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chore: import upstream snapshot with attribution
2026-07-13 11:58:51 +08:00

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1.5 KiB
Python

"""Gemini thinking_level forwarding (Gemini 3.x).
The catalog is Gemini 3.x only, which takes the string ``thinking_level``
directly. Pro accepts low/high; Flash also accepts minimal/medium — an
unsupported "minimal" on Pro is mapped to "low".
"""
from unittest import mock
import pytest
from tradingagents.llm_clients.google_client import GoogleClient
def _captured_kwargs(model, **kwargs):
captured = {}
with mock.patch.object(
__import__("tradingagents.llm_clients.google_client", fromlist=["x"]),
"NormalizedChatGoogleGenerativeAI",
lambda **kw: captured.setdefault("kw", kw),
):
GoogleClient(model, api_key="x", **kwargs).get_llm()
return captured["kw"]
@pytest.mark.parametrize("level", ["minimal", "low", "medium", "high"])
def test_flash_passes_thinking_level_through(level):
kw = _captured_kwargs("gemini-3.5-flash", thinking_level=level)
assert kw["thinking_level"] == level
assert "thinking_budget" not in kw # the 2.5-era param is gone
def test_pro_remaps_minimal_to_low():
kw = _captured_kwargs("gemini-3.1-pro-preview", thinking_level="minimal")
assert kw["thinking_level"] == "low" # Pro doesn't accept "minimal"
def test_pro_keeps_high():
kw = _captured_kwargs("gemini-3.1-pro-preview", thinking_level="high")
assert kw["thinking_level"] == "high"
def test_no_thinking_level_is_omitted():
kw = _captured_kwargs("gemini-3.5-flash")
assert "thinking_level" not in kw
assert "thinking_budget" not in kw