初始化提交

backend/tests/ai_provider/test_pipeline.py

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+"""Tests for the parameter pipeline (Task 4)."""
+
+from __future__ import annotations
+
+import pytest
+
+from app.ai_provider.config.models import ModelConfig, ParameterMapping, ProviderConfig
+from app.ai_provider.pipeline import PipelineContext, PipelineFactory
+
+
+class TestParameterPipeline:
+    """Test the config-driven 4-stage parameter pipeline."""
+
+    @pytest.fixture
+    def pipeline(self):
+        provider_cfg = ProviderConfig(
+            name="deepseek",
+            format="openai",
+            base_url_env="DEEPSEEK_BASE_URL",
+            api_key_env="DEEPSEEK_API_KEY",
+            parameter_mappings={
+                "temperature": ParameterMapping(provider_param="temperature", min=0, max=2),
+                "max_tokens": ParameterMapping(provider_param="max_tokens", min=1),
+                "top_p": ParameterMapping(provider_param="top_p", min=0, max=1),
+            },
+        )
+        return PipelineFactory.create(provider_cfg)
+
+    def test_normalize_temperature(self, pipeline):
+        ctx = PipelineContext(params={"temperature": 0.7})
+        result = pipeline.run(ctx)
+        assert result.params["temperature"] == 0.7
+
+    def test_clamp_temperature(self, pipeline):
+        ctx = PipelineContext(params={"temperature": 5.0})
+        result = pipeline.run(ctx)
+        assert result.params["temperature"] == 2.0  # clamped to max
+
+    def test_filter_unknown_param(self, pipeline):
+        ctx = PipelineContext(params={"temperature": 0.5, "unknown_param": "value"})
+        result = pipeline.run(ctx)
+        assert "unknown_param" not in result.params
+        assert "temperature" in result.params
+
+    def test_inject_provider_defaults(self):
+        provider_cfg = ProviderConfig(
+            name="anthropic",
+            format="anthropic",
+            base_url_env="ANTHROPIC_BASE_URL",
+            api_key_env="ANTHROPIC_API_KEY",
+            parameter_mappings={
+                "max_tokens": ParameterMapping(provider_param="max_tokens", default=4096),
+            },
+        )
+        pipeline = PipelineFactory.create(provider_cfg)
+        ctx = PipelineContext(params={})
+        result = pipeline.run(ctx)
+        assert result.params["max_tokens"] == 4096
+
+    def test_transform_param(self):
+        provider_cfg = ProviderConfig(
+            name="openai",
+            format="openai",
+            base_url_env="OPENAI_BASE_URL",
+            api_key_env="OPENAI_API_KEY",
+            parameter_mappings={
+                "max_tokens": ParameterMapping(provider_param="max_tokens", transform="int"),
+            },
+        )
+        pipeline = PipelineFactory.create(provider_cfg)
+        ctx = PipelineContext(params={"max_tokens": 4096.0})
+        result = pipeline.run(ctx)
+        assert isinstance(result.params["max_tokens"], int)
+
+    def test_capability_filter_vision(self):
+        model = ModelConfig(
+            name="test",
+            provider="openai",
+            model="gpt-4o",
+            format="openai",
+            supports_vision=False,
+        )
+        provider_cfg = ProviderConfig(
+            name="openai", format="openai", base_url_env="X", api_key_env="Y"
+        )
+        pipeline = PipelineFactory.create(provider_cfg)
+        ctx = PipelineContext(
+            params={"image_url": "http://example.com/img.png"}, model_config=model
+        )
+        result = pipeline.run(ctx)
+        assert "image_url" in result.filtered_params