feat(chat): 接入全局知识库上下文

tests/test_chat_knowledge_context.py

@@ -0,0 +1,59 @@
+import pytest
+
+from review_agent.models import KnowledgeBaseDocument
+from review_agent.services import build_knowledge_context
+
+
+pytestmark = pytest.mark.django_db
+
+
+def test_build_knowledge_context_ignores_irrelevant_rag_chunks(monkeypatch):
+    monkeypatch.setattr(
+        "review_agent.services.search_knowledge_base",
+        lambda query, n_results=5: {
+            "query": query,
+            "results": [
+                {
+                    "source": "附件 4 体外诊断试剂注册申报资料要求及说明.doc",
+                    "text": "预期用途应明确产品用于检测的分析物和功能。",
+                    "score": 7.636,
+                    "metadata": {"source_type": "regulatory_document"},
+                }
+            ],
+            "error_message": "",
+        },
+    )
+
+    context = build_knowledge_context("孙之烨是谁")
+
+    assert context == ""
+
+
+def test_build_knowledge_context_uses_full_document_when_name_matches(settings, tmp_path, monkeypatch, django_user_model):
+    settings.MEDIA_ROOT = tmp_path
+    user = django_user_model.objects.create_user(username="owner", password="pass")
+    document_path = tmp_path / "resume.txt"
+    document_path.write_text(
+        "孙之烨，负责审核智能体项目。\n完整经历：曾组织技术分享并带队参加竞赛。",
+        encoding="utf-8",
+    )
+    KnowledgeBaseDocument.objects.create(
+        user=user,
+        display_name="孙之烨简历",
+        original_name="孙之烨-260510.txt",
+        storage_path=str(document_path),
+        file_size=document_path.stat().st_size,
+        status=KnowledgeBaseDocument.Status.ACTIVE,
+        is_active=True,
+        indexed_chunk_count=2,
+    )
+    monkeypatch.setattr(
+        "review_agent.services.search_knowledge_base",
+        lambda query, n_results=5: {"query": query, "results": [], "error_message": ""},
+    )
+
+    context = build_knowledge_context("孙之烨是谁")
+
+    assert "全文材料" in context
+    assert "来源：用户知识库/孙之烨-260510.txt" in context
+    assert "完整经历：曾组织技术分享并带队参加竞赛" in context

tests/test_file_summary_workflow.py

@@ -201,17 +201,36 @@ def test_stream_message_returns_workflow_meta_when_triggered(settings, django_us
 def test_stream_message_uses_normal_llm_path_when_not_triggered(monkeypatch, django_user_model):
     user = django_user_model.objects.create_user(username="owner", password="pass")
     conversation = Conversation.objects.create(user=user, title="会话")
+    calls = []
 
-    def fake_stream_reply(conversation, content):
+    def fake_stream_reply(conversation, content, knowledge_context=""):
+        calls.append(knowledge_context)
         yield "普通回复"
 
     monkeypatch.setattr("review_agent.services.stream_reply", fake_stream_reply)
+    monkeypatch.setattr(
+        "review_agent.services.search_knowledge_base",
+        lambda query, n_results=3: {
+            "query": query,
+            "results": [
+                {
+                    "source": "用户知识库/1/2/孙之烨-260510.pdf",
+                    "text": "孙之烨负责审核智能体项目。",
+                    "score": 0.23,
+                }
+            ],
+            "error_message": "",
+        },
+    )
 
-    frames = list(stream_message(conversation, "你好"))
+    frames = list(stream_message(conversation, "孙之烨是谁"))
 
     joined = "".join(frames)
     assert "普通回复" in joined
     assert "workflow_started" not in joined
+    assert calls
+    assert "孙之烨负责审核智能体项目" in calls[0]
+    assert "用户知识库/1/2/孙之烨-260510.pdf" in calls[0]
 
 
 def test_stream_message_meta_uses_first_prompt_title_for_new_conversation(monkeypatch, django_user_model):
@@ -257,12 +276,15 @@ def test_stream_message_falls_back_to_non_stream_reply_when_stream_breaks(monkey
     user = django_user_model.objects.create_user(username="owner", password="pass")
     conversation = Conversation.objects.create(user=user, title="会话")
 
-    def broken_stream_reply(conversation, content):
+    def broken_stream_reply(conversation, content, knowledge_context=""):
         yield "已生成部分内容"
         raise RuntimeError("provider connection reset")
 
     monkeypatch.setattr("review_agent.services.stream_reply", broken_stream_reply)
-    monkeypatch.setattr("review_agent.services.generate_reply", lambda conversation, content: "非流式完整回复")
+    monkeypatch.setattr(
+        "review_agent.services.generate_reply",
+        lambda conversation, content, knowledge_context="": "非流式完整回复",
+    )
 
     frames = list(stream_message(conversation, "普通问题"))
 

tests/test_llm_streaming.py

@@ -3,7 +3,7 @@ from urllib import request
 
 import pytest
 
-from review_agent.llm import stream_reply
+from review_agent.llm import build_messages, stream_reply
 from review_agent.models import Conversation
 
 
@@ -39,3 +39,16 @@ def test_stream_reply_skips_malformed_sse_data(monkeypatch, settings, django_use
     chunks = list(stream_reply(conversation, "你好"))
 
     assert chunks == ["A", "B"]
+
+
+def test_build_messages_includes_knowledge_context(django_user_model):
+    user = django_user_model.objects.create_user(username="owner", password="pass")
+    conversation = Conversation.objects.create(user=user, title="会话")
+
+    messages = build_messages(conversation, "孙之烨是谁", knowledge_context="来源：简历\n孙之烨负责审核智能体项目。")
+
+    assert messages[0]["role"] == "system"
+    assert messages[1]["role"] == "system"
+    assert "全局知识库" in messages[1]["content"]
+    assert "孙之烨负责审核智能体项目" in messages[1]["content"]
+    assert messages[-1] == {"role": "user", "content": "孙之烨是谁"}