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feat(openai): align GPT-5.6 and Codex request contracts

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MMEXA
2026-07-11 07:40:12 +08:00
parent bc1da3bf3f
commit dfa121dd5b
178 changed files with 17947 additions and 3541 deletions
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crates/aether-model-fetch/src/logic.rs
+120 -12
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@@ -373,13 +373,7 @@ pub fn preset_models_for_provider(provider_type: &str) -> Option<Vec<Value>> {
preset_model("claude-sonnet-4-5-20250929", "anthropic", "Claude Sonnet 4.5", "claude:messages"),
preset_model("claude-haiku-4-5-20251001", "anthropic", "Claude Haiku 4.5", "claude:messages"),
],
"codex" => vec![
preset_model("gpt-5.5", "openai", "GPT-5.5", "openai:responses"),
preset_model("gpt-5.4", "openai", "GPT-5.4", "openai:responses"),
preset_model("gpt-5.4-mini", "openai", "GPT-5.4 Mini", "openai:responses"),
preset_model("gpt-5.3-codex", "openai", "GPT-5.3 Codex", "openai:responses"),
preset_model("gpt-5.3-codex-spark", "openai", "GPT-5.3 Codex Spark", "openai:responses"),
],
"codex" => aether_ai_formats::bundled_codex_model_cards().to_vec(),
"grok" => vec![
preset_model("grok-4.20-0309-non-reasoning", "xai", "Grok 4.20 0309 Non-Reasoning", "openai:chat"),
preset_model("grok-4.20-0309", "xai", "Grok 4.20 0309", "openai:chat"),
@@ -451,6 +445,35 @@ pub fn merge_upstream_metadata(current: Option<&Value>, incoming: &Value) -> Val
Value::Object(merged)
}
pub fn model_catalog_upstream_metadata(
provider_type: &str,
cached_models: &[Value],
) -> Option<Value> {
provider_type.trim().eq_ignore_ascii_case("codex").then(|| {
let cards = aether_ai_formats::effective_codex_model_cards(cached_models);
aether_ai_formats::build_codex_model_catalog_metadata(&cards)
})
}
pub fn upstream_metadata_namespace_updates(
current: Option<&Value>,
incoming: &Value,
) -> Vec<(String, Value)> {
let Some(incoming) = incoming.as_object() else {
return Vec::new();
};
let merged = merge_upstream_metadata(current, &Value::Object(incoming.clone()));
incoming
.keys()
.filter_map(|namespace| {
merged
.get(namespace)
.cloned()
.map(|value| (namespace.clone(), value))
})
.collect()
}
pub fn apply_model_filters(
fetched_model_ids: &[String],
locked_models: Vec<String>,
@@ -691,7 +714,8 @@ fn build_codex_models_url(base_url: &str) -> Option<String> {
if !has_client_version {
let separator = if url.contains('?') { '&' } else { '?' };
url.push(separator);
url.push_str("client_version=0.128.0-alpha.1");
url.push_str("client_version=");
url.push_str(aether_ai_formats::CODEX_CLIENT_VERSION);
}
Some(url)
}
@@ -1006,8 +1030,7 @@ mod tests {
"https://chatgpt.com/backend-api/codex"
),
Some((
"https://chatgpt.com/backend-api/codex/models?client_version=0.128.0-alpha.1"
.to_string(),
"https://chatgpt.com/backend-api/codex/models?client_version=0.144.1".to_string(),
"openai:responses".to_string()
))
);
@@ -1135,6 +1158,33 @@ mod tests {
);
}
#[test]
fn parse_models_response_preserves_gpt_5_6_model_card_capabilities() {
let card = json!({
"slug": "gpt-5.6-sol",
"default_reasoning_level": "low",
"supported_reasoning_levels": [
{"effort": "low"},
{"effort": "max"},
{"effort": "ultra"}
],
"multi_agent_version": "v2",
"supports_image_detail_original": true,
"future_capability": {"mode": "preserve-me"}
});
let parsed = parse_models_response("openai:responses", &json!({"models": [card]}))
.expect("Codex model card should parse");
let cached = &parsed.cached_models[0];
assert_eq!(cached["id"], "gpt-5.6-sol");
assert_eq!(cached["default_reasoning_level"], "low");
assert_eq!(cached["supported_reasoning_levels"][2]["effort"], "ultra");
assert_eq!(cached["multi_agent_version"], "v2");
assert_eq!(cached["supports_image_detail_original"], true);
assert_eq!(cached["future_capability"]["mode"], "preserve-me");
assert_eq!(cached["api_formats"], json!(["openai:responses"]));
}
#[test]
fn parse_models_response_page_reads_claude_pagination_state() {
let parsed = parse_models_response_page(
@@ -1243,13 +1293,71 @@ mod tests {
assert_eq!(
model_ids,
vec![
"gpt-5.6-sol",
"gpt-5.6-terra",
"gpt-5.6-luna",
"gpt-5.5",
"gpt-5.4",
"gpt-5.4-mini",
"gpt-5.3-codex",
"gpt-5.3-codex-spark",
"gpt-5.2",
"codex-auto-review",
]
);
let sol = models
.iter()
.find(|model| model["id"] == "gpt-5.6-sol")
.expect("Sol preset");
assert_eq!(sol["default_reasoning_level"], "low");
assert_eq!(
sol["supported_reasoning_levels"]
.as_array()
.expect("reasoning levels")
.iter()
.filter_map(|level| level["effort"].as_str())
.collect::<Vec<_>>(),
vec!["low", "medium", "high", "xhigh", "max", "ultra"]
);
assert_eq!(sol["multi_agent_version"], "v2");
assert_eq!(sol["supports_image_detail_original"], true);
assert_eq!(sol["context_window"], 372_000);
for model_id in ["gpt-5.6-sol", "gpt-5.6-terra", "gpt-5.6-luna"] {
let model = models
.iter()
.find(|model| model["id"] == model_id)
.expect("GPT-5.6 Codex preset");
assert_eq!(model["shell_type"], "shell_command");
assert_eq!(model["comp_hash"], "3000");
assert_eq!(model["experimental_supported_tools"], json!([]));
assert_eq!(model["tool_mode"], "code_mode_only");
assert_eq!(model["prefer_websockets"], true);
assert_eq!(model["reasoning_summary_format"], "experimental");
assert_eq!(model["truncation_policy"]["limit"], 10_000);
assert_eq!(model["minimal_client_version"], "0.144.0");
assert!(model.get("effective_context_window_percent").is_none());
}
let luna = models
.iter()
.find(|model| model["id"] == "gpt-5.6-luna")
.expect("Luna preset");
assert_eq!(luna["default_reasoning_level"], "medium");
assert_eq!(luna["multi_agent_version"], "v1");
assert!(!luna["supported_reasoning_levels"]
.as_array()
.expect("reasoning levels")
.iter()
.any(|level| level["effort"] == "ultra"));
let auto_review = models
.iter()
.find(|model| model["id"] == "codex-auto-review")
.expect("Codex auto review preset");
assert_eq!(auto_review["visibility"], "hide");
assert_eq!(auto_review["supported_in_api"], true);
assert_eq!(auto_review["default_reasoning_level"], "medium");
assert_eq!(auto_review["default_reasoning_summary"], "none");
assert_eq!(auto_review["use_responses_lite"], false);
}
#[test]