feat: add governed public knowledge retrieval

tests/unit/infrastructure/test_milvus_knowledge_adapter.py

@@ -0,0 +1,47 @@
+import pytest
+
+from app.core.errors import ForbiddenAgentError
+from app.infrastructure.milvus_knowledge_adapter import MilvusKnowledgeClient
+
+
+class FakeMilvus:
+    def __init__(self) -> None:
+        self.kwargs = None
+
+    async def search(self, **kwargs):
+        self.kwargs = kwargs
+        return [[{
+            "distance": 0.91,
+            "entity": {
+                "knowledge_id": "101",
+                "snippet": "开户说明",
+                "title": "基金开户",
+                "tags": ["开户"],
+                "version": "v1",
+            },
+        }]]
+
+
+@pytest.mark.asyncio
+async def test_knowledge_adapter_uses_cosine_and_minimal_public_projection() -> None:
+    client = MilvusKnowledgeClient("http://unused")
+    fake = FakeMilvus()
+    client._client = fake
+
+    hits = await client.search("fin_faq_collection", [0.1] * 1024, 3)
+
+    assert hits[0]["knowledge_id"] == "101"
+    assert hits[0]["snippet"] == "开户说明"
+    assert hits[0]["score"] == 0.91
+    assert fake.kwargs["collection_name"] == "fin_faq_collection"
+    assert fake.kwargs["limit"] == 3
+    assert fake.kwargs["search_params"] == {"metric_type": "COSINE"}
+    assert fake.kwargs["output_fields"] == ["knowledge_id", "title", "snippet", "tags", "version"]
+
+
+@pytest.mark.asyncio
+async def test_knowledge_adapter_rejects_non_public_collection() -> None:
+    client = MilvusKnowledgeClient("http://unused")
+
+    with pytest.raises(ForbiddenAgentError):
+        await client.search("customer_vectors", [0.1] * 1024, 3)