X-iZhang
521 lines
21 KiB
Python
521 lines
21 KiB
Python
"""Tests for EvoScientist LLM module."""
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from unittest.mock import patch
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from EvoScientist.llm import (
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MODELS,
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DEFAULT_MODEL,
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get_chat_model,
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get_models_for_provider,
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list_models,
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get_model_info,
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)
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from EvoScientist.llm.models import _MODEL_ENTRIES
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# =============================================================================
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# Test MODELS registry
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# =============================================================================
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class TestModelsRegistry:
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def test_models_is_dict(self):
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"""Test that MODELS is a dictionary."""
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assert isinstance(MODELS, dict)
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def test_entries_has_all_providers(self):
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"""Test that _MODEL_ENTRIES covers all registered providers."""
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providers = {p for _, _, p in _MODEL_ENTRIES}
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assert "anthropic" in providers
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assert "openai" in providers
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assert "google-genai" in providers
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assert "nvidia" in providers
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assert "siliconflow" in providers
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assert "openrouter" in providers
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assert "zhipu" in providers
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assert "zhipu-code" in providers
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def test_entries_are_valid_tuples(self):
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"""Test that _MODEL_ENTRIES contains valid (name, model_id, provider) tuples."""
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valid_providers = {"anthropic", "openai", "google-genai", "nvidia", "siliconflow", "openrouter", "zhipu", "zhipu-code"}
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for entry in _MODEL_ENTRIES:
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assert len(entry) == 3, f"Entry {entry} doesn't have 3 elements"
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name, model_id, provider = entry
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assert isinstance(name, str)
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assert isinstance(model_id, str)
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assert provider in valid_providers, f"Unknown provider '{provider}' for '{name}'"
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def test_get_models_for_provider(self):
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"""Test that get_models_for_provider returns correct models."""
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anthropic_models = get_models_for_provider("anthropic")
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assert len(anthropic_models) > 0
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for name, model_id in anthropic_models:
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assert isinstance(name, str)
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assert isinstance(model_id, str)
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# Third-party providers now have registered models
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openrouter_models = get_models_for_provider("openrouter")
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assert len(openrouter_models) > 0
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siliconflow_models = get_models_for_provider("siliconflow")
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assert len(siliconflow_models) > 0
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# =============================================================================
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# Test DEFAULT_MODEL
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# =============================================================================
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class TestDefaultModel:
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def test_default_model_exists_in_registry(self):
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"""Test that DEFAULT_MODEL is a valid model in MODELS."""
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assert DEFAULT_MODEL in MODELS
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def test_default_model_is_anthropic(self):
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"""Test that default model uses Anthropic."""
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_, provider = MODELS[DEFAULT_MODEL]
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assert provider == "anthropic"
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# =============================================================================
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# Test list_models
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# =============================================================================
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class TestListModels:
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def test_returns_list(self):
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"""Test that list_models returns a list."""
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result = list_models()
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assert isinstance(result, list)
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def test_returns_all_model_names(self):
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"""Test that list_models returns all model names."""
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result = list_models()
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assert set(result) == set(MODELS.keys())
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def test_list_is_not_empty(self):
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"""Test that the list is not empty."""
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assert len(list_models()) > 0
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# =============================================================================
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# Test get_model_info
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# =============================================================================
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class TestGetModelInfo:
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def test_returns_tuple_for_valid_model(self):
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"""Test that get_model_info returns tuple for valid model."""
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result = get_model_info("claude-sonnet-4-5")
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assert result is not None
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assert isinstance(result, tuple)
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assert len(result) == 2
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def test_returns_none_for_invalid_model(self):
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"""Test that get_model_info returns None for invalid model."""
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result = get_model_info("nonexistent-model")
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assert result is None
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def test_returns_correct_info(self):
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"""Test that get_model_info returns correct info."""
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model_id, provider = get_model_info("gpt-5-nano")
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assert model_id == "gpt-5-nano-2025-08-07"
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assert provider == "openai"
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# =============================================================================
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# Test get_chat_model
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# =============================================================================
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class TestGetChatModel:
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@patch("EvoScientist.llm.models.init_chat_model")
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def test_uses_default_model_when_none(self, mock_init):
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"""Test that get_chat_model uses default model when model=None."""
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mock_init.return_value = "mock_model"
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get_chat_model()
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mock_init.assert_called_once()
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call_kwargs = mock_init.call_args[1]
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# Default model should be resolved from MODELS
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expected_model_id, expected_provider = MODELS[DEFAULT_MODEL]
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assert call_kwargs["model"] == expected_model_id
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assert call_kwargs["model_provider"] == expected_provider
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@patch("EvoScientist.llm.models.init_chat_model")
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def test_resolves_short_name(self, mock_init):
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"""Test that get_chat_model resolves short names correctly."""
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mock_init.return_value = "mock_model"
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get_chat_model("claude-opus-4-5")
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call_kwargs = mock_init.call_args[1]
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assert call_kwargs["model"] == "claude-opus-4-5-20251101"
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assert call_kwargs["model_provider"] == "anthropic"
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@patch("EvoScientist.llm.models.init_chat_model")
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def test_resolves_openai_short_name(self, mock_init):
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"""Test that get_chat_model resolves OpenAI short names."""
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mock_init.return_value = "mock_model"
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get_chat_model("gpt-5-mini")
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call_kwargs = mock_init.call_args[1]
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assert call_kwargs["model"] == "gpt-5-mini-2025-08-07"
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assert call_kwargs["model_provider"] == "openai"
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@patch("EvoScientist.llm.models.init_chat_model")
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def test_uses_full_model_id(self, mock_init):
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"""Test that get_chat_model accepts full model IDs."""
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mock_init.return_value = "mock_model"
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get_chat_model("claude-3-opus-20240229")
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call_kwargs = mock_init.call_args[1]
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assert call_kwargs["model"] == "claude-3-opus-20240229"
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# Should infer anthropic from the model prefix
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assert call_kwargs["model_provider"] == "anthropic"
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@patch("EvoScientist.llm.models.init_chat_model")
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def test_provider_override(self, mock_init):
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"""Test that provider can be overridden."""
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mock_init.return_value = "mock_model"
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get_chat_model("claude-sonnet-4-5", provider="custom_provider")
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call_kwargs = mock_init.call_args[1]
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assert call_kwargs["model_provider"] == "custom_provider"
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@patch("EvoScientist.llm.models.init_chat_model")
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def test_passes_kwargs(self, mock_init):
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"""Test that additional kwargs are passed through."""
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mock_init.return_value = "mock_model"
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get_chat_model("gpt-5-nano", temperature=0.7, max_tokens=1000)
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call_kwargs = mock_init.call_args[1]
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assert call_kwargs["temperature"] == 0.7
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assert call_kwargs["max_tokens"] == 1000
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@patch("EvoScientist.llm.models.init_chat_model")
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def test_infers_openai_from_gpt_prefix(self, mock_init):
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"""Test that OpenAI is inferred from gpt- prefix."""
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mock_init.return_value = "mock_model"
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get_chat_model("gpt-4-turbo-preview")
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call_kwargs = mock_init.call_args[1]
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assert call_kwargs["model_provider"] == "openai"
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@patch("EvoScientist.llm.models.init_chat_model")
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def test_infers_openai_from_o1_prefix(self, mock_init):
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"""Test that OpenAI is inferred from o1 prefix."""
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mock_init.return_value = "mock_model"
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get_chat_model("o1-preview")
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call_kwargs = mock_init.call_args[1]
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assert call_kwargs["model_provider"] == "openai"
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@patch("EvoScientist.llm.models.init_chat_model")
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def test_infers_google_from_gemini_prefix(self, mock_init):
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"""Test that google-genai is inferred from gemini prefix."""
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mock_init.return_value = "mock_model"
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get_chat_model("gemini-2.0-flash")
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call_kwargs = mock_init.call_args[1]
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assert call_kwargs["model_provider"] == "google-genai"
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@patch("EvoScientist.llm.models.init_chat_model")
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def test_defaults_to_anthropic_for_unknown(self, mock_init):
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"""Test that anthropic is default for unknown model prefixes."""
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mock_init.return_value = "mock_model"
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get_chat_model("some-unknown-model")
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call_kwargs = mock_init.call_args[1]
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assert call_kwargs["model_provider"] == "anthropic"
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# =============================================================================
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# Test Ollama provider
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# =============================================================================
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class TestOllamaProvider:
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"""Ollama models are not in the static registry (detected dynamically).
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All tests use explicit provider or ollama: prefix."""
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@patch("EvoScientist.llm.models.init_chat_model")
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def test_explicit_provider(self, mock_init):
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"""Test that explicit provider='ollama' routes correctly."""
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mock_init.return_value = "mock_model"
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get_chat_model("llama3.1:8b", provider="ollama")
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call_kwargs = mock_init.call_args[1]
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assert call_kwargs["model"] == "llama3.1:8b"
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assert call_kwargs["model_provider"] == "ollama"
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@patch("EvoScientist.llm.models.init_chat_model")
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def test_ollama_base_url_passthrough(self, mock_init, monkeypatch):
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"""Test that OLLAMA_BASE_URL env var is passed to kwargs."""
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mock_init.return_value = "mock_model"
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monkeypatch.setenv("OLLAMA_BASE_URL", "http://gpu-cluster:11434")
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get_chat_model("llama3.1:8b", provider="ollama")
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call_kwargs = mock_init.call_args[1]
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assert call_kwargs["base_url"] == "http://gpu-cluster:11434"
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assert call_kwargs["model_provider"] == "ollama"
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@patch("EvoScientist.llm.models.init_chat_model")
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def test_ollama_no_base_url_when_unset(self, mock_init, monkeypatch):
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"""Test that base_url is not set when OLLAMA_BASE_URL is empty."""
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mock_init.return_value = "mock_model"
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monkeypatch.delenv("OLLAMA_BASE_URL", raising=False)
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get_chat_model("llama3.1:8b", provider="ollama")
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call_kwargs = mock_init.call_args[1]
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assert "base_url" not in call_kwargs
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@patch("EvoScientist.llm.models.init_chat_model")
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def test_reasoning_auto_enabled_for_ollama(self, mock_init, monkeypatch):
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"""Test that reasoning is auto-enabled for Ollama models."""
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mock_init.return_value = "mock_model"
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monkeypatch.delenv("OLLAMA_BASE_URL", raising=False)
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get_chat_model("llama3.1:8b", provider="ollama")
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call_kwargs = mock_init.call_args[1]
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assert "thinking" not in call_kwargs
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assert call_kwargs["reasoning"] is True
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@patch("EvoScientist.llm.models.init_chat_model")
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def test_reasoning_not_overridden_for_ollama(self, mock_init, monkeypatch):
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"""Test that explicit reasoning=False is not overridden for Ollama."""
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mock_init.return_value = "mock_model"
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monkeypatch.delenv("OLLAMA_BASE_URL", raising=False)
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get_chat_model("llama3.1:8b", provider="ollama", reasoning=False)
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call_kwargs = mock_init.call_args[1]
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assert call_kwargs["reasoning"] is False
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def test_no_static_registry_entries(self):
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"""Test that Ollama has no static registry entries (models detected dynamically)."""
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ollama_models = get_models_for_provider("ollama")
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assert len(ollama_models) == 0
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@patch("EvoScientist.llm.models.init_chat_model")
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def test_ollama_prefix_inference(self, mock_init, monkeypatch):
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"""Test that ollama: prefix infers ollama provider."""
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mock_init.return_value = "mock_model"
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monkeypatch.delenv("OLLAMA_BASE_URL", raising=False)
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get_chat_model("ollama:phi3:mini")
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call_kwargs = mock_init.call_args[1]
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assert call_kwargs["model"] == "phi3:mini"
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assert call_kwargs["model_provider"] == "ollama"
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# =============================================================================
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# Test slash model ID no longer routes to nvidia
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# =============================================================================
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class TestSlashModelIdFallback:
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@patch("EvoScientist.llm.models.init_chat_model")
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def test_slash_model_id_defaults_to_anthropic(self, mock_init):
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"""Unregistered model IDs containing '/' should NOT route to nvidia.
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They fall through to the default 'anthropic' provider, consistent
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with how all other unknown model IDs are handled.
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"""
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mock_init.return_value = "mock_model"
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get_chat_model("some-org/some-model")
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call_kwargs = mock_init.call_args[1]
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assert call_kwargs["model"] == "some-org/some-model"
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assert call_kwargs["model_provider"] == "anthropic"
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# =============================================================================
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# Test third-party provider routing
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# =============================================================================
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class TestThirdPartyRouting:
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@patch("EvoScientist.llm.models.init_chat_model")
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def test_siliconflow_routes_through_openai(self, mock_init, monkeypatch):
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"""SiliconFlow provider should route through OpenAI with correct base_url."""
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mock_init.return_value = "mock_model"
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monkeypatch.setenv("SILICONFLOW_API_KEY", "sf-key-123")
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get_chat_model("Pro/zai-org/GLM-5", provider="siliconflow")
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call_kwargs = mock_init.call_args[1]
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assert call_kwargs["model_provider"] == "openai"
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assert call_kwargs["base_url"] == "https://api.siliconflow.cn/v1"
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assert call_kwargs["api_key"] == "sf-key-123"
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# SiliconFlow should disable thinking
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assert call_kwargs["extra_body"]["enable_thinking"] is False
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@patch("EvoScientist.llm.models.init_chat_model")
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def test_openrouter_routes_through_openai(self, mock_init, monkeypatch):
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"""OpenRouter provider should route through OpenAI with correct base_url."""
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mock_init.return_value = "mock_model"
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monkeypatch.setenv("OPENROUTER_API_KEY", "or-key-456")
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get_chat_model("x-ai/grok-4.1-fast", provider="openrouter")
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call_kwargs = mock_init.call_args[1]
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assert call_kwargs["model_provider"] == "openai"
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assert call_kwargs["base_url"] == "https://openrouter.ai/api/v1"
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assert call_kwargs["api_key"] == "or-key-456"
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@patch("EvoScientist.llm.models.init_chat_model")
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def test_custom_routes_through_openai(self, mock_init, monkeypatch):
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"""Custom provider should route through OpenAI with env-configured base_url."""
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mock_init.return_value = "mock_model"
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monkeypatch.setenv("CUSTOM_BASE_URL", "https://my-llm.example.com/v1")
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monkeypatch.setenv("CUSTOM_API_KEY", "custom-key-789")
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get_chat_model("my-custom-model", provider="custom")
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call_kwargs = mock_init.call_args[1]
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assert call_kwargs["model_provider"] == "openai"
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assert call_kwargs["base_url"] == "https://my-llm.example.com/v1"
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assert call_kwargs["api_key"] == "custom-key-789"
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@patch("EvoScientist.llm.models.init_chat_model")
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def test_anthropic_base_url_override(self, mock_init, monkeypatch):
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"""Anthropic provider should support base_url override (e.g. ccproxy)."""
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mock_init.return_value = "mock_model"
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monkeypatch.setenv("ANTHROPIC_BASE_URL", "http://localhost:8000/api/v1")
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monkeypatch.setenv("ANTHROPIC_API_KEY", "sk-dummy")
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get_chat_model("claude-sonnet-4-6", provider="anthropic")
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call_kwargs = mock_init.call_args[1]
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assert call_kwargs["model_provider"] == "anthropic"
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assert call_kwargs["base_url"] == "http://localhost:8000/api/v1"
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assert call_kwargs["api_key"] == "sk-dummy"
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# Proxy mode: thinking skipped for 4-6 models (ccproxy manages it)
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assert "thinking" not in call_kwargs
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@patch("EvoScientist.llm.models.init_chat_model")
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def test_anthropic_no_base_url_when_unset(self, mock_init, monkeypatch):
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"""Anthropic provider should not set base_url when env var is empty."""
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mock_init.return_value = "mock_model"
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monkeypatch.delenv("ANTHROPIC_BASE_URL", raising=False)
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monkeypatch.setenv("ANTHROPIC_API_KEY", "sk-real")
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get_chat_model("claude-sonnet-4-6", provider="anthropic")
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call_kwargs = mock_init.call_args[1]
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assert call_kwargs["model_provider"] == "anthropic"
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assert "base_url" not in call_kwargs
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@patch("EvoScientist.llm.models.init_chat_model")
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def test_third_party_no_reasoning(self, mock_init, monkeypatch):
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"""Third-party providers routed through OpenAI should NOT get auto-reasoning."""
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mock_init.return_value = "mock_model"
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monkeypatch.setenv("OPENROUTER_API_KEY", "or-key")
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get_chat_model("x-ai/grok-4.1-fast", provider="openrouter")
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call_kwargs = mock_init.call_args[1]
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assert "reasoning" not in call_kwargs
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# =============================================================================
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# Test _apply_auto_config
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# =============================================================================
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class TestAutoConfig:
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@patch("EvoScientist.llm.models.init_chat_model")
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def test_anthropic_4_5_thinking(self, mock_init):
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"""Anthropic 4-5 models get enabled thinking with budget."""
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mock_init.return_value = "mock_model"
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get_chat_model("claude-sonnet-4-5")
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call_kwargs = mock_init.call_args[1]
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assert call_kwargs["thinking"] == {"type": "enabled", "budget_tokens": 10000}
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@patch("EvoScientist.llm.models.init_chat_model")
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def test_anthropic_4_6_adaptive_thinking(self, mock_init, monkeypatch):
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"""Anthropic 4-6 models get adaptive thinking with max effort."""
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mock_init.return_value = "mock_model"
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monkeypatch.delenv("ANTHROPIC_BASE_URL", raising=False)
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get_chat_model("claude-sonnet-4-6")
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call_kwargs = mock_init.call_args[1]
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assert call_kwargs["thinking"] == {"type": "adaptive"}
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assert call_kwargs["effort"] == "max"
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@patch("EvoScientist.llm.models.init_chat_model")
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def test_anthropic_4_6_proxy_no_thinking(self, mock_init, monkeypatch):
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"""Anthropic 4-6 models via proxy skip thinking (ccproxy manages it)."""
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mock_init.return_value = "mock_model"
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monkeypatch.setenv("ANTHROPIC_BASE_URL", "http://127.0.0.1:8000")
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monkeypatch.setenv("ANTHROPIC_API_KEY", "ccproxy-oauth")
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|
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get_chat_model("claude-sonnet-4-6")
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|
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call_kwargs = mock_init.call_args[1]
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assert "thinking" not in call_kwargs
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assert "effort" not in call_kwargs
|
|
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@patch("EvoScientist.llm.models.init_chat_model")
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|
def test_anthropic_4_6_no_proxy_no_downgrade(self, mock_init, monkeypatch):
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"""Anthropic 4-6 models without proxy still get adaptive thinking."""
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|
mock_init.return_value = "mock_model"
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monkeypatch.setenv("ANTHROPIC_BASE_URL", "https://api.anthropic.com")
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|
monkeypatch.setenv("ANTHROPIC_API_KEY", "sk-real")
|
|
|
|
get_chat_model("claude-sonnet-4-6")
|
|
|
|
call_kwargs = mock_init.call_args[1]
|
|
assert call_kwargs["thinking"] == {"type": "adaptive"}
|
|
assert call_kwargs["effort"] == "max"
|
|
|
|
@patch("EvoScientist.llm.models.init_chat_model")
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|
def test_anthropic_thinking_not_overridden(self, mock_init):
|
|
"""User-supplied thinking config should not be overridden."""
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|
mock_init.return_value = "mock_model"
|
|
custom_thinking = {"type": "enabled", "budget_tokens": 500}
|
|
|
|
get_chat_model("claude-sonnet-4-6", thinking=custom_thinking)
|
|
|
|
call_kwargs = mock_init.call_args[1]
|
|
assert call_kwargs["thinking"] == custom_thinking
|
|
|
|
@patch("EvoScientist.llm.models.init_chat_model")
|
|
def test_openai_reasoning(self, mock_init):
|
|
"""Native OpenAI models get auto-reasoning."""
|
|
mock_init.return_value = "mock_model"
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|
|
|
get_chat_model("gpt-5-nano")
|
|
|
|
call_kwargs = mock_init.call_args[1]
|
|
assert call_kwargs["reasoning"] == {"effort": "high", "summary": "auto"}
|
|
|
|
@patch("EvoScientist.llm.models.init_chat_model")
|
|
def test_google_thoughts(self, mock_init):
|
|
"""Google GenAI models get include_thoughts=True by default."""
|
|
mock_init.return_value = "mock_model"
|
|
|
|
get_chat_model("gemini-2.5-flash")
|
|
|
|
call_kwargs = mock_init.call_args[1]
|
|
assert call_kwargs["include_thoughts"] is True
|
|
|