feat: add embedding and rerank support

This commit is contained in:
Kayphoon
2026-05-03 17:32:41 +08:00
parent 3e2eca4fd0
commit 5abe664d65
87 changed files with 5520 additions and 184 deletions
@@ -37,6 +37,13 @@ const STANDARD_API_FORMAT_ORDER: &[&str] = &[
"claude:messages",
"gemini:generate_content",
];
const EMBEDDING_CANDIDATE_API_FORMATS: &[&str] = &[
"openai:embedding",
"gemini:embedding",
"jina:embedding",
"doubao:embedding",
];
const RERANK_CANDIDATE_API_FORMATS: &[&str] = &["openai:rerank", "jina:rerank"];
pub fn request_candidate_api_format_preference(
client_api_format: &str,
@@ -48,6 +55,26 @@ pub fn request_candidate_api_format_preference(
if client_api_format == "openai:responses:compact" {
return (provider_api_format == "openai:responses:compact").then_some((0, 0));
}
if is_embedding_api_format(client_api_format.as_str()) {
return is_embedding_api_format(provider_api_format.as_str()).then_some((
if client_api_format == provider_api_format {
0
} else {
1
},
embedding_api_format_priority(provider_api_format.as_str()),
));
}
if is_rerank_api_format(client_api_format.as_str()) {
return is_rerank_api_format(provider_api_format.as_str()).then_some((
if client_api_format == provider_api_format {
0
} else {
1
},
rerank_api_format_priority(provider_api_format.as_str()),
));
}
let (client_family, client_kind) =
parse_non_compact_standard_api_format(client_api_format.as_str())?;
@@ -77,6 +104,22 @@ pub fn request_candidate_api_formats(
if client_api_format == "openai:responses:compact" {
return vec!["openai:responses:compact"];
}
if is_embedding_api_format(client_api_format.as_str()) {
let mut candidate_api_formats = EMBEDDING_CANDIDATE_API_FORMATS.to_vec();
candidate_api_formats.sort_by_key(|provider_api_format| {
request_candidate_api_format_preference(client_api_format.as_str(), provider_api_format)
.unwrap_or((u8::MAX, u8::MAX))
});
return candidate_api_formats;
}
if is_rerank_api_format(client_api_format.as_str()) {
let mut candidate_api_formats = RERANK_CANDIDATE_API_FORMATS.to_vec();
candidate_api_formats.sort_by_key(|provider_api_format| {
request_candidate_api_format_preference(client_api_format.as_str(), provider_api_format)
.unwrap_or((u8::MAX, u8::MAX))
});
return candidate_api_formats;
}
if parse_non_compact_standard_api_format(client_api_format.as_str()).is_none() {
return Vec::new();
}
@@ -192,6 +235,20 @@ pub fn is_standard_api_format(api_format: &str) -> bool {
)
}
pub fn is_embedding_api_format(api_format: &str) -> bool {
matches!(
normalize_api_format_alias(api_format).as_str(),
"openai:embedding" | "gemini:embedding" | "jina:embedding" | "doubao:embedding"
)
}
pub fn is_rerank_api_format(api_format: &str) -> bool {
matches!(
normalize_api_format_alias(api_format).as_str(),
"openai:rerank" | "jina:rerank"
)
}
pub fn parse_non_compact_standard_api_format(
api_format: &str,
) -> Option<(&'static str, &'static str)> {
@@ -210,6 +267,10 @@ pub fn api_data_format_id(api_format: &str) -> Option<&'static str> {
"gemini:generate_content" => Some("gemini"),
"openai:chat" => Some("openai_chat"),
"openai:responses" | "openai:responses:compact" => Some("openai_responses"),
"openai:embedding" | "gemini:embedding" | "jina:embedding" | "doubao:embedding" => {
Some("embedding")
}
"openai:rerank" | "jina:rerank" => Some("rerank"),
_ => None,
}
}
@@ -226,9 +287,26 @@ fn standard_api_format_priority(api_format: &str) -> u8 {
.unwrap_or(STANDARD_API_FORMAT_ORDER.len()) as u8
}
fn embedding_api_format_priority(api_format: &str) -> u8 {
let api_format = normalize_api_format_alias(api_format);
EMBEDDING_CANDIDATE_API_FORMATS
.iter()
.position(|candidate| *candidate == api_format)
.unwrap_or(EMBEDDING_CANDIDATE_API_FORMATS.len()) as u8
}
fn rerank_api_format_priority(api_format: &str) -> u8 {
let api_format = normalize_api_format_alias(api_format);
RERANK_CANDIDATE_API_FORMATS
.iter()
.position(|candidate| *candidate == api_format)
.unwrap_or(RERANK_CANDIDATE_API_FORMATS.len()) as u8
}
#[cfg(test)]
mod tests {
use super::{
api_data_format_id, is_embedding_api_format, is_rerank_api_format,
request_candidate_api_format_preference, request_candidate_api_formats,
request_conversion_kind, request_conversion_requires_enable_flag,
sync_chat_response_conversion_kind, sync_cli_response_conversion_kind,
@@ -355,6 +433,162 @@ mod tests {
);
}
#[test]
fn embedding_candidate_registry_excludes_chat_generation_formats() {
assert_eq!(
request_candidate_api_formats("openai:embedding", false),
vec![
"openai:embedding",
"gemini:embedding",
"jina:embedding",
"doubao:embedding",
]
);
assert_eq!(
request_candidate_api_formats("jina:embedding", false),
vec![
"jina:embedding",
"openai:embedding",
"gemini:embedding",
"doubao:embedding",
]
);
assert!(!request_candidate_api_formats("openai:embedding", false).contains(&"openai:chat"));
assert!(!request_candidate_api_formats("openai:embedding", false)
.contains(&"gemini:generate_content"));
assert_eq!(
request_conversion_kind("openai:embedding", "jina:embedding"),
None
);
assert_eq!(
request_conversion_kind("openai:embedding", "openai:chat"),
None
);
assert!(!request_conversion_requires_enable_flag(
"openai:embedding",
"jina:embedding"
));
}
#[test]
fn embedding_candidate_registry_covers_all_provider_orderings() {
assert_eq!(
request_candidate_api_formats("gemini:embedding", true),
vec![
"gemini:embedding",
"openai:embedding",
"jina:embedding",
"doubao:embedding",
]
);
assert_eq!(
request_candidate_api_formats("doubao:embedding", false),
vec![
"doubao:embedding",
"openai:embedding",
"gemini:embedding",
"jina:embedding",
]
);
let embedding_formats = [
"openai:embedding",
"gemini:embedding",
"jina:embedding",
"doubao:embedding",
];
for client_api_format in embedding_formats {
for provider_api_format in embedding_formats {
assert!(
request_candidate_api_format_preference(client_api_format, provider_api_format)
.is_some(),
"{client_api_format} should consider {provider_api_format} as embedding candidate"
);
assert_eq!(
request_conversion_kind(client_api_format, provider_api_format),
None,
"embedding pair should not use chat/generation conversion kind"
);
}
}
}
#[test]
fn embedding_candidate_registry_never_crosses_chat_generation_boundary() {
let embedding_formats = [
"openai:embedding",
"gemini:embedding",
"jina:embedding",
"doubao:embedding",
];
let standard_formats = [
"openai:chat",
"openai:responses",
"claude:messages",
"gemini:generate_content",
];
for embedding_api_format in embedding_formats {
assert!(is_embedding_api_format(embedding_api_format));
assert_eq!(api_data_format_id(embedding_api_format), Some("embedding"));
for standard_api_format in standard_formats {
assert_eq!(
request_candidate_api_format_preference(
embedding_api_format,
standard_api_format
),
None
);
assert_eq!(
request_candidate_api_format_preference(
standard_api_format,
embedding_api_format
),
None
);
assert_eq!(
request_conversion_kind(embedding_api_format, standard_api_format),
None
);
assert_eq!(
request_conversion_kind(standard_api_format, embedding_api_format),
None
);
}
}
}
#[test]
fn rerank_candidate_registry_excludes_chat_and_embedding_formats() {
assert_eq!(
request_candidate_api_formats("openai:rerank", false),
vec!["openai:rerank", "jina:rerank"]
);
assert_eq!(
request_candidate_api_formats("jina:rerank", false),
vec!["jina:rerank", "openai:rerank"]
);
assert_eq!(api_data_format_id("openai:rerank"), Some("rerank"));
assert!(is_rerank_api_format("jina:rerank"));
assert!(!is_embedding_api_format("openai:rerank"));
assert_eq!(
request_candidate_api_format_preference("openai:rerank", "openai:embedding"),
None
);
assert_eq!(
request_candidate_api_format_preference("openai:rerank", "openai:chat"),
None
);
assert_eq!(
request_conversion_kind("openai:rerank", "jina:rerank"),
None
);
assert!(!request_conversion_requires_enable_flag(
"openai:rerank",
"jina:rerank"
));
}
#[test]
fn request_candidate_registry_prefers_same_kind_before_same_family_fallbacks() {
assert_eq!(