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Merge pull request #371 from Kayphoon/feature/embedding-model-support

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feat: add embedding and rerank support
This commit is contained in:
fawney19
2026-05-04 12:56:11 +08:00
committed by GitHub
parent 8dd4135f7c 6bdd7792eb
commit 627eb4f335
87 changed files with 5517 additions and 184 deletions
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apps/aether-gateway/src/tests/control/admin/models/global.rs
+146 -3
View File
@@ -450,6 +450,128 @@ async fn gateway_handles_admin_model_catalog_locally_with_trusted_admin_principa
upstream_handle.abort();
}
#[tokio::test]
async fn admin_global_models_include_embedding_capability() {
let upstream_hits = Arc::new(Mutex::new(0usize));
let upstream_hits_clone = Arc::clone(&upstream_hits);
let upstream = Router::new().route(
"/{*path}",
any(move |_request: Request| {
let upstream_hits_inner = Arc::clone(&upstream_hits_clone);
async move {
*upstream_hits_inner.lock().expect("mutex should lock") += 1;
(StatusCode::OK, Body::from("unexpected upstream hit"))
}
}),
);
let mut global_model = sample_admin_global_model(
"global-embedding-small",
"text-embedding-3-small",
"Text Embedding 3 Small",
);
global_model.supported_capabilities = Some(json!(["embedding"]));
global_model.config = Some(json!({
"api_formats": ["openai:embedding"],
"dimensions": 1536,
"model_type": "embedding"
}));
let mut provider_model = sample_admin_provider_model(
"model-openai-embedding-small",
"provider-openai",
"global-embedding-small",
"text-embedding-3-small",
);
provider_model.provider_model_mappings = Some(json!([{
"name": "text-embedding-3-small",
"priority": 1,
"api_formats": ["openai:embedding"]
}]));
provider_model.config = Some(json!({
"api_formats": ["openai:embedding"],
"dimensions": 1536,
"model_type": "embedding"
}));
provider_model.supports_streaming = Some(false);
provider_model.global_model_name = Some("text-embedding-3-small".to_string());
provider_model.global_model_display_name = Some("Text Embedding 3 Small".to_string());
provider_model.global_model_supported_capabilities = Some(json!(["embedding"]));
provider_model.global_model_config = global_model.config.clone();
let provider_catalog_repository = Arc::new(InMemoryProviderCatalogReadRepository::seed(
vec![sample_provider("provider-openai", "openai", 10)],
Vec::new(),
Vec::new(),
));
let global_model_repository = Arc::new(
InMemoryGlobalModelReadRepository::seed(Vec::new())
.with_admin_global_models(vec![global_model])
.with_admin_provider_models(vec![provider_model]),
);
let (upstream_url, upstream_handle) = start_server(upstream).await;
let gateway = build_router_with_state(
AppState::new()
.expect("gateway should build")
.with_data_state_for_tests(
GatewayDataState::with_provider_catalog_reader_for_tests(
provider_catalog_repository,
)
.with_global_model_repository_for_tests(global_model_repository),
),
);
let (gateway_url, gateway_handle) = start_server(gateway).await;
let client = reqwest::Client::new();
let list_response = client
.get(format!("{gateway_url}/api/admin/models/global?limit=20"))
.header(crate::constants::GATEWAY_HEADER, "rust-phase3b")
.header(TRUSTED_ADMIN_USER_ID_HEADER, "admin-user-123")
.header(TRUSTED_ADMIN_USER_ROLE_HEADER, "admin")
.header(TRUSTED_ADMIN_SESSION_ID_HEADER, "session-123")
.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["models"][0]["supported_capabilities"],
json!(["embedding"])
);
assert_eq!(
list_payload["models"][0]["config"]["api_formats"],
json!(["openai:embedding"])
);
let catalog_response = client
.get(format!("{gateway_url}/api/admin/models/catalog"))
.header(crate::constants::GATEWAY_HEADER, "rust-phase3b")
.header(TRUSTED_ADMIN_USER_ID_HEADER, "admin-user-123")
.header(TRUSTED_ADMIN_USER_ROLE_HEADER, "admin")
.header(TRUSTED_ADMIN_SESSION_ID_HEADER, "session-123")
.send()
.await
.expect("request should succeed");
assert_eq!(catalog_response.status(), StatusCode::OK);
let catalog_payload: serde_json::Value = catalog_response
.json()
.await
.expect("json body should parse");
assert_eq!(
catalog_payload["models"][0]["capabilities"]["supports_embedding"],
true
);
assert_eq!(
catalog_payload["models"][0]["providers"][0]["supports_embedding"],
true
);
assert_eq!(*upstream_hits.lock().expect("mutex should lock"), 0);
gateway_handle.abort();
upstream_handle.abort();
}
#[tokio::test]
async fn gateway_returns_service_unavailable_for_admin_model_catalog_without_required_readers() {
let upstream_hits = Arc::new(Mutex::new(0usize));
@@ -859,8 +981,8 @@ async fn gateway_creates_admin_global_model_locally_with_trusted_admin_principal
"output_price_per_1m": 24.0
}]
},
"supported_capabilities": ["streaming", "vision"],
"config": {"streaming": true}
"supported_capabilities": ["streaming", "vision", "embedding"],
"config": {"streaming": true, "api_formats": ["openai:embedding"], "model_type": "embedding"}
}))
.send()
.await
@@ -870,6 +992,14 @@ async fn gateway_creates_admin_global_model_locally_with_trusted_admin_principal
let payload: serde_json::Value = response.json().await.expect("json body should parse");
assert_eq!(payload["name"], "gpt-5-pro");
assert_eq!(payload["display_name"], "GPT 5 Pro");
assert_eq!(
payload["supported_capabilities"],
json!(["streaming", "vision", "embedding"])
);
assert_eq!(
payload["config"]["api_formats"],
json!(["openai:embedding"])
);
assert_eq!(*upstream_hits.lock().expect("mutex should lock"), 0);
let created = global_model_repository
@@ -878,6 +1008,10 @@ async fn gateway_creates_admin_global_model_locally_with_trusted_admin_principal
.expect("model lookup should succeed")
.expect("model should exist");
assert_eq!(created.display_name, "GPT 5 Pro");
assert_eq!(
created.supported_capabilities,
Some(json!(["streaming", "vision", "embedding"]))
);
gateway_handle.abort();
upstream_handle.abort();
@@ -926,7 +1060,8 @@ async fn gateway_updates_and_deletes_admin_global_model_locally_with_trusted_adm
.json(&json!({
"display_name": "GPT 5 Updated",
"is_active": false,
"config": {"streaming": false}
"supported_capabilities": ["embedding"],
"config": {"streaming": false, "api_formats": ["openai:embedding"], "dimensions": 1536}
}))
.send()
.await
@@ -939,6 +1074,14 @@ async fn gateway_updates_and_deletes_admin_global_model_locally_with_trusted_adm
.expect("json body should parse");
assert_eq!(update_payload["display_name"], "GPT 5 Updated");
assert_eq!(update_payload["is_active"], false);
assert_eq!(
update_payload["supported_capabilities"],
json!(["embedding"])
);
assert_eq!(
update_payload["config"]["api_formats"],
json!(["openai:embedding"])
);
let delete_response = reqwest::Client::new()
.delete(format!(
apps/aether-gateway/src/tests/control/admin/models/provider.rs
+55 -22
View File
@@ -233,7 +233,8 @@ async fn gateway_creates_admin_provider_model_locally_with_trusted_admin_princip
"provider_model_name": "gpt-5-upstream",
"global_model_id": "global-gpt-5",
"supports_vision": true,
"config": {"provider_hint": "gpt-5-upstream"}
"provider_model_mappings": [{"name": "text-embedding-3-small", "priority": 1, "api_formats": ["openai:embedding"]}],
"config": {"provider_hint": "gpt-5-upstream", "api_formats": ["openai:embedding"], "model_type": "embedding"}
}))
.send()
.await
@@ -245,6 +246,11 @@ async fn gateway_creates_admin_provider_model_locally_with_trusted_admin_princip
assert_eq!(payload["global_model_id"], "global-gpt-5");
assert_eq!(payload["provider_model_name"], "gpt-5-upstream");
assert_eq!(payload["effective_supports_vision"], true);
assert_eq!(payload["effective_supports_embedding"], true);
assert_eq!(
payload["provider_model_mappings"][0]["api_formats"],
json!(["openai:embedding"])
);
assert_eq!(*upstream_hits.lock().expect("mutex should lock"), 0);
let created = global_model_repository
@@ -258,6 +264,13 @@ async fn gateway_creates_admin_provider_model_locally_with_trusted_admin_princip
.expect("models should read");
assert_eq!(created.len(), 1);
assert_eq!(created[0].provider_model_name, "gpt-5-upstream");
assert_eq!(
created[0]
.config
.as_ref()
.and_then(|value| value.get("api_formats")),
Some(&json!(["openai:embedding"]))
);
gateway_handle.abort();
upstream_handle.abort();
@@ -320,8 +333,10 @@ async fn gateway_updates_and_deletes_admin_provider_model_locally_with_trusted_a
.json(&json!({
"provider_model_name": "gpt-5-mini-upstream",
"global_model_id": "global-gpt-5-mini",
"provider_model_mappings": [{"name": "text-embedding-3-small", "priority": 1, "api_formats": ["openai:embedding"]}],
"supports_streaming": false,
"is_available": false
"is_available": false,
"config": {"api_formats": ["openai:embedding"], "model_type": "embedding"}
}))
.send()
.await
@@ -334,6 +349,7 @@ async fn gateway_updates_and_deletes_admin_provider_model_locally_with_trusted_a
assert_eq!(update_payload["provider_model_name"], "gpt-5-mini-upstream");
assert_eq!(update_payload["global_model_id"], "global-gpt-5-mini");
assert_eq!(update_payload["is_available"], false);
assert_eq!(update_payload["effective_supports_embedding"], true);
let delete_response = reqwest::Client::new()
.delete(format!(
@@ -456,27 +472,37 @@ async fn gateway_handles_admin_provider_available_source_models_locally_with_tru
Vec::new(),
Vec::new(),
));
let mut global_model = sample_admin_global_model(
"global-gpt-5",
"text-embedding-3-small",
"Text Embedding 3 Small",
);
global_model.supported_capabilities = Some(json!(["embedding"]));
global_model.config = Some(json!({"api_formats": ["openai:embedding"]}));
let mut primary_model = sample_admin_provider_model(
"model-openai-gpt5",
"provider-openai",
"global-gpt-5",
"text-embedding-3-small",
);
primary_model.global_model_name = Some("text-embedding-3-small".to_string());
primary_model.global_model_display_name = Some("Text Embedding 3 Small".to_string());
primary_model.global_model_supported_capabilities = Some(json!(["embedding"]));
primary_model.global_model_config = Some(json!({"api_formats": ["openai:embedding"]}));
let mut alternate_model = sample_admin_provider_model(
"model-openai-gpt5-b",
"provider-openai",
"global-gpt-5",
"gpt-5-alt",
);
alternate_model.global_model_name = Some("text-embedding-3-small".to_string());
alternate_model.global_model_display_name = Some("Text Embedding 3 Small".to_string());
alternate_model.global_model_supported_capabilities = Some(json!(["embedding"]));
alternate_model.global_model_config = Some(json!({"api_formats": ["openai:embedding"]}));
let global_model_repository = Arc::new(
InMemoryGlobalModelReadRepository::seed(Vec::new())
.with_admin_global_models(vec![sample_admin_global_model(
"global-gpt-5",
"gpt-5",
"GPT 5",
)])
.with_admin_provider_models(vec![
sample_admin_provider_model(
"model-openai-gpt5",
"provider-openai",
"global-gpt-5",
"gpt-5-upstream",
),
sample_admin_provider_model(
"model-openai-gpt5-b",
"provider-openai",
"global-gpt-5",
"gpt-5-alt",
),
]),
.with_admin_global_models(vec![global_model])
.with_admin_provider_models(vec![primary_model, alternate_model]),
);
let (upstream_url, upstream_handle) = start_server(upstream).await;
@@ -507,7 +533,14 @@ async fn gateway_handles_admin_provider_available_source_models_locally_with_tru
assert_eq!(response.status(), StatusCode::OK);
let payload: serde_json::Value = response.json().await.expect("json body should parse");
assert_eq!(payload["total"], 1);
assert_eq!(payload["models"][0]["global_model_name"], "gpt-5");
assert_eq!(
payload["models"][0]["global_model_name"],
"text-embedding-3-small"
);
assert_eq!(
payload["models"][0]["capabilities"]["supports_embedding"],
true
);
assert_eq!(*upstream_hits.lock().expect("mutex should lock"), 0);
gateway_handle.abort();
apps/aether-gateway/src/tests/control/admin/system.rs
+6
View File
@@ -1078,6 +1078,12 @@ async fn gateway_handles_admin_system_api_formats_locally_with_trusted_admin_pri
.expect("formats should be an array");
assert_eq!(formats[0]["value"], "openai:chat");
assert_eq!(formats[0]["default_path"], "/v1/chat/completions");
assert!(formats
.iter()
.any(|item| item["value"] == "openai:embedding"));
assert!(formats.iter().any(|item| item["value"] == "openai:rerank"));
assert!(formats.iter().any(|item| item["value"] == "jina:embedding"));
assert!(formats.iter().any(|item| item["value"] == "jina:rerank"));
assert!(formats.iter().any(|item| item["value"] == "gemini:video"));
assert_eq!(*upstream_hits.lock().expect("mutex should lock"), 0);