Fix: handle non-string tool call arguments in memory consolidation

Fixes #1042. When the LLM returns tool call arguments as a dict or
JSON string instead of parsed values, memory consolidation would fail
with "TypeError: data must be str, not dict".

Changes:
- Add type guard in MemoryStore.consolidate() to parse string arguments
  and reject unexpected types gracefully
- Add regression tests covering dict args, string args, and edge cases
This commit is contained in:
alairjt
2026-02-23 13:59:49 -03:00
parent 25f0a236fd
commit 3eeac4e8f8
2 changed files with 154 additions and 0 deletions

View File

@@ -125,6 +125,13 @@ class MemoryStore:
return False
args = response.tool_calls[0].arguments
# Some providers return arguments as a JSON string instead of dict
if isinstance(args, str):
args = json.loads(args)
if not isinstance(args, dict):
logger.warning("Memory consolidation: unexpected arguments type %s", type(args).__name__)
return False
if entry := args.get("history_entry"):
if not isinstance(entry, str):
entry = json.dumps(entry, ensure_ascii=False)

View File

@@ -0,0 +1,147 @@
"""Test MemoryStore.consolidate() handles non-string tool call arguments.
Regression test for https://github.com/HKUDS/nanobot/issues/1042
When memory consolidation receives dict values instead of strings from the LLM
tool call response, it should serialize them to JSON instead of raising TypeError.
"""
import json
from pathlib import Path
from unittest.mock import AsyncMock, MagicMock
import pytest
from nanobot.agent.memory import MemoryStore
from nanobot.providers.base import LLMResponse, ToolCallRequest
def _make_session(message_count: int = 30, memory_window: int = 50):
"""Create a mock session with messages."""
session = MagicMock()
session.messages = [
{"role": "user", "content": f"msg{i}", "timestamp": "2026-01-01 00:00"}
for i in range(message_count)
]
session.last_consolidated = 0
return session
def _make_tool_response(history_entry, memory_update):
"""Create an LLMResponse with a save_memory tool call."""
return LLMResponse(
content=None,
tool_calls=[
ToolCallRequest(
id="call_1",
name="save_memory",
arguments={
"history_entry": history_entry,
"memory_update": memory_update,
},
)
],
)
class TestMemoryConsolidationTypeHandling:
"""Test that consolidation handles various argument types correctly."""
@pytest.mark.asyncio
async def test_string_arguments_work(self, tmp_path: Path) -> None:
"""Normal case: LLM returns string arguments."""
store = MemoryStore(tmp_path)
provider = AsyncMock()
provider.chat = AsyncMock(
return_value=_make_tool_response(
history_entry="[2026-01-01] User discussed testing.",
memory_update="# Memory\nUser likes testing.",
)
)
session = _make_session(message_count=60)
result = await store.consolidate(session, provider, "test-model", memory_window=50)
assert result is True
assert store.history_file.exists()
assert "[2026-01-01] User discussed testing." in store.history_file.read_text()
assert "User likes testing." in store.memory_file.read_text()
@pytest.mark.asyncio
async def test_dict_arguments_serialized_to_json(self, tmp_path: Path) -> None:
"""Issue #1042: LLM returns dict instead of string — must not raise TypeError."""
store = MemoryStore(tmp_path)
provider = AsyncMock()
provider.chat = AsyncMock(
return_value=_make_tool_response(
history_entry={"timestamp": "2026-01-01", "summary": "User discussed testing."},
memory_update={"facts": ["User likes testing"], "topics": ["testing"]},
)
)
session = _make_session(message_count=60)
result = await store.consolidate(session, provider, "test-model", memory_window=50)
assert result is True
assert store.history_file.exists()
history_content = store.history_file.read_text()
parsed = json.loads(history_content.strip())
assert parsed["summary"] == "User discussed testing."
memory_content = store.memory_file.read_text()
parsed_mem = json.loads(memory_content)
assert "User likes testing" in parsed_mem["facts"]
@pytest.mark.asyncio
async def test_string_arguments_as_raw_json(self, tmp_path: Path) -> None:
"""Some providers return arguments as a JSON string instead of parsed dict."""
store = MemoryStore(tmp_path)
provider = AsyncMock()
# Simulate arguments being a JSON string (not yet parsed)
response = LLMResponse(
content=None,
tool_calls=[
ToolCallRequest(
id="call_1",
name="save_memory",
arguments=json.dumps({
"history_entry": "[2026-01-01] User discussed testing.",
"memory_update": "# Memory\nUser likes testing.",
}),
)
],
)
provider.chat = AsyncMock(return_value=response)
session = _make_session(message_count=60)
result = await store.consolidate(session, provider, "test-model", memory_window=50)
assert result is True
assert "User discussed testing." in store.history_file.read_text()
@pytest.mark.asyncio
async def test_no_tool_call_returns_false(self, tmp_path: Path) -> None:
"""When LLM doesn't use the save_memory tool, return False."""
store = MemoryStore(tmp_path)
provider = AsyncMock()
provider.chat = AsyncMock(
return_value=LLMResponse(content="I summarized the conversation.", tool_calls=[])
)
session = _make_session(message_count=60)
result = await store.consolidate(session, provider, "test-model", memory_window=50)
assert result is False
assert not store.history_file.exists()
@pytest.mark.asyncio
async def test_skips_when_few_messages(self, tmp_path: Path) -> None:
"""Consolidation should be a no-op when messages < keep_count."""
store = MemoryStore(tmp_path)
provider = AsyncMock()
session = _make_session(message_count=10)
result = await store.consolidate(session, provider, "test-model", memory_window=50)
assert result is True
provider.chat.assert_not_called()