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