Send up Zed version with edit prediction and completion requests (#30136)
This PR makes it so we send up an `x-zed-version` header with the client's version when making a request to llm.zed.dev for edit predictions and completions. Release Notes: - N/A
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5
Cargo.lock
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5
Cargo.lock
generated
@ -7901,6 +7901,7 @@ dependencies = [
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"partial-json-fixer",
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"project",
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"proto",
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"release_channel",
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"schemars",
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"serde",
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"serde_json",
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@ -18873,9 +18874,9 @@ dependencies = [
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[[package]]
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name = "zed_llm_client"
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version = "0.7.5"
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version = "0.8.0"
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source = "registry+https://github.com/rust-lang/crates.io-index"
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checksum = "6fe0d60001c02d0d21a4114a13bee3a905fbb9e146ada80a90435c05fda18852"
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checksum = "a23b2fd00776b0c55072f389654910ceb501eb0083d7f78905ab0e5cc86949ec"
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dependencies = [
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"anyhow",
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"serde",
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@ -609,7 +609,7 @@ wasmtime-wasi = "29"
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which = "6.0.0"
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wit-component = "0.221"
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workspace-hack = "0.1.0"
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zed_llm_client = "0.7.5"
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zed_llm_client = "0.8.0"
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zstd = "0.11"
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[workspace.dependencies.async-stripe]
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@ -1546,9 +1546,9 @@ impl Thread {
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completion.queue_state = QueueState::Started;
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}
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CompletionRequestStatus::Failed {
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code, message
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code, message, request_id
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} => {
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return Err(anyhow!("completion request failed. code: {code}, message: {message}"));
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return Err(anyhow!("completion request failed. request_id: {request_id}, code: {code}, message: {message}"));
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}
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CompletionRequestStatus::UsageUpdated {
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amount, limit
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@ -41,6 +41,7 @@ open_ai = { workspace = true, features = ["schemars"] }
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partial-json-fixer.workspace = true
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project.workspace = true
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proto.workspace = true
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release_channel.workspace = true
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schemars.workspace = true
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serde.workspace = true
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serde_json.workspace = true
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@ -6,7 +6,9 @@ use feature_flags::{FeatureFlagAppExt, LlmClosedBetaFeatureFlag, ZedProFeatureFl
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use futures::{
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AsyncBufReadExt, FutureExt, Stream, StreamExt, future::BoxFuture, stream::BoxStream,
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};
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use gpui::{AnyElement, AnyView, App, AsyncApp, Context, Entity, Subscription, Task};
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use gpui::{
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AnyElement, AnyView, App, AsyncApp, Context, Entity, SemanticVersion, Subscription, Task,
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};
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use http_client::{AsyncBody, HttpClient, Method, Response, StatusCode};
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use language_model::{
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AuthenticateError, CloudModel, LanguageModel, LanguageModelCacheConfiguration,
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@ -20,6 +22,7 @@ use language_model::{
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MaxMonthlySpendReachedError, PaymentRequiredError, RefreshLlmTokenListener,
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};
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use proto::Plan;
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use release_channel::AppVersion;
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use schemars::JsonSchema;
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use serde::{Deserialize, Serialize, de::DeserializeOwned};
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use settings::{Settings, SettingsStore};
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@ -39,7 +42,7 @@ use zed_llm_client::{
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CompletionRequestStatus, CountTokensBody, CountTokensResponse, EXPIRED_LLM_TOKEN_HEADER_NAME,
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MAX_LLM_MONTHLY_SPEND_REACHED_HEADER_NAME, MODEL_REQUESTS_RESOURCE_HEADER_VALUE,
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SERVER_SUPPORTS_STATUS_MESSAGES_HEADER_NAME, SUBSCRIPTION_LIMIT_RESOURCE_HEADER_NAME,
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TOOL_USE_LIMIT_REACHED_HEADER_NAME,
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TOOL_USE_LIMIT_REACHED_HEADER_NAME, ZED_VERSION_HEADER_NAME,
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};
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use crate::AllLanguageModelSettings;
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@ -526,6 +529,7 @@ impl CloudLanguageModel {
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async fn perform_llm_completion(
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client: Arc<Client>,
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llm_api_token: LlmApiToken,
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app_version: Option<SemanticVersion>,
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body: CompletionBody,
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) -> Result<PerformLlmCompletionResponse> {
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let http_client = &client.http_client();
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@ -542,6 +546,12 @@ impl CloudLanguageModel {
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} else {
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request_builder.uri(http_client.build_zed_llm_url("/completions", &[])?.as_ref())
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};
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let request_builder = if let Some(app_version) = app_version {
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request_builder.header(ZED_VERSION_HEADER_NAME, app_version.to_string())
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} else {
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request_builder
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};
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let request = request_builder
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.header("Content-Type", "application/json")
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.header("Authorization", format!("Bearer {token}"))
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@ -773,7 +783,7 @@ impl LanguageModel for CloudLanguageModel {
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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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cx: &AsyncApp,
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) -> BoxFuture<
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'static,
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Result<
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@ -783,6 +793,7 @@ impl LanguageModel for CloudLanguageModel {
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let thread_id = request.thread_id.clone();
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let prompt_id = request.prompt_id.clone();
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let mode = request.mode;
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let app_version = cx.update(|cx| AppVersion::global(cx)).ok();
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match &self.model {
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CloudModel::Anthropic(model) => {
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let request = into_anthropic(
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@ -803,6 +814,7 @@ impl LanguageModel for CloudLanguageModel {
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} = Self::perform_llm_completion(
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client.clone(),
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llm_api_token,
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app_version,
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CompletionBody {
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thread_id,
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prompt_id,
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@ -854,6 +866,7 @@ impl LanguageModel for CloudLanguageModel {
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} = Self::perform_llm_completion(
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client.clone(),
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llm_api_token,
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app_version,
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CompletionBody {
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thread_id,
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prompt_id,
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@ -890,6 +903,7 @@ impl LanguageModel for CloudLanguageModel {
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} = Self::perform_llm_completion(
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client.clone(),
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llm_api_token,
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app_version,
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CompletionBody {
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thread_id,
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prompt_id,
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@ -55,7 +55,7 @@ use workspace::notifications::{ErrorMessagePrompt, NotificationId};
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use worktree::Worktree;
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use zed_llm_client::{
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EXPIRED_LLM_TOKEN_HEADER_NAME, MINIMUM_REQUIRED_VERSION_HEADER_NAME, PredictEditsBody,
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PredictEditsResponse,
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PredictEditsResponse, ZED_VERSION_HEADER_NAME,
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};
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const CURSOR_MARKER: &'static str = "<|user_cursor_is_here|>";
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@ -754,6 +754,7 @@ and then another
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let request = request_builder
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.header("Content-Type", "application/json")
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.header("Authorization", format!("Bearer {}", token))
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.header(ZED_VERSION_HEADER_NAME, app_version.to_string())
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.body(serde_json::to_string(&body)?.into())?;
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let mut response = http_client.send(request).await?;
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