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Unparseable (_raw) args now get a truthful error: cut-off-by-output-limit says 'smaller pieces', bad JSON says 're-send with declared parameters'. Raw junk is shrunk before entering history so replays can't teach the model the _raw shape. Anthropic default max_tokens 16k -> 32k so typical report files fit outright.
111 lines
4.4 KiB
Python
111 lines
4.4 KiB
Python
"""Mangled tool calls (`{"_raw": …}` fallback args) get a real diagnosis, not execution.
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The field failure (2026-08-15, report-page generation): a large write_file call blew the
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output-token limit, the truncated JSON became `{"_raw": …}`, and the tool's bare
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parameter error sent the model into a "wrong parameter" retry loop. Worse, each stored
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`_raw` call read as a worked example — after a few, the model began emitting `_raw` as
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if it were a real parameter, and every replay re-sent thousands of junk tokens.
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"""
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from __future__ import annotations
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import json
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import pytest
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from coworker.engine import EventType, TurnEngine, _MANGLED_PREVIEW_CHARS
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from coworker.permissions import Mode, PermissionEngine
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from coworker.providers import AssistantTurn, ModelCapabilities, ProviderClient, ToolCall
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from coworker.tools import ToolRegistry
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class MangledProvider(ProviderClient):
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"""One turn with unparseable write_file args, then a plain reply."""
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def __init__(self, finish_reason: str, raw: str = "x" * 5000):
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self.calls = 0
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self.finish_reason = finish_reason
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self.raw = raw
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def complete(self, *, model, messages, tools=None, **settings):
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self.calls += 1
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if self.calls == 1:
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return AssistantTurn(
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text="",
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tool_calls=[
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ToolCall(id="t1", name="write_file", arguments={"_raw": self.raw})
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],
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finish_reason=self.finish_reason,
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)
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return AssistantTurn(text="done", tool_calls=[])
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def capabilities(self, model):
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return ModelCapabilities(tools=True)
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def _engine(tmp_path, provider) -> TurnEngine:
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return TurnEngine(
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provider=provider,
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registry=ToolRegistry(),
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permissions=PermissionEngine(workspace_root=tmp_path, mode=Mode.INTERACTIVE),
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model="m",
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)
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async def _run(engine) -> list:
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return [e async for e in engine.run("build the report")]
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def _last_tool_message(engine) -> str:
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return str([m for m in engine.messages if m.get("role") == "tool"][-1]["content"])
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@pytest.mark.asyncio
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async def test_truncated_call_is_answered_with_the_truncation_diagnosis(tmp_path):
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"""finish_reason "length" + unparseable args = the call was cut off. The model's cure
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is smaller pieces — the error must say so instead of a bare parameter complaint."""
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engine = _engine(tmp_path, MangledProvider("length"))
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events = await _run(engine)
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finished = [e for e in events if e.type is EventType.TOOL_FINISHED]
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assert finished[0].data["status"] == "error"
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body = _last_tool_message(engine)
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assert "output-token limit" in body
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assert "smaller pieces" in body
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# The turn continues — no retry loop, the model answers after the diagnosis.
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assert [e for e in events if e.type is EventType.TURN_END]
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@pytest.mark.asyncio
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async def test_plain_bad_json_is_answered_with_the_parameter_diagnosis(tmp_path):
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"""No truncation → the model wrote bad JSON (or imitated `_raw`). Tell it `_raw` is
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not a parameter and to re-issue with the declared ones."""
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engine = _engine(tmp_path, MangledProvider("stop"))
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await _run(engine)
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body = _last_tool_message(engine)
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assert "_raw" in body and "not a parameter" in body
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assert "declared parameters" in body
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@pytest.mark.asyncio
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async def test_raw_junk_is_shrunk_before_it_enters_history(tmp_path):
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"""The unparsed text must not be replayed at full size: it costs tokens every turn
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and teaches the model that `_raw` is a shape to imitate."""
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engine = _engine(tmp_path, MangledProvider("length", raw="y" * 5000))
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await _run(engine)
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assistant = [m for m in engine.messages if m.get("role") == "assistant" and m.get("tool_calls")][0]
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stored = json.loads(assistant["tool_calls"][0]["function"]["arguments"])
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assert len(stored["_raw"]) < _MANGLED_PREVIEW_CHARS + 100
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assert "truncated in history" in stored["_raw"]
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@pytest.mark.asyncio
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async def test_short_raw_args_are_kept_verbatim(tmp_path):
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"""Below the preview cap there is nothing to shrink — storage stays faithful."""
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engine = _engine(tmp_path, MangledProvider("stop", raw='{"path": "repo'))
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await _run(engine)
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assistant = [m for m in engine.messages if m.get("role") == "assistant" and m.get("tool_calls")][0]
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stored = json.loads(assistant["tool_calls"][0]["function"]["arguments"])
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assert stored == {"_raw": '{"path": "repo'}
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