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https://github.com/mudler/LocalAI.git
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7a3583b52c
Two bugs broke OpenAI-style tool calling on the MLX backend (and any
Python backend sharing backend/python/common), reproduced end-to-end on
LocalAI v4.5.5 with the metal-mlx backend and
mlx-community/Qwen3.5-2B-MLX-8bit.
messages_to_dicts left each tool call's function.arguments as the raw
OpenAI-wire JSON string. HuggingFace chat templates (e.g. Qwen3.5)
iterate arguments as a mapping (.items()), so any request whose history
contained a prior assistant tool_calls message failed with HTTP 500
"Generation failed: Can only get item pairs from a mapping." — breaking
every agent loop on its second turn. Decode the string back into a dict
so the template sees a mapping.
split_reasoning returned ("", text) whenever the opening think tag was
absent. Models like Qwen3.5 open the assistant turn already inside
thinking, so the generated text carries only the closing </think>; the
whole chain-of-thought leaked into content. When the opener is missing
but the closer is present, treat everything before the closer as
reasoning.
Adds platform-independent unit tests under backend/python/common
(stdlib-only, no MLX/venv required, following parent_watch_test.py).
Assisted-by: Claude Code:claude-opus-4-8
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
76 lines
2.7 KiB
Python
76 lines
2.7 KiB
Python
"""Unit tests for the mlx/mlx-vlm shared helpers (mlx_utils.py).
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Run standalone (Python standard library only, no backend venv needed):
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python3 -m unittest mlx_utils_test
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These mirror the server-less helper tests in backend/python/mlx/test.py
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(TestSharedHelpers), but live here so they run on any platform: the mlx
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test module imports grpc/backend_pb2 at import time and needs the MLX venv,
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whereas mlx_utils only needs the standard library.
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"""
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import types
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import unittest
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from mlx_utils import parse_tool_calls, split_reasoning
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class TestSplitReasoning(unittest.TestCase):
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def test_both_tags(self):
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r, c = split_reasoning(
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"<think>step 1\nstep 2</think>The answer is 42.", "<think>", "</think>"
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)
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self.assertEqual(r, "step 1\nstep 2")
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self.assertEqual(c, "The answer is 42.")
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def test_implicit_opener_only_closing_tag(self):
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# Qwen3.5 opens the assistant turn already inside thinking, so the
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# output carries only the closing tag; everything before it is reasoning.
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r, c = split_reasoning(
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"The user is asking about the weather.\n</think>\n\nThe weather in Rome is sunny.",
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"<think>",
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"</think>",
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)
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self.assertEqual(r, "The user is asking about the weather.")
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self.assertEqual(c, "The weather in Rome is sunny.")
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def test_no_tags_at_all(self):
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r, c = split_reasoning("just text", "<think>", "</think>")
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self.assertEqual(r, "")
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self.assertEqual(c, "just text")
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def test_empty_think_end_and_no_opener_match(self):
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# No think_end to anchor on, and the opener is absent → return unchanged.
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r, c = split_reasoning("no opener here", "<think>", "")
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self.assertEqual(r, "")
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self.assertEqual(c, "no opener here")
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def test_empty_text(self):
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r, c = split_reasoning("", "<think>", "</think>")
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self.assertEqual(r, "")
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self.assertEqual(c, "")
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class TestParseToolCalls(unittest.TestCase):
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def test_with_shim(self):
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tm = types.SimpleNamespace(
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tool_call_start="<tool_call>",
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tool_call_end="</tool_call>",
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parse_tool_call=lambda body, tools: {
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"name": "get_weather",
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"arguments": {"location": body.strip()},
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},
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)
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calls, remaining = parse_tool_calls(
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"Sure: <tool_call>Paris</tool_call>", tm, tools=None
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)
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self.assertEqual(len(calls), 1)
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self.assertEqual(calls[0]["name"], "get_weather")
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self.assertEqual(calls[0]["arguments"], '{"location": "Paris"}')
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self.assertEqual(calls[0]["index"], 0)
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self.assertNotIn("<tool_call>", remaining)
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if __name__ == "__main__":
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unittest.main()
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