Extract completion provider crate (#14823)
We will soon need `semantic_index` to be able to use
`CompletionProvider`. This is currently impossible due to a cyclic crate
dependency, because `CompletionProvider` lives in the `assistant` crate,
which depends on `semantic_index`.
This PR breaks the dependency cycle by extracting two crates out of
`assistant`: `language_model` and `completion`.
Only one piece of logic changed: [this
code](922fcaf5a6 (diff-3857b3707687a4d585f1200eec4c34a7a079eae8d303b4ce5b4fce46234ace9fR61-R69)).
* As of https://github.com/zed-industries/zed/pull/13276, whenever we
ask a given completion provider for its available models, OpenAI
providers would go and ask the global assistant settings whether the
user had configured an `available_models` setting, and if so, return
that.
* This PR changes it so that instead of eagerly asking the assistant
settings for this info (the new crate must not depend on `assistant`, or
else the dependency cycle would be back), OpenAI completion providers
now store the user-configured settings as part of their struct, and
whenever the settings change, we update the provider.
In theory, this change should not change user-visible behavior...but
since it's the only change in this large PR that's more than just moving
code around, I'm mentioning it here in case there's an unexpected
regression in practice! (cc @amtoaer in case you'd like to try out this
branch and verify that the feature is still working the way you expect.)
Release Notes:
- N/A
---------
Co-authored-by: Marshall Bowers <elliott.codes@gmail.com>
This commit is contained in:
Richard Feldman
GitHub
parent
b9a53ffa0b
commit
ec487d8f64
30 changed files with 820 additions and 610 deletions
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@ -1,6 +1,5 @@
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pub mod assistant_panel;
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pub mod assistant_settings;
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mod completion_provider;
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mod context;
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pub mod context_store;
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mod inline_assistant;
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@ -12,17 +11,20 @@ mod streaming_diff;
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mod terminal_inline_assistant;
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pub use assistant_panel::{AssistantPanel, AssistantPanelEvent};
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use assistant_settings::{AnthropicModel, AssistantSettings, CloudModel, OllamaModel, OpenAiModel};
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use assistant_settings::AssistantSettings;
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use assistant_slash_command::SlashCommandRegistry;
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use client::{proto, Client};
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use command_palette_hooks::CommandPaletteFilter;
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pub use completion_provider::*;
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use completion::CompletionProvider;
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pub use context::*;
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pub use context_store::*;
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use fs::Fs;
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use gpui::{actions, impl_actions, AppContext, Global, SharedString, UpdateGlobal};
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use gpui::{
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actions, impl_actions, AppContext, BorrowAppContext, Global, SharedString, UpdateGlobal,
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};
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use indexed_docs::IndexedDocsRegistry;
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pub(crate) use inline_assistant::*;
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use language_model::LanguageModelResponseMessage;
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pub(crate) use model_selector::*;
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use semantic_index::{CloudEmbeddingProvider, SemanticIndex};
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use serde::{Deserialize, Serialize};
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@ -32,10 +34,7 @@ use slash_command::{
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file_command, now_command, project_command, prompt_command, search_command, symbols_command,
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tabs_command, term_command,
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};
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use std::{
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fmt::{self, Display},
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sync::Arc,
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};
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use std::sync::Arc;
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pub(crate) use streaming_diff::*;
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actions!(
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@ -73,166 +72,6 @@ impl MessageId {
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}
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}
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#[derive(Clone, Copy, Serialize, Deserialize, Debug, Eq, PartialEq)]
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#[serde(rename_all = "lowercase")]
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pub enum Role {
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User,
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Assistant,
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System,
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}
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impl Role {
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pub fn from_proto(role: i32) -> Role {
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match proto::LanguageModelRole::from_i32(role) {
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Some(proto::LanguageModelRole::LanguageModelUser) => Role::User,
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Some(proto::LanguageModelRole::LanguageModelAssistant) => Role::Assistant,
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Some(proto::LanguageModelRole::LanguageModelSystem) => Role::System,
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Some(proto::LanguageModelRole::LanguageModelTool) => Role::System,
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None => Role::User,
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}
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}
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pub fn to_proto(&self) -> proto::LanguageModelRole {
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match self {
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Role::User => proto::LanguageModelRole::LanguageModelUser,
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Role::Assistant => proto::LanguageModelRole::LanguageModelAssistant,
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Role::System => proto::LanguageModelRole::LanguageModelSystem,
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}
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}
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pub fn cycle(self) -> Role {
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match self {
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Role::User => Role::Assistant,
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Role::Assistant => Role::System,
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Role::System => Role::User,
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}
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}
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}
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impl Display for Role {
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fn fmt(&self, f: &mut fmt::Formatter<'_>) -> std::fmt::Result {
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match self {
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Role::User => write!(f, "user"),
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Role::Assistant => write!(f, "assistant"),
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Role::System => write!(f, "system"),
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}
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}
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}
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#[derive(Clone, Debug, Serialize, Deserialize, PartialEq)]
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pub enum LanguageModel {
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Cloud(CloudModel),
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OpenAi(OpenAiModel),
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Anthropic(AnthropicModel),
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Ollama(OllamaModel),
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}
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impl Default for LanguageModel {
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fn default() -> Self {
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LanguageModel::Cloud(CloudModel::default())
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}
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}
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impl LanguageModel {
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pub fn telemetry_id(&self) -> String {
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match self {
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LanguageModel::OpenAi(model) => format!("openai/{}", model.id()),
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LanguageModel::Anthropic(model) => format!("anthropic/{}", model.id()),
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LanguageModel::Cloud(model) => format!("zed.dev/{}", model.id()),
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LanguageModel::Ollama(model) => format!("ollama/{}", model.id()),
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}
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}
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pub fn display_name(&self) -> String {
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match self {
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LanguageModel::OpenAi(model) => model.display_name().into(),
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LanguageModel::Anthropic(model) => model.display_name().into(),
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LanguageModel::Cloud(model) => model.display_name().into(),
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LanguageModel::Ollama(model) => model.display_name().into(),
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}
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}
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pub fn max_token_count(&self) -> usize {
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match self {
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LanguageModel::OpenAi(model) => model.max_token_count(),
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LanguageModel::Anthropic(model) => model.max_token_count(),
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LanguageModel::Cloud(model) => model.max_token_count(),
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LanguageModel::Ollama(model) => model.max_token_count(),
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}
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}
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pub fn id(&self) -> &str {
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match self {
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LanguageModel::OpenAi(model) => model.id(),
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LanguageModel::Anthropic(model) => model.id(),
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LanguageModel::Cloud(model) => model.id(),
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LanguageModel::Ollama(model) => model.id(),
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}
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}
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}
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#[derive(Serialize, Deserialize, Debug, Eq, PartialEq)]
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pub struct LanguageModelRequestMessage {
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pub role: Role,
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pub content: String,
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}
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impl LanguageModelRequestMessage {
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pub fn to_proto(&self) -> proto::LanguageModelRequestMessage {
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proto::LanguageModelRequestMessage {
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role: self.role.to_proto() as i32,
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content: self.content.clone(),
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tool_calls: Vec::new(),
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tool_call_id: None,
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}
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}
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}
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#[derive(Debug, Default, Serialize, Deserialize)]
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pub struct LanguageModelRequest {
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pub model: LanguageModel,
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pub messages: Vec<LanguageModelRequestMessage>,
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pub stop: Vec<String>,
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pub temperature: f32,
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}
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impl LanguageModelRequest {
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pub fn to_proto(&self) -> proto::CompleteWithLanguageModel {
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proto::CompleteWithLanguageModel {
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model: self.model.id().to_string(),
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messages: self.messages.iter().map(|m| m.to_proto()).collect(),
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stop: self.stop.clone(),
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temperature: self.temperature,
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tool_choice: None,
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tools: Vec::new(),
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}
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}
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/// Before we send the request to the server, we can perform fixups on it appropriate to the model.
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pub fn preprocess(&mut self) {
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match &self.model {
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LanguageModel::OpenAi(_) => {}
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LanguageModel::Anthropic(_) => {}
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LanguageModel::Ollama(_) => {}
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LanguageModel::Cloud(model) => match model {
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CloudModel::Claude3Opus
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| CloudModel::Claude3Sonnet
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| CloudModel::Claude3Haiku
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| CloudModel::Claude3_5Sonnet => {
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preprocess_anthropic_request(self);
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}
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_ => {}
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},
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}
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}
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}
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#[derive(Serialize, Deserialize, Debug, Eq, PartialEq)]
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pub struct LanguageModelResponseMessage {
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pub role: Option<Role>,
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pub content: Option<String>,
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}
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#[derive(Deserialize, Debug)]
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pub struct LanguageModelUsage {
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pub prompt_tokens: u32,
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@ -343,7 +182,7 @@ pub fn init(fs: Arc<dyn Fs>, client: Arc<Client>, cx: &mut AppContext) {
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context_store::init(&client);
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prompt_library::init(cx);
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completion_provider::init(client.clone(), cx);
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init_completion_provider(Arc::clone(&client), cx);
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assistant_slash_command::init(cx);
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register_slash_commands(cx);
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assistant_panel::init(cx);
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@ -368,6 +207,20 @@ pub fn init(fs: Arc<dyn Fs>, client: Arc<Client>, cx: &mut AppContext) {
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.detach();
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}
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fn init_completion_provider(client: Arc<Client>, cx: &mut AppContext) {
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let provider = assistant_settings::create_provider_from_settings(client.clone(), 0, cx);
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cx.set_global(CompletionProvider::new(provider, Some(client)));
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let mut settings_version = 0;
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cx.observe_global::<SettingsStore>(move |cx| {
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settings_version += 1;
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cx.update_global::<CompletionProvider, _>(|provider, cx| {
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assistant_settings::update_completion_provider_settings(provider, settings_version, cx);
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})
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})
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.detach();
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}
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fn register_slash_commands(cx: &mut AppContext) {
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let slash_command_registry = SlashCommandRegistry::global(cx);
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slash_command_registry.register_command(file_command::FileSlashCommand, true);
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