fix(usage): handle terminal stream failures and preserve usage updates

This commit is contained in:
zhefox
2026-05-21 15:52:51 +08:00
parent be6e49b9c2
commit 12abde2aeb
14 changed files with 892 additions and 35 deletions

View File

@@ -1180,6 +1180,23 @@ impl OpenAIResponsesProviderState {
}
}
}
event_type if openai_stream_payload_is_terminal_error(&value) => {
self.finished = true;
let mut payload = value.clone();
if event_type != "response.failed"
&& event_type != "response.incomplete"
&& event_type != "error"
{
payload = openai_stream_terminal_error_body(&value).unwrap_or(payload);
if let Some(object) = payload.as_object_mut() {
object.insert(
"type".to_string(),
Value::String("response.failed".to_string()),
);
}
}
out.push(self.unknown_frame(report_context, payload));
}
"response.completed" => {
let Some(response) = value.get("response").and_then(Value::as_object) else {
return Ok(out);
@@ -1559,6 +1576,13 @@ impl OpenAIChatClientEmitter {
)?);
Ok(out)
}
CanonicalStreamEvent::UnknownEvent(payload)
if openai_stream_terminal_error_body(&payload).is_some() =>
{
self.finished = true;
let error_body = openai_stream_terminal_error_body(&payload).unwrap_or(payload);
encode_json_sse(None, &error_body)
}
CanonicalStreamEvent::UnknownEvent(_) => Ok(Vec::new()),
CanonicalStreamEvent::Finish {
finish_reason,
@@ -2456,6 +2480,29 @@ impl OpenAIResponsesClientEmitter {
}
Ok(out)
}
CanonicalStreamEvent::UnknownEvent(payload)
if openai_stream_terminal_error_body(&payload).is_some() =>
{
self.finished = true;
let raw_event = payload.get("type").and_then(Value::as_str);
let event = raw_event
.filter(|event| {
matches!(*event, "response.failed" | "response.incomplete" | "error")
})
.unwrap_or("response.failed")
.to_string();
let mut payload = if raw_event == Some(event.as_str()) {
payload
} else {
openai_stream_terminal_error_body(&payload).unwrap_or(payload)
};
if payload.get("type").is_none() {
if let Some(object) = payload.as_object_mut() {
object.insert("type".to_string(), Value::String(event.clone()));
}
}
self.encode_response_event(event.as_str(), payload)
}
CanonicalStreamEvent::UnknownEvent(_) => Ok(Vec::new()),
CanonicalStreamEvent::Finish { usage, .. } => {
if self.finished {
@@ -2682,6 +2729,40 @@ mod tests {
)));
}
#[test]
fn openai_responses_provider_state_treats_failed_event_as_terminal() {
let mut state = OpenAIResponsesProviderState::default();
let report_context = json!({});
let frames = state
.push_line(
&report_context,
data_line(json!({
"type": "response.failed",
"response": {
"id": "resp_failed_123",
"model": "gpt-5.4",
"status": "failed",
"error": {
"message": "policy failure",
"type": "invalid_request_error",
"code": "cyber_policy"
}
}
})),
)
.expect("failed response event should parse");
assert!(frames.iter().any(|frame| matches!(
frame.event,
CanonicalStreamEvent::UnknownEvent(ref payload)
if payload.get("type").and_then(Value::as_str) == Some("response.failed")
)));
assert!(state
.finish(&report_context)
.expect("terminal failure should not synthesize completion")
.is_empty());
}
#[test]
fn openai_usage_derives_missing_input_tokens_from_total() {
let usage = canonical_usage_from_openai_usage(Some(&json!({
@@ -2848,6 +2929,41 @@ mod tests {
assert_eq!(response_sequence_numbers(&sse), (1..=9).collect::<Vec<_>>());
}
#[test]
fn openai_responses_client_emitter_forwards_failed_unknown_event() {
let mut emitter = OpenAIResponsesClientEmitter::default();
let bytes = emitter
.emit(CanonicalStreamFrame {
id: "resp_failed_123".to_string(),
model: "gpt-5.4".to_string(),
event: CanonicalStreamEvent::UnknownEvent(json!({
"type": "response.failed",
"response": {
"id": "resp_failed_123",
"model": "gpt-5.4",
"status": "failed",
"error": {
"message": "policy failure",
"type": "invalid_request_error",
"code": "cyber_policy"
}
}
})),
})
.expect("failed response event should encode");
let mut all = bytes;
all.extend(
emitter
.finish()
.expect("failed stream should not synthesize completion"),
);
let sse = String::from_utf8(all).expect("sse should be utf8");
assert!(sse.contains("event: response.failed\n"));
assert!(sse.contains("\"message\":\"policy failure\""));
assert!(!sse.contains("event: response.completed\n"));
}
#[test]
fn openai_responses_client_emitter_keeps_text_item_id_stable_after_text_started() {
let mut emitter = OpenAIResponsesClientEmitter::default();

View File

@@ -239,6 +239,224 @@ fn extract_codex_prompt_cache_session_seed(provider_request_body: &Value) -> Opt
.or_else(|| object.get("metadata").and_then(session_seed_from_metadata))
}
fn sha256_hex(input: &[u8]) -> String {
let digest = Sha256::digest(input);
let mut output = String::with_capacity(digest.len() * 2);
for byte in digest {
let _ = write!(&mut output, "{byte:02x}");
}
output
}
fn stable_json_digest(value: &Value) -> Option<String> {
serde_json::to_vec(value)
.ok()
.map(|serialized| sha256_hex(&serialized))
}
fn compact_prompt_cache_text(value: &str) -> Option<Value> {
const MAX_PROMPT_CACHE_TEXT_CHARS: usize = 4096;
let normalized = value.trim();
if normalized.is_empty() {
return None;
}
let mut text = normalized
.chars()
.take(MAX_PROMPT_CACHE_TEXT_CHARS)
.collect::<String>();
if normalized.chars().count() > MAX_PROMPT_CACHE_TEXT_CHARS {
text.push_str("...");
}
Some(Value::String(text))
}
fn compact_prompt_cache_anchor(value: &Value) -> Value {
match value {
Value::String(text) => compact_prompt_cache_text(text).unwrap_or(Value::Null),
Value::Array(items) => Value::Array(
items
.iter()
.take(16)
.map(compact_prompt_cache_anchor)
.filter(|value| !value.is_null())
.collect(),
),
Value::Object(object) => {
let mut compacted = serde_json::Map::new();
for key in [
"type",
"role",
"id",
"name",
"description",
"text",
"input_text",
"output_text",
"content",
"call_id",
"arguments",
"output",
"parameters",
"strict",
"function",
"effort",
"summary",
] {
let Some(value) = object.get(key) else {
continue;
};
let value = compact_prompt_cache_anchor(value);
if !value.is_null() {
compacted.insert(key.to_string(), value);
}
}
Value::Object(compacted)
}
Value::Null | Value::Bool(_) | Value::Number(_) => value.clone(),
}
}
fn compact_prompt_cache_json_anchor(value: &Value) -> Value {
match value {
Value::String(text) => compact_prompt_cache_text(text).unwrap_or(Value::Null),
Value::Array(items) => Value::Array(
items
.iter()
.take(16)
.map(compact_prompt_cache_json_anchor)
.filter(|value| !value.is_null())
.collect(),
),
Value::Object(object) => {
let mut compacted = serde_json::Map::new();
let mut keys = object.keys().collect::<Vec<_>>();
keys.sort();
for key in keys {
if key == "cache_control" {
continue;
}
let Some(value) = object.get(key) else {
continue;
};
let value = compact_prompt_cache_json_anchor(value);
if !value.is_null() {
compacted.insert(key.clone(), value);
}
}
Value::Object(compacted)
}
Value::Null | Value::Bool(_) | Value::Number(_) => value.clone(),
}
}
fn collect_codex_prompt_cache_control_anchors(value: &Value, anchors: &mut Vec<Value>) {
const MAX_PROMPT_CACHE_CONTROL_ANCHORS: usize = 16;
if anchors.len() >= MAX_PROMPT_CACHE_CONTROL_ANCHORS {
return;
}
match value {
Value::Object(object) => {
if object.contains_key("cache_control") {
let mut anchor = object.clone();
anchor.remove("cache_control");
let anchor = compact_prompt_cache_anchor(&Value::Object(anchor));
if !anchor.is_null() {
anchors.push(anchor);
}
}
for child in object.values() {
if anchors.len() >= MAX_PROMPT_CACHE_CONTROL_ANCHORS {
break;
}
collect_codex_prompt_cache_control_anchors(child, anchors);
}
}
Value::Array(items) => {
for child in items {
if anchors.len() >= MAX_PROMPT_CACHE_CONTROL_ANCHORS {
break;
}
collect_codex_prompt_cache_control_anchors(child, anchors);
}
}
_ => {}
}
}
fn extract_codex_prompt_cache_control_seed(provider_request_body: &Value) -> Option<String> {
let mut anchors = Vec::new();
collect_codex_prompt_cache_control_anchors(provider_request_body, &mut anchors);
if anchors.is_empty() {
return None;
}
let seed = json!({
"model": provider_request_body.get("model"),
"anchors": anchors,
});
stable_json_digest(&seed).map(|digest| format!("cache_control:{digest}"))
}
fn first_responses_input_anchor(input: &Value) -> Option<Value> {
let items = input.as_array()?;
let first_user_message = items.iter().find(|item| {
item.get("type")
.and_then(Value::as_str)
.is_some_and(|value| value == "message")
&& item
.get("role")
.and_then(Value::as_str)
.is_some_and(|value| value == "user")
});
let first_item = first_user_message.or_else(|| items.first())?;
let anchor = compact_prompt_cache_anchor(first_item);
(!anchor.is_null()).then_some(anchor)
}
fn extract_codex_stable_request_prompt_cache_seed(
provider_request_body: &Value,
user_api_key_id: Option<&str>,
) -> Option<String> {
let object = provider_request_body.as_object()?;
let mut seed = serde_json::Map::new();
for key in [
"model",
"instructions",
"reasoning",
"tools",
"tool_choice",
"parallel_tool_calls",
] {
if let Some(value) = object.get(key).filter(|value| !value.is_null()) {
let value = if key == "tools" {
compact_prompt_cache_json_anchor(value)
} else {
compact_prompt_cache_anchor(value)
};
seed.insert(key.to_string(), value);
}
}
if let Some(input_anchor) = object.get("input").and_then(first_responses_input_anchor) {
seed.insert("first_input".to_string(), input_anchor);
}
if let Some(user_api_key_id) = user_api_key_id
.map(str::trim)
.filter(|value| !value.is_empty())
{
seed.insert(
"api_key_id".to_string(),
Value::String(user_api_key_id.to_string()),
);
}
if seed.len() < 2 {
return None;
}
stable_json_digest(&Value::Object(seed)).map(|digest| format!("stable_request:{digest}"))
}
fn build_short_codex_header_id(seed: &str) -> Option<String> {
let normalized = seed.trim();
if normalized.is_empty() {
@@ -335,6 +553,14 @@ fn maybe_inject_codex_prompt_cache_key(
let prompt_cache_key = extract_codex_prompt_cache_session_seed(provider_request_body)
.and_then(|seed| build_stable_codex_prompt_cache_key_from_seed("session", &seed))
.or_else(|| {
extract_codex_prompt_cache_control_seed(provider_request_body)
.and_then(|seed| build_stable_codex_prompt_cache_key_from_seed("anchor", &seed))
})
.or_else(|| {
extract_codex_stable_request_prompt_cache_seed(provider_request_body, user_api_key_id)
.and_then(|seed| build_stable_codex_prompt_cache_key_from_seed("request", &seed))
})
.or_else(|| user_api_key_id.and_then(build_stable_codex_prompt_cache_key));
let Some(prompt_cache_key) = prompt_cache_key else {
return;
@@ -854,6 +1080,157 @@ mod tests {
assert!(body_c.get("metadata").is_none());
}
#[test]
fn codex_responses_body_edits_derive_prompt_cache_key_from_cache_control_anchor() {
let mut body_a = json!({
"input": [{
"type": "message",
"role": "user",
"content": [{
"type": "input_text",
"text": "stable project brief",
"cache_control": {"type": "ephemeral"}
}]
}, {
"type": "message",
"role": "user",
"content": [{"type": "input_text", "text": "new turn A"}]
}],
"model": "gpt-5.4"
});
let mut body_b = json!({
"input": [{
"type": "message",
"role": "user",
"content": [{
"type": "input_text",
"text": "stable project brief",
"cache_control": {"type": "ephemeral"}
}]
}, {
"type": "message",
"role": "user",
"content": [{"type": "input_text", "text": "new turn B"}]
}],
"model": "gpt-5.4"
});
let mut body_c = json!({
"input": [{
"type": "message",
"role": "user",
"content": [{
"type": "input_text",
"text": "different project brief",
"cache_control": {"type": "ephemeral"}
}]
}],
"model": "gpt-5.4"
});
apply_codex_openai_responses_special_body_edits(
&mut body_a,
"codex",
"openai:responses",
None,
Some("key-a"),
);
apply_codex_openai_responses_special_body_edits(
&mut body_b,
"codex",
"openai:responses",
None,
Some("key-b"),
);
apply_codex_openai_responses_special_body_edits(
&mut body_c,
"codex",
"openai:responses",
None,
Some("key-a"),
);
assert_eq!(body_a["prompt_cache_key"], body_b["prompt_cache_key"]);
assert_ne!(body_a["prompt_cache_key"], body_c["prompt_cache_key"]);
}
#[test]
fn codex_responses_body_edits_derive_prompt_cache_key_from_stable_request_anchor() {
let mut body_a = json!({
"input": [{
"type": "message",
"role": "user",
"content": [{"type": "input_text", "text": "open workspace"}]
}, {
"type": "message",
"role": "user",
"content": [{"type": "input_text", "text": "new turn A"}]
}],
"model": "gpt-5.4",
"instructions": "Be concise.",
"tools": [{
"type": "function",
"name": "shell",
"parameters": {"type": "object", "properties": {}}
}],
"reasoning": {"effort": "medium"}
});
let mut body_b = json!({
"input": [{
"type": "message",
"role": "user",
"content": [{"type": "input_text", "text": "open workspace"}]
}, {
"type": "message",
"role": "user",
"content": [{"type": "input_text", "text": "new turn B"}]
}],
"model": "gpt-5.4",
"instructions": "Be concise.",
"tools": [{
"type": "function",
"name": "shell",
"parameters": {"type": "object", "properties": {}}
}],
"reasoning": {"effort": "medium"}
});
let mut body_c = json!({
"input": [{
"type": "message",
"role": "user",
"content": [{"type": "input_text", "text": "open another workspace"}]
}],
"model": "gpt-5.4",
"instructions": "Be concise.",
"tools": [{"type": "function", "name": "shell"}],
"reasoning": {"effort": "medium"}
});
apply_codex_openai_responses_special_body_edits(
&mut body_a,
"codex",
"openai:responses",
None,
Some("key-a"),
);
apply_codex_openai_responses_special_body_edits(
&mut body_b,
"codex",
"openai:responses",
None,
Some("key-a"),
);
apply_codex_openai_responses_special_body_edits(
&mut body_c,
"codex",
"openai:responses",
None,
Some("key-a"),
);
assert_eq!(body_a["prompt_cache_key"], body_b["prompt_cache_key"]);
assert_ne!(body_a["prompt_cache_key"], body_c["prompt_cache_key"]);
}
#[test]
fn compact_body_edits_strip_include_store_and_stream() {
let mut provider_request_body = json!({

View File

@@ -108,6 +108,107 @@ pub fn canonical_usage_from_openai_usage(value: Option<&Value>) -> Option<Canoni
})
}
pub fn openai_stream_payload_is_terminal_error(payload: &Value) -> bool {
let event_type = payload
.get("type")
.and_then(Value::as_str)
.unwrap_or_default();
if payload.get("error").is_some() {
return true;
}
if matches!(
event_type,
"error" | "response.failed" | "response.incomplete"
) {
return true;
}
payload
.get("response")
.and_then(Value::as_object)
.and_then(|response| response.get("status"))
.and_then(Value::as_str)
.is_some_and(|status| matches!(status, "failed" | "incomplete"))
}
pub fn openai_stream_terminal_error_body(payload: &Value) -> Option<Value> {
if !openai_stream_payload_is_terminal_error(payload) {
return None;
}
let event_type = payload
.get("type")
.and_then(Value::as_str)
.unwrap_or_default();
let response = payload.get("response").and_then(Value::as_object);
let status = response
.and_then(|response| response.get("status"))
.and_then(Value::as_str);
let raw_error = response
.and_then(|response| response.get("error"))
.or_else(|| payload.get("error"));
let mut error = raw_error
.and_then(Value::as_object)
.cloned()
.unwrap_or_default();
let message = error
.get("message")
.and_then(Value::as_str)
.map(ToOwned::to_owned)
.or_else(|| raw_error.and_then(Value::as_str).map(ToOwned::to_owned))
.or_else(|| {
payload
.get("message")
.and_then(Value::as_str)
.map(ToOwned::to_owned)
})
.or_else(|| {
response
.and_then(|response| response.get("incomplete_details"))
.and_then(|details| details.get("reason"))
.and_then(Value::as_str)
.map(|reason| format!("Response incomplete: {reason}"))
})
.or_else(|| status.map(|status| format!("Response ended with status {status}")))
.unwrap_or_else(|| "Upstream stream ended with an error".to_string());
error
.entry("message".to_string())
.or_insert_with(|| Value::String(message));
error.entry("type".to_string()).or_insert_with(|| {
if event_type == "response.incomplete" || status == Some("incomplete") {
Value::String("incomplete".to_string())
} else {
Value::String("server_error".to_string())
}
});
if !error.contains_key("code") {
if let Some(reason) = response
.and_then(|response| response.get("incomplete_details"))
.and_then(|details| details.get("reason"))
.and_then(Value::as_str)
{
error.insert("code".to_string(), Value::String(reason.to_string()));
}
}
Some(json!({ "error": Value::Object(error) }))
}
pub fn openai_stream_terminal_error_message(payload: &Value) -> Option<String> {
openai_stream_terminal_error_body(payload)
.and_then(|body| body.get("error").cloned())
.and_then(|error| {
error
.get("message")
.and_then(Value::as_str)
.map(ToOwned::to_owned)
})
}
pub fn canonical_usage_from_claude_usage(value: Option<&Value>) -> Option<CanonicalUsage> {
let usage = value?.as_object()?;
let input_tokens = usage

View File

@@ -14,7 +14,8 @@ use crate::formats::shared::error_body::{
};
use crate::formats::shared::sse::encode_json_sse;
use crate::formats::shared::stream_core::common::{
decode_json_data_line, CanonicalStreamEvent, CanonicalStreamFrame, CanonicalUsage,
decode_json_data_line, openai_stream_terminal_error_body, openai_stream_terminal_error_message,
CanonicalStreamEvent, CanonicalStreamFrame, CanonicalUsage,
};
use crate::formats::shared::AiSurfaceFinalizeError;
@@ -197,6 +198,14 @@ impl StreamingStandardTerminalObserver {
summary.model = Some(model);
}
match event {
CanonicalStreamEvent::UnknownEvent(payload)
if openai_stream_terminal_error_body(&payload).is_some() =>
{
summary.unknown_event_count = summary.unknown_event_count.saturating_add(1);
summary.observed_finish = true;
summary.finish_reason = Some("error".to_string());
summary.parser_error = openai_stream_terminal_error_message(&payload);
}
CanonicalStreamEvent::UnknownEvent(_) => {
summary.unknown_event_count = summary.unknown_event_count.saturating_add(1);
}
@@ -410,7 +419,8 @@ fn parse_provider_error(
}
fn parse_openai_error(payload: &Value) -> Option<(String, Option<String>, LocalCoreSyncErrorKind)> {
let error = payload.get("error")?.as_object()?;
let error_body = openai_stream_terminal_error_body(payload)?;
let error = error_body.get("error")?.as_object()?;
let message = error.get("message").and_then(Value::as_str)?.to_string();
let code = error
.get("code")
@@ -973,6 +983,41 @@ mod tests {
assert!(!summary.observed_finish);
}
#[test]
fn terminal_observer_marks_openai_responses_failed_event_as_terminal_error() {
let mut report_context = report_context("openai:chat", "openai:responses");
report_context["provider_stream_event_api_format"] = json!("openai:responses");
let mut observer = StreamingStandardTerminalObserver::default();
observer
.push_line(
&report_context,
data_line(json!({
"type": "response.failed",
"response": {
"id": "resp_failed_123",
"model": "gpt-5.4",
"status": "failed",
"error": {
"message": "policy failure",
"type": "invalid_request_error",
"code": "cyber_policy"
}
}
})),
)
.expect("failed event should be observed");
let summary = observer
.latest_summary()
.cloned()
.expect("summary should exist");
assert!(summary.observed_finish);
assert_eq!(summary.finish_reason.as_deref(), Some("error"));
assert_eq!(summary.parser_error.as_deref(), Some("policy failure"));
assert_eq!(summary.unknown_event_count, 1);
}
#[test]
fn terminal_observer_tracks_openai_image_stream_usage() {
let mut report_context = report_context("openai:image", "openai:chat");