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196 lines
4.8 KiB
Python
196 lines
4.8 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 pytest
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from transformers import AutoTokenizer
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from tests.reasoning.utils import run_reasoning_extraction
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from vllm.reasoning import ReasoningParser, ReasoningParserManager
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parser_name = "minimax_m2_append_think"
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end_token = "</think>"
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# MiniMax M2 model path
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REASONING_MODEL_NAME = "MiniMaxAI/MiniMax-M2"
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@pytest.fixture(scope="module")
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def minimax_m2_tokenizer():
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return AutoTokenizer.from_pretrained(REASONING_MODEL_NAME)
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# =============================================================================
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# MiniMaxM2AppendThinkReasoningParser behavior:
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# - Prepends <think> to the beginning of the output
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# - Does NOT separate reasoning and content
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# - Returns everything as content (with <think> prepended)
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# - reasoning is always None
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#
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# This parser is used when you want to keep the raw output with <think> added
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# =============================================================================
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# Case: simple output with end token
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SIMPLE_OUTPUT = {
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"output": "This is reasoning</think>This is response",
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"reasoning": None,
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"content": "<think>This is reasoning</think>This is response",
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"is_reasoning_end": True,
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}
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# Case: output without end token (reasoning in progress)
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NO_END_TOKEN = {
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"output": "This is reasoning in progress",
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"reasoning": None,
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"content": "<think>This is reasoning in progress",
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"is_reasoning_end": False,
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}
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# Case: only end token
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ONLY_END_TOKEN = {
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"output": "</think>This is response",
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"reasoning": None,
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"content": "<think></think>This is response",
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"is_reasoning_end": True,
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}
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# Case: multiple lines
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MULTIPLE_LINES = {
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"output": "Line 1\nLine 2</think>Response 1\nResponse 2",
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"reasoning": None,
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"content": "<think>Line 1\nLine 2</think>Response 1\nResponse 2",
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"is_reasoning_end": True,
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}
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# Case: empty output (non-streaming prepends <think>)
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EMPTY = {
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"output": "",
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"reasoning": None,
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"content": "<think>",
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"is_reasoning_end": False,
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}
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# Case: empty output streaming (no tokens = no output)
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EMPTY_STREAMING = {
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"output": "",
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"reasoning": None,
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"content": None,
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"is_reasoning_end": False,
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}
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# Case: special characters
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SPECIAL_CHARS = {
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"output": "Let me think... 1+1=2</think>Yes!",
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"reasoning": None,
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"content": "<think>Let me think... 1+1=2</think>Yes!",
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"is_reasoning_end": True,
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}
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# Case: code in output
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CODE_OUTPUT = {
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"output": "```python\nprint('hi')\n```</think>Here's the code.",
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"reasoning": None,
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"content": "<think>```python\nprint('hi')\n```</think>Here's the code.",
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"is_reasoning_end": True,
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}
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TEST_CASES = [
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pytest.param(
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False,
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SIMPLE_OUTPUT,
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id="simple_output",
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),
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pytest.param(
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True,
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SIMPLE_OUTPUT,
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id="simple_output_streaming",
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),
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pytest.param(
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False,
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NO_END_TOKEN,
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id="no_end_token",
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),
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pytest.param(
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True,
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NO_END_TOKEN,
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id="no_end_token_streaming",
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),
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pytest.param(
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False,
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ONLY_END_TOKEN,
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id="only_end_token",
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),
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pytest.param(
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True,
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ONLY_END_TOKEN,
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id="only_end_token_streaming",
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),
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pytest.param(
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False,
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MULTIPLE_LINES,
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id="multiple_lines",
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),
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pytest.param(
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True,
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MULTIPLE_LINES,
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id="multiple_lines_streaming",
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),
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pytest.param(
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False,
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EMPTY,
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id="empty",
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),
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pytest.param(
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True,
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EMPTY_STREAMING,
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id="empty_streaming",
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),
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pytest.param(
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False,
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SPECIAL_CHARS,
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id="special_chars",
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),
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pytest.param(
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True,
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SPECIAL_CHARS,
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id="special_chars_streaming",
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),
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pytest.param(
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False,
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CODE_OUTPUT,
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id="code_output",
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),
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pytest.param(
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True,
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CODE_OUTPUT,
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id="code_output_streaming",
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),
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]
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@pytest.mark.parametrize("streaming, param_dict", TEST_CASES)
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def test_reasoning(
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streaming: bool,
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param_dict: dict,
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minimax_m2_tokenizer,
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):
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output = minimax_m2_tokenizer.tokenize(param_dict["output"])
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# decode everything to tokens
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output_tokens: list[str] = [
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minimax_m2_tokenizer.convert_tokens_to_string([token]) for token in output
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]
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parser: ReasoningParser = ReasoningParserManager.get_reasoning_parser(parser_name)(
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minimax_m2_tokenizer
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)
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reasoning, content = run_reasoning_extraction(
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parser, output_tokens, streaming=streaming
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)
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assert reasoning == param_dict["reasoning"]
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assert content == param_dict["content"]
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# Test is_reasoning_end
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output_ids = minimax_m2_tokenizer.convert_tokens_to_ids(output)
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is_reasoning_end = parser.is_reasoning_end(output_ids)
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assert is_reasoning_end == param_dict["is_reasoning_end"]
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