Files
llmx/llmx-rs/core/src/client.rs
Sebastian Krüger 3c7efc58c8 feat: Complete LLMX v0.1.0 - Rebrand from Codex with LiteLLM Integration
This release represents a comprehensive transformation of the codebase from Codex to LLMX,
enhanced with LiteLLM integration to support 100+ LLM providers through a unified API.

## Major Changes

### Phase 1: Repository & Infrastructure Setup
- Established new repository structure and branching strategy
- Created comprehensive project documentation (CLAUDE.md, LITELLM-SETUP.md)
- Set up development environment and tooling configuration

### Phase 2: Rust Workspace Transformation
- Renamed all Rust crates from `codex-*` to `llmx-*` (30+ crates)
- Updated package names, binary names, and workspace members
- Renamed core modules: codex.rs → llmx.rs, codex_delegate.rs → llmx_delegate.rs
- Updated all internal references, imports, and type names
- Renamed directories: codex-rs/ → llmx-rs/, codex-backend-openapi-models/ → llmx-backend-openapi-models/
- Fixed all Rust compilation errors after mass rename

### Phase 3: LiteLLM Integration
- Integrated LiteLLM for multi-provider LLM support (Anthropic, OpenAI, Azure, Google AI, AWS Bedrock, etc.)
- Implemented OpenAI-compatible Chat Completions API support
- Added model family detection and provider-specific handling
- Updated authentication to support LiteLLM API keys
- Renamed environment variables: OPENAI_BASE_URL → LLMX_BASE_URL
- Added LLMX_API_KEY for unified authentication
- Enhanced error handling for Chat Completions API responses
- Implemented fallback mechanisms between Responses API and Chat Completions API

### Phase 4: TypeScript/Node.js Components
- Renamed npm package: @codex/codex-cli → @valknar/llmx
- Updated TypeScript SDK to use new LLMX APIs and endpoints
- Fixed all TypeScript compilation and linting errors
- Updated SDK tests to support both API backends
- Enhanced mock server to handle multiple API formats
- Updated build scripts for cross-platform packaging

### Phase 5: Configuration & Documentation
- Updated all configuration files to use LLMX naming
- Rewrote README and documentation for LLMX branding
- Updated config paths: ~/.codex/ → ~/.llmx/
- Added comprehensive LiteLLM setup guide
- Updated all user-facing strings and help text
- Created release plan and migration documentation

### Phase 6: Testing & Validation
- Fixed all Rust tests for new naming scheme
- Updated snapshot tests in TUI (36 frame files)
- Fixed authentication storage tests
- Updated Chat Completions payload and SSE tests
- Fixed SDK tests for new API endpoints
- Ensured compatibility with Claude Sonnet 4.5 model
- Fixed test environment variables (LLMX_API_KEY, LLMX_BASE_URL)

### Phase 7: Build & Release Pipeline
- Updated GitHub Actions workflows for LLMX binary names
- Fixed rust-release.yml to reference llmx-rs/ instead of codex-rs/
- Updated CI/CD pipelines for new package names
- Made Apple code signing optional in release workflow
- Enhanced npm packaging resilience for partial platform builds
- Added Windows sandbox support to workspace
- Updated dotslash configuration for new binary names

### Phase 8: Final Polish
- Renamed all assets (.github images, labels, templates)
- Updated VSCode and DevContainer configurations
- Fixed all clippy warnings and formatting issues
- Applied cargo fmt and prettier formatting across codebase
- Updated issue templates and pull request templates
- Fixed all remaining UI text references

## Technical Details

**Breaking Changes:**
- Binary name changed from `codex` to `llmx`
- Config directory changed from `~/.codex/` to `~/.llmx/`
- Environment variables renamed (CODEX_* → LLMX_*)
- npm package renamed to `@valknar/llmx`

**New Features:**
- Support for 100+ LLM providers via LiteLLM
- Unified authentication with LLMX_API_KEY
- Enhanced model provider detection and handling
- Improved error handling and fallback mechanisms

**Files Changed:**
- 578 files modified across Rust, TypeScript, and documentation
- 30+ Rust crates renamed and updated
- Complete rebrand of UI, CLI, and documentation
- All tests updated and passing

**Dependencies:**
- Updated Cargo.lock with new package names
- Updated npm dependencies in llmx-cli
- Enhanced OpenAPI models for LLMX backend

This release establishes LLMX as a standalone project with comprehensive LiteLLM
integration, maintaining full backward compatibility with existing functionality
while opening support for a wide ecosystem of LLM providers.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
Co-Authored-By: Sebastian Krüger <support@pivoine.art>
2025-11-12 20:40:44 +01:00

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use std::io::BufRead;
use std::path::Path;
use std::sync::Arc;
use std::sync::OnceLock;
use std::time::Duration;
use bytes::Bytes;
use chrono::DateTime;
use chrono::Utc;
use eventsource_stream::Eventsource;
use futures::prelude::*;
use llmx_app_server_protocol::AuthMode;
use llmx_otel::otel_event_manager::OtelEventManager;
use llmx_protocol::ConversationId;
use llmx_protocol::config_types::ReasoningEffort as ReasoningEffortConfig;
use llmx_protocol::config_types::ReasoningSummary as ReasoningSummaryConfig;
use llmx_protocol::models::ResponseItem;
use llmx_protocol::protocol::SessionSource;
use regex_lite::Regex;
use reqwest::StatusCode;
use reqwest::header::HeaderMap;
use serde::Deserialize;
use serde::Serialize;
use serde_json::Value;
use tokio::sync::mpsc;
use tokio::time::timeout;
use tokio_util::io::ReaderStream;
use tracing::debug;
use tracing::trace;
use tracing::warn;
use crate::AuthManager;
use crate::auth::LlmxAuth;
use crate::auth::RefreshTokenError;
use crate::chat_completions::AggregateStreamExt;
use crate::chat_completions::stream_chat_completions;
use crate::client_common::Prompt;
use crate::client_common::ResponseEvent;
use crate::client_common::ResponseStream;
use crate::client_common::ResponsesApiRequest;
use crate::client_common::create_reasoning_param_for_request;
use crate::client_common::create_text_param_for_request;
use crate::config::Config;
use crate::default_client::LlmxHttpClient;
use crate::default_client::create_client;
use crate::error::ConnectionFailedError;
use crate::error::LlmxErr;
use crate::error::ResponseStreamFailed;
use crate::error::Result;
use crate::error::RetryLimitReachedError;
use crate::error::UnexpectedResponseError;
use crate::error::UsageLimitReachedError;
use crate::flags::LLMX_RS_SSE_FIXTURE;
use crate::model_family::ModelFamily;
use crate::model_provider_info::ModelProviderInfo;
use crate::model_provider_info::WireApi;
use crate::openai_model_info::get_model_info;
use crate::protocol::RateLimitSnapshot;
use crate::protocol::RateLimitWindow;
use crate::protocol::TokenUsage;
use crate::token_data::PlanType;
use crate::tools::spec::create_tools_json_for_responses_api;
use crate::util::backoff;
#[derive(Debug, Deserialize)]
struct ErrorResponse {
error: Error,
}
#[derive(Debug, Deserialize)]
struct Error {
r#type: Option<String>,
code: Option<String>,
message: Option<String>,
// Optional fields available on "usage_limit_reached" and "usage_not_included" errors
plan_type: Option<PlanType>,
resets_at: Option<i64>,
}
#[derive(Debug, Clone)]
pub struct ModelClient {
config: Arc<Config>,
auth_manager: Option<Arc<AuthManager>>,
otel_event_manager: OtelEventManager,
client: LlmxHttpClient,
provider: ModelProviderInfo,
conversation_id: ConversationId,
effort: Option<ReasoningEffortConfig>,
summary: ReasoningSummaryConfig,
session_source: SessionSource,
}
#[allow(clippy::too_many_arguments)]
impl ModelClient {
pub fn new(
config: Arc<Config>,
auth_manager: Option<Arc<AuthManager>>,
otel_event_manager: OtelEventManager,
provider: ModelProviderInfo,
effort: Option<ReasoningEffortConfig>,
summary: ReasoningSummaryConfig,
conversation_id: ConversationId,
session_source: SessionSource,
) -> Self {
let client = create_client();
Self {
config,
auth_manager,
otel_event_manager,
client,
provider,
conversation_id,
effort,
summary,
session_source,
}
}
pub fn get_model_context_window(&self) -> Option<i64> {
let pct = self.config.model_family.effective_context_window_percent;
self.config
.model_context_window
.or_else(|| get_model_info(&self.config.model_family).map(|info| info.context_window))
.map(|w| w.saturating_mul(pct) / 100)
}
pub fn get_auto_compact_token_limit(&self) -> Option<i64> {
self.config.model_auto_compact_token_limit.or_else(|| {
get_model_info(&self.config.model_family).and_then(|info| info.auto_compact_token_limit)
})
}
pub fn config(&self) -> Arc<Config> {
Arc::clone(&self.config)
}
pub fn provider(&self) -> &ModelProviderInfo {
&self.provider
}
pub async fn stream(&self, prompt: &Prompt) -> Result<ResponseStream> {
match self.provider.wire_api {
WireApi::Responses => self.stream_responses(prompt).await,
WireApi::Chat => {
// Create the raw streaming connection first.
let response_stream = stream_chat_completions(
prompt,
&self.config.model_family,
&self.client,
&self.provider,
&self.otel_event_manager,
&self.session_source,
)
.await?;
// Wrap it with the aggregation adapter so callers see *only*
// the final assistant message per turn (matching the
// behaviour of the Responses API).
let mut aggregated = if self.config.show_raw_agent_reasoning {
crate::chat_completions::AggregatedChatStream::streaming_mode(response_stream)
} else {
response_stream.aggregate()
};
// Bridge the aggregated stream back into a standard
// `ResponseStream` by forwarding events through a channel.
let (tx, rx) = mpsc::channel::<Result<ResponseEvent>>(16);
tokio::spawn(async move {
use futures::StreamExt;
while let Some(ev) = aggregated.next().await {
// Exit early if receiver hung up.
if tx.send(ev).await.is_err() {
break;
}
}
});
Ok(ResponseStream { rx_event: rx })
}
}
}
/// Implementation for the OpenAI *Responses* experimental API.
async fn stream_responses(&self, prompt: &Prompt) -> Result<ResponseStream> {
if let Some(path) = &*LLMX_RS_SSE_FIXTURE {
// short circuit for tests
warn!(path, "Streaming from fixture");
return stream_from_fixture(
path,
self.provider.clone(),
self.otel_event_manager.clone(),
)
.await;
}
let auth_manager = self.auth_manager.clone();
let full_instructions = prompt.get_full_instructions(&self.config.model_family);
let tools_json = create_tools_json_for_responses_api(&prompt.tools)?;
let reasoning = create_reasoning_param_for_request(
&self.config.model_family,
self.effort,
self.summary,
);
let include: Vec<String> = if reasoning.is_some() {
vec!["reasoning.encrypted_content".to_string()]
} else {
vec![]
};
let input_with_instructions = prompt.get_formatted_input();
let verbosity = if self.config.model_family.support_verbosity {
self.config.model_verbosity
} else {
if self.config.model_verbosity.is_some() {
warn!(
"model_verbosity is set but ignored as the model does not support verbosity: {}",
self.config.model_family.family
);
}
None
};
// Only include `text.verbosity` for GPT-5 family models
let text = create_text_param_for_request(verbosity, &prompt.output_schema);
// In general, we want to explicitly send `store: false` when using the Responses API,
// but in practice, the Azure Responses API rejects `store: false`:
//
// - If store = false and id is sent an error is thrown that ID is not found
// - If store = false and id is not sent an error is thrown that ID is required
//
// For Azure, we send `store: true` and preserve reasoning item IDs.
let azure_workaround = self.provider.is_azure_responses_endpoint();
let payload = ResponsesApiRequest {
model: &self.config.model,
instructions: &full_instructions,
input: &input_with_instructions,
tools: &tools_json,
tool_choice: "auto",
parallel_tool_calls: prompt.parallel_tool_calls,
reasoning,
store: azure_workaround,
stream: true,
include,
prompt_cache_key: Some(self.conversation_id.to_string()),
text,
};
let mut payload_json = serde_json::to_value(&payload)?;
if azure_workaround {
attach_item_ids(&mut payload_json, &input_with_instructions);
}
let max_attempts = self.provider.request_max_retries();
for attempt in 0..=max_attempts {
match self
.attempt_stream_responses(attempt, &payload_json, &auth_manager)
.await
{
Ok(stream) => {
return Ok(stream);
}
Err(StreamAttemptError::Fatal(e)) => {
return Err(e);
}
Err(retryable_attempt_error) => {
if attempt == max_attempts {
return Err(retryable_attempt_error.into_error());
}
tokio::time::sleep(retryable_attempt_error.delay(attempt)).await;
}
}
}
unreachable!("stream_responses_attempt should always return");
}
/// Single attempt to start a streaming Responses API call.
async fn attempt_stream_responses(
&self,
attempt: u64,
payload_json: &Value,
auth_manager: &Option<Arc<AuthManager>>,
) -> std::result::Result<ResponseStream, StreamAttemptError> {
// Always fetch the latest auth in case a prior attempt refreshed the token.
let auth = auth_manager.as_ref().and_then(|m| m.auth());
trace!(
"POST to {}: {:?}",
self.provider.get_full_url(&auth),
serde_json::to_string(payload_json)
.unwrap_or("<unable to serialize payload>".to_string())
);
let mut req_builder = self
.provider
.create_request_builder(&self.client, &auth)
.await
.map_err(StreamAttemptError::Fatal)?;
// Include subagent header only for subagent sessions.
if let SessionSource::SubAgent(sub) = &self.session_source {
let subagent = if let crate::protocol::SubAgentSource::Other(label) = sub {
label.clone()
} else {
serde_json::to_value(sub)
.ok()
.and_then(|v| v.as_str().map(std::string::ToString::to_string))
.unwrap_or_else(|| "other".to_string())
};
req_builder = req_builder.header("x-openai-subagent", subagent);
}
req_builder = req_builder
// Send session_id for compatibility.
.header("conversation_id", self.conversation_id.to_string())
.header("session_id", self.conversation_id.to_string())
.header(reqwest::header::ACCEPT, "text/event-stream")
.json(payload_json);
if let Some(auth) = auth.as_ref()
&& auth.mode == AuthMode::ChatGPT
&& let Some(account_id) = auth.get_account_id()
{
req_builder = req_builder.header("chatgpt-account-id", account_id);
}
let res = self
.otel_event_manager
.log_request(attempt, || req_builder.send())
.await;
let mut request_id = None;
if let Ok(resp) = &res {
request_id = resp
.headers()
.get("cf-ray")
.map(|v| v.to_str().unwrap_or_default().to_string());
}
match res {
Ok(resp) if resp.status().is_success() => {
let (tx_event, rx_event) = mpsc::channel::<Result<ResponseEvent>>(1600);
if let Some(snapshot) = parse_rate_limit_snapshot(resp.headers())
&& tx_event
.send(Ok(ResponseEvent::RateLimits(snapshot)))
.await
.is_err()
{
debug!("receiver dropped rate limit snapshot event");
}
// spawn task to process SSE
let stream = resp.bytes_stream().map_err(move |e| {
LlmxErr::ResponseStreamFailed(ResponseStreamFailed {
source: e,
request_id: request_id.clone(),
})
});
tokio::spawn(process_sse(
stream,
tx_event,
self.provider.stream_idle_timeout(),
self.otel_event_manager.clone(),
));
Ok(ResponseStream { rx_event })
}
Ok(res) => {
let status = res.status();
// Pull out RetryAfter header if present.
let retry_after_secs = res
.headers()
.get(reqwest::header::RETRY_AFTER)
.and_then(|v| v.to_str().ok())
.and_then(|s| s.parse::<u64>().ok());
let retry_after = retry_after_secs.map(|s| Duration::from_millis(s * 1_000));
if status == StatusCode::UNAUTHORIZED
&& let Some(manager) = auth_manager.as_ref()
&& let Some(auth) = auth.as_ref()
&& auth.mode == AuthMode::ChatGPT
&& let Err(err) = manager.refresh_token().await
{
let stream_error = match err {
RefreshTokenError::Permanent(failed) => {
StreamAttemptError::Fatal(LlmxErr::RefreshTokenFailed(failed))
}
RefreshTokenError::Transient(other) => {
StreamAttemptError::RetryableTransportError(LlmxErr::Io(other))
}
};
return Err(stream_error);
}
// The OpenAI Responses endpoint returns structured JSON bodies even for 4xx/5xx
// errors. When we bubble early with only the HTTP status the caller sees an opaque
// "unexpected status 400 Bad Request" which makes debugging nearly impossible.
// Instead, read (and include) the response text so higher layers and users see the
// exact error message (e.g. "Unknown parameter: 'input[0].metadata'"). The body is
// small and this branch only runs on error paths so the extra allocation is
// negligible.
if !(status == StatusCode::TOO_MANY_REQUESTS
|| status == StatusCode::UNAUTHORIZED
|| status.is_server_error())
{
// Surface the error body to callers. Use `unwrap_or_default` per Clippy.
let body = res.text().await.unwrap_or_default();
return Err(StreamAttemptError::Fatal(LlmxErr::UnexpectedStatus(
UnexpectedResponseError {
status,
body,
request_id: None,
},
)));
}
if status == StatusCode::TOO_MANY_REQUESTS {
let rate_limit_snapshot = parse_rate_limit_snapshot(res.headers());
let body = res.json::<ErrorResponse>().await.ok();
if let Some(ErrorResponse { error }) = body {
if error.r#type.as_deref() == Some("usage_limit_reached") {
// Prefer the plan_type provided in the error message if present
// because it's more up to date than the one encoded in the auth
// token.
let plan_type = error
.plan_type
.or_else(|| auth.as_ref().and_then(LlmxAuth::get_plan_type));
let resets_at = error
.resets_at
.and_then(|seconds| DateTime::<Utc>::from_timestamp(seconds, 0));
let llmx_err = LlmxErr::UsageLimitReached(UsageLimitReachedError {
plan_type,
resets_at,
rate_limits: rate_limit_snapshot,
});
return Err(StreamAttemptError::Fatal(llmx_err));
} else if error.r#type.as_deref() == Some("usage_not_included") {
return Err(StreamAttemptError::Fatal(LlmxErr::UsageNotIncluded));
} else if is_quota_exceeded_error(&error) {
return Err(StreamAttemptError::Fatal(LlmxErr::QuotaExceeded));
}
}
}
Err(StreamAttemptError::RetryableHttpError {
status,
retry_after,
request_id,
})
}
Err(e) => Err(StreamAttemptError::RetryableTransportError(
LlmxErr::ConnectionFailed(ConnectionFailedError { source: e }),
)),
}
}
pub fn get_provider(&self) -> ModelProviderInfo {
self.provider.clone()
}
pub fn get_otel_event_manager(&self) -> OtelEventManager {
self.otel_event_manager.clone()
}
pub fn get_session_source(&self) -> SessionSource {
self.session_source.clone()
}
/// Returns the currently configured model slug.
pub fn get_model(&self) -> String {
self.config.model.clone()
}
/// Returns the currently configured model family.
pub fn get_model_family(&self) -> ModelFamily {
self.config.model_family.clone()
}
/// Returns the current reasoning effort setting.
pub fn get_reasoning_effort(&self) -> Option<ReasoningEffortConfig> {
self.effort
}
/// Returns the current reasoning summary setting.
pub fn get_reasoning_summary(&self) -> ReasoningSummaryConfig {
self.summary
}
pub fn get_auth_manager(&self) -> Option<Arc<AuthManager>> {
self.auth_manager.clone()
}
}
enum StreamAttemptError {
RetryableHttpError {
status: StatusCode,
retry_after: Option<Duration>,
request_id: Option<String>,
},
RetryableTransportError(LlmxErr),
Fatal(LlmxErr),
}
impl StreamAttemptError {
/// attempt is 0-based.
fn delay(&self, attempt: u64) -> Duration {
// backoff() uses 1-based attempts.
let backoff_attempt = attempt + 1;
match self {
Self::RetryableHttpError { retry_after, .. } => {
retry_after.unwrap_or_else(|| backoff(backoff_attempt))
}
Self::RetryableTransportError { .. } => backoff(backoff_attempt),
Self::Fatal(_) => {
// Should not be called on Fatal errors.
Duration::from_secs(0)
}
}
}
fn into_error(self) -> LlmxErr {
match self {
Self::RetryableHttpError {
status, request_id, ..
} => {
if status == StatusCode::INTERNAL_SERVER_ERROR {
LlmxErr::InternalServerError
} else {
LlmxErr::RetryLimit(RetryLimitReachedError { status, request_id })
}
}
Self::RetryableTransportError(error) => error,
Self::Fatal(error) => error,
}
}
}
#[derive(Debug, Deserialize, Serialize)]
struct SseEvent {
#[serde(rename = "type")]
kind: String,
response: Option<Value>,
item: Option<Value>,
delta: Option<String>,
}
#[derive(Debug, Deserialize)]
struct ResponseCompleted {
id: String,
usage: Option<ResponseCompletedUsage>,
}
#[derive(Debug, Deserialize)]
struct ResponseCompletedUsage {
input_tokens: i64,
input_tokens_details: Option<ResponseCompletedInputTokensDetails>,
output_tokens: i64,
output_tokens_details: Option<ResponseCompletedOutputTokensDetails>,
total_tokens: i64,
}
impl From<ResponseCompletedUsage> for TokenUsage {
fn from(val: ResponseCompletedUsage) -> Self {
TokenUsage {
input_tokens: val.input_tokens,
cached_input_tokens: val
.input_tokens_details
.map(|d| d.cached_tokens)
.unwrap_or(0),
output_tokens: val.output_tokens,
reasoning_output_tokens: val
.output_tokens_details
.map(|d| d.reasoning_tokens)
.unwrap_or(0),
total_tokens: val.total_tokens,
}
}
}
#[derive(Debug, Deserialize)]
struct ResponseCompletedInputTokensDetails {
cached_tokens: i64,
}
#[derive(Debug, Deserialize)]
struct ResponseCompletedOutputTokensDetails {
reasoning_tokens: i64,
}
fn attach_item_ids(payload_json: &mut Value, original_items: &[ResponseItem]) {
let Some(input_value) = payload_json.get_mut("input") else {
return;
};
let serde_json::Value::Array(items) = input_value else {
return;
};
for (value, item) in items.iter_mut().zip(original_items.iter()) {
if let ResponseItem::Reasoning { id, .. }
| ResponseItem::Message { id: Some(id), .. }
| ResponseItem::WebSearchCall { id: Some(id), .. }
| ResponseItem::FunctionCall { id: Some(id), .. }
| ResponseItem::LocalShellCall { id: Some(id), .. }
| ResponseItem::CustomToolCall { id: Some(id), .. } = item
{
if id.is_empty() {
continue;
}
if let Some(obj) = value.as_object_mut() {
obj.insert("id".to_string(), Value::String(id.clone()));
}
}
}
}
fn parse_rate_limit_snapshot(headers: &HeaderMap) -> Option<RateLimitSnapshot> {
let primary = parse_rate_limit_window(
headers,
"x-llmx-primary-used-percent",
"x-llmx-primary-window-minutes",
"x-llmx-primary-reset-at",
);
let secondary = parse_rate_limit_window(
headers,
"x-llmx-secondary-used-percent",
"x-llmx-secondary-window-minutes",
"x-llmx-secondary-reset-at",
);
Some(RateLimitSnapshot { primary, secondary })
}
fn parse_rate_limit_window(
headers: &HeaderMap,
used_percent_header: &str,
window_minutes_header: &str,
resets_at_header: &str,
) -> Option<RateLimitWindow> {
let used_percent: Option<f64> = parse_header_f64(headers, used_percent_header);
used_percent.and_then(|used_percent| {
let window_minutes = parse_header_i64(headers, window_minutes_header);
let resets_at = parse_header_i64(headers, resets_at_header);
let has_data = used_percent != 0.0
|| window_minutes.is_some_and(|minutes| minutes != 0)
|| resets_at.is_some();
has_data.then_some(RateLimitWindow {
used_percent,
window_minutes,
resets_at,
})
})
}
fn parse_header_f64(headers: &HeaderMap, name: &str) -> Option<f64> {
parse_header_str(headers, name)?
.parse::<f64>()
.ok()
.filter(|v| v.is_finite())
}
fn parse_header_i64(headers: &HeaderMap, name: &str) -> Option<i64> {
parse_header_str(headers, name)?.parse::<i64>().ok()
}
fn parse_header_str<'a>(headers: &'a HeaderMap, name: &str) -> Option<&'a str> {
headers.get(name)?.to_str().ok()
}
async fn process_sse<S>(
stream: S,
tx_event: mpsc::Sender<Result<ResponseEvent>>,
idle_timeout: Duration,
otel_event_manager: OtelEventManager,
) where
S: Stream<Item = Result<Bytes>> + Unpin,
{
let mut stream = stream.eventsource();
// If the stream stays completely silent for an extended period treat it as disconnected.
// The response id returned from the "complete" message.
let mut response_completed: Option<ResponseCompleted> = None;
let mut response_error: Option<LlmxErr> = None;
loop {
let start = std::time::Instant::now();
let response = timeout(idle_timeout, stream.next()).await;
let duration = start.elapsed();
otel_event_manager.log_sse_event(&response, duration);
let sse = match response {
Ok(Some(Ok(sse))) => sse,
Ok(Some(Err(e))) => {
debug!("SSE Error: {e:#}");
let event = LlmxErr::Stream(e.to_string(), None);
let _ = tx_event.send(Err(event)).await;
return;
}
Ok(None) => {
match response_completed {
Some(ResponseCompleted {
id: response_id,
usage,
}) => {
if let Some(token_usage) = &usage {
otel_event_manager.sse_event_completed(
token_usage.input_tokens,
token_usage.output_tokens,
token_usage
.input_tokens_details
.as_ref()
.map(|d| d.cached_tokens),
token_usage
.output_tokens_details
.as_ref()
.map(|d| d.reasoning_tokens),
token_usage.total_tokens,
);
}
let event = ResponseEvent::Completed {
response_id,
token_usage: usage.map(Into::into),
};
let _ = tx_event.send(Ok(event)).await;
}
None => {
let error = response_error.unwrap_or(LlmxErr::Stream(
"stream closed before response.completed".into(),
None,
));
otel_event_manager.see_event_completed_failed(&error);
let _ = tx_event.send(Err(error)).await;
}
}
return;
}
Err(_) => {
let _ = tx_event
.send(Err(LlmxErr::Stream(
"idle timeout waiting for SSE".into(),
None,
)))
.await;
return;
}
};
let raw = sse.data.clone();
trace!("SSE event: {}", raw);
let event: SseEvent = match serde_json::from_str(&sse.data) {
Ok(event) => event,
Err(e) => {
debug!("Failed to parse SSE event: {e}, data: {}", &sse.data);
continue;
}
};
match event.kind.as_str() {
// Individual output item finalised. Forward immediately so the
// rest of the agent can stream assistant text/functions *live*
// instead of waiting for the final `response.completed` envelope.
//
// IMPORTANT: We used to ignore these events and forward the
// duplicated `output` array embedded in the `response.completed`
// payload. That produced two concrete issues:
// 1. No realtime streaming the user only saw output after the
// entire turn had finished, which broke the "typing" UX and
// made longrunning turns look stalled.
// 2. Duplicate `function_call_output` items both the
// individual *and* the completed array were forwarded, which
// confused the backend and triggered 400
// "previous_response_not_found" errors because the duplicated
// IDs did not match the incremental turn chain.
//
// The fix is to forward the incremental events *as they come* and
// drop the duplicated list inside `response.completed`.
"response.output_item.done" => {
let Some(item_val) = event.item else { continue };
let Ok(item) = serde_json::from_value::<ResponseItem>(item_val) else {
debug!("failed to parse ResponseItem from output_item.done");
continue;
};
let event = ResponseEvent::OutputItemDone(item);
if tx_event.send(Ok(event)).await.is_err() {
return;
}
}
"response.output_text.delta" => {
if let Some(delta) = event.delta {
let event = ResponseEvent::OutputTextDelta(delta);
if tx_event.send(Ok(event)).await.is_err() {
return;
}
}
}
"response.reasoning_summary_text.delta" => {
if let Some(delta) = event.delta {
let event = ResponseEvent::ReasoningSummaryDelta(delta);
if tx_event.send(Ok(event)).await.is_err() {
return;
}
}
}
"response.reasoning_text.delta" => {
if let Some(delta) = event.delta {
let event = ResponseEvent::ReasoningContentDelta(delta);
if tx_event.send(Ok(event)).await.is_err() {
return;
}
}
}
"response.created" => {
if event.response.is_some() {
let _ = tx_event.send(Ok(ResponseEvent::Created {})).await;
}
}
"response.failed" => {
if let Some(resp_val) = event.response {
response_error = Some(LlmxErr::Stream(
"response.failed event received".to_string(),
None,
));
let error = resp_val.get("error");
if let Some(error) = error {
match serde_json::from_value::<Error>(error.clone()) {
Ok(error) => {
if is_context_window_error(&error) {
response_error = Some(LlmxErr::ContextWindowExceeded);
} else if is_quota_exceeded_error(&error) {
response_error = Some(LlmxErr::QuotaExceeded);
} else {
let delay = try_parse_retry_after(&error);
let message = error.message.clone().unwrap_or_default();
response_error = Some(LlmxErr::Stream(message, delay));
}
}
Err(e) => {
let error = format!("failed to parse ErrorResponse: {e}");
debug!(error);
response_error = Some(LlmxErr::Stream(error, None))
}
}
}
}
}
// Final response completed includes array of output items & id
"response.completed" => {
if let Some(resp_val) = event.response {
match serde_json::from_value::<ResponseCompleted>(resp_val) {
Ok(r) => {
response_completed = Some(r);
}
Err(e) => {
let error = format!("failed to parse ResponseCompleted: {e}");
debug!(error);
response_error = Some(LlmxErr::Stream(error, None));
continue;
}
};
};
}
"response.content_part.done"
| "response.function_call_arguments.delta"
| "response.custom_tool_call_input.delta"
| "response.custom_tool_call_input.done" // also emitted as response.output_item.done
| "response.in_progress"
| "response.output_text.done" => {}
"response.output_item.added" => {
let Some(item_val) = event.item else { continue };
let Ok(item) = serde_json::from_value::<ResponseItem>(item_val) else {
debug!("failed to parse ResponseItem from output_item.done");
continue;
};
let event = ResponseEvent::OutputItemAdded(item);
if tx_event.send(Ok(event)).await.is_err() {
return;
}
}
"response.reasoning_summary_part.added" => {
// Boundary between reasoning summary sections (e.g., titles).
let event = ResponseEvent::ReasoningSummaryPartAdded;
if tx_event.send(Ok(event)).await.is_err() {
return;
}
}
"response.reasoning_summary_text.done" => {}
_ => {}
}
}
}
/// used in tests to stream from a text SSE file
async fn stream_from_fixture(
path: impl AsRef<Path>,
provider: ModelProviderInfo,
otel_event_manager: OtelEventManager,
) -> Result<ResponseStream> {
let (tx_event, rx_event) = mpsc::channel::<Result<ResponseEvent>>(1600);
let f = std::fs::File::open(path.as_ref())?;
let lines = std::io::BufReader::new(f).lines();
// insert \n\n after each line for proper SSE parsing
let mut content = String::new();
for line in lines {
content.push_str(&line?);
content.push_str("\n\n");
}
let rdr = std::io::Cursor::new(content);
let stream = ReaderStream::new(rdr).map_err(LlmxErr::Io);
tokio::spawn(process_sse(
stream,
tx_event,
provider.stream_idle_timeout(),
otel_event_manager,
));
Ok(ResponseStream { rx_event })
}
fn rate_limit_regex() -> &'static Regex {
static RE: OnceLock<Regex> = OnceLock::new();
// Match both OpenAI-style messages like "Please try again in 1.898s"
// and Azure OpenAI-style messages like "Try again in 35 seconds".
#[expect(clippy::unwrap_used)]
RE.get_or_init(|| Regex::new(r"(?i)try again in\s*(\d+(?:\.\d+)?)\s*(s|ms|seconds?)").unwrap())
}
fn try_parse_retry_after(err: &Error) -> Option<Duration> {
if err.code != Some("rate_limit_exceeded".to_string()) {
return None;
}
// parse retry hints like "try again in 1.898s" or
// "Try again in 35 seconds" using regex
let re = rate_limit_regex();
if let Some(message) = &err.message
&& let Some(captures) = re.captures(message)
{
let seconds = captures.get(1);
let unit = captures.get(2);
if let (Some(value), Some(unit)) = (seconds, unit) {
let value = value.as_str().parse::<f64>().ok()?;
let unit = unit.as_str().to_ascii_lowercase();
if unit == "s" || unit.starts_with("second") {
return Some(Duration::from_secs_f64(value));
} else if unit == "ms" {
return Some(Duration::from_millis(value as u64));
}
}
}
None
}
fn is_context_window_error(error: &Error) -> bool {
error.code.as_deref() == Some("context_length_exceeded")
}
fn is_quota_exceeded_error(error: &Error) -> bool {
error.code.as_deref() == Some("insufficient_quota")
}
#[cfg(test)]
mod tests {
use super::*;
use assert_matches::assert_matches;
use serde_json::json;
use tokio::sync::mpsc;
use tokio_test::io::Builder as IoBuilder;
use tokio_util::io::ReaderStream;
// ────────────────────────────
// Helpers
// ────────────────────────────
/// Runs the SSE parser on pre-chunked byte slices and returns every event
/// (including any final `Err` from a stream-closure check).
async fn collect_events(
chunks: &[&[u8]],
provider: ModelProviderInfo,
otel_event_manager: OtelEventManager,
) -> Vec<Result<ResponseEvent>> {
let mut builder = IoBuilder::new();
for chunk in chunks {
builder.read(chunk);
}
let reader = builder.build();
let stream = ReaderStream::new(reader).map_err(LlmxErr::Io);
let (tx, mut rx) = mpsc::channel::<Result<ResponseEvent>>(16);
tokio::spawn(process_sse(
stream,
tx,
provider.stream_idle_timeout(),
otel_event_manager,
));
let mut events = Vec::new();
while let Some(ev) = rx.recv().await {
events.push(ev);
}
events
}
/// Builds an in-memory SSE stream from JSON fixtures and returns only the
/// successfully parsed events (panics on internal channel errors).
async fn run_sse(
events: Vec<serde_json::Value>,
provider: ModelProviderInfo,
otel_event_manager: OtelEventManager,
) -> Vec<ResponseEvent> {
let mut body = String::new();
for e in events {
let kind = e
.get("type")
.and_then(|v| v.as_str())
.expect("fixture event missing type");
if e.as_object().map(|o| o.len() == 1).unwrap_or(false) {
body.push_str(&format!("event: {kind}\n\n"));
} else {
body.push_str(&format!("event: {kind}\ndata: {e}\n\n"));
}
}
let (tx, mut rx) = mpsc::channel::<Result<ResponseEvent>>(8);
let stream = ReaderStream::new(std::io::Cursor::new(body)).map_err(LlmxErr::Io);
tokio::spawn(process_sse(
stream,
tx,
provider.stream_idle_timeout(),
otel_event_manager,
));
let mut out = Vec::new();
while let Some(ev) = rx.recv().await {
out.push(ev.expect("channel closed"));
}
out
}
fn otel_event_manager() -> OtelEventManager {
OtelEventManager::new(
ConversationId::new(),
"test",
"test",
None,
Some("test@test.com".to_string()),
Some(AuthMode::ChatGPT),
false,
"test".to_string(),
)
}
// ────────────────────────────
// Tests from `implement-test-for-responses-api-sse-parser`
// ────────────────────────────
#[tokio::test]
async fn parses_items_and_completed() {
let item1 = json!({
"type": "response.output_item.done",
"item": {
"type": "message",
"role": "assistant",
"content": [{"type": "output_text", "text": "Hello"}]
}
})
.to_string();
let item2 = json!({
"type": "response.output_item.done",
"item": {
"type": "message",
"role": "assistant",
"content": [{"type": "output_text", "text": "World"}]
}
})
.to_string();
let completed = json!({
"type": "response.completed",
"response": { "id": "resp1" }
})
.to_string();
let sse1 = format!("event: response.output_item.done\ndata: {item1}\n\n");
let sse2 = format!("event: response.output_item.done\ndata: {item2}\n\n");
let sse3 = format!("event: response.completed\ndata: {completed}\n\n");
let provider = ModelProviderInfo {
name: "test".to_string(),
base_url: Some("https://test.com".to_string()),
env_key: Some("TEST_API_KEY".to_string()),
env_key_instructions: None,
experimental_bearer_token: None,
wire_api: WireApi::Responses,
query_params: None,
http_headers: None,
env_http_headers: None,
request_max_retries: Some(0),
stream_max_retries: Some(0),
stream_idle_timeout_ms: Some(1000),
requires_openai_auth: false,
};
let otel_event_manager = otel_event_manager();
let events = collect_events(
&[sse1.as_bytes(), sse2.as_bytes(), sse3.as_bytes()],
provider,
otel_event_manager,
)
.await;
assert_eq!(events.len(), 3);
matches!(
&events[0],
Ok(ResponseEvent::OutputItemDone(ResponseItem::Message { role, .. }))
if role == "assistant"
);
matches!(
&events[1],
Ok(ResponseEvent::OutputItemDone(ResponseItem::Message { role, .. }))
if role == "assistant"
);
match &events[2] {
Ok(ResponseEvent::Completed {
response_id,
token_usage,
}) => {
assert_eq!(response_id, "resp1");
assert!(token_usage.is_none());
}
other => panic!("unexpected third event: {other:?}"),
}
}
#[tokio::test]
async fn error_when_missing_completed() {
let item1 = json!({
"type": "response.output_item.done",
"item": {
"type": "message",
"role": "assistant",
"content": [{"type": "output_text", "text": "Hello"}]
}
})
.to_string();
let sse1 = format!("event: response.output_item.done\ndata: {item1}\n\n");
let provider = ModelProviderInfo {
name: "test".to_string(),
base_url: Some("https://test.com".to_string()),
env_key: Some("TEST_API_KEY".to_string()),
env_key_instructions: None,
experimental_bearer_token: None,
wire_api: WireApi::Responses,
query_params: None,
http_headers: None,
env_http_headers: None,
request_max_retries: Some(0),
stream_max_retries: Some(0),
stream_idle_timeout_ms: Some(1000),
requires_openai_auth: false,
};
let otel_event_manager = otel_event_manager();
let events = collect_events(&[sse1.as_bytes()], provider, otel_event_manager).await;
assert_eq!(events.len(), 2);
matches!(events[0], Ok(ResponseEvent::OutputItemDone(_)));
match &events[1] {
Err(LlmxErr::Stream(msg, _)) => {
assert_eq!(msg, "stream closed before response.completed")
}
other => panic!("unexpected second event: {other:?}"),
}
}
#[tokio::test]
async fn error_when_error_event() {
let raw_error = r#"{"type":"response.failed","sequence_number":3,"response":{"id":"resp_689bcf18d7f08194bf3440ba62fe05d803fee0cdac429894","object":"response","created_at":1755041560,"status":"failed","background":false,"error":{"code":"rate_limit_exceeded","message":"Rate limit reached for gpt-5 in organization org-AAA on tokens per min (TPM): Limit 30000, Used 22999, Requested 12528. Please try again in 11.054s. Visit https://platform.openai.com/account/rate-limits to learn more."}, "usage":null,"user":null,"metadata":{}}}"#;
let sse1 = format!("event: response.failed\ndata: {raw_error}\n\n");
let provider = ModelProviderInfo {
name: "test".to_string(),
base_url: Some("https://test.com".to_string()),
env_key: Some("TEST_API_KEY".to_string()),
env_key_instructions: None,
experimental_bearer_token: None,
wire_api: WireApi::Responses,
query_params: None,
http_headers: None,
env_http_headers: None,
request_max_retries: Some(0),
stream_max_retries: Some(0),
stream_idle_timeout_ms: Some(1000),
requires_openai_auth: false,
};
let otel_event_manager = otel_event_manager();
let events = collect_events(&[sse1.as_bytes()], provider, otel_event_manager).await;
assert_eq!(events.len(), 1);
match &events[0] {
Err(LlmxErr::Stream(msg, delay)) => {
assert_eq!(
msg,
"Rate limit reached for gpt-5 in organization org-AAA on tokens per min (TPM): Limit 30000, Used 22999, Requested 12528. Please try again in 11.054s. Visit https://platform.openai.com/account/rate-limits to learn more."
);
assert_eq!(*delay, Some(Duration::from_secs_f64(11.054)));
}
other => panic!("unexpected second event: {other:?}"),
}
}
#[tokio::test]
async fn context_window_error_is_fatal() {
let raw_error = r#"{"type":"response.failed","sequence_number":3,"response":{"id":"resp_5c66275b97b9baef1ed95550adb3b7ec13b17aafd1d2f11b","object":"response","created_at":1759510079,"status":"failed","background":false,"error":{"code":"context_length_exceeded","message":"Your input exceeds the context window of this model. Please adjust your input and try again."},"usage":null,"user":null,"metadata":{}}}"#;
let sse1 = format!("event: response.failed\ndata: {raw_error}\n\n");
let provider = ModelProviderInfo {
name: "test".to_string(),
base_url: Some("https://test.com".to_string()),
env_key: Some("TEST_API_KEY".to_string()),
env_key_instructions: None,
experimental_bearer_token: None,
wire_api: WireApi::Responses,
query_params: None,
http_headers: None,
env_http_headers: None,
request_max_retries: Some(0),
stream_max_retries: Some(0),
stream_idle_timeout_ms: Some(1000),
requires_openai_auth: false,
};
let otel_event_manager = otel_event_manager();
let events = collect_events(&[sse1.as_bytes()], provider, otel_event_manager).await;
assert_eq!(events.len(), 1);
match &events[0] {
Err(err @ LlmxErr::ContextWindowExceeded) => {
assert_eq!(err.to_string(), LlmxErr::ContextWindowExceeded.to_string());
}
other => panic!("unexpected context window event: {other:?}"),
}
}
#[tokio::test]
async fn context_window_error_with_newline_is_fatal() {
let raw_error = r#"{"type":"response.failed","sequence_number":4,"response":{"id":"resp_fatal_newline","object":"response","created_at":1759510080,"status":"failed","background":false,"error":{"code":"context_length_exceeded","message":"Your input exceeds the context window of this model. Please adjust your input and try\nagain."},"usage":null,"user":null,"metadata":{}}}"#;
let sse1 = format!("event: response.failed\ndata: {raw_error}\n\n");
let provider = ModelProviderInfo {
name: "test".to_string(),
base_url: Some("https://test.com".to_string()),
env_key: Some("TEST_API_KEY".to_string()),
env_key_instructions: None,
experimental_bearer_token: None,
wire_api: WireApi::Responses,
query_params: None,
http_headers: None,
env_http_headers: None,
request_max_retries: Some(0),
stream_max_retries: Some(0),
stream_idle_timeout_ms: Some(1000),
requires_openai_auth: false,
};
let otel_event_manager = otel_event_manager();
let events = collect_events(&[sse1.as_bytes()], provider, otel_event_manager).await;
assert_eq!(events.len(), 1);
match &events[0] {
Err(err @ LlmxErr::ContextWindowExceeded) => {
assert_eq!(err.to_string(), LlmxErr::ContextWindowExceeded.to_string());
}
other => panic!("unexpected context window event: {other:?}"),
}
}
#[tokio::test]
async fn quota_exceeded_error_is_fatal() {
let raw_error = r#"{"type":"response.failed","sequence_number":3,"response":{"id":"resp_fatal_quota","object":"response","created_at":1759771626,"status":"failed","background":false,"error":{"code":"insufficient_quota","message":"You exceeded your current quota, please check your plan and billing details. For more information on this error, read the docs: https://platform.openai.com/docs/guides/error-codes/api-errors."},"incomplete_details":null}}"#;
let sse1 = format!("event: response.failed\ndata: {raw_error}\n\n");
let provider = ModelProviderInfo {
name: "test".to_string(),
base_url: Some("https://test.com".to_string()),
env_key: Some("TEST_API_KEY".to_string()),
env_key_instructions: None,
experimental_bearer_token: None,
wire_api: WireApi::Responses,
query_params: None,
http_headers: None,
env_http_headers: None,
request_max_retries: Some(0),
stream_max_retries: Some(0),
stream_idle_timeout_ms: Some(1000),
requires_openai_auth: false,
};
let otel_event_manager = otel_event_manager();
let events = collect_events(&[sse1.as_bytes()], provider, otel_event_manager).await;
assert_eq!(events.len(), 1);
match &events[0] {
Err(err @ LlmxErr::QuotaExceeded) => {
assert_eq!(err.to_string(), LlmxErr::QuotaExceeded.to_string());
}
other => panic!("unexpected quota exceeded event: {other:?}"),
}
}
// ────────────────────────────
// Table-driven test from `main`
// ────────────────────────────
/// Verifies that the adapter produces the right `ResponseEvent` for a
/// variety of incoming `type` values.
#[tokio::test]
async fn table_driven_event_kinds() {
struct TestCase {
name: &'static str,
event: serde_json::Value,
expect_first: fn(&ResponseEvent) -> bool,
expected_len: usize,
}
fn is_created(ev: &ResponseEvent) -> bool {
matches!(ev, ResponseEvent::Created)
}
fn is_output(ev: &ResponseEvent) -> bool {
matches!(ev, ResponseEvent::OutputItemDone(_))
}
fn is_completed(ev: &ResponseEvent) -> bool {
matches!(ev, ResponseEvent::Completed { .. })
}
let completed = json!({
"type": "response.completed",
"response": {
"id": "c",
"usage": {
"input_tokens": 0,
"input_tokens_details": null,
"output_tokens": 0,
"output_tokens_details": null,
"total_tokens": 0
},
"output": []
}
});
let cases = vec![
TestCase {
name: "created",
event: json!({"type": "response.created", "response": {}}),
expect_first: is_created,
expected_len: 2,
},
TestCase {
name: "output_item.done",
event: json!({
"type": "response.output_item.done",
"item": {
"type": "message",
"role": "assistant",
"content": [
{"type": "output_text", "text": "hi"}
]
}
}),
expect_first: is_output,
expected_len: 2,
},
TestCase {
name: "unknown",
event: json!({"type": "response.new_tool_event"}),
expect_first: is_completed,
expected_len: 1,
},
];
for case in cases {
let mut evs = vec![case.event];
evs.push(completed.clone());
let provider = ModelProviderInfo {
name: "test".to_string(),
base_url: Some("https://test.com".to_string()),
env_key: Some("TEST_API_KEY".to_string()),
env_key_instructions: None,
experimental_bearer_token: None,
wire_api: WireApi::Responses,
query_params: None,
http_headers: None,
env_http_headers: None,
request_max_retries: Some(0),
stream_max_retries: Some(0),
stream_idle_timeout_ms: Some(1000),
requires_openai_auth: false,
};
let otel_event_manager = otel_event_manager();
let out = run_sse(evs, provider, otel_event_manager).await;
assert_eq!(out.len(), case.expected_len, "case {}", case.name);
assert!(
(case.expect_first)(&out[0]),
"first event mismatch in case {}",
case.name
);
}
}
#[test]
fn test_try_parse_retry_after() {
let err = Error {
r#type: None,
message: Some("Rate limit reached for gpt-5 in organization org- on tokens per min (TPM): Limit 1, Used 1, Requested 19304. Please try again in 28ms. Visit https://platform.openai.com/account/rate-limits to learn more.".to_string()),
code: Some("rate_limit_exceeded".to_string()),
plan_type: None,
resets_at: None
};
let delay = try_parse_retry_after(&err);
assert_eq!(delay, Some(Duration::from_millis(28)));
}
#[test]
fn test_try_parse_retry_after_no_delay() {
let err = Error {
r#type: None,
message: Some("Rate limit reached for gpt-5 in organization <ORG> on tokens per min (TPM): Limit 30000, Used 6899, Requested 24050. Please try again in 1.898s. Visit https://platform.openai.com/account/rate-limits to learn more.".to_string()),
code: Some("rate_limit_exceeded".to_string()),
plan_type: None,
resets_at: None
};
let delay = try_parse_retry_after(&err);
assert_eq!(delay, Some(Duration::from_secs_f64(1.898)));
}
#[test]
fn test_try_parse_retry_after_azure() {
let err = Error {
r#type: None,
message: Some("Rate limit exceeded. Try again in 35 seconds.".to_string()),
code: Some("rate_limit_exceeded".to_string()),
plan_type: None,
resets_at: None,
};
let delay = try_parse_retry_after(&err);
assert_eq!(delay, Some(Duration::from_secs(35)));
}
#[test]
fn error_response_deserializes_schema_known_plan_type_and_serializes_back() {
use crate::token_data::KnownPlan;
use crate::token_data::PlanType;
let json =
r#"{"error":{"type":"usage_limit_reached","plan_type":"pro","resets_at":1704067200}}"#;
let resp: ErrorResponse = serde_json::from_str(json).expect("should deserialize schema");
assert_matches!(resp.error.plan_type, Some(PlanType::Known(KnownPlan::Pro)));
let plan_json = serde_json::to_string(&resp.error.plan_type).expect("serialize plan_type");
assert_eq!(plan_json, "\"pro\"");
}
#[test]
fn error_response_deserializes_schema_unknown_plan_type_and_serializes_back() {
use crate::token_data::PlanType;
let json =
r#"{"error":{"type":"usage_limit_reached","plan_type":"vip","resets_at":1704067260}}"#;
let resp: ErrorResponse = serde_json::from_str(json).expect("should deserialize schema");
assert_matches!(resp.error.plan_type, Some(PlanType::Unknown(ref s)) if s == "vip");
let plan_json = serde_json::to_string(&resp.error.plan_type).expect("serialize plan_type");
assert_eq!(plan_json, "\"vip\"");
}
}