c7e80c80c6
https://ai.google.dev/gemini-api/docs/text-generation#system-instructions Release Notes: - agent: Improve performance of Gemini models
782 lines
28 KiB
Rust
782 lines
28 KiB
Rust
use anyhow::{Context as _, Result, anyhow};
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use collections::BTreeMap;
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use credentials_provider::CredentialsProvider;
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use editor::{Editor, EditorElement, EditorStyle};
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use futures::{FutureExt, Stream, StreamExt, future::BoxFuture};
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use google_ai::{
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FunctionDeclaration, GenerateContentResponse, Part, SystemInstructions, UsageMetadata,
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};
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use gpui::{
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AnyView, App, AsyncApp, Context, Entity, FontStyle, Subscription, Task, TextStyle, WhiteSpace,
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};
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use http_client::HttpClient;
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use language_model::{
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AuthenticateError, LanguageModelCompletionEvent, LanguageModelToolSchemaFormat,
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LanguageModelToolUse, LanguageModelToolUseId, MessageContent, StopReason,
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};
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use language_model::{
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LanguageModel, LanguageModelId, LanguageModelName, LanguageModelProvider,
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LanguageModelProviderId, LanguageModelProviderName, LanguageModelProviderState,
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LanguageModelRequest, RateLimiter, Role,
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};
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use schemars::JsonSchema;
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use serde::{Deserialize, Serialize};
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use settings::{Settings, SettingsStore};
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use std::pin::Pin;
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use std::sync::Arc;
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use strum::IntoEnumIterator;
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use theme::ThemeSettings;
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use ui::{Icon, IconName, List, Tooltip, prelude::*};
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use util::ResultExt;
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use crate::AllLanguageModelSettings;
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use crate::ui::InstructionListItem;
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const PROVIDER_ID: &str = "google";
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const PROVIDER_NAME: &str = "Google AI";
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#[derive(Default, Clone, Debug, PartialEq)]
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pub struct GoogleSettings {
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pub api_url: String,
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pub available_models: Vec<AvailableModel>,
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}
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#[derive(Clone, Debug, PartialEq, Serialize, Deserialize, JsonSchema)]
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pub struct AvailableModel {
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name: String,
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display_name: Option<String>,
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max_tokens: usize,
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}
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pub struct GoogleLanguageModelProvider {
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http_client: Arc<dyn HttpClient>,
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state: gpui::Entity<State>,
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}
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pub struct State {
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api_key: Option<String>,
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api_key_from_env: bool,
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_subscription: Subscription,
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}
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const GOOGLE_AI_API_KEY_VAR: &str = "GOOGLE_AI_API_KEY";
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impl State {
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fn is_authenticated(&self) -> bool {
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self.api_key.is_some()
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}
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fn reset_api_key(&self, cx: &mut Context<Self>) -> Task<Result<()>> {
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let credentials_provider = <dyn CredentialsProvider>::global(cx);
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let api_url = AllLanguageModelSettings::get_global(cx)
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.google
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.api_url
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.clone();
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cx.spawn(async move |this, cx| {
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credentials_provider
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.delete_credentials(&api_url, &cx)
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.await
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.log_err();
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this.update(cx, |this, cx| {
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this.api_key = None;
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this.api_key_from_env = false;
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cx.notify();
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})
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})
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}
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fn set_api_key(&mut self, api_key: String, cx: &mut Context<Self>) -> Task<Result<()>> {
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let credentials_provider = <dyn CredentialsProvider>::global(cx);
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let api_url = AllLanguageModelSettings::get_global(cx)
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.google
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.api_url
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.clone();
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cx.spawn(async move |this, cx| {
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credentials_provider
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.write_credentials(&api_url, "Bearer", api_key.as_bytes(), &cx)
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.await?;
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this.update(cx, |this, cx| {
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this.api_key = Some(api_key);
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cx.notify();
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})
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})
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}
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fn authenticate(&self, cx: &mut Context<Self>) -> Task<Result<(), AuthenticateError>> {
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if self.is_authenticated() {
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return Task::ready(Ok(()));
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}
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let credentials_provider = <dyn CredentialsProvider>::global(cx);
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let api_url = AllLanguageModelSettings::get_global(cx)
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.google
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.api_url
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.clone();
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cx.spawn(async move |this, cx| {
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let (api_key, from_env) = if let Ok(api_key) = std::env::var(GOOGLE_AI_API_KEY_VAR) {
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(api_key, true)
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} else {
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let (_, api_key) = credentials_provider
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.read_credentials(&api_url, &cx)
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.await?
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.ok_or(AuthenticateError::CredentialsNotFound)?;
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(
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String::from_utf8(api_key).context("invalid {PROVIDER_NAME} API key")?,
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false,
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)
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};
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this.update(cx, |this, cx| {
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this.api_key = Some(api_key);
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this.api_key_from_env = from_env;
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cx.notify();
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})?;
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Ok(())
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})
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}
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}
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impl GoogleLanguageModelProvider {
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pub fn new(http_client: Arc<dyn HttpClient>, cx: &mut App) -> Self {
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let state = cx.new(|cx| State {
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api_key: None,
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api_key_from_env: false,
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_subscription: cx.observe_global::<SettingsStore>(|_, cx| {
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cx.notify();
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}),
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});
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Self { http_client, state }
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}
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}
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impl LanguageModelProviderState for GoogleLanguageModelProvider {
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type ObservableEntity = State;
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fn observable_entity(&self) -> Option<gpui::Entity<Self::ObservableEntity>> {
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Some(self.state.clone())
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}
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}
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impl LanguageModelProvider for GoogleLanguageModelProvider {
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fn id(&self) -> LanguageModelProviderId {
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LanguageModelProviderId(PROVIDER_ID.into())
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}
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fn name(&self) -> LanguageModelProviderName {
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LanguageModelProviderName(PROVIDER_NAME.into())
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}
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fn icon(&self) -> IconName {
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IconName::AiGoogle
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}
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fn default_model(&self, _cx: &App) -> Option<Arc<dyn LanguageModel>> {
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let model = google_ai::Model::default();
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Some(Arc::new(GoogleLanguageModel {
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id: LanguageModelId::from(model.id().to_string()),
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model,
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state: self.state.clone(),
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http_client: self.http_client.clone(),
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request_limiter: RateLimiter::new(4),
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}))
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}
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fn provided_models(&self, cx: &App) -> Vec<Arc<dyn LanguageModel>> {
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let mut models = BTreeMap::default();
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// Add base models from google_ai::Model::iter()
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for model in google_ai::Model::iter() {
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if !matches!(model, google_ai::Model::Custom { .. }) {
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models.insert(model.id().to_string(), model);
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}
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}
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// Override with available models from settings
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for model in &AllLanguageModelSettings::get_global(cx)
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.google
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.available_models
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{
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models.insert(
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model.name.clone(),
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google_ai::Model::Custom {
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name: model.name.clone(),
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display_name: model.display_name.clone(),
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max_tokens: model.max_tokens,
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},
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);
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}
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models
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.into_values()
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.map(|model| {
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Arc::new(GoogleLanguageModel {
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id: LanguageModelId::from(model.id().to_string()),
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model,
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state: self.state.clone(),
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http_client: self.http_client.clone(),
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request_limiter: RateLimiter::new(4),
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}) as Arc<dyn LanguageModel>
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})
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.collect()
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}
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fn is_authenticated(&self, cx: &App) -> bool {
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self.state.read(cx).is_authenticated()
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}
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fn authenticate(&self, cx: &mut App) -> Task<Result<(), AuthenticateError>> {
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self.state.update(cx, |state, cx| state.authenticate(cx))
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}
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fn configuration_view(&self, window: &mut Window, cx: &mut App) -> AnyView {
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cx.new(|cx| ConfigurationView::new(self.state.clone(), window, cx))
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.into()
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}
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fn reset_credentials(&self, cx: &mut App) -> Task<Result<()>> {
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self.state.update(cx, |state, cx| state.reset_api_key(cx))
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}
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}
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pub struct GoogleLanguageModel {
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id: LanguageModelId,
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model: google_ai::Model,
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state: gpui::Entity<State>,
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http_client: Arc<dyn HttpClient>,
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request_limiter: RateLimiter,
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}
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impl GoogleLanguageModel {
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fn stream_completion(
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&self,
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request: google_ai::GenerateContentRequest,
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cx: &AsyncApp,
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) -> BoxFuture<
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'static,
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Result<futures::stream::BoxStream<'static, Result<GenerateContentResponse>>>,
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> {
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let http_client = self.http_client.clone();
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let Ok((api_key, api_url)) = cx.read_entity(&self.state, |state, cx| {
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let settings = &AllLanguageModelSettings::get_global(cx).google;
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(state.api_key.clone(), settings.api_url.clone())
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}) else {
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return futures::future::ready(Err(anyhow!("App state dropped"))).boxed();
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};
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async move {
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let api_key = api_key.ok_or_else(|| anyhow!("Missing Google API key"))?;
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let request = google_ai::stream_generate_content(
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http_client.as_ref(),
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&api_url,
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&api_key,
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request,
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);
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request.await.context("failed to stream completion")
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}
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.boxed()
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}
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}
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impl LanguageModel for GoogleLanguageModel {
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fn id(&self) -> LanguageModelId {
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self.id.clone()
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}
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fn name(&self) -> LanguageModelName {
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LanguageModelName::from(self.model.display_name().to_string())
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}
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fn provider_id(&self) -> LanguageModelProviderId {
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LanguageModelProviderId(PROVIDER_ID.into())
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}
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fn provider_name(&self) -> LanguageModelProviderName {
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LanguageModelProviderName(PROVIDER_NAME.into())
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}
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fn supports_tools(&self) -> bool {
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true
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}
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fn tool_input_format(&self) -> LanguageModelToolSchemaFormat {
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LanguageModelToolSchemaFormat::JsonSchemaSubset
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}
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fn telemetry_id(&self) -> String {
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format!("google/{}", self.model.id())
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}
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fn max_token_count(&self) -> usize {
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self.model.max_token_count()
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}
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fn count_tokens(
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&self,
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request: LanguageModelRequest,
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cx: &App,
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) -> BoxFuture<'static, Result<usize>> {
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let request = into_google(request, self.model.id().to_string());
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let http_client = self.http_client.clone();
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let api_key = self.state.read(cx).api_key.clone();
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let settings = &AllLanguageModelSettings::get_global(cx).google;
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let api_url = settings.api_url.clone();
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async move {
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let api_key = api_key.ok_or_else(|| anyhow!("Missing Google API key"))?;
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let response = google_ai::count_tokens(
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http_client.as_ref(),
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&api_url,
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&api_key,
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google_ai::CountTokensRequest {
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contents: request.contents,
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},
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)
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.await?;
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Ok(response.total_tokens)
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}
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.boxed()
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}
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fn stream_completion(
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&self,
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request: LanguageModelRequest,
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cx: &AsyncApp,
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) -> BoxFuture<
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'static,
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Result<futures::stream::BoxStream<'static, Result<LanguageModelCompletionEvent>>>,
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> {
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let request = into_google(request, self.model.id().to_string());
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let request = self.stream_completion(request, cx);
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let future = self.request_limiter.stream(async move {
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let response = request.await.map_err(|err| anyhow!(err))?;
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Ok(map_to_language_model_completion_events(response))
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});
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async move { Ok(future.await?.boxed()) }.boxed()
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}
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}
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pub fn into_google(
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mut request: LanguageModelRequest,
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model: String,
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) -> google_ai::GenerateContentRequest {
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fn map_content(content: Vec<MessageContent>) -> Vec<Part> {
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content
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.into_iter()
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.filter_map(|content| match content {
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language_model::MessageContent::Text(text) => {
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if !text.is_empty() {
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Some(Part::TextPart(google_ai::TextPart { text }))
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} else {
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None
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}
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}
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language_model::MessageContent::Image(_) => None,
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language_model::MessageContent::ToolUse(tool_use) => {
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Some(Part::FunctionCallPart(google_ai::FunctionCallPart {
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function_call: google_ai::FunctionCall {
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name: tool_use.name.to_string(),
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args: tool_use.input,
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},
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}))
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}
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language_model::MessageContent::ToolResult(tool_result) => Some(
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Part::FunctionResponsePart(google_ai::FunctionResponsePart {
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function_response: google_ai::FunctionResponse {
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name: tool_result.tool_name.to_string(),
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// The API expects a valid JSON object
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response: serde_json::json!({
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"output": tool_result.content
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}),
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},
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}),
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),
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})
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.collect()
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}
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let system_instructions = if request
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.messages
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.first()
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.map_or(false, |msg| matches!(msg.role, Role::System))
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{
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let message = request.messages.remove(0);
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Some(SystemInstructions {
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parts: map_content(message.content),
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})
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} else {
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None
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};
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google_ai::GenerateContentRequest {
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model,
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system_instructions,
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contents: request
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.messages
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.into_iter()
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.map(|message| google_ai::Content {
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parts: map_content(message.content),
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role: match message.role {
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Role::User => google_ai::Role::User,
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Role::Assistant => google_ai::Role::Model,
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Role::System => google_ai::Role::User, // Google AI doesn't have a system role
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},
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})
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.collect(),
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generation_config: Some(google_ai::GenerationConfig {
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candidate_count: Some(1),
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stop_sequences: Some(request.stop),
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max_output_tokens: None,
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temperature: request.temperature.map(|t| t as f64).or(Some(1.0)),
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top_p: None,
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top_k: None,
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}),
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safety_settings: None,
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tools: (request.tools.len() > 0).then(|| {
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vec![google_ai::Tool {
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function_declarations: request
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.tools
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.into_iter()
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.map(|tool| FunctionDeclaration {
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name: tool.name,
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description: tool.description,
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parameters: tool.input_schema,
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})
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.collect(),
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}]
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}),
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tool_config: None,
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}
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}
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pub fn map_to_language_model_completion_events(
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events: Pin<Box<dyn Send + Stream<Item = Result<GenerateContentResponse>>>>,
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) -> impl Stream<Item = Result<LanguageModelCompletionEvent>> {
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use std::sync::atomic::{AtomicU64, Ordering};
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static TOOL_CALL_COUNTER: AtomicU64 = AtomicU64::new(0);
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|
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struct State {
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events: Pin<Box<dyn Send + Stream<Item = Result<GenerateContentResponse>>>>,
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usage: UsageMetadata,
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stop_reason: StopReason,
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}
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futures::stream::unfold(
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State {
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events,
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usage: UsageMetadata::default(),
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stop_reason: StopReason::EndTurn,
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},
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|mut state| async move {
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if let Some(event) = state.events.next().await {
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match event {
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Ok(event) => {
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let mut events: Vec<Result<LanguageModelCompletionEvent>> = Vec::new();
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let mut wants_to_use_tool = false;
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if let Some(usage_metadata) = event.usage_metadata {
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update_usage(&mut state.usage, &usage_metadata);
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events.push(Ok(LanguageModelCompletionEvent::UsageUpdate(
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convert_usage(&state.usage),
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)))
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}
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if let Some(candidates) = event.candidates {
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for candidate in candidates {
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if let Some(finish_reason) = candidate.finish_reason.as_deref() {
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state.stop_reason = match finish_reason {
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"STOP" => StopReason::EndTurn,
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"MAX_TOKENS" => StopReason::MaxTokens,
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_ => {
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log::error!(
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"Unexpected google finish_reason: {finish_reason}"
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);
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StopReason::EndTurn
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}
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};
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}
|
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candidate
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.content
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.parts
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.into_iter()
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.for_each(|part| match part {
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Part::TextPart(text_part) => events.push(Ok(
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LanguageModelCompletionEvent::Text(text_part.text),
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)),
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Part::InlineDataPart(_) => {}
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Part::FunctionCallPart(function_call_part) => {
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wants_to_use_tool = true;
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let name: Arc<str> =
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function_call_part.function_call.name.into();
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let next_tool_id =
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TOOL_CALL_COUNTER.fetch_add(1, Ordering::SeqCst);
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let id: LanguageModelToolUseId =
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format!("{}-{}", name, next_tool_id).into();
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|
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events.push(Ok(LanguageModelCompletionEvent::ToolUse(
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LanguageModelToolUse {
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id,
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name,
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input: function_call_part.function_call.args,
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},
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)));
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}
|
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Part::FunctionResponsePart(_) => {}
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});
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}
|
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}
|
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|
|
// Even when Gemini wants to use a Tool, the API
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|
// responds with `finish_reason: STOP`
|
|
if wants_to_use_tool {
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state.stop_reason = StopReason::ToolUse;
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}
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|
events.push(Ok(LanguageModelCompletionEvent::Stop(state.stop_reason)));
|
|
return Some((events, state));
|
|
}
|
|
Err(err) => {
|
|
return Some((vec![Err(anyhow!(err))], state));
|
|
}
|
|
}
|
|
}
|
|
|
|
None
|
|
},
|
|
)
|
|
.flat_map(futures::stream::iter)
|
|
}
|
|
|
|
pub fn count_google_tokens(
|
|
request: LanguageModelRequest,
|
|
cx: &App,
|
|
) -> BoxFuture<'static, Result<usize>> {
|
|
// We couldn't use the GoogleLanguageModelProvider to count tokens because the github copilot doesn't have the access to google_ai directly.
|
|
// So we have to use tokenizer from tiktoken_rs to count tokens.
|
|
cx.background_spawn(async move {
|
|
let messages = request
|
|
.messages
|
|
.into_iter()
|
|
.map(|message| tiktoken_rs::ChatCompletionRequestMessage {
|
|
role: match message.role {
|
|
Role::User => "user".into(),
|
|
Role::Assistant => "assistant".into(),
|
|
Role::System => "system".into(),
|
|
},
|
|
content: Some(message.string_contents()),
|
|
name: None,
|
|
function_call: None,
|
|
})
|
|
.collect::<Vec<_>>();
|
|
|
|
// Tiktoken doesn't yet support these models, so we manually use the
|
|
// same tokenizer as GPT-4.
|
|
tiktoken_rs::num_tokens_from_messages("gpt-4", &messages)
|
|
})
|
|
.boxed()
|
|
}
|
|
|
|
fn update_usage(usage: &mut UsageMetadata, new: &UsageMetadata) {
|
|
if let Some(prompt_token_count) = new.prompt_token_count {
|
|
usage.prompt_token_count = Some(prompt_token_count);
|
|
}
|
|
if let Some(cached_content_token_count) = new.cached_content_token_count {
|
|
usage.cached_content_token_count = Some(cached_content_token_count);
|
|
}
|
|
if let Some(candidates_token_count) = new.candidates_token_count {
|
|
usage.candidates_token_count = Some(candidates_token_count);
|
|
}
|
|
if let Some(tool_use_prompt_token_count) = new.tool_use_prompt_token_count {
|
|
usage.tool_use_prompt_token_count = Some(tool_use_prompt_token_count);
|
|
}
|
|
if let Some(thoughts_token_count) = new.thoughts_token_count {
|
|
usage.thoughts_token_count = Some(thoughts_token_count);
|
|
}
|
|
if let Some(total_token_count) = new.total_token_count {
|
|
usage.total_token_count = Some(total_token_count);
|
|
}
|
|
}
|
|
|
|
fn convert_usage(usage: &UsageMetadata) -> language_model::TokenUsage {
|
|
language_model::TokenUsage {
|
|
input_tokens: usage.prompt_token_count.unwrap_or(0) as u32,
|
|
output_tokens: usage.candidates_token_count.unwrap_or(0) as u32,
|
|
cache_read_input_tokens: usage.cached_content_token_count.unwrap_or(0) as u32,
|
|
cache_creation_input_tokens: 0,
|
|
}
|
|
}
|
|
|
|
struct ConfigurationView {
|
|
api_key_editor: Entity<Editor>,
|
|
state: gpui::Entity<State>,
|
|
load_credentials_task: Option<Task<()>>,
|
|
}
|
|
|
|
impl ConfigurationView {
|
|
fn new(state: gpui::Entity<State>, window: &mut Window, cx: &mut Context<Self>) -> Self {
|
|
cx.observe(&state, |_, _, cx| {
|
|
cx.notify();
|
|
})
|
|
.detach();
|
|
|
|
let load_credentials_task = Some(cx.spawn_in(window, {
|
|
let state = state.clone();
|
|
async move |this, cx| {
|
|
if let Some(task) = state
|
|
.update(cx, |state, cx| state.authenticate(cx))
|
|
.log_err()
|
|
{
|
|
// We don't log an error, because "not signed in" is also an error.
|
|
let _ = task.await;
|
|
}
|
|
this.update(cx, |this, cx| {
|
|
this.load_credentials_task = None;
|
|
cx.notify();
|
|
})
|
|
.log_err();
|
|
}
|
|
}));
|
|
|
|
Self {
|
|
api_key_editor: cx.new(|cx| {
|
|
let mut editor = Editor::single_line(window, cx);
|
|
editor.set_placeholder_text("AIzaSy...", cx);
|
|
editor
|
|
}),
|
|
state,
|
|
load_credentials_task,
|
|
}
|
|
}
|
|
|
|
fn save_api_key(&mut self, _: &menu::Confirm, window: &mut Window, cx: &mut Context<Self>) {
|
|
let api_key = self.api_key_editor.read(cx).text(cx);
|
|
if api_key.is_empty() {
|
|
return;
|
|
}
|
|
|
|
let state = self.state.clone();
|
|
cx.spawn_in(window, async move |_, cx| {
|
|
state
|
|
.update(cx, |state, cx| state.set_api_key(api_key, cx))?
|
|
.await
|
|
})
|
|
.detach_and_log_err(cx);
|
|
|
|
cx.notify();
|
|
}
|
|
|
|
fn reset_api_key(&mut self, window: &mut Window, cx: &mut Context<Self>) {
|
|
self.api_key_editor
|
|
.update(cx, |editor, cx| editor.set_text("", window, cx));
|
|
|
|
let state = self.state.clone();
|
|
cx.spawn_in(window, async move |_, cx| {
|
|
state.update(cx, |state, cx| state.reset_api_key(cx))?.await
|
|
})
|
|
.detach_and_log_err(cx);
|
|
|
|
cx.notify();
|
|
}
|
|
|
|
fn render_api_key_editor(&self, cx: &mut Context<Self>) -> impl IntoElement {
|
|
let settings = ThemeSettings::get_global(cx);
|
|
let text_style = TextStyle {
|
|
color: cx.theme().colors().text,
|
|
font_family: settings.ui_font.family.clone(),
|
|
font_features: settings.ui_font.features.clone(),
|
|
font_fallbacks: settings.ui_font.fallbacks.clone(),
|
|
font_size: rems(0.875).into(),
|
|
font_weight: settings.ui_font.weight,
|
|
font_style: FontStyle::Normal,
|
|
line_height: relative(1.3),
|
|
white_space: WhiteSpace::Normal,
|
|
..Default::default()
|
|
};
|
|
EditorElement::new(
|
|
&self.api_key_editor,
|
|
EditorStyle {
|
|
background: cx.theme().colors().editor_background,
|
|
local_player: cx.theme().players().local(),
|
|
text: text_style,
|
|
..Default::default()
|
|
},
|
|
)
|
|
}
|
|
|
|
fn should_render_editor(&self, cx: &mut Context<Self>) -> bool {
|
|
!self.state.read(cx).is_authenticated()
|
|
}
|
|
}
|
|
|
|
impl Render for ConfigurationView {
|
|
fn render(&mut self, _: &mut Window, cx: &mut Context<Self>) -> impl IntoElement {
|
|
let env_var_set = self.state.read(cx).api_key_from_env;
|
|
|
|
if self.load_credentials_task.is_some() {
|
|
div().child(Label::new("Loading credentials...")).into_any()
|
|
} else if self.should_render_editor(cx) {
|
|
v_flex()
|
|
.size_full()
|
|
.on_action(cx.listener(Self::save_api_key))
|
|
.child(Label::new("To use Zed's assistant with Google AI, you need to add an API key. Follow these steps:"))
|
|
.child(
|
|
List::new()
|
|
.child(InstructionListItem::new(
|
|
"Create one by visiting",
|
|
Some("Google AI's console"),
|
|
Some("https://aistudio.google.com/app/apikey"),
|
|
))
|
|
.child(InstructionListItem::text_only(
|
|
"Paste your API key below and hit enter to start using the assistant",
|
|
)),
|
|
)
|
|
.child(
|
|
h_flex()
|
|
.w_full()
|
|
.my_2()
|
|
.px_2()
|
|
.py_1()
|
|
.bg(cx.theme().colors().editor_background)
|
|
.border_1()
|
|
.border_color(cx.theme().colors().border_variant)
|
|
.rounded_sm()
|
|
.child(self.render_api_key_editor(cx)),
|
|
)
|
|
.child(
|
|
Label::new(
|
|
format!("You can also assign the {GOOGLE_AI_API_KEY_VAR} environment variable and restart Zed."),
|
|
)
|
|
.size(LabelSize::Small).color(Color::Muted),
|
|
)
|
|
.into_any()
|
|
} else {
|
|
h_flex()
|
|
.size_full()
|
|
.justify_between()
|
|
.child(
|
|
h_flex()
|
|
.gap_1()
|
|
.child(Icon::new(IconName::Check).color(Color::Success))
|
|
.child(Label::new(if env_var_set {
|
|
format!("API key set in {GOOGLE_AI_API_KEY_VAR} environment variable.")
|
|
} else {
|
|
"API key configured.".to_string()
|
|
})),
|
|
)
|
|
.child(
|
|
Button::new("reset-key", "Reset key")
|
|
.icon(Some(IconName::Trash))
|
|
.icon_size(IconSize::Small)
|
|
.icon_position(IconPosition::Start)
|
|
.disabled(env_var_set)
|
|
.when(env_var_set, |this| {
|
|
this.tooltip(Tooltip::text(format!("To reset your API key, unset the {GOOGLE_AI_API_KEY_VAR} environment variable.")))
|
|
})
|
|
.on_click(cx.listener(|this, _, window, cx| this.reset_api_key(window, cx))),
|
|
)
|
|
.into_any()
|
|
}
|
|
}
|
|
}
|