biondizzle
4556945525
V3.2 __init__ sets self.tool_call_start_token and self.tool_call_end_token as instance attributes with function_calls tag values, shadowing the V4 class-level attributes that use tool_calls tags. Re-assign after super().
34 lines
1.4 KiB
Python
34 lines
1.4 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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import regex as re
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from vllm.tool_parsers.deepseekv32_tool_parser import DeepSeekV32ToolParser
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class DeepSeekV4ToolParser(DeepSeekV32ToolParser):
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"""
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DeepSeek V4 DSML tool parser.
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V4 keeps the V3.2 DSML invoke/parameter grammar, but wraps tool calls in
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``<｜DSML｜tool_calls>`` instead of ``<｜DSML｜function_calls>``.
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"""
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tool_call_start_token: str = "<｜DSML｜tool_calls>"
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tool_call_end_token: str = "</｜DSML｜tool_calls>"
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def __init__(self, tokenizer, tools=None):
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super().__init__(tokenizer, tools)
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# The V3.2 __init__ overwrites the class-level start/end tokens
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# with instance attributes set to "function_calls". Re-override
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# them to the V4 "tool_calls" tags so _extract_content(),
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# _extract_invoke_regions(), etc. match the correct tags.
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self.tool_call_start_token = "<｜DSML｜tool_calls>"
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self.tool_call_end_token = "</｜DSML｜tool_calls>"
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self.tool_calls_start_token = self.tool_call_start_token
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# Recompile regexes with the V4 tool_calls tags instead of
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# the V3.2 function_calls tags that the base class hardcodes.
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self.tool_call_complete_regex = re.compile(
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r"<｜DSML｜tool_calls>(.*?)</｜DSML｜tool_calls>", re.DOTALL
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)
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