Import AITURK IDE 1.0.0-beta.1 from Hermes 63279301; preserve MIT license
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"""E2E: compression.max_attempts=6 drives a 4th+ preflight compaction pass.
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The turn-start preflight loop in ``agent/turn_context.py`` was hardcoded to
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``range(3)``: even when every pass made real progress and the request stayed
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over threshold, the 4th pass never ran, regardless of configuration. The
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loop now sizes itself from the same resolved ``compression.max_attempts`` cap
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as the conversation loop's compression sites.
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This test builds a real ``AIAgent`` from a config with
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``compression.max_attempts: 6`` (the config-driven path through
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``agent_init``), then drives a full ``run_conversation()`` turn in which the
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estimated request size keeps shrinking ~10% per compaction but stays above
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threshold — the exact "progress, but not enough yet" shape that legitimately
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needs more than three rounds. With cap=6 the preflight must run a 4th pass
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(and ultimately all six).
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"""
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from __future__ import annotations
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import contextlib
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import io
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from pathlib import Path
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from types import SimpleNamespace
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from unittest.mock import MagicMock, patch
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from hermes_state import SessionDB
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from run_agent import AIAgent
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def _config(max_attempts) -> dict:
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return {
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"compression": {
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"enabled": True,
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"threshold": 0.50,
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"target_ratio": 0.20,
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"protect_first_n": 3,
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"protect_last_n": 20,
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"max_attempts": max_attempts,
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},
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"prompt_caching": {"cache_ttl": "5m"},
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"sessions": {},
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"bedrock": {},
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}
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def _stop_response():
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msg = SimpleNamespace(
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content="done",
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reasoning_content=None,
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reasoning=None,
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tool_calls=None,
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)
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choice = SimpleNamespace(message=msg, finish_reason="stop")
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return SimpleNamespace(choices=[choice], model="test/model", usage=None)
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def _make_agent(monkeypatch, tmp_path: Path, *, max_attempts) -> AIAgent:
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from hermes_cli import config as config_mod
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monkeypatch.setattr(
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config_mod, "load_config", lambda: _config(max_attempts)
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)
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monkeypatch.setattr(
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config_mod, "load_config_readonly", lambda: _config(max_attempts)
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)
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db = SessionDB(db_path=tmp_path / "state.db")
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with (
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contextlib.redirect_stdout(io.StringIO()),
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patch("run_agent.get_tool_definitions", return_value=[]),
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patch("run_agent.check_toolset_requirements", return_value={}),
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patch("run_agent.OpenAI"),
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):
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agent = AIAgent(
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base_url="https://openrouter.ai/api/v1",
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api_key="test-key",
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model="test/model",
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enabled_toolsets=[],
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disabled_toolsets=[],
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quiet_mode=True,
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skip_memory=True,
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skip_context_files=True,
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session_db=db,
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session_id="preflight-cap-e2e",
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)
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agent.client = MagicMock()
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agent._cached_system_prompt = "You are helpful."
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agent._use_prompt_caching = False
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agent._disable_streaming = True
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agent.tool_delay = 0
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agent.save_trajectories = False
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return agent
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def test_preflight_runs_fourth_compaction_pass_at_cap_six(monkeypatch, tmp_path):
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agent = _make_agent(monkeypatch, tmp_path, max_attempts=6)
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# Config-driven attach seam (agent_init) resolved the raised cap.
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assert agent.max_compression_attempts == 6
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# Keep the request permanently over threshold while every compaction
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# makes material (~10% > the 5% progress floor) headway.
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compressor = agent.context_compressor
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compressor.threshold_tokens = 50_000
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estimate_state = {"tokens": 1_000_000.0, "calls": 0}
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def _shrinking_estimate(*_args, **_kwargs):
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if estimate_state["calls"]:
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estimate_state["tokens"] *= 0.9
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estimate_state["calls"] += 1
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return int(estimate_state["tokens"])
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compress_calls = []
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def _fake_compress(messages, system_message, **_kwargs):
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compress_calls.append(len(messages))
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return messages, "compressed prompt"
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# 60 messages > protect_first_n + protect_last_n + 1, so the cheap
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# preflight count gate opens without patching internals.
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history = [
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{"role": "user" if i % 2 == 0 else "assistant", "content": f"msg {i}"}
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for i in range(60)
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]
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agent.client.chat.completions.create.return_value = _stop_response()
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with (
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patch(
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"agent.turn_context.estimate_request_tokens_rough",
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side_effect=_shrinking_estimate,
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),
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patch.object(agent, "_compress_context", side_effect=_fake_compress),
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patch.object(agent, "_persist_session"),
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patch.object(agent, "_save_trajectory"),
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patch.object(agent, "_cleanup_task_resources"),
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):
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result = agent.run_conversation("hello", conversation_history=history)
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assert result["completed"] is True
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# The old hardcoded range(3) made a 4th pass impossible; cap=6 must
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# deliver it (and, with steady progress over threshold, all six).
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assert len(compress_calls) >= 4, (
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f"expected a 4th preflight compaction pass at cap=6, "
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f"got {len(compress_calls)} passes"
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)
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assert len(compress_calls) == 6
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