feat: assemble memory context from facts and similar summaries

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01V57jSQPqwkGG8BuAXg59X5

Claude outputs/main.py

@@ -328,6 +328,28 @@ async def search_similar_conversation_summaries(query_embedding: list, exclude_c
     )
 
 
+async def build_memory_context(user_message: str, conversation_id: int) -> str:
+    sections = []
+
+    facts = await get_all_memory_facts()
+    if facts:
+        facts_lines = "\n".join(f"- {f['content']}" for f in facts)
+        sections.append(f"Bekannte Fakten ueber den Nutzer:\n{facts_lines}")
+
+    try:
+        query_embedding = await get_embedding(user_message)
+        summaries = await search_similar_conversation_summaries(query_embedding, conversation_id, limit=3)
+    except Exception as e:
+        logger.warning(f"Memory retrieval skipped, embedding/search failed: {e}")
+        summaries = []
+
+    if summaries:
+        summary_lines = "\n".join(f"- {s['summary']}" for s in summaries)
+        sections.append(f"Relevante fruehere Gespraeche:\n{summary_lines}")
+
+    return "\n\n".join(sections)
+
+
 def _caldav_calendar():
     dav_root = NEXTCLOUD_CALDAV_URL.split("/calendars/")[0] + "/"
     client = caldav.DAVClient(url=dav_root, username=NEXTCLOUD_USER, password=NEXTCLOUD_APP_PASSWORD)

Claude outputs/tests/test_memory.py

@@ -141,3 +141,48 @@ async def test_execute_tool_dispatches_remember_and_forget_fact():
     with patch.object(main, "forget_fact", new=AsyncMock(return_value={"deleted": True, "content": "X"})):
         result = await main.execute_tool("forget_fact", {"query": "X"})
     assert json.loads(result) == {"deleted": True, "content": "X"}
+
+
+@pytest.mark.asyncio
+async def test_build_memory_context_empty_when_nothing_stored():
+    with patch.object(main, "get_all_memory_facts", new=AsyncMock(return_value=[])), patch.object(
+        main, "get_embedding", new=AsyncMock(return_value=[0.1])
+    ), patch.object(main, "search_similar_conversation_summaries", new=AsyncMock(return_value=[])):
+        context = await main.build_memory_context("Hallo", conversation_id=1)
+
+    assert context == ""
+
+
+@pytest.mark.asyncio
+async def test_build_memory_context_includes_facts_section():
+    facts = [{"id": 1, "content": "Hund heisst Bruno"}]
+    with patch.object(main, "get_all_memory_facts", new=AsyncMock(return_value=facts)), patch.object(
+        main, "get_embedding", new=AsyncMock(return_value=[0.1])
+    ), patch.object(main, "search_similar_conversation_summaries", new=AsyncMock(return_value=[])):
+        context = await main.build_memory_context("Wie geht es meinem Hund?", conversation_id=1)
+
+    assert "Bekannte Fakten ueber den Nutzer" in context
+    assert "Hund heisst Bruno" in context
+    assert "Relevante fruehere Gespraeche" not in context
+
+
+@pytest.mark.asyncio
+async def test_build_memory_context_includes_summaries_section():
+    summaries = [{"conversation_id": 2, "summary": "Ging um den Kalender", "distance": 0.05}]
+    with patch.object(main, "get_all_memory_facts", new=AsyncMock(return_value=[])), patch.object(
+        main, "get_embedding", new=AsyncMock(return_value=[0.1])
+    ), patch.object(main, "search_similar_conversation_summaries", new=AsyncMock(return_value=summaries)):
+        context = await main.build_memory_context("Was war nochmal mit dem Termin?", conversation_id=1)
+
+    assert "Relevante fruehere Gespraeche" in context
+    assert "Ging um den Kalender" in context
+
+
+@pytest.mark.asyncio
+async def test_build_memory_context_skips_summaries_when_embedding_fails():
+    with patch.object(main, "get_all_memory_facts", new=AsyncMock(return_value=[])), patch.object(
+        main, "get_embedding", new=AsyncMock(side_effect=RuntimeError("Ollama down"))
+    ):
+        context = await main.build_memory_context("Hallo", conversation_id=1)
+
+    assert context == ""