Support inference and evaluation with Math Code Interpreter (#695)

Co-authored-by: wangzy <wangziyi@pjlab.org.cn>

README.md

@@ -261,7 +261,7 @@ To learn more about data contamination assessment, please check the [contaminati
 ### Agent Evaluation
 
 - To evaluate tool utilization, please refer to [T-Eval](https://github.com/open-compass/T-Eval).
-- For code interpreter evaluation, use the [gsm-8k-agent](https://github.com/open-compass/opencompass/blob/main/configs/datasets/gsm8k/gsm8k_agent_gen_be1606.py) provided in the repository. Additionally, you need to install [Lagent](https://github.com/InternLM/lagent).
+- For code interpreter evaluation, use the [Math Agent Evaluation](agent/README.md) provided in the repository.
 
 ### Subjective Evaluation
 

agent/README.md

@@ -11,7 +11,7 @@ InternLM2-Chat, open sourced on January 17, 2024, further enhances its capabilit
 The results of InternLM2-Chat-20B on math code interpreter is as below:
 
 |                                          | GSM8K | MATH  |
-| :--------------------------------------: | :---: | :--: |
+| :--------------------------------------: | :---: | :---: |
 |            InternLM2-Chat-20B            | 79.6  | 32.5  |
 | InternLM2-Chat-20B with Code Interpreter | 84.5  | 51.2  |
 |            ChatGPT (GPT-3.5)             | 78.2  | 28.0  |
@@ -19,4 +19,69 @@ The results of InternLM2-Chat-20B on math code interpreter is as below:
 
 ## Usages
 
-We offer examples using [Lagent](lagent.md) to build agents based on InternLM2-Chat to call code interpreter or search API. Additionally, we provide an example code using [PAL to evaluate GSM8K math problems](pal_inference.md) with InternLM-Chat-7B.
+We offer an example using [Lagent](lagent.md) to build agents based on InternLM2-Chat to call the code interpreter. Firstly install the extra dependencies:
+
+```bash
+pip install -r requirements.txt
+```
+
+Run the following script to perform inference and evaluation on GSM8K and MATH test.
+
+```bash
+python streaming_inference.py \
+  --backend=lmdeploy \  # For HuggingFace models: hf
+  --model_path=internlm/internlm2-chat-20b \
+  --tp=2 \
+  --temperature=0.0 \
+  --dataset=math \
+  --output_path=math_lmdeploy.jsonl \
+  --do_eval
+```
+
+`output_path` is a jsonl format file to save the inference results. Each line is like
+
+```json
+{
+    "idx": 41, 
+    "query": "The point $(a, b)$ lies on the line with the equation $3x + 2y = 12.$ When $a = 4$, what is the value of $b$?",
+    "gt": "0",
+    "pred": ["0"],
+    "steps": [
+        {
+            "role": "language",
+            "content": ""
+        },
+        {
+            "role": "tool",
+            "content": {
+                "name": "IPythonInteractive",
+                "parameters": {
+                    "command": "```python\nfrom sympy import symbols, solve\n\ndef find_b():\n    x, y = symbols('x y')\n    equation = 3*x + 2*y - 12\n    b = solve(equation.subs(x, 4), y)[0]\n\n    return b\n\nresult = find_b()\nprint(result)\n```"
+                }
+            },
+            "name": "interpreter"
+        },
+        {
+            "role": "environment",
+            "content": "0",
+            "name": "interpreter"
+        },
+        {
+            "role": "language",
+            "content": "The value of $b$ when $a = 4$ is $\\boxed{0}$."
+        }
+    ],
+    "error": null
+}
+```
+
+Once it is prepared, just skip the inference stage as follows.
+
+```bash
+python streaming_inference.py \
+  --output_path=math_lmdeploy.jsonl \
+  --no-do_infer \
+  --do_eval
+```
+
+Please refer to [`streaming_inference.py`](streaming_inference.py) for more information about the arguments.

agent/README_zh-CN.md

@@ -11,7 +11,7 @@ InternLM2-Chat 进一步提高了它在代码解释和通用工具调用方面
 以下是 InternLM2-Chat-20B 在数学代码解释器上的结果。
 
 |                                     | GSM8K | MATH  |
-| :---------------------------------: | :---: | :--: |
+| :---------------------------------: | :---: | :---: |
 | InternLM2-Chat-20B 单纯依靠内在能力 | 79.6  | 32.5  |
 |  InternLM2-Chat-20B 配合代码解释器  | 84.5  | 51.2  |
 |          ChatGPT (GPT-3.5)          | 78.2  | 28.0  |
@@ -19,4 +19,69 @@ InternLM2-Chat 进一步提高了它在代码解释和通用工具调用方面
 
 ## 体验
 
-我们提供了使用 [Lagent](lagent_zh-CN.md) 来基于 InternLM2-Chat 构建智能体调用代码解释器或者搜索等工具的例子。同时，我们也提供了采用 [PAL 评测 GSM8K 数学题](pal_inference_zh-CN.md) InternLM-Chat-7B 的样例。
+我们提供了使用 [Lagent](lagent_zh-CN.md) 来基于 InternLM2-Chat 构建智能体调用代码解释器的例子。首先安装额外依赖：
+
+```bash
+pip install -r requirements.txt
+```
+
+运行以下脚本在 GSM8K 和 MATH 测试集上进行推理和评估：
+
+```bash
+python streaming_inference.py \
+  --backend=lmdeploy \  # For HuggingFace models: hf
+  --model_path=internlm/internlm2-chat-20b \
+  --tp=2 \
+  --temperature=0.0 \
+  --dataset=math \
+  --output_path=math_lmdeploy.jsonl \
+  --do_eval
+```
+
+`output_path` 是一个存储推理结果的 jsonl 格式文件，每行形如：
+
+```json
+{
+    "idx": 41, 
+    "query": "The point $(a, b)$ lies on the line with the equation $3x + 2y = 12.$ When $a = 4$, what is the value of $b$?",
+    "gt": "0",
+    "pred": ["0"],
+    "steps": [
+        {
+            "role": "language",
+            "content": ""
+        },
+        {
+            "role": "tool",
+            "content": {
+                "name": "IPythonInteractive",
+                "parameters": {
+                    "command": "```python\nfrom sympy import symbols, solve\n\ndef find_b():\n    x, y = symbols('x y')\n    equation = 3*x + 2*y - 12\n    b = solve(equation.subs(x, 4), y)[0]\n\n    return b\n\nresult = find_b()\nprint(result)\n```"
+                }
+            },
+            "name": "interpreter"
+        },
+        {
+            "role": "environment",
+            "content": "0",
+            "name": "interpreter"
+        },
+        {
+            "role": "language",
+            "content": "The value of $b$ when $a = 4$ is $\\boxed{0}$."
+        }
+    ],
+    "error": null
+}
+```
+
+如果已经准备好了该文件，可直接跳过推理阶段进行评估：
+
+```bash
+python streaming_inference.py \
+  --output_path=math_lmdeploy.jsonl \
+  --no-do_infer \
+  --do_eval
+```
+
+请参考 [`streaming_inference.py`](streaming_inference.py) 获取更多关于参数的信息。

agent/requirements.txt

@@ -0,0 +1,10 @@
+lmdeploy>=0.2.2
+datasets
+tqdm
+numpy
+pebble
+jsonlines
+sympy==1.12
+antlr4-python3-runtime==4.11.0
+lagent
+einops

agent/streaming_inference.py

@@ -0,0 +1,681 @@
+# flake8: noqa
+# isort: skip_file
+
+# This logic is modified from ToRA:
+#   - https://github.com/microsoft/ToRA
+#
+# Copyright (c) Microsoft Corporation.
+#
+# Permission is hereby granted, free of charge, to any person obtaining a copy
+# of this software and associated documentation files (the "Software"), to deal
+# in the Software without restriction, including without limitation the rights
+# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+# copies of the Software, and to permit persons to whom the Software is
+# furnished to do so, subject to the following conditions:
+#
+# The above copyright notice and this permission notice shall be included in all
+# copies or substantial portions of the Software.
+#
+# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+# SOFTWARE
+
+import argparse
+import multiprocessing
+import os
+import re
+import sys
+import traceback
+from math import isclose
+from typing import Union
+
+import jsonlines
+import numpy as np
+from datasets import load_dataset
+from lagent import (INTERNLM2_META, ActionExecutor, HFTransformer,
+                    Internlm2Agent, Internlm2Protocol, LMDeployPipeline,
+                    get_tool)
+from pebble import ProcessPool
+from sympy import N, simplify
+from sympy.parsing.latex import parse_latex
+from sympy.parsing.sympy_parser import parse_expr
+from tqdm import tqdm
+
+DEFAULT_PROMPT = (
+    'Integrate step-by-step reasoning and Python code to solve math problems '
+    'using the following guidelines:\n'
+    '- Just write jupyter code to solve the problem without giving your thought;\n'
+    r"- Present the final result in LaTeX using a '\boxed{{}}' without any "
+    'units. \n')
+
+
+def parse_args():
+    parser = argparse.ArgumentParser(description='Math Code Interpreter')
+    parser.add_argument('--backend',
+                        type=str,
+                        default='lmdeploy',
+                        help='Which inference framework to use.',
+                        choices=['lmdeploy', 'hf'])
+    parser.add_argument(
+        '--model_path',
+        type=str,
+        default='internlm/internlm2-chat-7b',
+        help='Path or name to the model, could be HuggingFace model specifier.'
+    )
+    parser.add_argument(
+        '--output_path',
+        type=str,
+        required=True,
+        help='Path to save inference results to, should be a `jsonl` file')
+    parser.add_argument('--dataset',
+                        type=str,
+                        default='math',
+                        choices=['gsm8k', 'math'],
+                        help='Dataset for inference')
+    parser.add_argument(
+        '--tp',
+        type=int,
+        default=1,
+        help='Number of tensor parallelism. It may be required in LMDelpoy.')
+    parser.add_argument('--temperature',
+                        type=float,
+                        default=0.1,
+                        help='Temperature in next token prediction')
+    parser.add_argument('--top_p',
+                        type=float,
+                        default=0.8,
+                        help='Parameter for Top-P Sampling.')
+    parser.add_argument('--top_k',
+                        type=int,
+                        default=None,
+                        help='Parameter for Top-K Sampling.')
+    parser.add_argument('--stop_words',
+                        type=str,
+                        default=['<|action_end|>', '<|im_end|>'],
+                        action='append',
+                        help='Stop words')
+    parser.add_argument('--max_new_tokens',
+                        type=int,
+                        default=512,
+                        help='Number of maximum generated tokens.')
+    parser.add_argument(
+        '--do_infer',
+        default=True,
+        action=argparse.BooleanOptionalAction,  # python > 3.8
+        help='Whether to launch model inference.')
+    # parser.add_argument(
+    #     '--no-do_infer',
+    #     dest='do_infer',
+    #     action='store_false',
+    #     help='Disable the inference.'
+    # )
+    parser.add_argument('--do_eval',
+                        default=False,
+                        action='store_true',
+                        help='Whether to evaluate the inference results.')
+    parser.add_argument('--overwrite',
+                        default=False,
+                        action='store_true',
+                        help='Whether to overwrite the existing result file')
+    parser.add_argument('--debug',
+                        default=False,
+                        action='store_true',
+                        help='Only infer the first 50 samples')
+    return parser.parse_args()
+
+
+def _fix_fracs(string):
+    substrs = string.split('\\frac')
+    new_str = substrs[0]
+    if len(substrs) > 1:
+        substrs = substrs[1:]
+        for substr in substrs:
+            new_str += '\\frac'
+            if len(substr) > 0 and substr[0] == '{':
+                new_str += substr
+            else:
+                try:
+                    assert len(substr) >= 2
+                except Exception:
+                    return string
+                a = substr[0]
+                b = substr[1]
+                if b != '{':
+                    if len(substr) > 2:
+                        post_substr = substr[2:]
+                        new_str += '{' + a + '}{' + b + '}' + post_substr
+                    else:
+                        new_str += '{' + a + '}{' + b + '}'
+                else:
+                    if len(substr) > 2:
+                        post_substr = substr[2:]
+                        new_str += '{' + a + '}' + b + post_substr
+                    else:
+                        new_str += '{' + a + '}' + b
+    string = new_str
+    return string
+
+
+def _fix_a_slash_b(string):
+    if len(string.split('/')) != 2:
+        return string
+    a = string.split('/')[0]
+    b = string.split('/')[1]
+    try:
+        if 'sqrt' not in a:
+            a = int(a)
+        if 'sqrt' not in b:
+            b = int(b)
+        assert string == '{}/{}'.format(a, b)
+        new_string = '\\frac{' + str(a) + '}{' + str(b) + '}'
+        return new_string
+    except Exception:
+        return string
+
+
+def _fix_sqrt(string):
+    _string = re.sub(r'\\sqrt(\w+)', r'\\sqrt{\1}', string)
+    return _string
+
+
+def strip_string(string):
+    string = str(string).strip()
+    # linebreaks
+    string = string.replace('\n', '')
+
+    # right "."
+    string = string.rstrip('.')
+
+    # remove inverse spaces
+    string = string.replace('\\!', '')
+    string = string.replace('\\ ', '')
+
+    # replace \\ with \
+    string = string.replace('\\\\', '\\')
+    string = string.replace('\\\\', '\\')
+
+    # replace tfrac and dfrac with frac
+    string = string.replace('tfrac', 'frac')
+    string = string.replace('dfrac', 'frac')
+
+    # remove \left and \right
+    string = string.replace('\\left', '')
+    string = string.replace('\\right', '')
+
+    # Remove unit: miles, dollars if after is not none
+    _string = re.sub(r'\\text{.*?}$', '', string).strip()
+    if _string != '' and _string != string:
+        # print("Warning: unit not removed: '{}' -> '{}'".format(string, _string))
+        string = _string
+
+    # Remove circ (degrees)
+    string = string.replace('^{\\circ}', '')
+    string = string.replace('^\\circ', '')
+
+    # remove dollar signs
+    string = string.replace('\\$', '')
+    string = string.replace('$', '')
+
+    string = string.replace('\\text', '')
+    string = string.replace('x\\in', '')
+
+    # remove percentage
+    string = string.replace('\\%', '')
+    string = string.replace('\%', '')
+    string = string.replace('%', '')
+
+    # " 0." equivalent to " ." and "{0." equivalent to "{." Alternatively, add "0" if "." is the start of the string
+    string = string.replace(' .', ' 0.')
+    string = string.replace('{.', '{0.')
+
+    # cdot
+    string = string.replace('\\cdot', '')
+
+    # inf
+    string = string.replace('infinity', '\\infty')
+    if '\\infty' not in string:
+        string = string.replace('inf', '\\infty')
+    string = string.replace('+\\inity', '\\infty')
+
+    # and
+    string = string.replace('and', '')
+    string = string.replace('\\mathbf', '')
+
+    # use regex to remove \mbox{...}
+    string = re.sub(r'\\mbox{.*?}', '', string)
+
+    # quote
+    string.replace("'", '')
+    string.replace('"', '')
+
+    # i, j
+    if 'j' in string and 'i' not in string:
+        string = string.replace('j', 'i')
+
+    # replace a.000b where b is not number or b is end, with ab, use regex
+    string = re.sub(r'(\d+)\.0+([^\d])', r'\1\2', string)
+    string = re.sub(r'(\d+)\.0+$', r'\1', string)
+
+    # if empty, return empty string
+    if len(string) == 0:
+        return string
+    if string[0] == '.':
+        string = '0' + string
+
+    # to consider: get rid of e.g. "k = " or "q = " at beginning
+    if len(string.split('=')) == 2:
+        if len(string.split('=')[0]) <= 2:
+            string = string.split('=')[1]
+
+    string = _fix_sqrt(string)
+    string = string.replace(' ', '')
+
+    # \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}
+    string = _fix_fracs(string)
+
+    # NOTE: X/Y changed to \frac{X}{Y} in dataset, but in simple cases fix in case the model output is X/Y
+    string = _fix_a_slash_b(string)
+
+    return string
+
+
+def last_boxed_only_string(string):
+    idx = string.rfind('\\boxed')
+    if idx < 0:
+        idx = string.rfind('\\fbox')
+        if idx < 0:
+            return None
+
+    i = idx
+    right_brace_idx = None
+    num_left_braces_open = 0
+    while i < len(string):
+        if string[i] == '{':
+            num_left_braces_open += 1
+        if string[i] == '}':
+            num_left_braces_open -= 1
+            if num_left_braces_open == 0:
+                right_brace_idx = i
+                break
+        i += 1
+
+    if right_brace_idx is None:
+        retval = None
+    else:
+        retval = string[idx:right_brace_idx + 1]
+
+    return retval
+
+
+def extract_answer(pred_str):
+    if 'boxed' not in pred_str:
+        return ''
+    answer = pred_str.split('boxed')[-1]
+    if len(answer) == 0:
+        return ''
+    elif (answer[0] == '{'):
+        stack = 1
+        a = ''
+        for c in answer[1:]:
+            if (c == '{'):
+                stack += 1
+                a += c
+            elif (c == '}'):
+                stack -= 1
+                if (stack == 0): break
+                a += c
+            else:
+                a += c
+    else:
+        a = answer.split('$')[0].strip()
+
+    pred = a.split('\n')[0]
+    if pred != '' and pred[0] == ':':
+        pred = pred[1:]
+    if pred != '' and pred[-1] == '.':
+        pred = pred[:-1]
+    if pred != '' and pred[-1] == '/':
+        pred = pred[:-1]
+    pred = strip_string(pred)
+    return pred
+
+
+def is_digit(s):
+    try:
+        float(str(s).replace(',', ''))
+        return True
+    except ValueError:
+        return False
+
+
+def math_equal(
+    prediction: Union[bool, float, str],
+    reference: Union[float, str],
+    include_percentage: bool = True,
+    is_close: bool = True,
+    tolerance: float = 1e-4,
+    timeout: bool = False,
+) -> bool:
+    """Exact match of math if and only if:
+
+    1. numerical equal: both can convert to float and are equal
+    2. symbolic equal: both can convert to sympy expression and are equal
+    """
+    try:  # 1. numerical equal
+        if is_digit(prediction) and is_digit(reference):
+            prediction = float(str(prediction).replace(',', ''))
+            reference = float(str(reference).replace(',', ''))
+            # number questions
+            if include_percentage:
+                gt_result = [reference / 100, reference, reference * 100]
+            else:
+                gt_result = [reference]
+            for item in gt_result:
+                try:
+                    if is_close:
+                        if isclose(item, prediction, rel_tol=tolerance):
+                            return True
+                    else:
+                        if item == prediction:
+                            return True
+                except Exception:
+                    continue
+            return False
+    except Exception:
+        pass
+
+    if not prediction and prediction not in [0, False]:
+        return False
+
+    # 2. symbolic equal
+    reference = str(reference).strip()
+    prediction = str(prediction).strip()
+
+    ## deal with [], (), {}
+    pred_str, ref_str = prediction, reference
+    if (prediction.startswith('[') and prediction.endswith(']')
+            and not reference.startswith('(')) or (
+                prediction.startswith('(') and prediction.endswith(')')
+                and not reference.startswith('[')):
+        pred_str = pred_str.strip('[]()')
+        ref_str = ref_str.strip('[]()')
+    for s in ['{', '}', '(', ')']:
+        ref_str = ref_str.replace(s, '')
+        pred_str = pred_str.replace(s, '')
+    if pred_str == ref_str:
+        return True
+
+    ## [a, b] vs. [c, d], return a==c and b==d
+    if ((prediction.startswith('[') and prediction.endswith(']')) and
+        (reference.startswith('[') and reference.endswith(']'))
+            or (prediction.startswith('(') and prediction.endswith(')')) and
+        (reference.startswith('(') and reference.endswith(')'))):
+        pred_parts = prediction[1:-1].split(',')
+        ref_parts = reference[1:-1].split(',')
+        if len(pred_parts) == len(ref_parts):
+            if all([
+                    math_equal(pred_parts[i], ref_parts[i], include_percentage,
+                               is_close) for i in range(len(pred_parts))
+            ]):
+                return True
+
+    # symbolic equal with sympy
+    if timeout:
+        if call_with_timeout(symbolic_equal_process, prediction, reference):
+            return True
+    else:
+        if symbolic_equal(prediction, reference):
+            return True
+
+    return False
+
+
+def math_equal_process(param):
+    return math_equal(param[-2], param[-1])
+
+
+def symbolic_equal(a, b):
+
+    def _parse(s):
+        for f in [parse_latex, parse_expr]:
+            try:
+                return f(s)
+            except Exception:
+                pass
+        return s
+
+    a = _parse(a)
+    b = _parse(b)
+
+    try:
+        if simplify(a - b) == 0:
+            return True
+    except Exception:
+        pass
+
+    try:
+        if isclose(N(a), N(b), rel_tol=1e-3):
+            return True
+    except Exception:
+        pass
+    return False
+
+
+def symbolic_equal_process(a, b, output_queue):
+    result = symbolic_equal(a, b)
+    output_queue.put(result)
+
+
+def call_with_timeout(func, *args, timeout=1, **kwargs):
+    output_queue = multiprocessing.Queue()
+    process_args = args + (output_queue, )
+    process = multiprocessing.Process(target=func,
+                                      args=process_args,
+                                      kwargs=kwargs)
+    process.start()
+    process.join(timeout)
+
+    if process.is_alive():
+        process.terminate()
+        process.join()
+        return False
+
+    return output_queue.get()
+
+
+def init_agent(backend: str, model_path: str, tp: int, **kwargs):
+    if backend == 'lmdeploy':
+        model = LMDeployPipeline(path=model_path,
+                                 meta_template=INTERNLM2_META,
+                                 tp=tp,
+                                 **kwargs)
+    elif backend == 'hf':
+        model = HFTransformer(path=model_path,
+                              meta_template=INTERNLM2_META,
+                              **kwargs)
+    else:
+        raise NotImplementedError
+
+    agent = Internlm2Agent(llm=model,
+                           protocol=Internlm2Protocol(
+                               meta_prompt=None,
+                               interpreter_prompt=DEFAULT_PROMPT),
+                           interpreter_executor=ActionExecutor(
+                               actions=[get_tool('IPythonInteractive')]))
+    return agent
+
+
+def predict(args):
+    if args.dataset == 'gsm8k':
+
+        def process(d, k):
+            d['answer'] = re.sub(r'#### (.+)', r'The answer is \1',
+                                 re.sub(r'<<.*?>>', '',
+                                        d['answer'])).replace('$', '')
+            d['idx'] = k
+            d['query'] = d['question'].replace('$', '')
+            d['gt'] = re.search('The answer is (.+)', d['answer'])[1]
+            d['pred'], d['steps'], d['error'] = [], [], None
+            return d
+
+        dataset = load_dataset('gsm8k', 'main',
+                               split='test').map(process, True)
+
+    elif args.dataset == 'math':
+
+        def process(d, k):
+            d['idx'] = k
+            d['query'] = d['problem']
+            gt = extract_answer(d['solution'])
+            if '\\boxed{90\\text{ square\nunits}}' in d['solution']:
+                gt = '90'
+            elif '$6$ is our answer' in d['solution']:
+                gt = '6'
+            elif gt.startswith('x\\in'):
+                gt = gt[len('x\\in'):]
+            gt = strip_string(gt)
+            d['gt'] = gt
+            d['pred'], d['steps'] = [], []
+            d['error'] = None
+            return d
+
+        dataset = load_dataset('lighteval/MATH',
+                               split='test').map(process, True)
+
+    else:
+        raise NotImplementedError
+
+    agent = init_agent(
+        backend=args.backend,
+        model_path=args.model_path,
+        tp=args.tp,
+        temperature=args.temperature,
+        stop_words=args.stop_words,
+        top_p=args.top_p,
+        top_k=args.top_k,
+        max_new_tokens=args.max_new_tokens,
+    )
+    with jsonlines.open(args.output_path, 'w') as f:
+        for item in tqdm(
+                dataset if not args.debug else dataset.select(range(50))):
+            try:
+                ret = agent.chat(item['query'])
+                item['steps'] = ret.inner_steps
+
+                lang = [
+                    step for step in item['steps']
+                    if step['role'] == 'language'
+                ]
+                item['pred'].append('😭' if not lang else
+                                    extract_answer(lang[-1]['content']) or '😭')
+                agent._interpreter_executor.actions[
+                    'IPythonInteractive'].reset()
+            except Exception as e:
+                err = str(traceback.format_exc())
+                print(f'Error processing index {item["idx"]}: {e}\n{err}')
+                item['error'] = err
+            f.write(item)
+
+
+def evaluate(args):
+    samples = [sample for sample in jsonlines.open(args.output_path)]
+    scores = []
+    timeout_cnt = 0
+    with ProcessPool() as pool:
+        future = pool.map(
+            math_equal_process,
+            [(idx, pred, sample['gt']) for idx, sample in enumerate(samples)
+             for pred in sample['pred']],
+            timeout=20,
+        )
+        iterator = future.result()
+        with tqdm(total=len(samples), desc='Evaluate') as progress_bar:
+            while True:
+                try:
+                    result = next(iterator)
+                    scores.append(result)
+                except StopIteration:
+                    break
+                except TimeoutError as error:
+                    print(error)
+                    scores.append(False)
+                    timeout_cnt += 1
+                except Exception as error:
+                    print(error.__traceback__)
+                    sys.exit()
+                progress_bar.update(1)
+
+    idx = 0
+    score_mat = []
+    for sample in samples:
+        sample['score'] = scores[idx:idx + len(sample['pred'])]
+        assert len(sample['score']) == len(sample['pred'])
+        score_mat.append(sample['score'])
+        idx += len(sample['pred'])
+
+    max_len = max([len(s) for s in score_mat])
+
+    for i, s in enumerate(score_mat):
+        if len(s) < max_len:
+            score_mat[i] = s + [s[-1]] * (max_len - len(s))  # pad
+
+    # output mean of each column of scores
+    col_means = np.array(score_mat).mean(axis=0)
+    mean_score = list(np.round(col_means * 100, decimals=1))
+
+    result_str = f'Num samples: {len(samples)}\n' \
+        f'Num scores: {len(scores)}\n' \
+        f'Sum scores: {sum(scores)}\n' \
+        f'Timeout samples: {timeout_cnt}\n' \
+        f"Empty samples: {len([s for s in samples if not s['pred'][-1]])}\n" \
+        f'Mean score: {mean_score}\n'
+
+    # each type score
+    if 'type' in samples[0]:
+        type_scores = {}
+        for sample in samples:
+            if sample['type'] not in type_scores:
+                type_scores[sample['type']] = []
+            type_scores[sample['type']].append(sample['score'][-1])
+        type_scores = {
+            k: np.round(np.array(v).mean() * 100, decimals=1)
+            for k, v in type_scores.items()
+        }
+        type_scores = {
+            k: v
+            for k, v in sorted(type_scores.items(), key=lambda item: item[0])
+        }
+        result_str += f'Type scores: {type_scores}\n'
+
+    print(result_str)
+
+
+if __name__ == '__main__':
+    args = parse_args()
+    if args.do_infer and os.path.exists(
+            args.output_path) and not args.overwrite:
+        args.do_infer = False
+        print(f'File {args.output_path} already exists. '
+              f'Please add the `--overwrite` flag if needed.')
+    if args.do_infer:
+        predict(args)
+    if args.do_eval:
+        if not args.do_infer:
+            evaluate(args)
+        else:
+            import subprocess
+
+            res = subprocess.run(
+                [
+                    sys.executable, __file__, '--output_path',
+                    args.output_path, '--no-do_infer', '--do_eval'
+                ],
+                capture_output=True,
+                text=True,
+                check=True,
+            )
+            print(res.stdout)