fix(gateway): route Gemini embedding batches correctly

This commit is contained in:
MMEXA
2026-05-17 14:24:32 +00:00
parent a2f91b4108
commit 81ff375bfd
37 changed files with 1353 additions and 120 deletions

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@@ -49,14 +49,15 @@ pub(crate) use aether_ai_formats::api::{
resolve_claude_sync_spec, resolve_gemini_stream_spec, resolve_gemini_sync_spec,
resolve_local_image_stream_spec, resolve_local_image_sync_spec,
resolve_local_same_format_stream_spec, resolve_local_same_format_sync_spec,
AiControlPlanRequest, ExecutionRuntimeAuthContext, LocalCoreSyncErrorKind,
LocalOpenAiImageSpec, LocalSameFormatProviderFamily, LocalSameFormatProviderSpec,
LocalStandardSourceFamily, LocalStandardSourceMode, LocalStandardSpec,
StreamingStandardTerminalObserver, EXECUTION_RUNTIME_STREAM_DECISION_ACTION,
EXECUTION_RUNTIME_SYNC_DECISION_ACTION, GEMINI_FILES_DOWNLOAD_PLAN_KIND,
GEMINI_VIDEO_CANCEL_SYNC_PLAN_KIND, OPENAI_EMBEDDING_SYNC_PLAN_KIND,
OPENAI_IMAGE_STREAM_PLAN_KIND, OPENAI_IMAGE_SYNC_FINALIZE_REPORT_KIND,
OPENAI_IMAGE_SYNC_PLAN_KIND, OPENAI_RERANK_SYNC_PLAN_KIND, OPENAI_VIDEO_CANCEL_SYNC_PLAN_KIND,
resolve_openai_embedding_sync_spec, AiControlPlanRequest, ExecutionRuntimeAuthContext,
LocalCoreSyncErrorKind, LocalOpenAiImageSpec, LocalSameFormatProviderFamily,
LocalSameFormatProviderSpec, LocalStandardSourceFamily, LocalStandardSourceMode,
LocalStandardSpec, StreamingStandardTerminalObserver, EXECUTION_RUNTIME_STREAM_DECISION_ACTION,
EXECUTION_RUNTIME_SYNC_DECISION_ACTION, GEMINI_EMBEDDING_SYNC_PLAN_KIND,
GEMINI_FILES_DOWNLOAD_PLAN_KIND, GEMINI_VIDEO_CANCEL_SYNC_PLAN_KIND,
OPENAI_EMBEDDING_SYNC_PLAN_KIND, OPENAI_IMAGE_STREAM_PLAN_KIND,
OPENAI_IMAGE_SYNC_FINALIZE_REPORT_KIND, OPENAI_IMAGE_SYNC_PLAN_KIND,
OPENAI_RERANK_SYNC_PLAN_KIND, OPENAI_VIDEO_CANCEL_SYNC_PLAN_KIND,
OPENAI_VIDEO_CONTENT_PLAN_KIND, OPENAI_VIDEO_DELETE_SYNC_PLAN_KIND,
OPENAI_VIDEO_REMIX_SYNC_PLAN_KIND,
};

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@@ -64,7 +64,8 @@ pub(crate) use self::transport::{
candidate_common_transport_skip_reason, candidate_transport_pair_skip_reason,
request_conversion_direct_auth, request_conversion_enabled_for_transport,
request_conversion_transport_supported, request_conversion_transport_unsupported_reason,
request_pair_allowed_for_transport, CandidateTransportPolicyFacts,
request_pair_allowed_for_transport, request_pair_direct_auth,
request_pair_transport_unsupported_reason, CandidateTransportPolicyFacts,
};
pub(crate) use crate::control::GatewayControlDecision;
pub(crate) use crate::execution_runtime::{ConversionMode, ExecutionStrategy};
@@ -97,6 +98,28 @@ pub(crate) fn build_provider_transport_request_url(
)
}
pub(crate) fn build_provider_transport_request_url_for_request_body(
transport: &GatewayProviderTransportSnapshot,
provider_api_format: &str,
mapped_model: Option<&str>,
upstream_is_stream: bool,
request_query: Option<&str>,
kiro_api_region: Option<&str>,
provider_request_body: Option<&serde_json::Value>,
) -> Option<String> {
self::transport::build_transport_request_url_for_request_body(
transport,
self::transport::TransportRequestUrlParams {
provider_api_format,
mapped_model,
upstream_is_stream,
request_query,
kiro_api_region,
},
provider_request_body,
)
}
pub(crate) async fn resolve_execution_runtime_auth_context(
state: &AppState,
decision: &GatewayControlDecision,

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@@ -13,8 +13,9 @@ pub(crate) use crate::ai_serving::{
EXECUTION_RUNTIME_STREAM_DECISION_ACTION, EXECUTION_RUNTIME_SYNC_ACTION,
EXECUTION_RUNTIME_SYNC_DECISION_ACTION, GEMINI_CHAT_STREAM_PLAN_KIND,
GEMINI_CHAT_SYNC_PLAN_KIND, GEMINI_CLI_STREAM_PLAN_KIND, GEMINI_CLI_SYNC_PLAN_KIND,
GEMINI_FILES_DELETE_PLAN_KIND, GEMINI_FILES_DOWNLOAD_PLAN_KIND, GEMINI_FILES_GET_PLAN_KIND,
GEMINI_FILES_LIST_PLAN_KIND, GEMINI_FILES_UPLOAD_PLAN_KIND, GEMINI_VIDEO_CANCEL_SYNC_PLAN_KIND,
GEMINI_EMBEDDING_SYNC_PLAN_KIND, GEMINI_FILES_DELETE_PLAN_KIND,
GEMINI_FILES_DOWNLOAD_PLAN_KIND, GEMINI_FILES_GET_PLAN_KIND, GEMINI_FILES_LIST_PLAN_KIND,
GEMINI_FILES_UPLOAD_PLAN_KIND, GEMINI_VIDEO_CANCEL_SYNC_PLAN_KIND,
GEMINI_VIDEO_CREATE_SYNC_PLAN_KIND, OPENAI_CHAT_STREAM_PLAN_KIND, OPENAI_CHAT_SYNC_PLAN_KIND,
OPENAI_EMBEDDING_SYNC_PLAN_KIND, OPENAI_IMAGE_STREAM_PLAN_KIND, OPENAI_IMAGE_SYNC_PLAN_KIND,
OPENAI_RERANK_SYNC_PLAN_KIND, OPENAI_RESPONSES_COMPACT_STREAM_PLAN_KIND,

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@@ -1,16 +1,16 @@
use crate::ai_serving::planner::common::{
CLAUDE_CHAT_STREAM_PLAN_KIND, CLAUDE_CHAT_SYNC_PLAN_KIND, CLAUDE_CLI_STREAM_PLAN_KIND,
CLAUDE_CLI_SYNC_PLAN_KIND, GEMINI_CHAT_STREAM_PLAN_KIND, GEMINI_CHAT_SYNC_PLAN_KIND,
GEMINI_CLI_STREAM_PLAN_KIND, GEMINI_CLI_SYNC_PLAN_KIND, GEMINI_FILES_DELETE_PLAN_KIND,
GEMINI_FILES_DOWNLOAD_PLAN_KIND, GEMINI_FILES_GET_PLAN_KIND, GEMINI_FILES_LIST_PLAN_KIND,
GEMINI_VIDEO_CANCEL_SYNC_PLAN_KIND, GEMINI_VIDEO_CREATE_SYNC_PLAN_KIND,
OPENAI_CHAT_STREAM_PLAN_KIND, OPENAI_CHAT_SYNC_PLAN_KIND, OPENAI_EMBEDDING_SYNC_PLAN_KIND,
OPENAI_IMAGE_STREAM_PLAN_KIND, OPENAI_IMAGE_SYNC_PLAN_KIND, OPENAI_RERANK_SYNC_PLAN_KIND,
OPENAI_RESPONSES_COMPACT_STREAM_PLAN_KIND, OPENAI_RESPONSES_COMPACT_SYNC_PLAN_KIND,
OPENAI_RESPONSES_STREAM_PLAN_KIND, OPENAI_RESPONSES_SYNC_PLAN_KIND,
OPENAI_VIDEO_CANCEL_SYNC_PLAN_KIND, OPENAI_VIDEO_CONTENT_PLAN_KIND,
OPENAI_VIDEO_CREATE_SYNC_PLAN_KIND, OPENAI_VIDEO_DELETE_SYNC_PLAN_KIND,
OPENAI_VIDEO_REMIX_SYNC_PLAN_KIND,
GEMINI_CLI_STREAM_PLAN_KIND, GEMINI_CLI_SYNC_PLAN_KIND, GEMINI_EMBEDDING_SYNC_PLAN_KIND,
GEMINI_FILES_DELETE_PLAN_KIND, GEMINI_FILES_DOWNLOAD_PLAN_KIND, GEMINI_FILES_GET_PLAN_KIND,
GEMINI_FILES_LIST_PLAN_KIND, GEMINI_VIDEO_CANCEL_SYNC_PLAN_KIND,
GEMINI_VIDEO_CREATE_SYNC_PLAN_KIND, OPENAI_CHAT_STREAM_PLAN_KIND, OPENAI_CHAT_SYNC_PLAN_KIND,
OPENAI_EMBEDDING_SYNC_PLAN_KIND, OPENAI_IMAGE_STREAM_PLAN_KIND, OPENAI_IMAGE_SYNC_PLAN_KIND,
OPENAI_RERANK_SYNC_PLAN_KIND, OPENAI_RESPONSES_COMPACT_STREAM_PLAN_KIND,
OPENAI_RESPONSES_COMPACT_SYNC_PLAN_KIND, OPENAI_RESPONSES_STREAM_PLAN_KIND,
OPENAI_RESPONSES_SYNC_PLAN_KIND, OPENAI_VIDEO_CANCEL_SYNC_PLAN_KIND,
OPENAI_VIDEO_CONTENT_PLAN_KIND, OPENAI_VIDEO_CREATE_SYNC_PLAN_KIND,
OPENAI_VIDEO_DELETE_SYNC_PLAN_KIND, OPENAI_VIDEO_REMIX_SYNC_PLAN_KIND,
};
use crate::ai_serving::planner::plan_builders::{
build_gemini_stream_plan_from_decision, build_gemini_sync_plan_from_decision,
@@ -110,7 +110,9 @@ fn build_sync_plan_payload_from_decision(
| OPENAI_RERANK_SYNC_PLAN_KIND => {
build_standard_sync_plan_from_decision(parts, body_json, payload)?
}
GEMINI_CHAT_SYNC_PLAN_KIND | GEMINI_CLI_SYNC_PLAN_KIND => {
GEMINI_CHAT_SYNC_PLAN_KIND
| GEMINI_CLI_SYNC_PLAN_KIND
| GEMINI_EMBEDDING_SYNC_PLAN_KIND => {
build_gemini_sync_plan_from_decision(parts, body_json, payload)?
}
OPENAI_VIDEO_CREATE_SYNC_PLAN_KIND

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@@ -254,6 +254,7 @@ pub(crate) async fn resolve_local_same_format_provider_candidate_payload_parts(
spec,
prepared.upstream_is_stream,
prepared.kiro_auth.as_ref(),
Some(&provider_request_body),
) else {
mark_skipped_local_same_format_provider_candidate_with_failure_diagnostic(
state,

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@@ -14,6 +14,7 @@ pub(crate) fn build_same_format_upstream_url(
spec: LocalSameFormatProviderSpec,
upstream_is_stream: bool,
kiro_auth: Option<&crate::ai_serving::transport::kiro::KiroRequestAuth>,
provider_request_body: Option<&serde_json::Value>,
) -> Option<String> {
build_same_format_provider_upstream_url_impl(
transport,
@@ -23,6 +24,7 @@ pub(crate) fn build_same_format_upstream_url(
upstream_is_stream,
request_query: parts.uri.query(),
kiro_api_region: kiro_auth.map(|auth| auth.auth_config.effective_api_region()),
provider_request_body,
},
)
}

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@@ -361,6 +361,7 @@ async fn resolve_local_openai_image_to_gemini_candidate_payload_parts(
&converted.mapped_model,
provider_api_format,
upstream_is_stream,
Some(&converted.body_json),
) else {
mark_skipped_local_openai_image_candidate_with_failure_diagnostic(
state,

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@@ -75,15 +75,18 @@ pub(crate) async fn resolve_local_standard_candidate_payload_parts(
.await;
}
let is_kiro_claude_cli = is_kiro_claude_messages_transport(transport, provider_api_format);
let Some(conversion_kind) =
crate::ai_serving::request_conversion_kind(spec_metadata.api_format, provider_api_format)
else {
return None;
};
if let Some(skip_reason) = crate::ai_serving::request_conversion_transport_unsupported_reason(
if !crate::ai_serving::request_pair_allowed_for_transport(
transport,
conversion_kind,
spec_metadata.api_format,
provider_api_format,
) {
return None;
}
if let Some(skip_reason) = crate::ai_serving::request_pair_transport_unsupported_reason(
transport,
spec_metadata.api_format,
provider_api_format,
) {
mark_skipped_local_standard_candidate(
state,
@@ -156,7 +159,7 @@ pub(crate) async fn resolve_local_standard_candidate_payload_parts(
planner_state,
transport,
candidate,
crate::ai_serving::request_conversion_direct_auth(transport, conversion_kind),
crate::ai_serving::request_pair_direct_auth(transport, provider_api_format),
oauth_context,
)
.await
@@ -286,6 +289,7 @@ pub(crate) async fn resolve_local_standard_candidate_payload_parts(
&prepared_candidate.mapped_model,
provider_api_format,
upstream_is_stream,
Some(&provider_request_body),
) {
Some(url) => url,
None => {

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@@ -38,6 +38,7 @@ pub(crate) use self::openai::{
map_openai_reasoning_effort_to_gemini_budget, maybe_build_stream_local_decision_payload,
maybe_build_stream_local_openai_responses_decision_payload,
maybe_build_sync_local_decision_payload,
maybe_build_sync_local_openai_embedding_decision_payload,
maybe_build_sync_local_openai_responses_decision_payload, parse_openai_stop_sequences,
resolve_openai_chat_max_tokens, set_local_openai_chat_execution_exhausted_diagnostic,
value_as_u64,
@@ -66,14 +67,16 @@ pub(crate) fn build_standard_upstream_url(
mapped_model: &str,
provider_api_format: &str,
upstream_is_stream: bool,
provider_request_body: Option<&serde_json::Value>,
) -> Option<String> {
crate::ai_serving::build_provider_transport_request_url(
crate::ai_serving::build_provider_transport_request_url_for_request_body(
transport,
provider_api_format,
Some(mapped_model),
upstream_is_stream,
parts.uri.query(),
None,
provider_request_body,
)
}
@@ -85,6 +88,14 @@ pub(crate) async fn maybe_build_sync_local_standard_decision_payload(
body_json: &serde_json::Value,
plan_kind: &str,
) -> Result<Option<AiExecutionDecision>, GatewayError> {
if let Some(payload) = self::openai::maybe_build_sync_local_openai_embedding_decision_payload(
state, parts, trace_id, decision, body_json, plan_kind,
)
.await?
{
return Ok(Some(payload));
}
if let Some(payload) = self::claude::maybe_build_sync_local_claude_decision_payload(
state, parts, trace_id, decision, body_json, plan_kind,
)

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@@ -0,0 +1,31 @@
use crate::ai_serving::resolve_openai_embedding_sync_spec as resolve_surface_sync_spec;
use crate::ai_serving::GatewayControlDecision;
use crate::{AiExecutionDecision, AppState, GatewayError};
use super::super::family::maybe_build_sync_via_standard_family_payload;
pub(crate) fn resolve_sync_spec(
plan_kind: &str,
) -> Option<super::super::family::LocalStandardSpec> {
resolve_surface_sync_spec(plan_kind)
}
pub(crate) async fn maybe_build_sync_local_openai_embedding_decision_payload(
state: &AppState,
parts: &http::request::Parts,
trace_id: &str,
decision: &GatewayControlDecision,
body_json: &serde_json::Value,
plan_kind: &str,
) -> Result<Option<AiExecutionDecision>, GatewayError> {
maybe_build_sync_via_standard_family_payload(
state,
parts,
trace_id,
decision,
body_json,
plan_kind,
resolve_sync_spec,
)
.await
}

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@@ -1,4 +1,5 @@
mod chat;
mod embedding;
mod responses;
pub(crate) use crate::ai_serving::{
@@ -14,6 +15,7 @@ pub(crate) use chat::{
maybe_build_stream_local_decision_payload, maybe_build_sync_local_decision_payload,
set_local_openai_chat_execution_exhausted_diagnostic,
};
pub(crate) use embedding::maybe_build_sync_local_openai_embedding_decision_payload;
pub(crate) use responses::{
build_local_openai_responses_stream_attempt_source_for_kind,
build_local_openai_responses_stream_plan_and_reports_for_kind,

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@@ -80,8 +80,8 @@ pub(crate) use aether_ai_formats::api::{
resolve_local_image_stream_spec, resolve_local_image_sync_spec,
resolve_local_same_format_stream_spec, resolve_local_same_format_sync_spec,
resolve_local_video_sync_spec, resolve_openai_chat_max_tokens,
resolve_openai_responses_stream_spec, resolve_openai_responses_sync_spec,
resolve_requested_gemini_image_model_for_request,
resolve_openai_embedding_sync_spec, resolve_openai_responses_stream_spec,
resolve_openai_responses_sync_spec, resolve_requested_gemini_image_model_for_request,
resolve_requested_openai_image_model_for_request,
resolve_upstream_is_stream_from_endpoint_config, sanitize_request_path,
sanitize_request_path_and_query, sanitize_request_query_string,
@@ -119,6 +119,7 @@ pub(crate) use aether_ai_formats::api::{
GEMINI_CLI_STREAM_SUCCESS_REPORT_KIND, GEMINI_CLI_SYNC_ERROR_REPORT_KIND,
GEMINI_CLI_SYNC_FINALIZE_REPORT_KIND, GEMINI_CLI_SYNC_PLAN_KIND,
GEMINI_CLI_SYNC_SUCCESS_REPORT_KIND, GEMINI_CLI_V1INTERNAL_ENVELOPE_NAME,
GEMINI_EMBEDDING_SYNC_PLAN_KIND, GEMINI_EMBEDDING_SYNC_SUCCESS_REPORT_KIND,
GEMINI_FILES_DELETE_PLAN_KIND, GEMINI_FILES_DOWNLOAD_PLAN_KIND, GEMINI_FILES_GET_PLAN_KIND,
GEMINI_FILES_LIST_PLAN_KIND, GEMINI_FILES_UPLOAD_PLAN_KIND, GEMINI_VIDEO_CANCEL_SYNC_PLAN_KIND,
GEMINI_VIDEO_CREATE_SYNC_FINALIZE_REPORT_KIND, GEMINI_VIDEO_CREATE_SYNC_PLAN_KIND,

View File

@@ -61,18 +61,19 @@ pub(crate) use aether_provider_transport::{
build_same_format_provider_upstream_url, build_standard_plan_fallback_headers,
build_standard_plan_fallback_openai_chat_url,
build_standard_plan_fallback_openai_responses_url, build_standard_provider_request_headers,
build_transport_request_url, build_video_create_headers, build_video_create_request_body,
build_video_create_upstream_url, candidate_common_transport_skip_reason,
candidate_transport_pair_skip_reason, classify_same_format_provider_request_behavior,
ensure_upstream_auth_header, gemini_files_transport_unsupported_reason,
header_rules_are_locally_supported, header_rules_have_enabled_rules,
local_gemini_transport_unsupported_reason_with_network,
build_transport_request_url, build_transport_request_url_for_request_body,
build_video_create_headers, build_video_create_request_body, build_video_create_upstream_url,
candidate_common_transport_skip_reason, candidate_transport_pair_skip_reason,
classify_same_format_provider_request_behavior, ensure_upstream_auth_header,
gemini_files_transport_unsupported_reason, header_rules_are_locally_supported,
header_rules_have_enabled_rules, local_gemini_transport_unsupported_reason_with_network,
local_openai_chat_transport_unsupported_reason,
local_standard_transport_unsupported_reason_with_network,
openai_image_transport_unsupported_reason, request_conversion_direct_auth,
request_conversion_enabled_for_transport, request_conversion_transport_supported,
request_conversion_transport_unsupported_reason, request_pair_allowed_for_transport,
resolve_gemini_files_auth, resolve_openai_image_auth, resolve_same_format_provider_direct_auth,
request_pair_direct_auth, request_pair_transport_unsupported_reason, resolve_gemini_files_auth,
resolve_openai_image_auth, resolve_same_format_provider_direct_auth,
resolve_transport_execution_timeouts, resolve_transport_profile,
resolve_transport_proxy_snapshot, resolve_transport_proxy_snapshot_with_tunnel_affinity,
resolve_video_create_auth, same_format_provider_transport_supported,

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@@ -104,6 +104,17 @@ pub(super) fn classify_ai_public_route(
"gemini:video",
true,
))
} else if normalized_path.ends_with(":embedContent")
|| normalized_path.ends_with(":batchEmbedContents")
{
Some(classified_with_request_auth_channel(
"ai_public",
"gemini",
"embedding",
"api_key",
"gemini:embedding",
true,
))
} else if is_gemini_cli_request(headers) {
Some(classified_with_request_auth_channel(
"ai_public",

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@@ -229,6 +229,8 @@ pub(super) fn is_gemini_models_route(path: &str) -> bool {
(path.starts_with("/v1/models/") || path.starts_with("/v1beta/models/"))
&& (path.contains(":generateContent")
|| path.contains(":streamGenerateContent")
|| path.contains(":embedContent")
|| path.contains(":batchEmbedContents")
|| path.contains(":predictLongRunning"))
}

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@@ -197,6 +197,44 @@ fn classifies_gemini_generate_content_api_key_without_cli_marker() {
assert!(decision.is_execution_runtime_candidate());
}
#[test]
fn classifies_gemini_embed_content_as_embedding_route() {
let headers = headers(&[("x-goog-api-key", "gemini-key")]);
let uri: Uri = "/v1beta/models/gemini-embedding-2-preview:embedContent"
.parse()
.expect("uri should parse");
let decision =
classify_control_route(&http::Method::POST, &uri, &headers).expect("route should classify");
assert_eq!(decision.route_family.as_deref(), Some("gemini"));
assert_eq!(decision.route_kind.as_deref(), Some("embedding"));
assert_eq!(decision.request_auth_channel.as_deref(), Some("api_key"));
assert_eq!(
decision.auth_endpoint_signature.as_deref(),
Some("gemini:embedding")
);
assert!(decision.is_execution_runtime_candidate());
}
#[test]
fn classifies_gemini_batch_embed_contents_as_embedding_route() {
let headers = headers(&[("x-goog-api-key", "gemini-key")]);
let uri: Uri = "/v1beta/models/gemini-embedding-2-preview:batchEmbedContents"
.parse()
.expect("uri should parse");
let decision =
classify_control_route(&http::Method::POST, &uri, &headers).expect("route should classify");
assert_eq!(decision.route_family.as_deref(), Some("gemini"));
assert_eq!(decision.route_kind.as_deref(), Some("embedding"));
assert_eq!(decision.request_auth_channel.as_deref(), Some("api_key"));
assert_eq!(
decision.auth_endpoint_signature.as_deref(),
Some("gemini:embedding")
);
assert!(decision.is_execution_runtime_candidate());
}
#[test]
fn classifies_gemini_predict_long_running_as_video_route() {
let headers = headers(&[]);

View File

@@ -78,6 +78,87 @@ fn embedding_execution_runtime() -> Router {
)
}
fn gemini_embedding_success_state(
execution_runtime_url: String,
client_api_format: &str,
) -> AppState {
let mut snapshot = sample_currently_usable_auth_snapshot(
"key-gemini-embedding-success",
"user-gemini-embedding-success",
);
snapshot.user_allowed_providers = None;
snapshot.api_key_allowed_providers = None;
snapshot.user_allowed_api_formats = Some(vec![client_api_format.to_string()]);
snapshot.api_key_allowed_api_formats = Some(vec![client_api_format.to_string()]);
snapshot.user_allowed_models = Some(vec!["gemini-embedding-2-preview".to_string()]);
snapshot.api_key_allowed_models = Some(vec!["gemini-embedding-2-preview".to_string()]);
let auth_repository = Arc::new(InMemoryAuthApiKeySnapshotRepository::seed(vec![(
Some(hash_api_key("sk-gemini-embedding-success")),
snapshot,
)]));
let candidate_repository =
Arc::new(InMemoryMinimalCandidateSelectionReadRepository::seed(vec![
gemini_embedding_candidate_row(),
]));
let mut provider = sample_provider("provider-gemini-embedding", "Gemini Embeddings", 1);
provider.provider_type = "gemini".to_string();
let provider_catalog_repository = Arc::new(InMemoryProviderCatalogReadRepository::seed(
vec![provider],
vec![sample_endpoint(
"endpoint-gemini-embedding",
"provider-gemini-embedding",
"gemini:embedding",
"https://generativelanguage.googleapis.com/v1beta",
)],
vec![sample_key(
"key-upstream-gemini-embedding",
"provider-gemini-embedding",
"gemini:embedding",
"sk-upstream-gemini-embedding",
)],
));
let data_state =
GatewayDataState::with_provider_catalog_and_minimal_candidate_selection_for_tests(
provider_catalog_repository,
candidate_repository,
)
.with_auth_api_key_reader(auth_repository)
.with_encryption_key_for_tests(DEVELOPMENT_ENCRYPTION_KEY);
build_state_with_execution_runtime_override(execution_runtime_url)
.with_data_state_for_tests(data_state)
}
fn gemini_embedding_conversion_execution_runtime() -> Router {
Router::new().route(
"/v1/execute/sync",
any(|Json(plan): Json<ExecutionPlan>| async move {
assert_openai_to_gemini_embedding_execution_plan(&plan);
Json(gemini_embedding_execution_result(&plan))
}),
)
}
fn gemini_embedding_batch_conversion_execution_runtime() -> Router {
Router::new().route(
"/v1/execute/sync",
any(|Json(plan): Json<ExecutionPlan>| async move {
assert_openai_to_gemini_batch_embedding_execution_plan(&plan);
Json(gemini_batch_embedding_execution_result(&plan))
}),
)
}
fn gemini_embedding_native_execution_runtime() -> Router {
Router::new().route(
"/v1/execute/sync",
any(|Json(plan): Json<ExecutionPlan>| async move {
assert_native_gemini_embedding_execution_plan(&plan);
Json(gemini_embedding_execution_result(&plan))
}),
)
}
fn embedding_candidate_row() -> StoredMinimalCandidateSelectionRow {
StoredMinimalCandidateSelectionRow {
provider_id: "provider-embedding".to_string(),
@@ -112,6 +193,40 @@ fn embedding_candidate_row() -> StoredMinimalCandidateSelectionRow {
}
}
fn gemini_embedding_candidate_row() -> StoredMinimalCandidateSelectionRow {
StoredMinimalCandidateSelectionRow {
provider_id: "provider-gemini-embedding".to_string(),
provider_name: "Gemini Embeddings".to_string(),
provider_type: "gemini".to_string(),
provider_priority: 1,
provider_is_active: true,
endpoint_id: "endpoint-gemini-embedding".to_string(),
endpoint_api_format: "gemini:embedding".to_string(),
endpoint_api_family: Some("gemini".to_string()),
endpoint_kind: Some("embedding".to_string()),
endpoint_is_active: true,
key_id: "key-upstream-gemini-embedding".to_string(),
key_name: "default".to_string(),
key_auth_type: "api_key".to_string(),
key_is_active: true,
key_api_formats: Some(vec!["gemini:embedding".to_string()]),
key_allowed_models: None,
key_capabilities: None,
key_internal_priority: 50,
key_global_priority_by_format: None,
model_id: "model-gemini-embedding-preview".to_string(),
global_model_id: "global-gemini-embedding-preview".to_string(),
global_model_name: "gemini-embedding-2-preview".to_string(),
global_model_mappings: None,
global_model_supports_streaming: Some(false),
model_provider_model_name: "gemini-embedding-2-preview".to_string(),
model_provider_model_mappings: None,
model_supports_streaming: Some(false),
model_is_active: true,
model_is_available: true,
}
}
fn assert_embedding_execution_plan(plan: &ExecutionPlan) {
assert_eq!(plan.client_api_format, "openai:embedding");
assert_eq!(plan.provider_api_format, "openai:embedding");
@@ -123,6 +238,78 @@ fn assert_embedding_execution_plan(plan: &ExecutionPlan) {
assert!(body.get("input").is_some());
}
fn assert_openai_to_gemini_embedding_execution_plan(plan: &ExecutionPlan) {
assert_eq!(plan.client_api_format, "openai:embedding");
assert_eq!(plan.provider_api_format, "gemini:embedding");
assert_eq!(plan.method, "POST");
assert_eq!(
plan.url,
"https://generativelanguage.googleapis.com/v1beta/models/gemini-embedding-2-preview:embedContent"
);
assert_eq!(
plan.headers.get("x-goog-api-key").map(String::as_str),
Some("sk-upstream-gemini-embedding")
);
assert_eq!(
plan.model_name.as_deref(),
Some("gemini-embedding-2-preview")
);
assert!(!plan.stream);
let body = plan.body.json_body.as_ref().expect("json request body");
assert_eq!(body["model"], "gemini-embedding-2-preview");
assert_eq!(body["content"]["parts"][0]["text"], "hello");
assert!(body.get("input").is_none());
assert!(body.get("messages").is_none());
}
fn assert_openai_to_gemini_batch_embedding_execution_plan(plan: &ExecutionPlan) {
assert_eq!(plan.client_api_format, "openai:embedding");
assert_eq!(plan.provider_api_format, "gemini:embedding");
assert_eq!(plan.method, "POST");
assert_eq!(
plan.url,
"https://generativelanguage.googleapis.com/v1beta/models/gemini-embedding-2-preview:batchEmbedContents"
);
assert_eq!(
plan.headers.get("x-goog-api-key").map(String::as_str),
Some("sk-upstream-gemini-embedding")
);
assert!(!plan.stream);
let body = plan.body.json_body.as_ref().expect("json request body");
assert!(body.get("model").is_none());
let requests = body["requests"].as_array().expect("batch requests");
assert_eq!(requests.len(), 2);
assert_eq!(requests[0]["model"], "models/gemini-embedding-2-preview");
assert_eq!(requests[0]["content"]["parts"][0]["text"], "hello");
assert_eq!(requests[1]["model"], "models/gemini-embedding-2-preview");
assert_eq!(requests[1]["content"]["parts"][0]["text"], "world");
assert!(body.get("input").is_none());
assert!(body.get("messages").is_none());
}
fn assert_native_gemini_embedding_execution_plan(plan: &ExecutionPlan) {
assert_eq!(plan.client_api_format, "gemini:embedding");
assert_eq!(plan.provider_api_format, "gemini:embedding");
assert_eq!(plan.method, "POST");
assert_eq!(
plan.url,
"https://generativelanguage.googleapis.com/v1beta/models/gemini-embedding-2-preview:embedContent"
);
assert_eq!(
plan.headers.get("x-goog-api-key").map(String::as_str),
Some("sk-upstream-gemini-embedding")
);
assert_eq!(
plan.model_name.as_deref(),
Some("gemini-embedding-2-preview")
);
assert!(!plan.stream);
let body = plan.body.json_body.as_ref().expect("json request body");
assert_eq!(body["content"]["parts"][0]["text"], "hello");
assert!(body.get("input").is_none());
assert!(body.get("messages").is_none());
}
fn embedding_execution_result(plan: &ExecutionPlan) -> ExecutionResult {
ExecutionResult {
request_id: plan.request_id.clone(),
@@ -145,6 +332,55 @@ fn embedding_execution_result(plan: &ExecutionPlan) -> ExecutionResult {
}
}
fn gemini_embedding_execution_result(plan: &ExecutionPlan) -> ExecutionResult {
ExecutionResult {
request_id: plan.request_id.clone(),
candidate_id: plan.candidate_id.clone(),
status_code: 200,
headers: BTreeMap::from([("content-type".to_string(), "application/json".to_string())]),
body: Some(ResponseBody {
json_body: Some(json!({
"model": "gemini-embedding-2-preview",
"embedding": {
"values": [0.1, 0.2, 0.3]
},
"usageMetadata": {
"promptTokenCount": 4,
"totalTokenCount": 4
}
})),
body_bytes_b64: None,
}),
telemetry: None,
error: None,
}
}
fn gemini_batch_embedding_execution_result(plan: &ExecutionPlan) -> ExecutionResult {
ExecutionResult {
request_id: plan.request_id.clone(),
candidate_id: plan.candidate_id.clone(),
status_code: 200,
headers: BTreeMap::from([("content-type".to_string(), "application/json".to_string())]),
body: Some(ResponseBody {
json_body: Some(json!({
"model": "gemini-embedding-2-preview",
"embeddings": [
{"values": [0.1, 0.2, 0.3]},
{"values": [0.4, 0.5, 0.6]}
],
"usageMetadata": {
"promptTokenCount": 8,
"totalTokenCount": 8
}
})),
body_bytes_b64: None,
}),
telemetry: None,
error: None,
}
}
#[tokio::test]
async fn embeddings_route_accepts_openai_payload() {
let (execution_runtime_url, execution_runtime_handle) =
@@ -215,6 +451,157 @@ async fn embeddings_route_accepts_openai_payload() {
execution_runtime_handle.abort();
}
#[tokio::test]
async fn embeddings_route_converts_openai_payload_to_gemini_embedding_provider() {
let (execution_runtime_url, execution_runtime_handle) =
start_server(gemini_embedding_conversion_execution_runtime()).await;
let gateway = build_router_with_state(gemini_embedding_success_state(
execution_runtime_url,
"openai:embedding",
));
let (gateway_url, gateway_handle) = start_server(gateway).await;
let response = reqwest::Client::new()
.post(format!("{gateway_url}/v1/embeddings"))
.header(
http::header::AUTHORIZATION,
"Bearer sk-gemini-embedding-success",
)
.json(&json!({
"model": "gemini-embedding-2-preview",
"input": "hello"
}))
.send()
.await
.expect("request should succeed");
assert_eq!(response.status(), StatusCode::OK);
assert_eq!(
response
.headers()
.get(CONTROL_ENDPOINT_SIGNATURE_HEADER)
.and_then(|value| value.to_str().ok()),
Some("openai:embedding")
);
assert_eq!(
response
.headers()
.get(CONTROL_EXECUTION_RUNTIME_HEADER)
.and_then(|value| value.to_str().ok()),
Some("true")
);
let payload: serde_json::Value = response.json().await.expect("body should parse");
assert_eq!(payload["object"], "list");
assert_eq!(payload["model"], "gemini-embedding-2-preview");
assert_eq!(payload["data"][0]["object"], "embedding");
assert_eq!(payload["data"][0]["embedding"], json!([0.1, 0.2, 0.3]));
assert_eq!(payload["usage"]["prompt_tokens"], json!(4));
assert_eq!(payload["usage"]["total_tokens"], json!(4));
gateway_handle.abort();
execution_runtime_handle.abort();
}
#[tokio::test]
async fn embeddings_route_converts_openai_batch_payload_to_gemini_batch_endpoint() {
let (execution_runtime_url, execution_runtime_handle) =
start_server(gemini_embedding_batch_conversion_execution_runtime()).await;
let gateway = build_router_with_state(gemini_embedding_success_state(
execution_runtime_url,
"openai:embedding",
));
let (gateway_url, gateway_handle) = start_server(gateway).await;
let response = reqwest::Client::new()
.post(format!("{gateway_url}/v1/embeddings"))
.header(
http::header::AUTHORIZATION,
"Bearer sk-gemini-embedding-success",
)
.json(&json!({
"model": "gemini-embedding-2-preview",
"input": ["hello", "world"]
}))
.send()
.await
.expect("request should succeed");
assert_eq!(response.status(), StatusCode::OK);
assert_eq!(
response
.headers()
.get(CONTROL_ENDPOINT_SIGNATURE_HEADER)
.and_then(|value| value.to_str().ok()),
Some("openai:embedding")
);
let payload: serde_json::Value = response.json().await.expect("body should parse");
assert_eq!(payload["object"], "list");
assert_eq!(payload["data"].as_array().map(Vec::len), Some(2));
assert_eq!(payload["data"][0]["index"], json!(0));
assert_eq!(payload["data"][0]["embedding"], json!([0.1, 0.2, 0.3]));
assert_eq!(payload["data"][1]["index"], json!(1));
assert_eq!(payload["data"][1]["embedding"], json!([0.4, 0.5, 0.6]));
assert_eq!(payload["usage"]["prompt_tokens"], json!(8));
assert_eq!(payload["usage"]["total_tokens"], json!(8));
gateway_handle.abort();
execution_runtime_handle.abort();
}
#[tokio::test]
async fn gemini_embed_content_route_uses_native_gemini_embedding_provider() {
let (execution_runtime_url, execution_runtime_handle) =
start_server(gemini_embedding_native_execution_runtime()).await;
let gateway = build_router_with_state(gemini_embedding_success_state(
execution_runtime_url,
"gemini:embedding",
));
let (gateway_url, gateway_handle) = start_server(gateway).await;
let response = reqwest::Client::new()
.post(format!(
"{gateway_url}/v1beta/models/gemini-embedding-2-preview:embedContent"
))
.header("x-goog-api-key", "sk-gemini-embedding-success")
.json(&json!({
"content": {
"parts": [{"text": "hello"}]
}
}))
.send()
.await
.expect("request should succeed");
assert_eq!(response.status(), StatusCode::OK);
assert_eq!(
response
.headers()
.get(CONTROL_ROUTE_FAMILY_HEADER)
.and_then(|value| value.to_str().ok()),
Some("gemini")
);
assert_eq!(
response
.headers()
.get(CONTROL_ROUTE_KIND_HEADER)
.and_then(|value| value.to_str().ok()),
Some("embedding")
);
assert_eq!(
response
.headers()
.get(CONTROL_ENDPOINT_SIGNATURE_HEADER)
.and_then(|value| value.to_str().ok()),
Some("gemini:embedding")
);
let payload: serde_json::Value = response.json().await.expect("body should parse");
assert_eq!(payload["embedding"]["values"], json!([0.1, 0.2, 0.3]));
assert_eq!(payload["model"], "gemini-embedding-2-preview");
gateway_handle.abort();
execution_runtime_handle.abort();
}
#[tokio::test]
async fn embeddings_route_accepts_all_canonical_input_shapes() {
let (execution_runtime_url, execution_runtime_handle) =

View File

@@ -16,18 +16,21 @@ pub use crate::contracts::{
GEMINI_CHAT_SYNC_SUCCESS_REPORT_KIND, GEMINI_CLI_STREAM_PLAN_KIND,
GEMINI_CLI_STREAM_SUCCESS_REPORT_KIND, GEMINI_CLI_SYNC_ERROR_REPORT_KIND,
GEMINI_CLI_SYNC_FINALIZE_REPORT_KIND, GEMINI_CLI_SYNC_PLAN_KIND,
GEMINI_CLI_SYNC_SUCCESS_REPORT_KIND, GEMINI_FILES_DELETE_PLAN_KIND,
GEMINI_CLI_SYNC_SUCCESS_REPORT_KIND, GEMINI_EMBEDDING_SYNC_PLAN_KIND,
GEMINI_EMBEDDING_SYNC_SUCCESS_REPORT_KIND, GEMINI_FILES_DELETE_PLAN_KIND,
GEMINI_FILES_DOWNLOAD_PLAN_KIND, GEMINI_FILES_GET_PLAN_KIND, GEMINI_FILES_LIST_PLAN_KIND,
GEMINI_FILES_UPLOAD_PLAN_KIND, GEMINI_VIDEO_CANCEL_SYNC_PLAN_KIND,
GEMINI_VIDEO_CREATE_SYNC_FINALIZE_REPORT_KIND, GEMINI_VIDEO_CREATE_SYNC_PLAN_KIND,
OPENAI_CHAT_STREAM_PLAN_KIND, OPENAI_CHAT_STREAM_SUCCESS_REPORT_KIND,
OPENAI_CHAT_SYNC_ERROR_REPORT_KIND, OPENAI_CHAT_SYNC_FINALIZE_REPORT_KIND,
OPENAI_CHAT_SYNC_PLAN_KIND, OPENAI_CHAT_SYNC_SUCCESS_REPORT_KIND,
OPENAI_EMBEDDING_SYNC_PLAN_KIND, OPENAI_IMAGE_STREAM_PLAN_KIND,
OPENAI_IMAGE_STREAM_SUCCESS_REPORT_KIND, OPENAI_IMAGE_SYNC_ERROR_REPORT_KIND,
OPENAI_IMAGE_SYNC_FINALIZE_REPORT_KIND, OPENAI_IMAGE_SYNC_PLAN_KIND,
OPENAI_IMAGE_SYNC_SUCCESS_REPORT_KIND, OPENAI_RERANK_SYNC_PLAN_KIND,
OPENAI_RESPONSES_COMPACT_STREAM_PLAN_KIND, OPENAI_RESPONSES_COMPACT_STREAM_SUCCESS_REPORT_KIND,
OPENAI_EMBEDDING_SYNC_ERROR_REPORT_KIND, OPENAI_EMBEDDING_SYNC_FINALIZE_REPORT_KIND,
OPENAI_EMBEDDING_SYNC_PLAN_KIND, OPENAI_EMBEDDING_SYNC_SUCCESS_REPORT_KIND,
OPENAI_IMAGE_STREAM_PLAN_KIND, OPENAI_IMAGE_STREAM_SUCCESS_REPORT_KIND,
OPENAI_IMAGE_SYNC_ERROR_REPORT_KIND, OPENAI_IMAGE_SYNC_FINALIZE_REPORT_KIND,
OPENAI_IMAGE_SYNC_PLAN_KIND, OPENAI_IMAGE_SYNC_SUCCESS_REPORT_KIND,
OPENAI_RERANK_SYNC_PLAN_KIND, OPENAI_RESPONSES_COMPACT_STREAM_PLAN_KIND,
OPENAI_RESPONSES_COMPACT_STREAM_SUCCESS_REPORT_KIND,
OPENAI_RESPONSES_COMPACT_SYNC_ERROR_REPORT_KIND,
OPENAI_RESPONSES_COMPACT_SYNC_FINALIZE_REPORT_KIND, OPENAI_RESPONSES_COMPACT_SYNC_PLAN_KIND,
OPENAI_RESPONSES_COMPACT_SYNC_SUCCESS_REPORT_KIND, OPENAI_RESPONSES_STREAM_PLAN_KIND,
@@ -139,18 +142,22 @@ pub use crate::formats::{
resolve_stream_spec as resolve_gemini_stream_spec,
resolve_sync_spec as resolve_gemini_sync_spec,
},
openai::responses::{
codex::{
apply_codex_openai_responses_chat_body_edits,
apply_codex_openai_responses_special_body_edits,
apply_codex_openai_responses_special_headers,
apply_openai_responses_compact_special_body_edits, CODEX_OPENAI_IMAGE_DEFAULT_MODEL,
CODEX_OPENAI_IMAGE_DEFAULT_OUTPUT_FORMAT, CODEX_OPENAI_IMAGE_DEFAULT_VARIATION_MODEL,
CODEX_OPENAI_IMAGE_DEFAULT_VARIATION_PROMPT, CODEX_OPENAI_IMAGE_INTERNAL_MODEL,
},
spec::{
resolve_stream_spec as resolve_openai_responses_stream_spec,
resolve_sync_spec as resolve_openai_responses_sync_spec, LocalOpenAiResponsesSpec,
openai::{
embedding::spec::resolve_sync_spec as resolve_openai_embedding_sync_spec,
responses::{
codex::{
apply_codex_openai_responses_chat_body_edits,
apply_codex_openai_responses_special_body_edits,
apply_codex_openai_responses_special_headers,
apply_openai_responses_compact_special_body_edits,
CODEX_OPENAI_IMAGE_DEFAULT_MODEL, CODEX_OPENAI_IMAGE_DEFAULT_OUTPUT_FORMAT,
CODEX_OPENAI_IMAGE_DEFAULT_VARIATION_MODEL,
CODEX_OPENAI_IMAGE_DEFAULT_VARIATION_PROMPT, CODEX_OPENAI_IMAGE_INTERNAL_MODEL,
},
spec::{
resolve_stream_spec as resolve_openai_responses_stream_spec,
resolve_sync_spec as resolve_openai_responses_sync_spec, LocalOpenAiResponsesSpec,
},
},
},
shared::{

View File

@@ -14,9 +14,9 @@ pub use plan_kinds::{
is_openai_responses_stream_plan_kind, is_openai_responses_sync_plan_kind,
CLAUDE_CHAT_STREAM_PLAN_KIND, CLAUDE_CHAT_SYNC_PLAN_KIND, CLAUDE_CLI_STREAM_PLAN_KIND,
CLAUDE_CLI_SYNC_PLAN_KIND, GEMINI_CHAT_STREAM_PLAN_KIND, GEMINI_CHAT_SYNC_PLAN_KIND,
GEMINI_CLI_STREAM_PLAN_KIND, GEMINI_CLI_SYNC_PLAN_KIND, GEMINI_FILES_DELETE_PLAN_KIND,
GEMINI_FILES_DOWNLOAD_PLAN_KIND, GEMINI_FILES_GET_PLAN_KIND, GEMINI_FILES_LIST_PLAN_KIND,
GEMINI_FILES_UPLOAD_PLAN_KIND, GEMINI_VIDEO_CANCEL_SYNC_PLAN_KIND,
GEMINI_CLI_STREAM_PLAN_KIND, GEMINI_CLI_SYNC_PLAN_KIND, GEMINI_EMBEDDING_SYNC_PLAN_KIND,
GEMINI_FILES_DELETE_PLAN_KIND, GEMINI_FILES_DOWNLOAD_PLAN_KIND, GEMINI_FILES_GET_PLAN_KIND,
GEMINI_FILES_LIST_PLAN_KIND, GEMINI_FILES_UPLOAD_PLAN_KIND, GEMINI_VIDEO_CANCEL_SYNC_PLAN_KIND,
GEMINI_VIDEO_CREATE_SYNC_PLAN_KIND, OPENAI_CHAT_STREAM_PLAN_KIND, OPENAI_CHAT_SYNC_PLAN_KIND,
OPENAI_EMBEDDING_SYNC_PLAN_KIND, OPENAI_IMAGE_STREAM_PLAN_KIND, OPENAI_IMAGE_SYNC_PLAN_KIND,
OPENAI_RERANK_SYNC_PLAN_KIND, OPENAI_RESPONSES_COMPACT_STREAM_PLAN_KIND,
@@ -36,9 +36,11 @@ pub use report_kinds::{
GEMINI_CHAT_SYNC_ERROR_REPORT_KIND, GEMINI_CHAT_SYNC_FINALIZE_REPORT_KIND,
GEMINI_CHAT_SYNC_SUCCESS_REPORT_KIND, GEMINI_CLI_STREAM_SUCCESS_REPORT_KIND,
GEMINI_CLI_SYNC_ERROR_REPORT_KIND, GEMINI_CLI_SYNC_FINALIZE_REPORT_KIND,
GEMINI_CLI_SYNC_SUCCESS_REPORT_KIND, GEMINI_VIDEO_CREATE_SYNC_FINALIZE_REPORT_KIND,
OPENAI_CHAT_STREAM_SUCCESS_REPORT_KIND, OPENAI_CHAT_SYNC_ERROR_REPORT_KIND,
OPENAI_CHAT_SYNC_FINALIZE_REPORT_KIND, OPENAI_CHAT_SYNC_SUCCESS_REPORT_KIND,
GEMINI_CLI_SYNC_SUCCESS_REPORT_KIND, GEMINI_EMBEDDING_SYNC_SUCCESS_REPORT_KIND,
GEMINI_VIDEO_CREATE_SYNC_FINALIZE_REPORT_KIND, OPENAI_CHAT_STREAM_SUCCESS_REPORT_KIND,
OPENAI_CHAT_SYNC_ERROR_REPORT_KIND, OPENAI_CHAT_SYNC_FINALIZE_REPORT_KIND,
OPENAI_CHAT_SYNC_SUCCESS_REPORT_KIND, OPENAI_EMBEDDING_SYNC_ERROR_REPORT_KIND,
OPENAI_EMBEDDING_SYNC_FINALIZE_REPORT_KIND, OPENAI_EMBEDDING_SYNC_SUCCESS_REPORT_KIND,
OPENAI_IMAGE_STREAM_SUCCESS_REPORT_KIND, OPENAI_IMAGE_SYNC_ERROR_REPORT_KIND,
OPENAI_IMAGE_SYNC_FINALIZE_REPORT_KIND, OPENAI_IMAGE_SYNC_SUCCESS_REPORT_KIND,
OPENAI_RESPONSES_COMPACT_STREAM_SUCCESS_REPORT_KIND,

View File

@@ -22,6 +22,7 @@ pub const OPENAI_VIDEO_CREATE_SYNC_PLAN_KIND: &str = "openai_video_create_sync";
pub const OPENAI_CHAT_SYNC_PLAN_KIND: &str = "openai_chat_sync";
pub const OPENAI_EMBEDDING_SYNC_PLAN_KIND: &str = "openai_embedding_sync";
pub const OPENAI_RERANK_SYNC_PLAN_KIND: &str = "openai_rerank_sync";
pub const GEMINI_EMBEDDING_SYNC_PLAN_KIND: &str = "gemini_embedding_sync";
pub const OPENAI_RESPONSES_SYNC_PLAN_KIND: &str = "openai_responses_sync";
pub const OPENAI_RESPONSES_COMPACT_SYNC_PLAN_KIND: &str = "openai_responses_compact_sync";
pub const CLAUDE_CHAT_SYNC_PLAN_KIND: &str = "claude_chat_sync";

View File

@@ -1,8 +1,8 @@
use crate::contracts::{
CLAUDE_CHAT_SYNC_PLAN_KIND, CLAUDE_CLI_SYNC_PLAN_KIND, GEMINI_CHAT_SYNC_PLAN_KIND,
GEMINI_CLI_SYNC_PLAN_KIND, OPENAI_CHAT_SYNC_PLAN_KIND, OPENAI_IMAGE_STREAM_PLAN_KIND,
OPENAI_IMAGE_SYNC_PLAN_KIND, OPENAI_RESPONSES_COMPACT_SYNC_PLAN_KIND,
OPENAI_RESPONSES_SYNC_PLAN_KIND,
GEMINI_CLI_SYNC_PLAN_KIND, OPENAI_CHAT_SYNC_PLAN_KIND, OPENAI_EMBEDDING_SYNC_PLAN_KIND,
OPENAI_IMAGE_STREAM_PLAN_KIND, OPENAI_IMAGE_SYNC_PLAN_KIND,
OPENAI_RESPONSES_COMPACT_SYNC_PLAN_KIND, OPENAI_RESPONSES_SYNC_PLAN_KIND,
};
pub const OPENAI_CHAT_SYNC_FINALIZE_REPORT_KIND: &str = "openai_chat_sync_finalize";
@@ -11,6 +11,7 @@ pub const GEMINI_CHAT_SYNC_FINALIZE_REPORT_KIND: &str = "gemini_chat_sync_finali
pub const OPENAI_RESPONSES_SYNC_FINALIZE_REPORT_KIND: &str = "openai_responses_sync_finalize";
pub const OPENAI_RESPONSES_COMPACT_SYNC_FINALIZE_REPORT_KIND: &str =
"openai_responses_compact_sync_finalize";
pub const OPENAI_EMBEDDING_SYNC_FINALIZE_REPORT_KIND: &str = "openai_embedding_sync_finalize";
pub const OPENAI_IMAGE_SYNC_FINALIZE_REPORT_KIND: &str = "openai_image_sync_finalize";
pub const CLAUDE_CLI_SYNC_FINALIZE_REPORT_KIND: &str = "claude_cli_sync_finalize";
pub const GEMINI_CLI_SYNC_FINALIZE_REPORT_KIND: &str = "gemini_cli_sync_finalize";
@@ -25,6 +26,8 @@ pub const GEMINI_CHAT_SYNC_SUCCESS_REPORT_KIND: &str = "gemini_chat_sync_success
pub const OPENAI_RESPONSES_SYNC_SUCCESS_REPORT_KIND: &str = "openai_responses_sync_success";
pub const OPENAI_RESPONSES_COMPACT_SYNC_SUCCESS_REPORT_KIND: &str =
"openai_responses_compact_sync_success";
pub const OPENAI_EMBEDDING_SYNC_SUCCESS_REPORT_KIND: &str = "openai_embedding_sync_success";
pub const GEMINI_EMBEDDING_SYNC_SUCCESS_REPORT_KIND: &str = "gemini_embedding_sync_success";
pub const OPENAI_IMAGE_SYNC_SUCCESS_REPORT_KIND: &str = "openai_image_sync_success";
pub const CLAUDE_CLI_SYNC_SUCCESS_REPORT_KIND: &str = "claude_cli_sync_success";
pub const GEMINI_CLI_SYNC_SUCCESS_REPORT_KIND: &str = "gemini_cli_sync_success";
@@ -45,6 +48,7 @@ pub const GEMINI_CHAT_SYNC_ERROR_REPORT_KIND: &str = "gemini_chat_sync_error";
pub const OPENAI_RESPONSES_SYNC_ERROR_REPORT_KIND: &str = "openai_responses_sync_error";
pub const OPENAI_RESPONSES_COMPACT_SYNC_ERROR_REPORT_KIND: &str =
"openai_responses_compact_sync_error";
pub const OPENAI_EMBEDDING_SYNC_ERROR_REPORT_KIND: &str = "openai_embedding_sync_error";
pub const OPENAI_IMAGE_SYNC_ERROR_REPORT_KIND: &str = "openai_image_sync_error";
pub const CLAUDE_CLI_SYNC_ERROR_REPORT_KIND: &str = "claude_cli_sync_error";
pub const GEMINI_CLI_SYNC_ERROR_REPORT_KIND: &str = "gemini_cli_sync_error";
@@ -58,6 +62,7 @@ pub fn implicit_sync_finalize_report_kind(plan_kind: &str) -> Option<&'static st
OPENAI_RESPONSES_COMPACT_SYNC_PLAN_KIND => {
Some(OPENAI_RESPONSES_COMPACT_SYNC_FINALIZE_REPORT_KIND)
}
OPENAI_EMBEDDING_SYNC_PLAN_KIND => Some(OPENAI_EMBEDDING_SYNC_FINALIZE_REPORT_KIND),
OPENAI_IMAGE_SYNC_PLAN_KIND => Some(OPENAI_IMAGE_SYNC_FINALIZE_REPORT_KIND),
CLAUDE_CLI_SYNC_PLAN_KIND => Some(CLAUDE_CLI_SYNC_FINALIZE_REPORT_KIND),
GEMINI_CLI_SYNC_PLAN_KIND => Some(GEMINI_CLI_SYNC_FINALIZE_REPORT_KIND),
@@ -72,6 +77,7 @@ pub fn core_error_default_client_api_format(report_kind: &str) -> Option<&'stati
GEMINI_CHAT_SYNC_FINALIZE_REPORT_KIND => Some("gemini:generate_content"),
OPENAI_RESPONSES_SYNC_FINALIZE_REPORT_KIND => Some("openai:responses"),
OPENAI_RESPONSES_COMPACT_SYNC_FINALIZE_REPORT_KIND => Some("openai:responses:compact"),
OPENAI_EMBEDDING_SYNC_FINALIZE_REPORT_KIND => Some("openai:embedding"),
LEGACY_OPENAI_CLI_SYNC_FINALIZE_REPORT_KIND => Some("openai:responses"),
LEGACY_OPENAI_COMPACT_SYNC_FINALIZE_REPORT_KIND => Some("openai:responses:compact"),
OPENAI_IMAGE_SYNC_FINALIZE_REPORT_KIND => Some("openai:image"),
@@ -90,6 +96,7 @@ pub fn core_error_background_report_kind(report_kind: &str) -> Option<&'static s
OPENAI_RESPONSES_COMPACT_SYNC_FINALIZE_REPORT_KIND => {
Some(OPENAI_RESPONSES_COMPACT_SYNC_ERROR_REPORT_KIND)
}
OPENAI_EMBEDDING_SYNC_FINALIZE_REPORT_KIND => Some(OPENAI_EMBEDDING_SYNC_ERROR_REPORT_KIND),
LEGACY_OPENAI_CLI_SYNC_FINALIZE_REPORT_KIND => {
Some(OPENAI_RESPONSES_SYNC_ERROR_REPORT_KIND)
}
@@ -115,6 +122,9 @@ pub fn core_success_background_report_kind(report_kind: &str) -> Option<&'static
OPENAI_RESPONSES_COMPACT_SYNC_FINALIZE_REPORT_KIND => {
Some(OPENAI_RESPONSES_COMPACT_SYNC_SUCCESS_REPORT_KIND)
}
OPENAI_EMBEDDING_SYNC_FINALIZE_REPORT_KIND => {
Some(OPENAI_EMBEDDING_SYNC_SUCCESS_REPORT_KIND)
}
LEGACY_OPENAI_CLI_SYNC_FINALIZE_REPORT_KIND => {
Some(OPENAI_RESPONSES_SYNC_SUCCESS_REPORT_KIND)
}

View File

@@ -1 +1,2 @@
pub mod request;
pub mod response;

View File

@@ -1,9 +1,8 @@
use serde_json::json;
use serde_json::Value;
use serde_json::{json, Map, Value};
use crate::formats::context::FormatContext;
use crate::formats::openai::embedding::request::mapped_embedding_model;
use crate::protocol::canonical::CanonicalRequest;
use crate::protocol::canonical::{CanonicalEmbeddingRequest, CanonicalRequest};
pub fn to(request: &CanonicalRequest, ctx: &FormatContext) -> Option<Value> {
let embedding = request.embedding.as_ref()?;
@@ -13,22 +12,169 @@ pub fn to(request: &CanonicalRequest, ctx: &FormatContext) -> Option<Value> {
}
let model = mapped_embedding_model(request, ctx.mapped_model_or(request.model.as_str()));
if items.len() == 1 {
return Some(json!({
"model": model,
"content": {
"parts": [{"text": items[0]}]
}
}));
return Some(Value::Object(gemini_embedding_request_object(
&model, items[0], embedding,
)));
}
let model_resource = gemini_embedding_model_resource_name(&model);
let requests = items
.into_iter()
.map(|text| {
Value::Object(gemini_embedding_request_object(
&model_resource,
text,
embedding,
))
})
.collect::<Vec<_>>();
Some(json!({ "requests": requests }))
}
fn gemini_embedding_request_object(
model: &str,
text: &str,
embedding: &CanonicalEmbeddingRequest,
) -> Map<String, Value> {
let mut object = Map::new();
object.insert("model".to_string(), Value::String(model.to_string()));
object.insert(
"content".to_string(),
json!({
"parts": [{"text": text}]
}),
);
insert_gemini_embedding_options(&mut object, embedding);
object
}
fn gemini_embedding_model_resource_name(model: &str) -> String {
let trimmed = model.trim();
if trimmed.starts_with("models/") {
trimmed.to_string()
} else {
format!("models/{trimmed}")
}
}
fn insert_gemini_embedding_options(
object: &mut Map<String, Value>,
embedding: &CanonicalEmbeddingRequest,
) {
if let Some(dimensions) = embedding.dimensions {
object.insert("outputDimensionality".to_string(), Value::from(dimensions));
}
if let Some(task_type) = embedding
.task
.as_deref()
.and_then(normalize_gemini_embedding_task_type)
{
object.insert("taskType".to_string(), Value::String(task_type));
}
}
fn normalize_gemini_embedding_task_type(value: &str) -> Option<String> {
let normalized = value.trim();
if normalized.is_empty() {
return None;
}
let key = normalized.replace(['-', ' '], "_").to_ascii_uppercase();
let task_type = match key.as_str() {
"QUERY" | "RETRIEVAL_QUERY" => "RETRIEVAL_QUERY",
"DOCUMENT" | "RETRIEVAL_DOCUMENT" => "RETRIEVAL_DOCUMENT",
"TEXT_MATCHING" | "SEMANTIC_SIMILARITY" => "SEMANTIC_SIMILARITY",
"CLASSIFICATION" => "CLASSIFICATION",
"CLUSTERING" => "CLUSTERING",
"QUESTION_ANSWERING" => "QUESTION_ANSWERING",
"FACT_VERIFICATION" => "FACT_VERIFICATION",
"CODE_RETRIEVAL_QUERY" => "CODE_RETRIEVAL_QUERY",
_ => key.as_str(),
};
Some(task_type.to_string())
}
#[cfg(test)]
mod tests {
use std::collections::BTreeMap;
use serde_json::json;
use super::to;
use crate::formats::context::FormatContext;
use crate::protocol::canonical::{
CanonicalEmbeddingInput, CanonicalEmbeddingRequest, CanonicalRequest,
};
fn canonical_embedding(input: CanonicalEmbeddingInput) -> CanonicalRequest {
CanonicalRequest {
model: "text-embedding-3-small".to_string(),
embedding: Some(CanonicalEmbeddingRequest {
input,
encoding_format: None,
dimensions: None,
task: None,
user: None,
extensions: BTreeMap::new(),
}),
..CanonicalRequest::default()
}
}
#[test]
fn single_string_array_item_uses_single_embed_content_body() {
let request = canonical_embedding(CanonicalEmbeddingInput::StringArray(vec![
"hello".to_string()
]));
let body = to(
&request,
&FormatContext::default().with_mapped_model("gemini-embedding-2-preview"),
)
.expect("gemini embedding request");
assert_eq!(body["model"], "gemini-embedding-2-preview");
assert_eq!(body["content"]["parts"][0]["text"], "hello");
assert!(body.get("requests").is_none());
}
#[test]
fn multiple_string_items_use_gemini_batch_request_body() {
let request = canonical_embedding(CanonicalEmbeddingInput::StringArray(vec![
"alpha".to_string(),
"beta".to_string(),
]));
let body = to(
&request,
&FormatContext::default().with_mapped_model("gemini-embedding-2-preview"),
)
.expect("gemini embedding request");
assert!(body.get("model").is_none());
assert_eq!(body["requests"].as_array().map(Vec::len), Some(2));
assert_eq!(
body["requests"][0]["model"],
"models/gemini-embedding-2-preview"
);
assert_eq!(body["requests"][0]["content"]["parts"][0]["text"], "alpha");
assert_eq!(
body["requests"][1]["model"],
"models/gemini-embedding-2-preview"
);
assert_eq!(body["requests"][1]["content"]["parts"][0]["text"], "beta");
}
#[test]
fn explicit_embedding_options_are_preserved_without_defaults() {
let mut request = canonical_embedding(CanonicalEmbeddingInput::String("query".to_string()));
let embedding = request.embedding.as_mut().expect("embedding request");
embedding.dimensions = Some(768);
embedding.task = Some("retrieval_query".to_string());
let body = to(
&request,
&FormatContext::default().with_mapped_model("gemini-embedding-2-preview"),
)
.expect("gemini embedding request");
assert_eq!(body["outputDimensionality"], json!(768));
assert_eq!(body["taskType"], "RETRIEVAL_QUERY");
}
Some(json!({
"model": model,
"requests": items.into_iter().map(|text| {
json!({
"model": model,
"content": {
"parts": [{"text": text}]
}
})
}).collect::<Vec<_>>()
}))
}

View File

@@ -0,0 +1,108 @@
use serde_json::Value;
use crate::formats::openai::embedding::request::namespace_extensions;
use crate::protocol::canonical::{
gemini_usage_to_canonical, CanonicalEmbedding, CanonicalEmbeddingResponse,
};
pub fn from(body_json: &Value) -> Option<CanonicalEmbeddingResponse> {
let body = body_json.as_object()?;
if body.contains_key("error") {
return None;
}
let embeddings = if let Some(values) = body
.get("embedding")
.and_then(Value::as_object)
.and_then(|embedding| embedding.get("values"))
.and_then(Value::as_array)
{
vec![CanonicalEmbedding {
index: 0,
embedding: embedding_values(values)?,
extensions: Default::default(),
}]
} else {
let raw_embeddings = body.get("embeddings")?.as_array()?;
raw_embeddings
.iter()
.enumerate()
.map(|(index, item)| {
let item_object = item.as_object()?;
let values = item_object.get("values")?.as_array()?;
Some(CanonicalEmbedding {
index,
embedding: embedding_values(values)?,
extensions: namespace_extensions("gemini", item_object, &["values"]),
})
})
.collect::<Option<Vec<_>>>()?
};
if embeddings.is_empty()
|| embeddings
.iter()
.any(|embedding| embedding.embedding.is_empty())
{
return None;
}
Some(CanonicalEmbeddingResponse {
id: body
.get("id")
.or_else(|| body.get("responseId"))
.and_then(Value::as_str)
.unwrap_or("embd-gemini-unknown")
.to_string(),
model: body
.get("model")
.or_else(|| body.get("modelVersion"))
.and_then(Value::as_str)
.unwrap_or("unknown")
.to_string(),
embeddings,
usage: gemini_usage_to_canonical(body.get("usageMetadata")),
extensions: namespace_extensions(
"gemini",
body,
&[
"id",
"responseId",
"model",
"modelVersion",
"embedding",
"embeddings",
"usageMetadata",
],
),
})
}
fn embedding_values(values: &[Value]) -> Option<Vec<f64>> {
values.iter().map(Value::as_f64).collect()
}
#[cfg(test)]
mod tests {
use serde_json::json;
use super::from;
#[test]
fn parses_gemini_single_embedding_response() {
let body = json!({
"embedding": {"values": [0.1, 0.2, 0.3]},
"usageMetadata": {
"promptTokenCount": 4,
"totalTokenCount": 4
}
});
let parsed = from(&body).expect("response should parse");
assert_eq!(parsed.model, "unknown");
assert_eq!(parsed.embeddings[0].embedding, vec![0.1, 0.2, 0.3]);
let usage = parsed.usage.expect("usage should parse");
assert_eq!(usage.input_tokens, 4);
assert_eq!(usage.total_tokens, 4);
}
}

View File

@@ -1,2 +1,3 @@
pub mod request;
pub mod response;
pub mod spec;

View File

@@ -0,0 +1,35 @@
use crate::contracts::{
OPENAI_EMBEDDING_SYNC_FINALIZE_REPORT_KIND, OPENAI_EMBEDDING_SYNC_PLAN_KIND,
};
use crate::formats::shared::family::{
LocalStandardSourceFamily, LocalStandardSourceMode, LocalStandardSpec,
};
pub fn resolve_sync_spec(plan_kind: &str) -> Option<LocalStandardSpec> {
match plan_kind {
OPENAI_EMBEDDING_SYNC_PLAN_KIND => Some(LocalStandardSpec {
api_format: "openai:embedding",
decision_kind: OPENAI_EMBEDDING_SYNC_PLAN_KIND,
report_kind: OPENAI_EMBEDDING_SYNC_FINALIZE_REPORT_KIND,
family: LocalStandardSourceFamily::Standard,
mode: LocalStandardSourceMode::Embedding,
require_streaming: false,
}),
_ => None,
}
}
#[cfg(test)]
mod tests {
use super::resolve_sync_spec;
use crate::formats::shared::family::LocalStandardSourceMode;
#[test]
fn resolves_openai_embedding_sync_standard_spec() {
let spec = resolve_sync_spec("openai_embedding_sync").expect("spec");
assert_eq!(spec.api_format, "openai:embedding");
assert_eq!(spec.report_kind, "openai_embedding_sync_finalize");
assert_eq!(spec.mode, LocalStandardSourceMode::Embedding);
assert!(!spec.require_streaming);
}
}

View File

@@ -228,11 +228,16 @@ mod tests {
&FormatContext::default().with_mapped_model("gemini-embedding-001"),
)
.expect("gemini embedding conversion should succeed");
assert_eq!(gemini["model"], "gemini-embedding-001");
assert!(gemini.get("model").is_none());
assert_eq!(
gemini["requests"][0]["model"],
"models/gemini-embedding-001"
);
assert_eq!(
gemini["requests"][0]["content"]["parts"][0]["text"],
"alpha"
);
assert_eq!(gemini["requests"][0]["outputDimensionality"], 2);
assert!(gemini.get("messages").is_none());
let doubao = convert_request(

View File

@@ -38,7 +38,7 @@ pub fn build_core_error_body_for_client_format(
error_object.insert("message".to_string(), Value::String(message.to_string()));
match aether_ai_formats::normalize_api_format_alias(client_api_format).as_str() {
"openai:chat" | "openai:responses" | "openai:responses:compact" => {
"openai:chat" | "openai:responses" | "openai:responses:compact" | "openai:embedding" => {
error_object.insert(
"type".to_string(),
Value::String(map_local_sync_error_kind_to_openai_type(kind).to_string()),

View File

@@ -1,7 +1,8 @@
use crate::contracts::{
CLAUDE_CHAT_STREAM_PLAN_KIND, CLAUDE_CHAT_SYNC_PLAN_KIND, CLAUDE_CLI_STREAM_PLAN_KIND,
CLAUDE_CLI_SYNC_PLAN_KIND, GEMINI_CHAT_STREAM_PLAN_KIND, GEMINI_CHAT_SYNC_PLAN_KIND,
GEMINI_CLI_STREAM_PLAN_KIND, GEMINI_CLI_SYNC_PLAN_KIND, OPENAI_EMBEDDING_SYNC_PLAN_KIND,
GEMINI_CLI_STREAM_PLAN_KIND, GEMINI_CLI_SYNC_PLAN_KIND, GEMINI_EMBEDDING_SYNC_PLAN_KIND,
GEMINI_EMBEDDING_SYNC_SUCCESS_REPORT_KIND, OPENAI_EMBEDDING_SYNC_PLAN_KIND,
OPENAI_RERANK_SYNC_PLAN_KIND,
};
@@ -50,6 +51,13 @@ pub fn resolve_sync_spec(plan_kind: &str) -> Option<LocalSameFormatProviderSpec>
family: LocalSameFormatProviderFamily::Gemini,
require_streaming: false,
}),
GEMINI_EMBEDDING_SYNC_PLAN_KIND => Some(LocalSameFormatProviderSpec {
api_format: "gemini:embedding",
decision_kind: GEMINI_EMBEDDING_SYNC_PLAN_KIND,
report_kind: GEMINI_EMBEDDING_SYNC_SUCCESS_REPORT_KIND,
family: LocalSameFormatProviderFamily::Gemini,
require_streaming: false,
}),
OPENAI_EMBEDDING_SYNC_PLAN_KIND => Some(LocalSameFormatProviderSpec {
api_format: "openai:embedding",
decision_kind: OPENAI_EMBEDDING_SYNC_PLAN_KIND,
@@ -130,6 +138,15 @@ mod tests {
assert!(!spec.require_streaming);
}
#[test]
fn resolves_gemini_embedding_sync_same_format_spec() {
let spec = resolve_sync_spec("gemini_embedding_sync").expect("spec");
assert_eq!(spec.api_format, "gemini:embedding");
assert_eq!(spec.report_kind, "gemini_embedding_sync_success");
assert_eq!(spec.family, super::LocalSameFormatProviderFamily::Gemini);
assert!(!spec.require_streaming);
}
#[test]
fn resolves_openai_rerank_sync_same_format_spec() {
let spec = resolve_sync_spec("openai_rerank_sync").expect("spec");

View File

@@ -4,9 +4,9 @@ use url::form_urlencoded;
use crate::contracts::{
CLAUDE_CHAT_STREAM_PLAN_KIND, CLAUDE_CHAT_SYNC_PLAN_KIND, CLAUDE_CLI_STREAM_PLAN_KIND,
CLAUDE_CLI_SYNC_PLAN_KIND, GEMINI_CHAT_STREAM_PLAN_KIND, GEMINI_CHAT_SYNC_PLAN_KIND,
GEMINI_CLI_STREAM_PLAN_KIND, GEMINI_CLI_SYNC_PLAN_KIND, GEMINI_FILES_DELETE_PLAN_KIND,
GEMINI_FILES_DOWNLOAD_PLAN_KIND, GEMINI_FILES_GET_PLAN_KIND, GEMINI_FILES_LIST_PLAN_KIND,
GEMINI_FILES_UPLOAD_PLAN_KIND, GEMINI_VIDEO_CANCEL_SYNC_PLAN_KIND,
GEMINI_CLI_STREAM_PLAN_KIND, GEMINI_CLI_SYNC_PLAN_KIND, GEMINI_EMBEDDING_SYNC_PLAN_KIND,
GEMINI_FILES_DELETE_PLAN_KIND, GEMINI_FILES_DOWNLOAD_PLAN_KIND, GEMINI_FILES_GET_PLAN_KIND,
GEMINI_FILES_LIST_PLAN_KIND, GEMINI_FILES_UPLOAD_PLAN_KIND, GEMINI_VIDEO_CANCEL_SYNC_PLAN_KIND,
GEMINI_VIDEO_CREATE_SYNC_PLAN_KIND, OPENAI_CHAT_STREAM_PLAN_KIND, OPENAI_CHAT_SYNC_PLAN_KIND,
OPENAI_EMBEDDING_SYNC_PLAN_KIND, OPENAI_IMAGE_STREAM_PLAN_KIND, OPENAI_IMAGE_SYNC_PLAN_KIND,
OPENAI_RERANK_SYNC_PLAN_KIND, OPENAI_RESPONSES_COMPACT_STREAM_PLAN_KIND,
@@ -166,6 +166,14 @@ pub fn resolve_execution_runtime_sync_plan_kind(
return Some(GEMINI_VIDEO_CREATE_SYNC_PLAN_KIND);
}
if route_family == Some("gemini")
&& route_kind == Some("embedding")
&& *method == Method::POST
&& (path.ends_with(":embedContent") || path.ends_with(":batchEmbedContents"))
{
return Some(GEMINI_EMBEDDING_SYNC_PLAN_KIND);
}
if route_family == Some("openai")
&& route_kind == Some("chat")
&& *method == Method::POST
@@ -414,6 +422,7 @@ pub fn supports_sync_execution_decision_kind(plan_kind: &str) -> bool {
| CLAUDE_CLI_SYNC_PLAN_KIND
| GEMINI_CHAT_SYNC_PLAN_KIND
| GEMINI_CLI_SYNC_PLAN_KIND
| GEMINI_EMBEDDING_SYNC_PLAN_KIND
| GEMINI_FILES_UPLOAD_PLAN_KIND
| OPENAI_VIDEO_CREATE_SYNC_PLAN_KIND
| OPENAI_VIDEO_REMIX_SYNC_PLAN_KIND
@@ -458,9 +467,9 @@ mod tests {
use crate::contracts::{
CLAUDE_CHAT_STREAM_PLAN_KIND, CLAUDE_CHAT_SYNC_PLAN_KIND, CLAUDE_CLI_STREAM_PLAN_KIND,
CLAUDE_CLI_SYNC_PLAN_KIND, GEMINI_CHAT_STREAM_PLAN_KIND, GEMINI_CHAT_SYNC_PLAN_KIND,
GEMINI_CLI_STREAM_PLAN_KIND, GEMINI_CLI_SYNC_PLAN_KIND, OPENAI_CHAT_STREAM_PLAN_KIND,
OPENAI_CHAT_SYNC_PLAN_KIND, OPENAI_EMBEDDING_SYNC_PLAN_KIND, OPENAI_IMAGE_STREAM_PLAN_KIND,
OPENAI_IMAGE_SYNC_PLAN_KIND, OPENAI_RERANK_SYNC_PLAN_KIND,
GEMINI_CLI_STREAM_PLAN_KIND, GEMINI_CLI_SYNC_PLAN_KIND, GEMINI_EMBEDDING_SYNC_PLAN_KIND,
OPENAI_CHAT_STREAM_PLAN_KIND, OPENAI_CHAT_SYNC_PLAN_KIND, OPENAI_EMBEDDING_SYNC_PLAN_KIND,
OPENAI_IMAGE_STREAM_PLAN_KIND, OPENAI_IMAGE_SYNC_PLAN_KIND, OPENAI_RERANK_SYNC_PLAN_KIND,
OPENAI_RESPONSES_COMPACT_STREAM_PLAN_KIND, OPENAI_RESPONSES_COMPACT_SYNC_PLAN_KIND,
OPENAI_RESPONSES_STREAM_PLAN_KIND, OPENAI_RESPONSES_SYNC_PLAN_KIND,
};
@@ -786,6 +795,35 @@ mod tests {
));
}
#[test]
fn resolves_gemini_embedding_sync_plan_kind() {
assert_eq!(
resolve_execution_runtime_sync_plan_kind(
Some("ai_public"),
Some("gemini"),
Some("embedding"),
Some("api_key"),
&Method::POST,
"/v1beta/models/gemini-embedding-2-preview:embedContent",
),
Some(GEMINI_EMBEDDING_SYNC_PLAN_KIND)
);
assert_eq!(
resolve_execution_runtime_sync_plan_kind(
Some("ai_public"),
Some("gemini"),
Some("embedding"),
Some("api_key"),
&Method::POST,
"/v1beta/models/gemini-embedding-2-preview:batchEmbedContents",
),
Some(GEMINI_EMBEDDING_SYNC_PLAN_KIND)
);
assert!(supports_sync_execution_decision_kind(
GEMINI_EMBEDDING_SYNC_PLAN_KIND
));
}
#[test]
fn resolves_openai_rerank_sync_plan_kind() {
assert_eq!(

View File

@@ -9,9 +9,10 @@ use aether_ai_formats::formats::conversion::response::{
};
use aether_ai_formats::formats::registry::{convert_response, FormatContext};
use aether_ai_formats::{
canonical_to_claude_response, canonical_to_gemini_response, canonical_to_openai_chat_response,
canonical_to_openai_responses_compact_response, canonical_to_openai_responses_response,
from_claude_to_canonical_response, from_gemini_to_canonical_response,
canonical_to_claude_response, canonical_to_embedding_response, canonical_to_gemini_response,
canonical_to_openai_chat_response, canonical_to_openai_responses_compact_response,
canonical_to_openai_responses_response, from_claude_to_canonical_response,
from_embedding_to_canonical_response, from_gemini_to_canonical_response,
from_openai_chat_to_canonical_response, from_openai_responses_to_canonical_response,
sync_chat_response_conversion_kind, sync_cli_response_conversion_kind,
};
@@ -330,6 +331,18 @@ pub fn maybe_build_standard_sync_finalize_product_from_normalized_payload(
)));
}
if let Some(product) = maybe_build_embedding_cross_format_sync_product_from_normalized_payload(
report_kind,
status_code,
report_context,
body_json,
body_base64,
)? {
return Ok(Some(StandardSyncFinalizeNormalizedProduct::CrossFormat(
product,
)));
}
Ok(
maybe_build_standard_cross_format_sync_product_from_normalized_payload(
report_kind,
@@ -342,6 +355,90 @@ pub fn maybe_build_standard_sync_finalize_product_from_normalized_payload(
)
}
pub fn maybe_build_embedding_cross_format_sync_product_from_normalized_payload(
report_kind: &str,
status_code: u16,
report_context: Option<&Value>,
body_json: Option<&Value>,
body_base64: Option<&str>,
) -> Result<Option<StandardCrossFormatSyncProduct>, AiSurfaceFinalizeError> {
if report_kind != crate::contracts::OPENAI_EMBEDDING_SYNC_FINALIZE_REPORT_KIND
|| status_code >= 400
{
return Ok(None);
}
let Some(report_context) = report_context else {
return Ok(None);
};
let provider_api_format = report_context
.get("provider_api_format")
.and_then(Value::as_str)
.unwrap_or_default()
.trim()
.to_ascii_lowercase();
let client_api_format = report_context
.get("client_api_format")
.and_then(Value::as_str)
.unwrap_or_default()
.trim()
.to_ascii_lowercase();
if provider_api_format == client_api_format {
return Ok(None);
}
let Some(provider_namespace) =
embedding_response_namespace_for_api_format(&provider_api_format)
else {
return Ok(None);
};
let Some(client_namespace) = embedding_response_namespace_for_api_format(&client_api_format)
else {
return Ok(None);
};
let provider_body_json = match body_base64 {
Some(body_base64) => {
let body_bytes = base64::engine::general_purpose::STANDARD.decode(body_base64)?;
serde_json::from_slice::<Value>(&body_bytes).ok()
}
None => body_json.cloned(),
};
let Some(provider_body_json) =
provider_body_json.filter(|value| !is_error_like_sync_body(value))
else {
return Ok(None);
};
let mut canonical =
match from_embedding_to_canonical_response(&provider_body_json, provider_namespace) {
Some(canonical) => canonical,
None => return Ok(None),
};
apply_report_context_model_fallback(&mut canonical.model, report_context);
let Some(client_body_json) = canonical_to_embedding_response(&canonical, client_namespace)
else {
return Ok(None);
};
let client_body_json =
client_body_with_report_context_model(client_body_json, report_context, &client_api_format);
Ok(Some(StandardCrossFormatSyncProduct {
client_body_json,
provider_body_json,
}))
}
fn embedding_response_namespace_for_api_format(api_format: &str) -> Option<&'static str> {
match aether_ai_formats::normalize_api_format_alias(api_format).as_str() {
"openai:embedding" => Some("openai"),
"jina:embedding" => Some("jina"),
"gemini:embedding" => Some("gemini"),
_ => None,
}
}
fn maybe_build_standard_same_format_sync_body(
report_kind: &str,
status_code: u16,
@@ -829,6 +926,9 @@ fn client_body_with_report_context_model(
"openai:chat" | "openai:responses" | "openai:responses:compact" | "claude:messages" => {
object.insert("model".to_string(), Value::String(display_model));
}
"openai:embedding" | "jina:embedding" => {
object.insert("model".to_string(), Value::String(display_model));
}
"gemini:generate_content" => {
object.insert("modelVersion".to_string(), Value::String(display_model));
}
@@ -1310,6 +1410,7 @@ fn standard_same_format_api_format(report_kind: &str) -> Option<&'static str> {
"openai_chat_sync_finalize" => Some("openai:chat"),
"claude_chat_sync_finalize" => Some("claude:messages"),
"gemini_chat_sync_finalize" => Some("gemini:generate_content"),
"openai_embedding_sync_finalize" => Some("openai:embedding"),
"claude_cli_sync_finalize" => Some("claude:messages"),
"gemini_cli_sync_finalize" => Some("gemini:generate_content"),
_ => None,

View File

@@ -684,6 +684,7 @@ pub fn from_embedding_to_canonical_response(
crate::formats::openai::embedding::response::from_namespace(body_json, "openai")
}
"jina" => crate::formats::openai::embedding::response::from_namespace(body_json, "jina"),
"gemini" => crate::formats::gemini::embedding::response::from(body_json),
_ => None,
}
}
@@ -4752,10 +4753,16 @@ mod tests {
let gemini =
super::canonical_to_embedding_request(&canonical, "gemini-embedding-001", "gemini")
.expect("gemini embedding request");
assert!(gemini.get("model").is_none());
assert_eq!(
gemini["requests"][0]["model"],
"models/gemini-embedding-001"
);
assert_eq!(
gemini["requests"][0]["content"]["parts"][0]["text"],
"alpha"
);
assert_eq!(gemini["requests"][0]["outputDimensionality"], 2);
assert!(gemini.get("messages").is_none());
let doubao = super::canonical_to_embedding_request(

View File

@@ -1,5 +1,6 @@
use aether_ai_formats::formats::matrix::{
request_conversion_kind, request_conversion_requires_enable_flag, RequestConversionKind,
api_data_format_id, request_conversion_kind, request_conversion_requires_enable_flag,
RequestConversionKind,
};
use aether_ai_formats::normalize_api_format_alias;
@@ -39,7 +40,14 @@ pub fn request_conversion_enabled_for_transport(
if client_api_format == provider_api_format {
return true;
}
if request_conversion_kind(client_api_format.as_str(), provider_api_format.as_str()).is_none() {
let conversion_kind =
request_conversion_kind(client_api_format.as_str(), provider_api_format.as_str());
if conversion_kind.is_none()
&& !same_data_format_transport_pair(
client_api_format.as_str(),
provider_api_format.as_str(),
)
{
return false;
}
if !request_conversion_requires_enable_flag(
@@ -62,7 +70,14 @@ pub fn request_pair_allowed_for_transport(
if client_api_format == provider_api_format {
return true;
}
if request_conversion_kind(client_api_format.as_str(), provider_api_format.as_str()).is_none() {
let conversion_kind =
request_conversion_kind(client_api_format.as_str(), provider_api_format.as_str());
if conversion_kind.is_none()
&& !same_data_format_transport_pair(
client_api_format.as_str(),
provider_api_format.as_str(),
)
{
return false;
}
if is_kiro_claude_messages_transport(transport, &provider_api_format) {
@@ -80,6 +95,19 @@ pub fn request_pair_allowed_for_transport(
)
}
fn same_data_format_transport_pair(client_api_format: &str, provider_api_format: &str) -> bool {
if aether_ai_formats::api_format_alias_matches(client_api_format, provider_api_format) {
return false;
}
matches!(
(
api_data_format_id(client_api_format),
api_data_format_id(provider_api_format)
),
(Some("embedding"), Some("embedding")) | (Some("rerank"), Some("rerank"))
)
}
pub fn request_conversion_transport_supported(
transport: &GatewayProviderTransportSnapshot,
kind: RequestConversionKind,
@@ -117,15 +145,72 @@ pub fn request_conversion_transport_unsupported_reason(
}
}
pub fn request_pair_transport_unsupported_reason(
transport: &GatewayProviderTransportSnapshot,
client_api_format: &str,
provider_api_format: &str,
) -> Option<&'static str> {
let client_api_format = normalize_api_format_alias(client_api_format);
let provider_api_format = normalize_api_format_alias(provider_api_format);
if let Some(kind) =
request_conversion_kind(client_api_format.as_str(), provider_api_format.as_str())
{
return request_conversion_transport_unsupported_reason(transport, kind);
}
if !same_data_format_transport_pair(client_api_format.as_str(), provider_api_format.as_str()) {
return Some("transport_api_format_unsupported");
}
match provider_api_format.as_str() {
"gemini:embedding" => {
if is_vertex_transport_context(transport) {
local_vertex_gemini_transport_unsupported_reason_with_network(transport)
} else {
local_gemini_transport_unsupported_reason_with_network(
transport,
"gemini:embedding",
)
}
}
"openai:embedding" | "jina:embedding" | "doubao:embedding" | "openai:rerank"
| "jina:rerank" => local_standard_transport_unsupported_reason_with_network(
transport,
provider_api_format.as_str(),
),
_ => Some("transport_api_format_unsupported"),
}
}
pub fn request_conversion_direct_auth(
transport: &GatewayProviderTransportSnapshot,
_kind: RequestConversionKind,
) -> Option<(String, String)> {
match normalize_api_format_alias(&transport.endpoint.api_format).as_str() {
"openai:chat" | "openai:responses" | "openai:responses:compact" => {
resolve_local_openai_bearer_auth(transport)
}
"gemini:generate_content" => {
request_direct_auth_for_provider_format(transport, transport.endpoint.api_format.as_str())
}
pub fn request_pair_direct_auth(
transport: &GatewayProviderTransportSnapshot,
provider_api_format: &str,
) -> Option<(String, String)> {
request_direct_auth_for_provider_format(transport, provider_api_format)
}
fn request_direct_auth_for_provider_format(
transport: &GatewayProviderTransportSnapshot,
provider_api_format: &str,
) -> Option<(String, String)> {
match normalize_api_format_alias(provider_api_format).as_str() {
"openai:chat"
| "openai:responses"
| "openai:responses:compact"
| "openai:embedding"
| "jina:embedding"
| "doubao:embedding"
| "openai:rerank"
| "jina:rerank" => resolve_local_openai_bearer_auth(transport),
"gemini:generate_content" | "gemini:embedding" => {
if is_vertex_api_key_transport_context(transport) {
resolve_local_vertex_api_key_query_auth(transport)
.map(|auth| (VERTEX_API_KEY_QUERY_PARAM.to_string(), auth.value))

View File

@@ -30,7 +30,8 @@ pub use conversion::{
candidate_common_transport_skip_reason, candidate_transport_pair_skip_reason,
request_conversion_direct_auth, request_conversion_enabled_for_transport,
request_conversion_transport_supported, request_conversion_transport_unsupported_reason,
request_pair_allowed_for_transport, CandidateTransportPolicyFacts,
request_pair_allowed_for_transport, request_pair_direct_auth,
request_pair_transport_unsupported_reason, CandidateTransportPolicyFacts,
};
pub use diagnostics::{
append_transport_diagnostics_to_value, build_request_trace_proxy_value,
@@ -72,6 +73,7 @@ pub use request_url::{
build_cross_format_openai_chat_upstream_url, build_cross_format_openai_responses_upstream_url,
build_kiro_cross_format_upstream_url, build_local_openai_chat_upstream_url,
build_local_openai_responses_upstream_url, build_transport_request_url,
build_transport_request_url_for_request_body, gemini_embedding_request_body_uses_batch,
TransportRequestUrlParams,
};
pub use rules::{

View File

@@ -2,6 +2,7 @@ use std::collections::BTreeMap;
use std::sync::OnceLock;
use regex::Regex;
use serde_json::Value;
use url::form_urlencoded;
use crate::antigravity::{
@@ -31,6 +32,35 @@ pub struct TransportRequestUrlParams<'a> {
pub fn build_transport_request_url(
transport: &GatewayProviderTransportSnapshot,
params: TransportRequestUrlParams<'_>,
) -> Option<String> {
build_transport_request_url_inner(transport, params, false)
}
pub fn build_transport_request_url_for_request_body(
transport: &GatewayProviderTransportSnapshot,
params: TransportRequestUrlParams<'_>,
provider_request_body: Option<&Value>,
) -> Option<String> {
let gemini_embedding_batch =
gemini_embedding_request_body_uses_batch(params.provider_api_format, provider_request_body);
build_transport_request_url_inner(transport, params, gemini_embedding_batch)
}
pub fn gemini_embedding_request_body_uses_batch(
provider_api_format: &str,
provider_request_body: Option<&Value>,
) -> bool {
aether_ai_formats::normalize_api_format_alias(provider_api_format) == "gemini:embedding"
&& provider_request_body
.and_then(|body| body.get("requests"))
.and_then(Value::as_array)
.is_some_and(|requests| !requests.is_empty())
}
fn build_transport_request_url_inner(
transport: &GatewayProviderTransportSnapshot,
params: TransportRequestUrlParams<'_>,
gemini_embedding_batch: bool,
) -> Option<String> {
if let Some(url) = build_transport_hook_url(transport, params) {
return Some(url);
@@ -45,7 +75,9 @@ pub fn build_transport_request_url(
.as_deref()
.map(str::trim)
.filter(|value| !value.is_empty())
.map(|path| expand_custom_path_template(path, build_path_params(params)));
.map(|path| {
expand_custom_path_template(path, build_path_params(params, gemini_embedding_batch))
});
if let Some(path) = custom_path.as_deref() {
let blocked_keys = if normalized_provider_api_format.starts_with("gemini:") {
@@ -55,6 +87,8 @@ pub fn build_transport_request_url(
};
let normalized_path = if normalized_provider_api_format == "gemini:generate_content" {
normalize_gemini_content_action_path(path, params.upstream_is_stream)
} else if normalized_provider_api_format == "gemini:embedding" {
normalize_gemini_embedding_action_path(path, gemini_embedding_batch)
} else {
path.to_string()
};
@@ -106,6 +140,7 @@ pub fn build_transport_request_url(
&transport.endpoint.base_url,
params.mapped_model?,
params.request_query,
gemini_embedding_batch,
),
"doubao:embedding" => build_passthrough_path_url(
&transport.endpoint.base_url,
@@ -287,7 +322,10 @@ fn build_transport_hook_url(
None
}
fn build_path_params(params: TransportRequestUrlParams<'_>) -> BTreeMap<&'static str, &str> {
fn build_path_params(
params: TransportRequestUrlParams<'_>,
gemini_embedding_batch: bool,
) -> BTreeMap<&'static str, &str> {
let mut path_params = BTreeMap::new();
if let Some(model) = params
.mapped_model
@@ -302,7 +340,11 @@ fn build_path_params(params: TransportRequestUrlParams<'_>) -> BTreeMap<&'static
path_params.insert(
"action",
if provider_api_format == "gemini:embedding" {
"embedContent"
if gemini_embedding_batch {
"batchEmbedContents"
} else {
"embedContent"
}
} else if params.upstream_is_stream {
"streamGenerateContent"
} else {
@@ -313,6 +355,14 @@ fn build_path_params(params: TransportRequestUrlParams<'_>) -> BTreeMap<&'static
path_params
}
fn normalize_gemini_embedding_action_path(path: &str, batch: bool) -> String {
if batch {
path.replace(":embedContent", ":batchEmbedContents")
} else {
path.replace(":batchEmbedContents", ":embedContent")
}
}
fn build_provider_embedding_v1_url(upstream_base_url: &str, query: Option<&str>) -> Option<String> {
build_provider_v1_url(upstream_base_url, "/embeddings", "/v1/embeddings", query)
}
@@ -345,6 +395,7 @@ fn build_gemini_embedding_url(
upstream_base_url: &str,
model: &str,
query: Option<&str>,
batch: bool,
) -> Option<String> {
let trimmed_base_url = upstream_base_url
.trim()
@@ -357,12 +408,17 @@ fn build_gemini_embedding_url(
return None;
}
let path = if trimmed_base_url.ends_with("/v1beta") {
format!("/models/{trimmed_model}:embedContent")
} else if trimmed_base_url.contains("/v1beta/models/") {
":embedContent".to_string()
let action = if batch {
"batchEmbedContents"
} else {
format!("/v1beta/models/{trimmed_model}:embedContent")
"embedContent"
};
let path = if trimmed_base_url.ends_with("/v1beta") {
format!("/models/{trimmed_model}:{action}")
} else if trimmed_base_url.contains("/v1beta/models/") {
format!(":{action}")
} else {
format!("/v1beta/models/{trimmed_model}:{action}")
};
build_passthrough_path_url(upstream_base_url, &path, query, &["key"])
}
@@ -440,12 +496,13 @@ fn custom_path_template_regex() -> &'static Regex {
mod tests {
use super::{
build_kiro_cross_format_upstream_url, build_transport_request_url,
TransportRequestUrlParams,
build_transport_request_url_for_request_body, TransportRequestUrlParams,
};
use crate::snapshot::{
GatewayProviderTransportEndpoint, GatewayProviderTransportKey,
GatewayProviderTransportProvider, GatewayProviderTransportSnapshot,
};
use serde_json::json;
fn sample_transport(
provider_type: &str,
@@ -829,6 +886,82 @@ mod tests {
);
}
#[test]
fn gemini_embedding_batch_body_uses_batch_endpoint() {
let gemini = sample_transport(
"gemini",
"gemini:embedding",
"https://generativelanguage.googleapis.com/v1beta",
None,
);
let batch_body = json!({
"requests": [
{
"model": "models/gemini-embedding-001",
"content": {"parts": [{"text": "alpha"}]}
},
{
"model": "models/gemini-embedding-001",
"content": {"parts": [{"text": "beta"}]}
}
]
});
assert_eq!(
build_transport_request_url_for_request_body(
&gemini,
TransportRequestUrlParams {
provider_api_format: "gemini:embedding",
mapped_model: Some("gemini-embedding-001"),
upstream_is_stream: false,
request_query: Some("key=client-key&foo=bar"),
kiro_api_region: None,
},
Some(&batch_body),
)
.as_deref(),
Some(
"https://generativelanguage.googleapis.com/v1beta/models/gemini-embedding-001:batchEmbedContents?foo=bar"
)
);
}
#[test]
fn gemini_embedding_custom_action_template_follows_batch_body() {
let gemini = sample_transport(
"gemini",
"gemini:embedding",
"https://generativelanguage.googleapis.com",
Some("/v1beta/models/{model}:{action}"),
);
let batch_body = json!({
"requests": [
{
"model": "models/gemini-embedding-001",
"content": {"parts": [{"text": "alpha"}]}
}
]
});
assert_eq!(
build_transport_request_url_for_request_body(
&gemini,
TransportRequestUrlParams {
provider_api_format: "gemini:embedding",
mapped_model: Some("gemini-embedding-001"),
upstream_is_stream: false,
request_query: None,
kiro_api_region: None,
},
Some(&batch_body),
)
.as_deref(),
Some(
"https://generativelanguage.googleapis.com/v1beta/models/gemini-embedding-001:batchEmbedContents"
)
);
}
#[test]
fn rerank_request_url_builds_provider_default_paths() {
let openai = sample_transport(

View File

@@ -26,7 +26,10 @@ use crate::vertex::{
is_vertex_service_account_transport_context, is_vertex_transport_context,
local_vertex_gemini_transport_unsupported_reason_with_network,
};
use crate::{build_transport_request_url, ensure_upstream_auth_header, TransportRequestUrlParams};
use crate::{
build_transport_request_url_for_request_body, ensure_upstream_auth_header,
TransportRequestUrlParams,
};
#[derive(Debug, Clone, Copy, PartialEq, Eq)]
pub enum SameFormatProviderFamily {
@@ -76,6 +79,7 @@ pub struct SameFormatProviderUpstreamUrlParams<'a> {
pub upstream_is_stream: bool,
pub request_query: Option<&'a str>,
pub kiro_api_region: Option<&'a str>,
pub provider_request_body: Option<&'a Value>,
}
#[derive(Debug, Clone, Copy)]
@@ -256,7 +260,7 @@ pub fn build_same_format_provider_upstream_url(
transport: &GatewayProviderTransportSnapshot,
params: SameFormatProviderUpstreamUrlParams<'_>,
) -> Option<String> {
build_transport_request_url(
build_transport_request_url_for_request_body(
transport,
TransportRequestUrlParams {
provider_api_format: params.provider_api_format,
@@ -265,6 +269,7 @@ pub fn build_same_format_provider_upstream_url(
request_query: params.request_query,
kiro_api_region: params.kiro_api_region,
},
params.provider_request_body,
)
}

View File

@@ -234,6 +234,9 @@ pub fn is_local_ai_sync_report_kind(report_kind: &str) -> bool {
| "openai_cli_sync_success"
| "openai_image_sync_success"
| "openai_image_sync_error"
| "openai_embedding_sync_success"
| "openai_embedding_sync_error"
| "gemini_embedding_sync_success"
| "claude_cli_sync_success"
| "gemini_cli_sync_success"
| "openai_cli_sync_error"
@@ -426,6 +429,13 @@ mod tests {
));
assert!(is_local_ai_sync_report_kind("openai_image_sync_success"));
assert!(is_local_ai_sync_report_kind("openai_image_sync_error"));
assert!(is_local_ai_sync_report_kind(
"openai_embedding_sync_success"
));
assert!(is_local_ai_sync_report_kind("openai_embedding_sync_error"));
assert!(is_local_ai_sync_report_kind(
"gemini_embedding_sync_success"
));
assert!(is_local_ai_sync_report_kind("gemini_files_delete_mapping"));
assert!(!is_local_ai_sync_report_kind("unknown_sync_kind"));
}