Allow AI interactions to be proxied through Zed's server so you don't need an API key (#7367)
Co-authored-by: Antonio <antonio@zed.dev> Resurrected this from some assistant work I did in Spring of 2023. - [x] Resurrect streaming responses - [x] Use streaming responses to enable AI via Zed's servers by default (but preserve API key option for now) - [x] Simplify protobuf - [x] Proxy to OpenAI on zed.dev - [x] Proxy to Gemini on zed.dev - [x] Improve UX for switching between openAI and google models - We current disallow cycling when setting a custom model, but we need a better solution to keep OpenAI models available while testing the google ones - [x] Show remaining tokens correctly for Google models - [x] Remove semantic index - [x] Delete `ai` crate - [x] Cloud front so we can ban abuse - [x] Rate-limiting - [x] Fix panic when using inline assistant - [x] Double check the upgraded `AssistantSettings` are backwards-compatible - [x] Add hosted LLM interaction behind a `language-models` feature flag. Release Notes: - We are temporarily removing the semantic index in order to redesign it from scratch. --------- Co-authored-by: Antonio <antonio@zed.dev> Co-authored-by: Antonio Scandurra <me@as-cii.com> Co-authored-by: Thorsten <thorsten@zed.dev> Co-authored-by: Max <max@zed.dev>
This commit is contained in:
Nathan Sobo
GitHub
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commit
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87 changed files with 3647 additions and 8937 deletions
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@ -1,22 +1,24 @@
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pub mod assistant_panel;
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pub mod assistant_settings;
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mod codegen;
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mod completion_provider;
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mod prompts;
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mod saved_conversation;
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mod streaming_diff;
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use ai::providers::open_ai::Role;
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use anyhow::Result;
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pub use assistant_panel::AssistantPanel;
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use assistant_settings::OpenAiModel;
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use assistant_settings::{AssistantSettings, OpenAiModel, ZedDotDevModel};
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use chrono::{DateTime, Local};
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use collections::HashMap;
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use fs::Fs;
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use futures::StreamExt;
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use client::{proto, Client};
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pub(crate) use completion_provider::*;
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use gpui::{actions, AppContext, SharedString};
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use regex::Regex;
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pub(crate) use saved_conversation::*;
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use serde::{Deserialize, Serialize};
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use std::{cmp::Reverse, ffi::OsStr, path::PathBuf, sync::Arc};
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use util::paths::CONVERSATIONS_DIR;
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use settings::Settings;
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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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actions!(
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assistant,
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@ -30,7 +32,6 @@ actions!(
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ResetKey,
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InlineAssist,
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ToggleIncludeConversation,
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ToggleRetrieveContext,
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]
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);
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@ -39,6 +40,139 @@ actions!(
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)]
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struct MessageId(usize);
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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 cycle(&mut self) {
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*self = 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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ZedDotDev(ZedDotDevModel),
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OpenAi(OpenAiModel),
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}
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impl Default for LanguageModel {
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fn default() -> Self {
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LanguageModel::ZedDotDev(ZedDotDevModel::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::ZedDotDev(model) => format!("zed.dev/{}", 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) => format!("openai/{}", model.display_name()),
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LanguageModel::ZedDotDev(model) => format!("zed.dev/{}", model.display_name()),
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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) => tiktoken_rs::model::get_context_size(model.id()),
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LanguageModel::ZedDotDev(model) => match model {
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ZedDotDevModel::GptThreePointFiveTurbo
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| ZedDotDevModel::GptFour
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| ZedDotDevModel::GptFourTurbo => tiktoken_rs::model::get_context_size(model.id()),
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ZedDotDevModel::Custom(_) => 30720, // TODO: Base this on the selected model.
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},
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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::ZedDotDev(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: match self.role {
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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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} as i32,
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content: self.content.clone(),
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}
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}
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}
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#[derive(Debug, Default, Serialize)]
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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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}
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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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pub completion_tokens: u32,
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pub total_tokens: u32,
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}
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#[derive(Deserialize, Debug)]
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pub struct LanguageModelChoiceDelta {
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pub index: u32,
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pub delta: LanguageModelResponseMessage,
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pub finish_reason: Option<String>,
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}
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#[derive(Clone, Debug, Serialize, Deserialize)]
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struct MessageMetadata {
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role: Role,
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@ -53,71 +187,9 @@ enum MessageStatus {
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Error(SharedString),
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}
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#[derive(Serialize, Deserialize)]
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struct SavedMessage {
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id: MessageId,
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start: usize,
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}
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#[derive(Serialize, Deserialize)]
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struct SavedConversation {
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id: Option<String>,
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zed: String,
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version: String,
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text: String,
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messages: Vec<SavedMessage>,
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message_metadata: HashMap<MessageId, MessageMetadata>,
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summary: String,
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api_url: Option<String>,
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model: OpenAiModel,
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}
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impl SavedConversation {
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const VERSION: &'static str = "0.1.0";
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}
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struct SavedConversationMetadata {
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title: String,
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path: PathBuf,
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mtime: chrono::DateTime<chrono::Local>,
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}
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impl SavedConversationMetadata {
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pub async fn list(fs: Arc<dyn Fs>) -> Result<Vec<Self>> {
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fs.create_dir(&CONVERSATIONS_DIR).await?;
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let mut paths = fs.read_dir(&CONVERSATIONS_DIR).await?;
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let mut conversations = Vec::<SavedConversationMetadata>::new();
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while let Some(path) = paths.next().await {
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let path = path?;
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if path.extension() != Some(OsStr::new("json")) {
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continue;
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}
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let pattern = r" - \d+.zed.json$";
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let re = Regex::new(pattern).unwrap();
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let metadata = fs.metadata(&path).await?;
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if let Some((file_name, metadata)) = path
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.file_name()
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.and_then(|name| name.to_str())
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.zip(metadata)
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{
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let title = re.replace(file_name, "");
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conversations.push(Self {
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title: title.into_owned(),
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path,
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mtime: metadata.mtime.into(),
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});
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}
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}
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conversations.sort_unstable_by_key(|conversation| Reverse(conversation.mtime));
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Ok(conversations)
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}
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}
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pub fn init(cx: &mut AppContext) {
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pub fn init(client: Arc<Client>, cx: &mut AppContext) {
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AssistantSettings::register(cx);
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completion_provider::init(client, cx);
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assistant_panel::init(cx);
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}
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