Allow unlimited LLM memory through traitlets configuration (jupyterla…

…b#986)

packages/jupyter-ai/jupyter_ai/extension.py

@@ -188,7 +188,13 @@ class AiExtension(ExtensionApp):
         default_value=2,
         help="""
         Number of chat interactions to keep in the conversational memory object.
+
+        An interaction is defined as an exchange between a human and AI, thus
+        comprising of one or two messages.
+
+        Set to `None` to keep all interactions.
         """,
+        allow_none=True,
         config=True,
     )
 

packages/jupyter-ai/jupyter_ai/history.py

@@ -1,5 +1,5 @@
 import time
-from typing import List, Optional, Sequence, Set
+from typing import List, Optional, Sequence, Set, Union
 
 from langchain_core.chat_history import BaseChatMessageHistory
 from langchain_core.messages import BaseMessage
@@ -16,16 +16,18 @@ class BoundedChatHistory(BaseChatMessageHistory, BaseModel):
     `k` exchanges between a user and an LLM.
 
     For example, when `k=2`, `BoundedChatHistory` will store up to 2 human
-    messages and 2 AI messages.
+    messages and 2 AI messages. If `k` is set to `None` all messages are kept.
     """
 
-    k: int
+    k: Union[int, None]
     clear_time: float = 0.0
     cleared_msgs: Set[str] = set()
     _all_messages: List[BaseMessage] = PrivateAttr(default_factory=list)
 
     @property
     def messages(self) -> List[BaseMessage]:
+        if self.k is None:
+            return self._all_messages
         return self._all_messages[-self.k * 2 :]
 
     async def aget_messages(self) -> List[BaseMessage]:

packages/jupyter-ai/jupyter_ai/tests/test_extension.py

@@ -1,7 +1,12 @@
 # Copyright (c) Jupyter Development Team.
 # Distributed under the terms of the Modified BSD License.
+from unittest import mock
+
 import pytest
 from jupyter_ai.extension import AiExtension
+from jupyter_ai.history import HUMAN_MSG_ID_KEY
+from jupyter_ai_magics import BaseProvider
+from langchain_core.messages import BaseMessage
 
 pytest_plugins = ["pytest_jupyter.jupyter_server"]
 
@@ -43,3 +48,46 @@ def test_blocks_providers(argv, jp_configurable_serverapp):
     ai._link_jupyter_server_extension(server)
     ai.initialize_settings()
     assert KNOWN_LM_A not in ai.settings["lm_providers"]
+
+
+@pytest.fixture
+def jp_server_config(jp_server_config):
+    # Disable the extension during server startup to avoid double initialization
+    return {"ServerApp": {"jpserver_extensions": {"jupyter_ai": False}}}
+
+
+@pytest.fixture
+def ai_extension(jp_serverapp):
+    ai = AiExtension()
+    # `BaseProvider.server_settings` can be only initialized once; however, the tests
+    # may run in parallel setting it with race condition; because we are not testing
+    # the `BaseProvider.server_settings` here, we can just mock the setter
+    settings_mock = mock.PropertyMock()
+    with mock.patch.object(BaseProvider.__class__, "server_settings", settings_mock):
+        yield ai
+
+
+@pytest.mark.parametrize(
+    "max_history,messages_to_add,expected_size",
+    [
+        # for max_history = 1 we expect to see up to 2 messages (1 human and 1 AI message)
+        (1, 4, 2),
+        # if there is less than `max_history` messages, all should be returned
+        (1, 1, 1),
+        # if no limit is set, all messages should be returned
+        (None, 9, 9),
+    ],
+)
+def test_max_chat_history(ai_extension, max_history, messages_to_add, expected_size):
+    ai = ai_extension
+    ai.default_max_chat_history = max_history
+    ai.initialize_settings()
+    for i in range(messages_to_add):
+        message = BaseMessage(
+            content=f"Test message {i}",
+            type="test",
+            additional_kwargs={HUMAN_MSG_ID_KEY: f"message-{i}"},
+        )
+        ai.settings["llm_chat_memory"].add_message(message)
+
+    assert len(ai.settings["llm_chat_memory"].messages) == expected_size