generated from coulomb/repo-seed
Bernd Worsch
d71f4114d1
WP-0001 — Foundation & GAAF Baseline - SCOPE.md, ARCHITECTURE-LAYERS.md, contracts/ tree - .claude/rules/ stubs filled (architecture, stack, boundary) - 57 tests (pytest), pyproject.toml with ruff+mypy, CI workflow WP-0002 — Core Extensions (FR-4 + FR-3) - FR-4: BudgetTracker (thread-safe) + LLMBudgetExceededError + optional RunConfig.budget_tracker + enforcement in all adapters - FR-3: async_execute_prompt on LLMAdapter ABC (asyncio.to_thread fallback) + native asyncio.create_subprocess_exec in ClaudeCodeAdapter 81 tests passing. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
87 lines
2.9 KiB
Python
87 lines
2.9 KiB
Python
"""
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Tests for RunConfig and LLMResponse (Core models).
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"""
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import pytest
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from llm_connect.models import RunConfig, LLMResponse
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class TestRunConfig:
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def test_defaults(self):
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cfg = RunConfig()
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assert cfg.model_name == "gpt-4"
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assert cfg.temperature == 0.7
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assert cfg.max_tokens == 2000
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assert cfg.model_params == {}
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assert cfg.max_depth == 3
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assert cfg.skip_if_exists is True
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assert cfg.timeout_seconds == 300
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def test_custom_values(self):
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cfg = RunConfig(model_name="gemini-2.5-flash", temperature=0.1, max_tokens=500)
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assert cfg.model_name == "gemini-2.5-flash"
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assert cfg.temperature == 0.1
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assert cfg.max_tokens == 500
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def test_to_dict_roundtrip(self):
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cfg = RunConfig(model_name="gpt-4o", temperature=0.3, max_tokens=1000)
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d = cfg.to_dict()
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assert d["model_name"] == "gpt-4o"
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assert d["temperature"] == 0.3
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assert d["max_tokens"] == 1000
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def test_from_dict_roundtrip(self):
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original = RunConfig(model_name="claude-3", temperature=0.5, max_tokens=800)
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restored = RunConfig.from_dict(original.to_dict())
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assert restored.model_name == original.model_name
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assert restored.temperature == original.temperature
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assert restored.max_tokens == original.max_tokens
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def test_from_dict_uses_defaults_for_missing_keys(self):
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cfg = RunConfig.from_dict({})
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assert cfg.model_name == "gpt-4"
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assert cfg.temperature == 0.7
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def test_model_params_default_is_independent(self):
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a = RunConfig()
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b = RunConfig()
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a.model_params["x"] = 1
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assert "x" not in b.model_params
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class TestLLMResponse:
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def test_minimal_construction(self):
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r = LLMResponse(content="hello", model="test-model")
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assert r.content == "hello"
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assert r.model == "test-model"
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assert r.usage == {}
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assert r.finish_reason == "stop"
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assert r.metadata == {}
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def test_full_construction(self):
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r = LLMResponse(
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content="response text",
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model="gpt-4",
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usage={"prompt_tokens": 10, "completion_tokens": 5, "total_tokens": 15},
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finish_reason="length",
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metadata={"provider": "openai", "latency_seconds": 1.2},
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)
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assert r.usage["total_tokens"] == 15
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assert r.finish_reason == "length"
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assert r.metadata["provider"] == "openai"
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def test_to_dict(self):
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r = LLMResponse(content="hi", model="m", finish_reason="stop")
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d = r.to_dict()
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assert d["content"] == "hi"
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assert d["model"] == "m"
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assert d["finish_reason"] == "stop"
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assert "usage" in d
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assert "metadata" in d
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def test_metadata_default_is_independent(self):
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a = LLMResponse(content="a", model="m")
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b = LLMResponse(content="b", model="m")
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a.metadata["x"] = 1
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assert "x" not in b.metadata
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