feat: show history compression progress and fix action trace overlays

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somew1nd committed 2026-09-03 20:48:23 -07:00
1 parent ab03e1d2bb
commit c79c6eb27b
7 files changed
+468 -43

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@@ -33,7 +33,9 @@ from dataclasses import dataclass, field
import json
from pathlib import Path
import re
import time
from typing import Any, Callable
from uuid import uuid4
from langchain_core.messages import BaseMessage, HumanMessage, SystemMessage
@@ -55,6 +57,9 @@ CHUNK_PENDING_NOTE = (
_NOTE_TOOLS = ("save_note", "update_note", "append_note")
# Reuse one tool trace per chunk across running, success, and failed states.
COMPRESSION_TRACE_NAME = "compress_history"
# ---------------------------------------------------------------------------
# Band ③ — mechanical per-step action ledger
@@ -528,6 +533,15 @@ class ChunkCapsuleService(StepMemoryService):
def __init__(self, ctx: Any, lens: StepCapsuleLens, **kwargs):
super().__init__(ctx, lens=lens, **kwargs)
# Report exhausted retries without waiting for the next render.
self.failure_hook: Callable[[JobKey], None] | None = None
def _on_status(self, key: JobKey, status: str) -> None:
if status == "failed" and self.failure_hook is not None:
try:
self.failure_hook(key)
except Exception as e:
logger.warning(f"Capsule failure hook for {key} raised: {e}")
def _on_ready(self, key: JobKey, summary: str) -> None:
# The turn transcripts only serve generation. A ready capsule is never
@@ -570,6 +584,15 @@ class ChunkState:
band1: dict[str, Any] = field(default_factory=dict)
band2: str | None = None
annotations: list[dict[str, Any]] = field(default_factory=list)
# Segment closure reason: milestone, size, or pressure.
trigger: str | None = None
trace_id: Any = None
trace_step_id: Any = None
announced_at: float | None = None
# Measure source at close and summary at swap; estimate tokens as chars // 4.
# Forced swaps without a capsule leave summary_chars unset.
source_chars: int = 0
summary_chars: int | None = None
@property
def capsule_key(self) -> str:
@@ -881,6 +904,8 @@ class HistoryChunkManager:
self._meter_getter = meter_getter
self._capsule_service = capsule_service or self._build_capsule_service(ctx)
if isinstance(self._capsule_service, ChunkCapsuleService):
self._capsule_service.failure_hook = self._on_capsule_failed
# Trigger state (fed from the graph).
self._step_hashes: dict[str, str] = {}
@@ -1053,7 +1078,7 @@ class HistoryChunkManager:
# bounded to trigger/pressure renders, never every render.
self._redispatch_failed_capsules()
self._harvest_capsules()
self._swap_ready_segments(ledger, hard=hard)
self._swap_ready_segments(ledger, hard=hard, base_tokens=base_tokens)
def _close_new_segments(self, ledger, soft: bool) -> bool:
"""Trigger evaluation: close due segments and dispatch their capsules.
@@ -1082,7 +1107,7 @@ class HistoryChunkManager:
# (the previous segment becomes one HistoryChunk; the floor only
# delays the event, it never splits the segment). The trailing segment
# is subject to the size/soft triggers over its eligible portion only.
selected: list[tuple[str | None, list[dict]]] = []
selected: list[tuple[str | None, list[dict], str]] = []
open_hash = self._last_hash
consumed_prefix = 0
@@ -1092,7 +1117,7 @@ class HistoryChunkManager:
is_last = idx == len(segments) - 1
closed = (not is_last) or seg_hash != open_hash
if closed and consumed_prefix + len(seg_turns) <= remaining_eligible:
selected.append(segment)
selected.append((seg_hash, seg_turns, "milestone"))
consumed_prefix += len(seg_turns)
continue
tail_segment = segment
@@ -1113,19 +1138,21 @@ class HistoryChunkManager:
)
if size_event:
selected.append((tail_segment[0], tail_portion))
selected.append((tail_segment[0], tail_portion, "size"))
elif not milestone_event and soft and tail_portion:
# Soft threshold with nothing else due: close the oldest open
# segment's eligible portion (bounded by the chunk size cap).
selected.append((tail_segment[0], tail_portion[: self._max_steps]))
selected.append((tail_segment[0], tail_portion[: self._max_steps], "pressure"))
if not selected:
return False
steps_by_id = self._load_steps_by_id()
for seg_hash, seg_turns in selected:
for seg_hash, seg_turns, trigger in selected:
for slice_turns in self._slices(seg_turns):
chunk = self._create_chunk(slice_turns, seg_hash, steps_by_id, ledger)
chunk = self._create_chunk(
slice_turns, seg_hash, steps_by_id, ledger, trigger=trigger
)
self._awaiting.append({"chunk": chunk, "turns": list(slice_turns)})
logger.info(
f"History segments closed (ready-gated): {len(self._awaiting)} awaiting"
@@ -1150,10 +1177,11 @@ class HistoryChunkManager:
" retained until a capsule lands."
)
self._capsule_service.submit(key, payload)
self._announce(chunk, "running", note="retrying")
except Exception as e:
logger.error(f"Capsule re-dispatch for {key} failed: {e}")
def _swap_ready_segments(self, ledger, *, hard: bool) -> None:
def _swap_ready_segments(self, ledger, *, hard: bool, base_tokens: int | None = None) -> None:
"""Swap the ready prefix of awaiting segments into the frozen region.
Swaps consume the transcript's oldest unchunked turns, so only a
@@ -1161,6 +1189,9 @@ class HistoryChunkManager:
(and every younger segment's) original text live. The hard threshold
is the sole exception: everything closed force-swaps, pending chunks
included, and the frozen region renders as the L3 snapshot.
``base_tokens`` is the prompt size before the swap, used to estimate
the remaining context on the last swapped chunk's trace.
"""
if not self._awaiting:
return
@@ -1188,6 +1219,51 @@ class HistoryChunkManager:
f" ({len(self._chunks)} chunks, {len(self._eras)} eras,"
f" {len(self._awaiting)} still awaiting, hard={hard})."
)
# Pending chunks contribute only their minimal index to the L3 snapshot.
# Include that size in the context estimate, without a compression ratio.
swapped = [e for e in swap if e["chunk"] is not None]
source_tokens_total = 0
replacement_tokens_total = 0
for entry in swapped:
chunk = entry["chunk"]
if chunk.status == "ready":
chunk.summary_chars = len(render_chunk_block(chunk))
replacement_chars = chunk.summary_chars
else:
chunk.summary_chars = None
replacement_chars = len(chunk.minimal_index or "")
source_tokens_total += chunk.source_chars // 4
replacement_tokens_total += replacement_chars // 4
context_tokens: int | None = None
if base_tokens is not None:
context_tokens = max(
0, int(base_tokens) - source_tokens_total + replacement_tokens_total
)
for index, entry in enumerate(swapped):
chunk = entry["chunk"]
turns = len(entry["turns"])
forced = hard and chunk.status != "ready"
if not forced:
result = f"Replaced {turns} turn{'s' if turns != 1 else ''} with the summary."
else:
result = (
"Context budget reached before the summary was ready;"
f" replaced {turns} turn{'s' if turns != 1 else ''} with a brief"
" snapshot."
)
extra: dict[str, Any] = {
"source_tokens": chunk.source_chars // 4,
"summary_tokens": (
chunk.summary_chars // 4 if chunk.summary_chars is not None else None
),
}
# Show the context estimate once per swap, on its last trace.
if context_tokens is not None and index == len(swapped) - 1:
extra["context_tokens"] = context_tokens
extra["context_budget"] = self._budget
extra["context_estimated"] = True
self._announce(chunk, "success", result=result, forced=forced, extra=extra)
def _partition(self, eligible: list[dict]) -> list[tuple[str | None, list[dict]]]:
"""Split eligible turns into consecutive same-hash segments."""
@@ -1254,6 +1330,8 @@ class HistoryChunkManager:
seg_hash: str | None,
steps_by_id: dict[str, dict],
ledger: Any = None,
*,
trigger: str | None = None,
) -> ChunkState | None:
# A turn carries every step id it recorded (``step_keys``, Flash
# multi-action turns); older ledgers only expose ``step_key``. Each
@@ -1302,14 +1380,89 @@ class HistoryChunkManager:
band3=build_action_ledger(steps, session_start),
minimal_index=build_action_ledger(steps, session_start, minimal=True),
user_lines=[line for line in (injected_instruction_line(s) for s in steps) if line],
trigger=trigger,
)
# Ready gating: the caller queues the chunk as awaiting — it only
# enters self._chunks (and the frozen region) once its capsule is
# ready, or through the hard-threshold emergency swap.
self._persist(chunk)
self._dispatch_capsule(chunk, steps, session_start, turn_records)
# Attach the trace to the step allocated before this prompt render.
chunk.trace_id = uuid4()
chunk.trace_step_id = getattr(self._engine, "current_step_id", None)
chunk.announced_at = time.time()
if ledger is not None:
try:
chunk.source_chars = int(ledger.turn_text_chars(slice_turns))
except Exception as e:
logger.debug(f"Chunk source size unavailable for {chunk.capsule_key}: {e}")
self._announce(chunk, "running", extra={"source_tokens": chunk.source_chars // 4})
return chunk
def _announce(
self,
chunk: ChunkState,
status: str,
*,
result: str | None = None,
error: str | None = None,
note: str | None = None,
forced: bool = False,
extra: dict[str, Any] | None = None,
) -> None:
"""Update the chunk's timeline trace without interrupting compression."""
if chunk.trace_id is None:
return
engine = self._engine
if engine is None or not hasattr(engine, "record_trace"):
return
args: dict[str, Any] = {
"start_step": chunk.start_step_number,
"end_step": chunk.end_step_number,
"steps": len(chunk.source_step_ids),
"milestone": chunk.milestone_label,
"trigger": chunk.trigger,
}
if note:
args["note"] = note
if forced:
args["forced"] = True
if extra:
args.update(extra)
payload: dict[str, Any] = {"args": args}
if result is not None:
payload["result"] = result
if error is not None:
payload["error"] = error
duration = None
if status != "running" and chunk.announced_at is not None:
duration = max(0.0, time.time() - chunk.announced_at)
try:
engine.record_trace(
type="tool",
name=COMPRESSION_TRACE_NAME,
payload=payload,
step_id=chunk.trace_step_id,
status=status,
duration=duration,
trace_id=chunk.trace_id,
)
except Exception as e:
logger.debug(f"Compression announcement skipped for {chunk.capsule_key}: {e}")
def _on_capsule_failed(self, key: JobKey) -> None:
"""Mark the trace failed; keep the chunk pending for a later retry."""
for chunk in self._all_chunks():
if chunk.status != "pending" or chunk.capsule_key != key:
continue
self._announce(
chunk,
"failed",
error="Summary attempts exhausted; the full record is kept and"
" the summary will be retried later.",
)
return
@staticmethod
def _step_payload(step: dict, session_start: float | None) -> dict[str, Any]:
"""Mechanical per-step facts handed to the capsule lens."""