app.py

import gradio as gr

from dataclasses import dataclass
from concurrent.futures import ThreadPoolExecutor, TimeoutError

import os
import re
import subprocess
import tempfile
import json
import datasets
import random
from typing import Tuple, Dict, Any, List
from sympy import N, simplify
from sympy.parsing.latex import parse_latex
from openai import OpenAI


# client = OpenAI(
#     base_url=os.environ.get("SERVER_URL"),
#     api_key=os.environ.get("HF_TOKEN"),
# )


@dataclass
class Config:
    model_id: str  # SELECT MODEL
    revision: str  # SELECT REVISION

    # Append an optional system prompt to each problem
    system_prompt: str

    # Number of samples to generate per problem
    num_samples: int
    num_generations: int
    # Generation parameters
    do_sample: bool
    temperature: float
    top_p: float
    top_k: int
    max_new_tokens: int
    restart_on_fail: bool

    # Enable 4-bit quantization
    is_quantized: bool

    # Run on train or test data?
    is_submission: bool = True if os.getenv("KAGGLE_IS_COMPETITION_RERUN") else False
    validation_set: str = "kaggle-validation-set-medium"

    notebook_time_limit: int = 9 * 60 * 60 - 15 * 60  # 9 hours - 15 minute buffer

    # Debug by solving only the first problem
    debug: bool = False

    # Push solutions to the Hub
    push_to_hub: bool = False


class PythonREPL:
    def __init__(self, timeout=5):
        self.timeout = timeout

    def execute(self, query: str) -> Tuple[bool, str]:
        query = "import math\nimport numpy as np\nimport sympy as sp\n" + query
        query = query.strip().split("\n")
        if "print(" not in query[-1]:
            if "#" in query[-1]:
                query[-1] = query[-1].split("#")[0]
            query[-1] = "print(" + query[-1] + ")"
        query = "\n".join(query)

        with tempfile.TemporaryDirectory() as temp_dir:
            temp_file_path = os.path.join(temp_dir, "tmp.py")

            with open(temp_file_path, "w") as f:
                f.write(query)

            result = subprocess.run(
                ["python3", temp_file_path],
                capture_output=True,
                check=False,
                text=True,
                timeout=self.timeout,
            )

            if result.returncode == 0:
                output = result.stdout
                return True, output.strip()
            else:
                error_msg = result.stderr.strip()
                msgs = error_msg.split("\n")
                new_msgs = []
                want_next = False
                for m in msgs:
                    if "Traceback" in m:
                        new_msgs.append(m)
                    elif m == msgs[-1]:
                        new_msgs.append(m)
                    elif temp_file_path in m:
                        st = m.index('"/') + 1 if '"/' in m else 0
                        ed = m.index(temp_file_path) + 1 if temp_file_path in m else None
                        clr = m[st:ed] if not ed else m[st:]
                        m = m.replace(clr, "")
                        new_msgs.append(m)
                        want_next = True
                    elif want_next:
                        new_msgs.append(m)
                        want_next = False
                error_msg = "\n".join(new_msgs)
                return False, error_msg.strip()

    def __call__(self, query: str) -> Tuple[bool, str]:
        with ThreadPoolExecutor() as executor:
            future = executor.submit(self.execute, query)
            try:
                return future.result(timeout=self.timeout)
            except TimeoutError:
                return False, f"Timed out after {self.timeout} seconds."


def execute_completion(
    executor: PythonREPL,
    completion: str,
    return_status: bool = False,
    last_code_block: bool = False,
) -> str | Tuple[str, bool]:
    # executions = ["!" + code for code in re.findall(r"```bash(.*?)```", completion, re.DOTALL) if "!" not in code]
    executions = re.findall(r"```python(.*?)```", completion, re.DOTALL)

    if len(executions) == 0:  # directly return cot result
        return completion, False if return_status else completion
    else:
        if last_code_block:
            executions = [executions[-1]]

        # Python
        execution_outputs = []
        successes = []
        for code in executions:
            success = False

            if "subprocess" in code:
                output = "subprocess is not allowed"
                execution_outputs.append(output)
                successes.append(success)
                continue

            if "venv" in code:
                output = "venv is not allowed"
                execution_outputs.append(output)
                successes.append(success)
                continue

            try:
                success, output = executor(code)
            except TimeoutError as e:
                print("time out")
                output = e

            if not success and not return_status:
                output = ""

            execution_outputs.append(output)
            successes.append(success)

        output = str(execution_outputs[-1]).strip()
        success = successes[-1]

        if return_status:
            return output, success
        else:
            return output


def postprocess_completion(
    text: str, return_status: bool = False, last_code_block=False, timeout=5
) -> str | Tuple[str, bool]:
    executor = PythonREPL(timeout=timeout)

    result = execute_completion(executor, text, return_status=return_status, last_code_block=last_code_block)
    del executor

    return result


def apply_template(example: Dict[str, Any], prompt: str) -> Dict[str, Any]:
    return prompt.format(example["prompt"], "{}")


def last_boxed_only_string(string):
    """
    Extracts the last LaTeX boxed or framed expression from a string.
    Args:
        string (str): The input string containing LaTeX expressions.
    Returns:
        str or None: The last boxed or framed expression, if found;
        otherwise, None.
    """

    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 remove_boxed(s):
    """
    Removes the LaTeX boxed command, returning the content inside the braces.
    Args:
        s (str): The string containing a LaTeX boxed expression.
    Returns:
        str or None: The content inside the boxed command, if valid;
        otherwise, None.
    """

    left = "\\boxed{"
    try:
        assert s[: len(left)] == left
        assert s[-1] == "}"
        length = len(left)
        return s[length:-1]
    except Exception:
        return None


def extract_boxed_answer(pred_str, strip_double_curly_brace=False):
    """
    Extracts the answer from a LaTeX boxed expression within
    a prediction string.
    Args:
        pred_str (str): The string containing one or more LaTeX
        boxed expressions.
        strip_double_curly_brace (bool): If True, removes an additional
        layer of braces.
    Returns:
        str or None: The extracted answer, if any; otherwise, None.
    """

    boxed_str = last_boxed_only_string(pred_str)
    if boxed_str is None:
        return None
    answer = remove_boxed(boxed_str)
    if answer is None:
        return None
    if strip_double_curly_brace:
        match = re.match("^\{(.*)\}$", answer)  # noqa: W605
        if match:
            answer = match.group(1)
    return answer


def normalize_final_answer(final_answer: str) -> str:
    """
    Normalizes a final answer string by removing or replacing various LaTeX
    and text elements.
    Args:
        final_answer (str): The answer string to normalize.
    Returns:
        str: The normalized answer string.
    """

    match = re.search(r"(.*?)Problem:", final_answer, flags=re.S)
    if match:
        final_answer = match.group(1)  # 返回匹配的第一部分，即"Problem"之前的所有文本
    """Normalize a final answer to a quantitative reasoning question."""
    # final_answer = final_answer.split('=')[-1]
    SUBSTITUTIONS = [
        ("an ", ""),
        ("a ", ""),
        (".$", "$"),
        ("\\$", ""),
        (r"\ ", ""),
        (" ", ""),
        ("mbox", "text"),
        (",\\text{and}", ","),
        ("\\text{and}", ","),
        ("\\text{m}", "\\text{}"),
        ("\\le", "<"),
    ]
    REMOVED_EXPRESSIONS = [
        "square",
        "ways",
        "integers",
        "dollars",
        "mph",
        "inches",
        "ft",
        "hours",
        "km",
        "units",
        "\\ldots",
        "sue",
        "points",
        "feet",
        "minutes",
        "digits",
        "cents",
        "degrees",
        "cm",
        "gm",
        "pounds",
        "meters",
        "meals",
        "edges",
        "students",
        "childrentickets",
        "multiples",
        "\\text{s}",
        "\\text{.}",
        "\\text{\ns}",
        "\\text{}^2",
        "\\text{}^3",
        "\\text{\n}",
        "\\text{}",
        r"\mathrm{th}",
        r"^\circ",
        r"^{\circ}",
        r"\;",
        r",\!",
        "{,}",
        '"',
        "\\dots",
        "\n",
        "\r",
        "\f",
        "\%",
    ]
    for before, after in SUBSTITUTIONS:
        final_answer = final_answer.replace(before, after)
    for expr in REMOVED_EXPRESSIONS:
        final_answer = final_answer.replace(expr, "")

    # Extract answer that is in LaTeX math, is bold,
    # is surrounded by a box, etc.
    final_answer = re.sub(r"(\\text\{)(.*?)(\})", "\\2", final_answer)
    final_answer = re.sub(r"(\\textbf\{)(.*?)(\})", "\\2", final_answer)
    final_answer = re.sub(r"(\\overline\{)(.*?)(\})", "\\2", final_answer)
    final_answer = re.sub(r"(\\boxed\{)(.*)(\})", "\\2", final_answer)
    assert "\n" not in final_answer
    assert "\r" not in final_answer
    assert "\f" not in final_answer
    if len(re.findall(r"finalansweris(.*)", final_answer)) > 0:
        final_answer = re.findall(r"finalansweris(.*)", final_answer)[-1]

    if len(re.findall(r"answer?is:?(.*)", final_answer)) > 0:
        final_answer = re.findall(r"answer?is:?(.*)", final_answer)[-1]

    if len(re.findall(r"oxed\{(.*?)\}", final_answer)) > 0:
        final_answer = re.findall(r"oxed\{(.*?)\}", final_answer)[-1]

    if len(re.findall(r"\$(.*?)\$", final_answer)) > 0:
        final_answer = re.findall(r"\$(.*?)\$", final_answer)[-1]
    final_answer = final_answer.strip()
    if "rac" in final_answer and "\\frac" not in final_answer:
        final_answer = final_answer.replace("rac", "\\frac")

    final_answer = re.sub(r"(frac)([^{])(.)", "frac{\\2}{\\3}", final_answer)
    final_answer = re.sub(r"(sqrt)([^{])", "sqrt{\\2}", final_answer)
    final_answer = final_answer.replace("$", "")

    if final_answer.replace(",", "").isdigit():
        final_answer = final_answer.replace(",", "")

    return final_answer


def naive_parse(answer: str) -> str:
    """
    Extracts and returns the numeric digits from the input string, processing them in reverse order
    until a non-numeric character is encountered after encountering the first numeric character.

    Args:
        answer (str): The input string to parse.

    Returns:
        str: A string consisting of the numeric digits extracted from the input, in their original order.

    Example:
        >>> naive_parse("abc123def")
        '123'
        >>> naive_parse("def456ghi")
        '456'
        >>> naive_parse("no numbers here")
        ''
    """
    out = []
    start = False
    end = False
    for l in reversed(list(answer)):
        if l in "0123456789" and not end:
            start = True
            out.append(l)
        else:
            if start:
                end = True

    out = reversed(out)
    return "".join(out)


def validate_answer_is_numeric(x: str | int | float) -> int:
    FLOAT_TOLERANCE = 0.2
    try:
        x = round(float(x))
        f = float(x)
        if abs(x - f) > FLOAT_TOLERANCE:
            x = -1
    except Exception:
        x = -1
    return x


def filter_answers(answers: List[str]) -> List[int]:
    formatted_answers = [validate_answer_is_numeric(a) for a in answers]

    # Filter for non-negative answers
    formatted_answers = [a for a in formatted_answers if a >= 0]
    # Compute modulo
    formatted_answers = [a % 1_000 for a in formatted_answers]
    # less than 2.1 billion or cannot convert to C int (32-bit)
    formatted_answers = [a for a in formatted_answers if a <= 999]
    return formatted_answers


def check_sympy_equivalence(ref_answer: str, model_answer: str) -> bool:
    def do_answers_match(ref_answer: str, model_answer: str) -> bool:
        ref_sympy = parse_latex(ref_answer)
        model_sympy = parse_latex(model_answer)
        diff = simplify(ref_sympy - model_sympy)
        return True if -1e-12 < N(diff) < 1e-12 or diff.is_zero else False

    try:
        result = do_answers_match(ref_answer, model_answer)
        return result
    except Exception as e:
        print(e)
        return False


def check_string_match(ref_answer: str, model_answer: str) -> bool:
    try:
        return ref_answer == model_answer
    except Exception as e:
        print(e)
    return False


def check_answer(ref_answer: str, model_answer: str) -> bool:
    # check if strings are the same
    correct = check_string_match(ref_answer, model_answer)
    if correct:
        return True

    # use the sympy library to check if the expressions are the same
    correct = check_sympy_equivalence(ref_answer, model_answer)
    if correct:
        return True

    return False


debug = False
model_id = "Numina-Math-7B"
revision = "main"
system_prompt = "{}"
validation_set = "kaggle-validation-set-medium"
is_submission = True
num_samples = 4
num_generations = 4
temperature = 0.8
is_quantized = False
restart_on_fail = False
top_p = 1.0
top_k = 0
max_new_tokens = 2048
# Papermill related variables
push_to_hub = False
notebook_name = ""

config = Config(
    debug=debug,
    push_to_hub=push_to_hub,
    model_id=model_id,
    revision=revision,
    system_prompt=system_prompt,
    validation_set=validation_set,
    is_quantized=is_quantized,
    restart_on_fail=restart_on_fail,
    is_submission=is_submission,
    num_samples=num_samples,
    num_generations=num_generations,
    do_sample=True,
    temperature=temperature,
    top_p=top_p,
    top_k=top_k,
    max_new_tokens=max_new_tokens,
)
print(f"=== Running submission with config ===\n\n{config}")


def generate(message, temperature):
    """
    Generates a chat completion response by streaming data from the client chat model.

    This function streams the response from the client chat model and yields the content
    of the response chunk by chunk. If an error occurs, it yields the error message.

    Parameters:
    message (str): The input message to be sent to the chat model.
    temperature (float): The sampling temperature to use. Higher values mean the model will take more risks.

    Yields:
    tuple: A tuple containing the content of the response and a boolean flag indicating if an error occurred.
           If no error occurred, the boolean flag will be False and the content will be the response text.
           If an error occurred, the boolean flag will be True and the content will be the error message.
    """
    stream = client.chat.completions.create(
        model="tgi",
        messages=message,
        stream=True,
        max_tokens=1024,
        stop=["```output\n"],
        temperature=temperature,
        timeout=30,
    )

    response = stream.response

    # The reason why the library method is not used here is that if an error occurs,
    #    the returned data will not be a stream, and using the official library will result in an error.
    for chunk in response.iter_bytes():
        chunk = chunk.decode("utf-8")
        chune_json = json.loads(chunk.replace("data:", ""))
        try:
            if "error" in chune_json and chune_json["error"]:
                yield chune_json["error"], True
                break

            content = chune_json["choices"][0]["delta"]["content"]
            if content is not None:
                yield content, False
        except Exception as e:
            print(f"func: generate error occurred\njson:{chune_json}\nerror:{e}")
            yield "", True


def get_majority_text(data):
    from collections import Counter

    # Count the frequency of each answer in model_answers
    answer_counts = Counter(data["model_answers"])

    # Find the majority response
    majority_response = answer_counts.most_common(1)[0][0]

    # Find the index of the first occurrence of the majority response
    majority_index = data["model_answers"].index(majority_response)

    # Return the corresponding text in gen_texts
    return data["gen_texts"][majority_index]


def extract_solution(text):
    # Split the text at "### Solution:"
    parts = text.split("### Solution:", 1)
    if len(parts) > 1:
        # Return everything after "### Solution:"
        return parts[1].strip()
    else:
        # Return an empty string if "### Solution:" is not found
        return ""


def process_code(
    example: Dict[str, Any],
    config: Config,
    restart_on_fail: bool = False,
    last_step: bool = False,
) -> Dict[str, Any]:
    gen_text = example["gen_texts"]
    num_python_blocks = len(re.findall(r"```python(.*?)```", gen_text, re.DOTALL))

    if num_python_blocks == 0:
        if restart_on_fail:
            print("no code has ever been generated, RESTARTING")
            # reset the text to the original
            example["gen_texts"] = example["text"]
        else:
            print("no code has ever been generated, STOP")
            example["should_prune"] = True
            example["has_code"] = False
        return example

    if gen_text[-10:] != "```output\n" and ("answer is" in gen_text[-100:] or "\\boxed" in gen_text[-100:]):
        num_output_blocks = len(re.findall(r"```output(.*?)```", gen_text, re.DOTALL))
        if num_output_blocks == 0:
            print("the model hallucinated the code answer")
            example["should_prune"] = True
            return example

        if "boxed" in gen_text[-100:]:
            try:
                answer = normalize_final_answer(extract_boxed_answer(gen_text[-100:]))
            except Exception:
                answer = "-1"
        else:
            answer = normalize_final_answer(gen_text[-100:])

        example["model_answers"] = answer
        if not config.is_submission:
            example["corrects"] = check_answer(example["ground_truth"], answer)
        example["should_prune"] = True
        print("Answer is: ", answer, example["ground_truth"], example["corrects"])
        return example

    if last_step:
        # no point in continuing if we are at the last step
        return example

    if gen_text[-10:] != "```output\n":
        # something else has gone wrong with the generation
        print("warning: output block not found: ", gen_text[-40:])
        if restart_on_fail:
            example["gen_texts"] = example["text"]
        else:
            example["should_prune"] = True
        return example

    code_result, status = postprocess_completion(gen_text, return_status=True, last_code_block=True)
    # add the code result for the next round of generation
    TRUNCATION_LIMIT = 200
    if len(code_result) > TRUNCATION_LIMIT:
        code_result = code_result[:TRUNCATION_LIMIT] + " ... (output truncated)"
    example["gen_texts"] = gen_text + f"{code_result}\n```"

    return example


def solve_problem(problem, temperature, progress=gr.Progress()):
    problem = apply_template({"prompt": problem}, prompt=config.system_prompt)
    print(f"Problem: {problem}")

    sample = {
        "problem": problem,  # not used for the submission TODO Remove
        "ground_truth": "unknown",  # not used for the submission TODO Remove
        "text": "## Solution:\n",
        "gen_texts": "## Solution:\n",  # used to store all the generated text
        "should_prune": False,
        "problem_index": -1,  # not used for the submission TODO Remove
        "model_answers": "-1",
        "has_code": True,
        "corrects": False,  # not used for the submission TODO Remove
    }

    for step in progress.tqdm(
        range(config.num_generations), desc="Generating candidates"
    ):  # Depth of the tree (e.g. 6 steps = 5 code blocks)

        step_reponse = sample["gen_texts"]

        messages = [
            {"role": "user", "content": sample["problem"]},
            {"role": "assistant", "content": sample["gen_texts"]},
        ]

        for reponse_message, error in generate(messages, temperature):
            if reponse_message is not None:
                step_reponse += reponse_message
                yield step_reponse

                if error:
                    return

        sample["gen_texts"] = step_reponse

        # TODO: Maybe it should just return the result of running the code
        sample = process_code(
            sample,
            config=config,
            restart_on_fail=config.restart_on_fail,
            last_step=(step == (config.num_generations - 1)),
        )
        sample["gen_texts"] = sample["gen_texts"] + "\n"

        run_code_reponse = sample["gen_texts"].replace(step_reponse, "")

        for output_mseeage in run_code_reponse:
            if output_mseeage is not None:
                step_reponse += output_mseeage
                yield step_reponse

        if sample["should_prune"]:
            break

    yield sample["gen_texts"]


example_data = datasets.load_dataset(
    "AI-MO/kaggle-validation-set-medium-extended",
    split="train",
    use_auth_token=os.environ.get("HF_DATASET_TOKEN", None),
)


def get_random_problems():
    examples = random.sample(list(example_data), 2)
    problems = [ex["problem"] for ex in examples]
    return problems[0], problems[1]


def copy_problem_to_input(problem):
    return problem


def update_problems():
    problem_1_text, problem_2_text = get_random_problems()
    return (
        problem_1_text[:100] + "..." if len(problem_1_text) > 100 else problem_1_text,
        problem_2_text[:100] + "..." if len(problem_2_text) > 100 else problem_2_text,
        problem_1_text,
        problem_2_text,
    )


def clear():
    problem_1_display, problem_2_display, problem_1_full, problem_2_full = update_problems()
    return "", 0.1, "", problem_1_display, problem_2_display, problem_1_full, problem_2_full


with open("app.css", "r") as f:
    css = f.read()

latex_delimiters = [
    {"left": "[", "right": "]", "display": True},
]

with gr.Blocks(css=css, title="Math Olympiad Solver") as demo:
    with gr.Row(elem_classes="title"):
        gr.HTML("Math Olympiad Solver", elem_classes="title-content")

    with gr.Row(elem_classes="sub-title"):
        gr.HTML("Here may need to add some description string", elem_classes="sub-title-content")

    with gr.Row(elem_classes="main-area"):
        with gr.Column(scale=1, elem_classes="left"):
            with gr.Row(elem_classes="probelm-example-container"):
                with gr.Blocks(elem_classes="probelm-example-title"):
                    gr.HTML("Probelm example", elem_classes="probelm-example-title-content")

                with gr.Blocks(elem_classes="action-container"):
                    gr.HTML("another", elem_classes="probelm-example-another")
                    gr.HTML("copy", elem_classes="probelm-example-copy")

                with gr.Row(elem_classes="copy-icon-container"):
                    gr.Markdown(
                        value="Problem example 2",
                        latex_delimiters=latex_delimiters,
                        elem_classes="probelm-example-content",
                    )

            with gr.Accordion("Advanced Options", open=False):
                temperature = gr.Slider(minimum=0.0, maximum=1.0, value=0.1, step=0.1, label="Temperature")

            inp = gr.Textbox(placeholder="Problem", label="Problem input", lines=5)

            with gr.Row():
                btn = gr.Button("Run")
                btn_clear = gr.Button("Clear")

        with gr.Column(scale=1, elem_classes="right"):
            gr.HTML("Solution", elem_classes="solution-title-content")
            out = gr.Markdown(latex_delimiters=latex_delimiters)

if __name__ == "__main__":
    demo.queue(default_concurrency_limit=5).launch()