Merge PR #669: align GPT-5.6 and Codex request protocols

This commit is contained in:
elky
2026-07-12 21:50:20 +08:00
313 changed files with 29823 additions and 5178 deletions
@@ -104,6 +104,7 @@ fn is_known_admin_monitoring_api_format(value: &str) -> bool {
"openai:chat"
| "openai:responses"
| "openai:responses:compact"
| "openai:search"
| "openai:image"
| "openai:video"
| "openai:embedding"
@@ -492,6 +493,20 @@ mod tests {
);
}
#[test]
fn parses_v2_scheduler_affinity_key_for_openai_search() {
let parsed = parse_admin_monitoring_scheduler_affinity_key(
"scheduler_affinity:v2:user-key-1:openai:search:gpt-5.6-sol:codex:sessionhash",
)
.expect("Search scheduler key should parse");
assert_eq!(parsed.affinity_key, "user-key-1");
assert_eq!(parsed.api_format, "openai:search");
assert_eq!(parsed.model_name, "gpt-5.6-sol");
assert_eq!(parsed.client_family.as_deref(), Some("codex"));
assert_eq!(parsed.session_hash.as_deref(), Some("sessionhash"));
}
#[test]
fn parses_v2_scheduler_affinity_key_with_three_segment_api_format() {
let parsed = parse_admin_monitoring_scheduler_affinity_key(
@@ -6,7 +6,8 @@ use crate::handlers::admin::provider::shared::payloads::{
AdminProviderCreateRequest, AdminProviderUpdatePatch,
};
use crate::handlers::admin::provider::write::provider::{
reconcile_admin_fixed_provider_template_endpoints, reconcile_admin_fixed_provider_template_keys,
reconcile_admin_fixed_provider_template_endpoints,
reconcile_admin_fixed_provider_template_endpoints_after_update,
};
use crate::handlers::admin::request::{AdminAppState, AdminRequestContext};
use crate::handlers::admin::shared::attach_admin_audit_response;
@@ -80,7 +81,6 @@ pub(crate) async fn maybe_build_local_admin_provider_writes_response(
.is_some()
{
reconcile_admin_fixed_provider_template_endpoints(state, &created_provider).await?;
reconcile_admin_fixed_provider_template_keys(state, &created_provider).await?;
}
return Ok(Some(attach_admin_audit_response(
Json(json!({
@@ -161,8 +161,12 @@ pub(crate) async fn maybe_build_local_admin_provider_writes_response(
.fixed_provider_template(&updated_record.provider_type)
.is_some()
{
reconcile_admin_fixed_provider_template_endpoints(state, &updated_record).await?;
reconcile_admin_fixed_provider_template_keys(state, &updated_record).await?;
reconcile_admin_fixed_provider_template_endpoints_after_update(
state,
&existing_provider,
&updated_record,
)
.await?;
}
return Ok(Some(
match state
@@ -64,7 +64,8 @@ use aether_data_contracts::repository::provider_catalog::{
};
use aether_model_fetch::{
aggregate_models_for_cache, fetch_models_from_transports, json_string_list,
merge_upstream_metadata, preset_models_for_provider, selected_models_fetch_endpoints,
model_catalog_upstream_metadata, preset_models_for_provider, selected_models_fetch_endpoints,
upstream_metadata_namespace_updates,
};
use axum::{
body::{to_bytes, Body},
@@ -281,6 +282,7 @@ fn provider_query_attach_model_test_capabilities(
fn provider_query_codex_preset_fallback(
provider: &StoredProviderCatalogProvider,
fetch_error: &str,
) -> Option<ProviderQueryKeyFetchResult> {
if !provider.provider_type.trim().eq_ignore_ascii_case("codex") {
return None;
@@ -289,12 +291,59 @@ fn provider_query_codex_preset_fallback(
Some(ProviderQueryKeyFetchResult {
models: aggregate_models_for_cache(&models),
error: None,
warning: None,
warning: Some(format!(
"Codex 动态模型目录不可用,已使用内置模型卡:{fetch_error}"
)),
from_cache: false,
has_success: true,
})
}
async fn provider_query_persist_preset_models(
state: &AdminAppState<'_>,
provider: &StoredProviderCatalogProvider,
key: &StoredProviderCatalogKey,
models: &[Value],
) -> Result<(), GatewayError> {
if models.is_empty() {
return Ok(());
}
<AppState as ModelFetchRuntimeState>::write_upstream_models_cache(
state.app(),
&provider.id,
&key.id,
models,
)
.await;
if let Some(catalog_metadata) = model_catalog_upstream_metadata(&provider.provider_type, models)
{
provider_query_persist_upstream_metadata(state, key, &catalog_metadata).await?;
}
Ok(())
}
async fn provider_query_persist_upstream_metadata(
state: &AdminAppState<'_>,
key: &StoredProviderCatalogKey,
upstream_metadata: &Value,
) -> Result<(), GatewayError> {
let updated_at = current_unix_secs();
for (namespace, value) in
upstream_metadata_namespace_updates(key.upstream_metadata.as_ref(), upstream_metadata)
{
state
.app()
.upsert_provider_catalog_key_upstream_metadata_namespace(
&key.id,
&namespace,
&value,
Some(updated_at),
)
.await?;
}
Ok(())
}
mod model_test;
pub(crate) use self::model_test::{
@@ -439,11 +488,9 @@ async fn provider_query_fetch_models_for_key(
let selected_endpoints = selected_models_fetch_endpoints(endpoints, key);
if selected_endpoints.is_empty() {
if let Some(models) = preset_models_for_provider(&provider.provider_type) {
let models = provider_query_filter_models_for_key(
provider,
key,
aggregate_models_for_cache(&models),
);
let models = aggregate_models_for_cache(&models);
provider_query_persist_preset_models(state, provider, key, &models).await?;
let models = provider_query_filter_models_for_key(provider, key, models);
return Ok(ProviderQueryKeyFetchResult {
models,
error: None,
@@ -492,7 +539,11 @@ async fn provider_query_fetch_models_for_key(
Ok(outcome) => outcome,
Err(err) => {
all_errors.push(err);
if let Some(fallback) = provider_query_codex_preset_fallback(provider) {
if let Some(fallback) =
provider_query_codex_preset_fallback(provider, &all_errors.join("; "))
{
provider_query_persist_preset_models(state, provider, key, &fallback.models)
.await?;
return Ok(fallback);
}
return Ok(ProviderQueryKeyFetchResult {
@@ -517,20 +568,14 @@ async fn provider_query_fetch_models_for_key(
.await;
}
if let Some(upstream_metadata) = outcome.upstream_metadata.as_ref() {
let merged_metadata =
merge_upstream_metadata(key.upstream_metadata.as_ref(), upstream_metadata);
state
.app()
.update_provider_catalog_key_upstream_metadata(
&key.id,
Some(&merged_metadata),
Some(current_unix_secs()),
)
.await?;
provider_query_persist_upstream_metadata(state, key, upstream_metadata).await?;
}
if unique_models.is_empty() && !all_errors.is_empty() {
if let Some(fallback) = provider_query_codex_preset_fallback(provider) {
if let Some(fallback) =
provider_query_codex_preset_fallback(provider, &all_errors.join("; "))
{
provider_query_persist_preset_models(state, provider, key, &fallback.models).await?;
return Ok(fallback);
}
}
@@ -29,10 +29,7 @@ use crate::handlers::shared::{
provider_key_status_snapshot_payload,
};
use crate::model_fetch::ModelFetchRuntimeState;
use crate::provider_key_auth::{
provider_key_auth_semantics, provider_key_configured_api_formats,
provider_key_inherits_provider_api_formats,
};
use crate::provider_key_auth::provider_key_auth_semantics;
use crate::provider_transport::antigravity::{
build_antigravity_safe_v1internal_request, build_antigravity_static_identity_headers,
classify_local_antigravity_request_support, AntigravityEnvelopeRequestType,
@@ -543,6 +540,22 @@ fn provider_query_build_test_request_body_for_api_format(
model: &str,
route_path: &str,
client_api_format: &str,
) -> Value {
provider_query_build_test_request_body_for_api_format_with_search_session(
payload,
model,
route_path,
client_api_format,
None,
)
}
fn provider_query_build_test_request_body_for_api_format_with_search_session(
payload: &Value,
model: &str,
route_path: &str,
client_api_format: &str,
search_session_id: Option<&str>,
) -> Value {
let client_api_format = provider_query_normalize_api_format_alias(client_api_format);
let override_custom_model = route_path.ends_with("/test-model-failover")
@@ -568,7 +581,7 @@ fn provider_query_build_test_request_body_for_api_format(
);
} else if matches!(
client_api_format.as_str(),
"openai:responses" | "openai:responses:compact"
"openai:responses" | "openai:responses:compact" | "openai:search"
) && !value_has_non_empty_text(object.get("input"))
{
if let Some(prompt) = object
@@ -580,7 +593,7 @@ fn provider_query_build_test_request_body_for_api_format(
}
if matches!(
client_api_format.as_str(),
"openai:responses" | "openai:responses:compact"
"openai:responses" | "openai:responses:compact" | "openai:search"
) && value_has_non_empty_text(object.get("input"))
{
object.remove("prompt");
@@ -590,6 +603,9 @@ fn provider_query_build_test_request_body_for_api_format(
{
object.remove("messages");
}
if client_api_format == "openai:search" {
provider_query_ensure_search_test_fields(object, payload, search_session_id);
}
}
return body;
}
@@ -620,6 +636,15 @@ fn provider_query_build_test_request_body_for_api_format(
"temperature": 0.7,
"stream": true,
}),
"openai:search" => json!({
"id": provider_query_search_test_session_id(search_session_id),
"model": model,
"input": message,
"commands": {
"search_query": [{"q": message}]
},
"max_output_tokens": 256,
}),
"claude:messages" => json!({
"model": model,
"messages": [{
@@ -680,7 +705,7 @@ fn provider_query_insert_default_test_conversation(
.entry("top_n".to_string())
.or_insert_with(|| Value::from(4_u64));
}
"openai:responses" | "openai:responses:compact" => {
"openai:responses" | "openai:responses:compact" | "openai:search" => {
object.insert("input".to_string(), Value::String(message));
}
"claude:messages" => {
@@ -698,6 +723,48 @@ fn provider_query_insert_default_test_conversation(
}
}
fn provider_query_search_test_session_id(search_session_id: Option<&str>) -> String {
search_session_id
.map(str::trim)
.filter(|value| !value.is_empty())
.map(|value| format!("aether-model-test-{value}"))
.unwrap_or_else(|| format!("aether-model-test-{}", Uuid::new_v4().simple()))
}
fn provider_query_ensure_search_test_fields(
object: &mut Map<String, Value>,
payload: &Value,
search_session_id: Option<&str>,
) {
let query = object
.get("input")
.and_then(Value::as_str)
.map(str::trim)
.filter(|value| !value.is_empty())
.map(ToOwned::to_owned)
.or_else(|| provider_query_extract_message(payload))
.unwrap_or_else(|| DEFAULT_PROVIDER_QUERY_TEST_MESSAGE.to_string());
let has_session_id = object
.get("id")
.and_then(Value::as_str)
.is_some_and(|value| !value.trim().is_empty());
if !has_session_id {
object.insert(
"id".to_string(),
provider_query_search_test_session_id(search_session_id).into(),
);
}
object
.entry("input".to_string())
.or_insert_with(|| Value::String(query.clone()));
object
.entry("commands".to_string())
.or_insert_with(|| json!({"search_query": [{"q": query}]}));
object
.entry("max_output_tokens".to_string())
.or_insert_with(|| Value::from(256_u64));
}
fn provider_query_grok_test_client_api_format(provider_api_format: &str) -> &'static str {
match provider_query_normalize_api_format_alias(provider_api_format).as_str() {
"openai:responses" | "openai:responses:compact" => "openai:responses",
@@ -767,7 +834,7 @@ fn provider_query_request_body_has_conversation_for_api_format(
client_api_format: &str,
) -> bool {
match provider_query_normalize_api_format_alias(client_api_format).as_str() {
"openai:responses" | "openai:responses:compact" => {
"openai:responses" | "openai:responses:compact" | "openai:search" => {
value_has_non_empty_text(body.get("input"))
|| value_has_non_empty_text(body.get("prompt"))
}
@@ -828,14 +895,12 @@ fn provider_query_resolve_standard_test_upstream_is_stream(
provider_type: &str,
provider_api_format: &str,
) -> bool {
let hard_requires_streaming = crate::ai_serving::force_upstream_streaming_for_provider(
crate::ai_serving::resolve_upstream_is_stream_for_provider(
endpoint_config,
provider_type,
provider_api_format,
);
crate::ai_serving::resolve_upstream_is_stream_from_endpoint_config(
endpoint_config,
false,
hard_requires_streaming,
false,
)
}
@@ -876,15 +941,11 @@ fn provider_query_key_supports_endpoint(
provider_type: &str,
endpoint_api_format: &str,
) -> bool {
if provider_key_inherits_provider_api_formats(key, provider_type) {
return true;
}
let formats = provider_key_configured_api_formats(key);
let endpoint_api_format = provider_query_normalize_api_format_alias(endpoint_api_format);
formats.is_empty()
|| formats
.iter()
.any(|value| provider_query_normalize_api_format_alias(value) == endpoint_api_format)
crate::handlers::shared::provider_catalog_key_supports_format(
key,
provider_type,
endpoint_api_format,
)
}
async fn provider_query_select_preferred_non_kiro_endpoint(
@@ -1626,6 +1687,15 @@ fn provider_query_standard_execution_response_body(
{
return None;
}
if result.status_code < 400
&& provider_query_normalize_api_format_alias(provider_api_format) == "openai:search"
&& !body
.get("output")
.and_then(Value::as_str)
.is_some_and(|value| !value.trim().is_empty())
{
return None;
}
Some(body)
}
@@ -2104,8 +2174,18 @@ async fn provider_query_execute_openai_image_test_candidate(
route_path,
);
let incoming_request_headers = provider_query_extract_request_headers(payload);
let image_request_path = if request_body.get("image").is_some()
|| request_body
.get("images")
.and_then(Value::as_array)
.is_some_and(|images| !images.is_empty())
{
"/v1/images/edits"
} else {
"/v1/images/generations"
};
let mut synthetic_request = http::Request::builder()
.uri("/v1/images/generations")
.uri(image_request_path)
.body(())
.map_err(|err| GatewayError::Internal(err.to_string()))?;
*synthetic_request.headers_mut() = incoming_request_headers;
@@ -2116,11 +2196,18 @@ async fn provider_query_execute_openai_image_test_candidate(
&parts,
&request_body,
None,
provider_query_openai_image_normalize_options(provider_type),
provider_query_openai_image_normalize_options(
provider_type,
Some(candidate.effective_model.as_str()),
),
) else {
return Ok(provider_query_skipped_execution_outcome(
request_body.clone(),
provider_query_openai_image_normalize_failure_message(provider_type, &request_body),
provider_query_openai_image_normalize_failure_message(
provider_type,
Some(candidate.effective_model.as_str()),
&request_body,
),
));
};
@@ -2139,29 +2226,50 @@ async fn provider_query_execute_openai_image_test_candidate(
.provider_type
.trim()
.eq_ignore_ascii_case("codex");
let mut provider_request_body = if is_chatgpt_web {
match crate::ai_serving::build_chatgpt_web_image_request_body(&parts, &request_body, None) {
Ok(body) => body,
Err(err) => err.to_error_json(),
}
} else if is_codex || is_grok {
crate::ai_serving::build_openai_image_provider_request_body(&normalized_request)
let upstream_is_stream = crate::ai_serving::resolve_upstream_is_stream_for_provider(
transport.endpoint.config.as_ref(),
transport.provider.provider_type.as_str(),
"openai:image",
request_body
.get("stream")
.and_then(Value::as_bool)
.unwrap_or(false),
false,
);
let provider_request_body = if is_chatgpt_web {
Some(
match crate::ai_serving::build_chatgpt_web_image_request_body(
&parts,
&request_body,
None,
) {
Ok(body) => body,
Err(err) => err.to_error_json(),
},
)
} else if is_codex {
crate::ai_serving::build_codex_openai_image_api_provider_request_body(
&normalized_request,
Some(candidate.effective_model.as_str()),
upstream_is_stream,
)
} else if is_grok {
Some(crate::ai_serving::build_openai_image_provider_request_body(
&normalized_request,
))
} else {
crate::ai_serving::build_openai_image_api_provider_request_body(
&normalized_request,
Some(candidate.effective_model.as_str()),
upstream_is_stream,
)
};
if !is_chatgpt_web {
crate::ai_serving::apply_codex_openai_responses_special_body_edits(
&mut provider_request_body,
transport.provider.provider_type.as_str(),
"openai:image",
transport.endpoint.body_rules.as_ref(),
Some(candidate.key.id.as_str()),
);
}
let Some(provider_request_body) = provider_request_body else {
return Ok(provider_query_skipped_execution_outcome(
request_body,
"Provider request is outside the Codex Images contract",
));
};
let oauth_auth = state.resolve_local_oauth_header_auth(&transport).await?;
let Some((auth_header, auth_value)) =
crate::provider_transport::resolve_openai_image_auth(&transport).or(oauth_auth)
@@ -2193,10 +2301,12 @@ async fn provider_query_execute_openai_image_test_candidate(
headers: &parts.headers,
auth_header: &auth_header,
auth_value: &auth_value,
accept: if is_codex || is_chatgpt_web {
"text/event-stream"
accept: if is_codex {
None
} else if upstream_is_stream {
Some("text/event-stream")
} else {
"application/json"
Some("application/json")
},
header_rules: transport.endpoint.header_rules.as_ref(),
provider_request_body: &provider_request_body,
@@ -2221,7 +2331,7 @@ async fn provider_query_execute_openai_image_test_candidate(
request_headers.insert("x-aether-chatgpt-web-image".to_string(), "1".to_string());
} else if is_grok {
} else {
crate::ai_serving::apply_codex_openai_responses_special_headers(
crate::ai_serving::apply_codex_openai_special_headers(
&mut request_headers,
&provider_request_body,
&parts.headers,
@@ -2260,13 +2370,9 @@ async fn provider_query_execute_openai_image_test_candidate(
};
let request_url = provider_query_openai_image_test_upstream_url(
&transport,
Some(parts.uri.path()),
Some(image_request_path),
parts.uri.query(),
);
let upstream_is_stream = provider_request_body
.get("stream")
.and_then(Value::as_bool)
.unwrap_or(true);
let plan = ExecutionPlan {
request_id: trace_id.to_string(),
@@ -2842,12 +2948,14 @@ async fn provider_query_execute_standard_test_candidate(
crate::ai_serving::normalize_api_format_alias(provider_api_format);
let client_api_format =
provider_query_standard_test_client_api_format(normalized_provider_api_format.as_str());
let original_request_body = provider_query_build_test_request_body_for_api_format(
payload,
&candidate.effective_model,
route_path,
client_api_format,
);
let original_request_body =
provider_query_build_test_request_body_for_api_format_with_search_session(
payload,
&candidate.effective_model,
route_path,
client_api_format,
Some(trace_id),
);
if crate::provider_transport::is_windsurf_provider_transport(&transport)
&& provider_query_normalize_api_format_alias(candidate.endpoint.api_format.as_str())
== "openai:chat"
@@ -2992,6 +3100,45 @@ async fn provider_query_execute_standard_test_candidate(
);
provider_request_body
}
"openai:search" => {
let Some(mut provider_request_body) =
crate::provider_transport::build_same_format_provider_request_body(
crate::provider_transport::SameFormatProviderRequestBodyInput {
body_json: &request_body,
mapped_model: request_model,
client_api_format,
provider_api_format,
source_model: request_body.get("model").and_then(Value::as_str),
family: crate::provider_transport::SameFormatProviderFamily::Standard,
body_rules: transport.endpoint.body_rules.as_ref(),
request_headers: Some(&incoming_request_headers),
upstream_is_stream,
force_body_stream_field: require_body_stream_field,
kiro_auth_config: None,
is_claude_code: false,
enable_model_directives: false,
},
)
else {
return Ok(provider_query_skipped_execution_outcome(
request_body.clone(),
format!("Provider request body could not be built for {provider_api_format}"),
));
};
if let Err(err) = crate::provider_transport::apply_transport_request_body_semantics(
&mut provider_request_body,
&transport,
normalized_provider_api_format.as_str(),
) {
return Ok(provider_query_skipped_execution_outcome(
provider_request_body,
format!(
"Provider request body is not compatible with transport semantics: {err}"
),
));
}
provider_request_body
}
"openai:embedding"
| "gemini:embedding"
| "jina:embedding"
@@ -3046,6 +3193,37 @@ async fn provider_query_execute_standard_test_candidate(
upstream_is_stream,
require_body_stream_field,
);
let source_model = provider_query_request_body_model(&request_body, request_model);
let codex_model_capabilities = crate::ai_serving::codex_model_capabilities_for_transport(
&transport,
provider_api_format,
request_model,
source_model,
);
if matches!(
normalized_provider_api_format.as_str(),
"openai:chat" | "openai:responses" | "openai:responses:compact" | "openai:search"
) && crate::ai_serving::finalize_openai_provider_request_with_codex_model_capabilities(
&mut provider_request_body,
crate::ai_serving::OpenAiProviderRequestFinalization {
source_api_format: client_api_format,
provider_api_format,
provider_type: transport.provider.provider_type.as_str(),
provider_model: request_model,
source_model,
body_rules: transport.endpoint.body_rules.as_ref(),
upstream_is_stream,
require_body_stream_field,
},
codex_model_capabilities.as_ref(),
)
.is_err()
{
return Ok(provider_query_skipped_execution_outcome(
provider_request_body,
"Provider request body violates the OpenAI provider contract",
));
}
if crate::provider_transport::is_gemini_cli_provider_transport(&transport)
&& normalized_provider_api_format == "gemini:generate_content"
{
@@ -3122,6 +3300,7 @@ async fn provider_query_execute_standard_test_candidate(
"openai:chat"
| "openai:responses"
| "openai:responses:compact"
| "openai:search"
| "claude:messages"
| "gemini:generate_content"
| "openai:embedding"
@@ -3137,6 +3316,7 @@ async fn provider_query_execute_standard_test_candidate(
"openai:chat"
| "openai:responses"
| "openai:responses:compact"
| "openai:search"
| "openai:embedding"
| "jina:embedding"
| "doubao:embedding"
@@ -3202,7 +3382,7 @@ async fn provider_query_execute_standard_test_candidate(
&BTreeMap::new(),
Some("application/json"),
),
"openai:responses" | "openai:responses:compact" => {
"openai:responses" | "openai:responses:compact" | "openai:search" => {
crate::provider_transport::auth::build_complete_passthrough_headers_with_auth(
&parts.headers,
auth_header.as_deref().unwrap_or_default(),
@@ -3268,8 +3448,10 @@ async fn provider_query_execute_standard_test_candidate(
response_body: None,
});
}
if crate::ai_serving::is_openai_responses_format(provider_api_format) {
crate::ai_serving::apply_codex_openai_responses_special_headers(
if crate::ai_serving::is_openai_responses_family_format(provider_api_format)
|| crate::ai_serving::api_format_alias_matches(provider_api_format, "openai:search")
{
crate::ai_serving::apply_codex_openai_special_headers(
&mut request_headers,
&provider_request_body,
&parts.headers,
@@ -3278,9 +3460,17 @@ async fn provider_query_execute_standard_test_candidate(
Some(trace_id),
transport.key.decrypted_auth_config.as_deref(),
);
crate::provider_transport::apply_local_auth_config_header_overrides(
let final_provider_model = provider_request_body
.get("model")
.and_then(Value::as_str)
.unwrap_or(request_model);
crate::ai_serving::apply_codex_openai_responses_lite_header_with_capabilities(
&mut request_headers,
transport.key.decrypted_auth_config.as_deref(),
transport.provider.provider_type.as_str(),
provider_api_format,
final_provider_model,
source_model,
codex_model_capabilities.as_ref(),
);
}
if !uses_vertex_query_auth {
@@ -33,6 +33,8 @@ pub(super) fn provider_query_standard_test_client_api_format(
let normalized_api_format = crate::ai_serving::normalize_api_format_alias(provider_api_format);
if normalized_api_format == "openai:responses:compact" {
"openai:responses:compact"
} else if normalized_api_format == "openai:search" {
"openai:search"
} else if crate::ai_serving::is_embedding_api_format(&normalized_api_format) {
"openai:embedding"
} else if crate::ai_serving::is_rerank_api_format(&normalized_api_format) {
@@ -71,6 +73,7 @@ pub(super) fn provider_query_standard_test_unsupported_reason(
}
"openai:responses"
| "openai:responses:compact"
| "openai:search"
| "claude:messages"
| "openai:embedding"
| "jina:embedding"
@@ -261,6 +264,7 @@ pub(super) fn provider_query_test_adapter_for_provider_api_format(
"openai:chat"
| "openai:responses"
| "openai:responses:compact"
| "openai:search"
| "claude:messages"
| "gemini:generate_content"
| "gemini:interactions"
@@ -365,6 +369,7 @@ pub(super) fn provider_query_transport_supports_model_test_execution(
}
"openai:responses"
| "openai:responses:compact"
| "openai:search"
| "openai:embedding"
| "jina:embedding"
| "doubao:embedding"
@@ -9,16 +9,19 @@ pub(super) struct ProviderQueryOpenAiImageTestCapability(AdminProviderOpenAiImag
pub(super) fn provider_query_openai_image_test_capability(
provider_type: &str,
provider_model: Option<&str>,
) -> ProviderQueryOpenAiImageTestCapability {
ProviderQueryOpenAiImageTestCapability(admin_provider_openai_image_test_capability(
provider_type,
provider_model,
))
}
pub(super) fn provider_query_openai_image_normalize_options(
provider_type: &str,
provider_model: Option<&str>,
) -> crate::ai_serving::OpenAiImageNormalizeOptions {
admin_provider_openai_image_normalize_options(provider_type)
admin_provider_openai_image_normalize_options(provider_type, provider_model)
}
pub(super) fn provider_query_openai_image_requested_count(request_body: &Value) -> Option<u64> {
@@ -35,9 +38,10 @@ pub(super) fn provider_query_openai_image_requested_count(request_body: &Value)
pub(super) fn provider_query_openai_image_normalize_failure_message(
provider_type: &str,
provider_model: Option<&str>,
request_body: &Value,
) -> String {
let capability = provider_query_openai_image_test_capability(provider_type);
let capability = provider_query_openai_image_test_capability(provider_type, provider_model);
if provider_query_openai_image_requested_count(request_body)
.is_some_and(|value| !capability.0.supports_generation_count(value))
{
@@ -101,8 +101,7 @@ fn provider_query_model_mapping_matches_endpoint(
) -> bool {
let api_format_matches = mapping.api_formats.as_ref().is_none_or(|api_formats| {
api_formats.iter().any(|value| {
aether_scheduler_core::normalize_api_format(value)
== aether_scheduler_core::normalize_api_format(&endpoint.api_format)
crate::ai_serving::api_format_permission_covers(value, &endpoint.api_format)
})
});
if !api_format_matches {
@@ -367,3 +366,41 @@ fn provider_query_parse_mapping_string_list_array(
}
Ok(parsed)
}
#[cfg(test)]
mod tests {
use super::*;
fn sample_endpoint(api_format: &str) -> StoredProviderCatalogEndpoint {
StoredProviderCatalogEndpoint::new(
"endpoint-1".to_string(),
"provider-1".to_string(),
api_format.to_string(),
None,
None,
true,
)
.expect("endpoint should build")
}
fn sample_mapping(api_format: &str) -> StoredProviderModelMapping {
StoredProviderModelMapping {
name: "gpt-5.6-luna".to_string(),
priority: 1,
api_formats: Some(vec![api_format.to_string()]),
endpoint_ids: None,
}
}
#[test]
fn responses_mapping_scope_covers_search_in_one_direction() {
assert!(provider_query_model_mapping_matches_endpoint(
&sample_mapping("openai:responses"),
&sample_endpoint("openai:search"),
));
assert!(!provider_query_model_mapping_matches_endpoint(
&sample_mapping("openai:search"),
&sample_endpoint("openai:responses"),
));
}
}
@@ -337,6 +337,11 @@ fn provider_query_standard_test_resolves_codex_responses_upstream_streaming() {
"codex",
"openai:responses:compact",
));
assert!(!provider_query_resolve_standard_test_upstream_is_stream(
Some(&json!({"upstream_stream_policy": "force_stream"})),
"codex",
"openai:responses:compact",
));
assert!(!provider_query_resolve_standard_test_upstream_is_stream(
None,
"custom",
@@ -470,6 +475,118 @@ fn provider_query_compact_test_request_body_defaults_to_responses_input() {
assert!(body.get("messages").is_none());
}
#[test]
fn provider_query_search_test_request_body_defaults_to_typed_search_input() {
let payload = json!({"message": "find current documentation"});
let client_api_format = provider_query_standard_test_client_api_format("openai:search");
let body = provider_query_build_test_request_body_for_api_format(
&payload,
"gpt-5.6-sol",
"/api/admin/provider-query/test-model",
client_api_format,
);
assert_eq!(client_api_format, "openai:search");
assert!(body["id"]
.as_str()
.is_some_and(|value| value.starts_with("aether-model-test-")));
assert_eq!(body["model"], json!("gpt-5.6-sol"));
assert_eq!(body["input"], json!("find current documentation"));
assert_eq!(
body["commands"]["search_query"][0]["q"],
json!("find current documentation")
);
assert_eq!(body["max_output_tokens"], json!(256));
assert!(body.get("messages").is_none());
assert!(body.get("stream").is_none());
}
#[test]
fn provider_query_search_test_completes_missing_protocol_fields() {
let payload = json!({
"request_body": {
"model": "gpt-5.6-luna",
"input": "find release notes"
}
});
let body = provider_query_build_test_request_body_for_api_format_with_search_session(
&payload,
"gpt-5.6-luna",
"/api/admin/provider-query/test-model",
"openai:search",
Some("trace-model-test-1"),
);
assert_eq!(body["id"], json!("aether-model-test-trace-model-test-1"));
assert_eq!(
body["commands"]["search_query"][0]["q"],
json!("find release notes")
);
assert_eq!(body["max_output_tokens"], json!(256));
}
#[test]
fn provider_query_search_test_preserves_a_non_empty_client_session_id() {
let payload = json!({
"request_body": {
"id": "client-search-session",
"model": "gpt-5.6-luna",
"input": "find release notes"
}
});
let body = provider_query_build_test_request_body_for_api_format_with_search_session(
&payload,
"gpt-5.6-luna",
"/api/admin/provider-query/test-model",
"openai:search",
Some("trace-model-test-1"),
);
assert_eq!(body["id"], json!("client-search-session"));
}
#[test]
fn provider_query_search_success_requires_non_empty_output() {
fn result(body: Value) -> aether_contracts::ExecutionResult {
aether_contracts::ExecutionResult {
request_id: "provider-search-test".to_string(),
candidate_id: Some("candidate-0".to_string()),
status_code: 200,
headers: BTreeMap::new(),
body: Some(aether_contracts::ResponseBody {
json_body: Some(body),
body_bytes_b64: None,
}),
telemetry: None,
error: None,
}
}
assert!(provider_query_standard_execution_response_body(
"openai:search",
&result(json!({})),
None,
)
.is_none());
assert!(provider_query_standard_execution_response_body(
"openai:search",
&result(json!({"output": " "})),
None,
)
.is_none());
assert_eq!(
provider_query_standard_execution_response_body(
"openai:search",
&result(json!({"output": "search result", "encrypted_output": "ciphertext"})),
None,
),
Some(json!({"output": "search result", "encrypted_output": "ciphertext"}))
);
}
#[test]
fn provider_query_embedding_test_request_body_defaults_to_embedding_input() {
let payload = json!({"message": "hello from embedding"});
@@ -632,6 +749,10 @@ fn provider_query_test_adapter_routes_fixed_provider_endpoint_types() {
provider_query_test_adapter_for_provider_api_format("codex", "openai:responses:compact"),
Some(ProviderQueryTestAdapter::Standard)
);
assert_eq!(
provider_query_test_adapter_for_provider_api_format("codex", "openai:search"),
Some(ProviderQueryTestAdapter::Standard)
);
assert_eq!(
provider_query_test_adapter_for_provider_api_format("chatgpt_web", "openai:image"),
Some(ProviderQueryTestAdapter::OpenAiImage)
@@ -717,6 +838,10 @@ fn provider_query_endpoint_priority_prefers_text_before_cli_and_image() {
provider_query_model_test_endpoint_priority("codex", "openai:responses:compact"),
Some(1)
);
assert_eq!(
provider_query_model_test_endpoint_priority("codex", "openai:search"),
Some(1)
);
assert_eq!(
provider_query_model_test_endpoint_priority("chatgpt_web", "openai:image"),
Some(2)
@@ -997,7 +1122,7 @@ fn provider_query_grok_image_test_allows_multi_generation_count() {
&parts,
&body,
None,
provider_query_openai_image_normalize_options("grok"),
provider_query_openai_image_normalize_options("grok", Some("grok-imagine-image")),
)
.expect("grok image model tests should allow multi-image generation");
let provider_body = crate::ai_serving::build_openai_image_provider_request_body(&normalized);
@@ -1065,12 +1190,48 @@ fn provider_query_non_grok_image_test_keeps_single_generation_boundary() {
&parts,
&body,
None,
provider_query_openai_image_normalize_options("chatgpt_web"),
provider_query_openai_image_normalize_options("chatgpt_web", Some("gpt-image-2")),
)
.is_none()
);
assert_eq!(
provider_query_openai_image_normalize_failure_message("chatgpt_web", &body),
provider_query_openai_image_normalize_failure_message(
"chatgpt_web",
Some("gpt-image-2"),
&body,
),
"Provider request body could not be normalized for openai:image: selected provider supports n=1..1 for generation"
);
}
#[test]
fn provider_query_dall_e_3_image_test_keeps_single_generation_boundary() {
let request = http::Request::builder()
.uri("/v1/images/generations")
.body(())
.expect("request should build");
let (parts, _) = request.into_parts();
let body = json!({
"model": "dall-e-3",
"prompt": "draw",
"n": 2
});
assert!(
crate::ai_serving::normalize_openai_image_request_with_options(
&parts,
&body,
None,
provider_query_openai_image_normalize_options("openai", Some("dall-e-3")),
)
.is_none()
);
assert_eq!(
provider_query_openai_image_normalize_failure_message(
"openai",
Some("dall-e-3"),
&body,
),
"Provider request body could not be normalized for openai:image: selected provider supports n=1..1 for generation"
);
}
@@ -1,5 +1,6 @@
use crate::image_capabilities::{
openai_image_normalize_options_for_provider, openai_image_provider_max_generation_count,
openai_image_normalize_options_for_provider,
openai_image_provider_max_generation_count_for_model,
};
use serde_json::{json, Value};
@@ -24,16 +25,21 @@ impl AdminProviderOpenAiImageTestCapability {
pub(crate) fn admin_provider_openai_image_test_capability(
provider_type: &str,
provider_model: Option<&str>,
) -> AdminProviderOpenAiImageTestCapability {
AdminProviderOpenAiImageTestCapability {
max_generation_count: openai_image_provider_max_generation_count(provider_type),
max_generation_count: openai_image_provider_max_generation_count_for_model(
provider_type,
provider_model,
),
}
}
pub(crate) fn admin_provider_openai_image_normalize_options(
provider_type: &str,
provider_model: Option<&str>,
) -> crate::ai_serving::OpenAiImageNormalizeOptions {
openai_image_normalize_options_for_provider(provider_type)
openai_image_normalize_options_for_provider(provider_type, provider_model)
}
pub(crate) fn admin_provider_model_test_capabilities_payload(
@@ -47,7 +53,7 @@ pub(crate) fn admin_provider_model_test_capabilities_payload(
provider_type.eq_ignore_ascii_case("grok") && model_id == GROK_IMAGE_EDIT_MODEL_ID;
let openai_image = if supports_image_generation {
Some(json!({
"max_generation_count": admin_provider_openai_image_test_capability(provider_type).max_generation_count,
"max_generation_count": admin_provider_openai_image_test_capability(provider_type, Some(model_id)).max_generation_count,
"supports_generation": !is_grok_image_edit,
"supports_edit": is_grok_image_edit,
}))
@@ -105,6 +111,13 @@ mod tests {
assert!(payload["openai:image"].is_null());
}
#[test]
fn dall_e_3_reports_its_model_specific_generation_limit() {
let payload = admin_provider_model_test_capabilities_payload("openai", "dall-e-3", true);
assert_eq!(payload["openai:image"]["max_generation_count"], 1);
}
#[test]
fn grok_image_support_uses_catalog_model_ids_not_global_fallback() {
assert!(admin_provider_model_supports_image_generation(
@@ -2,7 +2,7 @@ use crate::handlers::admin::provider::shared::payloads::AdminProviderKeyCreateRe
use crate::handlers::admin::provider::write::normalize::{
normalize_allow_auth_channel_mismatch_formats, normalize_api_format_json_object_keys,
normalize_api_format_list, normalize_auth_type, normalize_auth_type_by_format,
normalize_max_probe_interval_minutes, validate_vertex_api_formats,
normalize_max_probe_interval_minutes, normalize_rate_multipliers, validate_vertex_api_formats,
};
use crate::handlers::admin::request::AdminAppState;
use crate::handlers::admin::shared::{
@@ -165,7 +165,7 @@ pub(crate) async fn build_admin_create_provider_key_record(
},
encrypted_api_key,
encrypted_auth_config,
normalize_api_format_json_object_keys(payload.rate_multipliers, "rate_multipliers")?,
normalize_rate_multipliers(payload.rate_multipliers)?,
None,
normalize_string_list(payload.allowed_models).map(|value| json!(value)),
None,
@@ -2,7 +2,7 @@ use crate::handlers::admin::provider::shared::payloads::AdminProviderKeyUpdatePa
use crate::handlers::admin::provider::write::normalize::{
normalize_allow_auth_channel_mismatch_formats, normalize_api_format_json_object_keys,
normalize_api_format_list, normalize_auth_type, normalize_auth_type_by_format,
normalize_max_probe_interval_minutes, validate_vertex_api_formats,
normalize_max_probe_interval_minutes, normalize_rate_multipliers, validate_vertex_api_formats,
};
use crate::handlers::admin::request::AdminAppState;
use crate::handlers::admin::shared::{
@@ -260,8 +260,7 @@ pub(crate) async fn build_admin_update_provider_key_record(
updated.name = trimmed.to_string();
}
if fields.contains("rate_multipliers") {
updated.rate_multipliers =
normalize_api_format_json_object_keys(payload.rate_multipliers, "rate_multipliers")?;
updated.rate_multipliers = normalize_rate_multipliers(payload.rate_multipliers)?;
}
if let Some(internal_priority) = payload.internal_priority {
updated.internal_priority = internal_priority;
@@ -42,6 +42,31 @@ pub(crate) fn normalize_api_format_json_object_keys(
Ok(Some(serde_json::Value::Object(normalized)))
}
pub(crate) fn normalize_rate_multipliers(
value: Option<serde_json::Value>,
) -> Result<Option<serde_json::Value>, String> {
let Some(value) = normalize_json_like_object(value, "rate_multipliers")? else {
return Ok(None);
};
let serde_json::Value::Object(map) = value else {
return Ok(Some(value));
};
let mut normalized = serde_json::Map::new();
for (key, value) in map {
let canonical = crate::ai_serving::normalize_api_format_alias(&key);
let multiplier = value
.as_f64()
.filter(|value| value.is_finite() && *value >= 0.0)
.ok_or_else(|| format!("rate_multipliers.{canonical} 必须是大于或等于 0 的有限数值"))?;
normalized.insert(canonical, serde_json::Value::from(multiplier));
}
if normalized.is_empty() {
Ok(None)
} else {
Ok(Some(serde_json::Value::Object(normalized)))
}
}
pub(crate) fn normalize_auth_type_by_format(
value: Option<serde_json::Value>,
field_name: &str,
@@ -212,7 +237,7 @@ mod tests {
normalize_allow_auth_channel_mismatch_formats, normalize_api_format_json_object_keys,
normalize_api_format_list, normalize_auth_type, normalize_auth_type_by_format,
normalize_chat_pii_redaction_config, normalize_pool_advanced_config,
normalize_provider_type_input, validate_vertex_api_formats,
normalize_provider_type_input, normalize_rate_multipliers, validate_vertex_api_formats,
};
use serde_json::json;
@@ -224,6 +249,21 @@ mod tests {
);
}
#[test]
fn rate_multipliers_require_non_negative_finite_numbers() {
assert_eq!(
normalize_rate_multipliers(Some(json!({" OPENAI:RESPONSES ": 1.25})))
.expect("valid multiplier should normalize"),
Some(json!({"openai:responses": 1.25}))
);
for value in [
json!({"openai:responses": -0.1}),
json!({"openai:responses": "1.0"}),
] {
assert!(normalize_rate_multipliers(Some(value)).is_err());
}
}
#[test]
fn normalize_pool_advanced_rejects_legacy_booleans() {
assert_eq!(
@@ -3,11 +3,79 @@ mod endpoint;
mod template;
mod update;
fn normalize_provider_request_timeout(value: Option<f64>) -> Result<Option<f64>, String> {
let max = aether_contracts::MAX_EXECUTION_REQUEST_TIMEOUT_SECS as f64;
match value {
Some(value) if (1.0..=max).contains(&value) => Ok(Some(value)),
Some(_) => Err(format!(
"request_timeout 必须是 1 到 {} 之间的数字",
aether_contracts::MAX_EXECUTION_REQUEST_TIMEOUT_SECS
)),
None => Ok(None),
}
}
fn normalize_provider_stream_first_byte_timeout(value: Option<f64>) -> Result<Option<f64>, String> {
let max = aether_contracts::MAX_EXECUTION_STREAM_FIRST_BYTE_TIMEOUT_SECS as f64;
match value {
Some(value) if (1.0..=max).contains(&value) => Ok(Some(value)),
Some(_) => Err(format!(
"stream_first_byte_timeout 必须是 1 到 {} 之间的数字",
aether_contracts::MAX_EXECUTION_STREAM_FIRST_BYTE_TIMEOUT_SECS
)),
None => Ok(None),
}
}
pub(crate) use self::create::build_admin_create_provider_record;
pub(crate) use self::endpoint::build_admin_fixed_provider_endpoint_record;
pub(crate) use self::template::{
apply_admin_fixed_provider_endpoint_template_overrides,
reconcile_admin_fixed_provider_template_endpoints,
reconcile_admin_fixed_provider_template_keys,
reconcile_admin_fixed_provider_template_endpoints_after_update,
};
pub(crate) use self::update::build_admin_update_provider_record;
#[cfg(test)]
mod tests {
use super::{normalize_provider_request_timeout, normalize_provider_stream_first_byte_timeout};
#[test]
fn provider_request_timeout_accepts_the_execution_protocol_range() {
assert_eq!(normalize_provider_request_timeout(Some(1.0)), Ok(Some(1.0)));
assert_eq!(
normalize_provider_request_timeout(Some(
aether_contracts::MAX_EXECUTION_REQUEST_TIMEOUT_SECS as f64,
)),
Ok(Some(
aether_contracts::MAX_EXECUTION_REQUEST_TIMEOUT_SECS as f64,
))
);
assert!(normalize_provider_request_timeout(Some(0.0)).is_err());
assert!(normalize_provider_request_timeout(Some(
aether_contracts::MAX_EXECUTION_REQUEST_TIMEOUT_SECS as f64 + 1.0,
))
.is_err());
assert!(normalize_provider_request_timeout(Some(f64::NAN)).is_err());
}
#[test]
fn provider_stream_first_byte_timeout_keeps_its_protocol_range() {
assert_eq!(
normalize_provider_stream_first_byte_timeout(Some(1.0)),
Ok(Some(1.0))
);
assert_eq!(
normalize_provider_stream_first_byte_timeout(Some(
aether_contracts::MAX_EXECUTION_STREAM_FIRST_BYTE_TIMEOUT_SECS as f64,
)),
Ok(Some(
aether_contracts::MAX_EXECUTION_STREAM_FIRST_BYTE_TIMEOUT_SECS as f64,
))
);
assert!(normalize_provider_stream_first_byte_timeout(Some(
aether_contracts::MAX_EXECUTION_STREAM_FIRST_BYTE_TIMEOUT_SECS as f64 + 1.0,
))
.is_err());
}
}
@@ -107,16 +107,9 @@ pub(crate) async fn build_admin_create_provider_record(
None => Some(2),
};
let proxy = normalize_json_object(payload.proxy, "proxy")?;
let stream_first_byte_timeout_secs = match payload.stream_first_byte_timeout {
Some(value) if (1.0..=300.0).contains(&value) => Some(value),
Some(_) => return Err("stream_first_byte_timeout 必须是 1 到 300 之间的数字".to_string()),
None => None,
};
let request_timeout_secs = match payload.request_timeout {
Some(value) if (1.0..=600.0).contains(&value) => Some(value),
Some(_) => return Err("request_timeout 必须是 1 到 600 之间的数字".to_string()),
None => None,
};
let stream_first_byte_timeout_secs =
super::normalize_provider_stream_first_byte_timeout(payload.stream_first_byte_timeout)?;
let request_timeout_secs = super::normalize_provider_request_timeout(payload.request_timeout)?;
let mut config_map = normalize_json_object(payload.config, "config")?
.and_then(|value| value.as_object().cloned())
@@ -1,11 +1,11 @@
use super::endpoint::{
build_admin_fixed_provider_endpoint_defaults, build_admin_fixed_provider_endpoint_record,
AdminFixedProviderEndpointDefaults,
};
use crate::handlers::admin::request::AdminAppState;
use crate::provider_key_auth::provider_key_is_oauth_managed;
use crate::GatewayError;
use aether_data_contracts::repository::provider_catalog::{
StoredProviderCatalogEndpoint, StoredProviderCatalogKey, StoredProviderCatalogProvider,
StoredProviderCatalogEndpoint, StoredProviderCatalogProvider,
};
use aether_provider_transport::provider_types::{
fixed_provider_template, FixedProviderEndpointTemplate, FixedProviderTemplate,
@@ -36,6 +36,30 @@ struct FixedProviderEndpointMetadata {
pub(crate) async fn reconcile_admin_fixed_provider_template_endpoints(
state: &AdminAppState<'_>,
provider: &StoredProviderCatalogProvider,
) -> Result<(), GatewayError> {
reconcile_admin_fixed_provider_template_endpoints_with_adoption_provider(
state, provider, provider,
)
.await
}
pub(crate) async fn reconcile_admin_fixed_provider_template_endpoints_after_update(
state: &AdminAppState<'_>,
previous_provider: &StoredProviderCatalogProvider,
updated_provider: &StoredProviderCatalogProvider,
) -> Result<(), GatewayError> {
reconcile_admin_fixed_provider_template_endpoints_with_adoption_provider(
state,
updated_provider,
previous_provider,
)
.await
}
async fn reconcile_admin_fixed_provider_template_endpoints_with_adoption_provider(
state: &AdminAppState<'_>,
provider: &StoredProviderCatalogProvider,
adoption_provider: &StoredProviderCatalogProvider,
) -> Result<(), GatewayError> {
let Some(template) = state.fixed_provider_template(&provider.provider_type) else {
return Ok(());
@@ -53,8 +77,9 @@ pub(crate) async fn reconcile_admin_fixed_provider_template_endpoints(
match existing_endpoint {
Some(existing_endpoint) => {
matched_endpoint_ids.insert(existing_endpoint.id.clone());
let updated = reconcile_fixed_provider_endpoint(
let updated = reconcile_fixed_provider_endpoint_with_adoption_provider(
provider,
adoption_provider,
existing_endpoint,
template,
endpoint_template,
@@ -115,31 +140,6 @@ pub(crate) async fn reconcile_admin_fixed_provider_template_endpoints(
Ok(())
}
pub(crate) async fn reconcile_admin_fixed_provider_template_keys(
state: &AdminAppState<'_>,
provider: &StoredProviderCatalogProvider,
) -> Result<(), GatewayError> {
let Some(_) = state.fixed_provider_template(&provider.provider_type) else {
return Ok(());
};
let existing_keys = state
.list_provider_catalog_keys_by_provider_ids(std::slice::from_ref(&provider.id))
.await?;
for existing_key in existing_keys {
let Some(updated_key) = reconcile_fixed_provider_key(provider, &existing_key) else {
continue;
};
let Some(_) = state.update_provider_catalog_key(&updated_key).await? else {
return Err(GatewayError::Internal(
"provider catalog key writer unavailable".to_string(),
));
};
}
Ok(())
}
pub(crate) fn apply_admin_fixed_provider_endpoint_template_overrides(
provider: &StoredProviderCatalogProvider,
existing_endpoint: &StoredProviderCatalogEndpoint,
@@ -156,8 +156,14 @@ pub(crate) fn apply_admin_fixed_provider_endpoint_template_overrides(
let defaults =
build_admin_fixed_provider_endpoint_defaults(provider, template, endpoint_template)?;
let mut metadata = fixed_provider_endpoint_metadata(existing_endpoint)
.unwrap_or_else(|| managed_fixed_provider_endpoint_metadata(template, endpoint_template));
let mut metadata = fixed_provider_endpoint_metadata(existing_endpoint).unwrap_or_else(|| {
adopt_fixed_provider_endpoint_metadata(
existing_endpoint,
&defaults,
template,
endpoint_template,
)
});
let mut overrides = metadata.overrides.clone();
sync_override_if_changed(
@@ -250,17 +256,48 @@ pub(crate) fn apply_admin_fixed_provider_endpoint_template_overrides(
Ok(())
}
#[cfg(test)]
fn reconcile_fixed_provider_endpoint(
provider: &StoredProviderCatalogProvider,
existing_endpoint: &StoredProviderCatalogEndpoint,
template: &FixedProviderTemplate,
endpoint_template: &FixedProviderEndpointTemplate,
) -> Result<StoredProviderCatalogEndpoint, String> {
reconcile_fixed_provider_endpoint_with_adoption_provider(
provider,
provider,
existing_endpoint,
template,
endpoint_template,
)
}
fn reconcile_fixed_provider_endpoint_with_adoption_provider(
provider: &StoredProviderCatalogProvider,
adoption_provider: &StoredProviderCatalogProvider,
existing_endpoint: &StoredProviderCatalogEndpoint,
template: &FixedProviderTemplate,
endpoint_template: &FixedProviderEndpointTemplate,
) -> Result<StoredProviderCatalogEndpoint, String> {
let defaults =
build_admin_fixed_provider_endpoint_defaults(provider, template, endpoint_template)?;
let mut updated = existing_endpoint.clone();
let metadata = fixed_provider_endpoint_metadata(existing_endpoint)
.unwrap_or_else(|| managed_fixed_provider_endpoint_metadata(template, endpoint_template));
let metadata = match fixed_provider_endpoint_metadata(existing_endpoint) {
Some(metadata) => metadata,
None => {
let adoption_defaults = build_admin_fixed_provider_endpoint_defaults(
adoption_provider,
template,
endpoint_template,
)?;
adopt_fixed_provider_endpoint_metadata(
existing_endpoint,
&adoption_defaults,
template,
endpoint_template,
)
}
};
updated.api_format = defaults.api_format.clone();
updated.api_family = Some(defaults.api_family.clone());
@@ -455,6 +492,77 @@ fn managed_fixed_provider_endpoint_metadata(
}
}
fn adopt_fixed_provider_endpoint_metadata(
existing_endpoint: &StoredProviderCatalogEndpoint,
defaults: &AdminFixedProviderEndpointDefaults,
template: &FixedProviderTemplate,
endpoint_template: &FixedProviderEndpointTemplate,
) -> FixedProviderEndpointMetadata {
let mut metadata = managed_fixed_provider_endpoint_metadata(template, endpoint_template);
sync_override(
&mut metadata.overrides,
OVERRIDE_BASE_URL,
&existing_endpoint.base_url,
&defaults.base_url,
);
sync_override(
&mut metadata.overrides,
OVERRIDE_CUSTOM_PATH,
&existing_endpoint.custom_path,
&defaults.custom_path,
);
sync_override(
&mut metadata.overrides,
OVERRIDE_HEADER_RULES,
&existing_endpoint.header_rules,
&defaults.header_rules,
);
sync_override(
&mut metadata.overrides,
OVERRIDE_BODY_RULES,
&existing_endpoint.body_rules,
&defaults.body_rules,
);
sync_override(
&mut metadata.overrides,
OVERRIDE_MAX_RETRIES,
&existing_endpoint.max_retries,
&defaults.max_retries,
);
sync_override(
&mut metadata.overrides,
OVERRIDE_IS_ACTIVE,
&existing_endpoint.is_active,
&defaults.is_active,
);
sync_override(
&mut metadata.overrides,
OVERRIDE_PROXY,
&existing_endpoint.proxy,
&defaults.proxy,
);
sync_override(
&mut metadata.overrides,
OVERRIDE_FORMAT_ACCEPTANCE_CONFIG,
&existing_endpoint.format_acceptance_config,
&defaults.format_acceptance_config,
);
let existing_config = endpoint_config_without_metadata(existing_endpoint.config.as_ref());
for (key, desired) in fixed_provider_endpoint_config_defaults(endpoint_template) {
let Some(actual) = existing_config.get(&key) else {
continue;
};
sync_override(
&mut metadata.overrides,
&config_override_key(&key),
actual,
&desired,
);
}
metadata
}
fn upsert_fixed_provider_endpoint_metadata(
endpoint: &mut StoredProviderCatalogEndpoint,
metadata: &FixedProviderEndpointMetadata,
@@ -513,22 +621,6 @@ fn current_unix_secs() -> u64 {
.unwrap_or(0)
}
fn reconcile_fixed_provider_key(
provider: &StoredProviderCatalogProvider,
existing_key: &StoredProviderCatalogKey,
) -> Option<StoredProviderCatalogKey> {
if !provider_key_is_oauth_managed(existing_key, &provider.provider_type)
|| existing_key.api_formats.is_none()
{
return None;
}
let mut updated = existing_key.clone();
updated.api_formats = None;
updated.updated_at_unix_secs = Some(current_unix_secs());
Some(updated)
}
fn sync_override<T>(overrides: &mut BTreeSet<String>, key: &str, actual: &T, desired: &T)
where
T: PartialEq,
@@ -624,4 +716,68 @@ mod tests {
.expect("endpoint should reconcile");
assert_eq!(reconciled.base_url, "http://127.0.0.1:18181/v1");
}
#[test]
fn fixed_provider_endpoint_reconcile_adopts_existing_customization() {
let provider = sample_codex_provider();
let template = fixed_provider_template("codex").expect("codex template should exist");
let endpoint_template = template
.endpoints
.iter()
.find(|endpoint| endpoint.api_format == "openai:responses")
.expect("responses endpoint template should exist");
let mut existing = sample_codex_endpoint("http://127.0.0.1:18181/backend-api/codex");
existing.is_active = false;
existing.max_retries = Some(9);
existing.proxy = Some(serde_json::json!({"url": "http://proxy.internal:8080"}));
existing.config = Some(serde_json::json!({
"upstream_stream_policy": "force_non_stream",
"custom_transport_option": true
}));
let reconciled =
reconcile_fixed_provider_endpoint(&provider, &existing, template, endpoint_template)
.expect("endpoint should reconcile");
assert_eq!(
reconciled.base_url,
"http://127.0.0.1:18181/backend-api/codex"
);
assert!(!reconciled.is_active);
assert_eq!(reconciled.max_retries, Some(9));
assert_eq!(
reconciled.proxy,
Some(serde_json::json!({"url": "http://proxy.internal:8080"}))
);
assert_eq!(
reconciled
.config
.as_ref()
.and_then(|value| value.get("upstream_stream_policy")),
Some(&serde_json::json!("force_non_stream"))
);
assert_eq!(
reconciled
.config
.as_ref()
.and_then(|value| value.get("custom_transport_option")),
Some(&serde_json::json!(true))
);
let metadata = fixed_provider_endpoint_metadata(&reconciled)
.expect("fixed provider metadata should exist");
for key in [
"base_url",
"is_active",
"max_retries",
"proxy",
"config.upstream_stream_policy",
] {
assert!(metadata.overrides.contains(key), "missing override {key}");
}
let second =
reconcile_fixed_provider_endpoint(&provider, &reconciled, template, endpoint_template)
.expect("endpoint should reconcile idempotently");
assert_eq!(second, reconciled);
}
}
@@ -202,21 +202,13 @@ pub(crate) async fn build_admin_update_provider_record(
}
if fields.contains("stream_first_byte_timeout") {
updated.stream_first_byte_timeout_secs = match payload.stream_first_byte_timeout {
Some(value) if (1.0..=300.0).contains(&value) => Some(value),
Some(_) => {
return Err("stream_first_byte_timeout 必须是 1 到 300 之间的数字".to_string());
}
None => None,
};
updated.stream_first_byte_timeout_secs =
super::normalize_provider_stream_first_byte_timeout(payload.stream_first_byte_timeout)?;
}
if fields.contains("request_timeout") {
updated.request_timeout_secs = match payload.request_timeout {
Some(value) if (1.0..=600.0).contains(&value) => Some(value),
Some(_) => return Err("request_timeout 必须是 1 到 600 之间的数字".to_string()),
None => None,
};
updated.request_timeout_secs =
super::normalize_provider_request_timeout(payload.request_timeout)?;
}
if fields.contains("enable_format_conversion") {
@@ -1,5 +1,26 @@
use super::*;
fn validate_admin_endpoint_stream_policy(
api_format: &str,
config: Option<&serde_json::Value>,
) -> Result<(), String> {
if !crate::ai_serving::api_format_alias_matches(api_format, "openai:search") {
return Ok(());
}
let requested = config
.and_then(serde_json::Value::as_object)
.and_then(|config| {
config
.get("upstream_stream_policy")
.or_else(|| config.get("upstreamStreamPolicy"))
.or_else(|| config.get("upstream_stream"))
});
if requested.is_some_and(crate::handlers::public::admin_requested_force_stream) {
return Err("OpenAI Search 端点仅支持非流式上游请求".to_string());
}
Ok(())
}
impl<'a> AdminAppState<'a> {
pub(crate) async fn build_admin_keys_grouped_by_format_payload(
&self,
@@ -232,6 +253,7 @@ impl<'a> AdminAppState<'a> {
let (normalized_api_format, api_family, endpoint_kind) =
admin_endpoint_signature_parts(&payload.api_format)
.ok_or_else(|| format!("无效的 api_format: {}", payload.api_format))?;
validate_admin_endpoint_stream_policy(normalized_api_format, payload.config.as_ref())?;
let base_url = normalize_admin_base_url(&payload.base_url)?;
let existing_endpoints = self
@@ -337,6 +359,13 @@ impl<'a> AdminAppState<'a> {
&update_fields,
)?;
if fields.contains("config") {
validate_admin_endpoint_stream_policy(
existing_endpoint.api_format.as_str(),
updated.config.as_ref(),
)?;
}
if provider_type == "codex"
&& crate::ai_serving::is_openai_responses_format(&existing_endpoint.api_format)
{
@@ -389,3 +418,40 @@ impl<'a> AdminAppState<'a> {
Ok(updated)
}
}
#[cfg(test)]
mod tests {
use serde_json::json;
use super::validate_admin_endpoint_stream_policy;
#[test]
fn search_endpoint_rejects_explicit_streaming_policy_for_all_config_keys() {
for (api_format, key, value) in [
(
"openai:search",
"upstream_stream_policy",
json!("force_stream"),
),
("openai:search", "upstreamStreamPolicy", json!(true)),
("/v1/alpha/search", "upstream_stream", json!("sse")),
] {
let config = json!({(key): value});
assert!(validate_admin_endpoint_stream_policy(api_format, Some(&config),).is_err());
}
}
#[test]
fn search_endpoint_accepts_non_streaming_and_unrelated_config() {
assert!(validate_admin_endpoint_stream_policy(
"openai:search",
Some(&json!({"upstream_stream_policy": "force_non_stream"})),
)
.is_ok());
assert!(validate_admin_endpoint_stream_policy(
"openai:responses",
Some(&json!({"upstream_stream_policy": "force_stream"})),
)
.is_ok());
}
}
+177 -14
View File
@@ -84,6 +84,8 @@ const OPENAI_RESPONSES_LOCAL_EXECUTION_RUNTIME_MISS_DETAIL: &str =
"当前 OpenAI Responses 请求无法在本地执行:没有匹配到可用的执行路径";
const OPENAI_RESPONSES_COMPACT_LOCAL_EXECUTION_RUNTIME_MISS_DETAIL: &str =
"当前 OpenAI Responses Compact 请求无法在本地执行:没有匹配到可用的执行路径";
const OPENAI_SEARCH_LOCAL_EXECUTION_RUNTIME_MISS_DETAIL: &str =
"当前 OpenAI Search 请求无法在本地执行:没有匹配到可用的执行路径";
const OPENAI_VIDEO_LOCAL_EXECUTION_RUNTIME_MISS_DETAIL: &str =
"当前 OpenAI Video 请求无法在本地执行:没有匹配到可用的执行路径";
const CLAUDE_MESSAGES_LOCAL_EXECUTION_RUNTIME_MISS_DETAIL: &str =
@@ -381,8 +383,9 @@ async fn maybe_forward_public_request_to_tunnel_owner(
serde_json::from_slice::<serde_json::Value>(body.as_ref()).ok()
});
let client_session_affinity =
crate::client_session_affinity::client_session_affinity_from_parts(
parts,
crate::client_session_affinity::client_session_affinity_from_api_request(
api_format,
&parts.headers,
body_json.as_ref(),
);
let Some(target) = crate::scheduler::affinity::read_cached_scheduler_affinity_target(
@@ -452,7 +455,27 @@ async fn maybe_forward_public_request_to_tunnel_owner(
owner.relay_base_url.trim_end_matches('/'),
request_context.request_path_and_query()
);
let mut upstream_request = state.client.request(parts.method.clone(), owner_url);
let is_stream =
owner_forward_request_is_stream(parts, decision, buffered_body.unwrap_or(&empty_body));
let transport_timeouts =
crate::provider_transport::resolve_transport_execution_timeouts(&transport);
let non_stream_timeout =
crate::execution_runtime::transport::resolve_non_stream_total_timeout_for_request(
is_stream,
&transport.endpoint.api_format,
transport_timeouts.as_ref(),
);
let stream_first_byte_timeout =
crate::execution_runtime::transport::resolve_stream_first_byte_timeout_for_request(
is_stream,
transport_timeouts.as_ref(),
);
let mut upstream_request = state
.owner_forward_client
.request(parts.method.clone(), owner_url);
if let Some(timeout) = non_stream_timeout {
upstream_request = upstream_request.timeout(timeout);
}
for (name, value) in &parts.headers {
if should_skip_request_header(name.as_str()) || name == http::header::HOST {
continue;
@@ -498,14 +521,15 @@ async fn maybe_forward_public_request_to_tunnel_owner(
upstream_request.header(TRUSTED_AUTH_BALANCE_HEADER, balance_remaining.to_string());
}
let upstream_response = upstream_request
.body(buffered_body.cloned().unwrap_or_default())
.send()
.await
.map_err(|err| GatewayError::UpstreamUnavailable {
trace_id: request_context.trace_id.clone(),
message: format!("owner gateway affinity forward failed: {err}"),
})?;
let upstream_response = crate::tunnel::send_owner_forward_request(
upstream_request.body(buffered_body.cloned().unwrap_or_default()),
stream_first_byte_timeout,
)
.await
.map_err(|message| GatewayError::UpstreamUnavailable {
trace_id: request_context.trace_id.clone(),
message: format!("owner gateway affinity forward failed: {message}"),
})?;
let mut response = build_sync_aware_affinity_forward_response(
request_context,
@@ -523,6 +547,29 @@ async fn maybe_forward_public_request_to_tunnel_owner(
Ok(Some(response))
}
fn owner_forward_request_is_stream(
parts: &http::request::Parts,
decision: &GatewayControlDecision,
body_bytes: &Bytes,
) -> bool {
let Some(plan_kind) =
crate::ai_serving::api::resolve_execution_runtime_stream_plan_kind(parts, decision)
else {
return false;
};
let Some((body_json, body_base64)) =
crate::ai_serving::api::parse_direct_request_body(parts, body_bytes)
else {
return false;
};
crate::ai_serving::api::is_matching_stream_request(
plan_kind,
parts,
&body_json,
body_base64.as_deref(),
)
}
fn upstream_response_is_sse(headers: &reqwest::header::HeaderMap) -> bool {
headers
.get(http::header::CONTENT_TYPE)
@@ -2196,6 +2243,7 @@ fn local_execution_runtime_miss_route_label(
"/v1/chat/completions" => "OpenAI Chat Completions",
"/v1/responses" => "OpenAI Responses",
"/v1/responses/compact" => "OpenAI Responses Compact",
"/v1/alpha/search" => "OpenAI Search",
"/v1/messages" => "Claude Messages",
path if path.starts_with("/v1/videos") => "OpenAI Video",
path if path.starts_with("/upload/v1beta/files") || path.starts_with("/v1beta/files") => {
@@ -2238,6 +2286,7 @@ fn local_execution_runtime_miss_route_detail(
"/v1/responses/compact" => {
Some(OPENAI_RESPONSES_COMPACT_LOCAL_EXECUTION_RUNTIME_MISS_DETAIL)
}
"/v1/alpha/search" => Some(OPENAI_SEARCH_LOCAL_EXECUTION_RUNTIME_MISS_DETAIL),
"/v1/messages" => Some(CLAUDE_MESSAGES_LOCAL_EXECUTION_RUNTIME_MISS_DETAIL),
path if path.starts_with("/v1/videos") => {
Some(OPENAI_VIDEO_LOCAL_EXECUTION_RUNTIME_MISS_DETAIL)
@@ -2262,15 +2311,129 @@ mod tests {
use super::{
api_key_remote_ip_allowed, buffer_and_normalize_request_body,
diagnostic_is_auth_api_key_concurrency_limited, local_execution_runtime_miss_detail,
restore_redacted_stream_execution_response, restore_redacted_sync_execution_response,
GatewayControlDecision, LocalExecutionRuntimeMissDiagnostic, RequestBodyBufferError,
RequestBodyBufferPolicy,
owner_forward_request_is_stream, restore_redacted_stream_execution_response,
restore_redacted_sync_execution_response, GatewayControlDecision,
LocalExecutionRuntimeMissDiagnostic, RequestBodyBufferError, RequestBodyBufferPolicy,
};
use axum::body::{to_bytes, Body, Bytes};
use axum::http::{header, HeaderMap, HeaderValue, Method, Response};
use serde_json::json;
use tokio::sync::Semaphore;
#[test]
fn owner_forward_uses_search_protocol_timeout_semantics() {
let request = http::Request::builder()
.method(Method::POST)
.uri("/v1/alpha/search")
.header(header::CONTENT_TYPE, "application/json")
.body(())
.expect("request should build");
let (parts, _) = request.into_parts();
let decision = GatewayControlDecision::synthetic(
"/v1/alpha/search",
Some("ai_public".to_string()),
Some("openai".to_string()),
Some("search".to_string()),
Some("openai:search".to_string()),
);
let body =
Bytes::from_static(br#"{"model":"gpt-5.6-sol","input":"find docs","stream":true}"#);
let is_stream = owner_forward_request_is_stream(&parts, &decision, &body);
let timeouts = aether_contracts::ExecutionTimeouts {
total_ms: Some(aether_contracts::MAX_EXECUTION_REQUEST_TIMEOUT_MS),
first_byte_ms: Some(10),
..aether_contracts::ExecutionTimeouts::default()
};
assert!(!is_stream);
assert_eq!(
crate::execution_runtime::transport::resolve_non_stream_total_timeout_for_request(
is_stream,
"openai:search",
Some(&timeouts),
),
Some(Duration::from_millis(
aether_contracts::MAX_EXECUTION_REQUEST_TIMEOUT_MS
))
);
assert_eq!(
crate::execution_runtime::transport::resolve_stream_first_byte_timeout_for_request(
is_stream,
Some(&timeouts),
),
None
);
}
#[test]
fn owner_forward_keeps_streaming_for_stream_capable_protocols() {
let chat_request = http::Request::builder()
.method(Method::POST)
.uri("/v1/chat/completions")
.header(header::CONTENT_TYPE, "application/json")
.body(())
.expect("request should build");
let (chat_parts, _) = chat_request.into_parts();
let chat_decision = GatewayControlDecision::synthetic(
"/v1/chat/completions",
Some("ai_public".to_string()),
Some("openai".to_string()),
Some("chat".to_string()),
Some("openai:chat".to_string()),
);
assert!(owner_forward_request_is_stream(
&chat_parts,
&chat_decision,
&Bytes::from_static(br#"{"model":"gpt-5.6-sol","stream":true}"#),
));
assert!(!owner_forward_request_is_stream(
&chat_parts,
&chat_decision,
&Bytes::from_static(br#"{"model":"gpt-5.6-sol","stream":false}"#),
));
let image_request = http::Request::builder()
.method(Method::POST)
.uri("/v1/images/generations")
.header(header::CONTENT_TYPE, "application/json")
.body(())
.expect("request should build");
let (image_parts, _) = image_request.into_parts();
let image_decision = GatewayControlDecision::synthetic(
"/v1/images/generations",
Some("ai_public".to_string()),
Some("openai".to_string()),
Some("image".to_string()),
Some("openai:image".to_string()),
);
assert!(owner_forward_request_is_stream(
&image_parts,
&image_decision,
&Bytes::from_static(br#"{"model":"gpt-image-1","stream":true}"#),
));
let compact_request = http::Request::builder()
.method(Method::POST)
.uri("/v1/responses/compact")
.header(header::CONTENT_TYPE, "application/json")
.body(())
.expect("request should build");
let (compact_parts, _) = compact_request.into_parts();
let compact_decision = GatewayControlDecision::synthetic(
"/v1/responses/compact",
Some("ai_public".to_string()),
Some("openai".to_string()),
Some("responses:compact".to_string()),
Some("openai:responses:compact".to_string()),
);
assert!(!owner_forward_request_is_stream(
&compact_parts,
&compact_decision,
&Bytes::from_static(br#"{"model":"gpt-5.6-sol","stream":true}"#),
));
}
#[test]
fn api_key_remote_ip_allows_unrestricted_keys() {
let remote_ip = "203.0.113.10".parse().expect("valid ip");
@@ -1,9 +1,8 @@
use crate::ai_serving::normalize_openai_image_quality;
use crate::async_task::CancelVideoTaskError;
use crate::control::GatewayControlDecision;
use crate::control::GatewayPublicRequestContext;
use crate::image_capabilities::{
openai_image_gateway_max_generation_count, openai_image_gateway_max_generation_count_for_model,
};
use crate::image_capabilities::openai_image_gateway_max_generation_count;
use crate::{AppState, GatewayError};
use aether_data_contracts::repository::video_tasks::{
StoredVideoTask, VideoTaskQueryFilter, VideoTaskStatus,
@@ -26,7 +25,7 @@ const OPENAI_IMAGE_PARTIAL_IMAGES_DETAIL: &str =
const OPENAI_IMAGE_STYLE_DETAIL: &str = "当前 Codex 图片反代暂不支持 style 参数";
const OPENAI_IMAGE_RESPONSE_FORMAT_DETAIL: &str = "response_format 仅支持 url 或 b64_json";
const OPENAI_IMAGE_OUTPUT_FORMAT_DETAIL: &str = "output_format 仅支持 png、jpeg 或 webp";
const OPENAI_IMAGE_QUALITY_DETAIL: &str = "quality 仅支持 low、medium、high、standard 或 hd";
const OPENAI_IMAGE_QUALITY_DETAIL: &str = "quality 仅支持 auto、low、medium、high、standard 或 hd";
const OPENAI_IMAGE_BACKGROUND_DETAIL: &str = "background 仅支持 auto、opaque 或 transparent";
const OPENAI_IMAGE_MODERATION_DETAIL: &str = "moderation 仅支持 auto 或 low";
const OPENAI_IMAGE_INPUT_FIDELITY_DETAIL: &str = "input_fidelity 仅支持 low 或 high";
@@ -303,7 +302,7 @@ fn maybe_build_local_openai_request_validation_response(
if validation
.quality
.as_deref()
.is_some_and(|value| !matches!(value, "low" | "medium" | "high" | "standard" | "hd"))
.is_some_and(|value| normalize_openai_image_quality(value).is_none())
{
return Some(build_ai_public_error_response(
http::StatusCode::BAD_REQUEST,
@@ -366,8 +365,7 @@ fn openai_image_n_detail(max_generation_count: u64) -> String {
}
fn validate_openai_image_n(validation: &OpenAiImageValidationInput) -> Option<String> {
let max_generation_count =
openai_image_gateway_max_generation_count_for_model(validation.model.as_deref());
let max_generation_count = openai_image_gateway_max_generation_count();
validation
.n
.is_some_and(|value| value == 0 || value > max_generation_count)
@@ -1761,7 +1759,7 @@ mod tests {
}
#[test]
fn image_validation_restricts_multi_image_count_to_grok_models() {
fn image_validation_applies_the_global_count_limit_before_model_mapping() {
let openai_body = Bytes::from_static(br#"{"model":"gpt-image-2","prompt":"draw","n":2}"#);
let openai_validation = parse_openai_image_validation_input(
OpenAiImageOperation::Generate,
@@ -1770,10 +1768,7 @@ mod tests {
)
.expect("valid image payload should parse");
assert_eq!(
validate_openai_image_n(&openai_validation).as_deref(),
Some("当前图片模型仅支持 n=1..1")
);
assert!(validate_openai_image_n(&openai_validation).is_none());
let grok_body =
Bytes::from_static(br#"{"model":"grok-imagine-image-lite","prompt":"draw","n":4}"#);
@@ -1785,5 +1780,28 @@ mod tests {
.expect("valid grok image payload should parse");
assert!(validate_openai_image_n(&grok_validation).is_none());
let alias_body =
Bytes::from_static(br#"{"model":"production-image-alias","prompt":"draw","n":10}"#);
let alias_validation = parse_openai_image_validation_input(
OpenAiImageOperation::Generate,
Some("application/json"),
&alias_body,
)
.expect("valid image alias payload should parse");
assert!(validate_openai_image_n(&alias_validation).is_none());
let excessive_body =
Bytes::from_static(br#"{"model":"production-image-alias","prompt":"draw","n":11}"#);
let excessive_validation = parse_openai_image_validation_input(
OpenAiImageOperation::Generate,
Some("application/json"),
&excessive_body,
)
.expect("image payload should parse before count validation");
assert_eq!(
validate_openai_image_n(&excessive_validation).as_deref(),
Some("当前图片反代仅支持 n=1..10")
);
}
}
@@ -89,6 +89,7 @@ pub(super) fn build_models_not_found_response(model_id: &str, api_format: &str)
pub(super) fn build_empty_models_list_response(api_format: &str) -> Response<Body> {
match api_format {
"openai:responses" => Json(json!({ "models": [] })).into_response(),
"claude:messages" => Json(json!({
"data": [],
"has_more": false,
@@ -101,6 +102,10 @@ pub(super) fn build_empty_models_list_response(api_format: &str) -> Response<Bod
}
}
pub(super) fn build_codex_models_list_response(models: Vec<serde_json::Value>) -> Response<Body> {
Json(json!({ "models": models })).into_response()
}
pub(super) fn build_openai_models_list_response(
rows: &[StoredMinimalCandidateSelectionRow],
) -> Response<Body> {
@@ -1,21 +1,24 @@
use std::collections::{BTreeMap, BTreeSet};
use std::fmt::Debug;
use std::future::Future;
use std::time::{Duration, SystemTime, UNIX_EPOCH};
use aether_data_contracts::repository::candidate_selection::StoredMinimalCandidateSelectionRow;
use axum::{body::Body, response::Response};
use serde_json::Value;
use tokio::time::timeout;
use tracing::warn;
use super::models_responses::{
build_claude_model_detail_response, build_claude_models_list_response,
build_empty_models_list_response, build_gemini_model_detail_response,
build_gemini_models_list_response, build_models_auth_error_response,
build_models_not_found_response, build_openai_model_detail_response,
build_openai_models_list_response,
build_codex_models_list_response, build_empty_models_list_response,
build_gemini_model_detail_response, build_gemini_models_list_response,
build_models_auth_error_response, build_models_not_found_response,
build_openai_model_detail_response, build_openai_models_list_response,
};
use super::models_shared::{
filter_rows_for_models, models_api_format, models_detail_id, models_query_api_formats,
filter_eligible_model_rows, filter_rows_for_models, models_api_format, models_detail_id,
models_query_api_formats,
};
use super::{query_param_value, AppState, GatewayPublicRequestContext};
@@ -23,6 +26,7 @@ use super::{query_param_value, AppState, GatewayPublicRequestContext};
const MODELS_ROUTE_READ_TIMEOUT: Duration = Duration::from_secs(5);
#[cfg(test)]
const MODELS_ROUTE_READ_TIMEOUT: Duration = Duration::from_millis(50);
const CODEX_MODELS_QUERY_API_FORMATS: &[&str] = &["openai:responses"];
async fn await_models_route_read<T, E, Fut>(operation: &'static str, future: Fut) -> Option<T>
where
@@ -72,7 +76,7 @@ fn build_models_read_fallback_response(
}
}
fn sort_and_dedup_model_rows(
fn sort_model_rows(
mut rows: Vec<StoredMinimalCandidateSelectionRow>,
) -> Vec<StoredMinimalCandidateSelectionRow> {
rows.sort_by(|left, right| {
@@ -85,9 +89,15 @@ fn sort_and_dedup_model_rows(
.then(left.key_id.cmp(&right.key_id))
.then(left.model_id.cmp(&right.model_id))
});
rows
}
fn sort_and_dedup_model_rows(
rows: Vec<StoredMinimalCandidateSelectionRow>,
) -> Vec<StoredMinimalCandidateSelectionRow> {
let mut deduped = Vec::with_capacity(rows.len());
let mut last_model_name: Option<String> = None;
for row in rows {
for row in sort_model_rows(rows) {
if last_model_name.as_deref() == Some(row.global_model_name.as_str()) {
continue;
}
@@ -97,22 +107,157 @@ fn sort_and_dedup_model_rows(
deduped
}
fn is_codex_models_api_format(api_format: &str) -> bool {
crate::ai_serving::normalize_api_format_alias(api_format) == "openai:responses"
}
fn is_codex_provider_row(row: &StoredMinimalCandidateSelectionRow) -> bool {
row.provider_type.trim().eq_ignore_ascii_case("codex")
}
fn codex_model_card_is_complete(card: &serde_json::Map<String, Value>) -> bool {
card.get("slug").and_then(Value::as_str).is_some()
&& card.get("display_name").and_then(Value::as_str).is_some()
&& card
.get("supported_reasoning_levels")
.and_then(Value::as_array)
.is_some()
&& card.get("shell_type").and_then(Value::as_str).is_some()
&& card.get("visibility").and_then(Value::as_str).is_some()
&& card
.get("supported_in_api")
.and_then(Value::as_bool)
.is_some()
&& card.get("priority").and_then(Value::as_i64).is_some()
&& card
.get("base_instructions")
.and_then(Value::as_str)
.is_some()
&& card
.get("supports_reasoning_summary_parameter")
.is_none_or(Value::is_boolean)
&& card
.get("support_verbosity")
.and_then(Value::as_bool)
.is_some()
&& card
.get("truncation_policy")
.and_then(Value::as_object)
.is_some()
&& card
.get("supports_parallel_tool_calls")
.and_then(Value::as_bool)
.is_some()
&& card
.get("experimental_supported_tools")
.and_then(Value::as_array)
.is_some()
}
fn project_codex_model_card(
cached_models: &[Value],
source_model: &str,
global_model: &str,
) -> Option<Value> {
let mut card = cached_models
.iter()
.find(|model| {
model.get("id").and_then(Value::as_str) == Some(source_model)
|| model.get("slug").and_then(Value::as_str) == Some(source_model)
})?
.as_object()?
.clone();
if !codex_model_card_is_complete(&card) {
return None;
}
card.remove("id");
card.remove("api_formats");
card.insert("slug".to_string(), Value::String(global_model.to_string()));
Some(Value::Object(card))
}
async fn load_codex_model_cards(
state: &AppState,
rows: &[StoredMinimalCandidateSelectionRow],
) -> Vec<Value> {
let cache_keys = rows
.iter()
.filter(|row| is_codex_provider_row(row))
.map(|row| format!("upstream_models:{}:{}", row.provider_id, row.key_id))
.collect::<BTreeSet<_>>()
.into_iter()
.collect::<Vec<_>>();
let cached_values = await_models_route_read(
"codex_models_cache",
state.runtime_state.kv_get_many(&cache_keys),
)
.await
.unwrap_or_default();
let cached_models_by_key = cache_keys
.into_iter()
.zip(cached_values)
.filter_map(|(key, raw)| {
let models = serde_json::from_str::<Vec<Value>>(raw.as_deref()?).ok()?;
Some((key, models))
})
.collect::<BTreeMap<_, _>>();
let mut seen_global_models = BTreeSet::new();
let mut cards = Vec::new();
for row in rows.iter().filter(|row| is_codex_provider_row(row)) {
if seen_global_models.contains(&row.global_model_name) {
continue;
}
let cache_key = format!("upstream_models:{}:{}", row.provider_id, row.key_id);
let Some(cached_models) = cached_models_by_key.get(&cache_key) else {
continue;
};
let source_model =
aether_scheduler_core::select_provider_model_name(row, "openai:responses");
let Some(card) = project_codex_model_card(
cached_models,
source_model.as_str(),
row.global_model_name.as_str(),
) else {
continue;
};
seen_global_models.insert(row.global_model_name.clone());
cards.push(card);
}
cards
}
async fn list_model_rows_for_client_format(
state: &AppState,
api_format: &str,
auth_snapshot: Option<&crate::data::auth::GatewayAuthApiKeySnapshot>,
) -> Option<Vec<StoredMinimalCandidateSelectionRow>> {
let mut collected = Vec::new();
for query_format in models_query_api_formats(api_format) {
let query_api_formats = if is_codex_models_api_format(api_format) {
CODEX_MODELS_QUERY_API_FORMATS
} else {
models_query_api_formats(api_format)
};
for query_format in query_api_formats {
let rows = await_models_route_read(
"candidate_selection_by_api_format",
state.list_minimal_candidate_selection_rows_for_api_format(query_format),
)
.await?;
let mut filtered = filter_rows_for_models(rows, auth_snapshot, query_format);
let mut filtered = if is_codex_models_api_format(api_format) {
filter_eligible_model_rows(rows, auth_snapshot, query_format)
} else {
filter_rows_for_models(rows, auth_snapshot, query_format)
};
collected.append(&mut filtered);
}
Some(sort_and_dedup_model_rows(collected))
if is_codex_models_api_format(api_format) {
collected.retain(is_codex_provider_row);
Some(sort_model_rows(collected))
} else {
Some(sort_and_dedup_model_rows(collected))
}
}
async fn list_model_rows_for_client_format_and_global_model(
@@ -190,6 +335,10 @@ pub(super) async fn maybe_build_local_models_route_response(
if rows.is_empty() {
return Some(build_empty_models_list_response(api_format));
}
if is_codex_models_api_format(api_format) {
let models = load_codex_model_cards(state, &rows).await;
return Some(build_codex_models_list_response(models));
}
let response = match api_format {
"claude:messages" => {
let before_id = query_param_value(
@@ -194,13 +194,12 @@ fn row_exposes_global_model_for_models(
false
}
pub(super) fn filter_rows_for_models(
pub(super) fn filter_eligible_model_rows(
rows: Vec<StoredMinimalCandidateSelectionRow>,
auth_snapshot: Option<&crate::data::auth::GatewayAuthApiKeySnapshot>,
api_format: &str,
) -> Vec<StoredMinimalCandidateSelectionRow> {
let mut filtered = rows
.into_iter()
rows.into_iter()
.filter(|row| {
auth_snapshot_allows_provider_for_models(
auth_snapshot,
@@ -211,7 +210,15 @@ pub(super) fn filter_rows_for_models(
})
.filter(|row| auth_snapshot_allows_model_for_models(auth_snapshot, &row.global_model_name))
.filter(|row| row_exposes_global_model_for_models(row, api_format))
.collect::<Vec<_>>();
.collect()
}
pub(super) fn filter_rows_for_models(
rows: Vec<StoredMinimalCandidateSelectionRow>,
auth_snapshot: Option<&crate::data::auth::GatewayAuthApiKeySnapshot>,
api_format: &str,
) -> Vec<StoredMinimalCandidateSelectionRow> {
let mut filtered = filter_eligible_model_rows(rows, auth_snapshot, api_format);
filtered.sort_by(|left, right| left.global_model_name.cmp(&right.global_model_name));
let mut deduped = Vec::new();
let mut last_model_name: Option<String> = None;
@@ -220,14 +220,7 @@ fn users_me_usage_api_format_defaults_to_non_stream(item: &StoredRequestUsageAud
let Some(value) = api_format else {
return false;
};
matches!(
crate::ai_serving::normalize_api_format_alias(value).as_str(),
"openai:chat"
| "openai:responses"
| "openai:responses:compact"
| "openai:image"
| "claude:messages"
)
crate::ai_serving::api_format_defaults_to_non_stream(value)
}
fn users_me_usage_request_body_implies_default_non_stream(item: &StoredRequestUsageAudit) -> bool {
@@ -515,6 +508,9 @@ fn build_users_me_usage_record_payload(
if let Some(service_tier) = item.provider_service_tier() {
payload["service_tier"] = json!(service_tier);
}
if let Some(actual_service_tier) = item.provider_actual_service_tier() {
payload["actual_service_tier"] = json!(actual_service_tier);
}
if include_actual_cost {
payload["actual_cost"] = json!(round_to(item.actual_total_cost_usd, 6));
payload["rate_multiplier"] = json!(rate_multiplier);
@@ -582,6 +578,9 @@ fn build_users_me_usage_active_payload(item: &StoredRequestUsageAudit) -> serde_
if let Some(service_tier) = item.provider_service_tier() {
payload["service_tier"] = json!(service_tier);
}
if let Some(actual_service_tier) = item.provider_actual_service_tier() {
payload["actual_service_tier"] = json!(actual_service_tier);
}
payload
}
@@ -1840,6 +1839,27 @@ mod tests {
assert_eq!(active_payload["client_is_stream"], false);
}
#[test]
fn user_usage_stream_defaults_to_non_stream_for_openai_search() {
let item = StoredRequestUsageAudit {
is_stream: false,
api_format: Some("openai:search".to_string()),
request_body: Some(json!({
"id": "session-search-1",
"model": "gpt-5.6-sol",
"input": "current documentation"
})),
..sample_usage("completed")
};
assert!(!users_me_usage_client_is_stream(&item));
let record_payload =
build_users_me_usage_record_payload(&item, false, &BTreeMap::new(), false);
assert_eq!(record_payload["client_requested_stream"], false);
assert_eq!(record_payload["client_is_stream"], false);
}
#[test]
fn user_usage_upstream_stream_prefers_request_metadata_flag() {
let item = StoredRequestUsageAudit {
@@ -38,7 +38,7 @@ pub(crate) fn provider_catalog_key_supports_format(
}
formats
.iter()
.any(|candidate| crate::ai_serving::api_format_alias_matches(candidate, api_format))
.any(|candidate| crate::ai_serving::api_format_permission_covers(candidate, api_format))
}
pub(crate) fn decrypt_catalog_secret_with_fallbacks(
@@ -2732,6 +2732,25 @@ mod tests {
.expect("key transport should build")
}
#[test]
fn responses_key_scope_covers_search_in_one_direction() {
let mut responses_key = sample_catalog_key();
responses_key.api_formats = Some(json!(["openai:responses"]));
assert!(provider_catalog_key_supports_format(
&responses_key,
"codex",
"openai:search",
));
let mut search_key = sample_catalog_key();
search_key.api_formats = Some(json!(["openai:search"]));
assert!(!provider_catalog_key_supports_format(
&search_key,
"codex",
"openai:responses",
));
}
#[test]
fn masked_catalog_api_key_handles_unicode_plaintext_without_panicking() {
let state = AppState::new().expect("gateway should build");