Files
Aether/crates/aether-ai-formats/src/formats/shared/model_directives.rs
T

628 lines
19 KiB
Rust

use serde_json::{json, Value};
#[derive(Debug, Clone, PartialEq, Eq)]
pub struct ModelDirective {
pub base_model: String,
pub overrides: Vec<ModelOverride>,
}
#[derive(Debug, Clone, PartialEq, Eq)]
pub enum ModelOverride {
ReasoningEffort(ReasoningEffort),
ServiceTier(ServiceTier),
}
#[derive(Debug, Clone, Copy, PartialEq, Eq)]
pub enum ReasoningEffort {
Low,
Medium,
High,
XHigh,
Max,
}
impl ReasoningEffort {
pub fn parse(value: &str) -> Option<Self> {
match value.trim().to_ascii_lowercase().as_str() {
"low" => Some(Self::Low),
"medium" => Some(Self::Medium),
"high" => Some(Self::High),
"xhigh" => Some(Self::XHigh),
"max" => Some(Self::Max),
_ => None,
}
}
pub fn as_openai_chat_value(self) -> &'static str {
match self {
Self::Low => "low",
Self::Medium => "medium",
Self::High => "high",
Self::XHigh => "xhigh",
Self::Max => "xhigh",
}
}
pub fn as_openai_responses_value(self) -> &'static str {
match self {
Self::Low => "low",
Self::Medium => "medium",
Self::High => "high",
Self::XHigh | Self::Max => "xhigh",
}
}
pub fn as_claude_output_value(self) -> &'static str {
match self {
Self::Low => "low",
Self::Medium => "medium",
Self::High => "high",
Self::XHigh => "xhigh",
Self::Max => "max",
}
}
pub fn as_gemini_level_value(self) -> &'static str {
match self {
Self::Low => "low",
Self::Medium => "medium",
Self::High | Self::XHigh | Self::Max => "high",
}
}
pub fn thinking_budget_tokens(self) -> u64 {
match self {
Self::Low => 1280,
Self::Medium => 2048,
Self::High => 4096,
Self::XHigh | Self::Max => 8192,
}
}
}
#[derive(Debug, Clone, Copy, PartialEq, Eq)]
pub enum ServiceTier {
Priority,
}
impl ServiceTier {
pub fn parse(value: &str) -> Option<Self> {
match value.trim().to_ascii_lowercase().as_str() {
"fast" => Some(Self::Priority),
_ => None,
}
}
pub fn as_openai_value(self) -> &'static str {
match self {
Self::Priority => "priority",
}
}
}
pub fn parse_model_directive(model: &str) -> Option<ModelDirective> {
let (base_model, overrides) = parse_model_directive_parts(model)?;
Some(ModelDirective {
base_model,
overrides,
})
}
fn parse_model_directive_parts(model: &str) -> Option<(String, Vec<ModelOverride>)> {
let mut base_model = model.trim();
let mut overrides = ModelOverrideAccumulator::default();
while let Some((candidate_base, suffix)) = base_model.rsplit_once('-') {
let Some(override_item) = parse_model_override(suffix) else {
break;
};
overrides.insert(override_item)?;
base_model = candidate_base.trim();
}
if base_model.is_empty() {
return None;
}
let overrides = overrides.into_overrides()?;
Some((base_model.to_string(), overrides))
}
fn parse_model_override(suffix: &str) -> Option<ModelOverride> {
ReasoningEffort::parse(suffix)
.map(ModelOverride::ReasoningEffort)
.or_else(|| ServiceTier::parse(suffix).map(ModelOverride::ServiceTier))
}
#[derive(Default)]
struct ModelOverrideAccumulator {
reasoning_effort: Option<ReasoningEffort>,
service_tier: Option<ServiceTier>,
}
impl ModelOverrideAccumulator {
fn insert(&mut self, override_item: ModelOverride) -> Option<()> {
match override_item {
ModelOverride::ReasoningEffort(value) => {
if self.reasoning_effort.replace(value).is_some() {
return None;
}
}
ModelOverride::ServiceTier(value) => {
if self.service_tier.replace(value).is_some() {
return None;
}
}
}
Some(())
}
fn into_overrides(self) -> Option<Vec<ModelOverride>> {
let mut overrides = Vec::new();
if let Some(reasoning_effort) = self.reasoning_effort {
overrides.push(ModelOverride::ReasoningEffort(reasoning_effort));
}
if let Some(service_tier) = self.service_tier {
overrides.push(ModelOverride::ServiceTier(service_tier));
}
(!overrides.is_empty()).then_some(overrides)
}
}
pub fn model_directive_base_model(model: &str) -> Option<String> {
parse_model_directive(model).map(|directive| directive.base_model)
}
pub(crate) fn model_directive_display_model(model: &str) -> Option<String> {
let model = model.trim();
parse_model_directive(model)?;
Some(model.to_string())
}
pub(crate) fn model_directive_display_model_from_report_context(
report_context: &Value,
) -> Option<String> {
report_context
.get("model")
.and_then(Value::as_str)
.and_then(model_directive_display_model)
}
pub fn normalize_model_directive_model(model: &str) -> String {
parse_model_directive(model)
.map(|directive| directive.base_model)
.unwrap_or_else(|| model.trim().to_string())
}
pub fn apply_model_directive_overrides_from_request(
provider_request_body: &mut Value,
provider_api_format: &str,
provider_model: &str,
request_body: &Value,
request_path: Option<&str>,
) -> Option<ModelDirective> {
let source_model = request_body
.get("model")
.and_then(Value::as_str)
.map(str::trim)
.filter(|value| !value.is_empty())
.map(ToOwned::to_owned)
.or_else(|| request_path.and_then(extract_gemini_model_from_path))?;
apply_model_directive_overrides_from_model(
provider_request_body,
provider_api_format,
provider_model,
&source_model,
)
}
pub fn apply_model_directive_overrides_from_model(
provider_request_body: &mut Value,
provider_api_format: &str,
provider_model: &str,
source_model: &str,
) -> Option<ModelDirective> {
let directive = parse_model_directive(source_model)?;
let mut patched_body = provider_request_body.clone();
for override_item in &directive.overrides {
match override_item {
ModelOverride::ReasoningEffort(effort) => {
apply_reasoning_effort_override(
&mut patched_body,
provider_api_format,
provider_model,
*effort,
)?;
}
ModelOverride::ServiceTier(tier) => {
apply_service_tier_override(&mut patched_body, provider_api_format, *tier)?;
}
}
}
*provider_request_body = patched_body;
Some(directive)
}
pub fn apply_model_directive_mapping_patch(
provider_request_body: &mut Value,
patch: &Value,
) -> Option<()> {
deep_merge_json(provider_request_body, patch);
Some(())
}
fn deep_merge_json(target: &mut Value, patch: &Value) {
match (target, patch) {
(Value::Object(target_object), Value::Object(patch_object)) => {
for (key, patch_value) in patch_object {
match target_object.get_mut(key) {
Some(target_value) => deep_merge_json(target_value, patch_value),
None => {
target_object.insert(key.clone(), patch_value.clone());
}
}
}
}
(target, patch) => {
*target = patch.clone();
}
}
}
fn apply_reasoning_effort_override(
provider_request_body: &mut Value,
provider_api_format: &str,
provider_model: &str,
effort: ReasoningEffort,
) -> Option<()> {
match crate::normalize_api_format_alias(provider_api_format).as_str() {
"openai:chat" => set_object_string(
provider_request_body,
"reasoning_effort",
effort.as_openai_chat_value(),
),
"openai:responses" | "openai:responses:compact" => {
set_openai_responses_reasoning_effort(provider_request_body, effort)
}
"claude:messages" => {
set_claude_reasoning_effort(provider_request_body, effort, provider_model)
}
"gemini:generate_content" => {
set_gemini_reasoning_effort(provider_request_body, effort, provider_model)
}
_ => None,
}
}
fn apply_service_tier_override(
provider_request_body: &mut Value,
provider_api_format: &str,
tier: ServiceTier,
) -> Option<()> {
match crate::normalize_api_format_alias(provider_api_format).as_str() {
"openai:chat" | "openai:responses" | "openai:responses:compact" => set_object_string(
provider_request_body,
"service_tier",
tier.as_openai_value(),
),
_ => None,
}
}
fn set_object_string(body: &mut Value, key: &str, value: &str) -> Option<()> {
body.as_object_mut()?
.insert(key.to_string(), Value::String(value.to_string()));
Some(())
}
fn set_openai_responses_reasoning_effort(body: &mut Value, effort: ReasoningEffort) -> Option<()> {
let body_object = body.as_object_mut()?;
let reasoning = body_object
.entry("reasoning".to_string())
.or_insert_with(|| json!({}));
if !reasoning.is_object() {
*reasoning = json!({});
}
reasoning.as_object_mut()?.insert(
"effort".to_string(),
Value::String(effort.as_openai_responses_value().to_string()),
);
Some(())
}
fn set_claude_reasoning_effort(
body: &mut Value,
effort: ReasoningEffort,
provider_model: &str,
) -> Option<()> {
let body_object = body.as_object_mut()?;
let output_config = body_object
.entry("output_config".to_string())
.or_insert_with(|| json!({}));
if !output_config.is_object() {
*output_config = json!({});
}
output_config.as_object_mut()?.insert(
"effort".to_string(),
Value::String(effort.as_claude_output_value().to_string()),
);
let thinking = body_object
.entry("thinking".to_string())
.or_insert_with(|| json!({}));
if !thinking.is_object() {
*thinking = json!({});
}
let thinking = thinking.as_object_mut()?;
if claude_model_uses_adaptive_effort(provider_model) {
thinking.insert("type".to_string(), Value::String("adaptive".to_string()));
thinking.remove("budget_tokens");
} else {
thinking.insert("type".to_string(), Value::String("enabled".to_string()));
thinking.insert(
"budget_tokens".to_string(),
Value::from(effort.thinking_budget_tokens()),
);
}
Some(())
}
fn set_gemini_reasoning_effort(
body: &mut Value,
effort: ReasoningEffort,
provider_model: &str,
) -> Option<()> {
let body_object = body.as_object_mut()?;
let generation_key = if body_object.contains_key("generation_config")
&& !body_object.contains_key("generationConfig")
{
"generation_config"
} else {
"generationConfig"
};
let generation_config = body_object
.entry(generation_key.to_string())
.or_insert_with(|| json!({}));
if !generation_config.is_object() {
*generation_config = json!({});
}
let generation_config = generation_config.as_object_mut()?;
let thinking_key = if generation_config.contains_key("thinking_config")
&& !generation_config.contains_key("thinkingConfig")
{
"thinking_config"
} else {
"thinkingConfig"
};
generation_config.insert(
thinking_key.to_string(),
gemini_reasoning_effort_config(effort, provider_model, thinking_key),
);
Some(())
}
fn gemini_reasoning_effort_config(
effort: ReasoningEffort,
provider_model: &str,
thinking_key: &str,
) -> Value {
if gemini_model_uses_thinking_level(provider_model) {
if thinking_key == "thinking_config" {
return json!({
"include_thoughts": true,
"thinking_level": effort.as_gemini_level_value(),
});
}
return json!({
"includeThoughts": true,
"thinkingLevel": effort.as_gemini_level_value(),
});
}
if thinking_key == "thinking_config" {
return json!({
"include_thoughts": true,
"thinking_budget": effort.thinking_budget_tokens(),
});
}
json!({
"includeThoughts": true,
"thinkingBudget": effort.thinking_budget_tokens(),
})
}
pub fn claude_model_uses_adaptive_effort(model: &str) -> bool {
let model = model.trim().to_ascii_lowercase().replace(['.', '_'], "-");
model.contains("mythos")
|| model.contains("opus-4-7")
|| model.contains("opus-4-6")
|| model.contains("sonnet-4-6")
}
pub fn gemini_model_uses_thinking_level(model: &str) -> bool {
model
.trim()
.to_ascii_lowercase()
.split('/')
.any(|part| part.starts_with("gemini-3"))
}
pub fn extract_gemini_model_from_path(path: &str) -> Option<String> {
let marker = "/models/";
let start = path.find(marker)? + marker.len();
let tail = &path[start..];
let end = tail.find(':').unwrap_or(tail.len());
let model = tail[..end].trim();
(!model.is_empty()).then(|| model.to_string())
}
#[cfg(test)]
mod tests {
use serde_json::json;
use super::{
apply_model_directive_overrides_from_model, parse_model_directive, ModelDirective,
ModelOverride, ReasoningEffort, ServiceTier,
};
#[test]
fn parses_supported_reasoning_effort_suffixes() {
assert_eq!(
parse_model_directive("gpt-5.4-xhigh"),
Some(ModelDirective {
base_model: "gpt-5.4".to_string(),
overrides: vec![ModelOverride::ReasoningEffort(ReasoningEffort::XHigh)],
})
);
assert_eq!(
parse_model_directive("gpt-5.4-MAX"),
Some(ModelDirective {
base_model: "gpt-5.4".to_string(),
overrides: vec![ModelOverride::ReasoningEffort(ReasoningEffort::Max)],
})
);
}
#[test]
fn parses_supported_service_tier_suffixes() {
assert_eq!(
parse_model_directive("gpt-5.4-fast"),
Some(ModelDirective {
base_model: "gpt-5.4".to_string(),
overrides: vec![ModelOverride::ServiceTier(ServiceTier::Priority)],
})
);
}
#[test]
fn parses_combined_suffixes_in_canonical_order() {
let expected = Some(ModelDirective {
base_model: "gpt-5.4".to_string(),
overrides: vec![
ModelOverride::ReasoningEffort(ReasoningEffort::XHigh),
ModelOverride::ServiceTier(ServiceTier::Priority),
],
});
assert_eq!(parse_model_directive("gpt-5.4-fast-xhigh"), expected);
assert_eq!(parse_model_directive("gpt-5.4-xhigh-fast"), expected);
}
#[test]
fn ignores_unknown_or_incomplete_suffixes() {
assert_eq!(parse_model_directive("gpt-5.4-ultra"), None);
assert_eq!(parse_model_directive("gpt-5.4"), None);
assert_eq!(parse_model_directive("-high"), None);
assert_eq!(parse_model_directive("gpt-5.4-high-json"), None);
assert_eq!(parse_model_directive("gpt-5.4-low-high"), None);
}
#[test]
fn applies_reasoning_effort_to_provider_body_shapes() {
let mut openai_chat = json!({"model": "gpt-5-upstream", "reasoning_effort": "low"});
apply_model_directive_overrides_from_model(
&mut openai_chat,
"openai:chat",
"gpt-5-upstream",
"gpt-5.4-xhigh",
)
.expect("directive should apply");
assert_eq!(openai_chat["reasoning_effort"], "xhigh");
let mut responses = json!({
"model": "gpt-5-upstream",
"reasoning": {"effort": "low", "summary": "auto"}
});
apply_model_directive_overrides_from_model(
&mut responses,
"openai:responses",
"gpt-5-upstream",
"gpt-5.4-max",
)
.expect("directive should apply");
assert_eq!(responses["reasoning"]["effort"], "xhigh");
assert_eq!(responses["reasoning"]["summary"], "auto");
let mut claude = json!({"model": "claude-sonnet-4-5"});
apply_model_directive_overrides_from_model(
&mut claude,
"claude:messages",
"claude-sonnet-4-5",
"gpt-5.4-high",
)
.expect("directive should apply");
assert_eq!(claude["thinking"]["budget_tokens"], 4096);
let mut gemini = json!({});
apply_model_directive_overrides_from_model(
&mut gemini,
"gemini:generate_content",
"gemini-2.5-pro",
"gpt-5.4-medium",
)
.expect("directive should apply");
assert_eq!(
gemini["generationConfig"]["thinkingConfig"]["thinkingBudget"],
2048
);
}
#[test]
fn applies_fast_suffix_to_openai_service_tier() {
let mut openai_chat = json!({"model": "gpt-5-upstream"});
apply_model_directive_overrides_from_model(
&mut openai_chat,
"openai:chat",
"gpt-5-upstream",
"gpt-5.4-fast",
)
.expect("directive should apply");
assert_eq!(openai_chat["service_tier"], "priority");
let mut responses = json!({"model": "gpt-5-upstream"});
apply_model_directive_overrides_from_model(
&mut responses,
"openai:responses",
"gpt-5-upstream",
"gpt-5.4-fast",
)
.expect("directive should apply");
assert_eq!(responses["service_tier"], "priority");
}
#[test]
fn applies_combined_suffixes_to_openai_body() {
let mut openai_chat = json!({"model": "gpt-5-upstream", "reasoning_effort": "low"});
apply_model_directive_overrides_from_model(
&mut openai_chat,
"openai:chat",
"gpt-5-upstream",
"gpt-5.4-fast-xhigh",
)
.expect("directive should apply");
assert_eq!(openai_chat["reasoning_effort"], "xhigh");
assert_eq!(openai_chat["service_tier"], "priority");
let mut reversed = json!({"model": "gpt-5-upstream", "reasoning_effort": "low"});
apply_model_directive_overrides_from_model(
&mut reversed,
"openai:chat",
"gpt-5-upstream",
"gpt-5.4-xhigh-fast",
)
.expect("directive should apply");
assert_eq!(reversed, openai_chat);
}
#[test]
fn unsupported_combined_suffix_leaves_body_unchanged() {
let mut claude = json!({"model": "claude-sonnet-4-5"});
let original = claude.clone();
assert!(apply_model_directive_overrides_from_model(
&mut claude,
"claude:messages",
"claude-sonnet-4-5",
"gpt-5.4-fast-xhigh",
)
.is_none());
assert_eq!(claude, original);
}
}