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https://github.com/NousResearch/hermes-agent.git
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2d3eac5fbd
22c5048d9 restored Anthropic-style cache_control for two of MoA's three
call paths: the acting aggregator (MoAChatCompletions.create, the
persistent `provider: moa` model) and the advisor fan-out (_run_reference).
aggregate_moa_context() -- the /moa <prompt> one-shot command's synthesis
call -- is the third, independent call path and was never covered: its
call_llm(task="moa_aggregator", ...) sent a single undecorated user message
containing the full joined reference output, re-billing the entire input on
every invocation even when the resolved aggregator slot is a cache-honoring
route (Claude on OpenRouter/native Anthropic, MiniMax, Qwen/DashScope).
- Generalize _maybe_apply_advisor_cache_control to
_maybe_apply_moa_cache_control (it never had advisor-specific logic --
same policy function, same breakpoint layout as the main loop, judged
purely on the passed-in runtime) and reuse it in aggregate_moa_context
the same way _run_reference already does.
- Compute _slot_runtime(aggregator) once and reuse it for both the
decoration call and the call_llm kwargs, instead of calling it twice.
Mutation-verified: reverting the moa_loop.py change makes the new
regression test fail by asserting a plain string aggregator-message
content where the cache-honoring case expects native cache_control
content blocks.
114 lines
4 KiB
Python
114 lines
4 KiB
Python
"""Regression test: the MoA aggregator's one-shot synthesis call
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(``aggregate_moa_context``, used by the ``/moa <prompt>`` command) must get
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the same Anthropic-style prompt-caching decoration as the acting-aggregator
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turn (``MoAChatCompletions.create``) and the advisor fan-out
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(``_run_reference``).
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22c5048d9 ("fix(moa): restore prompt caching for the aggregator and
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advisors") fixed the other two MoA call paths but never touched
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``aggregate_moa_context`` — a third, independent call path with its own
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``call_llm(task="moa_aggregator", ...)`` invocation. Without this fix, every
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``/moa <prompt>`` one-shot call re-bills its full input (system-less prompt
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containing all joined reference outputs) with zero cache_control breakpoints,
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even when the resolved aggregator slot is a cache-honoring route.
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"""
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from __future__ import annotations
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from types import SimpleNamespace
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import pytest
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def _response(content="synthesized guidance"):
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message = SimpleNamespace(content=content, tool_calls=[])
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choice = SimpleNamespace(message=message, finish_reason="stop")
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return SimpleNamespace(choices=[choice], usage=None, model="fake")
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@pytest.fixture
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def captured_calls(monkeypatch):
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calls = []
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def fake_call_llm(**kwargs):
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calls.append(kwargs)
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return _response()
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monkeypatch.setattr("agent.moa_loop.call_llm", fake_call_llm)
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monkeypatch.setattr(
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"agent.moa_loop._run_references_parallel",
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lambda *a, **k: [("advisor-a", "advice from a", None)],
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)
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return calls
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def _aggregator_kwargs(calls):
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return next(c for c in calls if c.get("task") == "moa_aggregator")
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def test_aggregator_synthesis_gets_cache_control_on_native_anthropic_route(
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captured_calls, monkeypatch
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):
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"""A cache-honoring aggregator slot (native Anthropic) must get
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cache_control breakpoints on its synthesis call."""
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from agent import moa_loop
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monkeypatch.setattr(
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moa_loop,
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"_slot_runtime",
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lambda slot: {
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"provider": "anthropic",
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"model": "claude-opus-4.8",
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"base_url": "",
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"api_mode": "anthropic_messages",
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},
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)
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moa_loop.aggregate_moa_context(
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user_prompt="what should I do next?",
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api_messages=[{"role": "user", "content": "help me plan"}],
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reference_models=[{"provider": "openrouter", "model": "openai/gpt-5.5"}],
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aggregator={"provider": "anthropic", "model": "claude-opus-4.8"},
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)
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agg_kwargs = _aggregator_kwargs(captured_calls)
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synth_message = agg_kwargs["messages"][0]
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assert synth_message["role"] == "user"
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content = synth_message["content"]
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# Native Anthropic layout places cache_control on inner content blocks,
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# so a cached message's content is a list of blocks rather than a bare
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# string once decorated.
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assert isinstance(content, list), "expected native cache_control block layout"
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assert any(
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isinstance(block, dict) and "cache_control" in block for block in content
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), "aggregator synthesis message must carry a cache_control breakpoint"
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def test_aggregator_synthesis_untouched_on_non_caching_route(
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captured_calls, monkeypatch
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):
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"""A non-cache-honoring aggregator slot (plain OpenAI) must not be
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decorated — proves the guard doesn't over-fire."""
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from agent import moa_loop
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monkeypatch.setattr(
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moa_loop,
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"_slot_runtime",
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lambda slot: {
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"provider": "openai",
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"model": "gpt-5.5",
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"base_url": "",
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"api_mode": "chat_completions",
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},
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)
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moa_loop.aggregate_moa_context(
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user_prompt="what should I do next?",
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api_messages=[{"role": "user", "content": "help me plan"}],
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reference_models=[{"provider": "openrouter", "model": "openai/gpt-5.5"}],
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aggregator={"provider": "openai", "model": "gpt-5.5"},
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)
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agg_kwargs = _aggregator_kwargs(captured_calls)
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synth_message = agg_kwargs["messages"][0]
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assert isinstance(synth_message["content"], str), "must stay undecorated (plain string content)"
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