import pytest import letta.functions.function_sets.base as base_functions from letta import LocalClient, create_client from letta.schemas.embedding_config import EmbeddingConfig from letta.schemas.llm_config import LLMConfig @pytest.fixture(scope="function") def client(): client = create_client() client.set_default_llm_config(LLMConfig.default_config("gpt-4o")) client.set_default_embedding_config(EmbeddingConfig.default_config(provider="openai")) yield client @pytest.fixture(scope="function") def agent_obj(client: LocalClient): """Create a test agent that we can call functions on""" send_message_to_agent_and_wait_for_reply_tool_id = client.get_tool_id(name="send_message_to_agent_and_wait_for_reply") agent_state = client.create_agent(tool_ids=[send_message_to_agent_and_wait_for_reply_tool_id]) agent_obj = client.server.load_agent(agent_id=agent_state.id, actor=client.user) yield agent_obj # client.delete_agent(agent_obj.agent_state.id) def query_in_search_results(search_results, query): for result in search_results: if query.lower() in result["content"].lower(): return True return False def test_archival(agent_obj): """Test archival memory functions comprehensively.""" # Test 1: Basic insertion and retrieval base_functions.archival_memory_insert(agent_obj, "The cat sleeps on the mat") base_functions.archival_memory_insert(agent_obj, "The dog plays in the park") base_functions.archival_memory_insert(agent_obj, "Python is a programming language") # Test exact text search results, _ = base_functions.archival_memory_search(agent_obj, "cat") assert query_in_search_results(results, "cat") # Test semantic search (should return animal-related content) results, _ = base_functions.archival_memory_search(agent_obj, "animal pets") assert query_in_search_results(results, "cat") or query_in_search_results(results, "dog") # Test unrelated search (should not return animal content) results, _ = base_functions.archival_memory_search(agent_obj, "programming computers") assert query_in_search_results(results, "python") # Test 2: Test pagination # Insert more items to test pagination for i in range(10): base_functions.archival_memory_insert(agent_obj, f"Test passage number {i}") # Get first page page0_results, next_page = base_functions.archival_memory_search(agent_obj, "Test passage", page=0) # Get second page page1_results, _ = base_functions.archival_memory_search(agent_obj, "Test passage", page=1, start=next_page) assert page0_results != page1_results assert query_in_search_results(page0_results, "Test passage") assert query_in_search_results(page1_results, "Test passage") # Test 3: Test complex text patterns base_functions.archival_memory_insert(agent_obj, "Important meeting on 2024-01-15 with John") base_functions.archival_memory_insert(agent_obj, "Follow-up meeting scheduled for next week") base_functions.archival_memory_insert(agent_obj, "Project deadline is approaching") # Search for meeting-related content results, _ = base_functions.archival_memory_search(agent_obj, "meeting schedule") assert query_in_search_results(results, "meeting") assert query_in_search_results(results, "2024-01-15") or query_in_search_results(results, "next week") # Test 4: Test error handling # Test invalid page number try: base_functions.archival_memory_search(agent_obj, "test", page="invalid") assert False, "Should have raised ValueError" except ValueError: pass def test_recall(client, agent_obj): # keyword keyword = "banana" # Send messages to agent client.send_message(agent_id=agent_obj.agent_state.id, role="user", message="hello") client.send_message(agent_id=agent_obj.agent_state.id, role="user", message=keyword) client.send_message(agent_id=agent_obj.agent_state.id, role="user", message="tell me a fun fact") # Conversation search result = base_functions.conversation_search(agent_obj, "banana") assert keyword in result