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dongarandClaude Opus 5.5 cb638fe687
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Compaction: the model's notes replace the middle of a long run (#158)
Before each driver call, over compact_at (0.6) of the prompt budget, the
same model is asked for notes over the very request it was about to get,
plus one message, so the server's cache covers all but the notes. The notes,
with code's list of the calls they replace, become a compaction event that
renders in place of its range, keeping word for word what started the work
and the last few turns. Rare, large steps keep the prompt's start unchanged
between them. A later compaction folds in the earlier; one from an earlier
run's view is hidden.

Failed notes are logged and fitting takes over. Fitting now applies
compactions before it measures, records what it cuts (Trim) and logs each
cut as context.trimmed. Wired into both agents' drivers and the benchmark;
nisse-dev's helper loop is a follow-up.

Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01J5Utyfzw7gF7UhjRDEtjTk
2026-10-17 22:51:36 +00:00

166 lines
6.3 KiB
Python

import json
from itertools import pairwise
from nisse_core.log.canonical import (
AssistantText,
Compaction,
GateOpened,
StoredEvent,
ToolCall,
ToolResult,
UserMessage,
)
from nisse_core.models.render import OpenAIChatRenderer, effective_events
def stored(events: list) -> list[StoredEvent]:
return [StoredEvent(id=i + 1, ts="t", event=e) for i, e in enumerate(events)]
def test_renders_mixed_transcript_in_order() -> None:
events = stored(
[
UserMessage(text="run the tests", source="m:1"),
ToolCall(call_id="call-9", tool="run_tests", arguments={"path": "x"}),
ToolResult(call_id="call-9", result="1 passed", success=True),
AssistantText(text="all green", model="local/qwen"),
]
)
body = OpenAIChatRenderer().render(events, tools=None, model="local/qwen")
assert body["model"] == "local/qwen"
roles = [m["role"] for m in body["messages"]]
assert roles == ["user", "assistant", "tool", "assistant"]
call = body["messages"][1]["tool_calls"][0]
assert call["id"] == "call-9"
assert call["function"]["name"] == "run_tests"
assert json.loads(call["function"]["arguments"]) == {"path": "x"}
assert body["messages"][2]["tool_call_id"] == "call-9"
assert "tools" not in body
def test_system_prompt_and_tools_pass_through() -> None:
tools = [{"type": "function", "function": {"name": "run_tests"}}]
body = OpenAIChatRenderer().render(
stored([UserMessage(text="hi", source="m:1")]),
tools=tools,
model="local/qwen",
system="you are nisse-dev",
)
assert body["messages"][0] == {"role": "system", "content": "you are nisse-dev"}
assert body["tools"] == tools
def test_compaction_replaces_its_range_only() -> None:
events = stored(
[
UserMessage(text="old-1", source="m:1"),
AssistantText(text="old-2", model="q"),
UserMessage(text="kept", source="m:3"),
]
)
events.append(
StoredEvent(
id=4,
ts="t",
event=Compaction(summary="the old stuff", model="q", replaces=[1, 2]),
)
)
remaining = effective_events(events)
# 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 == ["[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:
# Providers reject a dangling tool_use; this happens after a crash (L8)
# or with turn-ending gate tools like submit_plan.
events = stored(
[
UserMessage(text="go", source="m:1"),
ToolCall(call_id="call-x", tool="submit_plan", arguments={}),
]
)
body = OpenAIChatRenderer().render(events, tools=None, model="q")
assert [m["role"] for m in body["messages"]] == ["user", "assistant", "tool"]
assert body["messages"][2]["tool_call_id"] == "call-x"
assert body["messages"][2]["content"] == "[no result recorded]"
def test_answered_tool_call_gets_no_placeholder() -> None:
events = stored(
[
ToolCall(call_id="call-x", tool="run_command", arguments={}),
ToolResult(call_id="call-x", result="ok", success=True),
]
)
body = OpenAIChatRenderer().render(events, tools=None, model="q")
assert [m["role"] for m in body["messages"]] == ["assistant", "tool"]
assert body["messages"][1]["content"] == "ok"
def test_gate_event_renders_as_context() -> None:
events = stored([GateOpened(gate="arch", reason="plan submitted (rev-1)")])
body = OpenAIChatRenderer().render(events, tools=None, model="q")
assert body["messages"][0]["role"] == "user"
assert "arch" in body["messages"][0]["content"]
def _roles(body: dict) -> list[str]:
return [m["role"] for m in body["messages"]]
def test_one_turn_is_one_assistant_message() -> None:
# Text and two parallel tool calls from one model turn: the OpenAI format
# carries them as a single assistant message with a tool_calls list.
events = stored(
[
UserMessage(text="go", source="m:1"),
AssistantText(text="Looking around first.", model="q"),
ToolCall(call_id="a", tool="list_dir", arguments={"path": "."}),
ToolCall(call_id="b", tool="read_file", arguments={"path": "README.md"}),
ToolResult(call_id="a", result="README.md", success=True),
ToolResult(call_id="b", result="hello", success=True),
]
)
body = OpenAIChatRenderer().render(events, tools=None, model="q")
assert _roles(body) == ["user", "assistant", "tool", "tool"]
turn = body["messages"][1]
assert turn["content"] == "Looking around first."
assert [c["id"] for c in turn["tool_calls"]] == ["a", "b"]
def test_roles_never_repeat_for_strict_templates() -> None:
"""Mistral's chat template raises on two user or two assistant messages
in a row; every mix of events must render without one."""
events = stored(
[
UserMessage(text="one", source="m:1"),
UserMessage(text="two", source="m:2"),
AssistantText(text="thinking", model="q"),
ToolCall(call_id="a", tool="list_dir", arguments={}),
ToolResult(call_id="a", result="x", success=True),
AssistantText(text="more", model="q"),
AssistantText(text="and more", model="q"),
ToolCall(call_id="b", tool="finish", arguments={}),
]
)
roles = _roles(OpenAIChatRenderer().render(events, tools=None, model="q"))
for first, second in pairwise(roles):
assert not (first == second and first in ("user", "assistant")), roles