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4ab3bf66f1
Follow-up to #60168's salvage: aggregate_moa_context() is the third independent MoA call path; assert its aggregator call receives the custom-provider request_overrides.extra_body via **agg_runtime.
243 lines
8.1 KiB
Python
243 lines
8.1 KiB
Python
"""Tests for MoA slot_runtime api_mode propagation (issue #54379).
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Verify that _slot_runtime passes the resolved api_mode through to call_llm,
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so reference slots using providers that require a specific API surface
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(e.g. Copilot GPT-5.x → codex_responses) get routed correctly.
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"""
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from __future__ import annotations
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from types import SimpleNamespace
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from unittest.mock import patch
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import pytest
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def _response(content="ok"):
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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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class TestSlotRuntimeApiMode:
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"""_slot_runtime should include api_mode when resolve_runtime_provider returns it."""
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@patch("hermes_cli.runtime_provider.resolve_runtime_provider")
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def test_slot_runtime_includes_api_mode(self, mock_resolve):
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"""api_mode from resolve_runtime_provider is forwarded in output dict."""
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mock_resolve.return_value = {
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"provider": "copilot",
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"model": "gpt-5.5",
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"base_url": "https://api.githubcopilot.com",
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"api_key": "test-key",
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"api_mode": "codex_responses",
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}
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from agent.moa_loop import _slot_runtime
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result = _slot_runtime({"provider": "copilot", "model": "gpt-5.5"})
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assert result["api_mode"] == "codex_responses"
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assert result["base_url"] == "https://api.githubcopilot.com"
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assert result["api_key"] == "test-key"
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@patch("hermes_cli.runtime_provider.resolve_runtime_provider")
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def test_slot_runtime_omits_api_mode_when_absent(self, mock_resolve):
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"""When resolve_runtime_provider does not return api_mode, output omits it."""
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mock_resolve.return_value = {
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"provider": "openai",
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"model": "gpt-4o",
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"base_url": "https://api.openai.com/v1",
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"api_key": "test-key",
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}
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from agent.moa_loop import _slot_runtime
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result = _slot_runtime({"provider": "openai", "model": "gpt-4o"})
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assert "api_mode" not in result
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@patch("hermes_cli.runtime_provider.resolve_runtime_provider")
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def test_slot_runtime_omits_api_mode_when_empty(self, mock_resolve):
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"""Empty string api_mode is treated as absent."""
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mock_resolve.return_value = {
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"provider": "copilot",
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"model": "gpt-5.5",
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"base_url": "https://api.githubcopilot.com",
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"api_key": "test-key",
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"api_mode": "",
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}
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from agent.moa_loop import _slot_runtime
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result = _slot_runtime({"provider": "copilot", "model": "gpt-5.5"})
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assert "api_mode" not in result
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@patch("hermes_cli.runtime_provider.resolve_runtime_provider")
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def test_slot_runtime_includes_request_override_extra_body(self, mock_resolve):
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"""Custom-provider extra_body is forwarded in call_llm's shape."""
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mock_resolve.return_value = {
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"provider": "custom",
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"model": "qwen3.7-max",
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"base_url": "https://dashscope.example/v1",
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"api_key": "test-key",
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"api_mode": "chat_completions",
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"request_overrides": {
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"extra_body": {
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"enable_thinking": False,
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"reasoning": {"effort": "none"},
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}
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},
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}
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from agent.moa_loop import _slot_runtime
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result = _slot_runtime({"provider": "dashscope", "model": "qwen3.7-max"})
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assert result["extra_body"] == {
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"enable_thinking": False,
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"reasoning": {"effort": "none"},
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}
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def test_run_reference_passes_slot_extra_body(monkeypatch):
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"""Reference advisors should receive custom provider extra_body."""
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from agent import moa_loop
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captured = {}
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def fake_call_llm(**kwargs):
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captured.update(kwargs)
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return _response("advisor")
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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": "custom",
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"model": "qwen3.7-max",
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"base_url": "https://dashscope.example/v1",
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"api_key": "test-key",
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"extra_body": {"enable_thinking": False},
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},
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)
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monkeypatch.setattr(moa_loop, "call_llm", fake_call_llm)
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monkeypatch.setattr(moa_loop, "_maybe_apply_moa_cache_control", lambda messages, runtime: messages)
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label, text, _usage = moa_loop._run_reference(
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{"provider": "dashscope", "model": "qwen3.7-max"},
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[{"role": "user", "content": "hello"}],
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)
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assert label == "dashscope:qwen3.7-max"
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assert text == "advisor"
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assert captured["extra_body"] == {"enable_thinking": False}
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def test_moa_aggregator_merges_slot_extra_body_with_caller_override(tmp_path, monkeypatch):
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"""Aggregator calls should merge slot defaults without duplicate kwargs."""
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home = tmp_path / ".hermes"
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home.mkdir()
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(home / "config.yaml").write_text(
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"""
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moa:
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default_preset: closed
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presets:
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closed:
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enabled: true
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reference_models: []
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aggregator:
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provider: dashscope
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model: qwen3.7-max
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""".strip(),
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encoding="utf-8",
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)
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monkeypatch.setenv("HERMES_HOME", str(home))
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from agent import moa_loop
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captured = {}
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def fake_call_llm(**kwargs):
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captured.update(kwargs)
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return _response("acted")
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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": "custom",
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"model": "qwen3.7-max",
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"base_url": "https://dashscope.example/v1",
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"api_key": "test-key",
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"extra_body": {
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"enable_thinking": False,
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"metadata": {"source": "slot"},
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},
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},
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)
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monkeypatch.setattr(moa_loop, "call_llm", fake_call_llm)
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facade = moa_loop.MoAChatCompletions("closed")
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facade.create(
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model="closed",
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messages=[{"role": "user", "content": "hello"}],
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extra_body={
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"metadata": {"source": "caller"},
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"reasoning": {"effort": "none"},
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},
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)
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assert captured["extra_body"] == {
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"enable_thinking": False,
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"metadata": {"source": "caller"},
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"reasoning": {"effort": "none"},
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}
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def test_one_shot_aggregate_moa_context_passes_slot_extra_body(monkeypatch):
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"""The one-shot `/moa <prompt>` synthesis call (aggregate_moa_context) is
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the third independent MoA call path — its aggregator call receives the
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slot runtime via **agg_runtime, so custom-provider extra_body must flow
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through it too."""
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from agent import moa_loop
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captured_calls = []
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def fake_call_llm(**kwargs):
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captured_calls.append(kwargs)
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return _response("synthesis")
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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": "custom",
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"model": "qwen3.7-max",
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"base_url": "https://dashscope.example/v1",
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"api_key": "test-key",
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"extra_body": {"enable_thinking": False},
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},
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)
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monkeypatch.setattr(moa_loop, "call_llm", fake_call_llm)
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monkeypatch.setattr(
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moa_loop, "_maybe_apply_moa_cache_control", lambda messages, runtime: messages
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)
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result = moa_loop.aggregate_moa_context(
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user_prompt="hello",
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api_messages=[{"role": "user", "content": "hello"}],
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reference_models=[{"provider": "dashscope", "model": "qwen3.7-max"}],
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aggregator={"provider": "dashscope", "model": "qwen3.7-max"},
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)
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assert "synthesis" in result
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agg_calls = [c for c in captured_calls if c.get("task") == "moa_aggregator"]
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assert len(agg_calls) == 1
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assert agg_calls[0]["extra_body"] == {"enable_thinking": False}
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class TestCallLlmApiMode:
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"""call_llm should accept and forward api_mode parameter."""
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def test_call_llm_accepts_api_mode_kwarg(self):
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"""call_llm signature includes api_mode parameter."""
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import inspect
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from agent.auxiliary_client import call_llm
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sig = inspect.signature(call_llm)
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assert "api_mode" in sig.parameters
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assert sig.parameters["api_mode"].default is None
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