Adding long term, short term, entity and contextual memory

tests/agent_test.py

@@ -48,36 +48,6 @@ def test_custom_llm():
     assert agent.llm.temperature == 0
 
 
-@pytest.mark.vcr(filter_headers=["authorization"])
-def test_agent_without_memory():
-    no_memory_agent = Agent(
-        role="test role",
-        goal="test goal",
-        backstory="test backstory",
-        memory=False,
-        llm=ChatOpenAI(temperature=0, model="gpt-4"),
-    )
-
-    memory_agent = Agent(
-        role="test role",
-        goal="test goal",
-        backstory="test backstory",
-        memory=True,
-        llm=ChatOpenAI(temperature=0, model="gpt-4"),
-    )
-
-    task = Task(
-        description="How much is 1 + 1?",
-        agent=no_memory_agent,
-        expected_output="the result of the math operation.",
-    )
-    result = no_memory_agent.execute_task(task)
-
-    assert result == "The result of the math operation 1 + 1 is 2."
-    assert no_memory_agent.agent_executor.memory is None
-    assert memory_agent.agent_executor.memory is not None
-
-
 @pytest.mark.vcr(filter_headers=["authorization"])
 def test_agent_execution():
     agent = Agent(
@@ -403,7 +373,6 @@ def test_agent_repeated_tool_usage_check_even_with_disabled_cache(capsys):
     )
 
     captured = capsys.readouterr()
-    print(captured.out)
     assert (
         "I tried reusing the same input, I must stop using this action input. I'll try something else instead."
         in captured.out

tests/crew_test.py

@@ -648,9 +648,9 @@ def test_agent_usage_metrics_are_captured_for_sequential_process():
     assert result == "Howdy!"
     assert crew.usage_metrics == {
         "completion_tokens": 56,
-        "prompt_tokens": 164,
+        "prompt_tokens": 161,
         "successful_requests": 1,
-        "total_tokens": 220,
+        "total_tokens": 217,
     }
 
 
@@ -677,8 +677,8 @@ def test_agent_usage_metrics_are_captured_for_hierarchical_process():
     result = crew.kickoff()
     assert result == "Howdy!"
     assert crew.usage_metrics == {
-        "total_tokens": 1513,
-        "prompt_tokens": 1299,
+        "total_tokens": 1510,
+        "prompt_tokens": 1296,
         "completion_tokens": 214,
         "successful_requests": 3,
     }
@@ -735,6 +735,36 @@ def test_crew_inputs_interpolate_both_agents_and_tasks():
                 interpolate_task_inputs.assert_called()
 
 
+def test_task_callback_on_crew():
+    from unittest.mock import patch
+
+    researcher_agent = Agent(
+        role="Researcher",
+        goal="Make the best research and analysis on content about AI and AI agents",
+        backstory="You're an expert researcher, specialized in technology, software engineering, AI and startups. You work as a freelancer and is now working on doing research and analysis for a new customer.",
+        allow_delegation=False,
+    )
+
+    list_ideas = Task(
+        description="Give me a list of 5 interesting ideas to explore for na article, what makes them unique and interesting.",
+        expected_output="Bullet point list of 5 important events.",
+        agent=researcher_agent,
+        async_execution=True,
+    )
+
+    crew = Crew(
+        agents=[researcher_agent],
+        process=Process.sequential,
+        tasks=[list_ideas],
+        task_callback=lambda: None,
+    )
+
+    with patch.object(Agent, "execute_task") as execute:
+        execute.return_value = "ok"
+        crew.kickoff()
+        assert list_ideas.callback is not None
+
+
 @pytest.mark.vcr(filter_headers=["authorization"])
 def test_tools_with_custom_caching():
     from unittest.mock import patch
@@ -748,7 +778,6 @@ def test_tools_with_custom_caching():
 
     def cache_func(args, result):
         cache = result % 2 == 0
-        print(f"cache?: {cache}")
         return cache
 
     multiplcation_tool.cache_function = cache_func

tests/memory/long_term_memory_test.py

@@ -0,0 +1,29 @@
+import pytest
+
+from crewai.memory.long_term.long_term_memory import LongTermMemory
+from crewai.memory.long_term.long_term_memory_item import LongTermMemoryItem
+
+
+@pytest.fixture
+def long_term_memory():
+    """Fixture to create a LongTermMemory instance"""
+    return LongTermMemory()
+
+
+def test_save_and_search(long_term_memory):
+    memory = LongTermMemoryItem(
+        agent="test_agent",
+        task="test_task",
+        expected_output="test_output",
+        datetime="test_datetime",
+        quality=0.5,
+        metadata={"task": "test_task", "quality": 0.5},
+    )
+    long_term_memory.save(memory)
+    find = long_term_memory.search("test_task")[0]
+    assert find["score"] == 0.5
+    assert find["datetime"] == "test_datetime"
+    assert find["metadata"]["agent"] == "test_agent"
+    assert find["metadata"]["quality"] == 0.5
+    assert find["metadata"]["task"] == "test_task"
+    assert find["metadata"]["expected_output"] == "test_output"

tests/memory/short_term_memory_test.py

@@ -0,0 +1,24 @@
+import pytest
+
+from crewai.memory.short_term.short_term_memory import ShortTermMemory
+from crewai.memory.short_term.short_term_memory_item import ShortTermMemoryItem
+
+
+@pytest.fixture
+def short_term_memory():
+    """Fixture to create a ShortTermMemory instance"""
+    return ShortTermMemory()
+
+
+def test_save_and_search(short_term_memory):
+    memory = ShortTermMemoryItem(
+        data="""test value test value test value test value test value test value
+        test value test value test value test value test value test value
+        test value test value test value test value test value test value""",
+        agent="test_agent",
+        metadata={"task": "test_task"},
+    )
+    short_term_memory.save(memory)
+    find = short_term_memory.search("test value", score_threshold=0.01)[0]
+    assert find["context"] == memory.data, "Data value mismatch."
+    assert find["metadata"]["agent"] == "test_agent", "Agent value mismatch."