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Add logic for closed beta LLM models (#16482)
Release Notes: - N/A --------- Co-authored-by: Marshall <marshall@zed.dev>
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@ -139,6 +139,11 @@ spec:
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secretKeyRef:
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name: anthropic
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key: staff_api_key
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- name: LLM_CLOSED_BETA_MODEL_NAME
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valueFrom:
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secretKeyRef:
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name: llm-closed-beta
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key: model_name
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- name: GOOGLE_AI_API_KEY
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valueFrom:
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secretKeyRef:
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@ -168,6 +168,7 @@ pub struct Config {
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pub google_ai_api_key: Option<Arc<str>>,
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pub anthropic_api_key: Option<Arc<str>>,
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pub anthropic_staff_api_key: Option<Arc<str>>,
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pub llm_closed_beta_model_name: Option<Arc<str>>,
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pub qwen2_7b_api_key: Option<Arc<str>>,
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pub qwen2_7b_api_url: Option<Arc<str>>,
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pub zed_client_checksum_seed: Option<String>,
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@ -219,6 +220,7 @@ impl Config {
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google_ai_api_key: None,
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anthropic_api_key: None,
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anthropic_staff_api_key: None,
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llm_closed_beta_model_name: None,
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clickhouse_url: None,
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clickhouse_user: None,
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clickhouse_password: None,
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@ -12,11 +12,12 @@ pub fn authorize_access_to_language_model(
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model: &str,
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) -> Result<()> {
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authorize_access_for_country(config, country_code, provider)?;
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authorize_access_to_model(claims, provider, model)?;
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authorize_access_to_model(config, claims, provider, model)?;
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Ok(())
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}
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fn authorize_access_to_model(
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config: &Config,
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claims: &LlmTokenClaims,
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provider: LanguageModelProvider,
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model: &str,
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@ -25,13 +26,25 @@ fn authorize_access_to_model(
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return Ok(());
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}
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match (provider, model) {
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(LanguageModelProvider::Anthropic, "claude-3-5-sonnet") => Ok(()),
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_ => Err(Error::http(
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StatusCode::FORBIDDEN,
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format!("access to model {model:?} is not included in your plan"),
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))?,
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match provider {
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LanguageModelProvider::Anthropic => {
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if model == "claude-3-5-sonnet" {
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return Ok(());
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}
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if claims.has_llm_closed_beta_feature_flag
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&& Some(model) == config.llm_closed_beta_model_name.as_deref()
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{
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return Ok(());
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}
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}
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_ => {}
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}
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Err(Error::http(
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StatusCode::FORBIDDEN,
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format!("access to model {model:?} is not included in your plan"),
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))
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}
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fn authorize_access_for_country(
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@ -82,12 +82,13 @@ impl LlmDatabase {
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let tokens_per_minute = self.usage_measure_ids[&UsageMeasure::TokensPerMinute];
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let mut results = Vec::new();
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for (provider, model) in self.models.keys().cloned() {
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for ((provider, model_name), model) in self.models.iter() {
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let mut usages = usage::Entity::find()
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.filter(
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usage::Column::Timestamp
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.gte(past_minute.naive_utc())
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.and(usage::Column::IsStaff.eq(false))
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.and(usage::Column::ModelId.eq(model.id))
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.and(
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usage::Column::MeasureId
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.eq(requests_per_minute)
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@ -125,8 +126,8 @@ impl LlmDatabase {
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}
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results.push(ApplicationWideUsage {
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provider,
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model,
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provider: *provider,
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model: model_name.clone(),
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requests_this_minute,
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tokens_this_minute,
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})
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@ -20,6 +20,8 @@ pub struct LlmTokenClaims {
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#[serde(default)]
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pub github_user_login: Option<String>,
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pub is_staff: bool,
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#[serde(default)]
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pub has_llm_closed_beta_feature_flag: bool,
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pub plan: rpc::proto::Plan,
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}
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@ -30,6 +32,7 @@ impl LlmTokenClaims {
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user_id: UserId,
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github_user_login: String,
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is_staff: bool,
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has_llm_closed_beta_feature_flag: bool,
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plan: rpc::proto::Plan,
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config: &Config,
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) -> Result<String> {
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@ -46,6 +49,7 @@ impl LlmTokenClaims {
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user_id: user_id.to_proto(),
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github_user_login: Some(github_user_login),
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is_staff,
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has_llm_closed_beta_feature_flag,
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plan,
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};
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@ -4918,7 +4918,10 @@ async fn get_llm_api_token(
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let db = session.db().await;
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let flags = db.get_user_flags(session.user_id()).await?;
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if !session.is_staff() && !flags.iter().any(|flag| flag == "language-models") {
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let has_language_models_feature_flag = flags.iter().any(|flag| flag == "language-models");
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let has_llm_closed_beta_feature_flag = flags.iter().any(|flag| flag == "llm-closed-beta");
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if !session.is_staff() && !has_language_models_feature_flag {
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Err(anyhow!("permission denied"))?
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}
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@ -4943,6 +4946,7 @@ async fn get_llm_api_token(
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user.id,
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user.github_login.clone(),
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session.is_staff(),
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has_llm_closed_beta_feature_flag,
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session.current_plan(db).await?,
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&session.app_state.config,
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)?;
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@ -667,6 +667,7 @@ impl TestServer {
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google_ai_api_key: None,
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anthropic_api_key: None,
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anthropic_staff_api_key: None,
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llm_closed_beta_model_name: None,
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clickhouse_url: None,
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clickhouse_user: None,
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clickhouse_password: None,
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@ -43,6 +43,11 @@ impl FeatureFlag for LanguageModels {
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const NAME: &'static str = "language-models";
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}
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pub struct LlmClosedBeta {}
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impl FeatureFlag for LlmClosedBeta {
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const NAME: &'static str = "llm-closed-beta";
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}
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pub struct ZedPro {}
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impl FeatureFlag for ZedPro {
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const NAME: &'static str = "zed-pro";
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@ -8,7 +8,7 @@ use anthropic::AnthropicError;
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use anyhow::{anyhow, Result};
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use client::{Client, PerformCompletionParams, UserStore, EXPIRED_LLM_TOKEN_HEADER_NAME};
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use collections::BTreeMap;
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use feature_flags::{FeatureFlagAppExt, ZedPro};
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use feature_flags::{FeatureFlagAppExt, LlmClosedBeta, ZedPro};
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use futures::{
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future::BoxFuture, stream::BoxStream, AsyncBufReadExt, FutureExt, Stream, StreamExt,
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TryStreamExt as _,
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@ -26,7 +26,10 @@ use smol::{
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io::{AsyncReadExt, BufReader},
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lock::{RwLock, RwLockUpgradableReadGuard, RwLockWriteGuard},
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};
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use std::{future, sync::Arc};
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use std::{
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future,
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sync::{Arc, LazyLock},
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};
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use strum::IntoEnumIterator;
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use ui::prelude::*;
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@ -37,6 +40,18 @@ use super::anthropic::count_anthropic_tokens;
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pub const PROVIDER_ID: &str = "zed.dev";
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pub const PROVIDER_NAME: &str = "Zed";
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const ZED_CLOUD_PROVIDER_ADDITIONAL_MODELS_JSON: Option<&str> =
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option_env!("ZED_CLOUD_PROVIDER_ADDITIONAL_MODELS_JSON");
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fn zed_cloud_provider_additional_models() -> &'static [AvailableModel] {
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static ADDITIONAL_MODELS: LazyLock<Vec<AvailableModel>> = LazyLock::new(|| {
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ZED_CLOUD_PROVIDER_ADDITIONAL_MODELS_JSON
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.map(|json| serde_json::from_str(json).unwrap())
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.unwrap_or(Vec::new())
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});
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ADDITIONAL_MODELS.as_slice()
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}
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#[derive(Default, Clone, Debug, PartialEq)]
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pub struct ZedDotDevSettings {
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pub available_models: Vec<AvailableModel>,
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@ -200,40 +215,6 @@ impl LanguageModelProvider for CloudLanguageModelProvider {
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for model in ZedModel::iter() {
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models.insert(model.id().to_string(), CloudModel::Zed(model));
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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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.zed_dot_dev
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.available_models
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{
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let model = match model.provider {
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AvailableProvider::Anthropic => {
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CloudModel::Anthropic(anthropic::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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tool_override: model.tool_override.clone(),
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cache_configuration: model.cache_configuration.as_ref().map(|config| {
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anthropic::AnthropicModelCacheConfiguration {
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max_cache_anchors: config.max_cache_anchors,
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should_speculate: config.should_speculate,
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min_total_token: config.min_total_token,
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}
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}),
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max_output_tokens: model.max_output_tokens,
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})
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}
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AvailableProvider::OpenAi => CloudModel::OpenAi(open_ai::Model::Custom {
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name: model.name.clone(),
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max_tokens: model.max_tokens,
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}),
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AvailableProvider::Google => CloudModel::Google(google_ai::Model::Custom {
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name: model.name.clone(),
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max_tokens: model.max_tokens,
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}),
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};
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models.insert(model.id().to_string(), model.clone());
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}
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} else {
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models.insert(
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anthropic::Model::Claude3_5Sonnet.id().to_string(),
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@ -241,6 +222,47 @@ impl LanguageModelProvider for CloudLanguageModelProvider {
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);
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}
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let llm_closed_beta_models = if cx.has_flag::<LlmClosedBeta>() {
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zed_cloud_provider_additional_models()
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} else {
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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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.zed_dot_dev
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.available_models
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.iter()
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.chain(llm_closed_beta_models)
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.cloned()
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{
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let model = match model.provider {
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AvailableProvider::Anthropic => CloudModel::Anthropic(anthropic::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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tool_override: model.tool_override.clone(),
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cache_configuration: model.cache_configuration.as_ref().map(|config| {
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anthropic::AnthropicModelCacheConfiguration {
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max_cache_anchors: config.max_cache_anchors,
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should_speculate: config.should_speculate,
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min_total_token: config.min_total_token,
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}
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}),
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max_output_tokens: model.max_output_tokens,
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}),
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AvailableProvider::OpenAi => CloudModel::OpenAi(open_ai::Model::Custom {
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name: model.name.clone(),
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max_tokens: model.max_tokens,
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}),
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AvailableProvider::Google => CloudModel::Google(google_ai::Model::Custom {
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name: model.name.clone(),
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max_tokens: model.max_tokens,
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}),
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};
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models.insert(model.id().to_string(), model.clone());
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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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