Add xAI language model provider (#33593)
Closes #30010 Release Notes: - Add support for xAI language model provider
This commit is contained in:
parent
af0031ae8b
commit
ec52e9281a
14 changed files with 840 additions and 28 deletions
12
Cargo.lock
generated
12
Cargo.lock
generated
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@ -9094,6 +9094,7 @@ dependencies = [
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"util",
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"util",
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"vercel",
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"vercel",
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"workspace-hack",
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"workspace-hack",
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"x_ai",
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"zed_llm_client",
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"zed_llm_client",
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]
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]
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@ -19840,6 +19841,17 @@ version = "0.13.1"
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source = "registry+https://github.com/rust-lang/crates.io-index"
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source = "registry+https://github.com/rust-lang/crates.io-index"
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checksum = "ec107c4503ea0b4a98ef47356329af139c0a4f7750e621cf2973cd3385ebcb3d"
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checksum = "ec107c4503ea0b4a98ef47356329af139c0a4f7750e621cf2973cd3385ebcb3d"
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[[package]]
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name = "x_ai"
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version = "0.1.0"
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dependencies = [
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"anyhow",
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"schemars",
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"serde",
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"strum 0.27.1",
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"workspace-hack",
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]
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[[package]]
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[[package]]
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name = "xattr"
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name = "xattr"
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version = "0.2.3"
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version = "0.2.3"
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@ -179,6 +179,7 @@ members = [
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"crates/welcome",
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"crates/welcome",
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"crates/workspace",
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"crates/workspace",
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"crates/worktree",
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"crates/worktree",
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"crates/x_ai",
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"crates/zed",
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"crates/zed",
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"crates/zed_actions",
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"crates/zed_actions",
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"crates/zeta",
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"crates/zeta",
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@ -394,6 +395,7 @@ web_search_providers = { path = "crates/web_search_providers" }
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welcome = { path = "crates/welcome" }
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welcome = { path = "crates/welcome" }
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workspace = { path = "crates/workspace" }
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workspace = { path = "crates/workspace" }
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worktree = { path = "crates/worktree" }
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worktree = { path = "crates/worktree" }
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x_ai = { path = "crates/x_ai" }
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zed = { path = "crates/zed" }
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zed = { path = "crates/zed" }
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zed_actions = { path = "crates/zed_actions" }
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zed_actions = { path = "crates/zed_actions" }
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zeta = { path = "crates/zeta" }
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zeta = { path = "crates/zeta" }
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3
assets/icons/ai_x_ai.svg
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3
assets/icons/ai_x_ai.svg
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@ -0,0 +1,3 @@
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<svg width="16" height="16" viewBox="0 0 16 16" fill="none" xmlns="http://www.w3.org/2000/svg">
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<path d="m12.414 5.47.27 9.641h2.157l.27-13.15zM15.11.889h-3.293L6.651 7.613l1.647 2.142zM.889 15.11H4.18l1.647-2.142-1.647-2.143zm0-9.641 7.409 9.641h3.292L4.181 5.47z" fill="#000"/>
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</svg>
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After Width: | Height: | Size: 289 B |
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@ -21,6 +21,7 @@ pub enum IconName {
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AiOpenAi,
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AiOpenAi,
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AiOpenRouter,
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AiOpenRouter,
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AiVZero,
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AiVZero,
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AiXAi,
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AiZed,
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AiZed,
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ArrowCircle,
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ArrowCircle,
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ArrowDown,
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ArrowDown,
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@ -43,6 +43,7 @@ ollama = { workspace = true, features = ["schemars"] }
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open_ai = { workspace = true, features = ["schemars"] }
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open_ai = { workspace = true, features = ["schemars"] }
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open_router = { workspace = true, features = ["schemars"] }
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open_router = { workspace = true, features = ["schemars"] }
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vercel = { workspace = true, features = ["schemars"] }
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vercel = { workspace = true, features = ["schemars"] }
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x_ai = { workspace = true, features = ["schemars"] }
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partial-json-fixer.workspace = true
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partial-json-fixer.workspace = true
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proto.workspace = true
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proto.workspace = true
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release_channel.workspace = true
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release_channel.workspace = true
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@ -20,6 +20,7 @@ use crate::provider::ollama::OllamaLanguageModelProvider;
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use crate::provider::open_ai::OpenAiLanguageModelProvider;
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use crate::provider::open_ai::OpenAiLanguageModelProvider;
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use crate::provider::open_router::OpenRouterLanguageModelProvider;
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use crate::provider::open_router::OpenRouterLanguageModelProvider;
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use crate::provider::vercel::VercelLanguageModelProvider;
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use crate::provider::vercel::VercelLanguageModelProvider;
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use crate::provider::x_ai::XAiLanguageModelProvider;
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pub use crate::settings::*;
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pub use crate::settings::*;
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pub fn init(user_store: Entity<UserStore>, client: Arc<Client>, cx: &mut App) {
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pub fn init(user_store: Entity<UserStore>, client: Arc<Client>, cx: &mut App) {
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@ -81,5 +82,6 @@ fn register_language_model_providers(
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VercelLanguageModelProvider::new(client.http_client(), cx),
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VercelLanguageModelProvider::new(client.http_client(), cx),
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cx,
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cx,
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);
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);
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registry.register_provider(XAiLanguageModelProvider::new(client.http_client(), cx), cx);
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registry.register_provider(CopilotChatLanguageModelProvider::new(cx), cx);
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registry.register_provider(CopilotChatLanguageModelProvider::new(cx), cx);
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}
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}
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@ -10,3 +10,4 @@ pub mod ollama;
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pub mod open_ai;
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pub mod open_ai;
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pub mod open_router;
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pub mod open_router;
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pub mod vercel;
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pub mod vercel;
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pub mod x_ai;
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@ -376,7 +376,7 @@ impl LanguageModel for OpenRouterLanguageModel {
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fn tool_input_format(&self) -> LanguageModelToolSchemaFormat {
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fn tool_input_format(&self) -> LanguageModelToolSchemaFormat {
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let model_id = self.model.id().trim().to_lowercase();
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let model_id = self.model.id().trim().to_lowercase();
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if model_id.contains("gemini") {
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if model_id.contains("gemini") || model_id.contains("grok-4") {
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LanguageModelToolSchemaFormat::JsonSchemaSubset
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LanguageModelToolSchemaFormat::JsonSchemaSubset
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} else {
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} else {
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LanguageModelToolSchemaFormat::JsonSchema
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LanguageModelToolSchemaFormat::JsonSchema
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571
crates/language_models/src/provider/x_ai.rs
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571
crates/language_models/src/provider/x_ai.rs
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@ -0,0 +1,571 @@
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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 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, LanguageModelToolSchemaFormat, RateLimiter, Role,
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};
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use menu;
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use open_ai::ResponseStreamEvent;
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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::sync::Arc;
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use strum::IntoEnumIterator;
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use x_ai::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 = "x_ai";
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const PROVIDER_NAME: &str = "xAI";
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#[derive(Default, Clone, Debug, PartialEq)]
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pub struct XAiSettings {
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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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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 XAiLanguageModelProvider {
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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 XAI_API_KEY_VAR: &str = "XAI_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).x_ai;
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let api_url = if settings.api_url.is_empty() {
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x_ai::XAI_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).x_ai;
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let api_url = if settings.api_url.is_empty() {
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x_ai::XAI_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).x_ai;
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let api_url = if settings.api_url.is_empty() {
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x_ai::XAI_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(XAI_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 XAiLanguageModelProvider {
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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: x_ai::Model) -> Arc<dyn LanguageModel> {
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Arc::new(XAiLanguageModel {
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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 XAiLanguageModelProvider {
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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 XAiLanguageModelProvider {
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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::AiXAi
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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(x_ai::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(x_ai::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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for model in x_ai::Model::iter() {
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if !matches!(model, x_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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for model in &AllLanguageModelSettings::get_global(cx)
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.x_ai
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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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x_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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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 XAiLanguageModel {
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id: LanguageModelId,
|
||||||
|
model: x_ai::Model,
|
||||||
|
state: gpui::Entity<State>,
|
||||||
|
http_client: Arc<dyn HttpClient>,
|
||||||
|
request_limiter: RateLimiter,
|
||||||
|
}
|
||||||
|
|
||||||
|
impl XAiLanguageModel {
|
||||||
|
fn stream_completion(
|
||||||
|
&self,
|
||||||
|
request: open_ai::Request,
|
||||||
|
cx: &AsyncApp,
|
||||||
|
) -> BoxFuture<'static, Result<futures::stream::BoxStream<'static, Result<ResponseStreamEvent>>>>
|
||||||
|
{
|
||||||
|
let http_client = self.http_client.clone();
|
||||||
|
let Ok((api_key, api_url)) = cx.read_entity(&self.state, |state, cx| {
|
||||||
|
let settings = &AllLanguageModelSettings::get_global(cx).x_ai;
|
||||||
|
let api_url = if settings.api_url.is_empty() {
|
||||||
|
x_ai::XAI_API_URL.to_string()
|
||||||
|
} else {
|
||||||
|
settings.api_url.clone()
|
||||||
|
};
|
||||||
|
(state.api_key.clone(), api_url)
|
||||||
|
}) else {
|
||||||
|
return futures::future::ready(Err(anyhow!("App state dropped"))).boxed();
|
||||||
|
};
|
||||||
|
|
||||||
|
let future = self.request_limiter.stream(async move {
|
||||||
|
let api_key = api_key.context("Missing xAI API Key")?;
|
||||||
|
let request =
|
||||||
|
open_ai::stream_completion(http_client.as_ref(), &api_url, &api_key, request);
|
||||||
|
let response = request.await?;
|
||||||
|
Ok(response)
|
||||||
|
});
|
||||||
|
|
||||||
|
async move { Ok(future.await?.boxed()) }.boxed()
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
impl LanguageModel for XAiLanguageModel {
|
||||||
|
fn id(&self) -> LanguageModelId {
|
||||||
|
self.id.clone()
|
||||||
|
}
|
||||||
|
|
||||||
|
fn name(&self) -> LanguageModelName {
|
||||||
|
LanguageModelName::from(self.model.display_name().to_string())
|
||||||
|
}
|
||||||
|
|
||||||
|
fn provider_id(&self) -> LanguageModelProviderId {
|
||||||
|
LanguageModelProviderId(PROVIDER_ID.into())
|
||||||
|
}
|
||||||
|
|
||||||
|
fn provider_name(&self) -> LanguageModelProviderName {
|
||||||
|
LanguageModelProviderName(PROVIDER_NAME.into())
|
||||||
|
}
|
||||||
|
|
||||||
|
fn supports_tools(&self) -> bool {
|
||||||
|
self.model.supports_tool()
|
||||||
|
}
|
||||||
|
|
||||||
|
fn supports_images(&self) -> bool {
|
||||||
|
self.model.supports_images()
|
||||||
|
}
|
||||||
|
|
||||||
|
fn supports_tool_choice(&self, choice: LanguageModelToolChoice) -> bool {
|
||||||
|
match choice {
|
||||||
|
LanguageModelToolChoice::Auto
|
||||||
|
| LanguageModelToolChoice::Any
|
||||||
|
| LanguageModelToolChoice::None => true,
|
||||||
|
}
|
||||||
|
}
|
||||||
|
fn tool_input_format(&self) -> LanguageModelToolSchemaFormat {
|
||||||
|
let model_id = self.model.id().trim().to_lowercase();
|
||||||
|
if model_id.eq(x_ai::Model::Grok4.id()) {
|
||||||
|
LanguageModelToolSchemaFormat::JsonSchemaSubset
|
||||||
|
} else {
|
||||||
|
LanguageModelToolSchemaFormat::JsonSchema
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
fn telemetry_id(&self) -> String {
|
||||||
|
format!("x_ai/{}", self.model.id())
|
||||||
|
}
|
||||||
|
|
||||||
|
fn max_token_count(&self) -> u64 {
|
||||||
|
self.model.max_token_count()
|
||||||
|
}
|
||||||
|
|
||||||
|
fn max_output_tokens(&self) -> Option<u64> {
|
||||||
|
self.model.max_output_tokens()
|
||||||
|
}
|
||||||
|
|
||||||
|
fn count_tokens(
|
||||||
|
&self,
|
||||||
|
request: LanguageModelRequest,
|
||||||
|
cx: &App,
|
||||||
|
) -> BoxFuture<'static, Result<u64>> {
|
||||||
|
count_xai_tokens(request, self.model.clone(), cx)
|
||||||
|
}
|
||||||
|
|
||||||
|
fn stream_completion(
|
||||||
|
&self,
|
||||||
|
request: LanguageModelRequest,
|
||||||
|
cx: &AsyncApp,
|
||||||
|
) -> BoxFuture<
|
||||||
|
'static,
|
||||||
|
Result<
|
||||||
|
futures::stream::BoxStream<
|
||||||
|
'static,
|
||||||
|
Result<LanguageModelCompletionEvent, LanguageModelCompletionError>,
|
||||||
|
>,
|
||||||
|
LanguageModelCompletionError,
|
||||||
|
>,
|
||||||
|
> {
|
||||||
|
let request = crate::provider::open_ai::into_open_ai(
|
||||||
|
request,
|
||||||
|
self.model.id(),
|
||||||
|
self.model.supports_parallel_tool_calls(),
|
||||||
|
self.max_output_tokens(),
|
||||||
|
);
|
||||||
|
let completions = self.stream_completion(request, cx);
|
||||||
|
async move {
|
||||||
|
let mapper = crate::provider::open_ai::OpenAiEventMapper::new();
|
||||||
|
Ok(mapper.map_stream(completions.await?).boxed())
|
||||||
|
}
|
||||||
|
.boxed()
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
pub fn count_xai_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<_>>();
|
||||||
|
|
||||||
|
let model_name = if model.max_token_count() >= 100_000 {
|
||||||
|
"gpt-4o"
|
||||||
|
} else {
|
||||||
|
"gpt-4"
|
||||||
|
};
|
||||||
|
tiktoken_rs::num_tokens_from_messages(model_name, &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,
|
||||||
|
"xai-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 xAI, you need to add an API key. Follow these steps:"))
|
||||||
|
.child(
|
||||||
|
List::new()
|
||||||
|
.child(InstructionListItem::new(
|
||||||
|
"Create one by visiting",
|
||||||
|
Some("xAI console"),
|
||||||
|
Some("https://console.x.ai/team/default/api-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 {XAI_API_KEY_VAR} environment variable and restart Zed."
|
||||||
|
))
|
||||||
|
.size(LabelSize::Small)
|
||||||
|
.color(Color::Muted),
|
||||||
|
)
|
||||||
|
.child(
|
||||||
|
Label::new("Note that xAI 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 {XAI_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 {XAI_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()
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
|
@ -17,6 +17,7 @@ use crate::provider::{
|
||||||
open_ai::OpenAiSettings,
|
open_ai::OpenAiSettings,
|
||||||
open_router::OpenRouterSettings,
|
open_router::OpenRouterSettings,
|
||||||
vercel::VercelSettings,
|
vercel::VercelSettings,
|
||||||
|
x_ai::XAiSettings,
|
||||||
};
|
};
|
||||||
|
|
||||||
/// Initializes the language model settings.
|
/// Initializes the language model settings.
|
||||||
|
@ -28,33 +29,33 @@ pub fn init(cx: &mut App) {
|
||||||
pub struct AllLanguageModelSettings {
|
pub struct AllLanguageModelSettings {
|
||||||
pub anthropic: AnthropicSettings,
|
pub anthropic: AnthropicSettings,
|
||||||
pub bedrock: AmazonBedrockSettings,
|
pub bedrock: AmazonBedrockSettings,
|
||||||
pub ollama: OllamaSettings,
|
|
||||||
pub openai: OpenAiSettings,
|
|
||||||
pub open_router: OpenRouterSettings,
|
|
||||||
pub zed_dot_dev: ZedDotDevSettings,
|
|
||||||
pub google: GoogleSettings,
|
|
||||||
pub vercel: VercelSettings,
|
|
||||||
|
|
||||||
pub lmstudio: LmStudioSettings,
|
|
||||||
pub deepseek: DeepSeekSettings,
|
pub deepseek: DeepSeekSettings,
|
||||||
|
pub google: GoogleSettings,
|
||||||
|
pub lmstudio: LmStudioSettings,
|
||||||
pub mistral: MistralSettings,
|
pub mistral: MistralSettings,
|
||||||
|
pub ollama: OllamaSettings,
|
||||||
|
pub open_router: OpenRouterSettings,
|
||||||
|
pub openai: OpenAiSettings,
|
||||||
|
pub vercel: VercelSettings,
|
||||||
|
pub x_ai: XAiSettings,
|
||||||
|
pub zed_dot_dev: ZedDotDevSettings,
|
||||||
}
|
}
|
||||||
|
|
||||||
#[derive(Default, Clone, Debug, Serialize, Deserialize, PartialEq, JsonSchema)]
|
#[derive(Default, Clone, Debug, Serialize, Deserialize, PartialEq, JsonSchema)]
|
||||||
pub struct AllLanguageModelSettingsContent {
|
pub struct AllLanguageModelSettingsContent {
|
||||||
pub anthropic: Option<AnthropicSettingsContent>,
|
pub anthropic: Option<AnthropicSettingsContent>,
|
||||||
pub bedrock: Option<AmazonBedrockSettingsContent>,
|
pub bedrock: Option<AmazonBedrockSettingsContent>,
|
||||||
pub ollama: Option<OllamaSettingsContent>,
|
pub deepseek: Option<DeepseekSettingsContent>,
|
||||||
|
pub google: Option<GoogleSettingsContent>,
|
||||||
pub lmstudio: Option<LmStudioSettingsContent>,
|
pub lmstudio: Option<LmStudioSettingsContent>,
|
||||||
pub openai: Option<OpenAiSettingsContent>,
|
pub mistral: Option<MistralSettingsContent>,
|
||||||
|
pub ollama: Option<OllamaSettingsContent>,
|
||||||
pub open_router: Option<OpenRouterSettingsContent>,
|
pub open_router: Option<OpenRouterSettingsContent>,
|
||||||
|
pub openai: Option<OpenAiSettingsContent>,
|
||||||
|
pub vercel: Option<VercelSettingsContent>,
|
||||||
|
pub x_ai: Option<XAiSettingsContent>,
|
||||||
#[serde(rename = "zed.dev")]
|
#[serde(rename = "zed.dev")]
|
||||||
pub zed_dot_dev: Option<ZedDotDevSettingsContent>,
|
pub zed_dot_dev: Option<ZedDotDevSettingsContent>,
|
||||||
pub google: Option<GoogleSettingsContent>,
|
|
||||||
pub deepseek: Option<DeepseekSettingsContent>,
|
|
||||||
pub vercel: Option<VercelSettingsContent>,
|
|
||||||
|
|
||||||
pub mistral: Option<MistralSettingsContent>,
|
|
||||||
}
|
}
|
||||||
|
|
||||||
#[derive(Clone, Debug, Serialize, Deserialize, PartialEq, JsonSchema)]
|
#[derive(Clone, Debug, Serialize, Deserialize, PartialEq, JsonSchema)]
|
||||||
|
@ -114,6 +115,12 @@ pub struct GoogleSettingsContent {
|
||||||
pub available_models: Option<Vec<provider::google::AvailableModel>>,
|
pub available_models: Option<Vec<provider::google::AvailableModel>>,
|
||||||
}
|
}
|
||||||
|
|
||||||
|
#[derive(Default, Clone, Debug, Serialize, Deserialize, PartialEq, JsonSchema)]
|
||||||
|
pub struct XAiSettingsContent {
|
||||||
|
pub api_url: Option<String>,
|
||||||
|
pub available_models: Option<Vec<provider::x_ai::AvailableModel>>,
|
||||||
|
}
|
||||||
|
|
||||||
#[derive(Default, Clone, Debug, Serialize, Deserialize, PartialEq, JsonSchema)]
|
#[derive(Default, Clone, Debug, Serialize, Deserialize, PartialEq, JsonSchema)]
|
||||||
pub struct ZedDotDevSettingsContent {
|
pub struct ZedDotDevSettingsContent {
|
||||||
available_models: Option<Vec<cloud::AvailableModel>>,
|
available_models: Option<Vec<cloud::AvailableModel>>,
|
||||||
|
@ -230,6 +237,18 @@ impl settings::Settings for AllLanguageModelSettings {
|
||||||
vercel.as_ref().and_then(|s| s.available_models.clone()),
|
vercel.as_ref().and_then(|s| s.available_models.clone()),
|
||||||
);
|
);
|
||||||
|
|
||||||
|
// XAI
|
||||||
|
let x_ai = value.x_ai.clone();
|
||||||
|
merge(
|
||||||
|
&mut settings.x_ai.api_url,
|
||||||
|
x_ai.as_ref().and_then(|s| s.api_url.clone()),
|
||||||
|
);
|
||||||
|
merge(
|
||||||
|
&mut settings.x_ai.available_models,
|
||||||
|
x_ai.as_ref().and_then(|s| s.available_models.clone()),
|
||||||
|
);
|
||||||
|
|
||||||
|
// ZedDotDev
|
||||||
merge(
|
merge(
|
||||||
&mut settings.zed_dot_dev.available_models,
|
&mut settings.zed_dot_dev.available_models,
|
||||||
value
|
value
|
||||||
|
|
23
crates/x_ai/Cargo.toml
Normal file
23
crates/x_ai/Cargo.toml
Normal file
|
@ -0,0 +1,23 @@
|
||||||
|
[package]
|
||||||
|
name = "x_ai"
|
||||||
|
version = "0.1.0"
|
||||||
|
edition.workspace = true
|
||||||
|
publish.workspace = true
|
||||||
|
license = "GPL-3.0-or-later"
|
||||||
|
|
||||||
|
[lints]
|
||||||
|
workspace = true
|
||||||
|
|
||||||
|
[lib]
|
||||||
|
path = "src/x_ai.rs"
|
||||||
|
|
||||||
|
[features]
|
||||||
|
default = []
|
||||||
|
schemars = ["dep:schemars"]
|
||||||
|
|
||||||
|
[dependencies]
|
||||||
|
anyhow.workspace = true
|
||||||
|
schemars = { workspace = true, optional = true }
|
||||||
|
serde.workspace = true
|
||||||
|
strum.workspace = true
|
||||||
|
workspace-hack.workspace = true
|
1
crates/x_ai/LICENSE-GPL
Symbolic link
1
crates/x_ai/LICENSE-GPL
Symbolic link
|
@ -0,0 +1 @@
|
||||||
|
../../LICENSE-GPL
|
126
crates/x_ai/src/x_ai.rs
Normal file
126
crates/x_ai/src/x_ai.rs
Normal file
|
@ -0,0 +1,126 @@
|
||||||
|
use anyhow::Result;
|
||||||
|
use serde::{Deserialize, Serialize};
|
||||||
|
use strum::EnumIter;
|
||||||
|
|
||||||
|
pub const XAI_API_URL: &str = "https://api.x.ai/v1";
|
||||||
|
|
||||||
|
#[cfg_attr(feature = "schemars", derive(schemars::JsonSchema))]
|
||||||
|
#[derive(Clone, Debug, Default, Serialize, Deserialize, PartialEq, EnumIter)]
|
||||||
|
pub enum Model {
|
||||||
|
#[serde(rename = "grok-2-vision-latest")]
|
||||||
|
Grok2Vision,
|
||||||
|
#[default]
|
||||||
|
#[serde(rename = "grok-3-latest")]
|
||||||
|
Grok3,
|
||||||
|
#[serde(rename = "grok-3-mini-latest")]
|
||||||
|
Grok3Mini,
|
||||||
|
#[serde(rename = "grok-3-fast-latest")]
|
||||||
|
Grok3Fast,
|
||||||
|
#[serde(rename = "grok-3-mini-fast-latest")]
|
||||||
|
Grok3MiniFast,
|
||||||
|
#[serde(rename = "grok-4-latest")]
|
||||||
|
Grok4,
|
||||||
|
#[serde(rename = "custom")]
|
||||||
|
Custom {
|
||||||
|
name: String,
|
||||||
|
/// The name displayed in the UI, such as in the assistant panel model dropdown menu.
|
||||||
|
display_name: Option<String>,
|
||||||
|
max_tokens: u64,
|
||||||
|
max_output_tokens: Option<u64>,
|
||||||
|
max_completion_tokens: Option<u64>,
|
||||||
|
},
|
||||||
|
}
|
||||||
|
|
||||||
|
impl Model {
|
||||||
|
pub fn default_fast() -> Self {
|
||||||
|
Self::Grok3Fast
|
||||||
|
}
|
||||||
|
|
||||||
|
pub fn from_id(id: &str) -> Result<Self> {
|
||||||
|
match id {
|
||||||
|
"grok-2-vision" => Ok(Self::Grok2Vision),
|
||||||
|
"grok-3" => Ok(Self::Grok3),
|
||||||
|
"grok-3-mini" => Ok(Self::Grok3Mini),
|
||||||
|
"grok-3-fast" => Ok(Self::Grok3Fast),
|
||||||
|
"grok-3-mini-fast" => Ok(Self::Grok3MiniFast),
|
||||||
|
_ => anyhow::bail!("invalid model id '{id}'"),
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
pub fn id(&self) -> &str {
|
||||||
|
match self {
|
||||||
|
Self::Grok2Vision => "grok-2-vision",
|
||||||
|
Self::Grok3 => "grok-3",
|
||||||
|
Self::Grok3Mini => "grok-3-mini",
|
||||||
|
Self::Grok3Fast => "grok-3-fast",
|
||||||
|
Self::Grok3MiniFast => "grok-3-mini-fast",
|
||||||
|
Self::Grok4 => "grok-4",
|
||||||
|
Self::Custom { name, .. } => name,
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
pub fn display_name(&self) -> &str {
|
||||||
|
match self {
|
||||||
|
Self::Grok2Vision => "Grok 2 Vision",
|
||||||
|
Self::Grok3 => "Grok 3",
|
||||||
|
Self::Grok3Mini => "Grok 3 Mini",
|
||||||
|
Self::Grok3Fast => "Grok 3 Fast",
|
||||||
|
Self::Grok3MiniFast => "Grok 3 Mini Fast",
|
||||||
|
Self::Grok4 => "Grok 4",
|
||||||
|
Self::Custom {
|
||||||
|
name, display_name, ..
|
||||||
|
} => display_name.as_ref().unwrap_or(name),
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
pub fn max_token_count(&self) -> u64 {
|
||||||
|
match self {
|
||||||
|
Self::Grok3 | Self::Grok3Mini | Self::Grok3Fast | Self::Grok3MiniFast => 131_072,
|
||||||
|
Self::Grok4 => 256_000,
|
||||||
|
Self::Grok2Vision => 8_192,
|
||||||
|
Self::Custom { max_tokens, .. } => *max_tokens,
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
pub fn max_output_tokens(&self) -> Option<u64> {
|
||||||
|
match self {
|
||||||
|
Self::Grok3 | Self::Grok3Mini | Self::Grok3Fast | Self::Grok3MiniFast => Some(8_192),
|
||||||
|
Self::Grok4 => Some(64_000),
|
||||||
|
Self::Grok2Vision => Some(4_096),
|
||||||
|
Self::Custom {
|
||||||
|
max_output_tokens, ..
|
||||||
|
} => *max_output_tokens,
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
pub fn supports_parallel_tool_calls(&self) -> bool {
|
||||||
|
match self {
|
||||||
|
Self::Grok2Vision
|
||||||
|
| Self::Grok3
|
||||||
|
| Self::Grok3Mini
|
||||||
|
| Self::Grok3Fast
|
||||||
|
| Self::Grok3MiniFast
|
||||||
|
| Self::Grok4 => true,
|
||||||
|
Model::Custom { .. } => false,
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
pub fn supports_tool(&self) -> bool {
|
||||||
|
match self {
|
||||||
|
Self::Grok2Vision
|
||||||
|
| Self::Grok3
|
||||||
|
| Self::Grok3Mini
|
||||||
|
| Self::Grok3Fast
|
||||||
|
| Self::Grok3MiniFast
|
||||||
|
| Self::Grok4 => true,
|
||||||
|
Model::Custom { .. } => false,
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
pub fn supports_images(&self) -> bool {
|
||||||
|
match self {
|
||||||
|
Self::Grok2Vision => true,
|
||||||
|
_ => false,
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
|
@ -23,6 +23,8 @@ Here's an overview of the supported providers and tool call support:
|
||||||
| [OpenAI](#openai) | ✅ |
|
| [OpenAI](#openai) | ✅ |
|
||||||
| [OpenAI API Compatible](#openai-api-compatible) | 🚫 |
|
| [OpenAI API Compatible](#openai-api-compatible) | 🚫 |
|
||||||
| [OpenRouter](#openrouter) | ✅ |
|
| [OpenRouter](#openrouter) | ✅ |
|
||||||
|
| [Vercel](#vercel-v0) | ✅ |
|
||||||
|
| [xAI](#xai) | ✅ |
|
||||||
|
|
||||||
## Use Your Own Keys {#use-your-own-keys}
|
## Use Your Own Keys {#use-your-own-keys}
|
||||||
|
|
||||||
|
@ -444,27 +446,30 @@ Custom models will be listed in the model dropdown in the Agent Panel.
|
||||||
|
|
||||||
Zed supports using OpenAI compatible APIs by specifying a custom `endpoint` and `available_models` for the OpenAI provider.
|
Zed supports using OpenAI compatible APIs by specifying a custom `endpoint` and `available_models` for the OpenAI provider.
|
||||||
|
|
||||||
You can add a custom API URL for OpenAI either via the UI or by editing your `settings.json`.
|
Zed supports using OpenAI compatible APIs by specifying a custom `api_url` and `available_models` for the OpenAI provider. This is useful for connecting to other hosted services (like Together AI, Anyscale, etc.) or local models.
|
||||||
Here are a few model examples you can plug in by using this feature:
|
|
||||||
|
|
||||||
#### X.ai Grok
|
To configure a compatible API, you can add a custom API URL for OpenAI either via the UI or by editing your `settings.json`. For example, to connect to [Together AI](https://www.together.ai/):
|
||||||
|
|
||||||
Example configuration for using X.ai Grok with Zed:
|
1. Get an API key from your [Together AI account](https://api.together.ai/settings/api-keys).
|
||||||
|
2. Add the following to your `settings.json`:
|
||||||
|
|
||||||
```json
|
```json
|
||||||
|
{
|
||||||
"language_models": {
|
"language_models": {
|
||||||
"openai": {
|
"openai": {
|
||||||
"api_url": "https://api.x.ai/v1",
|
"api_url": "https://api.together.xyz/v1",
|
||||||
|
"api_key": "YOUR_TOGETHER_AI_API_KEY",
|
||||||
"available_models": [
|
"available_models": [
|
||||||
{
|
{
|
||||||
"name": "grok-beta",
|
"name": "mistralai/Mixtral-8x7B-Instruct-v0.1",
|
||||||
"display_name": "X.ai Grok (Beta)",
|
"display_name": "Together Mixtral 8x7B",
|
||||||
"max_tokens": 131072
|
"max_tokens": 32768,
|
||||||
|
"supports_tools": true
|
||||||
}
|
}
|
||||||
],
|
]
|
||||||
"version": "1"
|
}
|
||||||
},
|
|
||||||
}
|
}
|
||||||
|
}
|
||||||
```
|
```
|
||||||
|
|
||||||
### OpenRouter {#openrouter}
|
### OpenRouter {#openrouter}
|
||||||
|
@ -525,7 +530,9 @@ You can find available models and their specifications on the [OpenRouter models
|
||||||
|
|
||||||
Custom models will be listed in the model dropdown in the Agent Panel.
|
Custom models will be listed in the model dropdown in the Agent Panel.
|
||||||
|
|
||||||
### Vercel v0
|
### Vercel v0 {#vercel-v0}
|
||||||
|
|
||||||
|
> ✅ Supports tool use
|
||||||
|
|
||||||
[Vercel v0](https://vercel.com/docs/v0/api) is an expert model for generating full-stack apps, with framework-aware completions optimized for modern stacks like Next.js and Vercel.
|
[Vercel v0](https://vercel.com/docs/v0/api) is an expert model for generating full-stack apps, with framework-aware completions optimized for modern stacks like Next.js and Vercel.
|
||||||
It supports text and image inputs and provides fast streaming responses.
|
It supports text and image inputs and provides fast streaming responses.
|
||||||
|
@ -537,6 +544,49 @@ Once you have it, paste it directly into the Vercel provider section in the pane
|
||||||
|
|
||||||
You should then find it as `v0-1.5-md` in the model dropdown in the Agent Panel.
|
You should then find it as `v0-1.5-md` in the model dropdown in the Agent Panel.
|
||||||
|
|
||||||
|
### xAI {#xai}
|
||||||
|
|
||||||
|
> ✅ Supports tool use
|
||||||
|
|
||||||
|
Zed has first-class support for [xAI](https://x.ai/) models. You can use your own API key to access Grok models.
|
||||||
|
|
||||||
|
1. [Create an API key in the xAI Console](https://console.x.ai/team/default/api-keys)
|
||||||
|
2. Open the settings view (`agent: open configuration`) and go to the **xAI** section
|
||||||
|
3. Enter your xAI API key
|
||||||
|
|
||||||
|
The xAI API key will be saved in your keychain. Zed will also use the `XAI_API_KEY` environment variable if it's defined.
|
||||||
|
|
||||||
|
> **Note:** While the xAI API is OpenAI-compatible, Zed has first-class support for it as a dedicated provider. For the best experience, we recommend using the dedicated `x_ai` provider configuration instead of the [OpenAI API Compatible](#openai-api-compatible) method.
|
||||||
|
|
||||||
|
#### Custom Models {#xai-custom-models}
|
||||||
|
|
||||||
|
The Zed agent comes pre-configured with common Grok models. If you wish to use alternate models or customize their parameters, you can do so by adding the following to your Zed `settings.json`:
|
||||||
|
|
||||||
|
```json
|
||||||
|
{
|
||||||
|
"language_models": {
|
||||||
|
"x_ai": {
|
||||||
|
"api_url": "https://api.x.ai/v1",
|
||||||
|
"available_models": [
|
||||||
|
{
|
||||||
|
"name": "grok-1.5",
|
||||||
|
"display_name": "Grok 1.5",
|
||||||
|
"max_tokens": 131072,
|
||||||
|
"max_output_tokens": 8192
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"name": "grok-1.5v",
|
||||||
|
"display_name": "Grok 1.5V (Vision)",
|
||||||
|
"max_tokens": 131072,
|
||||||
|
"max_output_tokens": 8192,
|
||||||
|
"supports_images": true
|
||||||
|
}
|
||||||
|
]
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
```
|
||||||
|
|
||||||
## Advanced Configuration {#advanced-configuration}
|
## Advanced Configuration {#advanced-configuration}
|
||||||
|
|
||||||
### Custom Provider Endpoints {#custom-provider-endpoint}
|
### Custom Provider Endpoints {#custom-provider-endpoint}
|
||||||
|
|
Loading…
Add table
Add a link
Reference in a new issue