0ef5fcb1c5
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342 lines
14 KiB
Python
342 lines
14 KiB
Python
"""Compression safety rails (issue #847).
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Three rails, each of which only ever makes compression LESS aggressive:
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1. Error-output protection — failed tool calls / error outputs pass
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through ``ContentRouter`` verbatim (string path and content-block path,
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including Anthropic ``is_error: true``), capped by
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``error_protection_max_chars`` so big error-laden logs still reach
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``LogCompressor`` (which preserves error lines).
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2. Pipeline circuit breaker — after N consecutive pipeline failures,
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``TransformPipeline.apply`` passes messages through untouched for a
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cooldown window instead of re-running failing transforms.
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3. Library inflation guard — ``headroom.compress()`` reverts to the
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original messages when "optimization" inflated tokens, mirroring the
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proxy handlers.
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"""
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from __future__ import annotations
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import importlib
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import time
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from typing import Any
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import pytest
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from headroom import OpenAIProvider, Tokenizer
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from headroom.compress import compress
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from headroom.config import HeadroomConfig, TransformResult
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from headroom.tokenizer import Tokenizer as TokenizerType
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from headroom.transforms.base import Transform
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from headroom.transforms.content_router import ContentRouter, ContentRouterConfig
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from headroom.transforms.pipeline import TransformPipeline
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# ``headroom.compress`` the submodule is shadowed by the function of the
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# same name re-exported in ``headroom/__init__.py``.
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compress_module = importlib.import_module("headroom.compress")
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_provider = OpenAIProvider()
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@pytest.fixture
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def tokenizer() -> Tokenizer:
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return Tokenizer(_provider.get_token_counter("gpt-4o"), "gpt-4o")
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# A realistic failed-tool-call output: error indicators, > min_tokens (50),
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# well under the 8000-char protection cap.
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_TRACEBACK = (
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"Traceback (most recent call last):\n"
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+ "".join(
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f' File "/app/services/worker_{i}.py", line {i * 17}, in handle_request\n'
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f" result = downstream.dispatch(payload, retries={i})\n"
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for i in range(12)
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)
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+ "ValueError: connection refused while dispatching payload to upstream "
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"service after 3 retries; check that the worker pool is initialized "
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"before the scheduler starts accepting jobs\n"
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)
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# Error text with no error-indicator keywords — only the explicit
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# Anthropic ``is_error`` flag marks it as a failure.
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_NEUTRAL_TOOL_OUTPUT = (
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"The operation finished without producing the expected artifact. "
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"Output directory listing follows.\n"
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+ "\n".join(f"entry_{i}.txt 4096 bytes" for i in range(80))
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)
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# Benign outputs that merely MENTION errors — exactly one distinct
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# indicator keyword ("error"). A lax substring gate would exempt these
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# from compression (savings regression); the strong gate must not.
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_BENIGN_GREP_OUTPUT = (
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"src/error_handler.py:12:def handle_error(code):\n"
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"src/error_handler.py:48: log_error(code, context)\n"
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+ "\n".join(
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f"src/module_{i}.py:{i * 3}: error_count = metrics.get('error', 0)" for i in range(20)
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)
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)
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_BENIGN_JSON_OUTPUT = (
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'{"status": "completed", "errors": [], "warnings": [], "items": ['
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+ ", ".join(f'{{"id": {i}, "name": "artifact_{i}", "size": {i * 1024}}}' for i in range(30))
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+ "]}"
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)
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def _filler_messages(n: int = 2) -> list[dict[str, Any]]:
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return [{"role": "user", "content": f"step {i}: please continue the task"} for i in range(n)]
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class TestErrorOutputProtection:
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def test_string_tool_message_with_error_protected(self, tokenizer: Tokenizer) -> None:
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router = ContentRouter()
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messages = _filler_messages() + [
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{"role": "tool", "tool_call_id": "call_1", "content": _TRACEBACK},
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{"role": "user", "content": "what went wrong?"},
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]
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result = router.apply(messages, tokenizer)
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assert "router:protected:error_output" in result.transforms_applied
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tool_msgs = [m for m in result.messages if m.get("role") == "tool"]
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assert tool_msgs[0]["content"] == _TRACEBACK
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def test_tool_result_block_with_is_error_flag_protected(self, tokenizer: Tokenizer) -> None:
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router = ContentRouter()
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messages = _filler_messages() + [
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{
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"role": "user",
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"content": [
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{
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"type": "tool_result",
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"tool_use_id": "toolu_1",
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"is_error": True,
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"content": _NEUTRAL_TOOL_OUTPUT,
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}
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],
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},
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]
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result = router.apply(messages, tokenizer)
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assert "router:protected:error_output" in result.transforms_applied
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block = result.messages[-1]["content"][0]
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assert block["content"] == _NEUTRAL_TOOL_OUTPUT
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def test_tool_result_block_with_error_indicators_protected(self, tokenizer: Tokenizer) -> None:
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router = ContentRouter()
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messages = _filler_messages() + [
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{
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"role": "user",
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"content": [
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{
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"type": "tool_result",
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"tool_use_id": "toolu_2",
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"content": _TRACEBACK,
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}
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],
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},
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]
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result = router.apply(messages, tokenizer)
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assert "router:protected:error_output" in result.transforms_applied
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block = result.messages[-1]["content"][0]
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assert block["content"] == _TRACEBACK
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def test_single_indicator_string_output_not_protected(self, tokenizer: Tokenizer) -> None:
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"""Grep-style output mentioning "error" must not skip compression."""
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router = ContentRouter()
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messages = _filler_messages() + [
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{"role": "tool", "tool_call_id": "call_1", "content": _BENIGN_GREP_OUTPUT},
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]
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result = router.apply(messages, tokenizer)
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assert "router:protected:error_output" not in result.transforms_applied
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def test_single_indicator_block_not_protected_without_flag(self, tokenizer: Tokenizer) -> None:
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"""`"errors": []` JSON without `is_error` must not skip compression."""
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router = ContentRouter()
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messages = _filler_messages() + [
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{
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"role": "user",
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"content": [
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{
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"type": "tool_result",
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"tool_use_id": "toolu_3",
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"content": _BENIGN_JSON_OUTPUT,
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}
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],
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},
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]
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result = router.apply(messages, tokenizer)
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assert "router:protected:error_output" not in result.transforms_applied
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def test_is_error_flag_alone_protects_single_indicator_block(
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self, tokenizer: Tokenizer
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) -> None:
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"""The explicit `is_error` flag needs no indicator corroboration."""
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router = ContentRouter()
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messages = _filler_messages() + [
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{
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"role": "user",
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"content": [
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{
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"type": "tool_result",
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"tool_use_id": "toolu_4",
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"is_error": True,
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"content": _BENIGN_JSON_OUTPUT,
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}
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],
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},
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]
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result = router.apply(messages, tokenizer)
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assert "router:protected:error_output" in result.transforms_applied
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block = result.messages[-1]["content"][0]
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assert block["content"] == _BENIGN_JSON_OUTPUT
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def test_oversized_error_output_falls_through(self, tokenizer: Tokenizer) -> None:
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config = ContentRouterConfig(error_protection_max_chars=100)
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router = ContentRouter(config=config)
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messages = _filler_messages() + [
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{"role": "tool", "tool_call_id": "call_1", "content": _TRACEBACK},
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]
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result = router.apply(messages, tokenizer)
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assert "router:protected:error_output" not in result.transforms_applied
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def test_protection_disabled_via_config(self, tokenizer: Tokenizer) -> None:
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config = ContentRouterConfig(protect_error_outputs=False)
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router = ContentRouter(config=config)
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messages = _filler_messages() + [
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{"role": "tool", "tool_call_id": "call_1", "content": _TRACEBACK},
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{
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"role": "user",
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"content": [
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{
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"type": "tool_result",
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"tool_use_id": "toolu_1",
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"is_error": True,
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"content": _TRACEBACK,
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}
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],
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},
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]
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result = router.apply(messages, tokenizer)
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assert "router:protected:error_output" not in result.transforms_applied
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class _FailingTransform(Transform):
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name = "always_fails"
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def apply(
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self, messages: list[dict[str, Any]], tokenizer: TokenizerType, **kwargs: Any
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) -> TransformResult:
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raise RuntimeError("boom")
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class _FlakyTransform(Transform):
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"""Fails for the first ``fail_times`` calls, then succeeds."""
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name = "flaky"
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def __init__(self, fail_times: int) -> None:
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self.fail_times = fail_times
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self.calls = 0
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def apply(
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self, messages: list[dict[str, Any]], tokenizer: TokenizerType, **kwargs: Any
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) -> TransformResult:
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self.calls += 1
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if self.calls <= self.fail_times:
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raise RuntimeError("boom")
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tokens = tokenizer.count_messages(messages)
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return TransformResult(
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messages=messages,
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tokens_before=tokens,
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tokens_after=tokens,
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transforms_applied=[],
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)
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_MESSAGES = [{"role": "user", "content": "hello there, please summarize the build log"}]
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class TestPipelineCircuitBreaker:
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def test_opens_after_threshold_and_passes_through(self) -> None:
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pipeline = TransformPipeline(HeadroomConfig(), transforms=[_FailingTransform()])
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for _ in range(3):
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with pytest.raises(RuntimeError):
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pipeline.apply(_MESSAGES, model="gpt-4o", model_limit=1024)
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result = pipeline.apply(_MESSAGES, model="gpt-4o", model_limit=1024)
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assert result.transforms_applied == ["pipeline:circuit_open"]
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assert result.messages == _MESSAGES
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assert result.tokens_before == result.tokens_after
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def test_success_resets_consecutive_failures(self) -> None:
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flaky = _FlakyTransform(fail_times=2)
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pipeline = TransformPipeline(HeadroomConfig(), transforms=[flaky])
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for _ in range(2):
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with pytest.raises(RuntimeError):
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pipeline.apply(_MESSAGES, model="gpt-4o", model_limit=1024)
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# Third call succeeds — resets the consecutive-failure count.
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pipeline.apply(_MESSAGES, model="gpt-4o", model_limit=1024)
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# Two more failures still don't reach the threshold of 3.
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flaky.fail_times = flaky.calls + 2
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for _ in range(2):
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with pytest.raises(RuntimeError):
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pipeline.apply(_MESSAGES, model="gpt-4o", model_limit=1024)
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result = pipeline.apply(_MESSAGES, model="gpt-4o", model_limit=1024)
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assert result.transforms_applied != ["pipeline:circuit_open"]
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def test_cooldown_expiry_closes_breaker(self, monkeypatch: pytest.MonkeyPatch) -> None:
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monkeypatch.setenv("HEADROOM_PIPELINE_BREAKER_COOLDOWN_S", "0.05")
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flaky = _FlakyTransform(fail_times=3)
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pipeline = TransformPipeline(HeadroomConfig(), transforms=[flaky])
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for _ in range(3):
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with pytest.raises(RuntimeError):
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pipeline.apply(_MESSAGES, model="gpt-4o", model_limit=1024)
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assert pipeline.apply(_MESSAGES, model="gpt-4o", model_limit=1024).transforms_applied == [
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"pipeline:circuit_open"
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]
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time.sleep(0.1)
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result = pipeline.apply(_MESSAGES, model="gpt-4o", model_limit=1024)
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assert result.transforms_applied != ["pipeline:circuit_open"]
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def test_invalid_env_values_fall_back_to_defaults(
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self, monkeypatch: pytest.MonkeyPatch
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) -> None:
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"""Typo'd breaker env vars must not crash proxy startup."""
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monkeypatch.setenv("HEADROOM_PIPELINE_BREAKER_THRESHOLD", "three")
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monkeypatch.setenv("HEADROOM_PIPELINE_BREAKER_COOLDOWN_S", "1m")
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pipeline = TransformPipeline(HeadroomConfig(), transforms=[_FailingTransform()])
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assert pipeline._breaker_threshold == 3
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assert pipeline._breaker_cooldown_s == 60.0
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def test_disabled_via_env(self, monkeypatch: pytest.MonkeyPatch) -> None:
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monkeypatch.setenv("HEADROOM_PIPELINE_BREAKER_THRESHOLD", "0")
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pipeline = TransformPipeline(HeadroomConfig(), transforms=[_FailingTransform()])
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for _ in range(5):
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with pytest.raises(RuntimeError):
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pipeline.apply(_MESSAGES, model="gpt-4o", model_limit=1024)
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# Breaker never opens — failures keep propagating.
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with pytest.raises(RuntimeError):
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pipeline.apply(_MESSAGES, model="gpt-4o", model_limit=1024)
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class _InflatingPipeline:
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"""Fake pipeline whose 'optimization' makes messages bigger."""
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def apply(self, messages: list[dict[str, Any]], **kwargs: Any) -> TransformResult:
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bloated = [{**m, "content": str(m.get("content", "")) + " PADDING" * 50} for m in messages]
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return TransformResult(
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messages=bloated,
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tokens_before=100,
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tokens_after=250,
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transforms_applied=["fake:inflate"],
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)
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class TestLibraryInflationGuard:
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def test_inflated_result_reverts_to_originals(self, monkeypatch: pytest.MonkeyPatch) -> None:
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monkeypatch.setattr(compress_module, "_pipeline", _InflatingPipeline())
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messages = [{"role": "user", "content": "compress this message please"}]
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result = compress(messages, model="gpt-4o")
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assert result.messages == messages
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assert result.transforms_applied == ["inflation_guard:reverted"]
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assert result.tokens_saved == 0
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assert result.compression_ratio == 0.0
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