Merge remote-tracking branch 'upstream/main'

This commit is contained in:
AAEE86
2026-06-05 08:28:43 +08:00
101 changed files with 6967 additions and 602 deletions
@@ -13,6 +13,7 @@ const EMBEDDING_API_FORMATS: &[&str] = &[
"jina:embedding",
"gemini:embedding",
"doubao:embedding",
"aliyun:multimodal_embedding",
];
fn json_value_contains_string(value: &serde_json::Value, expected: &str) -> bool {
@@ -6,6 +6,7 @@ const EMBEDDING_API_FORMATS: &[&str] = &[
"jina:embedding",
"gemini:embedding",
"doubao:embedding",
"aliyun:multimodal_embedding",
];
pub(crate) fn model_tiered_pricing_first_tier_value(
@@ -94,7 +94,7 @@ fn split_admin_monitoring_api_format_and_model(
fn is_known_admin_monitoring_api_format_family(value: &str) -> bool {
matches!(
value.trim().to_ascii_lowercase().as_str(),
"openai" | "claude" | "gemini" | "jina" | "doubao"
"openai" | "claude" | "gemini" | "jina" | "doubao" | "aliyun"
)
}
@@ -116,6 +116,7 @@ fn is_known_admin_monitoring_api_format(value: &str) -> bool {
| "jina:embedding"
| "jina:rerank"
| "doubao:embedding"
| "aliyun:multimodal_embedding"
)
}
@@ -597,6 +597,22 @@ fn provider_query_build_test_request_body_for_api_format(
let message = provider_query_extract_message(payload)
.unwrap_or_else(|| DEFAULT_PROVIDER_QUERY_TEST_MESSAGE.to_string());
match client_api_format.as_str() {
"openai:embedding" => json!({
"model": model,
"input": message,
}),
"openai:rerank" => json!({
"model": model,
"query": message,
"documents": [
"apple",
"banana",
"fruit",
"vegetable"
],
"return_documents": true,
"top_n": 4,
}),
"openai:responses" | "openai:responses:compact" => json!({
"model": model,
"input": message,
@@ -649,6 +665,21 @@ fn provider_query_insert_default_test_conversation(
let message = provider_query_extract_message(payload)
.unwrap_or_else(|| DEFAULT_PROVIDER_QUERY_TEST_MESSAGE.to_string());
match client_api_format {
"openai:embedding" => {
object.insert("input".to_string(), Value::String(message));
}
"openai:rerank" => {
object.insert("query".to_string(), Value::String(message));
object
.entry("documents".to_string())
.or_insert_with(|| json!(["apple", "banana", "fruit", "vegetable"]));
object
.entry("return_documents".to_string())
.or_insert(Value::Bool(true));
object
.entry("top_n".to_string())
.or_insert_with(|| Value::from(4_u64));
}
"openai:responses" | "openai:responses:compact" => {
object.insert("input".to_string(), Value::String(message));
}
@@ -2920,8 +2951,13 @@ async fn provider_query_execute_standard_test_candidate(
);
provider_request_body
}
"openai:embedding" | "gemini:embedding" | "jina:embedding" | "doubao:embedding"
| "openai:rerank" | "jina:rerank" => {
"openai:embedding"
| "gemini:embedding"
| "jina:embedding"
| "doubao:embedding"
| "aliyun:multimodal_embedding"
| "openai:rerank"
| "jina:rerank" => {
let Some(mut provider_request_body) =
crate::ai_serving::build_standard_request_body_with_model_directives_and_request_headers(
&request_body,
@@ -3051,6 +3087,7 @@ async fn provider_query_execute_standard_test_candidate(
| "gemini:embedding"
| "jina:embedding"
| "doubao:embedding"
| "aliyun:multimodal_embedding"
| "openai:rerank"
| "jina:rerank" => state.resolve_local_oauth_header_auth(&transport).await?,
_ => None,
@@ -3062,6 +3099,7 @@ async fn provider_query_execute_standard_test_candidate(
| "openai:embedding"
| "jina:embedding"
| "doubao:embedding"
| "aliyun:multimodal_embedding"
| "openai:rerank"
| "jina:rerank" => {
crate::provider_transport::auth::resolve_local_openai_bearer_auth(&transport)
@@ -74,6 +74,7 @@ pub(super) fn provider_query_standard_test_unsupported_reason(
| "openai:embedding"
| "jina:embedding"
| "doubao:embedding"
| "aliyun:multimodal_embedding"
| "openai:rerank"
| "jina:rerank" => {
crate::provider_transport::policy::local_standard_transport_unsupported_reason_with_network(
@@ -253,6 +254,7 @@ pub(super) fn provider_query_test_adapter_for_provider_api_format(
| "gemini:embedding"
| "jina:embedding"
| "doubao:embedding"
| "aliyun:multimodal_embedding"
| "openai:rerank"
| "jina:rerank"
) {
@@ -352,6 +354,7 @@ pub(super) fn provider_query_transport_supports_model_test_execution(
| "openai:embedding"
| "jina:embedding"
| "doubao:embedding"
| "aliyun:multimodal_embedding"
| "openai:rerank"
| "jina:rerank" => {
crate::provider_transport::policy::supports_local_standard_transport_with_network(
@@ -138,6 +138,12 @@ fn provider_query_endpoint_route_payload(
"embeddings",
"openai_batch",
),
"aliyun:multimodal_embedding" => (
"Aliyun DashScope",
"dashscope_native",
"multimodal-embedding",
"dashscope_contents",
),
"openai:chat" if is_vertex && is_openai_compat => (
"Vertex AI OpenAI-compatible",
"openai_compatible",
@@ -470,6 +470,26 @@ fn provider_query_compact_test_request_body_defaults_to_responses_input() {
assert!(body.get("messages").is_none());
}
#[test]
fn provider_query_embedding_test_request_body_defaults_to_embedding_input() {
let payload = json!({"message": "hello from embedding"});
let client_api_format =
provider_query_standard_test_client_api_format("aliyun:multimodal_embedding");
let body = provider_query_build_test_request_body_for_api_format(
&payload,
"qwen3-vl-embedding",
"/api/admin/provider-query/test-model",
client_api_format,
);
assert_eq!(client_api_format, "openai:embedding");
assert_eq!(body["model"], json!("qwen3-vl-embedding"));
assert_eq!(body["input"], json!("hello from embedding"));
assert!(body.get("messages").is_none());
assert!(body.get("stream").is_none());
}
#[test]
fn provider_query_compact_test_request_body_promotes_prompt_to_input() {
let payload = json!({
@@ -658,6 +678,13 @@ fn provider_query_test_adapter_routes_fixed_provider_endpoint_types() {
provider_query_test_adapter_for_provider_api_format("custom", "gemini:embedding"),
Some(ProviderQueryTestAdapter::Standard)
);
assert_eq!(
provider_query_test_adapter_for_provider_api_format(
"aliyun",
"aliyun:multimodal_embedding"
),
Some(ProviderQueryTestAdapter::Standard)
);
assert_eq!(
provider_query_test_adapter_for_provider_api_format("jina", "jina:rerank"),
Some(ProviderQueryTestAdapter::Standard)
@@ -278,6 +278,9 @@ pub(crate) fn normalize_admin_user_api_formats(
if item.is_empty() {
return Err("allowed_api_formats 不能为空".to_string());
}
if !looks_like_admin_api_format_signature(item) {
return Err(format!("allowed_api_formats 格式无效: {item}"));
}
let Some(normalized_item) = crate::api::ai::normalize_admin_endpoint_signature(item) else {
return Err(format!("allowed_api_formats 格式无效: {item}"));
};
@@ -289,6 +292,12 @@ pub(crate) fn normalize_admin_user_api_formats(
Ok(Some(normalized))
}
fn looks_like_admin_api_format_signature(value: &str) -> bool {
value
.split_once(':')
.is_some_and(|(family, kind)| !family.trim().is_empty() && !kind.trim().is_empty())
}
pub(crate) fn normalize_admin_user_ip_rules(
value: Option<Vec<String>>,
) -> Result<Option<Vec<String>>, String> {
@@ -522,12 +522,45 @@ fn embedding_array_input_is_non_empty(items: &[Value]) -> bool {
item.as_array()
.is_some_and(|items| embedding_token_array_is_non_empty(items))
})
|| items.iter().all(embedding_multimodal_content_is_non_empty)
}
fn embedding_token_array_is_non_empty(items: &[Value]) -> bool {
!items.is_empty() && items.iter().all(|item| item.as_u64().is_some())
}
fn embedding_multimodal_content_is_non_empty(value: &Value) -> bool {
let Some(object) = value.as_object() else {
return false;
};
let valid_text = object
.get("text")
.map(|value| value.as_str().is_some_and(|text| !text.trim().is_empty()));
let valid_image = object
.get("image")
.map(|value| value.as_str().is_some_and(|image| !image.trim().is_empty()));
let valid_video = object
.get("video")
.map(|value| value.as_str().is_some_and(|video| !video.trim().is_empty()));
let valid_multi_images = object.get("multi_images").map(|value| {
value.as_array().is_some_and(|items| {
!items.is_empty()
&& items
.iter()
.all(|item| item.as_str().is_some_and(|image| !image.trim().is_empty()))
})
});
[valid_text, valid_image, valid_video, valid_multi_images]
.into_iter()
.flatten()
.all(|valid| valid)
&& [valid_text, valid_image, valid_video, valid_multi_images]
.into_iter()
.flatten()
.any(|valid| valid)
}
fn image_request_count(value: &Value) -> Option<u64> {
value
.as_u64()
@@ -327,6 +327,32 @@ pub(super) async fn handle_billing_plan_checkout(
false,
);
}
match state
.find_pending_plan_purchase_order_by_user_id(&auth.user.id, &plan.id)
.await
{
Ok(Some(order)) => {
return build_auth_json_response(
http::StatusCode::OK,
json!({
"order": payment_order_payload(&order, &plan),
"payment_instructions": sanitize_wallet_gateway_response(
order.gateway_response.clone()
),
"reused_pending_order": true,
}),
None,
)
}
Ok(None) => {}
Err(err) => {
return build_auth_error_response(
http::StatusCode::INTERNAL_SERVER_ERROR,
format!("pending billing checkout lookup failed: {err:?}"),
false,
)
}
}
let now = Utc::now();
let order_no = billing_order_no(now);
let expires_at = now + chrono::Duration::minutes(30);
@@ -25,6 +25,7 @@ pub(crate) fn models_api_format(request_context: &GatewayPublicRequestContext) -
"jina:embedding" => Some("jina:embedding"),
"jina:rerank" => Some("jina:rerank"),
"doubao:embedding" => Some("doubao:embedding"),
"aliyun:multimodal_embedding" => Some("aliyun:multimodal_embedding"),
_ => None,
}
}
@@ -43,6 +44,7 @@ const MODELS_EMBEDDING_QUERY_API_FORMATS: &[&str] = &[
"jina:embedding",
"gemini:embedding",
"doubao:embedding",
"aliyun:multimodal_embedding",
];
const MODELS_RERANK_QUERY_API_FORMATS: &[&str] = &["openai:rerank", "jina:rerank"];
@@ -54,9 +56,11 @@ pub(super) fn models_query_api_formats(api_format: &str) -> &'static [&'static s
| "claude:messages"
| "gemini:generate_content" => MODELS_CROSS_FORMAT_QUERY_API_FORMATS,
"openai:image" => &["openai:image"],
"openai:embedding" | "jina:embedding" | "gemini:embedding" | "doubao:embedding" => {
MODELS_EMBEDDING_QUERY_API_FORMATS
}
"openai:embedding"
| "jina:embedding"
| "gemini:embedding"
| "doubao:embedding"
| "aliyun:multimodal_embedding" => MODELS_EMBEDDING_QUERY_API_FORMATS,
"openai:rerank" | "jina:rerank" => MODELS_RERANK_QUERY_API_FORMATS,
_ => &[],
}