forked from phoenix-oss/llama-stack-mirror
feat: [new open benchmark] Math 500 (#1538)
## What does this PR do? Created a new math_500 open-benchmark based on OpenAI's [Let's Verify Step by Step](https://arxiv.org/abs/2305.20050) paper and hugging face's [HuggingFaceH4/MATH-500](https://huggingface.co/datasets/HuggingFaceH4/MATH-500) dataset. The challenge part of this benchmark is to parse the generated and expected answer and verify if they are same. For the parsing part, we refer to [Minerva: Solving Quantitative Reasoning Problems with Language Models](https://research.google/blog/minerva-solving-quantitative-reasoning-problems-with-language-models/). To simply the parse logic, as the next step, we plan to also refer to what [simple-eval](https://github.com/openai/simple-evals) is doing, using llm as judge to check if the generated answer matches the expected answer or not ## Test Plan on sever side, spin up a server with open-benchmark template `llama stack run llama_stack/templates/open-benchamrk/run.yaml` on client side, issue an open benchmark eval request `llama-stack-client --endpoint xxx eval run-benchmark "meta-reference-math-500" --model-id "meta-llama/Llama-3.3-70B-Instruct" --output-dir "/home/markchen1015/" --num-examples 20` and get ther aggregated eval results <img width="238" alt="Screenshot 2025-03-10 at 7 57 04 PM" src="https://github.com/user-attachments/assets/2c9da042-3b70-470e-a7c4-69f4cc24d1fb" /> check the generated answer and the related scoring and they make sense
This commit is contained in:
parent
ff853ccc38
commit
e3edca7739
6 changed files with 470 additions and 2 deletions
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@ -23,10 +23,11 @@ from llama_stack.providers.utils.common.data_schema_validator import (
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from .config import BasicScoringConfig
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from .scoring_fn.equality_scoring_fn import EqualityScoringFn
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from .scoring_fn.regex_parser_math_response_scoring_fn import RegexParserMathResponseScoringFn
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from .scoring_fn.regex_parser_scoring_fn import RegexParserScoringFn
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from .scoring_fn.subset_of_scoring_fn import SubsetOfScoringFn
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FIXED_FNS = [EqualityScoringFn, SubsetOfScoringFn, RegexParserScoringFn]
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FIXED_FNS = [EqualityScoringFn, SubsetOfScoringFn, RegexParserScoringFn, RegexParserMathResponseScoringFn]
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class BasicScoringImpl(
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@ -0,0 +1,27 @@
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# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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from llama_stack.apis.common.type_system import NumberType
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from llama_stack.apis.scoring_functions import (
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AggregationFunctionType,
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RegexParserScoringFnParams,
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ScoringFn,
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)
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MATH_ANSWER_REGEXES = [r".*final answer is:?\s*\$\\boxed{(?P<X>.*)}\$"]
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regex_parser_math_response = ScoringFn(
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identifier="basic::regex_parser_math_response",
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description="For math related benchmarks, extract answer from the generated response and expected_answer and see if they match",
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return_type=NumberType(),
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provider_id="basic",
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provider_resource_id="regex-parser-math-response",
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params=RegexParserScoringFnParams(
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parsing_regexes=MATH_ANSWER_REGEXES,
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aggregation_functions=[AggregationFunctionType.accuracy],
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),
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)
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@ -0,0 +1,66 @@
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# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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from typing import Any, Dict, Optional
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from llama_stack.apis.scoring import ScoringResultRow
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from llama_stack.apis.scoring_functions import ScoringFnParams, ScoringFnParamsType
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from llama_stack.providers.utils.scoring.base_scoring_fn import RegisteredBaseScoringFn
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from ..utils.math_utils import first_answer, normalize_final_answer, try_evaluate_frac, try_evaluate_latex
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from .fn_defs.regex_parser_math_response import (
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regex_parser_math_response,
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)
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class RegexParserMathResponseScoringFn(RegisteredBaseScoringFn):
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"""
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A scoring_fn for math benchamrks that parses answer from generated response according to context and check match with expected_answer.
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"""
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def __init__(self, *args, **kwargs) -> None:
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super().__init__(*args, **kwargs)
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self.supported_fn_defs_registry = {
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regex_parser_math_response.identifier: regex_parser_math_response,
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}
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async def score_row(
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self,
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input_row: Dict[str, Any],
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scoring_fn_identifier: Optional[str] = None,
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scoring_params: Optional[ScoringFnParams] = None,
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) -> ScoringResultRow:
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assert scoring_fn_identifier is not None, "Scoring function identifier not found."
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fn_def = self.supported_fn_defs_registry[scoring_fn_identifier]
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if scoring_params is not None:
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fn_def.params = scoring_params
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assert fn_def.params is not None and fn_def.params.type == ScoringFnParamsType.regex_parser.value, (
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f"RegexParserScoringFnParams not found for {fn_def}."
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)
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expected_answer = input_row["expected_answer"]
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generated_answer = input_row["generated_answer"]
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parsing_regexes = fn_def.params.parsing_regexes
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assert len(parsing_regexes) == 1, (
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"Only one parsing regex is supported for regex_parser_math_response scoring function."
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)
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parsing_regexes = fn_def.params.parsing_regexes[0]
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normalized_generated_answer = normalize_final_answer(
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first_answer(generated_answer),
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parsing_regexes,
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match_first=True,
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)
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normalized_generated_answer = try_evaluate_frac(try_evaluate_latex(normalized_generated_answer))
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normalized_expected_answer = normalize_final_answer(expected_answer, r".*")
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normalized_expected_answer = try_evaluate_frac(try_evaluate_latex(normalized_expected_answer))
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score = 1.0 if normalized_generated_answer == normalized_expected_answer else 0.0
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return {
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"score": score,
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}
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330
llama_stack/providers/inline/scoring/basic/utils/math_utils.py
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330
llama_stack/providers/inline/scoring/basic/utils/math_utils.py
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# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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import re
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from typing import Sequence
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from llama_stack.providers.utils.scoring.basic_scoring_utils import time_limit
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# from minerva
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SUBSTITUTIONS = [
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("an ", ""),
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("a ", ""),
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(".$", "$"),
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("\\$", ""),
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(r"\ ", ""),
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(" ", ""),
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("mbox", "text"),
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(",\\text{and}", ","),
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("\\text{and}", ","),
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("\\text{m}", "\\text{}"),
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]
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REMOVED_EXPRESSIONS = [
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"square",
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"ways",
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"integers",
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"dollars",
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"mph",
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"inches",
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"ft",
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"hours",
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"km",
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"units",
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"\\ldots",
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"sue",
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"points",
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"feet",
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"minutes",
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"digits",
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"cents",
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"degrees",
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"cm",
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"gm",
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"pounds",
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"meters",
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"meals",
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"edges",
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"students",
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"childrentickets",
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"multiples",
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"\\text{s}",
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"\\text{.}",
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"\\text{\ns}",
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"\\text{}^2",
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"\\text{}^3",
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"\\text{\n}",
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"\\text{}",
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r"\mathrm{th}",
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r"^\circ",
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r"^{\circ}",
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r"\;",
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r",\!",
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"{,}",
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'"',
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"\\dots",
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]
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def try_evaluate_frac(expression: str, fmt: str = "0.2e") -> str:
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if isinstance(expression, float):
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return expression
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new_expression = f"{expression}"
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regex = re.compile(r"\\frac{([^}]+)}{([^}]+)}")
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for match in re.finditer(regex, expression):
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try:
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value = float(match.group(1)) / float(match.group(2))
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new_expression = new_expression.replace(
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match.group(),
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f"{{value:{fmt}}}".format(value=value),
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1,
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)
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except Exception:
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continue
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return new_expression
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def try_evaluate_latex(expression: str, fmt: str = ".2e") -> str:
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try:
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with time_limit(seconds=5):
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from sympy.parsing.latex import parse_latex
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value = parse_latex(expression).evalf() # type: ignore
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return f"{{value:{fmt}}}".format(value=value)
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except Exception:
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return expression
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def first_answer(text: str, markers: Sequence[str] = ("Q:", "A:")) -> str:
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for marker in markers:
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text = text.split(marker)[0]
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return text
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def extract_result_from_boxed(answer: str) -> str:
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box_start = "\\boxed"
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# format is `\\boxed <value>$` or `\\boxed{<value>}`, with potential white spaces framing `<value>`
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start = answer.rfind(box_start)
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if start < 0:
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return ""
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answer = answer[start + len(box_start) :].strip()
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ends_with_curly = answer.startswith("{")
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i = 0
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open_braces = 0
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while i < len(answer):
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if answer[i] == "{":
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open_braces += 1
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elif answer[i] == "}":
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open_braces -= 1
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if open_braces == 0:
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if ends_with_curly:
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answer = answer[: i + 1].strip()
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break
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elif answer[i] == "$":
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answer = answer[:i].strip()
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break
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i += 1
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else:
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return ""
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# remove extra curly braces
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while True:
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if answer.startswith("{") and answer.endswith("}"):
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answer = answer[1:-1].strip()
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else:
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break
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return answer
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# from minerva paper + _normalise_result from xavierm
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def normalize_final_answer(final_answer: str, regex_pattern: str, match_first: bool = True) -> str:
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"""Extract and normalize a final answer to a quantitative reasoning question."""
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match = re.findall(regex_pattern, final_answer)
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extraction: str
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if len(match) > 0:
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if match_first:
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extraction = match[0]
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else:
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extraction = match[-1]
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else:
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extraction = extract_result_from_boxed(final_answer)
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if len(extraction) == 0:
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return final_answer
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else:
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final_answer = extraction
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final_answer = final_answer.split("=")[-1]
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for before, after in SUBSTITUTIONS:
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final_answer = final_answer.replace(before, after)
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for expr in REMOVED_EXPRESSIONS:
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final_answer = final_answer.replace(expr, "")
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# Extract answer that is in LaTeX math, is bold,
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# is surrounded by a box, etc.
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final_answer = re.sub(r"(.*?)(\$)(.*?)(\$)(.*)", "$\\3$", final_answer)
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final_answer = re.sub(r"(\\text\{)(.*?)(\})", "\\2", final_answer)
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final_answer = re.sub(r"(\\textbf\{)(.*?)(\})", "\\2", final_answer)
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final_answer = re.sub(r"(\\overline\{)(.*?)(\})", "\\2", final_answer)
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final_answer = re.sub(r"(\\boxed\{)(.*)(\})", "\\2", final_answer)
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# Normalize shorthand TeX:
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# \fracab -> \frac{a}{b}
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# \frac{abc}{bef} -> \frac{abc}{bef}
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# \fracabc -> \frac{a}{b}c
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# \sqrta -> \sqrt{a}
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# \sqrtab -> sqrt{a}b
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final_answer = re.sub(r"(frac)([^{])(.)", "frac{\\2}{\\3}", final_answer)
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final_answer = re.sub(r"(sqrt)([^{])", "sqrt{\\2}", final_answer)
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final_answer = final_answer.replace("$", "")
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# Normalize 100,000 -> 100000
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if final_answer.replace(",", "").isdigit():
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final_answer = final_answer.replace(",", "")
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# If the final answer is a single letter in parentheses, remove the parentheses
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# Example: (a) -> a (but not (ab) -> ab)
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if re.match(r"\([a-zA-Z]\)", final_answer):
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final_answer = final_answer[1]
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return _normalise_result(final_answer)
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def _normalise_result(string: str) -> str:
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# linebreaks
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string = string.replace("\n", "")
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# remove inverse spaces
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string = string.replace("\\!", "")
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# replace \\ with \
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string = string.replace("\\\\", "\\")
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# replace tfrac and dfrac with frac
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string = string.replace("cfrac", "frac")
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string = string.replace("tfrac", "frac")
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string = string.replace("dfrac", "frac")
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# remove \left and \right
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string = string.replace("\\left", "")
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string = string.replace("\\le", "")
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string = string.replace("\\right", "")
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# Remove circ (degrees)
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string = string.replace("^{\\circ}", "")
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string = string.replace("^\\circ", "")
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# remove dollar signs
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string = string.replace("\\$", "")
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# remove units (on the right)
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string = _remove_right_units(string)
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# remove percentage
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string = string.replace("\\%", "")
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string = string.replace(r"\%", "")
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# " 0." equivalent to " ." and "{0." equivalent to "{." Alternatively, add "0" if "." is the start of the string
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string = string.replace(" .", " 0.")
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string = string.replace("{.", "{0.")
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# if empty, return empty string
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if len(string) == 0:
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return string
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if string[0] == ".":
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string = "0" + string
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# to consider: get rid of e.g. "k = " or "q = " at beginning
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string = string.split("=")[-1]
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# fix sqrt3 --> sqrt{3}
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string = _fix_sqrt(string)
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# remove spaces
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string = string.replace(" ", "")
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# \frac1b or \frac12 --> \frac{1}{b} and \frac{1}{2}, etc. Even works with \frac1{72} (but not \frac{72}1). Also does a/b --> \\frac{a}{b}
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string = _fix_fracs(string)
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# manually change 0.5 --> \frac{1}{2}
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if string == "0.5":
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string = "\\frac{1}{2}"
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# NOTE: X/Y changed to \frac{X}{Y} in dataset, but in simple cases fix in case the model output is X/Y
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string = _fix_a_slash_b(string)
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return string
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def _remove_right_units(string: str) -> str:
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# "\\text{ " only ever occurs (at least in the val set) when describing units
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try:
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if "\\text{ " in string:
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splits = string.split("\\text{ ")
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assert len(splits) == 2
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return splits[0]
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else:
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return string
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except AssertionError:
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return string
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def _fix_sqrt(string: str) -> str:
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if "\\sqrt" not in string:
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return string
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splits = string.split("\\sqrt")
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new_string = splits[0]
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for split in splits[1:]:
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if len(split) == 0:
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return string
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if split[0] != "{":
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a = split[0]
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new_substr = "\\sqrt{" + a + "}" + split[1:]
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else:
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new_substr = "\\sqrt" + split
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new_string += new_substr
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return new_string
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def _fix_fracs(string: str) -> str:
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substrs = string.split("\\frac")
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new_str = substrs[0]
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if len(substrs) > 1:
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substrs = substrs[1:]
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for substr in substrs:
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new_str += "\\frac"
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if len(substr) == 0:
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return string
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if substr[0] == "{":
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new_str += substr
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else:
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try:
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assert len(substr) >= 2
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except AssertionError:
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return string
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a = substr[0]
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b = substr[1]
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if b != "{":
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if len(substr) > 2:
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post_substr = substr[2:]
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new_str += "{" + a + "}{" + b + "}" + post_substr
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else:
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new_str += "{" + a + "}{" + b + "}"
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else:
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if len(substr) > 2:
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post_substr = substr[2:]
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new_str += "{" + a + "}" + b + post_substr
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else:
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new_str += "{" + a + "}" + b
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string = new_str
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return string
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def _fix_a_slash_b(string: str) -> str:
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if len(string.split("/")) != 2:
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return string
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a = string.split("/")[0]
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b = string.split("/")[1]
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try:
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ia = int(a)
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ib = int(b)
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assert string == "{}/{}".format(ia, ib)
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new_string = "\\frac{" + str(ia) + "}{" + str(ib) + "}"
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return new_string
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except (ValueError, AssertionError):
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return string
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26
llama_stack/providers/utils/scoring/basic_scoring_utils.py
Normal file
26
llama_stack/providers/utils/scoring/basic_scoring_utils.py
Normal file
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# Copyright (c) Meta Platforms, Inc. and affiliates.
|
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# All rights reserved.
|
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#
|
||||
# This source code is licensed under the terms described in the LICENSE file in
|
||||
# the root directory of this source tree.
|
||||
import contextlib
|
||||
import signal
|
||||
from types import FrameType
|
||||
from typing import Iterator, Optional
|
||||
|
||||
|
||||
class TimeoutError(Exception):
|
||||
pass
|
||||
|
||||
|
||||
@contextlib.contextmanager
|
||||
def time_limit(seconds: float) -> Iterator[None]:
|
||||
def signal_handler(signum: int, frame: Optional[FrameType]) -> None:
|
||||
raise TimeoutError("Timed out!")
|
||||
|
||||
signal.setitimer(signal.ITIMER_REAL, seconds)
|
||||
signal.signal(signal.SIGALRM, signal_handler)
|
||||
try:
|
||||
yield
|
||||
finally:
|
||||
signal.setitimer(signal.ITIMER_REAL, 0)
|
|
@ -33,7 +33,7 @@ providers:
|
|||
provider_type: remote::together
|
||||
config:
|
||||
url: https://api.together.xyz/v1
|
||||
api_key: ${env.TOGETHER_API_KEY}
|
||||
api_key: ${env.TOGETHER_API_KEY:}
|
||||
vector_io:
|
||||
- provider_id: sqlite-vec
|
||||
provider_type: inline::sqlite-vec
|
||||
|
@ -190,6 +190,21 @@ datasets:
|
|||
type: string
|
||||
chat_completion_input:
|
||||
type: string
|
||||
- dataset_id: math_500
|
||||
provider_id: huggingface
|
||||
url:
|
||||
uri: https://huggingface.co/datasets/llamastack/math_500
|
||||
metadata:
|
||||
path: llamastack/math_500
|
||||
name:
|
||||
split: test
|
||||
dataset_schema:
|
||||
input_query:
|
||||
type: string
|
||||
expected_answer:
|
||||
type: string
|
||||
chat_completion_input:
|
||||
type: string
|
||||
scoring_fns: []
|
||||
benchmarks:
|
||||
- benchmark_id: meta-reference-simpleqa
|
||||
|
@ -201,6 +216,9 @@ benchmarks:
|
|||
- benchmark_id: meta-reference-gpqa-cot
|
||||
dataset_id: gpqa_cot
|
||||
scoring_functions: ["basic::regex_parser_multiple_choice_answer"]
|
||||
- benchmark_id: meta-reference-math-500
|
||||
dataset_id: math_500
|
||||
scoring_functions: ["basic::regex_parser_math_response"]
|
||||
tool_groups:
|
||||
- toolgroup_id: builtin::websearch
|
||||
provider_id: tavily-search
|
||||
|
|
Loading…
Add table
Add a link
Reference in a new issue