Rebase MessageHistory on ChatSequence (#4922)

* Rebase `MessageHistory` on `ChatSequence`

* Process feedback & make mypy happy

---------

Co-authored-by: James Collins <collijk@uw.edu>

tests/unit/test_message_history.py

@@ -38,8 +38,8 @@ def agent(config: Config):
     return agent
 
 
-def test_message_history_batch_summary(mocker, agent, config):
-    history = MessageHistory(agent)
+def test_message_history_batch_summary(mocker, agent: Agent, config: Config):
+    history = MessageHistory.for_model(agent.config.smart_llm, agent=agent)
     model = config.fast_llm
     message_tlength = 0
     message_count = 0
@@ -48,7 +48,7 @@ def test_message_history_batch_summary(mocker, agent, config):
     mock_summary_response = ChatModelResponse(
         model_info=OPEN_AI_CHAT_MODELS[model],
         content="I executed browse_website command for each of the websites returned from Google search, but none of them have any job openings.",
-        function_call={},
+        function_call=None,
     )
     mock_summary = mocker.patch(
         "autogpt.memory.message_history.create_chat_completion",
@@ -105,7 +105,7 @@ def test_message_history_batch_summary(mocker, agent, config):
         result = (
             "Command browse_website returned: Answer gathered from website: The text in job"
             + str(i)
-            + " does not provide information on specific job requirements or a job URL.]",
+            + " does not provide information on specific job requirements or a job URL.]"
         )
         msg = Message("system", result, "action_result")
         history.append(msg)
@@ -117,7 +117,7 @@ def test_message_history_batch_summary(mocker, agent, config):
         history.append(user_input_msg)
 
     # only take the last cycle of the message history,  trim the rest of previous messages, and generate a summary for them
-    for cycle in reversed(list(history.per_cycle(config))):
+    for cycle in reversed(list(history.per_cycle())):
         messages_to_add = [msg for msg in cycle if msg is not None]
         message_sequence.insert(insertion_index, *messages_to_add)
         break
@@ -134,7 +134,7 @@ def test_message_history_batch_summary(mocker, agent, config):
     )
 
     expected_call_count = math.ceil(
-        message_tlength / (OPEN_AI_CHAT_MODELS.get(config.fast_llm).max_tokens)
+        message_tlength / (OPEN_AI_CHAT_MODELS[config.fast_llm].max_tokens)
     )
     # Expecting 2 batches because of over max token
     assert mock_summary.call_count == expected_call_count  # 2 at the time of writing