Add support for Vercel as a language model provider (#33292)
Vercel v0 is an OpenAI-compatible model, so this is mostly a dupe of the OpenAI provider files with some adaptations for v0, including going ahead and using the custom endpoint for the API URL field. Release Notes: - Added support for Vercel as a language model provider.
This commit is contained in:
Danilo Leal
GitHub
parent
0d70bcb88c
commit
94735aef69
12 changed files with 1394 additions and 0 deletions
867
crates/language_models/src/provider/vercel.rs
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867
crates/language_models/src/provider/vercel.rs
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@ -0,0 +1,867 @@
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use anyhow::{Context as _, Result, anyhow};
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use collections::{BTreeMap, HashMap};
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use credentials_provider::CredentialsProvider;
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use futures::Stream;
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use futures::{FutureExt, StreamExt, future::BoxFuture};
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use gpui::{AnyView, App, AsyncApp, Context, Entity, Subscription, Task, Window};
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use http_client::HttpClient;
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use language_model::{
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AuthenticateError, LanguageModel, LanguageModelCompletionError, LanguageModelCompletionEvent,
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LanguageModelId, LanguageModelName, LanguageModelProvider, LanguageModelProviderId,
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LanguageModelProviderName, LanguageModelProviderState, LanguageModelRequest,
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LanguageModelToolChoice, LanguageModelToolResultContent, LanguageModelToolUse, MessageContent,
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RateLimiter, Role, StopReason,
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};
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use menu;
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use open_ai::{ImageUrl, ResponseStreamEvent, stream_completion};
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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::str::FromStr as _;
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use std::sync::Arc;
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use strum::IntoEnumIterator;
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use vercel::Model;
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use ui::{ElevationIndex, List, Tooltip, prelude::*};
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use ui_input::SingleLineInput;
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use util::ResultExt;
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use crate::{AllLanguageModelSettings, ui::InstructionListItem};
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const PROVIDER_ID: &str = "vercel";
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const PROVIDER_NAME: &str = "Vercel";
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#[derive(Default, Clone, Debug, PartialEq)]
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pub struct VercelSettings {
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pub api_url: String,
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pub available_models: Vec<AvailableModel>,
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pub needs_setting_migration: bool,
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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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pub name: String,
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pub display_name: Option<String>,
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pub max_tokens: u64,
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pub max_output_tokens: Option<u64>,
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pub max_completion_tokens: Option<u64>,
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}
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pub struct VercelLanguageModelProvider {
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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 VERCEL_API_KEY_VAR: &str = "VERCEL_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 settings = &AllLanguageModelSettings::get_global(cx).vercel;
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let api_url = if settings.api_url.is_empty() {
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vercel::VERCEL_API_URL.to_string()
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} else {
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settings.api_url.clone()
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};
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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 settings = &AllLanguageModelSettings::get_global(cx).vercel;
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let api_url = if settings.api_url.is_empty() {
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vercel::VERCEL_API_URL.to_string()
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} else {
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settings.api_url.clone()
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};
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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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.log_err();
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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 settings = &AllLanguageModelSettings::get_global(cx).vercel;
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let api_url = if settings.api_url.is_empty() {
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vercel::VERCEL_API_URL.to_string()
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} else {
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settings.api_url.clone()
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};
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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(VERCEL_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 VercelLanguageModelProvider {
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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>(|_this: &mut State, 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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fn create_language_model(&self, model: vercel::Model) -> Arc<dyn LanguageModel> {
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Arc::new(VercelLanguageModel {
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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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}
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impl LanguageModelProviderState for VercelLanguageModelProvider {
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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 VercelLanguageModelProvider {
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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::AiVZero
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}
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fn default_model(&self, _cx: &App) -> Option<Arc<dyn LanguageModel>> {
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Some(self.create_language_model(vercel::Model::default()))
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}
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fn default_fast_model(&self, _cx: &App) -> Option<Arc<dyn LanguageModel>> {
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Some(self.create_language_model(vercel::Model::default_fast()))
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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 vercel::Model::iter()
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for model in vercel::Model::iter() {
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if !matches!(model, vercel::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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.vercel
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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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vercel::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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max_output_tokens: model.max_output_tokens,
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max_completion_tokens: model.max_completion_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| self.create_language_model(model))
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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 VercelLanguageModel {
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id: LanguageModelId,
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model: vercel::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 VercelLanguageModel {
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fn stream_completion(
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&self,
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request: open_ai::Request,
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cx: &AsyncApp,
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) -> BoxFuture<'static, Result<futures::stream::BoxStream<'static, Result<ResponseStreamEvent>>>>
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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).vercel;
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let api_url = if settings.api_url.is_empty() {
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vercel::VERCEL_API_URL.to_string()
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} else {
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settings.api_url.clone()
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};
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(state.api_key.clone(), api_url)
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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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let future = self.request_limiter.stream(async move {
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let api_key = api_key.context("Missing Vercel API Key")?;
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let request = stream_completion(http_client.as_ref(), &api_url, &api_key, request);
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let response = request.await?;
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Ok(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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impl LanguageModel for VercelLanguageModel {
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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 supports_images(&self) -> bool {
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false
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}
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fn supports_tool_choice(&self, choice: LanguageModelToolChoice) -> bool {
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match choice {
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LanguageModelToolChoice::Auto => true,
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LanguageModelToolChoice::Any => true,
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LanguageModelToolChoice::None => true,
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}
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}
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fn telemetry_id(&self) -> String {
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format!("vercel/{}", self.model.id())
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}
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fn max_token_count(&self) -> u64 {
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self.model.max_token_count()
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}
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fn max_output_tokens(&self) -> Option<u64> {
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self.model.max_output_tokens()
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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<u64>> {
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count_vercel_tokens(request, self.model.clone(), cx)
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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<
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futures::stream::BoxStream<
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'static,
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Result<LanguageModelCompletionEvent, LanguageModelCompletionError>,
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>,
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LanguageModelCompletionError,
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>,
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> {
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let request = into_vercel(request, &self.model, self.max_output_tokens());
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let completions = self.stream_completion(request, cx);
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async move {
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let mapper = VercelEventMapper::new();
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Ok(mapper.map_stream(completions.await?).boxed())
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}
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.boxed()
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}
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}
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pub fn into_vercel(
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request: LanguageModelRequest,
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model: &vercel::Model,
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max_output_tokens: Option<u64>,
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) -> open_ai::Request {
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let stream = !model.id().starts_with("o1-");
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let mut messages = Vec::new();
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for message in request.messages {
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for content in message.content {
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match content {
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MessageContent::Text(text) | MessageContent::Thinking { text, .. } => {
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add_message_content_part(
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open_ai::MessagePart::Text { text: text },
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message.role,
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&mut messages,
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)
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}
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MessageContent::RedactedThinking(_) => {}
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MessageContent::Image(image) => {
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add_message_content_part(
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open_ai::MessagePart::Image {
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image_url: ImageUrl {
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url: image.to_base64_url(),
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detail: None,
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},
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},
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message.role,
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&mut messages,
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);
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}
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MessageContent::ToolUse(tool_use) => {
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let tool_call = open_ai::ToolCall {
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id: tool_use.id.to_string(),
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content: open_ai::ToolCallContent::Function {
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function: open_ai::FunctionContent {
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name: tool_use.name.to_string(),
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arguments: serde_json::to_string(&tool_use.input)
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.unwrap_or_default(),
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},
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},
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};
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if let Some(open_ai::RequestMessage::Assistant { tool_calls, .. }) =
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messages.last_mut()
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{
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tool_calls.push(tool_call);
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} else {
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messages.push(open_ai::RequestMessage::Assistant {
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content: None,
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tool_calls: vec![tool_call],
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});
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}
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}
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MessageContent::ToolResult(tool_result) => {
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let content = match &tool_result.content {
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LanguageModelToolResultContent::Text(text) => {
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vec![open_ai::MessagePart::Text {
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text: text.to_string(),
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}]
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}
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LanguageModelToolResultContent::Image(image) => {
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vec![open_ai::MessagePart::Image {
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image_url: ImageUrl {
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url: image.to_base64_url(),
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detail: None,
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},
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}]
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}
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};
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messages.push(open_ai::RequestMessage::Tool {
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content: content.into(),
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tool_call_id: tool_result.tool_use_id.to_string(),
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});
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}
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}
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}
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}
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open_ai::Request {
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model: model.id().into(),
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messages,
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stream,
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stop: request.stop,
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temperature: request.temperature.unwrap_or(1.0),
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max_completion_tokens: max_output_tokens,
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parallel_tool_calls: if model.supports_parallel_tool_calls() && !request.tools.is_empty() {
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// Disable parallel tool calls, as the Agent currently expects a maximum of one per turn.
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Some(false)
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} else {
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None
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},
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tools: request
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.tools
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.into_iter()
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.map(|tool| open_ai::ToolDefinition::Function {
|
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function: open_ai::FunctionDefinition {
|
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name: tool.name,
|
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description: Some(tool.description),
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parameters: Some(tool.input_schema),
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},
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})
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.collect(),
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tool_choice: request.tool_choice.map(|choice| match choice {
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LanguageModelToolChoice::Auto => open_ai::ToolChoice::Auto,
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LanguageModelToolChoice::Any => open_ai::ToolChoice::Required,
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LanguageModelToolChoice::None => open_ai::ToolChoice::None,
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}),
|
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}
|
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}
|
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|
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fn add_message_content_part(
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new_part: open_ai::MessagePart,
|
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role: Role,
|
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messages: &mut Vec<open_ai::RequestMessage>,
|
||||
) {
|
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match (role, messages.last_mut()) {
|
||||
(Role::User, Some(open_ai::RequestMessage::User { content }))
|
||||
| (
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Role::Assistant,
|
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Some(open_ai::RequestMessage::Assistant {
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content: Some(content),
|
||||
..
|
||||
}),
|
||||
)
|
||||
| (Role::System, Some(open_ai::RequestMessage::System { content, .. })) => {
|
||||
content.push_part(new_part);
|
||||
}
|
||||
_ => {
|
||||
messages.push(match role {
|
||||
Role::User => open_ai::RequestMessage::User {
|
||||
content: open_ai::MessageContent::from(vec![new_part]),
|
||||
},
|
||||
Role::Assistant => open_ai::RequestMessage::Assistant {
|
||||
content: Some(open_ai::MessageContent::from(vec![new_part])),
|
||||
tool_calls: Vec::new(),
|
||||
},
|
||||
Role::System => open_ai::RequestMessage::System {
|
||||
content: open_ai::MessageContent::from(vec![new_part]),
|
||||
},
|
||||
});
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
pub struct VercelEventMapper {
|
||||
tool_calls_by_index: HashMap<usize, RawToolCall>,
|
||||
}
|
||||
|
||||
impl VercelEventMapper {
|
||||
pub fn new() -> Self {
|
||||
Self {
|
||||
tool_calls_by_index: HashMap::default(),
|
||||
}
|
||||
}
|
||||
|
||||
pub fn map_stream(
|
||||
mut self,
|
||||
events: Pin<Box<dyn Send + Stream<Item = Result<ResponseStreamEvent>>>>,
|
||||
) -> impl Stream<Item = Result<LanguageModelCompletionEvent, LanguageModelCompletionError>>
|
||||
{
|
||||
events.flat_map(move |event| {
|
||||
futures::stream::iter(match event {
|
||||
Ok(event) => self.map_event(event),
|
||||
Err(error) => vec![Err(LanguageModelCompletionError::Other(anyhow!(error)))],
|
||||
})
|
||||
})
|
||||
}
|
||||
|
||||
pub fn map_event(
|
||||
&mut self,
|
||||
event: ResponseStreamEvent,
|
||||
) -> Vec<Result<LanguageModelCompletionEvent, LanguageModelCompletionError>> {
|
||||
let Some(choice) = event.choices.first() else {
|
||||
return Vec::new();
|
||||
};
|
||||
|
||||
let mut events = Vec::new();
|
||||
if let Some(content) = choice.delta.content.clone() {
|
||||
events.push(Ok(LanguageModelCompletionEvent::Text(content)));
|
||||
}
|
||||
|
||||
if let Some(tool_calls) = choice.delta.tool_calls.as_ref() {
|
||||
for tool_call in tool_calls {
|
||||
let entry = self.tool_calls_by_index.entry(tool_call.index).or_default();
|
||||
|
||||
if let Some(tool_id) = tool_call.id.clone() {
|
||||
entry.id = tool_id;
|
||||
}
|
||||
|
||||
if let Some(function) = tool_call.function.as_ref() {
|
||||
if let Some(name) = function.name.clone() {
|
||||
entry.name = name;
|
||||
}
|
||||
|
||||
if let Some(arguments) = function.arguments.clone() {
|
||||
entry.arguments.push_str(&arguments);
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
match choice.finish_reason.as_deref() {
|
||||
Some("stop") => {
|
||||
events.push(Ok(LanguageModelCompletionEvent::Stop(StopReason::EndTurn)));
|
||||
}
|
||||
Some("tool_calls") => {
|
||||
events.extend(self.tool_calls_by_index.drain().map(|(_, tool_call)| {
|
||||
match serde_json::Value::from_str(&tool_call.arguments) {
|
||||
Ok(input) => Ok(LanguageModelCompletionEvent::ToolUse(
|
||||
LanguageModelToolUse {
|
||||
id: tool_call.id.clone().into(),
|
||||
name: tool_call.name.as_str().into(),
|
||||
is_input_complete: true,
|
||||
input,
|
||||
raw_input: tool_call.arguments.clone(),
|
||||
},
|
||||
)),
|
||||
Err(error) => Err(LanguageModelCompletionError::BadInputJson {
|
||||
id: tool_call.id.into(),
|
||||
tool_name: tool_call.name.as_str().into(),
|
||||
raw_input: tool_call.arguments.into(),
|
||||
json_parse_error: error.to_string(),
|
||||
}),
|
||||
}
|
||||
}));
|
||||
|
||||
events.push(Ok(LanguageModelCompletionEvent::Stop(StopReason::ToolUse)));
|
||||
}
|
||||
Some(stop_reason) => {
|
||||
log::error!("Unexpected Vercel stop_reason: {stop_reason:?}",);
|
||||
events.push(Ok(LanguageModelCompletionEvent::Stop(StopReason::EndTurn)));
|
||||
}
|
||||
None => {}
|
||||
}
|
||||
|
||||
events
|
||||
}
|
||||
}
|
||||
|
||||
#[derive(Default)]
|
||||
struct RawToolCall {
|
||||
id: String,
|
||||
name: String,
|
||||
arguments: String,
|
||||
}
|
||||
|
||||
pub fn count_vercel_tokens(
|
||||
request: LanguageModelRequest,
|
||||
model: Model,
|
||||
cx: &App,
|
||||
) -> BoxFuture<'static, Result<u64>> {
|
||||
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<_>>();
|
||||
|
||||
match model {
|
||||
Model::Custom { max_tokens, .. } => {
|
||||
let model = if max_tokens >= 100_000 {
|
||||
// If the max tokens is 100k or more, it is likely the o200k_base tokenizer from gpt4o
|
||||
"gpt-4o"
|
||||
} else {
|
||||
// Otherwise fallback to gpt-4, since only cl100k_base and o200k_base are
|
||||
// supported with this tiktoken method
|
||||
"gpt-4"
|
||||
};
|
||||
tiktoken_rs::num_tokens_from_messages(model, &messages)
|
||||
}
|
||||
// Map Vercel models to appropriate OpenAI models for token counting
|
||||
// since Vercel uses OpenAI-compatible API
|
||||
Model::VZero => {
|
||||
// Vercel v0 is similar to GPT-4o, so use gpt-4o for token counting
|
||||
tiktoken_rs::num_tokens_from_messages("gpt-4o", &messages)
|
||||
}
|
||||
}
|
||||
.map(|tokens| tokens as u64)
|
||||
})
|
||||
.boxed()
|
||||
}
|
||||
|
||||
struct ConfigurationView {
|
||||
api_key_editor: Entity<SingleLineInput>,
|
||||
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 {
|
||||
let api_key_editor = cx.new(|cx| {
|
||||
SingleLineInput::new(
|
||||
window,
|
||||
cx,
|
||||
"v1:0000000000000000000000000000000000000000000000000",
|
||||
)
|
||||
.label("API key")
|
||||
});
|
||||
|
||||
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,
|
||||
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)
|
||||
.editor()
|
||||
.read(cx)
|
||||
.text(cx)
|
||||
.trim()
|
||||
.to_string();
|
||||
|
||||
// Don't proceed if no API key is provided and we're not authenticated
|
||||
if api_key.is_empty() && !self.state.read(cx).is_authenticated() {
|
||||
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, |input, cx| {
|
||||
input.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 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;
|
||||
|
||||
let api_key_section = if self.should_render_editor(cx) {
|
||||
v_flex()
|
||||
.on_action(cx.listener(Self::save_api_key))
|
||||
.child(Label::new("To use Zed's agent with Vercel v0, you need to add an API key. Follow these steps:"))
|
||||
.child(
|
||||
List::new()
|
||||
.child(InstructionListItem::new(
|
||||
"Create one by visiting",
|
||||
Some("Vercel v0's console"),
|
||||
Some("https://v0.dev/chat/settings/keys"),
|
||||
))
|
||||
.child(InstructionListItem::text_only(
|
||||
"Paste your API key below and hit enter to start using the agent",
|
||||
)),
|
||||
)
|
||||
.child(self.api_key_editor.clone())
|
||||
.child(
|
||||
Label::new(format!(
|
||||
"You can also assign the {VERCEL_API_KEY_VAR} environment variable and restart Zed."
|
||||
))
|
||||
.size(LabelSize::Small)
|
||||
.color(Color::Muted),
|
||||
)
|
||||
.child(
|
||||
Label::new("Note that Vercel v0 is a custom OpenAI-compatible provider.")
|
||||
.size(LabelSize::Small)
|
||||
.color(Color::Muted),
|
||||
)
|
||||
.into_any()
|
||||
} else {
|
||||
h_flex()
|
||||
.mt_1()
|
||||
.p_1()
|
||||
.justify_between()
|
||||
.rounded_md()
|
||||
.border_1()
|
||||
.border_color(cx.theme().colors().border)
|
||||
.bg(cx.theme().colors().background)
|
||||
.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 {VERCEL_API_KEY_VAR} environment variable.")
|
||||
} else {
|
||||
"API key configured.".to_string()
|
||||
})),
|
||||
)
|
||||
.child(
|
||||
Button::new("reset-api-key", "Reset API Key")
|
||||
.label_size(LabelSize::Small)
|
||||
.icon(IconName::Undo)
|
||||
.icon_size(IconSize::Small)
|
||||
.icon_position(IconPosition::Start)
|
||||
.layer(ElevationIndex::ModalSurface)
|
||||
.when(env_var_set, |this| {
|
||||
this.tooltip(Tooltip::text(format!("To reset your API key, unset the {VERCEL_API_KEY_VAR} environment variable.")))
|
||||
})
|
||||
.on_click(cx.listener(|this, _, window, cx| this.reset_api_key(window, cx))),
|
||||
)
|
||||
.into_any()
|
||||
};
|
||||
|
||||
if self.load_credentials_task.is_some() {
|
||||
div().child(Label::new("Loading credentials…")).into_any()
|
||||
} else {
|
||||
v_flex().size_full().child(api_key_section).into_any()
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
#[cfg(test)]
|
||||
mod tests {
|
||||
use gpui::TestAppContext;
|
||||
use language_model::LanguageModelRequestMessage;
|
||||
|
||||
use super::*;
|
||||
|
||||
#[gpui::test]
|
||||
fn tiktoken_rs_support(cx: &TestAppContext) {
|
||||
let request = LanguageModelRequest {
|
||||
thread_id: None,
|
||||
prompt_id: None,
|
||||
intent: None,
|
||||
mode: None,
|
||||
messages: vec![LanguageModelRequestMessage {
|
||||
role: Role::User,
|
||||
content: vec![MessageContent::Text("message".into())],
|
||||
cache: false,
|
||||
}],
|
||||
tools: vec![],
|
||||
tool_choice: None,
|
||||
stop: vec![],
|
||||
temperature: None,
|
||||
};
|
||||
|
||||
// Validate that all models are supported by tiktoken-rs
|
||||
for model in Model::iter() {
|
||||
let count = cx
|
||||
.executor()
|
||||
.block(count_vercel_tokens(
|
||||
request.clone(),
|
||||
model,
|
||||
&cx.app.borrow(),
|
||||
))
|
||||
.unwrap();
|
||||
assert!(count > 0);
|
||||
}
|
||||
}
|
||||
}
|
||||
Loading…
Add table
Add a link
Reference in a new issue