310aed9ff0
* docs: consolidate governance anchors and clean up test registries * refactor(cli): decompose cli into dedicated modules * test: fix broken test baselines and formatting * docs: add domain boundary READMEs for governance anchors * test: update baseline for determination lane * test: fix capability_pass expectation * test: fix CORE_SHOWCASE_SKIP_BUDGET enforcement * chore: cleanup CLI extraction and unreachable code
292 lines
10 KiB
Python
292 lines
10 KiB
Python
"""generate/bridge_trace.py — per-turn articulation bridge trace.
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Phase 1 of the full-sentence output mastery plan. Every call to
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``articulate_with_intent()`` in ``generate/intent_bridge.py`` emits
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one ``BridgeTraceRecord`` through the module-level sink when a sink
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has been attached. When no sink is attached the emission is a pure
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no-op with zero overhead beyond the ``is None`` check.
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Follows the same trust-boundary conventions as ADR-0040
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(``chat/telemetry.py``):
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* **Redact-by-default.** ``recalled_words_sample`` and
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``bridge_surface`` are only included in the serialized record when
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the caller sets ``include_content=True``.
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* **No implicit wall-clock.** ``timestamp`` is caller-provided.
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* **Append-only file paths.** ``JsonlFileSink`` opens in append mode.
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* **Idempotent flush.** Each ``emit()`` flushes immediately.
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The record covers every diagnostic dimension named in the mastery
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plan's Phase 1.3 trace specification:
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intent_tag — classifier output (string name of IntentTag)
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intent_subject — classifier subject slot
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plan_subject — ArticulationPlan.subject
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plan_predicate — ArticulationPlan.predicate
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plan_object — ArticulationPlan.object (None → empty string)
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recalled_words_len — len(recalled_words) passed to the bridge
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recalled_words_sample — first 5 recalled words (content-gated)
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pre_ground_obj — graph node obj before ground_graph() ran
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post_ground_obj — graph node obj after ground_graph() ran
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bridge_surface — the surface the bridge produced (content-gated)
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bridge_useful — whether _is_useful_surface() passed
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fallback_surface — ArticulationPlan.surface (content-gated)
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See ``docs/adr/full-sentence-output-plan.md``.
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"""
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from __future__ import annotations
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import json
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from dataclasses import dataclass, field
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from pathlib import Path
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from typing import IO, Protocol
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# ---------------------------------------------------------------------------
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# Record
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# ---------------------------------------------------------------------------
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@dataclass(frozen=True, slots=True)
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class BridgeTraceRecord:
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"""One per-turn observation record from the intent bridge.
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All fields are plain Python types so serialization is trivial and
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the record is safe to construct inside the hot path without any
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I/O or numpy dependency.
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"""
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intent_tag: str # IntentTag.name (e.g. "DEFINITION")
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intent_subject: str # classifier subject slot, "" if None
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plan_subject: str
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plan_predicate: str
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plan_object: str # "" when ArticulationPlan.object is None
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recalled_words_len: int
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recalled_words_sample: tuple[str, ...] # first ≤5 words; () when redacted
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pre_ground_obj: str # graph p0.obj before ground_graph
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post_ground_obj: str # graph p0.obj after ground_graph
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bridge_surface: str # "" when redacted
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bridge_useful: bool
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fallback_surface: str # "" when redacted
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# ---------------------------------------------------------------------------
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# Serializer
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# ---------------------------------------------------------------------------
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def serialize_bridge_trace(
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record: BridgeTraceRecord,
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*,
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include_content: bool = False,
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timestamp: str | None = None,
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) -> dict[str, object]:
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"""Produce a JSON-safe audit dict from a ``BridgeTraceRecord``.
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Content fields (``recalled_words_sample``, ``bridge_surface``,
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``fallback_surface``) are only emitted when ``include_content``
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is True. The metadata fields are always emitted so aggregation
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pipelines can compute grounding-rate statistics without ever
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seeing raw surface text.
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"""
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out: dict[str, object] = {
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"type": "bridge_trace",
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"intent_tag": record.intent_tag,
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"intent_subject_len": len(record.intent_subject),
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"plan_subject_len": len(record.plan_subject),
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"plan_predicate_len": len(record.plan_predicate),
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"plan_object_present": bool(record.plan_object),
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"recalled_words_len": record.recalled_words_len,
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"pre_ground_obj_pending": record.pre_ground_obj in ("<pending>", "<prior>"),
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"post_ground_obj_pending": record.post_ground_obj in ("<pending>", "<prior>"),
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"bridge_useful": record.bridge_useful,
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# Derived diagnostic flag: grounding changed something.
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"grounding_changed_obj": record.pre_ground_obj != record.post_ground_obj,
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}
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if include_content:
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out["intent_subject"] = record.intent_subject
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out["plan_subject"] = record.plan_subject
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out["plan_predicate"] = record.plan_predicate
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out["plan_object"] = record.plan_object
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out["recalled_words_sample"] = list(record.recalled_words_sample)
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out["pre_ground_obj"] = record.pre_ground_obj
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out["post_ground_obj"] = record.post_ground_obj
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out["bridge_surface"] = record.bridge_surface
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out["fallback_surface"] = record.fallback_surface
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if timestamp is not None:
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out["timestamp"] = str(timestamp)
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return out
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def format_bridge_trace_jsonl(
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record: BridgeTraceRecord,
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*,
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include_content: bool = False,
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timestamp: str | None = None,
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) -> str:
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"""Serialize one trace record as a deterministic JSONL line.
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Field order is alphabetical (``sort_keys=True``) for byte-stable
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replay diffing. No trailing newline — the sink owns termination.
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"""
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payload = serialize_bridge_trace(
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record, include_content=include_content, timestamp=timestamp
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)
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return json.dumps(payload, sort_keys=True, separators=(",", ":"))
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# ---------------------------------------------------------------------------
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# Sink protocol
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# ---------------------------------------------------------------------------
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class BridgeTraceSink(Protocol):
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"""Minimal sink contract (mirrors TurnEventSink in chat/telemetry.py).
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Sinks receive one already-serialized JSONL line per
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``articulate_with_intent()`` call. The sink is attached at the
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module level via ``attach_bridge_trace_sink``; callers that never
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attach a sink pay only the ``is None`` guard cost.
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"""
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def emit(self, line: str) -> None: ...
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# ---------------------------------------------------------------------------
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# Concrete sinks
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# ---------------------------------------------------------------------------
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@dataclass
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class JsonlBufferSink:
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"""In-memory sink that captures every emitted line.
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Useful for tests and interactive session analysis where
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persistence is the caller's responsibility.
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"""
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lines: list[str] = field(default_factory=list)
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include_content: bool = False
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def emit(self, line: str) -> None:
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self.lines.append(line)
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def records(self) -> list[dict]:
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"""Parse all emitted lines and return them as dicts."""
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return [json.loads(line) for line in self.lines]
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def grounding_rate(self) -> float:
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"""Fraction of turns where the bridge produced a useful surface.
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Returns 0.0 when no lines have been emitted yet.
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"""
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parsed = self.records()
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if not parsed:
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return 0.0
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return sum(1 for r in parsed if r.get("bridge_useful")) / len(parsed)
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def pending_rate(self) -> float:
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"""Fraction of turns where the post-ground obj was still <pending>.
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Returns 0.0 when no lines have been emitted yet.
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"""
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parsed = self.records()
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if not parsed:
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return 0.0
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return sum(1 for r in parsed if r.get("post_ground_obj_pending")) / len(parsed)
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def recalled_words_empty_rate(self) -> float:
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"""Fraction of turns where recalled_words_len == 0."""
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parsed = self.records()
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if not parsed:
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return 0.0
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return sum(1 for r in parsed if r.get("recalled_words_len", 0) == 0) / len(parsed)
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def summary(self) -> dict:
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"""One-shot diagnostic summary dict for operator inspection."""
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parsed = self.records()
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n = len(parsed)
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if n == 0:
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return {"turns": 0}
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by_intent: dict[str, dict] = {}
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for r in parsed:
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tag = r.get("intent_tag", "UNKNOWN")
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bucket = by_intent.setdefault(tag, {"total": 0, "useful": 0, "pending": 0, "no_recalled": 0})
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bucket["total"] += 1
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if r.get("bridge_useful"):
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bucket["useful"] += 1
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if r.get("post_ground_obj_pending"):
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bucket["pending"] += 1
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if r.get("recalled_words_len", 0) == 0:
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bucket["no_recalled"] += 1
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return {
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"turns": n,
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"grounding_rate": round(self.grounding_rate(), 4),
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"pending_rate": round(self.pending_rate(), 4),
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"recalled_words_empty_rate": round(self.recalled_words_empty_rate(), 4),
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"by_intent": by_intent,
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}
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class JsonlFileSink:
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"""Append-only JSONL file sink with eager flush.
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Path fixed at construction. Each ``emit()`` flushes immediately
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so a crashed turn loop still has prior turns durable on disk.
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Supports context-manager usage.
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"""
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def __init__(
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self,
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path: str | Path,
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*,
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include_content: bool = False,
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) -> None:
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self._path = Path(path)
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self._include_content = include_content
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self._fh: IO[str] | None = None
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def emit(self, line: str) -> None:
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if self._fh is None:
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self._path.parent.mkdir(parents=True, exist_ok=True)
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self._fh = self._path.open("a", encoding="utf-8")
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self._fh.write(line)
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self._fh.write("\n")
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self._fh.flush()
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def close(self) -> None:
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if self._fh is not None:
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self._fh.close()
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self._fh = None
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def __enter__(self) -> "JsonlFileSink":
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return self
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def __exit__(self, *exc_info) -> None:
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self.close()
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@dataclass
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class FanOutSink:
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"""Forward every emitted line to N sinks in declaration order.
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Fail-fast: if sink *i* raises, sinks *i+1..* are NOT called.
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"""
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sinks: tuple = () # tuple[BridgeTraceSink, ...]
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def emit(self, line: str) -> None:
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for sink in self.sinks:
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sink.emit(line)
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__all__ = [
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"BridgeTraceRecord",
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"BridgeTraceSink",
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"FanOutSink",
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"JsonlBufferSink",
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"JsonlFileSink",
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"format_bridge_trace_jsonl",
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"serialize_bridge_trace",
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]
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