ZIm/crates/assistant/src/assistant.rs
Antonio Scandurra 8944af7406
Lay the groundwork for collaborating on assistant panel (#13991)
This pull request introduces collaboration for the assistant panel by
turning `Context` into a CRDT. `ContextStore` is responsible for sending
and applying operations, as well as synchronizing missed changes while
the connection was lost.

Contexts are shared on a per-project basis, and only the host can share
them for now. Shared contexts can be accessed via the `History` tab in
the assistant panel.

<img width="1819" alt="image"
src="https://github.com/zed-industries/zed/assets/482957/c7ae46d2-cde3-4b03-b74a-6e9b1555c154">


Please note that this doesn't implement following yet, which is
scheduled for a subsequent pull request.

Release Notes:

- N/A
2024-07-10 17:36:22 +02:00

406 lines
13 KiB
Rust

pub mod assistant_panel;
pub mod assistant_settings;
mod completion_provider;
mod context;
pub mod context_store;
mod inline_assistant;
mod model_selector;
mod prompt_library;
mod prompts;
mod search;
mod slash_command;
mod streaming_diff;
mod terminal_inline_assistant;
pub use assistant_panel::{AssistantPanel, AssistantPanelEvent};
use assistant_settings::{AnthropicModel, AssistantSettings, CloudModel, OllamaModel, OpenAiModel};
use assistant_slash_command::SlashCommandRegistry;
use client::{proto, Client};
use command_palette_hooks::CommandPaletteFilter;
pub use completion_provider::*;
pub use context::*;
pub use context_store::*;
use fs::Fs;
use gpui::{actions, AppContext, Global, SharedString, UpdateGlobal};
use indexed_docs::IndexedDocsRegistry;
pub(crate) use inline_assistant::*;
pub(crate) use model_selector::*;
use semantic_index::{CloudEmbeddingProvider, SemanticIndex};
use serde::{Deserialize, Serialize};
use settings::{Settings, SettingsStore};
use slash_command::{
active_command, default_command, diagnostics_command, docs_command, fetch_command,
file_command, now_command, project_command, prompt_command, search_command, tabs_command,
term_command,
};
use std::{
fmt::{self, Display},
sync::Arc,
};
pub(crate) use streaming_diff::*;
actions!(
assistant,
[
Assist,
Split,
CycleMessageRole,
QuoteSelection,
InsertIntoEditor,
ToggleFocus,
ResetKey,
InlineAssist,
InsertActivePrompt,
DeployHistory,
DeployPromptLibrary,
ApplyEdit,
ConfirmCommand,
ToggleModelSelector
]
);
#[derive(Copy, Clone, Debug, Eq, PartialEq, PartialOrd, Ord, Hash, Serialize, Deserialize)]
pub struct MessageId(clock::Lamport);
impl MessageId {
pub fn as_u64(self) -> u64 {
self.0.as_u64()
}
}
#[derive(Clone, Copy, Serialize, Deserialize, Debug, Eq, PartialEq)]
#[serde(rename_all = "lowercase")]
pub enum Role {
User,
Assistant,
System,
}
impl Role {
pub fn from_proto(role: i32) -> Role {
match proto::LanguageModelRole::from_i32(role) {
Some(proto::LanguageModelRole::LanguageModelUser) => Role::User,
Some(proto::LanguageModelRole::LanguageModelAssistant) => Role::Assistant,
Some(proto::LanguageModelRole::LanguageModelSystem) => Role::System,
Some(proto::LanguageModelRole::LanguageModelTool) => Role::System,
None => Role::User,
}
}
pub fn to_proto(&self) -> proto::LanguageModelRole {
match self {
Role::User => proto::LanguageModelRole::LanguageModelUser,
Role::Assistant => proto::LanguageModelRole::LanguageModelAssistant,
Role::System => proto::LanguageModelRole::LanguageModelSystem,
}
}
pub fn cycle(self) -> Role {
match self {
Role::User => Role::Assistant,
Role::Assistant => Role::System,
Role::System => Role::User,
}
}
}
impl Display for Role {
fn fmt(&self, f: &mut fmt::Formatter<'_>) -> std::fmt::Result {
match self {
Role::User => write!(f, "user"),
Role::Assistant => write!(f, "assistant"),
Role::System => write!(f, "system"),
}
}
}
#[derive(Clone, Debug, Serialize, Deserialize, PartialEq)]
pub enum LanguageModel {
Cloud(CloudModel),
OpenAi(OpenAiModel),
Anthropic(AnthropicModel),
Ollama(OllamaModel),
}
impl Default for LanguageModel {
fn default() -> Self {
LanguageModel::Cloud(CloudModel::default())
}
}
impl LanguageModel {
pub fn telemetry_id(&self) -> String {
match self {
LanguageModel::OpenAi(model) => format!("openai/{}", model.id()),
LanguageModel::Anthropic(model) => format!("anthropic/{}", model.id()),
LanguageModel::Cloud(model) => format!("zed.dev/{}", model.id()),
LanguageModel::Ollama(model) => format!("ollama/{}", model.id()),
}
}
pub fn display_name(&self) -> String {
match self {
LanguageModel::OpenAi(model) => model.display_name().into(),
LanguageModel::Anthropic(model) => model.display_name().into(),
LanguageModel::Cloud(model) => model.display_name().into(),
LanguageModel::Ollama(model) => model.display_name().into(),
}
}
pub fn max_token_count(&self) -> usize {
match self {
LanguageModel::OpenAi(model) => model.max_token_count(),
LanguageModel::Anthropic(model) => model.max_token_count(),
LanguageModel::Cloud(model) => model.max_token_count(),
LanguageModel::Ollama(model) => model.max_token_count(),
}
}
pub fn id(&self) -> &str {
match self {
LanguageModel::OpenAi(model) => model.id(),
LanguageModel::Anthropic(model) => model.id(),
LanguageModel::Cloud(model) => model.id(),
LanguageModel::Ollama(model) => model.id(),
}
}
}
#[derive(Serialize, Deserialize, Debug, Eq, PartialEq)]
pub struct LanguageModelRequestMessage {
pub role: Role,
pub content: String,
}
impl LanguageModelRequestMessage {
pub fn to_proto(&self) -> proto::LanguageModelRequestMessage {
proto::LanguageModelRequestMessage {
role: self.role.to_proto() as i32,
content: self.content.clone(),
tool_calls: Vec::new(),
tool_call_id: None,
}
}
}
#[derive(Debug, Default, Serialize, Deserialize)]
pub struct LanguageModelRequest {
pub model: LanguageModel,
pub messages: Vec<LanguageModelRequestMessage>,
pub stop: Vec<String>,
pub temperature: f32,
}
impl LanguageModelRequest {
pub fn to_proto(&self) -> proto::CompleteWithLanguageModel {
proto::CompleteWithLanguageModel {
model: self.model.id().to_string(),
messages: self.messages.iter().map(|m| m.to_proto()).collect(),
stop: self.stop.clone(),
temperature: self.temperature,
tool_choice: None,
tools: Vec::new(),
}
}
/// Before we send the request to the server, we can perform fixups on it appropriate to the model.
pub fn preprocess(&mut self) {
match &self.model {
LanguageModel::OpenAi(_) => {}
LanguageModel::Anthropic(_) => {}
LanguageModel::Ollama(_) => {}
LanguageModel::Cloud(model) => match model {
CloudModel::Claude3Opus
| CloudModel::Claude3Sonnet
| CloudModel::Claude3Haiku
| CloudModel::Claude3_5Sonnet => {
preprocess_anthropic_request(self);
}
_ => {}
},
}
}
}
#[derive(Serialize, Deserialize, Debug, Eq, PartialEq)]
pub struct LanguageModelResponseMessage {
pub role: Option<Role>,
pub content: Option<String>,
}
#[derive(Deserialize, Debug)]
pub struct LanguageModelUsage {
pub prompt_tokens: u32,
pub completion_tokens: u32,
pub total_tokens: u32,
}
#[derive(Deserialize, Debug)]
pub struct LanguageModelChoiceDelta {
pub index: u32,
pub delta: LanguageModelResponseMessage,
pub finish_reason: Option<String>,
}
#[derive(Clone, Debug, Eq, PartialEq, Serialize, Deserialize)]
pub enum MessageStatus {
Pending,
Done,
Error(SharedString),
}
impl MessageStatus {
pub fn from_proto(status: proto::ContextMessageStatus) -> MessageStatus {
match status.variant {
Some(proto::context_message_status::Variant::Pending(_)) => MessageStatus::Pending,
Some(proto::context_message_status::Variant::Done(_)) => MessageStatus::Done,
Some(proto::context_message_status::Variant::Error(error)) => {
MessageStatus::Error(error.message.into())
}
None => MessageStatus::Pending,
}
}
pub fn to_proto(&self) -> proto::ContextMessageStatus {
match self {
MessageStatus::Pending => proto::ContextMessageStatus {
variant: Some(proto::context_message_status::Variant::Pending(
proto::context_message_status::Pending {},
)),
},
MessageStatus::Done => proto::ContextMessageStatus {
variant: Some(proto::context_message_status::Variant::Done(
proto::context_message_status::Done {},
)),
},
MessageStatus::Error(message) => proto::ContextMessageStatus {
variant: Some(proto::context_message_status::Variant::Error(
proto::context_message_status::Error {
message: message.to_string(),
},
)),
},
}
}
}
/// The state pertaining to the Assistant.
#[derive(Default)]
struct Assistant {
/// Whether the Assistant is enabled.
enabled: bool,
}
impl Global for Assistant {}
impl Assistant {
const NAMESPACE: &'static str = "assistant";
fn set_enabled(&mut self, enabled: bool, cx: &mut AppContext) {
if self.enabled == enabled {
return;
}
self.enabled = enabled;
if !enabled {
CommandPaletteFilter::update_global(cx, |filter, _cx| {
filter.hide_namespace(Self::NAMESPACE);
});
return;
}
CommandPaletteFilter::update_global(cx, |filter, _cx| {
filter.show_namespace(Self::NAMESPACE);
});
}
}
pub fn init(fs: Arc<dyn Fs>, client: Arc<Client>, cx: &mut AppContext) {
cx.set_global(Assistant::default());
AssistantSettings::register(cx);
cx.spawn(|mut cx| {
let client = client.clone();
async move {
let embedding_provider = CloudEmbeddingProvider::new(client.clone());
let semantic_index = SemanticIndex::new(
paths::embeddings_dir().join("semantic-index-db.0.mdb"),
Arc::new(embedding_provider),
&mut cx,
)
.await?;
cx.update(|cx| cx.set_global(semantic_index))
}
})
.detach();
context_store::init(&client);
prompt_library::init(cx);
completion_provider::init(client.clone(), cx);
assistant_slash_command::init(cx);
register_slash_commands(cx);
assistant_panel::init(cx);
inline_assistant::init(fs.clone(), client.telemetry().clone(), cx);
terminal_inline_assistant::init(fs.clone(), client.telemetry().clone(), cx);
IndexedDocsRegistry::init_global(cx);
CommandPaletteFilter::update_global(cx, |filter, _cx| {
filter.hide_namespace(Assistant::NAMESPACE);
});
Assistant::update_global(cx, |assistant, cx| {
let settings = AssistantSettings::get_global(cx);
assistant.set_enabled(settings.enabled, cx);
});
cx.observe_global::<SettingsStore>(|cx| {
Assistant::update_global(cx, |assistant, cx| {
let settings = AssistantSettings::get_global(cx);
assistant.set_enabled(settings.enabled, cx);
});
})
.detach();
}
fn register_slash_commands(cx: &mut AppContext) {
let slash_command_registry = SlashCommandRegistry::global(cx);
slash_command_registry.register_command(file_command::FileSlashCommand, true);
slash_command_registry.register_command(active_command::ActiveSlashCommand, true);
slash_command_registry.register_command(tabs_command::TabsSlashCommand, true);
slash_command_registry.register_command(project_command::ProjectSlashCommand, true);
slash_command_registry.register_command(search_command::SearchSlashCommand, true);
slash_command_registry.register_command(prompt_command::PromptSlashCommand, true);
slash_command_registry.register_command(default_command::DefaultSlashCommand, true);
slash_command_registry.register_command(term_command::TermSlashCommand, true);
slash_command_registry.register_command(now_command::NowSlashCommand, true);
slash_command_registry.register_command(diagnostics_command::DiagnosticsSlashCommand, true);
slash_command_registry.register_command(docs_command::DocsSlashCommand, true);
slash_command_registry.register_command(fetch_command::FetchSlashCommand, false);
}
pub fn humanize_token_count(count: usize) -> String {
match count {
0..=999 => count.to_string(),
1000..=9999 => {
let thousands = count / 1000;
let hundreds = (count % 1000 + 50) / 100;
if hundreds == 0 {
format!("{}k", thousands)
} else if hundreds == 10 {
format!("{}k", thousands + 1)
} else {
format!("{}.{}k", thousands, hundreds)
}
}
_ => format!("{}k", (count + 500) / 1000),
}
}
#[cfg(test)]
#[ctor::ctor]
fn init_logger() {
if std::env::var("RUST_LOG").is_ok() {
env_logger::init();
}
}