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https://github.com/TauricResearch/TradingAgents.git
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7bb16c5daa
Trim each provider to current-generation models and drop the special-casing they required: - OpenAI: remove gpt-4.1 (deprecated; the only non-reasoning model). - Anthropic: remove Claude Sonnet 4.5 (legacy; the only Sonnet that 400s on effort). - Google: remove the Gemini 2.5 line (superseded by 3.x). - Gemini client: drop the integer thinking_budget mapping; 3.x takes the string thinking_level directly. Effort/reasoning gates stay as defense in depth for custom model IDs. All kept IDs verified against live APIs.
47 lines
1.5 KiB
Python
47 lines
1.5 KiB
Python
"""Gemini thinking_level forwarding (Gemini 3.x).
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The catalog is Gemini 3.x only, which takes the string ``thinking_level``
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directly. Pro accepts low/high; Flash also accepts minimal/medium — an
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unsupported "minimal" on Pro is mapped to "low".
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"""
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from unittest import mock
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import pytest
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from tradingagents.llm_clients.google_client import GoogleClient
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def _captured_kwargs(model, **kwargs):
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captured = {}
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with mock.patch.object(
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__import__("tradingagents.llm_clients.google_client", fromlist=["x"]),
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"NormalizedChatGoogleGenerativeAI",
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lambda **kw: captured.setdefault("kw", kw),
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):
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GoogleClient(model, api_key="x", **kwargs).get_llm()
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return captured["kw"]
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@pytest.mark.parametrize("level", ["minimal", "low", "medium", "high"])
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def test_flash_passes_thinking_level_through(level):
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kw = _captured_kwargs("gemini-3.5-flash", thinking_level=level)
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assert kw["thinking_level"] == level
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assert "thinking_budget" not in kw # the 2.5-era param is gone
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def test_pro_remaps_minimal_to_low():
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kw = _captured_kwargs("gemini-3.1-pro-preview", thinking_level="minimal")
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assert kw["thinking_level"] == "low" # Pro doesn't accept "minimal"
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def test_pro_keeps_high():
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kw = _captured_kwargs("gemini-3.1-pro-preview", thinking_level="high")
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assert kw["thinking_level"] == "high"
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def test_no_thinking_level_is_omitted():
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kw = _captured_kwargs("gemini-3.5-flash")
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assert "thinking_level" not in kw
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assert "thinking_budget" not in kw
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