In-code documentation update

Evol_Instruct/breadth.py

@@ -8,6 +8,19 @@
 
 
 def createBreadthPrompt(instruction):
+	"""
+	Creates a breadth prompt by combining a base instruction with a given instruction.
+
+	Parameters
+	----------
+	instruction : str
+		The given instruction to be included in the prompt.
+
+	Returns
+	-------
+	prompt : str
+		The created breadth prompt.
+	"""
 	prompt = base_instruction
 	prompt += "#Given Prompt#: \r\n {} \r\n".format(instruction)
 	prompt += "#Created Prompt#:\r\n"

Evol_Instruct/depth.py

@@ -9,25 +9,80 @@
 
 
 def createConstraintsPrompt(instruction):
+	"""
+	Creates a prompt for adding constraints/requirements to a given instruction.
+
+	Parameters
+	----------
+	instruction : str
+		The given instruction to which constraints/requirements will be added.
+
+	Returns
+	-------
+	prompt : str
+		The prompt for adding constraints/requirements to the given instruction.
+	"""
 	prompt = base_instruction.format("Please add one more constraints/requirements into #The Given Prompt#'")
 	prompt += "#The Given Prompt#: \r\n {} \r\n".format(instruction)
 	prompt += "#Rewritten Prompt#:\r\n"
 	return prompt
 
 def createDeepenPrompt(instruction):
+	"""
+	Creates a deepened prompt by adding a rewritten prompt to the given instruction.
+
+	Parameters
+	----------
+	instruction : str
+		The given prompt that contains inquiries about certain issues.
+
+	Returns
+	-------
+	prompt : str
+		The deepened prompt that includes the given prompt and a rewritten prompt.
+
+	Notes
+	-----
+	The depth and breadth of the inquiry can be increased by adding a rewritten prompt to the given prompt.
+	"""
 	prompt = base_instruction.format("If #The Given Prompt# contains inquiries about certain issues, the depth and breadth of the inquiry can be increased.")
 	prompt += "#The Given Prompt#: \r\n {} \r\n".format(instruction)
 	prompt += "#Rewritten Prompt#:\r\n"
 	return prompt
 
 def createConcretizingPrompt(instruction):
+	"""
+	Creates a concretizing prompt by replacing general concepts with more specific concepts.
+
+	Parameters
+	----------
+	instruction : str
+		The original instruction to be concretized.
+
+	Returns
+	-------
+	prompt : str
+		The concretizing prompt with the given instruction and rewritten prompt.
+	"""
 	prompt = base_instruction.format("Please replace general concepts with more specific concepts.")
 	prompt += "#The Given Prompt#: \r\n {} \r\n".format(instruction)
 	prompt += "#Rewritten Prompt#:\r\n"
 	return prompt
 
-
 def createReasoningPrompt(instruction):
+	"""
+	Creates a reasoning prompt by rewriting the given prompt to explicitly request multiple-step reasoning.
+
+	Parameters
+	----------
+	instruction : str
+		The given prompt that needs to be rewritten.
+
+	Returns
+	-------
+	prompt : str
+		The rewritten prompt that explicitly requests multiple-step reasoning.
+	"""
 	prompt = base_instruction.format("If #The Given Prompt# can be solved with just a few simple thinking processes, you can rewrite it to explicitly request multiple-step reasoning.")
 	prompt += "#The Given Prompt#: \r\n {} \r\n".format(instruction)
 	prompt += "#Rewritten Prompt#:\r\n"

Evol_Instruct/openai_access.py

@@ -5,7 +5,33 @@
 
 
 def get_oai_completion(prompt):
+    """
+    Retrieves OpenAI GPT-3.5-Turbo completion for the given prompt.
 
+    Parameters
+    ----------
+    prompt : str
+        The input prompt for which completion is requested.
+
+    Returns
+    -------
+    gpt_output : str or None
+        The completion generated by the OpenAI GPT-3.5-Turbo model, or None if an error occurs.
+
+    Notes
+    -----
+    This function sends a request to the OpenAI API to generate completion for the given prompt
+    using the GPT-3.5-Turbo model. It handles various types of errors and retries the request
+    in case of a timeout error.
+
+    Raises
+    ------
+    None
+
+    See Also
+    --------
+    openai.ChatCompletion.create
+    """
     try: 
         response = openai.ChatCompletion.create(
   model="gpt-3.5-turbo",
@@ -47,6 +73,32 @@ def get_oai_completion(prompt):
         return get_oai_completion(prompt)
 
 def call_chatgpt(ins):
+    """
+    Calls the OpenAI GPT-3.5-Turbo model to generate completion for the given input.
+
+    Parameters
+    ----------
+    ins : str
+        The input prompt for which completion is requested.
+
+    Returns
+    -------
+    ans : str
+        The completion generated by the OpenAI GPT-3.5-Turbo model.
+
+    Notes
+    -----
+    This function repeatedly calls the `get_oai_completion` function to retrieve completion
+    for the given input prompt. It retries the request if an error occurs, with a maximum of 15 retries.
+
+    Raises
+    ------
+    None
+
+    See Also
+    --------
+    get_oai_completion
+    """
     success = False
     re_try_count = 15
     ans = ''

WizardMath/inference/grader.py

@@ -12,6 +12,23 @@
 
 
 def is_digit(s):
+    """
+    Checks if the input can be converted to a float.
+
+    Parameters
+    ----------
+    s : any
+        The input to check.
+
+    Returns
+    -------
+    bool
+        True if the input can be converted to a float, False otherwise.
+
+    Raises
+    ------
+    None
+    """
     try:
         float(str(s).replace(",", ""))
         return True
@@ -25,9 +42,37 @@ def math_equal(prediction: Union[bool, float, str],
                 timeout: bool = False,
                 ) -> bool:
     """
+    Determines if two math expressions are equal.
+
     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
+
+    Parameters
+    ----------
+    prediction : Union[bool, float, str]
+        The predicted value.
+
+    reference : Union[float, str]
+        The reference value.
+
+    include_percentage : bool, optional
+        Whether to include percentage variations, by default True.
+
+    is_close : bool, optional
+        Whether to consider close match using relative tolerance, by default True.
+
+    timeout : bool, optional
+        Whether to apply timeout to the symbolic equal check, by default False.
+
+    Returns
+    -------
+    bool
+        True if the values are equal, False otherwise.
+
+    Raises
+    ------
+    None
     """
     try: # 1. numerical equal
         if is_digit(prediction) and is_digit(reference):
@@ -92,10 +137,47 @@ def math_equal(prediction: Union[bool, float, str],
 
 
 def math_equal_process(param):
+    """
+    Calls `math_equal` function with the provided parameters.
+
+    Parameters
+    ----------
+    param : tuple
+        Tuple containing parameters for `math_equal` function.
+
+    Returns
+    -------
+    bool
+        True if the values are equal, False otherwise.
+
+    Raises
+    ------
+    None
+    """
     return math_equal(param[-2], param[-1])
 
 
 def symbolic_equal(a, b):
+    """
+    Checks if two expressions are symbolically equal using sympy.
+
+    Parameters
+    ----------
+    a : str
+        First expression.
+
+    b : str
+        Second expression.
+
+    Returns
+    -------
+    bool
+        True if the expressions are equal, False otherwise.
+
+    Raises
+    ------
+    None
+    """
     def _parse(s):
         for f in [parse_latex, parse_expr]:
             try:
@@ -120,12 +202,60 @@ def _parse(s):
     return False
 
 
-def symbolic_equal_process(a, b, output_queue):  
+def symbolic_equal_process(a, b, output_queue):
+    """
+    Checks if two expressions are symbolically equal using sympy.
+
+    Parameters
+    ----------
+    a : str
+        First expression.
+
+    b : str
+        Second expression.
+
+    output_queue : multiprocessing.Queue
+        Queue to store the result.
+
+    Returns
+    -------
+    None
+
+    Raises
+    ------
+    None
+    """
     result = symbolic_equal(a, b)
     output_queue.put(result)  
 
 
-def call_with_timeout(func, *args, timeout=1, **kwargs):  
+def call_with_timeout(func, *args, timeout=1, **kwargs):
+    """
+    Calls a function with a specified timeout.
+
+    Parameters
+    ----------
+    func : function
+        The function to call.
+
+    timeout : int, optional
+        Timeout value in seconds, by default 1.
+
+    *args : list
+        Positional arguments for the function.
+
+    **kwargs : dict
+        Keyword arguments for the function.
+
+    Returns
+    -------
+    bool
+        True if the function call succeeds within the timeout, False otherwise.
+
+    Raises
+    ------
+    None
+    """ 
     output_queue = multiprocessing.Queue()  
     process_args = args + (output_queue,)  
     process = multiprocessing.Process(target=func, args=process_args, kwargs=kwargs)