Initial commit

2026-05-08 18:12:45 +00:00
commit 866ba52287
243 changed files with 31492 additions and 0 deletions
@@ -0,0 +1,114 @@
+from __future__ import annotations
+
+import json
+import os
+from typing import Any, Callable
+
+from reflact.gradient.deep_probe import generate_deep_probe_instruction
+from reflact.gradient.reflect import run_minibatch_reflect
+
+
+def run_no_reference_deep_reflect(
+    adapter: Any,
+    results: list[dict],
+    skill_content: str,
+    out_dir: str,
+    *,
+    env_manager: Any = None,
+    prediction_dir: str | None = None,
+    random_seed: int | None = None,
+    step_buffer_context: str = "",
+    output_requirements: list[str] | None = None,
+    metadata_builder: Callable[[dict], dict] | None = None,
+) -> list[dict | None]:
+    """Run teacher-designed diagnostic probing without hidden references."""
+    if not getattr(adapter, "use_deep_reflect", False):
+        return []
+    if not isinstance(env_manager, list):
+        return []
+
+    prediction_dir = prediction_dir or os.path.join(out_dir, "predictions")
+    selected_items = adapter.select_representative_items(
+        results,
+        env_manager,
+        n_failures=getattr(adapter, "deep_reflect_failures", 4),
+        n_successes=getattr(adapter, "deep_reflect_successes", 2),
+        seed=random_seed,
+    )
+    if not selected_items:
+        return []
+
+    selected_ids = {str(item["id"]) for item in selected_items}
+    selected_results = [row for row in results if str(row.get("id")) in selected_ids]
+    if metadata_builder is None:
+        selected_metadata = [
+            {
+                "id": str(item.get("id")),
+                "task_type": str(item.get("task_type") or item.get("topic") or "unknown"),
+                "question_preview": str(item.get("question") or "")[:200],
+            }
+            for item in selected_items
+        ]
+    else:
+        selected_metadata = [metadata_builder(item) for item in selected_items]
+
+    deep_dir = os.path.join(out_dir, "deep_reflect")
+    rollout_dir = os.path.join(deep_dir, "rollout")
+    patches_dir = os.path.join(deep_dir, "patches")
+    os.makedirs(deep_dir, exist_ok=True)
+    print(
+        f"    [2b/6 DEEP REFLECT setup] selected={len(selected_items)} "
+        "mode=no_reference_probe"
+    )
+
+    probe = generate_deep_probe_instruction(
+        skill_content=skill_content,
+        items=selected_results,
+        prediction_dir=prediction_dir,
+        system_prompt=adapter.get_deep_probe_prompt(),
+        step_buffer_context=step_buffer_context,
+        output_requirements=output_requirements,
+    )
+    if not probe:
+        return []
+
+    with open(os.path.join(deep_dir, "probe.json"), "w", encoding="utf-8") as f:
+        json.dump(
+            {
+                **probe,
+                "reference_summary": {
+                    "mode": "no_reference_probe",
+                    "selected_count": len(selected_items),
+                },
+                "selected_examples": selected_metadata,
+            },
+            f,
+            ensure_ascii=False,
+            indent=2,
+        )
+
+    deep_results = adapter.rollout(
+        selected_items,
+        skill_content,
+        rollout_dir,
+        diagnostic_mode=True,
+        diagnostic_instruction=probe["probe_instruction"],
+    )
+    return run_minibatch_reflect(
+        results=deep_results,
+        skill_content=skill_content,
+        prediction_dir=os.path.join(rollout_dir, "predictions"),
+        patches_dir=patches_dir,
+        workers=getattr(adapter, "analyst_workers", 8),
+        failure_only=getattr(adapter, "failure_only", False),
+        minibatch_size=getattr(adapter, "minibatch_size", 8),
+        edit_budget=getattr(adapter, "edit_budget", 4),
+        random_seed=random_seed,
+        error_system=adapter.get_error_minibatch_prompt(),
+        success_system=adapter.get_success_minibatch_prompt(),
+        step_buffer_context=step_buffer_context,
+        update_mode=getattr(getattr(adapter, "_cfg", {}), "get", lambda *_: "patch")(
+            "skill_update_mode",
+            "patch",
+        ),
+    )