Files
Aether/crates/aether-scheduler-core/src/model.rs

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use std::collections::BTreeSet;
use aether_data_contracts::repository::candidate_selection::{
StoredMinimalCandidateSelectionRow, StoredProviderModelMapping,
};
use aether_data_contracts::DataLayerError;
use regex::RegexBuilder;
pub fn resolve_requested_global_model_name(
rows: &[StoredMinimalCandidateSelectionRow],
requested_model_name: &str,
api_format: &str,
) -> Option<String> {
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resolve_global_model_name_by(rows, |row| row.global_model_name == requested_model_name)
.or_else(|| {
resolve_global_model_name_by(rows, |row| {
row.model_provider_model_name == requested_model_name
})
})
.or_else(|| {
resolve_global_model_name_by(rows, |row| {
row.model_provider_model_mappings
.as_ref()
.is_some_and(|mappings| {
mappings.iter().any(|mapping| {
mapping_scope_matches(mapping, api_format)
&& mapping.name == requested_model_name
})
})
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})
})
.or_else(|| {
resolve_global_model_name_by(rows, |row| {
row.global_model_mappings.as_ref().is_some_and(|patterns| {
patterns
.iter()
.any(|pattern| matches_model_mapping(pattern, requested_model_name))
})
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})
})
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}
pub fn row_supports_requested_model(
row: &StoredMinimalCandidateSelectionRow,
requested_model_name: &str,
api_format: &str,
) -> bool {
row.global_model_name == requested_model_name
|| row.model_provider_model_name == requested_model_name
|| row
.model_provider_model_mappings
.as_ref()
.is_some_and(|mappings| {
mappings.iter().any(|mapping| {
mapping_scope_matches(mapping, api_format)
&& mapping.name == requested_model_name
})
})
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|| row.global_model_mappings.as_ref().is_some_and(|patterns| {
patterns
.iter()
.any(|pattern| matches_model_mapping(pattern, requested_model_name))
})
}
fn resolve_global_model_name_by<F>(
rows: &[StoredMinimalCandidateSelectionRow],
matches: F,
) -> Option<String>
where
F: Fn(&StoredMinimalCandidateSelectionRow) -> bool,
{
let mut best_match = None::<&str>;
for row in rows.iter().filter(|row| matches(row)) {
let candidate = row.global_model_name.trim();
if candidate.is_empty() {
continue;
}
if best_match.is_none_or(|current| candidate < current) {
best_match = Some(candidate);
}
}
best_match.map(ToOwned::to_owned)
}
pub fn resolve_provider_model_name(
row: &StoredMinimalCandidateSelectionRow,
requested_model_name: &str,
api_format: &str,
) -> Option<(String, Option<String>)> {
let selected_provider_model_name = select_provider_model_name(row, api_format);
let Some(key_allowed_models) = row.key_allowed_models.as_ref() else {
return Some((selected_provider_model_name, None));
};
if key_allowed_models.is_empty() {
return None;
}
if key_allowed_models
.iter()
.any(|value| value == requested_model_name)
{
return Some((selected_provider_model_name, None));
}
let mut sorted_allowed_models = key_allowed_models
.iter()
.map(String::as_str)
.map(str::trim)
.filter(|value| !value.is_empty())
.collect::<Vec<_>>();
sorted_allowed_models.sort_unstable();
for &allowed_model in &sorted_allowed_models {
if row_has_candidate_model_name(row, api_format, allowed_model) {
let allowed_model = allowed_model.to_owned();
return Some((selected_provider_model_name.clone(), Some(allowed_model)));
}
}
let global_model_mappings = row.global_model_mappings.as_ref()?;
for &allowed_model in &sorted_allowed_models {
for pattern in global_model_mappings {
if matches_model_mapping(pattern, allowed_model) {
let allowed_model = allowed_model.to_owned();
return Some((allowed_model.clone(), Some(allowed_model)));
}
}
}
None
}
pub fn select_provider_model_name(
row: &StoredMinimalCandidateSelectionRow,
api_format: &str,
) -> String {
let Some(mappings) = row.model_provider_model_mappings.as_ref() else {
return row.model_provider_model_name.clone();
};
mappings
.iter()
.filter(|mapping| mapping_scope_matches(mapping, api_format))
.min_by(|left, right| {
left.priority
.cmp(&right.priority)
.then(left.name.cmp(&right.name))
})
.map(|mapping| mapping.name.clone())
.unwrap_or_else(|| row.model_provider_model_name.clone())
}
pub fn candidate_model_names(
row: &StoredMinimalCandidateSelectionRow,
api_format: &str,
) -> BTreeSet<String> {
let mut names = BTreeSet::from([row.model_provider_model_name.clone()]);
if let Some(mappings) = row.model_provider_model_mappings.as_ref() {
for mapping in mappings {
if mapping_scope_matches(mapping, api_format) {
names.insert(mapping.name.clone());
}
}
}
names
}
fn mapping_scope_matches(mapping: &StoredProviderModelMapping, api_format: &str) -> bool {
let Some(api_formats) = mapping.api_formats.as_ref() else {
return true;
};
api_formats
.iter()
.any(|value| api_format_matches(value, api_format))
}
pub fn row_supports_required_capability(
row: &StoredMinimalCandidateSelectionRow,
required_capability: &str,
) -> bool {
capabilities_support_required_capability(row.key_capabilities.as_ref(), required_capability)
}
fn capabilities_support_required_capability(
capabilities: Option<&serde_json::Value>,
required_capability: &str,
) -> bool {
let required_capability = required_capability.trim();
if required_capability.is_empty() {
return true;
}
let Some(capabilities) = capabilities else {
return false;
};
if let Some(object) = capabilities.as_object() {
return object.iter().any(|(key, value)| {
key.eq_ignore_ascii_case(required_capability)
&& match value {
serde_json::Value::Bool(value) => *value,
serde_json::Value::String(value) => value.eq_ignore_ascii_case("true"),
serde_json::Value::Number(value) => {
value.as_i64().is_some_and(|value| value > 0)
}
_ => false,
}
});
}
if let Some(items) = capabilities.as_array() {
return items.iter().any(|value| {
value
.as_str()
.is_some_and(|value| value.eq_ignore_ascii_case(required_capability))
});
}
false
}
pub fn matches_model_mapping(pattern: &str, model_name: &str) -> bool {
if pattern.eq_ignore_ascii_case(model_name) {
return true;
}
let regex_pattern = format!("^(?:{pattern})$");
let Ok(compiled) = RegexBuilder::new(&regex_pattern)
.case_insensitive(true)
.build()
else {
return false;
};
compiled.is_match(model_name)
}
pub fn extract_global_priority_for_format(
raw: Option<&serde_json::Value>,
api_format: &str,
) -> Result<Option<i32>, DataLayerError> {
let Some(raw) = raw else {
return Ok(None);
};
let Some(object) = raw.as_object() else {
return Err(DataLayerError::UnexpectedValue(
"provider_api_keys.global_priority_by_format is not a JSON object".to_string(),
));
};
let Some(value) = object
.iter()
.find(|(key, _)| api_format_matches(key, api_format))
.map(|(_, value)| value)
else {
return Ok(None);
};
if let Some(value) = value.as_i64() {
return i32::try_from(value).map(Some).map_err(|_| {
DataLayerError::UnexpectedValue(format!(
"invalid provider_api_keys.global_priority_by_format value: {value}"
))
});
}
if let Some(value) = value.as_str() {
let value = value.trim().parse::<i32>().map_err(|_| {
DataLayerError::UnexpectedValue(format!(
"invalid provider_api_keys.global_priority_by_format value: {value}"
))
})?;
return Ok(Some(value));
}
Err(DataLayerError::UnexpectedValue(
"provider_api_keys.global_priority_by_format contains a non-integer value".to_string(),
))
}
pub fn normalize_api_format(value: &str) -> String {
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aether_ai_formats::normalize_api_format_alias(value)
}
fn row_has_candidate_model_name(
row: &StoredMinimalCandidateSelectionRow,
api_format: &str,
model_name: &str,
) -> bool {
row.model_provider_model_name == model_name
|| row
.model_provider_model_mappings
.as_ref()
.is_some_and(|mappings| {
mappings.iter().any(|mapping| {
mapping_scope_matches(mapping, api_format) && mapping.name == model_name
})
})
}
fn api_format_matches(left: &str, right: &str) -> bool {
normalize_api_format(left) == normalize_api_format(right)
}
#[cfg(test)]
mod tests {
use super::matches_model_mapping;
#[test]
fn model_mapping_match_is_case_insensitive() {
assert!(matches_model_mapping("gpt-4o", "GPT-4O"));
assert!(matches_model_mapping("gpt-5(?:\\.\\d+)?", "GPT-5.1"));
}
#[test]
fn model_mapping_match_is_anchored_to_full_text() {
assert!(matches_model_mapping("gpt-4o", "gpt-4o"));
assert!(!matches_model_mapping("gpt-4o", "gpt-4o-mini"));
}
#[test]
fn invalid_model_mapping_pattern_returns_false() {
assert!(!matches_model_mapping("([a-z", "gpt-4o"));
}
}