviderName = LanguageModelProviderName::new("LM Studio");
34
35#[derive(Default, Debug, Clone, PartialEq)]
36pub struct LmStudioSettings {
37 pub api_url: String,
38 pub available_models: Vec<AvailableModel>,
39}
40
41pub struct LmStudioLanguageModelProvider {
42 http_client: Arc<dyn HttpClient>,
43 state: Entity<State>,
44}
45
46pub struct State {
47 http_client: Arc<dyn HttpClient>,
48 available_models: Vec<lmstudio::Model>,
49 fetch_model_task: Option<Task<Result<()>>>,
50 _subscription: Subscription,
51}
52
53impl State {
54 fn is_authenticated(&self) -> bool {
55 !self.available_models.is_empty()
56 }
57
58 fn fetch_models(&mut self, cx: &mut Context<Self>) -> Task<Result<()>> {
59 let settings = &AllLanguageModelSettings::get_global(cx).lmstudio;
60 let http_client = self.http_client.clone();
61 let api_url = settings.api_url.clone();
62
63 // As a proxy for the server being "authenticated", we'll check if its up by fetching the models
64 cx.spawn(async move |this, cx| {
65 let models = get_models(http_client.as_ref(), &api_url, None).await?;
66
67 let mut models: Vec<lmstudio::Model> = models
68 .into_iter()
69 .filter(|model| model.r#type != ModelType::Embeddings)
70 .map(|model| {
71 lmstudio::Model::new(
72 &model.id,
73 None,
74 model
75 .loaded_context_length
76 .or_else(|| model.max_context_length),
77 model.capabilities.supports_tool_calls(),
78 model.capabilities.supports_images() || model.r#type == ModelType::Vlm,
79 )
80 })
81 .collect();
82
83 models.sort_by(|a, b| a.name.cmp(&b.name));
84
85 this.update(cx, |this, cx| {
86 this.available_models = models;
87 cx.notify();
88 })
89 })
90 }
91
92 fn restart_fetch_models_task(&mut self, cx: &mut Context<Self>) {
93 let task = self.fetch_models(cx);
94 self.fetch_model_task.replace(task);
95 }
96
97 fn authenticate(&mut self, cx: &mut Context<Self>) -> Task<Result<(), AuthenticateError>> {
98 if self.is_authenticated() {
99 return Task::ready(Ok(()));
100 }
101
102 let fetch_models_task = self.fetch_models(cx);
103 cx.spawn(async move |_this, _cx| {
104 match fetch_models_task.await {
105 Ok(()) => Ok(()),
106 Err(err) => {
107 // If any cause in the error chain is an std::io::Error with
108 // ErrorKind::ConnectionRefused, treat this as "credentials not found"
109 // (i.e. LM Studio not running).
110 let mut connection_refused = false;
111 for cause in err.chain() {
112 if let Some(io_err) = cause.downcast_ref::<std::io::Error>() {
113 if io_err.kind() == std::io::ErrorKind::ConnectionRefused {
114 connection_refused = true;
115 break;
116 }
117 }
118 }
119 if connection_refused {
120 Err(AuthenticateError::ConnectionRefused)
121 } else {
122 Err(AuthenticateError::Other(err))
123 }
124 }
125 }
126 })
127 }
128}
129
130impl LmStudioLanguageModelProvider {
131 pub fn new(http_client: Arc<dyn HttpClient>, cx: &mut App) -> Self {
132 let this = Self {
133 http_client: http_client.clone(),
134 state: cx.new(|cx| {
135 let subscription = cx.observe_global::<SettingsStore>({
136 let mut settings = AllLanguageModelSettings::get_global(cx).lmstudio.clone();
137 move |this: &mut State, cx| {
138 let new_settings = &AllLanguageModelSettings::get_global(cx).lmstudio;
139 if &settings != new_settings {
140 settings = new_settings.clone();
141 this.restart_fetch_models_task(cx);
142 cx.notify();
143 }
144 }
145 });
146
147 State {
148 http_client,
149 available_models: Default::default(),
150 fetch_model_task: None,
151 _subscription: subscription,
152 }
153 }),
154 };
155 this.state
156 .update(cx, |state, cx| state.restart_fetch_models_task(cx));
157 this
158 }
159}
160
161impl LanguageModelProviderState for LmStudioLanguageModelProvider {
162 type ObservableEntity = State;
163
164 fn observable_entity(&self) -> Option<Entity<Self::ObservableEntity>> {
165 Some(self.state.clone())
166 }
167}
168
169impl LanguageModelProvider for LmStudioLanguageModelProvider {
170 fn id(&self) -> LanguageModelProviderId {
171 PROVIDER_ID
172 }
173
174 fn name(&self) -> LanguageModelProviderName {
175 PROVIDER_NAME
176 }
177
178 fn icon(&self) -> IconOrSvg {
179 IconOrSvg::Icon(IconName::AiLmStudio)
180 }
181
182 fn default_model(&self, _: &App) -> Option<Arc<dyn LanguageModel>> {
183 // We shouldn't try to select default model, because it might lead to a load call for an unloaded model.
184 // In a constrained environment where user might not have enough resources it'll be a bad UX to select something
185 // to load by default.
186 None
187 }
188
189 fn default_fast_model(&self, _: &App) -> Option<Arc<dyn LanguageModel>> {
190 // See explanation for default_model.
191 None
192 }
193
194 fn provided_models(&self, cx: &App) -> Vec<Arc<dyn LanguageModel>> {
195 let mut models: BTreeMap<String, lmstudio::Model> = BTreeMap::default();
196
197 // Add models from the LM Studio API
198 for model in self.state.read(cx).available_models.iter() {
199 models.insert(model.name.clone(), model.clone());
200 }
201
202 // Override with available models from settings
203 for model in AllLanguageModelSettings::get_global(cx)
204 .lmstudio
205 .available_models
206 .iter()
207 {
208 models.insert(
209 model.name.clone(),
210 lmstudio::Model {
211 name: model.name.clone(),
212 display_name: model.display_name.clone(),
213 max_tokens: model.max_tokens,
214 supports_tool_calls: model.supports_tool_calls,
215 supports_images: model.supports_images,
216 },
217 );
218 }
219
220 models
221 .into_values()
222 .map(|model| {
223 Arc::new(LmStudioLanguageModel {
224 id: LanguageModelId::from(model.name.clone()),
225 model,
226 http_client: self.http_client.clone(),
227 request_limiter: RateLimiter::new(4),
228 }) as Arc<dyn LanguageModel>
229 })
230 .collect()
231 }
232
233 fn is_authenticated(&self, cx: &App) -> bool {
234 self.state.read(cx).is_authenticated()
235 }
236
237 fn authenticate(&self, cx: &mut App) -> Task<Result<(), AuthenticateError>> {
238 self.state.update(cx, |state, cx| state.authenticate(cx))
239 }
240
241 fn configuration_view(
242 &self,
243 _target_agent: language_model::ConfigurationViewTargetAgent,
244 _window: &mut Window,
245 cx: &mut App,
246 ) -> AnyView {
247 let state = self.state.clone();
248 cx.new(|cx| ConfigurationView::new(state, cx)).into()
249 }
250
251 fn reset_credentials(&self, cx: &mut App) -> Task<Result<()>> {
252 self.state.update(cx, |state, cx| state.fetch_models(cx))
253 }
254}
255
256pub struct LmStudioLanguageModel {
257 id: LanguageModelId,
258 model: lmstudio::Model,
259 http_client: Arc<dyn HttpClient>,
260 request_limiter: RateLimiter,
261}
262
263impl LmStudioLanguageModel {
264 fn to_lmstudio_request(
265 &self,
266 request: LanguageModelRequest,
267 ) -> lmstudio::ChatCompletionRequest {
268 let mut messages = Vec::new();
269
270 for message in request.messages {
271 for content in message.content {
272 match content {
273 MessageContent::Text(text) => add_message_content_part(
274 lmstudio::MessagePart::Text { text },
275 message.role,
276 &mut messages,
277 ),
278 MessageContent::Thinking { .. } => {}
279 MessageContent::RedactedThinking(_) => {}
280 MessageContent::Image(image) => {
281 add_message_content_part(
282 lmstudio::MessagePart::Image {
283 image_url: lmstudio::ImageUrl {
284 url: image.to_base64_url(),
285 detail: None,
286 },
287 },
288 message.role,
289 &mut messages,
290 );
291 }
292 MessageContent::ToolUse(tool_use) => {
293 let tool_call = lmstudio::ToolCall {
294 id: tool_use.id.to_string(),
295 content: lmstudio::ToolCallContent::Function {
296 function: lmstudio::FunctionContent {
297 name: tool_use.name.to_string(),
298 arguments: serde_json::to_string(&tool_use.input)
299 .unwrap_or_default(),
300 },
301 },
302 };
303
304 if let Some(lmstudio::ChatMessage::Assistant { tool_calls, .. }) =
305 messages.last_mut()
306 {
307 tool_calls.push(tool_call);
308 } else {
309 messages.push(lmstudio::ChatMessage::Assistant {
310 content: None,
311 tool_calls: vec![tool_call],
312 });
313 }
314 }
315 MessageContent::ToolResult(tool_result) => {
316 let content = match &tool_result.content {
317 LanguageModelToolResultContent::Text(text) => {
318 vec![lmstudio::MessagePart::Text {
319 text: text.to_string(),
320 }]
321 }
322 LanguageModelToolResultContent::Image(image) => {
323 vec![lmstudio::MessagePart::Image {
324 image_url: lmstudio::ImageUrl {
325 url: image.to_base64_url(),
326 detail: None,
327 },
328 }]
329 }
330 };
331
332 messages.push(lmstudio::ChatMessage::Tool {
333 content: content.into(),
334 tool_call_id: tool_result.tool_use_id.to_string(),
335 });
336 }
337 }
338 }
339 }
340
341 lmstudio::ChatCompletionRequest {
342 model: self.model.name.clone(),
343 messages,
344 stream: true,
345 max_tokens: Some(-1),
346 stop: Some(request.stop),
347 // In LM Studio you can configure specific settings you'd like to use for your model.
348 // For example Qwen3 is recommended to be used with 0.7 temperature.
349 // It would be a bad UX to silently override these settings from Zed, so we pass no temperature as a default.
350 temperature: request.temperature.or(None),
351 tools: request
352 .tools
353 .into_iter()
354 .map(|tool| lmstudio::ToolDefinition::Function {
355 function: lmstudio::FunctionDefinition {
356 name: tool.name,
357 description: Some(tool.description),
358 parameters: Some(tool.input_schema),
359 },
360 })
361 .collect(),
362 tool_choice: request.tool_choice.map(|choice| match choice {
363 LanguageModelToolChoice::Auto => lmstudio::ToolChoice::Auto,
364 LanguageModelToolChoice::Any => lmstudio::ToolChoice::Required,
365 LanguageModelToolChoice::None => lmstudio::ToolChoice::None,
366 }),
367 }
368 }
369
370 fn stream_completion(
371 &self,
372 request: lmstudio::ChatCompletionRequest,
373 cx: &AsyncApp,
374 ) -> BoxFuture<
375 'static,
376 Result<futures::stream::BoxStream<'static, Result<lmstudio::ResponseStreamEvent>>>,
377 > {
378 let http_client = self.http_client.clone();
379 let api_url = cx.update(|cx| {
380 let settings = &AllLanguageModelSettings::get_global(cx).lmstudio;
381 settings.api_url.clone()
382 });
383
384 let future = self.request_limiter.stream(async move {
385 let request = lmstudio::stream_chat_completion(http_client.as_ref(), &api_url, request);
386 let response = request.await?;
387 Ok(response)
388 });
389
390 async move { Ok(future.await?.boxed()) }.boxed()
391 }
392}
393
394impl LanguageModel for LmStudioLanguageModel {
395 fn id(&self) -> LanguageModelId {
396 self.id.clone()
397 }
398
399 fn name(&self) -> LanguageModelName {
400 LanguageModelName::from(self.model.display_name().to_string())
401 }
402
403 fn provider_id(&self) -> LanguageModelProviderId {
404 PROVIDER_ID
405 }
406
407 fn provider_name(&self) -> LanguageModelProviderName {
408 PROVIDER_NAME
409 }
410
411 fn supports_tools(&self) -> bool {
412 self.model.supports_tool_calls()
413 }
414
415 fn supports_tool_choice(&self, choice: LanguageModelToolChoice) -> bool {
416 self.supports_tools()
417 && match choice {
418 LanguageModelToolChoice::Auto => true,
419 LanguageModelToolChoice::Any => true,
420 LanguageModelToolChoice::None => true,
421 }
422 }
423
424 fn supports_images(&self) -> bool {
425 self.model.supports_images
426 }
427
428 fn telemetry_id(&self) -> String {
429 format!("lmstudio/{}", self.model.id())
430 }
431
432 fn max_token_count(&self) -> u64 {
433 self.model.max_token_count()
434 }
435
436 fn count_tokens(
437 &self,
438 request: LanguageModelRequest,
439 _cx: &App,
440 ) -> BoxFuture<'static, Result<u64>> {
441 // Endpoint for this is coming soon. In the meantime, hacky estimation
442 let token_count = request
443 .messages
444 .iter()
445 .map(|msg| msg.string_contents().split_whitespace().count())
446 .sum::<usize>();
447
448 let estimated_tokens = (token_count as f64 * 0.75) as u64;
449 async move { Ok(estimated_tokens) }.boxed()
450 }
451
452 fn stream_completion(
453 &self,
454 request: LanguageModelRequest,
455 cx: &AsyncApp,
456 ) -> BoxFuture<
457 'static,
458 Result<
459 BoxStream<'static, Result<LanguageModelCompletionEvent, LanguageModelCompletionError>>,
460 LanguageModelCompletionError,
461 >,
462 > {
463 let request = self.to_lmstudio_request(request);
464 let completions = self.stream_completion(request, cx);
465 async move {
466 let mapper = LmStudioEventMapper::new();
467 Ok(mapper.map_stream(completions.await?).boxed())
468 }
469 .boxed()
470 }
471}
472
473struct LmStudioEventMapper {
474 tool_calls_by_index: HashMap<usize, RawToolCall>,
475}
476
477impl LmStudioEventMapper {
478 fn new() -> Self {
479 Self {
480 tool_calls_by_index: HashMap::default(),
481 }
482 }
483
484 pub fn map_stream(
485 mut self,
486 events: Pin<Box<dyn Send + Stream<Item = Result<lmstudio::ResponseStreamEvent>>>>,
487 ) -> impl Stream<Item = Result<LanguageModelCompletionEvent, LanguageModelCompletionError>>
488 {
489 events.flat_map(move |event| {
490 futures::stream::iter(match event {
491 Ok(event) => self.map_event(event),
492 Err(error) => vec![Err(LanguageModelCompletionError::from(error))],
493 })
494 })
495 }
496
497 pub fn map_event(
498 &mut self,
499 event: lmstudio::ResponseStreamEvent,
500 ) -> Vec<Result<LanguageModelCompletionEvent, LanguageModelCompletionError>> {
501 let Some(choice) = event.choices.into_iter().next() else {
502 return vec![Err(LanguageModelCompletionError::from(anyhow!(
503 "Response contained no choices"
504 )))];
505 };
506
507 let mut events = Vec::new();
508 if let Some(content) = choice.delta.content {
509 events.push(Ok(LanguageModelCompletionEvent::Text(content)));
510 }
511
512 if let Some(reasoning_content) = choice.delta.reasoning_content {
513 events.push(Ok(LanguageModelCompletionEvent::Thinking {
514 text: reasoning_content,
515 signature: None,
516 }));
517 }
518
519 if let Some(tool_calls) = choice.delta.tool_calls {
520 for tool_call in tool_calls {
521 let entry = self.tool_calls_by_index.entry(tool_call.index).or_default();
522
523 if let Some(tool_id) = tool_call.id {
524 entry.id = tool_id;
525 }
526
527 if let Some(function) = tool_call.function {
528 if let Some(name) = function.name {
529 // At the time of writing this code LM Studio (0.3.15) is incompatible with the OpenAI API:
530 // 1. It sends function name in the first chunk
531 // 2. It sends empty string in the function name field in all subsequent chunks for arguments
532 // According to https://platform.openai.com/docs/guides/function-calling?api-mode=responses#streaming
533 // function name field should be sent only inside the first chunk.
534 if !name.is_empty() {
535 entry.name = name;
536 }
537 }
538
539 if let Some(arguments) = function.arguments {
540 entry.arguments.push_str(&arguments);
541 }
542 }
543 }
544 }
545
546 if let Some(usage) = event.usage {
547 events.push(Ok(LanguageModelCompletionEvent::UsageUpdate(TokenUsage {
548 input_tokens: usage.prompt_tokens,
549 output_tokens: usage.completion_tokens,
550 cache_creation_input_tokens: 0,
551 cache_read_input_tokens: 0,
552 })));
553 }
554
555 match choice.finish_reason.as_deref() {
556 Some("stop") => {
557 events.push(Ok(LanguageModelCompletionEvent::Stop(StopReason::EndTurn)));
558 }
559 Some("tool_calls") => {
560 events.extend(self.tool_calls_by_index.drain().map(|(_, tool_call)| {
561 match serde_json::Value::from_str(&tool_call.arguments) {
562 Ok(input) => Ok(LanguageModelCompletionEvent::ToolUse(
563 LanguageModelToolUse {
564 id: tool_call.id.into(),
565 name: tool_call.name.into(),
566 is_input_complete: true,
567 input,
568 raw_input: tool_call.arguments,
569 thought_signature: None,
570 },
571 )),
572 Err(error) => Ok(LanguageModelCompletionEvent::ToolUseJsonParseError {
573 id: tool_call.id.into(),
574 tool_name: tool_call.name.into(),
575 raw_input: tool_call.arguments.into(),
576 json_parse_error: error.to_string(),
577 }),
578 }
579 }));
580
581 events.push(Ok(LanguageModelCompletionEvent::Stop(StopReason::ToolUse)));
582 }
583 Some(stop_reason) => {
584 log::error!("Unexpected LMStudio stop_reason: {stop_reason:?}",);
585 events.push(Ok(LanguageModelCompletionEvent::Stop(StopReason::EndTurn)));
586 }
587 None => {}
588 }
589
590 events
591 }
592}
593
594#[derive(Default)]
595struct RawToolCall {
596 id: String,
597 name: String,
598 arguments: String,
599}
600
601fn add_message_content_part(
602 new_part: lmstudio::MessagePart,
603 role: Role,
604 messages: &mut Vec<lmstudio::ChatMessage>,
605) {
606 match (role, messages.last_mut()) {
607 (Role::User, Some(lmstudio::ChatMessage::User { content }))
608 | (
609 Role::Assistant,
610 Some(lmstudio::ChatMessage::Assistant {
611 content: Some(content),
612 ..
613 }),
614 )
615 | (Role::System, Some(lmstudio::ChatMessage::System { content })) => {
616 content.push_part(new_part);
617 }
618 _ => {
619 messages.push(match role {
620 Role::User => lmstudio::ChatMessage::User {
621 content: lmstudio::MessageContent::from(vec![new_part]),
622 },
623 Role::Assistant => lmstudio::ChatMessage::Assistant {
624 content: Some(lmstudio::MessageContent::from(vec![new_part])),
625 tool_calls: Vec::new(),
626 },
627 Role::System => lmstudio::ChatMessage::System {
628 content: lmstudio::MessageContent::from(vec![new_part]),
629 },
630 });
631 }
632 }
633}
634
635struct ConfigurationView {
636 state: Entity<State>,
637 loading_models_task: Option<Task<()>>,
638}
639
640impl ConfigurationView {
641 pub fn new(state: Entity<State>, cx: &mut Context<Self>) -> Self {
642 let loading_models_task = Some(cx.spawn({
643 let state = state.clone();
644 async move |this, cx| {
645 if let Some(task) = Some(state.update(cx, |state, cx| state.authenticate(cx))) {
646 task.await.log_err();
647 }
648 this.update(cx, |this, cx| {
649 this.loading_models_task = None;
650 cx.notify();
651 })
652 .log_err();
653 }
654 }));
655
656 Self {
657 state,
658 loading_models_task,
659 }
660 }
661
662 fn retry_connection(&self, cx: &mut App) {
663 self.state
664 .update(cx, |state, cx| state.fetch_models(cx))
665 .detach_and_log_err(cx);
666 }
667}
668
669impl Render for ConfigurationView {
670 fn render(&mut self, _window: &mut Window, cx: &mut Context<Self>) -> impl IntoElement {
671 let is_authenticated = self.state.read(cx).is_authenticated();
672
673 let lmstudio_intro = "Run local LLMs like Llama, Phi, and Qwen.";
674
675 if self.loading_models_task.is_some() {
676 div().child(Label::new("Loading models...")).into_any()
677 } else {
678 v_flex()
679 .gap_2()
680 .child(
681 v_flex().gap_1().child(Label::new(lmstudio_intro)).child(
682 List::new()
683 .child(ListBulletItem::new(
684 "LM Studio needs to be running with at least one model downloaded.",
685 ))
686 .child(
687 ListBulletItem::new("")
688 .child(Label::new("To get your first model, try running"))
689 .child(Label::new("lms get qwen2.5-coder-7b").inline_code(cx)),
690 ),
691 ),
692 )
693 .child(
694 h_flex()
695 .w_full()
696 .justify_between()
697 .gap_2()
698 .child(
699 h_flex()
700 .w_full()
701 .gap_2()
702 .map(|this| {
703 if is_authenticated {
704 this.child(
705 Button::new("lmstudio-site", "LM Studio")
706 .style(ButtonStyle::Subtle)
707 .icon(IconName::ArrowUpRight)
708 .icon_size(IconSize::Small)
709 .icon_color(Color::Muted)
710 .on_click(move |_, _window, cx| {
711 cx.open_url(LMSTUDIO_SITE)
712 })
713 .into_any_element(),
714 )
715 } else {
716 this.child(
717 Button::new(
718 "download_lmstudio_button",
719 "Download LM Studio",
720 )
721 .style(ButtonStyle::Subtle)
722 .icon(IconName::ArrowUpRight)
723 .icon_size(IconSize::Small)
724 .icon_color(Color::Muted)
725 .on_click(move |_, _window, cx| {
726 cx.open_url(LMSTUDIO_DOWNLOAD_URL)
727 })
728 .into_any_element(),
729 )
730 }
731 })
732 .child(
733 Button::new("view-models", "Model Catalog")
734 .style(ButtonStyle::Subtle)
735 .icon(IconName::ArrowUpRight)
736 .icon_size(IconSize::Small)
737 .icon_color(Color::Muted)
738 .on_click(move |_, _window, cx| {
739 cx.open_url(LMSTUDIO_CATALOG_URL)
740 }),
741 ),
742 )
743 .map(|this| {
744 if is_authenticated {
745 this.child(
746 ButtonLike::new("connected")
747 .disabled(true)
748 .cursor_style(gpui::CursorStyle::Arrow)
749 .child(
750 h_flex()
751 .gap_2()
752 .child(Indicator::dot().color(Color::Success))
753 .child(Label::new("Connected"))
754 .into_any_element(),
755 ),
756 )
757 } else {
758 this.child(
759 Button::new("retry_lmstudio_models", "Connect")
760 .icon_position(IconPosition::Start)
761 .icon_size(IconSize::XSmall)
762 .icon(IconName::PlayFilled)
763 .on_click(cx.listener(move |this, _, _window, cx| {
764 this.retry_connection(cx)
765 })),
766 )
767 }
768 }),
769 )
770 .into_any()
771 }
772 }
773}