Files
Aether/apps/aether-gateway/src/tests/frontdoor/ai.rs
T

2420 lines
90 KiB
Rust

use super::{
hash_api_key, sample_models_candidate_row, unrestricted_models_snapshot,
InMemoryAuthApiKeySnapshotRepository, InMemoryMinimalCandidateSelectionReadRepository,
InMemoryVideoTaskRepository, StoredAuthApiKeySnapshot, UpsertVideoTask, VideoTaskLookupKey,
VideoTaskReadRepository, VideoTaskStatus, VideoTaskWriteRepository, DEVELOPMENT_ENCRYPTION_KEY,
};
use crate::image_capabilities::openai_image_gateway_max_generation_count;
use crate::tests::{
any, build_router_with_state, build_state_with_execution_runtime_override, json, start_server,
to_bytes, wait_until, AppState, Arc, Body, Json, Mutex, Request, Router, StatusCode,
EXECUTION_PATH_HEADER, EXECUTION_PATH_LOCAL_AI_PUBLIC,
EXECUTION_PATH_LOCAL_EXECUTION_RUNTIME_MISS,
};
use aether_contracts::{ExecutionResult, ExecutionTelemetry, ResponseBody};
use aether_crypto::encrypt_python_fernet_plaintext;
use aether_data::repository::global_models::InMemoryGlobalModelReadRepository;
use aether_data::repository::provider_catalog::InMemoryProviderCatalogReadRepository;
use aether_data::DataLayerError;
use aether_data_contracts::repository::auth::AuthApiKeyWriteRepository;
use aether_data_contracts::repository::candidate_selection::{
MinimalCandidateSelectionReadRepository, StoredMinimalCandidateSelectionRow,
StoredPoolKeyCandidateRowsByKeyIdsQuery, StoredPoolKeyCandidateRowsQuery,
StoredRequestedModelCandidateRowsQuery,
};
use aether_data_contracts::repository::global_models::{
StoredAdminGlobalModel, UpdateAdminGlobalModelRecord,
};
use aether_data_contracts::repository::provider_catalog::{
ProviderCatalogReadRepository, StoredProviderCatalogEndpoint, StoredProviderCatalogKey,
StoredProviderCatalogProvider,
};
use async_trait::async_trait;
use axum::response::IntoResponse;
use std::collections::HashMap;
use std::future::pending;
use std::sync::atomic::{AtomicBool, AtomicUsize, Ordering};
fn codex_models_snapshot(
api_key_id: &str,
user_id: &str,
allowed_models: &[&str],
) -> StoredAuthApiKeySnapshot {
StoredAuthApiKeySnapshot::new(
user_id.to_string(),
"alice".to_string(),
Some("[email protected]".to_string()),
"user".to_string(),
"local".to_string(),
true,
false,
Some(json!(["codex"])),
Some(json!(["openai:responses"])),
Some(json!(allowed_models)),
api_key_id.to_string(),
Some("codex-models".to_string()),
true,
false,
false,
Some(10),
Some(5),
Some(4_102_444_800),
Some(json!(["codex"])),
Some(json!(["openai:responses"])),
Some(json!(allowed_models)),
)
.expect("Codex models auth snapshot should build")
}
fn sample_codex_models_candidate_row(
provider_id: &str,
global_model_name: &str,
source_model_name: &str,
) -> StoredMinimalCandidateSelectionRow {
let mut row = sample_models_candidate_row(
provider_id,
"codex",
"openai:responses",
global_model_name,
10,
);
row.provider_type = "codex".to_string();
row.key_auth_type = "oauth".to_string();
row.model_provider_model_name = source_model_name.to_string();
row.model_provider_model_mappings = Some(vec![
aether_data_contracts::repository::candidate_selection::StoredProviderModelMapping {
name: source_model_name.to_string(),
priority: 1,
api_formats: Some(vec!["openai:responses".to_string()]),
endpoint_ids: None,
operations: None,
},
]);
row
}
fn complete_codex_model_card(source_model_name: &str) -> serde_json::Value {
json!({
"id": source_model_name,
"api_formats": ["openai:responses"],
"slug": source_model_name,
"display_name": "GPT-5.6-Sol",
"description": "Frontier coding model",
"default_reasoning_level": "low",
"supported_reasoning_levels": [
{"effort": "low", "description": "Low"},
{"effort": "medium", "description": "Medium"},
{"effort": "high", "description": "High"},
{"effort": "xhigh", "description": "XHigh"},
{"effort": "max", "description": "Max"},
{"effort": "ultra", "description": "Ultra"}
],
"shell_type": "shell_command",
"visibility": "list",
"supported_in_api": true,
"priority": 1,
"availability_nux": null,
"upgrade": null,
"base_instructions": "Use the current Codex instructions.",
"model_messages": null,
"available_in_plans": ["plus", "pro"],
"support_verbosity": true,
"default_verbosity": "low",
"apply_patch_tool_type": "freeform",
"truncation_policy": {"mode": "tokens", "limit": 10000},
"supports_parallel_tool_calls": true,
"experimental_supported_tools": [],
"minimal_client_version": "0.144.0",
"future_capability": {"enabled": true}
})
}
fn codex_catalog_provider(provider_id: &str) -> StoredProviderCatalogProvider {
StoredProviderCatalogProvider::new(
provider_id.to_string(),
"codex".to_string(),
Some("https://chatgpt.com".to_string()),
"codex".to_string(),
)
.expect("Codex provider should build")
}
fn codex_catalog_endpoint(provider_id: &str, endpoint_id: &str) -> StoredProviderCatalogEndpoint {
StoredProviderCatalogEndpoint::new(
endpoint_id.to_string(),
provider_id.to_string(),
"openai:responses".to_string(),
Some("openai".to_string()),
Some("responses".to_string()),
true,
)
.expect("Codex endpoint should build")
.with_transport_fields(
"https://chatgpt.example/backend-api/codex".to_string(),
None,
None,
None,
None,
None,
None,
None,
)
.expect("Codex endpoint transport should build")
}
fn codex_catalog_key(
provider_id: &str,
key_id: &str,
allowed_models: &[&str],
) -> StoredProviderCatalogKey {
let mut key = StoredProviderCatalogKey::new(
key_id.to_string(),
provider_id.to_string(),
"manual".to_string(),
"bearer".to_string(),
None,
true,
)
.expect("Codex key should build")
.with_transport_fields(
Some(json!(["openai:responses"])),
encrypt_python_fernet_plaintext(DEVELOPMENT_ENCRYPTION_KEY, "oauth-upstream-secret")
.expect("Codex test token should encrypt"),
None,
None,
None,
Some(json!(allowed_models)),
None,
None,
None,
)
.expect("Codex key transport should build");
key.auto_fetch_models = false;
key.locked_models = Some(json!(["manual-locked-model"]));
key.model_include_patterns = Some(json!(["gpt-future-*"]));
key.model_exclude_patterns = Some(json!(["gpt-future-denied"]));
key
}
fn codex_catalog_execution_result(
plan: &aether_contracts::ExecutionPlan,
status_code: u16,
body: serde_json::Value,
etag: Option<&str>,
) -> ExecutionResult {
let mut headers = std::collections::BTreeMap::from([(
"content-type".to_string(),
"application/json".to_string(),
)]);
if let Some(etag) = etag {
headers.insert("ETag".to_string(), etag.to_string());
}
ExecutionResult {
request_id: plan.request_id.clone(),
candidate_id: plan.candidate_id.clone(),
status_code,
headers,
response_observation: None,
body: Some(ResponseBody {
json_body: Some(body),
body_bytes_b64: None,
}),
telemetry: Some(ExecutionTelemetry {
ttfb_ms: Some(1),
elapsed_ms: Some(2),
upstream_bytes: None,
}),
error: None,
}
}
fn gemini_operation_status_label(status: VideoTaskStatus) -> &'static str {
match status {
VideoTaskStatus::Pending => "Pending",
VideoTaskStatus::Submitted => "Submitted",
VideoTaskStatus::Queued => "Queued",
VideoTaskStatus::Processing => "Processing",
VideoTaskStatus::Completed => "Completed",
VideoTaskStatus::Failed => "Failed",
VideoTaskStatus::Cancelled => "Cancelled",
VideoTaskStatus::Expired => "Expired",
VideoTaskStatus::Deleted => "Deleted",
}
}
fn sample_gemini_video_task(
id: &str,
short_id: &str,
user_id: &str,
api_key_id: &str,
external_task_id: &str,
status: VideoTaskStatus,
) -> UpsertVideoTask {
let completed = matches!(status, VideoTaskStatus::Completed);
UpsertVideoTask {
id: id.to_string(),
short_id: Some(short_id.to_string()),
request_id: format!("request-{id}"),
user_id: Some(user_id.to_string()),
api_key_id: Some(api_key_id.to_string()),
username: Some(format!("user-{user_id}")),
api_key_name: Some("video-key".to_string()),
external_task_id: Some(external_task_id.to_string()),
provider_id: Some("provider-gemini-video-local-1".to_string()),
endpoint_id: Some("endpoint-gemini-video-local-1".to_string()),
key_id: Some("key-gemini-video-local-1".to_string()),
client_api_format: Some("gemini:video".to_string()),
provider_api_format: Some("gemini:video".to_string()),
format_converted: false,
model: Some("veo-3".to_string()),
prompt: Some("gemini video prompt".to_string()),
original_request_body: Some(json!({"prompt": "gemini video prompt"})),
duration_seconds: Some(8),
resolution: Some("720p".to_string()),
aspect_ratio: Some("16:9".to_string()),
size: Some("720p".to_string()),
status,
progress_percent: if completed { 100 } else { 50 },
progress_message: None,
retry_count: 0,
poll_interval_seconds: 10,
next_poll_at_unix_secs: (!completed).then_some(124),
poll_count: 0,
max_poll_count: 360,
created_at_unix_ms: 123,
submitted_at_unix_secs: Some(123),
completed_at_unix_secs: completed.then_some(124),
updated_at_unix_secs: 124,
error_code: None,
error_message: None,
video_url: None,
request_metadata: Some(json!({
"rust_local_snapshot": {
"Gemini": {
"local_short_id": short_id,
"upstream_operation_name": external_task_id,
"user_id": user_id,
"api_key_id": api_key_id,
"model": "veo-3",
"status": gemini_operation_status_label(status),
"progress_percent": if completed { 100 } else { 50 },
"error_code": null,
"error_message": null,
"metadata": {},
"persistence": {
"request_id": format!("request-{id}"),
"username": format!("user-{user_id}"),
"api_key_name": "video-key",
"client_api_format": "gemini:video",
"provider_api_format": "gemini:video",
"original_request_body": {
"prompt": "gemini video prompt"
},
"format_converted": false
},
"transport": {
"upstream_base_url": "https://generativelanguage.googleapis.com",
"provider_name": "gemini-video",
"provider_id": "provider-gemini-video-local-1",
"endpoint_id": "endpoint-gemini-video-local-1",
"key_id": "key-gemini-video-local-1",
"headers": {
"x-goog-api-key": "sk-upstream-gemini-video",
"content-type": "application/json"
},
"content_type": "application/json",
"model_name": "veo-3-upstream",
"proxy": null,
"transport_profile": null,
"timeouts": null
}
}
}
})),
}
}
struct PendingMinimalCandidateSelectionReadRepository;
impl PendingMinimalCandidateSelectionReadRepository {
async fn pending_rows(
&self,
) -> Result<Vec<StoredMinimalCandidateSelectionRow>, DataLayerError> {
pending::<Result<Vec<StoredMinimalCandidateSelectionRow>, DataLayerError>>().await
}
}
#[async_trait]
impl MinimalCandidateSelectionReadRepository for PendingMinimalCandidateSelectionReadRepository {
async fn list_for_exact_api_format(
&self,
_api_format: &str,
) -> Result<Vec<StoredMinimalCandidateSelectionRow>, DataLayerError> {
self.pending_rows().await
}
async fn list_for_exact_api_format_and_global_model(
&self,
_api_format: &str,
_global_model_name: &str,
) -> Result<Vec<StoredMinimalCandidateSelectionRow>, DataLayerError> {
self.pending_rows().await
}
async fn list_for_exact_api_format_and_requested_model(
&self,
_api_format: &str,
_requested_model_name: &str,
) -> Result<Vec<StoredMinimalCandidateSelectionRow>, DataLayerError> {
self.pending_rows().await
}
async fn list_for_exact_api_format_and_requested_model_page(
&self,
_query: &StoredRequestedModelCandidateRowsQuery,
) -> Result<Vec<StoredMinimalCandidateSelectionRow>, DataLayerError> {
self.pending_rows().await
}
async fn list_pool_key_rows_for_group(
&self,
_query: &StoredPoolKeyCandidateRowsQuery,
) -> Result<Vec<StoredMinimalCandidateSelectionRow>, DataLayerError> {
self.pending_rows().await
}
async fn list_pool_key_rows_for_group_key_ids(
&self,
_query: &StoredPoolKeyCandidateRowsByKeyIdsQuery,
) -> Result<Vec<StoredMinimalCandidateSelectionRow>, DataLayerError> {
self.pending_rows().await
}
}
struct CachedToggleMinimalCandidateSelectionReadRepository {
row: StoredMinimalCandidateSelectionRow,
active: AtomicBool,
cached_rows_by_api_format: Mutex<HashMap<String, Vec<StoredMinimalCandidateSelectionRow>>>,
}
impl CachedToggleMinimalCandidateSelectionReadRepository {
fn new(row: StoredMinimalCandidateSelectionRow) -> Self {
Self {
row,
active: AtomicBool::new(true),
cached_rows_by_api_format: Mutex::new(HashMap::new()),
}
}
fn set_active(&self, active: bool) {
self.active.store(active, Ordering::SeqCst);
}
fn rows_for_api_format(&self, api_format: &str) -> Vec<StoredMinimalCandidateSelectionRow> {
let api_format = api_format.trim().to_string();
let mut cached = self
.cached_rows_by_api_format
.lock()
.expect("candidate row cache lock");
if let Some(rows) = cached.get(&api_format) {
return rows.clone();
}
let rows = if self.active.load(Ordering::SeqCst)
&& self
.row
.endpoint_api_format
.eq_ignore_ascii_case(&api_format)
{
vec![self.row.clone()]
} else {
Vec::new()
};
cached.insert(api_format, rows.clone());
rows
}
}
#[async_trait]
impl MinimalCandidateSelectionReadRepository
for CachedToggleMinimalCandidateSelectionReadRepository
{
fn clear_local_cache(&self) {
self.cached_rows_by_api_format
.lock()
.expect("candidate row cache lock")
.clear();
}
async fn list_for_exact_api_format(
&self,
api_format: &str,
) -> Result<Vec<StoredMinimalCandidateSelectionRow>, DataLayerError> {
Ok(self.rows_for_api_format(api_format))
}
async fn list_for_exact_api_format_and_global_model(
&self,
api_format: &str,
global_model_name: &str,
) -> Result<Vec<StoredMinimalCandidateSelectionRow>, DataLayerError> {
Ok(self
.rows_for_api_format(api_format)
.into_iter()
.filter(|row| row.global_model_name == global_model_name)
.collect())
}
async fn list_for_exact_api_format_and_requested_model(
&self,
api_format: &str,
requested_model_name: &str,
) -> Result<Vec<StoredMinimalCandidateSelectionRow>, DataLayerError> {
Ok(self
.rows_for_api_format(api_format)
.into_iter()
.filter(|row| row.global_model_name == requested_model_name)
.collect())
}
async fn list_for_exact_api_format_and_requested_model_page(
&self,
query: &StoredRequestedModelCandidateRowsQuery,
) -> Result<Vec<StoredMinimalCandidateSelectionRow>, DataLayerError> {
Ok(self
.rows_for_api_format(&query.api_format)
.into_iter()
.filter(|row| row.global_model_name == query.requested_model_name)
.skip(query.offset as usize)
.take(query.limit as usize)
.collect())
}
async fn list_pool_key_rows_for_group(
&self,
_query: &StoredPoolKeyCandidateRowsQuery,
) -> Result<Vec<StoredMinimalCandidateSelectionRow>, DataLayerError> {
Ok(Vec::new())
}
async fn list_pool_key_rows_for_group_key_ids(
&self,
_query: &StoredPoolKeyCandidateRowsByKeyIdsQuery,
) -> Result<Vec<StoredMinimalCandidateSelectionRow>, DataLayerError> {
Ok(Vec::new())
}
}
#[tokio::test]
async fn gateway_handles_public_openai_models_without_hitting_fallback_probe() {
let fallback_probe_hits = Arc::new(Mutex::new(0usize));
let fallback_probe_hits_clone = Arc::clone(&fallback_probe_hits);
let fallback_probe = Router::new().route(
"/{*path}",
any(move |_request: Request| {
let fallback_probe_hits_inner = Arc::clone(&fallback_probe_hits_clone);
async move {
*fallback_probe_hits_inner.lock().expect("mutex should lock") += 1;
(StatusCode::OK, Body::from("proxied"))
}
}),
);
let auth_repository = Arc::new(InMemoryAuthApiKeySnapshotRepository::seed(vec![(
Some(hash_api_key("sk-openai-models")),
unrestricted_models_snapshot("key-1", "user-1"),
)]));
let candidate_repository =
Arc::new(InMemoryMinimalCandidateSelectionReadRepository::seed(vec![
sample_models_candidate_row("provider-openai", "openai", "openai:chat", "gpt-5", 10),
sample_models_candidate_row("provider-openai", "openai", "openai:chat", "gpt-4.1", 10),
]));
let (_unused_fallback_probe_url, fallback_probe_handle) = start_server(fallback_probe).await;
let gateway = build_router_with_state(
AppState::new()
.expect("gateway should build")
.with_data_state_for_tests(
crate::data::GatewayDataState::with_minimal_candidate_selection_and_auth_for_tests(
candidate_repository,
auth_repository,
),
),
);
let (gateway_url, gateway_handle) = start_server(gateway).await;
let response = reqwest::Client::new()
.get(format!("{gateway_url}/v1/models"))
.header("authorization", "Bearer sk-openai-models")
.send()
.await
.expect("request should succeed");
assert_eq!(response.status(), StatusCode::OK);
let payload: serde_json::Value = response.json().await.expect("json body should parse");
assert_eq!(payload["object"], "list");
assert_eq!(payload["data"][0]["id"], "gpt-4.1");
assert_eq!(payload["data"][1]["id"], "gpt-5");
assert_eq!(payload["data"][0]["owned_by"], "aether");
assert_eq!(*fallback_probe_hits.lock().expect("mutex should lock"), 0);
gateway_handle.abort();
fallback_probe_handle.abort();
}
#[test]
fn gateway_versioned_models_fail_closed_when_cached_auth_becomes_unusable_or_missing() {
std::thread::Builder::new()
.name("codex-model-catalog-auth-race".to_string())
.stack_size(16 * 1024 * 1024)
.spawn(|| {
tokio::runtime::Builder::new_current_thread()
.enable_all()
.build()
.expect("Codex auth race test runtime should build")
.block_on(run_versioned_models_auth_race_scenario());
})
.expect("Codex auth race test thread should spawn")
.join()
.expect("Codex auth race test thread should finish");
}
async fn run_versioned_models_auth_race_scenario() {
let auth_repository = Arc::new(InMemoryAuthApiKeySnapshotRepository::seed(vec![(
Some(hash_api_key("sk-codex-models-auth-race")),
codex_models_snapshot(
"key-codex-models-auth-race",
"user-codex-models-auth-race",
&["future-alias"],
),
)]));
let candidate_repository = Arc::new(InMemoryMinimalCandidateSelectionReadRepository::seed(
Vec::new(),
));
let gateway = build_router_with_state(
AppState::new()
.expect("gateway should build")
.with_data_state_for_tests(
crate::data::GatewayDataState::with_minimal_candidate_selection_and_auth_for_tests(
candidate_repository,
auth_repository.clone(),
),
),
);
let (gateway_url, gateway_handle) = start_server(gateway).await;
let client = reqwest::Client::new();
let models_url = format!("{gateway_url}/v1/models?client_version=0.145.2");
let warm_response = client
.get(&models_url)
.header("authorization", "Bearer sk-codex-models-auth-race")
.send()
.await
.expect("initial versioned models request should succeed");
assert_eq!(warm_response.status(), StatusCode::OK);
assert!(auth_repository
.set_user_api_key_locked(
"user-codex-models-auth-race",
"key-codex-models-auth-race",
true,
)
.await
.expect("locking the API key should succeed"));
let locked_response = client
.get(&models_url)
.header("authorization", "Bearer sk-codex-models-auth-race")
.send()
.await
.expect("locked versioned models request should complete");
assert_eq!(locked_response.status(), StatusCode::UNAUTHORIZED);
assert!(auth_repository
.delete_user_api_key("user-codex-models-auth-race", "key-codex-models-auth-race",)
.await
.expect("deleting the API key should succeed"));
let missing_response = client
.get(&models_url)
.header("authorization", "Bearer sk-codex-models-auth-race")
.send()
.await
.expect("missing versioned models request should complete");
assert_eq!(missing_response.status(), StatusCode::UNAUTHORIZED);
gateway_handle.abort();
}
#[test]
fn gateway_serves_codex_model_cards_for_versioned_models_requests() {
std::thread::Builder::new()
.name("codex-model-catalog-frontdoor".to_string())
.stack_size(16 * 1024 * 1024)
.spawn(|| {
tokio::runtime::Builder::new_current_thread()
.enable_all()
.build()
.expect("Codex frontdoor test runtime should build")
.block_on(run_versioned_codex_model_cards_frontdoor_scenario());
})
.expect("Codex frontdoor test thread should spawn")
.join()
.expect("Codex frontdoor test thread should finish");
}
async fn run_versioned_codex_model_cards_frontdoor_scenario() {
const PROVIDER_ID: &str = "provider-codex-models";
const CATALOG_KEY_ID: &str = "key-provider-codex-models";
const CATALOG_ENDPOINT_ID: &str = "endpoint-provider-codex-models";
const SOURCE_MODELS: &[&str] = &[
"gpt-future-dynamic",
"gpt-future-legacy",
"gpt-future-second",
"gpt-hidden-direct",
];
const GLOBAL_MODELS: &[&str] = &["future-alias", "legacy-alias"];
let mut codex_rows = vec![
sample_codex_models_candidate_row(PROVIDER_ID, "future-alias", "gpt-future-dynamic"),
sample_codex_models_candidate_row(PROVIDER_ID, "legacy-alias", "gpt-future-legacy"),
sample_codex_models_candidate_row(PROVIDER_ID, "second-alias", "gpt-future-second"),
sample_codex_models_candidate_row(PROVIDER_ID, "hidden-alias", "gpt-hidden-direct"),
];
for row in &mut codex_rows {
row.key_allowed_models = Some(
SOURCE_MODELS
.iter()
.map(|value| value.to_string())
.collect(),
);
}
let mut all_candidate_rows = codex_rows.clone();
all_candidate_rows.push(sample_models_candidate_row(
"provider-openai-responses",
"openai",
"openai:responses",
"custom-responses-model",
20,
));
let candidate_repository = Arc::new(InMemoryMinimalCandidateSelectionReadRepository::seed(
all_candidate_rows,
));
let auth_repository = Arc::new(InMemoryAuthApiKeySnapshotRepository::seed(vec![
(
Some(hash_api_key("sk-codex-models")),
codex_models_snapshot("key-codex-models", "user-codex-models", GLOBAL_MODELS),
),
(
Some(hash_api_key("sk-standard-models")),
unrestricted_models_snapshot("key-standard-models", "user-standard-models"),
),
(
Some(hash_api_key("sk-codex-legacy-only")),
codex_models_snapshot(
"key-codex-legacy-only",
"user-codex-legacy-only",
&["legacy-alias"],
),
),
(
Some(hash_api_key("sk-codex-hidden-mixed")),
codex_models_snapshot(
"key-codex-hidden-mixed",
"user-codex-hidden-mixed",
&["future-alias", "hidden-alias"],
),
),
(
Some(hash_api_key("sk-codex-hidden-only")),
codex_models_snapshot(
"key-codex-hidden-only",
"user-codex-hidden-only",
&["hidden-alias"],
),
),
(
Some(hash_api_key("sk-codex-second-mixed")),
codex_models_snapshot(
"key-codex-second-mixed",
"user-codex-second-mixed",
&["future-alias", "second-alias"],
),
),
]));
let original_catalog_key = codex_catalog_key(PROVIDER_ID, CATALOG_KEY_ID, SOURCE_MODELS);
assert!(!original_catalog_key.auto_fetch_models);
let provider_catalog_repository = Arc::new(InMemoryProviderCatalogReadRepository::seed(
vec![codex_catalog_provider(PROVIDER_ID)],
vec![codex_catalog_endpoint(PROVIDER_ID, CATALOG_ENDPOINT_ID)],
vec![original_catalog_key.clone()],
));
let rows_before = candidate_repository
.list_for_exact_api_format("openai:responses")
.await
.expect("candidate rows should load before request");
let catalog_generation = Arc::new(AtomicUsize::new(0));
let catalog_hits = Arc::new(AtomicUsize::new(0));
let captured_plans = Arc::new(Mutex::new(Vec::<(String, Option<String>)>::new()));
let generation_for_runtime = Arc::clone(&catalog_generation);
let hits_for_runtime = Arc::clone(&catalog_hits);
let plans_for_runtime = Arc::clone(&captured_plans);
let execution_runtime = Router::new().route(
"/v1/execute/sync",
any(move |request: Request| {
let generation_for_request = Arc::clone(&generation_for_runtime);
let hits_for_request = Arc::clone(&hits_for_runtime);
let plans_for_request = Arc::clone(&plans_for_runtime);
async move {
let (_parts, body) = request.into_parts();
let raw_body = to_bytes(body, usize::MAX)
.await
.expect("execution runtime request body should read");
let plan: aether_contracts::ExecutionPlan =
serde_json::from_slice(&raw_body).expect("execution runtime plan should parse");
plans_for_request
.lock()
.expect("plans mutex")
.push((plan.url.clone(), plan.headers.get("user-agent").cloned()));
if plan.url.contains("/models?") {
hits_for_request.fetch_add(1, Ordering::SeqCst);
let generation = generation_for_request.load(Ordering::SeqCst);
if generation == 1 {
return Json(codex_catalog_execution_result(
&plan,
503,
json!({"error":{"message":"temporary catalog outage"}}),
None,
));
}
let mut current = complete_codex_model_card("gpt-future-dynamic");
let current_object = current.as_object_mut().expect("current card object");
current_object.remove("base_instructions");
current_object.insert(
"model_messages".to_string(),
json!({"instructions_template":"Use future dynamic instructions."}),
);
current_object.insert(
"future_capability".to_string(),
json!({"mode":"opaque-current"}),
);
let mut legacy = complete_codex_model_card("gpt-future-legacy");
legacy["base_instructions"] = json!("Use legacy future instructions.");
legacy["future_capability"] = json!({"mode":"opaque-legacy"});
let mut models = vec![current, legacy];
if generation >= 2 {
let mut second = complete_codex_model_card("gpt-future-second");
second
.as_object_mut()
.expect("second card object")
.remove("base_instructions");
second["model_messages"] =
json!({"instructions_template":"Use second future instructions."});
second["future_capability"] = json!({"mode":"added-without-code-change"});
models.push(second);
models.push(complete_codex_model_card("gpt-future-unmapped"));
}
let etag = if generation >= 2 {
"\"catalog-etag-v2\""
} else {
"\"catalog-etag-v1\""
};
return Json(codex_catalog_execution_result(
&plan,
200,
json!({"models": models, "future_top_level": true}),
Some(etag),
));
}
Json(codex_catalog_execution_result(
&plan,
200,
json!({
"id": "resp-future-dynamic",
"object": "response",
"model": "gpt-future-dynamic",
"output": [],
"usage": {
"input_tokens": 1,
"output_tokens": 2,
"total_tokens": 3
}
}),
Some("\"catalog-etag-v2\""),
))
}
}),
);
let (execution_runtime_url, execution_runtime_handle) = start_server(execution_runtime).await;
let state = build_state_with_execution_runtime_override(execution_runtime_url)
.with_data_state_for_tests(
crate::data::GatewayDataState::with_minimal_candidate_selection_and_auth_for_tests(
candidate_repository.clone(),
auth_repository,
)
.attach_provider_catalog_repository_for_tests(provider_catalog_repository.clone())
.with_encryption_key_for_tests(DEVELOPMENT_ENCRYPTION_KEY),
);
let configured_rows = state
.list_minimal_candidate_selection_rows_for_api_format("openai:responses")
.await
.expect("configured Codex candidate rows should be readable");
assert_eq!(
configured_rows
.iter()
.filter(|row| row.provider_type == "codex")
.count(),
codex_rows.len()
);
let resolved_auth =
aether_data_contracts::repository::auth::ResolvedAuthApiKeySnapshot::from_stored(
codex_models_snapshot("key-codex-models", "user-codex-models", GLOBAL_MODELS),
std::time::SystemTime::now()
.duration_since(std::time::UNIX_EPOCH)
.unwrap_or_default()
.as_secs(),
);
let eligible_rows = crate::handlers::public::filter_eligible_model_rows(
configured_rows.clone(),
Some(&resolved_auth),
"openai:responses",
);
assert_eq!(
eligible_rows
.iter()
.filter(|row| row.provider_type == "codex")
.count(),
GLOBAL_MODELS.len(),
"Codex fixture rows must survive the same provider/model/key authorization filters as the route"
);
let actual_auth = state
.data
.read_auth_api_key_snapshot(
"user-codex-models",
"key-codex-models",
std::time::SystemTime::now()
.duration_since(std::time::UNIX_EPOCH)
.unwrap_or_default()
.as_secs(),
)
.await
.expect("Codex auth snapshot read should succeed")
.expect("Codex auth snapshot should exist");
assert_eq!(
crate::handlers::public::filter_eligible_model_rows(
configured_rows.clone(),
Some(&actual_auth),
"openai:responses",
)
.iter()
.filter(|row| row.provider_type == "codex")
.count(),
GLOBAL_MODELS.len(),
"stored Codex auth snapshot must preserve every authorized manual mapping"
);
assert!(
<AppState as crate::model_fetch::CodexCatalogRuntime>::read_codex_catalog_transport_snapshot(
&state,
PROVIDER_ID,
CATALOG_ENDPOINT_ID,
CATALOG_KEY_ID,
)
.await
.expect("Codex catalog transport lookup should succeed")
.is_some(),
"Codex catalog transport must be available even when auto_fetch_models is disabled"
);
let gateway = build_router_with_state(state);
let (gateway_url, gateway_handle) = start_server(gateway).await;
let client = reqwest::Client::new();
let codex_response = client
.get(format!(
"{gateway_url}/v1/models?client_version=0.145.2-beta.7%2Bdesktop.9"
))
.header("authorization", "Bearer sk-codex-models")
.send()
.await
.expect("Codex models request should succeed");
assert_eq!(codex_response.status(), StatusCode::OK);
let codex_etag = codex_response
.headers()
.get(http::header::ETAG)
.and_then(|value| value.to_str().ok())
.map(ToOwned::to_owned);
let codex_payload: serde_json::Value = codex_response
.json()
.await
.expect("Codex models body should parse");
assert_eq!(
catalog_hits.load(Ordering::SeqCst),
1,
"cold Codex request must reach the upstream catalog once; payload={codex_payload}"
);
assert_eq!(codex_etag.as_deref(), Some("\"catalog-etag-v1\""));
assert_eq!(codex_payload["models"].as_array().map(Vec::len), Some(2));
let current_card = codex_payload["models"]
.as_array()
.and_then(|models| models.iter().find(|model| model["slug"] == "future-alias"))
.expect("current model card should be projected");
assert_eq!(
current_card["model_messages"]["instructions_template"],
"Use future dynamic instructions."
);
assert_eq!(
current_card["future_capability"],
json!({"mode":"opaque-current"})
);
assert_eq!(current_card["available_in_plans"], json!(["plus", "pro"]));
assert!(current_card.get("base_instructions").is_none());
assert!(current_card.get("id").is_none());
assert!(current_card.get("api_formats").is_none());
let legacy_card = codex_payload["models"]
.as_array()
.and_then(|models| models.iter().find(|model| model["slug"] == "legacy-alias"))
.expect("legacy model card should be projected");
assert_eq!(
legacy_card["base_instructions"],
"Use legacy future instructions."
);
assert_eq!(
legacy_card["future_capability"],
json!({"mode":"opaque-legacy"})
);
assert!(codex_payload["models"]
.as_array()
.is_some_and(
|models| models.iter().all(|model| model["slug"] != "hidden-alias"
&& model["slug"] != "second-alias"
&& model["slug"] != "gpt-future-unmapped")
));
assert!(codex_payload.get("object").is_none());
assert_eq!(catalog_hits.load(Ordering::SeqCst), 1);
let restricted_response = client
.get(format!("{gateway_url}/v1/models?client_version=0.145.2"))
.header("authorization", "Bearer sk-codex-legacy-only")
.send()
.await
.expect("restricted Codex models request should succeed");
assert_eq!(restricted_response.status(), StatusCode::OK);
let restricted_payload: serde_json::Value = restricted_response
.json()
.await
.expect("restricted Codex models body should parse");
assert_eq!(
restricted_payload["models"].as_array().map(|models| models
.iter()
.map(|model| model["slug"].as_str().unwrap_or_default())
.collect::<Vec<_>>()),
Some(vec!["legacy-alias"])
);
assert_eq!(catalog_hits.load(Ordering::SeqCst), 1);
let incomplete_authorized_response = client
.get(format!("{gateway_url}/v1/models?client_version=0.145.2"))
.header("authorization", "Bearer sk-codex-hidden-mixed")
.send()
.await
.expect("incomplete authorized Codex catalog request should succeed");
assert_eq!(incomplete_authorized_response.status(), StatusCode::OK);
assert_eq!(
incomplete_authorized_response
.headers()
.get(http::header::ETAG)
.and_then(|value| value.to_str().ok()),
Some("\"catalog-etag-v1\"")
);
let incomplete_authorized_payload: serde_json::Value = incomplete_authorized_response
.json()
.await
.expect("incomplete authorized Codex body should parse");
assert_eq!(
incomplete_authorized_payload["models"]
.as_array()
.map(|models| models
.iter()
.map(|model| model["slug"].as_str().unwrap_or_default())
.collect::<Vec<_>>()),
Some(vec!["future-alias"]),
"one hidden or not-yet-described mapping must not erase valid dynamic cards"
);
assert_eq!(catalog_hits.load(Ordering::SeqCst), 1);
let hidden_only_response = client
.get(format!("{gateway_url}/v1/models?client_version=0.145.2"))
.header("authorization", "Bearer sk-codex-hidden-only")
.send()
.await
.expect("hidden-only authorized Codex catalog request should succeed");
assert_eq!(hidden_only_response.status(), StatusCode::OK);
assert!(hidden_only_response
.headers()
.get(http::header::ETAG)
.is_none());
let hidden_only_payload: serde_json::Value = hidden_only_response
.json()
.await
.expect("hidden-only authorized Codex body should parse");
assert_eq!(
hidden_only_payload["models"].as_array().map(Vec::len),
Some(0),
"a model absent from the authoritative upstream catalog must not receive a fabricated card"
);
assert_eq!(catalog_hits.load(Ordering::SeqCst), 1);
let pending_second_response = client
.get(format!("{gateway_url}/v1/models?client_version=0.145.2"))
.header("authorization", "Bearer sk-codex-second-mixed")
.send()
.await
.expect("not-yet-published authorized model request should succeed");
assert_eq!(pending_second_response.status(), StatusCode::OK);
let pending_second_payload: serde_json::Value = pending_second_response
.json()
.await
.expect("not-yet-published authorized model body should parse");
assert_eq!(
pending_second_payload["models"]
.as_array()
.map(|models| models
.iter()
.map(|model| model["slug"].as_str().unwrap_or_default())
.collect::<Vec<_>>()),
Some(vec!["future-alias"])
);
assert_eq!(catalog_hits.load(Ordering::SeqCst), 1);
let captured_catalog_plan = captured_plans
.lock()
.expect("plans mutex")
.iter()
.find(|(url, _)| url.contains("/models?"))
.cloned()
.expect("catalog execution plan should be captured");
assert_eq!(
captured_catalog_plan.0,
"https://chatgpt.example/backend-api/codex/models?client_version=0.145.2"
);
assert_eq!(
captured_catalog_plan.1.as_deref(),
Some("codex_cli_rs/0.145.2")
);
let fresh_response = client
.get(format!("{gateway_url}/v1/models?client_version=0.145.2"))
.header("authorization", "Bearer sk-codex-models")
.send()
.await
.expect("fresh Codex models request should succeed");
assert_eq!(fresh_response.status(), StatusCode::OK);
assert_eq!(catalog_hits.load(Ordering::SeqCst), 1);
tokio::time::sleep(std::time::Duration::from_millis(1_100)).await;
catalog_generation.store(1, Ordering::SeqCst);
let stale_started = std::time::Instant::now();
let stale_response = client
.get(format!("{gateway_url}/v1/models?client_version=0.145.2"))
.header("authorization", "Bearer sk-codex-models")
.send()
.await
.expect("stale Codex models request should succeed");
assert_eq!(stale_response.status(), StatusCode::OK);
assert!(stale_started.elapsed() < std::time::Duration::from_millis(400));
let stale_payload: serde_json::Value = stale_response
.json()
.await
.expect("stale body should parse");
assert!(stale_payload["models"]
.as_array()
.is_some_and(|models| models.iter().any(|model| model["slug"] == "future-alias")));
wait_until(1_000, || catalog_hits.load(Ordering::SeqCst) >= 2).await;
let failed_refresh_lkg_response = client
.get(format!("{gateway_url}/v1/models?client_version=0.145.2"))
.header("authorization", "Bearer sk-codex-models")
.send()
.await
.expect("failed refresh should keep serving LKG");
let failed_refresh_lkg_payload: serde_json::Value = failed_refresh_lkg_response
.json()
.await
.expect("failed refresh LKG body should parse");
assert!(failed_refresh_lkg_payload["models"]
.as_array()
.is_some_and(|models| models.iter().any(|model| model["slug"] == "future-alias")));
assert_eq!(catalog_hits.load(Ordering::SeqCst), 2);
tokio::time::sleep(std::time::Duration::from_millis(150)).await;
catalog_generation.store(2, Ordering::SeqCst);
let refresh_trigger = client
.get(format!("{gateway_url}/v1/models?client_version=0.145.2"))
.header("authorization", "Bearer sk-codex-models")
.send()
.await
.expect("recovered refresh trigger should succeed");
assert_eq!(refresh_trigger.status(), StatusCode::OK);
wait_until(1_000, || catalog_hits.load(Ordering::SeqCst) >= 3).await;
let updated_response = client
.get(format!("{gateway_url}/v1/models?client_version=0.145.2"))
.header("authorization", "Bearer sk-codex-second-mixed")
.send()
.await
.expect("updated catalog request should succeed");
assert_eq!(
updated_response
.headers()
.get(http::header::ETAG)
.and_then(|value| value.to_str().ok()),
Some("\"catalog-etag-v2\"")
);
let updated_payload: serde_json::Value = updated_response
.json()
.await
.expect("updated body should parse");
assert!(updated_payload["models"]
.as_array()
.is_some_and(|models| models.iter().any(|model| {
model["slug"] == "second-alias"
&& model["future_capability"] == json!({"mode":"added-without-code-change"})
})));
assert!(updated_payload["models"]
.as_array()
.is_some_and(|models| models.iter().all(|model| {
model["slug"] != "hidden-alias" && model["slug"] != "gpt-future-unmapped"
})));
let stored_keys = provider_catalog_repository
.list_keys_by_ids(&[CATALOG_KEY_ID.to_string()])
.await
.expect("catalog key should remain readable");
assert_eq!(stored_keys.as_slice(), &[original_catalog_key]);
let rows_after = candidate_repository
.list_for_exact_api_format("openai:responses")
.await
.expect("candidate rows should load after request");
assert_eq!(rows_after, rows_before);
let inference_response = client
.post(format!("{gateway_url}/v1/responses"))
.header(http::header::CONTENT_TYPE, "application/json")
.header("authorization", "Bearer sk-codex-models")
.body(r#"{"model":"future-alias","input":"hello","store":false}"#)
.send()
.await
.expect("manual alias inference should succeed");
assert_eq!(inference_response.status(), StatusCode::OK);
let inference_payload: serde_json::Value = inference_response
.json()
.await
.expect("inference body should parse");
assert_eq!(inference_payload["model"], "gpt-future-dynamic");
let standard_response = client
.get(format!("{gateway_url}/v1/models"))
.header("authorization", "Bearer sk-standard-models")
.send()
.await
.expect("standard models request should succeed");
assert_eq!(standard_response.status(), StatusCode::OK);
let standard_payload: serde_json::Value = standard_response
.json()
.await
.expect("standard models body should parse");
assert_eq!(standard_payload["object"], "list");
assert!(standard_payload["data"].is_array());
assert!(standard_payload.get("models").is_none());
gateway_handle.abort();
execution_runtime_handle.abort();
}
#[tokio::test]
async fn gateway_openai_models_list_drops_disabled_global_model_after_cache_invalidation() {
let auth_repository = Arc::new(InMemoryAuthApiKeySnapshotRepository::seed(vec![(
Some(hash_api_key("sk-openai-models-cache")),
unrestricted_models_snapshot("key-models-cache", "user-models-cache"),
)]));
let row = sample_models_candidate_row(
"provider-openai-cache",
"openai",
"openai:chat",
"gpt-5",
10,
);
let global_model_id = row.global_model_id.clone();
let candidate_repository = Arc::new(CachedToggleMinimalCandidateSelectionReadRepository::new(
row.clone(),
));
let global_model_repository = Arc::new(
InMemoryGlobalModelReadRepository::seed(Vec::new()).with_admin_global_models(vec![
StoredAdminGlobalModel::new(
global_model_id.clone(),
row.global_model_name.clone(),
"GPT 5".to_string(),
true,
None,
None,
None,
None,
0,
1,
0,
Some(1_711_000_000),
Some(1_711_000_000),
)
.expect("global model should build"),
]),
);
let state = AppState::new()
.expect("gateway should build")
.with_data_state_for_tests(
crate::data::GatewayDataState::with_minimal_candidate_selection_and_auth_for_tests(
candidate_repository.clone(),
auth_repository,
)
.with_global_model_repository_for_tests(global_model_repository),
);
let gateway = build_router_with_state(state.clone());
let (gateway_url, gateway_handle) = start_server(gateway).await;
let client = reqwest::Client::new();
let response = client
.get(format!("{gateway_url}/v1/models"))
.header("authorization", "Bearer sk-openai-models-cache")
.send()
.await
.expect("initial models request should succeed");
assert_eq!(response.status(), StatusCode::OK);
let payload: serde_json::Value = response.json().await.expect("json body should parse");
assert_eq!(payload["data"][0]["id"], "gpt-5");
candidate_repository.set_active(false);
let disabled_global_model = UpdateAdminGlobalModelRecord::new(
global_model_id,
"GPT 5".to_string(),
false,
None,
None,
None,
None,
)
.expect("global model update record should build");
state
.update_admin_global_model(&disabled_global_model)
.await
.expect("global model update should succeed")
.expect("global model should update");
let response = client
.get(format!("{gateway_url}/v1/models"))
.header("authorization", "Bearer sk-openai-models-cache")
.send()
.await
.expect("models request after disable should succeed");
assert_eq!(response.status(), StatusCode::OK);
let payload: serde_json::Value = response.json().await.expect("json body should parse");
assert_eq!(
payload["data"]
.as_array()
.expect("data should be an array")
.len(),
0
);
gateway_handle.abort();
}
#[tokio::test]
async fn gateway_returns_empty_openai_models_when_candidate_rows_stall() {
let fallback_probe_hits = Arc::new(Mutex::new(0usize));
let fallback_probe_hits_clone = Arc::clone(&fallback_probe_hits);
let fallback_probe = Router::new().route(
"/{*path}",
any(move |_request: Request| {
let fallback_probe_hits_inner = Arc::clone(&fallback_probe_hits_clone);
async move {
*fallback_probe_hits_inner.lock().expect("mutex should lock") += 1;
(StatusCode::OK, Body::from("proxied"))
}
}),
);
let auth_repository = Arc::new(InMemoryAuthApiKeySnapshotRepository::seed(vec![(
Some(hash_api_key("sk-openai-models-stalled")),
unrestricted_models_snapshot("key-stalled", "user-stalled"),
)]));
let candidate_repository = Arc::new(PendingMinimalCandidateSelectionReadRepository);
let (_unused_fallback_probe_url, fallback_probe_handle) = start_server(fallback_probe).await;
let gateway = build_router_with_state(
AppState::new()
.expect("gateway should build")
.with_data_state_for_tests(
crate::data::GatewayDataState::with_minimal_candidate_selection_and_auth_for_tests(
candidate_repository,
auth_repository,
),
),
);
let (gateway_url, gateway_handle) = start_server(gateway).await;
let response = reqwest::Client::builder()
.timeout(std::time::Duration::from_secs(3))
.build()
.expect("client should build")
.get(format!("{gateway_url}/v1/models"))
.header("authorization", "Bearer sk-openai-models-stalled")
.send()
.await
.expect("request should return before client timeout");
assert_eq!(response.status(), StatusCode::OK);
let payload: serde_json::Value = response.json().await.expect("json body should parse");
assert_eq!(payload["object"], "list");
assert_eq!(
payload["data"]
.as_array()
.expect("data should be an array")
.len(),
0
);
assert_eq!(*fallback_probe_hits.lock().expect("mutex should lock"), 0);
gateway_handle.abort();
fallback_probe_handle.abort();
}
#[tokio::test]
async fn gateway_returns_not_found_for_openai_model_detail_when_candidate_rows_stall() {
let fallback_probe_hits = Arc::new(Mutex::new(0usize));
let fallback_probe_hits_clone = Arc::clone(&fallback_probe_hits);
let fallback_probe = Router::new().route(
"/{*path}",
any(move |_request: Request| {
let fallback_probe_hits_inner = Arc::clone(&fallback_probe_hits_clone);
async move {
*fallback_probe_hits_inner.lock().expect("mutex should lock") += 1;
(StatusCode::OK, Body::from("proxied"))
}
}),
);
let auth_repository = Arc::new(InMemoryAuthApiKeySnapshotRepository::seed(vec![(
Some(hash_api_key("sk-openai-model-detail-stalled")),
unrestricted_models_snapshot("key-detail-stalled", "user-detail-stalled"),
)]));
let candidate_repository = Arc::new(PendingMinimalCandidateSelectionReadRepository);
let (_unused_fallback_probe_url, fallback_probe_handle) = start_server(fallback_probe).await;
let gateway = build_router_with_state(
AppState::new()
.expect("gateway should build")
.with_data_state_for_tests(
crate::data::GatewayDataState::with_minimal_candidate_selection_and_auth_for_tests(
candidate_repository,
auth_repository,
),
),
);
let (gateway_url, gateway_handle) = start_server(gateway).await;
let response = reqwest::Client::builder()
.timeout(std::time::Duration::from_secs(3))
.build()
.expect("client should build")
.get(format!("{gateway_url}/v1/models/gpt-stalled"))
.header("authorization", "Bearer sk-openai-model-detail-stalled")
.send()
.await
.expect("request should return before client timeout");
assert_eq!(response.status(), StatusCode::NOT_FOUND);
let payload: serde_json::Value = response.json().await.expect("json body should parse");
assert_eq!(payload["error"]["code"], "model_not_found");
assert_eq!(*fallback_probe_hits.lock().expect("mutex should lock"), 0);
gateway_handle.abort();
fallback_probe_handle.abort();
}
#[tokio::test]
async fn gateway_handles_public_openai_models_with_cross_format_candidates_without_hitting_fallback_probe(
) {
let fallback_probe_hits = Arc::new(Mutex::new(0usize));
let fallback_probe_hits_clone = Arc::clone(&fallback_probe_hits);
let fallback_probe = Router::new().route(
"/{*path}",
any(move |_request: Request| {
let fallback_probe_hits_inner = Arc::clone(&fallback_probe_hits_clone);
async move {
*fallback_probe_hits_inner.lock().expect("mutex should lock") += 1;
(StatusCode::OK, Body::from("proxied"))
}
}),
);
let auth_repository = Arc::new(InMemoryAuthApiKeySnapshotRepository::seed(vec![(
Some(hash_api_key("sk-openai-models-cross-format")),
unrestricted_models_snapshot("key-1", "user-1"),
)]));
let candidate_repository =
Arc::new(InMemoryMinimalCandidateSelectionReadRepository::seed(vec![
sample_models_candidate_row(
"provider-claude",
"claude",
"claude:messages",
"claude-3-7-sonnet",
10,
),
]));
let (_unused_fallback_probe_url, fallback_probe_handle) = start_server(fallback_probe).await;
let gateway = build_router_with_state(
AppState::new()
.expect("gateway should build")
.with_data_state_for_tests(
crate::data::GatewayDataState::with_minimal_candidate_selection_and_auth_for_tests(
candidate_repository,
auth_repository,
),
),
);
let (gateway_url, gateway_handle) = start_server(gateway).await;
let client = reqwest::Client::new();
let list_response = client
.get(format!("{gateway_url}/v1/models"))
.header("authorization", "Bearer sk-openai-models-cross-format")
.send()
.await
.expect("request should succeed");
assert_eq!(list_response.status(), StatusCode::OK);
let list_payload: serde_json::Value =
list_response.json().await.expect("json body should parse");
assert_eq!(list_payload["object"], "list");
assert_eq!(list_payload["data"][0]["id"], "claude-3-7-sonnet");
assert_eq!(list_payload["data"][0]["owned_by"], "aether");
let detail_response = client
.get(format!("{gateway_url}/v1/models/claude-3-7-sonnet"))
.header("authorization", "Bearer sk-openai-models-cross-format")
.send()
.await
.expect("request should succeed");
assert_eq!(detail_response.status(), StatusCode::OK);
let detail_payload: serde_json::Value = detail_response
.json()
.await
.expect("json body should parse");
assert_eq!(detail_payload["id"], "claude-3-7-sonnet");
assert_eq!(detail_payload["owned_by"], "aether");
assert_eq!(*fallback_probe_hits.lock().expect("mutex should lock"), 0);
gateway_handle.abort();
fallback_probe_handle.abort();
}
#[tokio::test]
async fn gateway_handles_public_claude_models_without_hitting_fallback_probe() {
let fallback_probe_hits = Arc::new(Mutex::new(0usize));
let fallback_probe_hits_clone = Arc::clone(&fallback_probe_hits);
let fallback_probe = Router::new().route(
"/{*path}",
any(move |_request: Request| {
let fallback_probe_hits_inner = Arc::clone(&fallback_probe_hits_clone);
async move {
*fallback_probe_hits_inner.lock().expect("mutex should lock") += 1;
(StatusCode::OK, Json(json!({"proxied": true}))).into_response()
}
}),
);
let auth_repository = Arc::new(InMemoryAuthApiKeySnapshotRepository::seed(vec![(
Some(hash_api_key("sk-claude-models")),
unrestricted_models_snapshot("key-claude", "user-claude"),
)]));
let candidate_repository =
Arc::new(InMemoryMinimalCandidateSelectionReadRepository::seed(vec![
sample_models_candidate_row(
"provider-claude",
"claude",
"claude:messages",
"claude-3-7-sonnet",
10,
),
sample_models_candidate_row(
"provider-claude",
"claude",
"claude:messages",
"claude-3-5-haiku",
10,
),
]));
let (_unused_fallback_probe_url, fallback_probe_handle) = start_server(fallback_probe).await;
let gateway = build_router_with_state(
AppState::new()
.expect("gateway should build")
.with_data_state_for_tests(
crate::data::GatewayDataState::with_minimal_candidate_selection_and_auth_for_tests(
candidate_repository,
auth_repository,
),
),
);
let (gateway_url, gateway_handle) = start_server(gateway).await;
let response = reqwest::Client::new()
.get(format!("{gateway_url}/v1/models?limit=1"))
.header("x-api-key", "sk-claude-models")
.header("anthropic-version", "2023-06-01")
.send()
.await
.expect("request should succeed");
assert_eq!(response.status(), StatusCode::OK);
let payload: serde_json::Value = response.json().await.expect("json body should parse");
assert_eq!(payload["data"][0]["id"], "claude-3-5-haiku");
assert_eq!(payload["first_id"], "claude-3-5-haiku");
assert_eq!(payload["last_id"], "claude-3-5-haiku");
assert_eq!(payload["has_more"], true);
assert_eq!(*fallback_probe_hits.lock().expect("mutex should lock"), 0);
gateway_handle.abort();
fallback_probe_handle.abort();
}
#[tokio::test]
async fn gateway_handles_public_gemini_models_without_hitting_fallback_probe() {
let fallback_probe_hits = Arc::new(Mutex::new(0usize));
let fallback_probe_hits_clone = Arc::clone(&fallback_probe_hits);
let fallback_probe = Router::new().route(
"/{*path}",
any(move |_request: Request| {
let fallback_probe_hits_inner = Arc::clone(&fallback_probe_hits_clone);
async move {
*fallback_probe_hits_inner.lock().expect("mutex should lock") += 1;
(StatusCode::OK, Json(json!({"proxied": true}))).into_response()
}
}),
);
let auth_repository = Arc::new(InMemoryAuthApiKeySnapshotRepository::seed(vec![(
Some(hash_api_key("sk-gemini-models")),
unrestricted_models_snapshot("key-gemini", "user-gemini"),
)]));
let candidate_repository =
Arc::new(InMemoryMinimalCandidateSelectionReadRepository::seed(vec![
sample_models_candidate_row(
"provider-gemini",
"gemini",
"gemini:generate_content",
"gemini-2.5-flash",
10,
),
sample_models_candidate_row(
"provider-gemini",
"gemini",
"gemini:generate_content",
"gemini-2.5-pro",
10,
),
]));
let (_unused_fallback_probe_url, fallback_probe_handle) = start_server(fallback_probe).await;
let gateway = build_router_with_state(
AppState::new()
.expect("gateway should build")
.with_data_state_for_tests(
crate::data::GatewayDataState::with_minimal_candidate_selection_and_auth_for_tests(
candidate_repository,
auth_repository,
),
),
);
let (gateway_url, gateway_handle) = start_server(gateway).await;
let response = reqwest::Client::new()
.get(format!(
"{gateway_url}/v1beta/models?pageSize=1&key=sk-gemini-models"
))
.send()
.await
.expect("request should succeed");
assert_eq!(response.status(), StatusCode::OK);
let payload: serde_json::Value = response.json().await.expect("json body should parse");
assert_eq!(payload["models"][0]["name"], "models/gemini-2.5-flash");
assert_eq!(payload["nextPageToken"], "1");
assert_eq!(*fallback_probe_hits.lock().expect("mutex should lock"), 0);
gateway_handle.abort();
fallback_probe_handle.abort();
}
#[tokio::test]
async fn gateway_handles_antigravity_v1internal_control_plane_without_proxying() {
let fallback_probe_hits = Arc::new(Mutex::new(0usize));
let fallback_probe_hits_clone = Arc::clone(&fallback_probe_hits);
let fallback_probe = Router::new().route(
"/{*path}",
any(move |_request: Request| {
let fallback_probe_hits_inner = Arc::clone(&fallback_probe_hits_clone);
async move {
*fallback_probe_hits_inner.lock().expect("mutex should lock") += 1;
(StatusCode::OK, Json(json!({"proxied": true}))).into_response()
}
}),
);
let (_unused_fallback_probe_url, fallback_probe_handle) = start_server(fallback_probe).await;
let gateway = build_router_with_state(AppState::new().expect("gateway should build"));
let (gateway_url, gateway_handle) = start_server(gateway).await;
let client = reqwest::Client::new();
let user_settings = json!({
"preferredModelId": "gemini-3.1-flash-lite",
"theme": "dark"
});
let requests = vec![
(
"/v1internal:loadCodeAssist",
json!({"metadata": {"ideType": "ANTIGRAVITY_CLI"}}),
),
(
"/v1internal:fetchAvailableModels",
json!({"project": "aether-antigravity-local"}),
),
(
"/v1internal:retrieveUserQuotaSummary",
json!({"project": "aether-antigravity-local"}),
),
(
"/v1internal:fetchUserInfo",
json!({"project": "aether-antigravity-local"}),
),
(
"/v1internal:fetchAdminControls",
json!({"project": "aether-antigravity-local"}),
),
("/v1internal:listExperiments", json!({})),
(
"/v1internal:recordCodeAssistMetrics",
json!({
"project": "aether-antigravity-local",
"requestId": "opaque-request-id",
"metrics": []
}),
),
(
"/v1internal:writeTrajectoryAcls",
json!({"trajectoryId": "trajectory-ant-123"}),
),
(
"/v1internal:setUserSettings",
json!({"userSettings": user_settings.clone()}),
),
];
for (path, request_body) in requests {
let response = client
.post(format!("{gateway_url}{path}"))
.header("authorization", "Bearer ant-access-token")
.header("user-agent", "antigravity/cli/1.0.2 linux/arm64")
.json(&request_body)
.send()
.await
.expect("request should succeed");
assert_eq!(response.status(), StatusCode::OK, "path {path}");
assert_eq!(
response
.headers()
.get(EXECUTION_PATH_HEADER)
.and_then(|value| value.to_str().ok()),
Some(EXECUTION_PATH_LOCAL_AI_PUBLIC),
"path {path}"
);
let payload: serde_json::Value = response.json().await.expect("json body should parse");
match path {
"/v1internal:loadCodeAssist" => {
assert_eq!(
payload["cloudaicompanionProject"],
"aether-antigravity-local"
);
assert_eq!(payload["currentTier"]["id"], "free-tier");
assert_eq!(payload["currentTier"]["name"], "Antigravity");
assert_eq!(payload["paidTier"]["id"], "g1-pro-tier");
assert_eq!(payload["gcpManaged"], false);
assert_eq!(payload["allowedTiers"][0]["id"], "free-tier");
assert_eq!(payload["allowedTiers"][0]["isDefault"], true);
assert_eq!(payload["allowedTiers"][1]["id"], "standard-tier");
assert_eq!(
payload["upgradeSubscriptionUri"],
"https://codeassist.google.com/upgrade"
);
}
"/v1internal:fetchAvailableModels" => {
assert_eq!(payload["defaultAgentModelId"], "gemini-3.5-flash-low");
assert_eq!(
payload["tieredModelIds"]["flash"],
json!(["gemini-3-flash-agent"])
);
assert_eq!(
payload["tieredModelIds"]["pro"],
json!(["gemini-3.1-pro-low"])
);
assert_eq!(
payload["models"]["gemini-3-flash-agent"]["displayName"],
"Gemini 3.5 Flash (High)"
);
assert_eq!(
payload["models"]["gemini-3.5-flash-low"]["displayName"],
"Gemini 3.5 Flash (Medium)"
);
assert_eq!(
payload["models"]["gemini-3.5-flash-extra-low"]["displayName"],
"Gemini 3.5 Flash (Low)"
);
assert_eq!(
payload["models"]["gemini-pro-agent"]["displayName"],
"Gemini 3.1 Pro (High)"
);
assert_eq!(
payload["models"]["claude-opus-4-6-thinking"]["displayName"],
"Claude Opus 4.6 (Thinking)"
);
assert_eq!(
payload["models"]["gpt-oss-120b-medium"]["displayName"],
"GPT-OSS 120B (Medium)"
);
assert_eq!(
payload["models"]["gemini-pro-agent"]["model"],
"MODEL_PLACEHOLDER_M16"
);
assert_eq!(
payload["models"]["gemini-3.1-pro-high"]["model"],
"MODEL_PLACEHOLDER_M37"
);
assert_eq!(
payload["models"]["gemini-3.5-flash-extra-low"]["model"],
"MODEL_PLACEHOLDER_M187"
);
assert_eq!(
payload["models"]["claude-sonnet-4-6"]["apiProvider"],
"API_PROVIDER_ANTHROPIC_VERTEX"
);
assert_eq!(
payload["models"]["gpt-oss-120b-medium"]["apiProvider"],
"API_PROVIDER_OPENAI_VERTEX"
);
assert_eq!(
payload["models"]["gemini-3.5-flash-low"]["apiProvider"],
"API_PROVIDER_GOOGLE_GEMINI"
);
assert_eq!(
payload["models"]["gemini-2.5-flash-lite"]["model"],
"MODEL_GOOGLE_GEMINI_2_5_FLASH_LITE"
);
assert_eq!(
payload["agentModelSorts"][0]["groups"][0]["modelIds"],
json!([
"gemini-3.5-flash-low",
"gemini-3-flash-agent",
"gemini-3.5-flash-extra-low",
"gemini-3.1-pro-low",
"gemini-pro-agent",
"claude-sonnet-4-6",
"claude-opus-4-6-thinking",
"gpt-oss-120b-medium"
])
);
assert_eq!(
payload["deprecatedModelIds"]["gemini-3.1-pro-high"]["newModelId"],
"gemini-pro-agent"
);
assert_eq!(payload["commandModelIds"], json!(["gemini-3-flash"]));
assert_eq!(
payload["imageGenerationModelIds"],
json!(["gemini-3.1-flash-image"])
);
assert_eq!(payload["tabModelIds"], json!(["chat_20706", "chat_23310"]));
assert_eq!(payload["mqueryModelIds"], json!(["gemini-3.1-flash-lite"]));
assert_eq!(
payload["webSearchModelIds"],
json!(["gemini-3.1-flash-lite"])
);
assert_eq!(
payload["commitMessageModelIds"],
json!(["gemini-3.1-flash-lite"])
);
}
"/v1internal:fetchUserInfo" => {
assert_eq!(payload["regionCode"], "US");
assert_eq!(
payload["userSettings"]["preferredModelId"],
"gemini-3.5-flash-low"
);
}
"/v1internal:retrieveUserQuotaSummary" => {
assert_eq!(payload["description"], "");
assert_eq!(payload["groups"], json!([]));
}
"/v1internal:fetchAdminControls" => {
assert_eq!(payload, json!({}));
}
"/v1internal:listExperiments" => {
assert_eq!(payload["experimentIds"], json!([]));
assert_eq!(payload["flags"], json!([]));
}
"/v1internal:recordCodeAssistMetrics" => {
assert_eq!(payload, json!({}));
}
"/v1internal:writeTrajectoryAcls" => {
assert_eq!(payload, json!({}));
}
"/v1internal:setUserSettings" => {
assert_eq!(payload["userSettings"], user_settings);
}
other => panic!("unexpected path {other}"),
}
}
assert_eq!(*fallback_probe_hits.lock().expect("mutex should lock"), 0);
gateway_handle.abort();
fallback_probe_handle.abort();
}
#[tokio::test]
async fn gateway_does_not_locally_reject_image_model_name_on_chat_completions() {
let fallback_probe_hits = Arc::new(Mutex::new(0usize));
let fallback_probe_hits_clone = Arc::clone(&fallback_probe_hits);
let fallback_probe = Router::new().route(
"/{*path}",
any(move |_request: Request| {
let fallback_probe_hits_inner = Arc::clone(&fallback_probe_hits_clone);
async move {
*fallback_probe_hits_inner.lock().expect("mutex should lock") += 1;
(StatusCode::OK, Json(json!({"proxied": true}))).into_response()
}
}),
);
let auth_repository = Arc::new(InMemoryAuthApiKeySnapshotRepository::seed(vec![(
Some(hash_api_key("sk-openai-chat-image-model")),
unrestricted_models_snapshot(
"key-openai-chat-image-model",
"user-openai-chat-image-model",
),
)]));
let (_unused_fallback_probe_url, fallback_probe_handle) = start_server(fallback_probe).await;
let gateway = build_router_with_state(
AppState::new()
.expect("gateway should build")
.with_auth_api_key_data_reader_for_tests(auth_repository),
);
let (gateway_url, gateway_handle) = start_server(gateway).await;
let response = reqwest::Client::new()
.post(format!("{gateway_url}/v1/chat/completions"))
.header("authorization", "Bearer sk-openai-chat-image-model")
.header(http::header::CONTENT_TYPE, "application/json")
.body(
serde_json::to_vec(&json!({
"model": "gpt-image-2",
"messages": [{"role": "user", "content": "hello"}]
}))
.expect("request body should encode"),
)
.send()
.await
.expect("request should succeed");
assert_eq!(response.status(), StatusCode::SERVICE_UNAVAILABLE);
assert_eq!(
response
.headers()
.get(EXECUTION_PATH_HEADER)
.and_then(|value| value.to_str().ok()),
Some(EXECUTION_PATH_LOCAL_EXECUTION_RUNTIME_MISS)
);
assert_eq!(*fallback_probe_hits.lock().expect("mutex should lock"), 0);
gateway_handle.abort();
fallback_probe_handle.abort();
}
#[tokio::test]
async fn gateway_rejects_image_request_above_gateway_limit_without_hitting_fallback_probe() {
let fallback_probe_hits = Arc::new(Mutex::new(0usize));
let fallback_probe_hits_clone = Arc::clone(&fallback_probe_hits);
let fallback_probe = Router::new().route(
"/{*path}",
any(move |_request: Request| {
let fallback_probe_hits_inner = Arc::clone(&fallback_probe_hits_clone);
async move {
*fallback_probe_hits_inner.lock().expect("mutex should lock") += 1;
(StatusCode::OK, Json(json!({"proxied": true}))).into_response()
}
}),
);
let auth_repository = Arc::new(InMemoryAuthApiKeySnapshotRepository::seed(vec![(
Some(hash_api_key("sk-openai-image-n")),
unrestricted_models_snapshot("key-openai-image-n", "user-openai-image-n"),
)]));
let (_unused_fallback_probe_url, fallback_probe_handle) = start_server(fallback_probe).await;
let gateway = build_router_with_state(
AppState::new()
.expect("gateway should build")
.with_auth_api_key_data_reader_for_tests(auth_repository),
);
let (gateway_url, gateway_handle) = start_server(gateway).await;
let response = reqwest::Client::new()
.post(format!("{gateway_url}/v1/images/generations"))
.header("authorization", "Bearer sk-openai-image-n")
.header(http::header::CONTENT_TYPE, "application/json")
.body(
serde_json::to_vec(&json!({
"model": "grok-imagine-image-lite",
"prompt": "draw",
"n": openai_image_gateway_max_generation_count() + 1,
"response_format": "b64_json"
}))
.expect("request body should encode"),
)
.send()
.await
.expect("request should succeed");
assert_eq!(response.status(), StatusCode::BAD_REQUEST);
assert_eq!(
response
.headers()
.get(EXECUTION_PATH_HEADER)
.and_then(|value| value.to_str().ok()),
Some(EXECUTION_PATH_LOCAL_AI_PUBLIC)
);
let payload: serde_json::Value = response.json().await.expect("json body should parse");
assert_eq!(
payload["detail"],
format!(
"当前图片反代仅支持 n=1..{}",
openai_image_gateway_max_generation_count()
)
);
assert_eq!(*fallback_probe_hits.lock().expect("mutex should lock"), 0);
gateway_handle.abort();
fallback_probe_handle.abort();
}
#[tokio::test]
async fn gateway_does_not_mount_image_variation_route_without_hitting_fallback_probe() {
let fallback_probe_hits = Arc::new(Mutex::new(0usize));
let fallback_probe_hits_clone = Arc::clone(&fallback_probe_hits);
let fallback_probe = Router::new().route(
"/{*path}",
any(move |_request: Request| {
let fallback_probe_hits_inner = Arc::clone(&fallback_probe_hits_clone);
async move {
*fallback_probe_hits_inner.lock().expect("mutex should lock") += 1;
(StatusCode::OK, Json(json!({"proxied": true}))).into_response()
}
}),
);
let auth_repository = Arc::new(InMemoryAuthApiKeySnapshotRepository::seed(vec![(
Some(hash_api_key("sk-openai-image-variation")),
unrestricted_models_snapshot("key-openai-image-variation", "user-openai-image-variation"),
)]));
let (_unused_fallback_probe_url, fallback_probe_handle) = start_server(fallback_probe).await;
let gateway = build_router_with_state(
AppState::new()
.expect("gateway should build")
.with_auth_api_key_data_reader_for_tests(auth_repository),
);
let (gateway_url, gateway_handle) = start_server(gateway).await;
let response = reqwest::Client::new()
.post(format!("{gateway_url}/v1/images/variations"))
.header("authorization", "Bearer sk-openai-image-variation")
.header(http::header::CONTENT_TYPE, "application/json")
.body(
serde_json::to_vec(&json!({
"model": "dall-e-2",
"response_format": "url"
}))
.expect("request body should encode"),
)
.send()
.await
.expect("request should succeed");
assert_eq!(response.status(), StatusCode::NOT_FOUND);
assert_eq!(*fallback_probe_hits.lock().expect("mutex should lock"), 0);
gateway_handle.abort();
fallback_probe_handle.abort();
}
#[tokio::test]
async fn gateway_handles_gemini_operation_detail_without_hitting_fallback_probe() {
let fallback_probe_hits = Arc::new(Mutex::new(0usize));
let fallback_probe_hits_clone = Arc::clone(&fallback_probe_hits);
let fallback_probe = Router::new().route(
"/{*path}",
any(move |_request: Request| {
let fallback_probe_hits_inner = Arc::clone(&fallback_probe_hits_clone);
async move {
*fallback_probe_hits_inner.lock().expect("mutex should lock") += 1;
(StatusCode::OK, Json(json!({"proxied": true}))).into_response()
}
}),
);
let auth_repository = Arc::new(InMemoryAuthApiKeySnapshotRepository::seed(vec![(
Some(hash_api_key("sk-gemini-operation-detail")),
unrestricted_models_snapshot(
"key-gemini-operation-detail",
"user-gemini-operation-detail",
),
)]));
let repository = Arc::new(InMemoryVideoTaskRepository::default());
repository
.upsert(sample_gemini_video_task(
"task-gemini-operation-detail",
"opshort123",
"user-gemini-operation-detail",
"key-gemini-operation-detail",
"operations/ext-op-123",
VideoTaskStatus::Completed,
))
.await
.expect("upsert should succeed");
let (_unused_fallback_probe_url, fallback_probe_handle) = start_server(fallback_probe).await;
let gateway = build_router_with_state(
AppState::new()
.expect("gateway should build")
.with_data_state_for_tests(
crate::data::GatewayDataState::with_auth_and_video_task_repository_for_tests(
auth_repository,
repository,
),
),
);
let (gateway_url, gateway_handle) = start_server(gateway).await;
let response = reqwest::Client::new()
.get(format!(
"{gateway_url}/v1beta/operations/opshort123?key=sk-gemini-operation-detail"
))
.send()
.await
.expect("request should succeed");
assert_eq!(response.status(), StatusCode::OK);
assert_eq!(
response
.headers()
.get(EXECUTION_PATH_HEADER)
.and_then(|value| value.to_str().ok()),
Some(EXECUTION_PATH_LOCAL_AI_PUBLIC)
);
let payload: serde_json::Value = response.json().await.expect("json body should parse");
assert_eq!(payload["name"], "models/veo-3/operations/opshort123");
assert_eq!(payload["done"], true);
assert_eq!(
payload["response"]["generateVideoResponse"]["generatedSamples"][0]["video"]["uri"],
"/v1beta/files/aev_opshort123:download?alt=media"
);
assert_eq!(*fallback_probe_hits.lock().expect("mutex should lock"), 0);
gateway_handle.abort();
fallback_probe_handle.abort();
}
#[tokio::test]
async fn gateway_lists_gemini_operations_without_hitting_fallback_probe() {
let fallback_probe_hits = Arc::new(Mutex::new(0usize));
let fallback_probe_hits_clone = Arc::clone(&fallback_probe_hits);
let fallback_probe = Router::new().route(
"/{*path}",
any(move |_request: Request| {
let fallback_probe_hits_inner = Arc::clone(&fallback_probe_hits_clone);
async move {
*fallback_probe_hits_inner.lock().expect("mutex should lock") += 1;
(StatusCode::OK, Json(json!({"proxied": true}))).into_response()
}
}),
);
let auth_repository = Arc::new(InMemoryAuthApiKeySnapshotRepository::seed(vec![(
Some(hash_api_key("sk-gemini-operation-list")),
unrestricted_models_snapshot("key-gemini-operation-list", "user-gemini-operation-list"),
)]));
let repository = Arc::new(InMemoryVideoTaskRepository::default());
repository
.upsert(sample_gemini_video_task(
"task-gemini-operation-list-1",
"opshort-list-1",
"user-gemini-operation-list",
"key-gemini-operation-list",
"operations/ext-list-1",
VideoTaskStatus::Completed,
))
.await
.expect("upsert should succeed");
repository
.upsert(sample_gemini_video_task(
"task-gemini-operation-list-2",
"opshort-list-2",
"user-gemini-operation-list",
"key-gemini-operation-list",
"operations/ext-list-2",
VideoTaskStatus::Processing,
))
.await
.expect("upsert should succeed");
repository
.upsert(sample_gemini_video_task(
"task-gemini-operation-list-other",
"opshort-list-other",
"user-other",
"key-other",
"operations/ext-list-other",
VideoTaskStatus::Completed,
))
.await
.expect("upsert should succeed");
let (_unused_fallback_probe_url, fallback_probe_handle) = start_server(fallback_probe).await;
let gateway = build_router_with_state(
AppState::new()
.expect("gateway should build")
.with_data_state_for_tests(
crate::data::GatewayDataState::with_auth_and_video_task_repository_for_tests(
auth_repository,
repository,
),
),
);
let (gateway_url, gateway_handle) = start_server(gateway).await;
let response = reqwest::Client::new()
.get(format!(
"{gateway_url}/v1beta/operations?key=sk-gemini-operation-list"
))
.send()
.await
.expect("request should succeed");
assert_eq!(response.status(), StatusCode::OK);
assert_eq!(
response
.headers()
.get(EXECUTION_PATH_HEADER)
.and_then(|value| value.to_str().ok()),
Some(EXECUTION_PATH_LOCAL_AI_PUBLIC)
);
let payload: serde_json::Value = response.json().await.expect("json body should parse");
let operations = payload["operations"]
.as_array()
.expect("operations should be an array");
assert_eq!(operations.len(), 2);
let operation_names = operations
.iter()
.map(|value| {
value["name"]
.as_str()
.expect("operation name should be a string")
.to_string()
})
.collect::<std::collections::BTreeSet<_>>();
assert_eq!(
operation_names,
std::collections::BTreeSet::from([
"models/veo-3/operations/opshort-list-1".to_string(),
"models/veo-3/operations/opshort-list-2".to_string(),
])
);
assert_eq!(*fallback_probe_hits.lock().expect("mutex should lock"), 0);
gateway_handle.abort();
fallback_probe_handle.abort();
}
#[tokio::test]
async fn gateway_cancels_gemini_operation_without_hitting_fallback_probe() {
#[derive(Debug, Clone, PartialEq, Eq)]
struct SeenExecutionRuntimeSyncRequest {
method: String,
url: String,
api_key: String,
}
let fallback_probe_hits = Arc::new(Mutex::new(0usize));
let fallback_probe_hits_clone = Arc::clone(&fallback_probe_hits);
let fallback_probe = Router::new().route(
"/{*path}",
any(move |_request: Request| {
let fallback_probe_hits_inner = Arc::clone(&fallback_probe_hits_clone);
async move {
*fallback_probe_hits_inner.lock().expect("mutex should lock") += 1;
(StatusCode::OK, Json(json!({"proxied": true}))).into_response()
}
}),
);
let seen_execution_runtime = Arc::new(Mutex::new(None::<SeenExecutionRuntimeSyncRequest>));
let seen_execution_runtime_clone = Arc::clone(&seen_execution_runtime);
let execution_runtime = Router::new().route(
"/v1/execute/sync",
any(move |request: Request| {
let seen_execution_runtime_inner = Arc::clone(&seen_execution_runtime_clone);
async move {
let (_parts, body) = request.into_parts();
let raw_body = to_bytes(body, usize::MAX).await.expect("body should read");
let payload: serde_json::Value = serde_json::from_slice(&raw_body)
.expect("execution runtime payload should parse");
*seen_execution_runtime_inner
.lock()
.expect("mutex should lock") = Some(SeenExecutionRuntimeSyncRequest {
method: payload
.get("method")
.and_then(|value| value.as_str())
.unwrap_or_default()
.to_string(),
url: payload
.get("url")
.and_then(|value| value.as_str())
.unwrap_or_default()
.to_string(),
api_key: payload
.get("headers")
.and_then(|value| value.get("x-goog-api-key"))
.and_then(|value| value.as_str())
.unwrap_or_default()
.to_string(),
});
Json(json!({
"request_id": "trace-gemini-operation-cancel",
"status_code": 200,
"headers": {
"content-type": "application/json"
},
"body": {
"json_body": {}
},
"telemetry": {
"elapsed_ms": 12
}
}))
}
}),
);
let auth_repository = Arc::new(InMemoryAuthApiKeySnapshotRepository::seed(vec![(
Some(hash_api_key("sk-gemini-operation-cancel")),
unrestricted_models_snapshot(
"key-gemini-operation-cancel",
"user-gemini-operation-cancel",
),
)]));
let repository = Arc::new(InMemoryVideoTaskRepository::default());
repository
.upsert(sample_gemini_video_task(
"task-gemini-operation-cancel",
"opshort-cancel",
"user-gemini-operation-cancel",
"key-gemini-operation-cancel",
"operations/ext-op-123",
VideoTaskStatus::Submitted,
))
.await
.expect("upsert should succeed");
let (fallback_probe_url, fallback_probe_handle) = start_server(fallback_probe).await;
let (execution_runtime_url, execution_runtime_handle) = start_server(execution_runtime).await;
let gateway = build_router_with_state(
build_state_with_execution_runtime_override(execution_runtime_url)
.with_data_state_for_tests(
crate::data::GatewayDataState::with_auth_and_video_task_repository_for_tests(
auth_repository,
Arc::clone(&repository),
),
),
);
let (gateway_url, gateway_handle) = start_server(gateway).await;
let response = reqwest::Client::new()
.post(format!(
"{gateway_url}/v1beta/operations/opshort-cancel:cancel"
))
.header("x-goog-api-key", "sk-gemini-operation-cancel")
.header(http::header::CONTENT_TYPE, "application/json")
.body("{}")
.send()
.await
.expect("request should succeed");
assert_eq!(response.status(), StatusCode::OK);
assert_eq!(
response
.headers()
.get(EXECUTION_PATH_HEADER)
.and_then(|value| value.to_str().ok()),
Some(EXECUTION_PATH_LOCAL_AI_PUBLIC)
);
assert_eq!(
response
.json::<serde_json::Value>()
.await
.expect("json body should parse"),
json!({})
);
let seen_execution_runtime_request = seen_execution_runtime
.lock()
.expect("mutex should lock")
.clone()
.expect("execution runtime sync should be captured");
assert_eq!(seen_execution_runtime_request.method, "POST");
assert_eq!(
seen_execution_runtime_request.url,
"https://generativelanguage.googleapis.com/v1beta/models/veo-3/operations/ext-op-123:cancel"
);
assert_eq!(
seen_execution_runtime_request.api_key,
"sk-upstream-gemini-video"
);
let stored = repository
.find(VideoTaskLookupKey::Id("task-gemini-operation-cancel"))
.await
.expect("task lookup should succeed")
.expect("task should exist");
assert_eq!(stored.status, VideoTaskStatus::Cancelled);
assert_eq!(*fallback_probe_hits.lock().expect("mutex should lock"), 0);
gateway_handle.abort();
execution_runtime_handle.abort();
fallback_probe_handle.abort();
}