docs/Architecture.md

@@ -332,9 +332,15 @@ logs the outage; interrupted outbound effects are covered by intents (L8).
 ### L6. Context and memory
 
 **1. The working context of one model call** is rendered from the log at call time
-for one role, fitted to that model's window, and never stored. Fitting never drops
-the system prompt, the current plan or the most recent turns; a call that still
-doesn't fit fails (L9).
+for one role, fitted to that model's window, and never stored.
+- **A long run is compacted:** well before the window fills, the model's own
+  notes replace the middle of its run in one step (a `compaction` event, L7),
+  keeping word for word what started the work and its last few turns. Rare,
+  large steps keep the start of the prompt unchanged between them, so the
+  model server reuses its cache.
+- **Fitting is the last guard:** it never drops the system prompt, the current
+  plan or the most recent turns, and a call that still doesn't fit fails (L9).
+  Each cut it makes is logged; after compaction one is a sign of trouble.
 
 **2. The work-item transcript** (the log, L7) is durable and scoped to one item:
 nothing crosses items, and agent-level calls (switching, duty runs) see other items

docs/Development-Plan.md

@@ -713,6 +713,10 @@ of earlier points, replies on threads, the round cap and its reset, `stop` and
   environment only. A stop ends a git command, and a cut-short first clone is
   removed. `review.clone` / `review.fetch` log the time and size. No size
   limits yet. Tests: `test_clones.py`, against local bare repositories.
+- **Compaction** (#158; reviews of PRs touching about 20 files hit the turn cap,
+  re-reading files fitting had cut): shared by both agents' driver runs, as in
+  L6 above. Each cut fitting still makes is logged (`context.trimmed`).
+  Tests: `test_compact.py` in nisse-core.
 
 **M7.6 Deployment.** *Waits for the agent host (Phase 6).* Its image, container,
 Gitea account and secrets (R5). The image needs `git`, and `scratch/` a
@@ -771,6 +775,15 @@ if the implementation differs.
   proposal comment older than the reply.
 - **L5 transport:** the `Transport` interface is send, ask and receive. Intake
   backoff is exponential, capped at a few minutes.
+- **L6 compaction (#158):** before each driver call, over `compact_at` (0.6) of
+  the prompt budget, the same model is asked, over the same request plus one
+  message, for notes on everything between what started the work and the last
+  turns (at most `compact_keep_turns`, 3, in `compact_to`, 0.25). The notes,
+  with code's list of the calls they replace, become a `compaction` event
+  that renders in place of its range; a later one folds in the earlier.
+  Failed notes are logged (`context.compaction_failed`) and fitting takes
+  over; `context.compacted` logs each one. Not yet in nisse-dev's helper
+  loop.
 - **L6 fitting order:** first shorten old tool results to their first and last
   lines, then drop the oldest events with a note saying so; never the system
   prompt, the current plan or the most recent turns. View labels:

docs/Tuning-Guide.md

@@ -283,9 +283,39 @@ what failed last; the start keeps the exit code.
 - **Too high:** the transcript outgrows the context window sooner. The
   context budget copes (see below), but by cutting older output harder.
 
-### `tuning.context` — fitting each request into the window
+### `tuning.context` — compaction, and fitting each request into the window
 
-Before any request is sent, the agent checks it against the model's context
+**Compaction comes first.** A driver run's request grows with every tool
+result. Once it passes `compact_at` of the prompt budget, the model is asked
+for notes on its run so far: findings with the code they rest on, what each
+file told it, what is left to do. The notes replace everything between what
+started the work (the brief, or the conversation) and the last few turns,
+which stay word for word. The model server has the request cached already,
+so the notes cost only their own output. Because it happens rarely and drops
+the request well below the limit, the start of the prompt stays the same for
+many calls, and the server keeps reusing its cache.
+
+Logged as `context.compacted` (tokens before and after, seconds). Notes that
+fail, come back empty or leave the request still too big are logged as
+`context.compaction_failed`; the run goes on and fitting (below) cuts
+instead, and compaction isn't tried again for `compact_keep_turns` turns.
+
+| Knob | Default | |
+|---|---|---|
+| `compact_at` | 0.6 | fraction of the prompt budget that sets compaction off; 0 turns it off |
+| `compact_to` | 0.25 | what the kept recent turns may take, at most |
+| `compact_keep_turns` | 3 | recent turns kept word for word, at most |
+
+- **`compact_at` too high:** little room left for the notes call and a big
+  result that lands in one turn, so fitting cuts more often. **Too low:**
+  compactions come often, and each one loses detail.
+- **`compact_to` / `compact_keep_turns` too low:** the model loses sight of
+  what it just did. **Too high:** the notes don't bring the request far
+  enough down, and compactions come sooner.
+- **Deciding:** look for `context.trimmed` in the log. After compaction it
+  should be rare; each one means the model lost something it had read.
+
+**Fitting is the last guard.** Before any request is sent, the agent checks it against the model's context
 window and makes it fit. A server doesn't always refuse a prompt that's too
 long. Ollama silently drops its start, which is where the system prompt and
 the plan are, so an unfitted request can fail in a way nobody sees.
@@ -304,6 +334,9 @@ order, stopping at the first that fits:
 3. **If the system prompt and the recent turns still don't fit,** the
    request is not sent. The milestone stops and asks you.
 
+Each cut is logged as `context.trimmed`, with how many results were
+shortened and events dropped.
+
 Tokens are estimated from characters (pessimistically, at 3 per token) and
 the estimate is corrected from the prompt sizes the server reports. The
 correction only ever makes the estimate larger.

nisse-core/src/nisse_core/loop/driver.py

@@ -2,7 +2,8 @@
 tool, runs out of turns, or is stopped.
 
 Everything the run does is written to the item's transcript as the driver
-(L7), and every model call sees the driver's view of it (L6). Execution tools
+(L7), and every model call sees the driver's view of it (L6), compacted
+when it grows long (``compact``). Execution tools
 go to the item's executor, on its tool VM (L13); control tools are answered
 here, and a waiting one ends the run, so the scheduler can put it to the
 operator. Which tools wait is the agent's: each run is told.
@@ -14,6 +15,7 @@ from typing import Any, Literal, Protocol
 
 from nisse_core.log.canonical import AssistantText, Fact, ToolCall, ToolResult
 from nisse_core.loop.tools import names
+from nisse_core.models.compact import Compactor
 from nisse_core.models.llm import LLMClient, LLMError
 from nisse_core.state.cancel import Cancel, skip_calls
 from nisse_core.state.store import Transcript
@@ -82,8 +84,10 @@ class Driver:
         max_turns: int = DEFAULT_MAX_TURNS,
         cancel: Cancel | None = None,
         failure_limit: int = 0,  # 0: no limit
+        compactor: Compactor | None = None,
     ) -> None:
         self._client = client
+        self._compactor = compactor
         self._model = model
         self._max_turns = max_turns
         self._failure_limit = failure_limit
@@ -123,6 +127,12 @@ class Driver:
             # L2: stop takes effect at the next tool boundary.
             if self._cancel.requested:
                 return RunOutcome("stopped", note=f"before turn {turn + 1}")
+            if self._compactor is not None:
+                # Not a turn: the model's notes replace the middle of a long
+                # run before it outgrows the window (L6).
+                self._compactor.compact(
+                    transcript, system=system, tools=tools, model=model
+                )
             try:
                 produced = self._client.complete(
                     transcript.view(), tools=tools, model=model, system=system

nisse-core/src/nisse_core/models/compact.py

@@ -0,0 +1,262 @@
+"""Compaction (architecture L6, L7): the model's own notes replace the middle
+of a long run, so it stays inside the window without losing what it found.
+
+Before each model call of a driver run, ``Compactor.compact`` looks at the
+size of the request. Below ``compact_at`` (a fraction of the prompt budget)
+it does nothing. Above it, in one step:
+
+1. It keeps, word for word, everything before the first turn (the brief, or
+   the conversation that started the work) and the last few turns, as many
+   as fit in ``compact_to`` of the budget, at most ``keep_turns``.
+2. It asks the same model, over the very same request plus one more
+   message, for notes on everything in between. The model server has that
+   request cached from the last call, so the notes cost only their own
+   output. The model offered the run's tools is not made to call one.
+3. It records a ``Compaction`` event replacing that range, the notes with a
+   list of the calls made in it appended by code, so the model knows what it
+   can look at again. The log keeps everything it replaces.
+
+Doing this rarely, and well below the limit, keeps the start of the prompt
+the same for many calls, which is what lets the server reuse its cache.
+Cutting a little every call, as fitting does, changes it every time.
+
+A compaction that fails (the call fails, the notes are empty, or they leave
+the request still over ``compact_at``) is logged and the run goes on; the
+request is then fitted as before (``context``). It isn't tried again until
+``keep_turns`` more turns have passed.
+"""
+
+import json
+import time
+from collections.abc import Sequence
+from dataclasses import dataclass
+from typing import Any
+
+from nisse_core.log.canonical import (
+    AssistantText,
+    Compaction,
+    StoredEvent,
+    ToolCall,
+    UserMessage,
+)
+from nisse_core.models.context import _MODEL_SIDE, _turn_starts
+from nisse_core.models.llm import LLMError
+from nisse_core.models.render import effective_events
+from nisse_core.oplog import OpLog
+from nisse_core.state.store import Transcript
+
+# The list of calls appended to the notes: how many, and how long each line.
+MAX_LISTED_CALLS = 80
+LISTED_CALL_CHARS = 200
+
+NOTES_REQUEST = """\
+[orchestrator] Your context is nearly full. Write notes to replace the \
+conversation from your task up to your last few turns (the task itself and \
+those turns stay as they are). Reply with the notes as plain text, not a \
+tool call. Include:
+
+- What the task is, and what you have done so far.
+- Your findings and conclusions so far, each with its file and line and \
+the exact code or text it rests on, quoted.
+- Decisions made and anything the operator or a peer asked for, word for \
+word where the wording matters.
+- What each file you read or command you ran told you that you still need.
+- What is left to do, in order.
+
+Leave out what you no longer need. These notes are all you will have of that \
+part of the conversation; anything else you would have to look at again."""
+
+
+@dataclass(frozen=True)
+class CompactionTuning:
+    compact_at: float = 0.6  # of the prompt budget; 0: never compact
+    compact_to: float = 0.25  # what the kept recent turns may take
+    keep_turns: int = 3  # recent turns kept word for word, at most
+
+
+def check_tuning(tuning: CompactionTuning, section: str, errors: list[str]) -> None:
+    """The agents' config check: notes must leave the request smaller than
+    what set them off, or every call would compact again."""
+    if tuning.compact_at and not tuning.compact_to < tuning.compact_at <= 1:
+        errors.append(
+            f"{section}: compact_to must be less than compact_at, which is at "
+            "most 1 (or 0: never compact)"
+        )
+
+
+class Compactor:
+    def __init__(
+        self,
+        client: Any,
+        tuning: CompactionTuning | None = None,
+        *,
+        oplog: OpLog | None = None,
+    ) -> None:
+        """``client``: the run's client. Compaction needs its budget
+        (``budget_for``, ``estimate``); with a client that has none, as in
+        tests with a scripted model, it never compacts."""
+        self._client = client
+        self._tuning = tuning or CompactionTuning()
+        self._oplog = oplog
+        # Per run (work item, first event shown): the number of turns when
+        # compaction last failed.
+        self._failed_at: dict[tuple[str | None, int], int] = {}
+
+    def compact(
+        self,
+        transcript: Transcript,
+        *,
+        system: str | None,
+        tools: list[dict[str, Any]] | None,
+        model: str,
+    ) -> bool:
+        """Compact the transcript if its request is over ``compact_at``.
+        True if a compaction was recorded."""
+        tuning = self._tuning
+        budget_for = getattr(self._client, "budget_for", None)
+        estimate = getattr(self._client, "estimate", None)
+        if not tuning.compact_at or budget_for is None or estimate is None:
+            return False
+        limit = budget_for(model).for_prompt
+        events = effective_events(transcript.view())
+        before = estimate(events, system, tools, model)
+        if before <= tuning.compact_at * limit:
+            return False
+
+        starts = _turn_starts(events)
+        run = (transcript.work_item, events[0].id if events else 0)
+        failed_at = self._failed_at.get(run)
+        if failed_at is not None and len(starts) < failed_at + tuning.keep_turns:
+            return False
+        head = _head_end(events)
+        # The recent turns kept: at most keep_turns, as many as fit in
+        # compact_to, and at least one, so the model sees where it is.
+        later = [s for s in starts if s > head]
+        recent_from = len(events)
+        for start in reversed(later[-tuning.keep_turns :]):
+            if recent_from < len(events) and (
+                estimate(events[start:], None, None, model) > tuning.compact_to * limit
+            ):
+                break
+            recent_from = start
+        middle = events[head:recent_from]
+        turns = sum(1 for s in later if s < recent_from)
+        if turns < 2:
+            # Too little to be worth notes (or nothing at all): fitting
+            # covers it, and logs what it cuts.
+            return False
+
+        started = time.monotonic()
+        try:
+            notes = self._notes(events, system, tools, model)
+        except LLMError as exc:  # a failed compaction never fails the run
+            return self._failed(run, transcript, len(starts), f"the call failed: {exc}")
+        if not notes:
+            return self._failed(run, transcript, len(starts), "the notes were empty")
+
+        first = min(
+            e.event.replaces[0] if isinstance(e.event, Compaction) else e.id
+            for e in middle
+        )
+        last = max(e.id for e in middle if not isinstance(e.event, Compaction))
+        listed = _calls(middle)
+        summary = notes + (
+            "\n\nCalls made in the part these notes replace (make one again "
+            "to see its result):\n" + "\n".join(listed)
+            if listed
+            else ""
+        )
+        compaction = Compaction(summary=summary, model=model, replaces=[first, last])
+        placed = StoredEvent(id=first, ts="", event=compaction)
+        after = estimate(
+            [*events[:head], placed, *events[recent_from:]], system, tools, model
+        )
+        if after > tuning.compact_at * limit:
+            return self._failed(
+                run,
+                transcript,
+                len(starts),
+                f"the request would still be {after} tokens, over "
+                f"{int(tuning.compact_at * limit)}",
+            )
+        transcript.append(compaction)
+        self._failed_at.pop(run, None)
+        if self._oplog is not None:
+            self._oplog.emit(
+                "context.compacted",
+                cause=f"the request was {before} tokens of {limit}",
+                work_item=transcript.work_item,
+                model=model,
+                tokens_before=before,
+                tokens_after=after,
+                replaced=[first, last],
+                turns_replaced=turns,
+                seconds=round(time.monotonic() - started, 1),
+            )
+        return True
+
+    def _notes(
+        self,
+        events: list[StoredEvent],
+        system: str | None,
+        tools: list[dict[str, Any]] | None,
+        model: str,
+    ) -> str:
+        # The same system prompt and tools as the run's calls, so the server
+        # reuses the cached request: only the last message is new.
+        ask = StoredEvent(
+            id=0, ts="", event=UserMessage(text=NOTES_REQUEST, source="compaction")
+        )
+        produced = self._client.complete(
+            [*events, ask], tools, model, system=system, require_tool_call=False
+        )
+        return "\n".join(
+            e.text.strip() for e in produced if isinstance(e, AssistantText)
+        ).strip()
+
+    def _failed(
+        self,
+        run: tuple[str | None, int],
+        transcript: Transcript,
+        turns: int,
+        why: str,
+    ) -> bool:
+        self._failed_at[run] = turns
+        if self._oplog is not None:
+            self._oplog.emit(
+                "context.compaction_failed",
+                cause=why[:300],
+                work_item=transcript.work_item,
+            )
+        return False
+
+
+def _head_end(events: Sequence[StoredEvent]) -> int:
+    """Where the part before the first turn ends: the brief, or what started
+    the work. An earlier compaction is the start of the middle."""
+    for index, stored in enumerate(events):
+        if isinstance(stored.event, (*_MODEL_SIDE, Compaction)):
+            return index
+    return len(events)
+
+
+def _calls(events: Sequence[StoredEvent]) -> list[str]:
+    """The calls made in ``events``, once each, in order, as lines; earlier
+    compactions' lists carried over."""
+    lines: list[str] = []
+    for stored in events:
+        event = stored.event
+        if isinstance(event, Compaction):
+            _, marker, listed = event.summary.partition(
+                "(make one again to see its result):\n"
+            )
+            if marker:
+                lines.extend(listed.splitlines())
+        elif isinstance(event, ToolCall):
+            arguments = json.dumps(event.arguments, ensure_ascii=False)
+            line = f"- {event.tool} {arguments}"
+            if len(line) > LISTED_CALL_CHARS:
+                line = line[: LISTED_CALL_CHARS - 3] + "..."
+            lines.append(line)
+    unique = list(dict.fromkeys(lines))
+    return unique[-MAX_LISTED_CALLS:]

nisse-core/src/nisse_core/models/context.py

@@ -6,8 +6,15 @@ start of the prompt, which is where the system prompt and the plan are. So a
 request is made to fit the model's declared window *before* it is sent, and
 one that cannot be made to fit is never sent.
 
-The log itself is never changed. Fitting works on the events about to be
-rendered, in three steps, stopping at the first that fits:
+The log itself is never changed. Compaction (``compact``) is what keeps a
+long run inside the window: the model's own notes replace the middle of the
+conversation, now and then, in one large step. Fitting is the last guard
+under it, and normally sends everything as it is. When it has to cut, the
+cut is recorded (``Trim``) and logged as ``context.trimmed``: after
+compaction that should be rare, and each one is worth a look.
+
+Fitting works on the events about to be rendered, compactions applied, in
+three steps, stopping at the first that fits:
 
 1. Tool results older than the most recent turns are cut to their first and
    last lines, with a note saying how much was left out.
@@ -39,6 +46,8 @@ from nisse_core.log.canonical import (
     UserMessage,
 )
 from nisse_core.models.llm import DEFAULT_MAX_OUTPUT_TOKENS, LLMError
+from nisse_core.models.render import effective_events
+from nisse_core.oplog import OpLog
 
 # English and code run at about four characters a token. Three is deliberately
 # pessimistic, before any correction from what the server reports.
@@ -129,6 +138,18 @@ class Budget:
         return int(self.window * (1 - self.safety_margin)) - self.max_output
 
 
+@dataclass(frozen=True)
+class Trim:
+    """What fitting cut from one request."""
+
+    step: int  # 1: older results shortened; 2: the oldest events dropped too
+    tokens_before: int
+    tokens_after: int
+    limit: int
+    results_cut: int
+    events_dropped: int
+
+
 def fit(
     events: Sequence[StoredEvent],
     system: str | None,
@@ -138,14 +159,29 @@ def fit(
 ) -> list[StoredEvent]:
     """The events to render: all of them if they fit, otherwise the result of
     the three steps in the module docstring."""
+    return fit_report(events, system, tools, budget, factor)[0]
+
+
+def fit_report(
+    events: Sequence[StoredEvent],
+    system: str | None,
+    tools: list[dict[str, Any]] | None,
+    budget: Budget,
+    factor: float = 1.0,
+) -> tuple[list[StoredEvent], Trim | None]:
+    """``fit``, and what it cut: None when nothing was."""
     limit = budget.for_prompt
 
+    def tokens(candidate: Sequence[StoredEvent]) -> int:
+        return estimate_tokens(candidate, system, tools, factor)
+
     def fits(candidate: Sequence[StoredEvent]) -> bool:
-        return estimate_tokens(candidate, system, tools, factor) <= limit
+        return tokens(candidate) <= limit
 
     kept = list(events)
-    if fits(kept):
-        return kept
+    before = tokens(kept)
+    if before <= limit:
+        return kept, None
 
     starts = _turn_starts(kept)
     recent_from = (
@@ -155,6 +191,13 @@ def fit(
     )
 
     # Step 1: cut older tool results down.
+    results_cut = sum(
+        1
+        for index, stored in enumerate(kept)
+        if index < recent_from
+        and isinstance(stored.event, ToolResult)
+        and len(stored.event.result) > ELIDED_RESULT_CHARS
+    )
     kept = [
         replace(
             stored,
@@ -168,7 +211,7 @@ def fit(
         for index, stored in enumerate(kept)
     ]
     if fits(kept):
-        return kept
+        return kept, Trim(1, before, tokens(kept), limit, results_cut, 0)
 
     # Step 2: drop the oldest events, one turn at a time, never the recent
     # ones. The note keeps the transcript starting with a user message, which
@@ -189,7 +232,10 @@ def fit(
         )
         candidate = [note, *remaining]
         if fits(candidate):
-            return candidate
+            dropped = len(kept) - len(remaining)
+            return candidate, Trim(
+                2, before, tokens(candidate), limit, results_cut, dropped
+            )
 
     # Step 3: nothing more can go.
     needed = estimate_tokens(kept[recent_from:], system, tools, factor)
@@ -216,8 +262,10 @@ class BudgetedClient:
         keep_recent_turns: int = 6,
         safety_margin: float = 0.1,
         enforces_tool_choice: Callable[[str], bool] = lambda model: False,
+        oplog: OpLog | None = None,
     ) -> None:
         self._inner = inner
+        self._oplog = oplog
         self._limits_for = limits_for
         # Whether a model's server holds it to the offered tools when asked
         # (LiteLLM's supports_tool_choice). Asking one that doesn't can be
@@ -231,6 +279,7 @@ class BudgetedClient:
         # from reported usage. Starts at 1 and only grows.
         self._factors: dict[str, float] = {}
         self.trimmed_requests = 0
+        self.last_trim: Trim | None = None  # the last request's, if it was cut
 
     @property
     def last_usage(self) -> dict[str, int]:
@@ -260,20 +309,57 @@ class BudgetedClient:
             safety_margin=self._safety_margin,
         )
 
+    def estimate(
+        self,
+        events: Sequence[StoredEvent],
+        system: str | None,
+        tools: list[dict[str, Any]] | None,
+        model: str,
+    ) -> int:
+        """A request's size in tokens, compactions applied, as fitting
+        would count it."""
+        factor = self._factors.get(model, 1.0)
+        return estimate_tokens(effective_events(list(events)), system, tools, factor)
+
     def complete(
         self,
         events: list[StoredEvent],
         tools: list[dict[str, Any]] | None,
         model: str,
         system: str | None = None,
+        *,
+        require_tool_call: bool | None = None,
     ) -> list[CanonicalEvent]:
+        """``require_tool_call``: None asks for a tool call whenever tools
+        are offered (and the model's server enforces it); False lets the
+        model answer in prose, as compaction's notes do."""
         budget = self.budget_for(model)
         factor = self._factors.get(model, 1.0)
-        fitted = fit(events, system, tools, budget, factor)
-        # Counted so the benchmark can report how often a model's window was
-        # the constraint: any request that had to be cut down or shortened.
-        if fitted != list(events):
+        events = effective_events(list(events))
+        fitted, trim = fit_report(events, system, tools, budget, factor)
+        self.last_trim = trim
+        if trim is not None:
+            # Counted so the benchmark can report how often a model's window
+            # was the constraint, and logged: each cut lost the model
+            # something it had read.
             self.trimmed_requests += 1
+            if self._oplog is not None:
+                self._oplog.emit(
+                    "context.trimmed",
+                    cause=(
+                        "older tool results shortened"
+                        if trim.step == 1
+                        else "the oldest events dropped"
+                    ),
+                    model=model,
+                    tokens_before=trim.tokens_before,
+                    tokens_after=trim.tokens_after,
+                    limit=trim.limit,
+                    results_cut=trim.results_cut,
+                    events_dropped=trim.events_dropped,
+                )
+        if require_tool_call is None:
+            require_tool_call = bool(tools) and self._enforces_tool_choice(model)
         produced = self._inner.complete(
             fitted,
             tools,
@@ -283,7 +369,7 @@ class BudgetedClient:
             # Every caller that offers tools needs one called: the executor
             # finishes with finish, the planner with submit_plan or
             # ask_human, a delegation with hand_back.
-            require_tool_call=bool(tools) and self._enforces_tool_choice(model),
+            require_tool_call=require_tool_call,
         )
         reported = int(self.last_usage.get("input", 0))
         if reported > 0:

nisse-core/src/nisse_core/models/interruptible.py

@@ -35,10 +35,11 @@ class Interruptible:
         tools: list[dict[str, Any]] | None,
         model: str,
         system: str | None = None,
+        **options: Any,
     ) -> list[CanonicalEvent]:
         self._calling = True
         try:
-            return self._client.complete(events, tools, model, system)
+            return self._client.complete(events, tools, model, system, **options)
         finally:
             self._calling = False
 

nisse-core/src/nisse_core/models/render.py

@@ -4,8 +4,7 @@ call time, never stored provider-shaped.
 First adapter: the OpenAI-compatible chat format LiteLLM's normalized route
 speaks — the executor role's path (L9). The Anthropic passthrough adapter
 arrives with delegations (L9). Token budgeting and prompt-cache breakpoints
-are render-time concerns and are never stored (L7); neither exists yet in
-this skeleton.
+are render-time concerns and are never stored (L7).
 """
 
 import json
@@ -27,20 +26,54 @@ from nisse_core.log.canonical import (
 
 
 def effective_events(stored: list[StoredEvent]) -> list[StoredEvent]:
-    """Apply compactions: events whose ids fall in a compaction's replaced
-    range are dropped; the compaction event itself stays as their summary."""
-    replaced: list[tuple[int, int]] = [
-        (e.event.replaces[0], e.event.replaces[1])
-        for e in stored
-        if isinstance(e.event, Compaction)
+    """Apply compactions: the events in a compaction's replaced range give way
+    to the compaction, which takes the place of the first of them, so the
+    summary sits where the conversation it summarises was. A compaction
+    whose range a later one covers is folded into it and not shown. One
+    whose range is no longer in the list (it was applied already) stays
+    where it is, so applying this twice changes nothing."""
+    compactions = [e for e in stored if isinstance(e.event, Compaction)]
+    active = [
+        c
+        for c in compactions
+        if not any(
+            later.id > c.id
+            and later.event.replaces[0] <= c.event.replaces[0]
+            and later.event.replaces[1] >= c.event.replaces[1]
+            for later in compactions
+        )
     ]
 
-    def is_replaced(event_id: int) -> bool:
-        return any(first <= event_id <= last for first, last in replaced)
+    active_ids = {c.id for c in active}
 
-    return [
-        e for e in stored if isinstance(e.event, Compaction) or not is_replaced(e.id)
-    ]
+    def covering(event_id: int) -> StoredEvent | None:
+        for c in active:
+            first, last = c.event.replaces
+            if first <= event_id <= last:
+                return c
+        return None
+
+    present = {e.id for e in stored if not isinstance(e.event, Compaction)}
+    placed = {
+        c.id
+        for c in active
+        if any(c.event.replaces[0] <= i <= c.event.replaces[1] for i in present)
+    }
+    out: list[StoredEvent] = []
+    shown: set[int] = set()
+    for e in stored:
+        if isinstance(e.event, Compaction):
+            if e.id in active_ids and e.id not in placed and e.id not in shown:
+                out.append(e)
+                shown.add(e.id)
+            continue
+        c = covering(e.id)
+        if c is None:
+            out.append(e)
+        elif c.id not in shown:
+            out.append(c)
+            shown.add(c.id)
+    return out
 
 
 class OpenAIChatRenderer:

nisse-core/src/nisse_core/state/store.py

@@ -20,6 +20,7 @@ from typing import Any, Self
 
 from nisse_core.log.canonical import (
     CanonicalEvent,
+    Compaction,
     StoredEvent,
     UserMessage,
     event_type,
@@ -573,9 +574,15 @@ class Transcript:
     def view(self, after: int = 0) -> list[StoredEvent]:
         """The log as this actor is shown it: what a model's context is
         built from (L6). See ``views``."""
-        return project(
-            self.read(max(after, self._start)), self.actor, self._store.SHOWN
-        )
+        start = max(after, self._start)
+        # A compaction of events before the start belongs to an earlier
+        # run's view, not this one's.
+        events = [
+            e
+            for e in self.read(start)
+            if not (isinstance(e.event, Compaction) and e.event.replaces[0] <= start)
+        ]
+        return project(events, self.actor, self._store.SHOWN)
 
     def since(self, event_id: int) -> "Transcript":
         """The same transcript, its view starting after ``event_id``: a run

nisse-core/tests/test_compact.py

@@ -0,0 +1,310 @@
+"""Compaction (L6, L7): a long driver run's middle gives way to the model's
+own notes, in one step now and then, so the run stays inside the window and
+the start of its prompt stays the same between compactions."""
+
+import io
+import json
+from itertools import pairwise
+from pathlib import Path
+from typing import Any
+
+import pytest
+
+from nisse_core.log.canonical import (
+    AssistantText,
+    CanonicalEvent,
+    Compaction,
+    Fact,
+    StoredEvent,
+    ToolCall,
+    ToolResult,
+    UserMessage,
+)
+from nisse_core.loop.driver import Driver, ToolOutcome
+from nisse_core.loop.tools import tool
+from nisse_core.models.compact import CompactionTuning, Compactor
+from nisse_core.models.context import BudgetedClient
+from nisse_core.models.interruptible import Interruptible, Stopped
+from nisse_core.oplog import OpLog
+from nisse_core.state.store import StateStore
+
+READ = tool("read_file", "Read a file.", path="Its path.")
+POST = tool("post_review", "Post the review. Ends your turn.", body="The review.")
+TOOLS = [READ, POST]
+BRIEF = "BRIEF: review PR #1"
+FILE_CHARS = 6000  # about 2000 tokens a read
+
+
+class Model:
+    """Reads one file a turn, then posts; writes notes when asked for them."""
+
+    def __init__(self, reads: int, notes: Any = "NOTES: all fine so far") -> None:
+        self.reads = reads
+        self.notes = notes
+        self.requests: list[dict[str, Any]] = []
+        self.turn = 0
+        self.on_notes: Any = None
+
+    def complete(
+        self,
+        events: list[StoredEvent],
+        tools: Any,
+        model: str,
+        system: str | None = None,
+        *,
+        max_tokens: int | None = None,
+        require_tool_call: bool = False,
+    ) -> list[CanonicalEvent]:
+        asked = _asks_for_notes(events)
+        self.requests.append(
+            {
+                "events": list(events),
+                "tools": tools,
+                "system": system,
+                "require_tool_call": require_tool_call,
+                "notes": asked,
+            }
+        )
+        if asked:
+            if self.on_notes is not None:
+                self.on_notes()
+            notes = self.notes(events) if callable(self.notes) else self.notes
+            return [AssistantText(text=notes, model=model)]
+        self.turn += 1
+        if self.turn > self.reads:
+            return [ToolCall(call_id="c-post", tool="post_review", arguments={})]
+        return [
+            AssistantText(text=f"reading f{self.turn}", model=model),
+            ToolCall(
+                call_id=f"c-{self.turn}",
+                tool="read_file",
+                arguments={"path": f"f{self.turn}.py"},
+            ),
+        ]
+
+    def turns_sent(self) -> list[list[StoredEvent]]:
+        return [r["events"] for r in self.requests if not r["notes"]]
+
+
+def _asks_for_notes(events: list[StoredEvent]) -> bool:
+    last = events[-1].event if events else None
+    return isinstance(last, UserMessage) and last.source == "compaction"
+
+
+class Files:
+    def dispatch(self, name: str, arguments: dict[str, Any]) -> ToolOutcome:
+        path = arguments["path"]
+        return ToolOutcome(f"{path}\n" + "x" * FILE_CHARS, True)
+
+
+class World:
+    def __init__(
+        self,
+        tmp_path: Path,
+        model: Model,
+        *,
+        tuning: CompactionTuning | None = None,
+        interruptible: bool = False,
+    ) -> None:
+        self.stream = io.StringIO()
+        oplog = OpLog("t", self.stream)
+        store = StateStore(tmp_path / "s.db", oplog=OpLog("t", io.StringIO()))
+        self.log = store.transcript("x", "driver")
+        self.log.as_actor("orchestrator").append(Fact(text=BRIEF))
+        self.model = model
+        # A 20k window less the margin and output ceiling: 17,000 tokens for
+        # the prompt, so compaction starts at about 10,200.
+        budgeted = BudgetedClient(
+            model,
+            lambda m: (20_000, None),
+            max_output_tokens=1000,
+            oplog=oplog,
+            enforces_tool_choice=lambda m: True,
+        )
+        self.client: Any = Interruptible(budgeted) if interruptible else budgeted
+        self.driver = Driver(
+            self.client,
+            "m",
+            max_turns=60,
+            compactor=Compactor(self.client, tuning, oplog=oplog),
+        )
+
+    def run(self) -> Any:
+        return self.driver.run(
+            self.log,
+            system="you review",
+            tools=TOOLS,
+            waiting={"post_review"},
+            workspace=Files(),
+        )
+
+    def oplog(self, event: str) -> list[dict[str, Any]]:
+        records = [json.loads(line) for line in self.stream.getvalue().splitlines()]
+        return [r for r in records if r["event"] == event]
+
+    def compactions(self) -> list[Compaction]:
+        return [e.event for e in self.log.read() if isinstance(e.event, Compaction)]
+
+
+def test_a_long_run_is_compacted_keeping_its_brief_and_recent_turns(
+    tmp_path: Path,
+) -> None:
+    world = World(tmp_path, Model(reads=7))
+    assert world.run().kind == "wait"
+
+    [compaction] = world.compactions()
+    [logged] = world.oplog("context.compacted")
+    assert logged["tokens_after"] < logged["tokens_before"]
+    assert logged["work_item"] == "x"
+    assert world.oplog("context.trimmed") == []  # fitting never had to cut
+
+    last = world.model.turns_sent()[-1]
+    # The brief first, word for word; then the notes; then the recent turns.
+    assert last[0].event.text == BRIEF
+    assert isinstance(last[1].event, Compaction)
+    assert last[1].event.summary.startswith("NOTES: all fine so far")
+    assert any(
+        isinstance(e.event, ToolResult) and e.event.result.startswith("f7.py")
+        for e in last
+    )
+    assert not any(
+        isinstance(e.event, ToolResult) and e.event.result.startswith("f1.py")
+        for e in last
+    )
+    # The turn just before the compaction is still there, word for word.
+    sent = world.model.turns_sent()
+    after = next(
+        i for i, r in enumerate(sent) if any(isinstance(e.event, Compaction) for e in r)
+    )
+    latest = [e for e in sent[after - 1] if isinstance(e.event, ToolResult)][-1]
+    assert latest in sent[after]
+    # The calls it replaced are listed by code, so the model can make them again.
+    assert '- read_file {"path": "f1.py"}' in compaction.summary
+
+
+def test_the_notes_are_asked_for_over_the_runs_own_request(tmp_path: Path) -> None:
+    world = World(tmp_path, Model(reads=8))
+    world.run()
+    requests = world.model.requests
+    asked = next(i for i, r in enumerate(requests) if r["notes"])
+    before, notes = requests[asked - 1], requests[asked]
+    # Same system prompt and tools, and the last request plus the model's
+    # reply and its result before it: only the request for notes is new,
+    # so the server reuses its cache.
+    assert notes["system"] == before["system"]
+    assert notes["tools"] == before["tools"]
+    assert before["require_tool_call"] is True
+    assert notes["require_tool_call"] is False
+    ids = [e.id for e in notes["events"][:-1]]
+    assert ids[: len(before["events"])] == [e.id for e in before["events"]]
+
+
+def test_the_prompt_start_stays_the_same_between_compactions(tmp_path: Path) -> None:
+    world = World(tmp_path, Model(reads=20))
+    world.run()
+    assert len(world.compactions()) >= 2
+    sent = world.model.turns_sent()
+    unchanged = 0
+    for earlier, later in pairwise(sent):
+        compacted = any(isinstance(e.event, Compaction) for e in later) and not any(
+            isinstance(e.event, Compaction) and e.event == c.event
+            for e in later
+            for c in earlier
+            if isinstance(c.event, Compaction)
+        )
+        if compacted:
+            continue
+        # Between compactions, each request extends the one before it.
+        assert [e.id for e in later[: len(earlier)]] == [e.id for e in earlier]
+        unchanged += 1
+    assert unchanged > len(sent) // 2
+
+
+def test_a_second_compaction_folds_in_the_first(tmp_path: Path) -> None:
+    world = World(tmp_path, Model(reads=20))
+    world.run()
+    first, second, *_ = world.compactions()
+    assert second.replaces[0] == first.replaces[0]
+    assert second.replaces[1] > first.replaces[1]
+    # The first one's list of calls is carried into the second.
+    assert '- read_file {"path": "f1.py"}' in second.summary
+    last = world.model.turns_sent()[-1]
+    assert sum(isinstance(e.event, Compaction) for e in last) == 1
+    assert last[0].event.text == BRIEF
+
+
+def test_tool_calls_are_never_parted_from_their_results(tmp_path: Path) -> None:
+    world = World(tmp_path, Model(reads=20))
+    world.run()
+    for sent in world.model.turns_sent():
+        calls = {e.event.call_id for e in sent if isinstance(e.event, ToolCall)}
+        answered = {e.event.call_id for e in sent if isinstance(e.event, ToolResult)}
+        assert answered <= calls
+
+
+def test_a_short_run_is_never_compacted(tmp_path: Path) -> None:
+    world = World(tmp_path, Model(reads=2))
+    world.run()
+    assert world.compactions() == []
+    assert not any(r["notes"] for r in world.model.requests)
+
+
+def test_empty_notes_fail_without_failing_the_run(tmp_path: Path) -> None:
+    world = World(tmp_path, Model(reads=8, notes=""))
+    assert world.run().kind == "wait"
+    assert world.compactions() == []
+    failed = world.oplog("context.compaction_failed")
+    assert failed and failed[0]["cause"] == "the notes were empty"
+    # Not tried again every turn: only after keep_turns more.
+    asked = [i for i, r in enumerate(world.model.requests) if r["notes"]]
+    assert all(b - a > 3 for a, b in pairwise(asked))
+
+
+def test_with_no_compaction_fitting_cuts_and_says_so(tmp_path: Path) -> None:
+    world = World(tmp_path, Model(reads=12, notes=""))
+    world.run()
+    [first, *_] = world.oplog("context.trimmed")
+    assert first["results_cut"] > 0
+    assert first["tokens_after"] <= first["limit"] < first["tokens_before"]
+
+
+def test_notes_that_leave_it_too_long_are_not_kept(tmp_path: Path) -> None:
+    world = World(tmp_path, Model(reads=8, notes="n" * 40_000))
+    world.run()
+    assert world.compactions() == []
+    [failed, *_] = world.oplog("context.compaction_failed")
+    assert "would still be" in failed["cause"]
+
+
+def test_a_stop_while_writing_notes_breaks_off_cleanly(tmp_path: Path) -> None:
+    model = Model(reads=8)
+    world = World(tmp_path, model, interruptible=True)
+    model.on_notes = world.client.interrupt
+    with pytest.raises(Stopped):
+        world.run()
+    assert world.compactions() == []
+
+
+def test_compact_at_zero_turns_it_off(tmp_path: Path) -> None:
+    world = World(tmp_path, Model(reads=10), tuning=CompactionTuning(compact_at=0))
+    world.run()
+    assert world.compactions() == []
+    assert world.oplog("context.trimmed")
+
+
+def test_a_view_from_a_start_hides_compactions_of_what_came_before(
+    tmp_path: Path,
+) -> None:
+    world = World(tmp_path, Model(reads=0))
+    log = world.log
+    log.as_actor("orchestrator").append(Fact(text="old work"))
+    start = log.read()[-1].id
+    log.as_actor("orchestrator").append(Fact(text="BRIEF again"))
+    log.append(Compaction(summary="stale", model="m", replaces=[1, start]))
+    log.append(
+        Compaction(summary="this run's", model="m", replaces=[start + 1, start + 1])
+    )
+    shown = log.since(start).view()
+    assert [e.event.summary for e in shown if isinstance(e.event, Compaction)] == [
+        "this run's"
+    ]

nisse-core/tests/test_context.py

@@ -9,6 +9,7 @@ import pytest
 from nisse_core.log.canonical import (
     AssistantText,
     CanonicalEvent,
+    Compaction,
     StoredEvent,
     ToolCall,
     ToolResult,
@@ -189,6 +190,46 @@ def test_reported_usage_only_ever_raises_the_estimate() -> None:
     assert under_then_over._factors["m"] == 2.0  # never loosened
 
 
+def test_a_request_that_fits_is_sent_whole_and_nothing_is_logged() -> None:
+    stream = io.StringIO()
+    client = BudgetedClient(
+        RecordingClient(), lambda m: (100_000, None), oplog=OpLog("t", stream)
+    )
+    events = transcript(3, 100)
+    client.complete(events, None, "m")
+    assert client.last_trim is None
+    assert stream.getvalue() == ""
+
+
+def test_a_cut_is_recorded_and_logged() -> None:
+    stream = io.StringIO()
+    client = BudgetedClient(
+        RecordingClient(),
+        lambda m: (4000, 500),
+        keep_recent_turns=2,
+        oplog=OpLog("t", stream),
+    )
+    client.complete(transcript(20, 3000), None, "m", system="system")
+    assert client.last_trim is not None and client.last_trim.step == 2
+    assert '"event": "context.trimmed"' in stream.getvalue()
+
+
+def test_a_compaction_counts_for_what_it_replaced() -> None:
+    events = transcript(20, 3000)
+    last = events[-1].id
+    compaction = StoredEvent(
+        id=last + 1,
+        ts="t",
+        event=Compaction(summary="notes", model="m", replaces=[2, last - 4]),
+    )
+    inner = RecordingClient()
+    client = BudgetedClient(inner, lambda m: (8000, 500), keep_recent_turns=2)
+    client.complete([*events, compaction], None, "m")
+    assert client.last_trim is None  # fits once the summary stands in
+    sent = inner.calls[0]["events"]
+    assert isinstance(sent[1].event, Compaction)
+
+
 def test_last_usage_passes_through() -> None:
     client = BudgetedClient(RecordingClient(reported_input=7), lambda m: (100, None))
     assert client.last_usage["input"] == 7

nisse-core/tests/test_render.py

@@ -66,11 +66,25 @@ def test_compaction_replaces_its_range_only() -> None:
         )
     )
     remaining = effective_events(events)
-    assert [e.id for e in remaining] == [3, 4]
+    # The summary takes the place of what it replaces.
+    assert [e.id for e in remaining] == [4, 3]
+    assert effective_events(remaining) == remaining  # applying again: no change
     body = OpenAIChatRenderer().render(events, tools=None, model="q")
     contents = [m["content"] for m in body["messages"]]
     # Both render as user messages, so they share one: roles must alternate.
-    assert contents == ["kept\n\n[summary of earlier conversation]\nthe old stuff"]
+    assert contents == ["[summary of earlier conversation]\nthe old stuff\n\nkept"]
+
+
+def test_a_later_compaction_folds_in_an_earlier_one() -> None:
+    events = stored([UserMessage(text=f"e{i}", source="m") for i in range(1, 7)])
+    events.append(
+        StoredEvent(id=7, ts="t", event=Compaction("first", "q", replaces=[2, 3]))
+    )
+    events.append(
+        StoredEvent(id=8, ts="t", event=Compaction("second", "q", replaces=[2, 5]))
+    )
+    remaining = effective_events(events)
+    assert [e.id for e in remaining] == [1, 8, 6]
 
 
 def test_tool_call_without_a_result_gets_a_placeholder() -> None:

nisse-dev/src/nisse_dev/bench/runner.py

@@ -22,6 +22,7 @@ from nisse_core.log.canonical import (
 )
 from nisse_core.loop.driver import Driver, RunOutcome
 from nisse_core.models.catalog import ModelFacts
+from nisse_core.models.compact import Compactor
 from nisse_core.oplog import OpLog
 from nisse_dev.bench.tasks import Task
 from nisse_dev.config import Tuning
@@ -78,10 +79,13 @@ class MeteringClient:
         tools: list[dict[str, Any]] | None,
         model: str,
         system: str | None = None,
+        **options: Any,
     ) -> list[CanonicalEvent]:
         self.calls += 1
         try:
-            produced = self._inner.complete(events, tools, model, system=system)
+            produced = self._inner.complete(
+                events, tools, model, system=system, **options
+            )
         finally:
             # Counted even when the call fails: a rate limit that never
             # cleared still cost the run its wait.
@@ -95,10 +99,16 @@ class MeteringClient:
         answered = getattr(self._inner, "last_model", None)
         if not self._facts.answered(answered):
             self.fallbacks.append(str(answered))
-        if not any(isinstance(e, ToolCall) for e in produced):
+        # Compaction's notes are prose by request, not a broken turn.
+        asked_for_prose = options.get("require_tool_call") is False
+        if not asked_for_prose and not any(isinstance(e, ToolCall) for e in produced):
             self.prose_turns += 1
         return produced
 
+    def __getattr__(self, name: str) -> Any:
+        # The budget (budget_for, estimate) compaction reads.
+        return getattr(self._inner, name)
+
 
 @dataclass
 class RunRecord:
@@ -222,6 +232,8 @@ def run_task(
             model,
             max_turns=tuning.driver.max_turns,
             failure_limit=tuning.driver.failure_limit,
+            # As the agent runs it, so a long task measures the same thing.
+            compactor=Compactor(meter, tuning.context.compaction()),
         )
         system = SYSTEM.format(
             repo=f"bench/{task.name}",

nisse-dev/src/nisse_dev/config.py

@@ -34,6 +34,7 @@ from nisse_core.config import (
     resolve,
 )
 from nisse_core.conversation.matrix import MatrixConfig
+from nisse_core.models.compact import CompactionTuning, check_tuning
 from nisse_core.models.llm import (
     DEFAULT_MAX_OUTPUT_TOKENS,
     DEFAULT_REQUEST_TIMEOUT_S,
@@ -134,6 +135,19 @@ class ToolsTuning:
 class ContextTuning:
     keep_recent_turns: int = 6
     safety_margin: float = 0.1
+    # Compaction (L6): over compact_at of the prompt budget, the model's
+    # notes replace the middle of the run, keeping at most compact_keep_turns
+    # recent turns, in compact_to of it. compact_at 0: never.
+    compact_at: float = field(default=0.6, metadata={"zero": True})
+    compact_to: float = 0.25
+    compact_keep_turns: int = 3
+
+    def compaction(self) -> CompactionTuning:
+        return CompactionTuning(
+            compact_at=self.compact_at,
+            compact_to=self.compact_to,
+            keep_turns=self.compact_keep_turns,
+        )
 
 
 @dataclass(frozen=True)
@@ -182,6 +196,7 @@ def _parse_tuning(raw: Any, errors: list[str]) -> Tuning:
     )
     if tuning.context.safety_margin >= 1:
         errors.append("tuning.context.safety_margin: must be less than 1")
+    check_tuning(tuning.context.compaction(), "tuning.context", errors)
     return tuning
 
 

nisse-dev/src/nisse_dev/loop/build.py

@@ -15,6 +15,7 @@ from nisse_core.knowledge.memory import Memory
 from nisse_core.knowledge.vault import Vault
 from nisse_core.loop.driver import Driver
 from nisse_core.models.catalog import ModelCatalog, select_client
+from nisse_core.models.compact import Compactor
 from nisse_core.models.context import BudgetedClient
 from nisse_core.models.llm import AnthropicPassthroughClient, LiteLLMClient
 from nisse_core.oplog import OpLog
@@ -110,7 +111,7 @@ class RunningLoop:
 
 
 def make_llm_clients(
-    config: AgentConfig, catalog: ModelCatalog
+    config: AgentConfig, catalog: ModelCatalog, oplog: OpLog | None = None
 ) -> tuple[BudgetedClient, BudgetedClient]:
     """The two LLM routes, as every model call in the agent uses them.
 
@@ -136,6 +137,7 @@ def make_llm_clients(
             enforces_tool_choice=lambda m: (
                 catalog.facts(m).supports_tool_choice is True
             ),
+            oplog=oplog,  # a cut that fitting has to make is logged
         )
 
     normalized = budgeted(
@@ -276,7 +278,7 @@ def build_loop_agent(
         project_runtime(config, entry, store, gitea, account)
         for entry in config.projects
     ]
-    normalized, passthrough = make_llm_clients(config, catalog)
+    normalized, passthrough = make_llm_clients(config, catalog, oplog)
     cancel = Cancel()
     # The configured driver; each work item runs on the one it pinned (L9).
     driver = Driver(
@@ -285,6 +287,9 @@ def build_loop_agent(
         max_turns=config.tuning.driver.max_turns,
         cancel=cancel,
         failure_limit=config.tuning.driver.failure_limit,
+        compactor=Compactor(
+            normalized, config.tuning.context.compaction(), oplog=oplog
+        ),
     )
     tuning = config.tuning
     helpers = Helpers(

nisse-dev/tests/test_config.py

@@ -354,6 +354,18 @@ def test_context_tuning_is_read_and_checked() -> None:
         build(tuning={"context": {"safety_margin": 1}})
 
 
+def test_compaction_tuning_is_read_and_checked() -> None:
+    compaction = build().tuning.context.compaction()
+    assert (compaction.compact_at, compaction.compact_to) == (0.6, 0.25)
+    assert compaction.keep_turns == 3
+    off = build(tuning={"context": {"compact_at": 0}}).tuning.context
+    assert off.compaction().compact_at == 0
+    with pytest.raises(ConfigError, match="compact_to must be less than compact_at"):
+        build(tuning={"context": {"compact_at": 0.3, "compact_to": 0.5}})
+    with pytest.raises(ConfigError, match="compact_to must be less than compact_at"):
+        build(tuning={"context": {"compact_at": 1.5}})
+
+
 def test_the_build_host_is_required_and_defaults_to_root_on_22() -> None:
     host = only(build()).build_host
     assert (host.address, host.user) == ("build.test", "root")

nisse-review/src/nisse_review/build.py

@@ -10,6 +10,7 @@ from nisse_core.knowledge.vault import Vault
 from nisse_core.loop.driver import Driver
 from nisse_core.loop.expert import ExpertDesk
 from nisse_core.models.catalog import ModelCatalog
+from nisse_core.models.compact import Compactor
 from nisse_core.models.context import BudgetedClient
 from nisse_core.models.interruptible import Interruptible
 from nisse_core.models.llm import LiteLLMClient
@@ -65,7 +66,7 @@ def check_access(
     return account, repos
 
 
-def llm_client(config: ReviewConfig) -> BudgetedClient:
+def llm_client(config: ReviewConfig, oplog: OpLog | None = None) -> BudgetedClient:
     """The one route to the models, every request fitted to its window
     (L6), against what LiteLLM says the configured models are (L9)."""
     catalog = ModelCatalog.discover(config.llm_base_url, config.llm_token)
@@ -92,6 +93,7 @@ def llm_client(config: ReviewConfig) -> BudgetedClient:
         keep_recent_turns=tuning.keep_recent_turns,
         safety_margin=tuning.safety_margin,
         enforces_tool_choice=lambda m: catalog.facts(m).supports_tool_choice is True,
+        oplog=oplog,  # a cut that fitting has to make is logged
     )
 
 
@@ -106,7 +108,7 @@ def build(
     gitea = gitea or GiteaClient(config.gitea_url, config.gitea_token)
     account, repos = check_access(gitea, config.repositories, oplog)
     # Every model call, the reviewer's and ask_expert's, can be broken off.
-    model = Interruptible(client if client is not None else llm_client(config))  # type: ignore[arg-type]
+    model = Interruptible(client if client is not None else llm_client(config, oplog))  # type: ignore[arg-type]
     config.state_db.parent.mkdir(parents=True, exist_ok=True)
     store = StateStore(config.state_db, oplog=oplog)
     vault = (
@@ -129,7 +131,12 @@ def build(
     reviewer = Reviewer(
         store,
         gitea,
-        Driver(model, config.roles.resolve("driver"), cancel=cancel),  # type: ignore[arg-type]
+        Driver(
+            model,  # type: ignore[arg-type]
+            config.roles.resolve("driver"),
+            cancel=cancel,
+            compactor=Compactor(model, tuning.context.compaction(), oplog=oplog),
+        ),
         account=account,
         gitea_url=config.gitea_url,
         oplog=oplog,

nisse-review/src/nisse_review/config.py

@@ -22,6 +22,7 @@ from nisse_core.config import (
     read_file,
     resolve,
 )
+from nisse_core.models.compact import CompactionTuning, check_tuning
 from nisse_core.models.llm import (
     DEFAULT_MAX_OUTPUT_TOKENS,
     DEFAULT_REQUEST_TIMEOUT_S,
@@ -72,6 +73,19 @@ class ExpertTuning:
 class ContextTuning:
     keep_recent_turns: int = 6
     safety_margin: float = 0.1
+    # Compaction (L6): over compact_at of the prompt budget, the model's
+    # notes replace the middle of the run, keeping at most compact_keep_turns
+    # recent turns, in compact_to of it. compact_at 0: never.
+    compact_at: float = field(default=0.6, metadata={"zero": True})
+    compact_to: float = 0.25
+    compact_keep_turns: int = 3
+
+    def compaction(self) -> CompactionTuning:
+        return CompactionTuning(
+            compact_at=self.compact_at,
+            compact_to=self.compact_to,
+            keep_turns=self.compact_keep_turns,
+        )
 
 
 @dataclass(frozen=True)
@@ -118,6 +132,7 @@ class ReviewConfig:
         tuning = parse_tuning(tree.get("tuning"), Tuning, errors)
         if tuning.context.safety_margin >= 1:
             errors.append("tuning.context.safety_margin: must be less than 1")
+        check_tuning(tuning.context.compaction(), "tuning.context", errors)
         vault = parse_vault(tree.get("vault"), errors)
         flat = flatten({k: v for k, v in tree.items() if k != "vault"})
         flat.pop("tuning", None)

nisse-review/tests/test_review.py

@@ -494,6 +494,30 @@ def test_the_ci_waits_may_be_zero(tmp_path: Path) -> None:
     assert (review.ci_wait_s, review.ci_grace_s) == (0, 0)
 
 
+def test_compaction_is_tuned_in_the_config(tmp_path: Path) -> None:
+    from nisse_core.config import ConfigError
+    from nisse_review.config import ReviewConfig
+
+    tree: dict[str, Any] = {
+        "state_db": str(tmp_path / "s.db"),
+        "llm": {"base_url": "http://llm", "token": "k"},
+        "roles": {"reviewer": "local", "expert": "frontier"},
+        "gitea": {"url": "https://g", "token": "t", "operators": ["don"]},
+    }
+    assert (
+        ReviewConfig.from_tree(tree, {}).tuning.context.compaction().compact_at == 0.6
+    )
+    tuned = {
+        **tree,
+        "tuning": {"context": {"compact_at": 0.7, "compact_keep_turns": 2}},
+    }
+    compaction = ReviewConfig.from_tree(tuned, {}).tuning.context.compaction()
+    assert (compaction.compact_at, compaction.keep_turns) == (0.7, 2)
+    wrong = {**tree, "tuning": {"context": {"compact_at": 0.2, "compact_to": 0.3}}}
+    with pytest.raises(ConfigError, match="compact_to must be less than compact_at"):
+        ReviewConfig.from_tree(wrong, {})
+
+
 def test_diff_lines_are_the_heads_lines_a_diff_shows() -> None:
     diff = (
         "--- a/x.py\n+++ b/x.py\n@@ -1,3 +1,4 @@\n a\n-b\n+c\n+d\n e\n"

nisse-review/tests/test_review_stop.py

@@ -163,6 +163,8 @@ def test_build_wires_a_stop_to_every_model_call(tmp_path: Path) -> None:
     try:
         driver = built.scheduler._reviewer._driver
         assert driver._client is built.model
+        # Compaction's notes are a model call a stop breaks off too.
+        assert driver._compactor._client is built.model
         assert built.scheduler._reviewer._expert._client is built.model
         built.stop()  # no call in flight: nothing raised
         assert driver._cancel.requested and built.scheduler._stop.is_set()