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Load language models in the background

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This commit is contained in:
Antonio Scandurra 2024-01-24 13:36:44 +01:00
parent 92b0184036
commit 22046ef9a7
4 changed files with 83 additions and 69 deletions
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6
crates/ai/src/providers/open_ai/completion.rs
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@ -201,8 +201,10 @@ pub struct OpenAICompletionProvider {
}
impl OpenAICompletionProvider {
pub fn new(model_name: &str, executor: BackgroundExecutor) -> Self {
let model = OpenAILanguageModel::load(model_name);
pub async fn new(model_name: String, executor: BackgroundExecutor) -> Self {
let model = executor
.spawn(async move { OpenAILanguageModel::load(&model_name) })
.await;
let credential = Arc::new(RwLock::new(ProviderCredential::NoCredentials));
Self {
model,

7
crates/ai/src/providers/open_ai/embedding.rs
View File

@ -67,11 +67,14 @@ struct OpenAIEmbeddingUsage {
}
impl OpenAIEmbeddingProvider {
pub fn new(client: Arc<dyn HttpClient>, executor: BackgroundExecutor) -> Self {
pub async fn new(client: Arc<dyn HttpClient>, executor: BackgroundExecutor) -> Self {
let (rate_limit_count_tx, rate_limit_count_rx) = watch::channel_with(None);
let rate_limit_count_tx = Arc::new(Mutex::new(rate_limit_count_tx));
let model = OpenAILanguageModel::load("text-embedding-ada-002");
// Loading the model is expensive, so ensure this runs off the main thread.
let model = executor
.spawn(async move { OpenAILanguageModel::load("text-embedding-ada-002") })
.await;
let credential = Arc::new(RwLock::new(ProviderCredential::NoCredentials));
OpenAIEmbeddingProvider {

132
crates/assistant/src/assistant_panel.rs
View File

@ -31,9 +31,9 @@ use fs::Fs;
use futures::StreamExt;
use gpui::{
canvas, div, point, relative, rems, uniform_list, Action, AnyElement, AppContext,
AsyncWindowContext, AvailableSpace, ClipboardItem, Context, EventEmitter, FocusHandle,
FocusableView, FontStyle, FontWeight, HighlightStyle, InteractiveElement, IntoElement, Model,
ModelContext, ParentElement, Pixels, PromptLevel, Render, SharedString,
AsyncAppContext, AsyncWindowContext, AvailableSpace, ClipboardItem, Context, EventEmitter,
FocusHandle, FocusableView, FontStyle, FontWeight, HighlightStyle, InteractiveElement,
IntoElement, Model, ModelContext, ParentElement, Pixels, PromptLevel, Render, SharedString,
StatefulInteractiveElement, Styled, Subscription, Task, TextStyle, UniformListScrollHandle,
View, ViewContext, VisualContext, WeakModel, WeakView, WhiteSpace, WindowContext,
};
@ -123,6 +123,10 @@ impl AssistantPanel {
.await
.log_err()
.unwrap_or_default();
// Defaulting currently to GPT4, allow for this to be set via config.
let completion_provider =
OpenAICompletionProvider::new("gpt-4".into(), cx.background_executor().clone())
.await;
// TODO: deserialize state.
let workspace_handle = workspace.clone();
@ -156,11 +160,6 @@ impl AssistantPanel {
});
let semantic_index = SemanticIndex::global(cx);
// Defaulting currently to GPT4, allow for this to be set via config.
let completion_provider = Arc::new(OpenAICompletionProvider::new(
"gpt-4",
cx.background_executor().clone(),
));
let focus_handle = cx.focus_handle();
cx.on_focus_in(&focus_handle, Self::focus_in).detach();
@ -176,7 +175,7 @@ impl AssistantPanel {
zoomed: false,
focus_handle,
toolbar,
completion_provider,
completion_provider: Arc::new(completion_provider),
api_key_editor: None,
languages: workspace.app_state().languages.clone(),
fs: workspace.app_state().fs.clone(),
@ -1079,9 +1078,9 @@ impl AssistantPanel {
cx.spawn(|this, mut cx| async move {
let saved_conversation = fs.load(&path).await?;
let saved_conversation = serde_json::from_str(&saved_conversation)?;
let conversation = cx.new_model(|cx| {
Conversation::deserialize(saved_conversation, path.clone(), languages, cx)
})?;
let conversation =
Conversation::deserialize(saved_conversation, path.clone(), languages, &mut cx)
.await?;
this.update(&mut cx, |this, cx| {
// If, by the time we've loaded the conversation, the user has already opened
// the same conversation, we don't want to open it again.
@ -1462,21 +1461,25 @@ impl Conversation {
}
}
fn deserialize(
async fn deserialize(
saved_conversation: SavedConversation,
path: PathBuf,
language_registry: Arc<LanguageRegistry>,
cx: &mut ModelContext<Self>,
) -> Self {
cx: &mut AsyncAppContext,
) -> Result<Model<Self>> {
let id = match saved_conversation.id {
Some(id) => Some(id),
None => Some(Uuid::new_v4().to_string()),
};
let model = saved_conversation.model;
let completion_provider: Arc<dyn CompletionProvider> = Arc::new(
OpenAICompletionProvider::new(model.full_name(), cx.background_executor().clone()),
OpenAICompletionProvider::new(
model.full_name().into(),
cx.background_executor().clone(),
)
.await,
);
completion_provider.retrieve_credentials(cx);
cx.update(|cx| completion_provider.retrieve_credentials(cx))?;
let markdown = language_registry.language_for_name("Markdown");
let mut message_anchors = Vec::new();
let mut next_message_id = MessageId(0);
@ -1499,32 +1502,34 @@ impl Conversation {
})
.detach_and_log_err(cx);
buffer
});
})?;
let mut this = Self {
id,
message_anchors,
messages_metadata: saved_conversation.message_metadata,
next_message_id,
summary: Some(Summary {
text: saved_conversation.summary,
done: true,
}),
pending_summary: Task::ready(None),
completion_count: Default::default(),
pending_completions: Default::default(),
token_count: None,
max_token_count: tiktoken_rs::model::get_context_size(&model.full_name()),
pending_token_count: Task::ready(None),
model,
_subscriptions: vec![cx.subscribe(&buffer, Self::handle_buffer_event)],
pending_save: Task::ready(Ok(())),
path: Some(path),
buffer,
completion_provider,
};
this.count_remaining_tokens(cx);
this
cx.new_model(|cx| {
let mut this = Self {
id,
message_anchors,
messages_metadata: saved_conversation.message_metadata,
next_message_id,
summary: Some(Summary {
text: saved_conversation.summary,
done: true,
}),
pending_summary: Task::ready(None),
completion_count: Default::default(),
pending_completions: Default::default(),
token_count: None,
max_token_count: tiktoken_rs::model::get_context_size(&model.full_name()),
pending_token_count: Task::ready(None),
model,
_subscriptions: vec![cx.subscribe(&buffer, Self::handle_buffer_event)],
pending_save: Task::ready(Ok(())),
path: Some(path),
buffer,
completion_provider,
};
this.count_remaining_tokens(cx);
this
})
}
fn handle_buffer_event(
@ -3169,7 +3174,7 @@ mod tests {
use super::*;
use crate::MessageId;
use ai::test::FakeCompletionProvider;
use gpui::AppContext;
use gpui::{AppContext, TestAppContext};
use settings::SettingsStore;
#[gpui::test]
@ -3487,16 +3492,17 @@ mod tests {
}
#[gpui::test]
fn test_serialization(cx: &mut AppContext) {
let settings_store = SettingsStore::test(cx);
async fn test_serialization(cx: &mut TestAppContext) {
let settings_store = cx.update(SettingsStore::test);
cx.set_global(settings_store);
init(cx);
cx.update(init);
let registry = Arc::new(LanguageRegistry::test());
let completion_provider = Arc::new(FakeCompletionProvider::new());
let conversation =
cx.new_model(|cx| Conversation::new(registry.clone(), cx, completion_provider));
let buffer = conversation.read(cx).buffer.clone();
let message_0 = conversation.read(cx).message_anchors[0].id;
let buffer = conversation.read_with(cx, |conversation, _| conversation.buffer.clone());
let message_0 =
conversation.read_with(cx, |conversation, _| conversation.message_anchors[0].id);
let message_1 = conversation.update(cx, |conversation, cx| {
conversation
.insert_message_after(message_0, Role::Assistant, MessageStatus::Done, cx)
@ -3517,9 +3523,9 @@ mod tests {
.unwrap()
});
buffer.update(cx, |buffer, cx| buffer.undo(cx));
assert_eq!(buffer.read(cx).text(), "a\nb\nc\n");
assert_eq!(buffer.read_with(cx, |buffer, _| buffer.text()), "a\nb\nc\n");
assert_eq!(
messages(&conversation, cx),
cx.read(|cx| messages(&conversation, cx)),
[
(message_0, Role::User, 0..2),
(message_1.id, Role::Assistant, 2..6),
@ -3527,18 +3533,22 @@ mod tests {
]
);
let deserialized_conversation = cx.new_model(|cx| {
Conversation::deserialize(
conversation.read(cx).serialize(cx),
Default::default(),
registry.clone(),
cx,
)
});
let deserialized_buffer = deserialized_conversation.read(cx).buffer.clone();
assert_eq!(deserialized_buffer.read(cx).text(), "a\nb\nc\n");
let deserialized_conversation = Conversation::deserialize(
conversation.read_with(cx, |conversation, cx| conversation.serialize(cx)),
Default::default(),
registry.clone(),
&mut cx.to_async(),
)
.await
.unwrap();
let deserialized_buffer =
deserialized_conversation.read_with(cx, |conversation, _| conversation.buffer.clone());
assert_eq!(
messages(&deserialized_conversation, cx),
deserialized_buffer.read_with(cx, |buffer, _| buffer.text()),
"a\nb\nc\n"
);
assert_eq!(
cx.read(|cx| messages(&deserialized_conversation, cx)),
[
(message_0, Role::User, 0..2),
(message_1.id, Role::Assistant, 2..6),

7
crates/semantic_index/src/semantic_index.rs
View File

@ -90,13 +90,12 @@ pub fn init(
.detach();
cx.spawn(move |cx| async move {
let embedding_provider =
OpenAIEmbeddingProvider::new(http_client, cx.background_executor().clone()).await;
let semantic_index = SemanticIndex::new(
fs,
db_file_path,
Arc::new(OpenAIEmbeddingProvider::new(
http_client,
cx.background_executor().clone(),
)),
Arc::new(embedding_provider),
language_registry,
cx.clone(),
)