fix: align Profile authoring with compaction and reasoning contracts (T-710)

Resolve MR seq9 supported-compaction-fields and numeric-extraction-reasoning findings. Cover all canonical CompactionConfigPartial settings, token aliases and ratio helpers; accept string effort and signed integer extraction budgets without materializing editor defaults. Audit the remaining Profile field groups against their real serde contracts.

Share an actual-provider value corpus across native, generated WASM, and shared save/projection/verified Runtime archive consumption. Prove inline/import/patch exact values and effective Manifest settings; gate canonical compaction field coverage against serialization of the actual partial type. Keep prior scope union and worker/feature diagnostics fixes intact.

Validation: root cargo check; config-source40; unfiltered server644+11; Runtime340+17+17; API typescript77; Deno39; deno task check0/0; wasm32 release regeneration byte-identical with wasm-bindgen0.2.117/Binaryen132; cargo fmt/diff checks. Logs target/t710-contract-{check,config-source,server,api,runtime}.log. Reviewer seq9 independently confirmed seq3/5/7 resolution and correct main/relative-cwd routing. No target integration/ref mutations.
This commit is contained in:
2026-10-07 02:51:29 +09:00
parent 61f0469986
commit e24fbabe54
6 changed files with 466 additions and 3 deletions
@@ -0,0 +1,116 @@
[
{
"name": "canonical_compaction_tokens",
"profile": {
"compaction": {
"kind": "tokens",
"prune_enabled": false,
"prune_protected_tokens": 3000,
"prune_min_savings": 1000,
"threshold": 80000,
"request_threshold": 90000,
"retained_tokens": 12000,
"overview_target_tokens": 1000,
"overview_warning_tokens": 2000,
"overview_deadline_tokens": 3000,
"worker_context_max_tokens": 20000,
"finish_warning_remaining_tokens": 1000,
"final_reserve_tokens": 2000,
"worker_max_turns": 5,
"summary_target_tokens": 1000,
"summary_max_tokens": 2000,
"auto_read_budget_tokens": 500,
"result_context_max_tokens": 4000,
"model": { "ref": "codex-oauth/gpt-5.6-sol" }
}
},
"manifest_expect": {
"/compaction/prune_enabled": false,
"/compaction/prune_protected_tokens": 3000,
"/compaction/prune_min_savings": 1000,
"/compaction/threshold": 80000,
"/compaction/request_threshold": 90000,
"/compaction/retained_tokens": 12000,
"/compaction/overview_target_tokens": 1000,
"/compaction/overview_warning_tokens": 2000,
"/compaction/overview_deadline_tokens": 3000,
"/compaction/worker_context_max_tokens": 20000,
"/compaction/finish_warning_remaining_tokens": 1000,
"/compaction/final_reserve_tokens": 2000,
"/compaction/worker_max_turns": 5,
"/compaction/summary_target_tokens": 1000,
"/compaction/summary_max_tokens": 2000,
"/compaction/auto_read_budget_tokens": 500,
"/compaction/result_context_max_tokens": 4000,
"/compaction/model/ref": "codex-oauth/gpt-5.6-sol"
}
},
{
"name": "compaction_token_aliases_without_kind",
"profile": {
"compaction": {
"compact_threshold": 80000,
"compact_request_threshold": 90000,
"compact_retained_tokens": 12000,
"compact_worker_max_input_tokens": 20000,
"compact_worker_max_turns": 5,
"compact_auto_read_budget": 500
}
},
"manifest_expect": {
"/compaction/threshold": 80000,
"/compaction/request_threshold": 90000,
"/compaction/retained_tokens": 12000,
"/compaction/worker_context_max_tokens": 20000,
"/compaction/worker_max_turns": 5,
"/compaction/auto_read_budget_tokens": 500
}
},
{
"name": "compaction_ratio_aliases",
"profile": {
"model": { "context_window": 100000 },
"compaction": {
"kind": "ratio",
"threshold": 0.9,
"request": 0.8,
"worker": 0.2
}
},
"manifest_expect": {
"/compaction/threshold": 90000,
"/compaction/request_threshold": 80000,
"/compaction/worker_context_max_tokens": 20000
}
},
{
"name": "numeric_extraction_reasoning",
"profile": {
"engine": { "reasoning": -1 },
"feature": {
"memory": { "extraction": { "enabled": true, "reasoning": 4096 } },
"subjektiv": { "extraction": { "enabled": true, "reasoning": 4096 } }
}
},
"manifest_expect": {
"/engine/reasoning": -1,
"/feature/memory/profile/extraction/reasoning": 4096,
"/feature/subjektiv/profile/extraction/reasoning": 4096
}
},
{
"name": "string_extraction_reasoning",
"profile": {
"feature": {
"memory": { "extraction": { "enabled": true, "reasoning": "high" } },
"subjektiv": {
"extraction": { "enabled": true, "reasoning": "medium" }
}
}
},
"manifest_expect": {
"/feature/memory/profile/extraction/reasoning": "high",
"/feature/subjektiv/profile/extraction/reasoning": "medium"
}
}
]
+14 -3
View File
@@ -9,7 +9,8 @@ let
capability = Unknown; context_window = Int; max_context_window = Int;
};
Extraction = {
enabled = Bool; model = Model; reasoning = String;
# ReasoningControl accepts string effort or signed integer budget.
enabled = Bool; model = Model; reasoning = Unknown;
threshold = Int; worker_max_turns = Int;
};
# Profile scope accepts either a string intent or a table. Decodal 0.4 has
@@ -56,9 +57,19 @@ let
env = { inherit = [...String]; set = { ...Unknown }; };
}]; };
compaction = {
# Token settings (CompactionConfigPartial) and ratio helper fields.
# Threshold/context values accept integer tokens or numeric ratios.
kind = String; threshold = Unknown; request_threshold = Unknown;
prune_enabled = Bool; worker_context_max_tokens = Unknown;
worker_max_turns = Int; model = Model;
worker_context_max_tokens = Unknown; request = Unknown; worker = Unknown;
prune_enabled = Bool; prune_protected_tokens = Int; prune_min_savings = Int;
retained_tokens = Int;
overview_target_tokens = Int; overview_warning_tokens = Int; overview_deadline_tokens = Int;
finish_warning_remaining_tokens = Int; final_reserve_tokens = Int;
worker_max_turns = Int; summary_target_tokens = Int; summary_max_tokens = Int;
auto_read_budget_tokens = Int; result_context_max_tokens = Int; model = Model;
# Supported token aliases remain authorable without rewriting recipes.
compact_threshold = Int; compact_request_threshold = Int; compact_retained_tokens = Int;
compact_worker_max_input_tokens = Int; compact_worker_max_turns = Int; compact_auto_read_budget = Int;
};
web = {
enabled = Bool; allow_private_addresses = Bool;