1use anyhow::{Result, anyhow};
2use futures::{FutureExt, StreamExt, future::BoxFuture, stream::BoxStream};
3use futures::{Stream, TryFutureExt, stream};
4use gpui::{AnyView, App, AsyncApp, Context, Subscription, Task};
5use http_client::HttpClient;
6use language_model::{
7 AuthenticateError, LanguageModel, LanguageModelCompletionError, LanguageModelCompletionEvent,
8 LanguageModelId, LanguageModelName, LanguageModelProvider, LanguageModelProviderId,
9 LanguageModelProviderName, LanguageModelProviderState, LanguageModelRequest,
10 LanguageModelRequestTool, LanguageModelToolChoice, LanguageModelToolUse,
11 LanguageModelToolUseId, MessageContent, RateLimiter, Role, StopReason, TokenUsage,
12};
13use ollama::{
14 ChatMessage, ChatOptions, ChatRequest, ChatResponseDelta, KeepAlive, OllamaFunctionTool,
15 OllamaToolCall, get_models, show_model, stream_chat_completion,
16};
17use schemars::JsonSchema;
18use serde::{Deserialize, Serialize};
19use settings::{Settings, SettingsStore};
20use std::pin::Pin;
21use std::sync::atomic::{AtomicU64, Ordering};
22use std::{collections::HashMap, sync::Arc};
23use ui::{ButtonLike, Indicator, List, prelude::*};
24use util::ResultExt;
25
26use crate::AllLanguageModelSettings;
27use crate::ui::InstructionListItem;
28
29const OLLAMA_DOWNLOAD_URL: &str = "https://ollama.com/download";
30const OLLAMA_LIBRARY_URL: &str = "https://ollama.com/library";
31const OLLAMA_SITE: &str = "https://ollama.com/";
32
33const PROVIDER_ID: LanguageModelProviderId = LanguageModelProviderId::new("ollama");
34const PROVIDER_NAME: LanguageModelProviderName = LanguageModelProviderName::new("Ollama");
35
36#[derive(Default, Debug, Clone, PartialEq)]
37pub struct OllamaSettings {
38 pub api_url: String,
39 pub available_models: Vec<AvailableModel>,
40}
41
42#[derive(Clone, Debug, PartialEq, Serialize, Deserialize, JsonSchema)]
43pub struct AvailableModel {
44 /// The model name in the Ollama API (e.g. "llama3.2:latest")
45 pub name: String,
46 /// The model's name in Zed's UI, such as in the model selector dropdown menu in the assistant panel.
47 pub display_name: Option<String>,
48 /// The Context Length parameter to the model (aka num_ctx or n_ctx)
49 pub max_tokens: u64,
50 /// The number of seconds to keep the connection open after the last request
51 pub keep_alive: Option<KeepAlive>,
52 /// Whether the model supports tools
53 pub supports_tools: Option<bool>,
54 /// Whether the model supports vision
55 pub supports_images: Option<bool>,
56 /// Whether to enable think mode
57 pub supports_thinking: Option<bool>,
58}
59
60pub struct OllamaLanguageModelProvider {
61 http_client: Arc<dyn HttpClient>,
62 state: gpui::Entity<State>,
63}
64
65pub struct State {
66 http_client: Arc<dyn HttpClient>,
67 available_models: Vec<ollama::Model>,
68 fetch_model_task: Option<Task<Result<()>>>,
69 _subscription: Subscription,
70}
71
72impl State {
73 fn is_authenticated(&self) -> bool {
74 !self.available_models.is_empty()
75 }
76
77 fn fetch_models(&mut self, cx: &mut Context<Self>) -> Task<Result<()>> {
78 let settings = &AllLanguageModelSettings::get_global(cx).ollama;
79 let http_client = Arc::clone(&self.http_client);
80 let api_url = settings.api_url.clone();
81
82 // As a proxy for the server being "authenticated", we'll check if its up by fetching the models
83 cx.spawn(async move |this, cx| {
84 let models = get_models(http_client.as_ref(), &api_url, None).await?;
85
86 let tasks = models
87 .into_iter()
88 // Since there is no metadata from the Ollama API
89 // indicating which models are embedding models,
90 // simply filter out models with "-embed" in their name
91 .filter(|model| !model.name.contains("-embed"))
92 .map(|model| {
93 let http_client = Arc::clone(&http_client);
94 let api_url = api_url.clone();
95 async move {
96 let name = model.name.as_str();
97 let capabilities = show_model(http_client.as_ref(), &api_url, name).await?;
98 let ollama_model = ollama::Model::new(
99 name,
100 None,
101 None,
102 Some(capabilities.supports_tools()),
103 Some(capabilities.supports_vision()),
104 Some(capabilities.supports_thinking()),
105 );
106 Ok(ollama_model)
107 }
108 });
109
110 // Rate-limit capability fetches
111 // since there is an arbitrary number of models available
112 let mut ollama_models: Vec<_> = futures::stream::iter(tasks)
113 .buffer_unordered(5)
114 .collect::<Vec<Result<_>>>()
115 .await
116 .into_iter()
117 .collect::<Result<Vec<_>>>()?;
118
119 ollama_models.sort_by(|a, b| a.name.cmp(&b.name));
120
121 this.update(cx, |this, cx| {
122 this.available_models = ollama_models;
123 cx.notify();
124 })
125 })
126 }
127
128 fn restart_fetch_models_task(&mut self, cx: &mut Context<Self>) {
129 let task = self.fetch_models(cx);
130 self.fetch_model_task.replace(task);
131 }
132
133 fn authenticate(&mut self, cx: &mut Context<Self>) -> Task<Result<(), AuthenticateError>> {
134 if self.is_authenticated() {
135 return Task::ready(Ok(()));
136 }
137
138 let fetch_models_task = self.fetch_models(cx);
139 cx.spawn(async move |_this, _cx| Ok(fetch_models_task.await?))
140 }
141}
142
143impl OllamaLanguageModelProvider {
144 pub fn new(http_client: Arc<dyn HttpClient>, cx: &mut App) -> Self {
145 let this = Self {
146 http_client: http_client.clone(),
147 state: cx.new(|cx| {
148 let subscription = cx.observe_global::<SettingsStore>({
149 let mut settings = AllLanguageModelSettings::get_global(cx).ollama.clone();
150 move |this: &mut State, cx| {
151 let new_settings = &AllLanguageModelSettings::get_global(cx).ollama;
152 if &settings != new_settings {
153 settings = new_settings.clone();
154 this.restart_fetch_models_task(cx);
155 cx.notify();
156 }
157 }
158 });
159
160 State {
161 http_client,
162 available_models: Default::default(),
163 fetch_model_task: None,
164 _subscription: subscription,
165 }
166 }),
167 };
168 this.state
169 .update(cx, |state, cx| state.restart_fetch_models_task(cx));
170 this
171 }
172}
173
174impl LanguageModelProviderState for OllamaLanguageModelProvider {
175 type ObservableEntity = State;
176
177 fn observable_entity(&self) -> Option<gpui::Entity<Self::ObservableEntity>> {
178 Some(self.state.clone())
179 }
180}
181
182impl LanguageModelProvider for OllamaLanguageModelProvider {
183 fn id(&self) -> LanguageModelProviderId {
184 PROVIDER_ID
185 }
186
187 fn name(&self) -> LanguageModelProviderName {
188 PROVIDER_NAME
189 }
190
191 fn icon(&self) -> IconName {
192 IconName::AiOllama
193 }
194
195 fn default_model(&self, _: &App) -> Option<Arc<dyn LanguageModel>> {
196 // We shouldn't try to select default model, because it might lead to a load call for an unloaded model.
197 // In a constrained environment where user might not have enough resources it'll be a bad UX to select something
198 // to load by default.
199 None
200 }
201
202 fn default_fast_model(&self, _: &App) -> Option<Arc<dyn LanguageModel>> {
203 // See explanation for default_model.
204 None
205 }
206
207 fn provided_models(&self, cx: &App) -> Vec<Arc<dyn LanguageModel>> {
208 let mut models: HashMap<String, ollama::Model> = HashMap::new();
209
210 // Add models from the Ollama API
211 for model in self.state.read(cx).available_models.iter() {
212 models.insert(model.name.clone(), model.clone());
213 }
214
215 // Override with available models from settings
216 for model in AllLanguageModelSettings::get_global(cx)
217 .ollama
218 .available_models
219 .iter()
220 {
221 models.insert(
222 model.name.clone(),
223 ollama::Model {
224 name: model.name.clone(),
225 display_name: model.display_name.clone(),
226 max_tokens: model.max_tokens,
227 keep_alive: model.keep_alive.clone(),
228 supports_tools: model.supports_tools,
229 supports_vision: model.supports_images,
230 supports_thinking: model.supports_thinking,
231 },
232 );
233 }
234
235 let mut models = models
236 .into_values()
237 .map(|model| {
238 Arc::new(OllamaLanguageModel {
239 id: LanguageModelId::from(model.name.clone()),
240 model,
241 http_client: self.http_client.clone(),
242 request_limiter: RateLimiter::new(4),
243 }) as Arc<dyn LanguageModel>
244 })
245 .collect::<Vec<_>>();
246 models.sort_by_key(|model| model.name());
247 models
248 }
249
250 fn is_authenticated(&self, cx: &App) -> bool {
251 self.state.read(cx).is_authenticated()
252 }
253
254 fn authenticate(&self, cx: &mut App) -> Task<Result<(), AuthenticateError>> {
255 self.state.update(cx, |state, cx| state.authenticate(cx))
256 }
257
258 fn configuration_view(
259 &self,
260 _target_agent: language_model::ConfigurationViewTargetAgent,
261 window: &mut Window,
262 cx: &mut App,
263 ) -> AnyView {
264 let state = self.state.clone();
265 cx.new(|cx| ConfigurationView::new(state, window, cx))
266 .into()
267 }
268
269 fn reset_credentials(&self, cx: &mut App) -> Task<Result<()>> {
270 self.state.update(cx, |state, cx| state.fetch_models(cx))
271 }
272}
273
274pub struct OllamaLanguageModel {
275 id: LanguageModelId,
276 model: ollama::Model,
277 http_client: Arc<dyn HttpClient>,
278 request_limiter: RateLimiter,
279}
280
281impl OllamaLanguageModel {
282 fn to_ollama_request(&self, request: LanguageModelRequest) -> ChatRequest {
283 let supports_vision = self.model.supports_vision.unwrap_or(false);
284
285 ChatRequest {
286 model: self.model.name.clone(),
287 messages: request
288 .messages
289 .into_iter()
290 .map(|msg| {
291 let images = if supports_vision {
292 msg.content
293 .iter()
294 .filter_map(|content| match content {
295 MessageContent::Image(image) => Some(image.source.to_string()),
296 _ => None,
297 })
298 .collect::<Vec<String>>()
299 } else {
300 vec![]
301 };
302
303 match msg.role {
304 Role::User => ChatMessage::User {
305 content: msg.string_contents(),
306 images: if images.is_empty() {
307 None
308 } else {
309 Some(images)
310 },
311 },
312 Role::Assistant => {
313 let content = msg.string_contents();
314 let thinking =
315 msg.content.into_iter().find_map(|content| match content {
316 MessageContent::Thinking { text, .. } if !text.is_empty() => {
317 Some(text)
318 }
319 _ => None,
320 });
321 ChatMessage::Assistant {
322 content,
323 tool_calls: None,
324 images: if images.is_empty() {
325 None
326 } else {
327 Some(images)
328 },
329 thinking,
330 }
331 }
332 Role::System => ChatMessage::System {
333 content: msg.string_contents(),
334 },
335 }
336 })
337 .collect(),
338 keep_alive: self.model.keep_alive.clone().unwrap_or_default(),
339 stream: true,
340 options: Some(ChatOptions {
341 num_ctx: Some(self.model.max_tokens),
342 stop: Some(request.stop),
343 temperature: request.temperature.or(Some(1.0)),
344 ..Default::default()
345 }),
346 think: self
347 .model
348 .supports_thinking
349 .map(|supports_thinking| supports_thinking && request.thinking_allowed),
350 tools: request.tools.into_iter().map(tool_into_ollama).collect(),
351 }
352 }
353}
354
355impl LanguageModel for OllamaLanguageModel {
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 PROVIDER_ID
366 }
367
368 fn provider_name(&self) -> LanguageModelProviderName {
369 PROVIDER_NAME
370 }
371
372 fn supports_tools(&self) -> bool {
373 self.model.supports_tools.unwrap_or(false)
374 }
375
376 fn supports_images(&self) -> bool {
377 self.model.supports_vision.unwrap_or(false)
378 }
379
380 fn supports_tool_choice(&self, choice: LanguageModelToolChoice) -> bool {
381 match choice {
382 LanguageModelToolChoice::Auto => false,
383 LanguageModelToolChoice::Any => false,
384 LanguageModelToolChoice::None => false,
385 }
386 }
387
388 fn telemetry_id(&self) -> String {
389 format!("ollama/{}", self.model.id())
390 }
391
392 fn max_token_count(&self) -> u64 {
393 self.model.max_token_count()
394 }
395
396 fn count_tokens(
397 &self,
398 request: LanguageModelRequest,
399 _cx: &App,
400 ) -> BoxFuture<'static, Result<u64>> {
401 // There is no endpoint for this _yet_ in Ollama
402 // see: https://github.com/ollama/ollama/issues/1716 and https://github.com/ollama/ollama/issues/3582
403 let token_count = request
404 .messages
405 .iter()
406 .map(|msg| msg.string_contents().chars().count())
407 .sum::<usize>()
408 / 4;
409
410 async move { Ok(token_count as u64) }.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 LanguageModelCompletionError,
422 >,
423 > {
424 let request = self.to_ollama_request(request);
425
426 let http_client = self.http_client.clone();
427 let Ok(api_url) = cx.update(|cx| {
428 let settings = &AllLanguageModelSettings::get_global(cx).ollama;
429 settings.api_url.clone()
430 }) else {
431 return futures::future::ready(Err(anyhow!("App state dropped").into())).boxed();
432 };
433
434 let future = self.request_limiter.stream(async move {
435 let stream = stream_chat_completion(http_client.as_ref(), &api_url, request).await?;
436 let stream = map_to_language_model_completion_events(stream);
437 Ok(stream)
438 });
439
440 future.map_ok(|f| f.boxed()).boxed()
441 }
442}
443
444fn map_to_language_model_completion_events(
445 stream: Pin<Box<dyn Stream<Item = anyhow::Result<ChatResponseDelta>> + Send>>,
446) -> impl Stream<Item = Result<LanguageModelCompletionEvent, LanguageModelCompletionError>> {
447 // Used for creating unique tool use ids
448 static TOOL_CALL_COUNTER: AtomicU64 = AtomicU64::new(0);
449
450 struct State {
451 stream: Pin<Box<dyn Stream<Item = anyhow::Result<ChatResponseDelta>> + Send>>,
452 used_tools: bool,
453 }
454
455 // We need to create a ToolUse and Stop event from a single
456 // response from the original stream
457 let stream = stream::unfold(
458 State {
459 stream,
460 used_tools: false,
461 },
462 async move |mut state| {
463 let response = state.stream.next().await?;
464
465 let delta = match response {
466 Ok(delta) => delta,
467 Err(e) => {
468 let event = Err(LanguageModelCompletionError::from(anyhow!(e)));
469 return Some((vec![event], state));
470 }
471 };
472
473 let mut events = Vec::new();
474
475 match delta.message {
476 ChatMessage::User { content, images: _ } => {
477 events.push(Ok(LanguageModelCompletionEvent::Text(content)));
478 }
479 ChatMessage::System { content } => {
480 events.push(Ok(LanguageModelCompletionEvent::Text(content)));
481 }
482 ChatMessage::Assistant {
483 content,
484 tool_calls,
485 images: _,
486 thinking,
487 } => {
488 if let Some(text) = thinking {
489 events.push(Ok(LanguageModelCompletionEvent::Thinking {
490 text,
491 signature: None,
492 }));
493 }
494
495 if let Some(tool_call) = tool_calls.and_then(|v| v.into_iter().next()) {
496 match tool_call {
497 OllamaToolCall::Function(function) => {
498 let tool_id = format!(
499 "{}-{}",
500 &function.name,
501 TOOL_CALL_COUNTER.fetch_add(1, Ordering::Relaxed)
502 );
503 let event =
504 LanguageModelCompletionEvent::ToolUse(LanguageModelToolUse {
505 id: LanguageModelToolUseId::from(tool_id),
506 name: Arc::from(function.name),
507 raw_input: function.arguments.to_string(),
508 input: function.arguments,
509 is_input_complete: true,
510 });
511 events.push(Ok(event));
512 state.used_tools = true;
513 }
514 }
515 } else if !content.is_empty() {
516 events.push(Ok(LanguageModelCompletionEvent::Text(content)));
517 }
518 }
519 };
520
521 if delta.done {
522 events.push(Ok(LanguageModelCompletionEvent::UsageUpdate(TokenUsage {
523 input_tokens: delta.prompt_eval_count.unwrap_or(0),
524 output_tokens: delta.eval_count.unwrap_or(0),
525 cache_creation_input_tokens: 0,
526 cache_read_input_tokens: 0,
527 })));
528 if state.used_tools {
529 state.used_tools = false;
530 events.push(Ok(LanguageModelCompletionEvent::Stop(StopReason::ToolUse)));
531 } else {
532 events.push(Ok(LanguageModelCompletionEvent::Stop(StopReason::EndTurn)));
533 }
534 }
535
536 Some((events, state))
537 },
538 );
539
540 stream.flat_map(futures::stream::iter)
541}
542
543struct ConfigurationView {
544 state: gpui::Entity<State>,
545 loading_models_task: Option<Task<()>>,
546}
547
548impl ConfigurationView {
549 pub fn new(state: gpui::Entity<State>, window: &mut Window, cx: &mut Context<Self>) -> Self {
550 let loading_models_task = Some(cx.spawn_in(window, {
551 let state = state.clone();
552 async move |this, cx| {
553 if let Some(task) = state
554 .update(cx, |state, cx| state.authenticate(cx))
555 .log_err()
556 {
557 task.await.log_err();
558 }
559 this.update(cx, |this, cx| {
560 this.loading_models_task = None;
561 cx.notify();
562 })
563 .log_err();
564 }
565 }));
566
567 Self {
568 state,
569 loading_models_task,
570 }
571 }
572
573 fn retry_connection(&self, cx: &mut App) {
574 self.state
575 .update(cx, |state, cx| state.fetch_models(cx))
576 .detach_and_log_err(cx);
577 }
578}
579
580impl Render for ConfigurationView {
581 fn render(&mut self, _: &mut Window, cx: &mut Context<Self>) -> impl IntoElement {
582 let is_authenticated = self.state.read(cx).is_authenticated();
583
584 let ollama_intro =
585 "Get up & running with Llama 3.3, Mistral, Gemma 2, and other LLMs with Ollama.";
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(ollama_intro)).child(
594 List::new()
595 .child(InstructionListItem::text_only("Ollama must be running with at least one model installed to use it in the assistant."))
596 .child(InstructionListItem::text_only(
597 "Once installed, try `ollama run llama3.2`",
598 )),
599 ),
600 )
601 .child(
602 h_flex()
603 .w_full()
604 .justify_between()
605 .gap_2()
606 .child(
607 h_flex()
608 .w_full()
609 .gap_2()
610 .map(|this| {
611 if is_authenticated {
612 this.child(
613 Button::new("ollama-site", "Ollama")
614 .style(ButtonStyle::Subtle)
615 .icon(IconName::ArrowUpRight)
616 .icon_size(IconSize::Small)
617 .icon_color(Color::Muted)
618 .on_click(move |_, _, cx| cx.open_url(OLLAMA_SITE))
619 .into_any_element(),
620 )
621 } else {
622 this.child(
623 Button::new(
624 "download_ollama_button",
625 "Download Ollama",
626 )
627 .style(ButtonStyle::Subtle)
628 .icon(IconName::ArrowUpRight)
629 .icon_size(IconSize::Small)
630 .icon_color(Color::Muted)
631 .on_click(move |_, _, cx| {
632 cx.open_url(OLLAMA_DOWNLOAD_URL)
633 })
634 .into_any_element(),
635 )
636 }
637 })
638 .child(
639 Button::new("view-models", "View All Models")
640 .style(ButtonStyle::Subtle)
641 .icon(IconName::ArrowUpRight)
642 .icon_size(IconSize::Small)
643 .icon_color(Color::Muted)
644 .on_click(move |_, _, cx| cx.open_url(OLLAMA_LIBRARY_URL)),
645 ),
646 )
647 .map(|this| {
648 if is_authenticated {
649 this.child(
650 ButtonLike::new("connected")
651 .disabled(true)
652 .cursor_style(gpui::CursorStyle::Arrow)
653 .child(
654 h_flex()
655 .gap_2()
656 .child(Indicator::dot().color(Color::Success))
657 .child(Label::new("Connected"))
658 .into_any_element(),
659 ),
660 )
661 } else {
662 this.child(
663 Button::new("retry_ollama_models", "Connect")
664 .icon_position(IconPosition::Start)
665 .icon_size(IconSize::XSmall)
666 .icon(IconName::PlayFilled)
667 .on_click(cx.listener(move |this, _, _, cx| {
668 this.retry_connection(cx)
669 })),
670 )
671 }
672 })
673 )
674 .into_any()
675 }
676 }
677}
678
679fn tool_into_ollama(tool: LanguageModelRequestTool) -> ollama::OllamaTool {
680 ollama::OllamaTool::Function {
681 function: OllamaFunctionTool {
682 name: tool.name,
683 description: Some(tool.description),
684 parameters: Some(tool.input_schema),
685 },
686 }
687}