import inspect
from inspect import Parameter, getsource, signature
from typing import Any, Callable, Dict, Mapping, Optional, Tuple, Type
from docstring_parser import parse
from jsonschema.exceptions import SchemaError
from pydantic import BaseModel, create_model
from pydantic.fields import FieldInfo
from jsonschema.validators import Draft202012Validator as JSONValidator
import re
import sys
import os
# FIXME
sys.path.append(os.curdir)
from logging_service import logger
def to_pascal(snake: str) -> str:
"""Convert a snake_case string to PascalCase.
Args:
snake (str): The snake_case string to be converted.
Returns:
str: The converted PascalCase string.
"""
# Check if the string is already in PascalCase
if re.match(r'^[A-Z][a-zA-Z0-9]*([A-Z][a-zA-Z0-9]*)*$', snake):
return snake
# Remove leading and trailing underscores
snake = snake.strip('_')
# Replace multiple underscores with a single one
snake = re.sub('_+', '_', snake)
# Convert to PascalCase
return re.sub(
'_([0-9A-Za-z])',
lambda m: m.group(1).upper(),
snake.title(),
)
def get_pydantic_object_schema(pydantic_params: Type[BaseModel]) -> Dict:
r"""Get the JSON schema of a Pydantic model.
Args:
pydantic_params (Type[BaseModel]): The Pydantic model class to retrieve
the schema for.
Returns:
dict: The JSON schema of the Pydantic model.
"""
return pydantic_params.model_json_schema()
def _remove_title_recursively(data, parent_key=None):
r"""Recursively removes the 'title' key from all levels of a nested
dictionary, except when 'title' is an argument name in the schema.
"""
if isinstance(data, dict):
# Only remove 'title' if it's not an argument name
if parent_key not in [
"properties",
"$defs",
"items",
"allOf",
"oneOf",
"anyOf",
]:
data.pop("title", None)
# Recursively process each key-value pair
for key, value in data.items():
_remove_title_recursively(value, parent_key=key)
elif isinstance(data, list):
# Recursively process each element in the list
for item in data:
_remove_title_recursively(item, parent_key=parent_key)
def get_openai_tool_schema(func: Callable) -> Dict[str, Any]:
r"""Generates an OpenAI JSON schema from a given Python function.
This function creates a schema compatible with OpenAI's API specifications,
based on the provided Python function. It processes the function's
parameters, types, and docstrings, and constructs a schema accordingly.
Note:
- Each parameter in `func` must have a type annotation; otherwise, it's
treated as 'Any'.
- Variable arguments (*args) and keyword arguments (**kwargs) are not
supported and will be ignored.
- A functional description including a brief and detailed explanation
should be provided in the docstring of `func`.
- All parameters of `func` must be described in its docstring.
- Supported docstring styles: ReST, Google, Numpydoc, and Epydoc.
Args:
func (Callable): The Python function to be converted into an OpenAI
JSON schema.
Returns:
Dict[str, Any]: A dictionary representing the OpenAI JSON schema of
the provided function.
See Also:
`OpenAI API Reference
<https://platform.openai.com/docs/api-reference/assistants/object>`_
"""
params: Mapping[str, Parameter] = signature(func).parameters
fields: Dict[str, Tuple[type, FieldInfo]] = {}
for param_name, p in params.items():
param_type = p.annotation
param_default = p.default
param_kind = p.kind
param_annotation = p.annotation
# Variable parameters are not supported
if (
param_kind == Parameter.VAR_POSITIONAL
or param_kind == Parameter.VAR_KEYWORD
):
continue
# If the parameter type is not specified, it defaults to typing.Any
if param_annotation is Parameter.empty:
param_type = Any
# Check if the parameter has a default value
if param_default is Parameter.empty:
fields[param_name] = (param_type, FieldInfo())
else:
fields[param_name] = (param_type, FieldInfo(default=param_default))
# Applying `create_model()` directly will result in a mypy error,
# create an alias to avoid this.
def _create_mol(name, field):
return create_model(name, **field)
model = _create_mol(to_pascal(func.__name__), fields)
parameters_dict = get_pydantic_object_schema(model)
# The `"title"` is generated by `model.model_json_schema()`
# but is useless for openai json schema, remove generated 'title' from
# parameters_dict
_remove_title_recursively(parameters_dict)
docstring = parse(func.__doc__ or "")
for param in docstring.params:
if (name := param.arg_name) in parameters_dict["properties"] and (
description := param.description
):
parameters_dict["properties"][name]["description"] = description
short_description = docstring.short_description or ""
long_description = docstring.long_description or ""
if long_description:
func_description = f"{short_description}\n{long_description}"
else:
func_description = short_description
# OpenAI client.beta.chat.completions.parse for structured output has
# additional requirements for the schema, refer:
# https://platform.openai.com/docs/guides/structured-outputs/some-type-specific-keywords-are-not-yet-supported#supported-schemas
parameters_dict["additionalProperties"] = False
openai_function_schema = {
"name": func.__name__,
"description": func_description,
"strict": True,
"parameters": parameters_dict,
}
openai_tool_schema = {
"type": "function",
"function": openai_function_schema,
}
openai_tool_schema = sanitize_and_enforce_required(openai_tool_schema)
return openai_tool_schema
def sanitize_and_enforce_required(parameters_dict):
r"""Cleans and updates the function schema to conform with OpenAI's
requirements:
- Removes invalid 'default' fields from the parameters schema.
- Ensures all fields or function parameters are marked as required.
Args:
parameters_dict (dict): The dictionary representing the function
schema.
Returns:
dict: The updated dictionary with invalid defaults removed and all
fields set as required.
"""
# Check if 'function' and 'parameters' exist
if (
'function' in parameters_dict
and 'parameters' in parameters_dict['function']
):
# Access the 'parameters' section
parameters = parameters_dict['function']['parameters']
properties = parameters.get('properties', {})
# Remove 'default' key from each property
for field in properties.values():
field.pop('default', None)
# Mark all keys in 'properties' as required
parameters['required'] = list(properties.keys())
return parameters_dict
class FunctionTool:
r"""An abstraction of a function that OpenAI chat models can call. See
https://platform.openai.com/docs/api-reference/chat/create.
By default, the tool schema will be parsed from the func, or you can
provide a user-defined tool schema to override.
Args:
func (Callable): The function to call. The tool schema is parsed from
the function signature and docstring by default.
openai_tool_schema (Optional[Dict[str, Any]], optional): A
user-defined OpenAI tool schema to override the default result.
(default: :obj:`None`)
"""
def __init__(
self,
func: Callable,
openai_tool_schema: Optional[Dict[str, Any]] = None
) -> None:
self.func = func
self.openai_tool_schema = openai_tool_schema or get_openai_tool_schema(
func
)
def __call__(self, *args: Any, **kwargs: Any) -> Any:
# Pass the extracted arguments to the indicated function
try:
result = self.func(*args, **kwargs)
return result
except Exception as e:
raise ValueError(
f"Execution of function {self.func.__name__} failed with "
f"arguments {args} and {kwargs}. "
f"Error: {e}"
)
async def async_call(self, *args: Any, **kwargs: Any) -> Any:
if self.is_async:
return await self.func(*args, **kwargs)
else:
return self.func(*args, **kwargs)
@property
def is_async(self) -> bool:
return inspect.iscoroutinefunction(self.func)
@staticmethod
def validate_openai_tool_schema(
openai_tool_schema: Dict[str, Any],
) -> None:
r"""Validates the OpenAI tool schema against
:obj:`ToolAssistantToolsFunction`.
This function checks if the provided :obj:`openai_tool_schema` adheres
to the specifications required by OpenAI's
:obj:`ToolAssistantToolsFunction`. It ensures that the function
description and parameters are correctly formatted according to JSON
Schema specifications.
Args:
openai_tool_schema (Dict[str, Any]): The OpenAI tool schema to
validate.
Raises:
ValidationError: If the schema does not comply with the
specifications.
SchemaError: If the parameters do not meet JSON Schema reference
specifications.
"""
# Check the type
if not openai_tool_schema["type"]:
raise ValueError("miss `type` in tool schema.")
# Check the function description, if no description then raise warming
if not openai_tool_schema["function"].get("description"):
logger.warning(f"""Function description is missing for
{openai_tool_schema['function']['name']}. This may
affect the quality of tool calling.""")
# Validate whether parameters
# meet the JSON Schema reference specifications.
# See https://platform.openai.com/docs/guides/gpt/function-calling
# for examples, and the
# https://json-schema.org/understanding-json-schema/ for
# documentation about the format.
parameters = openai_tool_schema["function"]["parameters"]
try:
JSONValidator.check_schema(parameters)
except SchemaError as e:
raise e
# Check the parameter description, if no description then raise warming
properties: Dict[str, Any] = parameters["properties"]
for param_name in properties.keys():
param_dict = properties[param_name]
if "description" not in param_dict:
logger.warning(f"""Parameter description is missing for
{param_dict}. This may affect the quality of tool
calling.""")
def get_openai_tool_schema(self) -> Dict[str, Any]:
r"""Gets the OpenAI tool schema for this function.
This method returns the OpenAI tool schema associated with this
function, after validating it to ensure it meets OpenAI's
specifications.
Returns:
Dict[str, Any]: The OpenAI tool schema for this function.
"""
self.validate_openai_tool_schema(self.openai_tool_schema)
return self.openai_tool_schema
def set_openai_tool_schema(self, schema: Dict[str, Any]) -> None:
r"""Sets the OpenAI tool schema for this function.
Allows setting a custom OpenAI tool schema for this function.
Args:
schema (Dict[str, Any]): The OpenAI tool schema to set.
"""
self.openai_tool_schema = schema
def get_openai_function_schema(self) -> Dict[str, Any]:
r"""Gets the schema of the function from the OpenAI tool schema.
This method extracts and returns the function-specific part of the
OpenAI tool schema associated with this function.
Returns:
Dict[str, Any]: The schema of the function within the OpenAI tool
schema.
"""
self.validate_openai_tool_schema(self.openai_tool_schema)
return self.openai_tool_schema["function"]
def set_openai_function_schema(
self,
openai_function_schema: Dict[str, Any],
) -> None:
r"""Sets the schema of the function within the OpenAI tool schema.
Args:
openai_function_schema (Dict[str, Any]): The function schema to
set within the OpenAI tool schema.
"""
self.openai_tool_schema["function"] = openai_function_schema
def get_function_name(self) -> str:
r"""Gets the name of the function from the OpenAI tool schema.
Returns:
str: The name of the function.
"""
self.validate_openai_tool_schema(self.openai_tool_schema)
return self.openai_tool_schema["function"]["name"]
def set_function_name(self, name: str) -> None:
r"""Sets the name of the function in the OpenAI tool schema.
Args:
name (str): The name of the function to set.
"""
self.openai_tool_schema["function"]["name"] = name
def get_function_description(self) -> str:
r"""Gets the description of the function from the OpenAI tool
schema.
Returns:
str: The description of the function.
"""
self.validate_openai_tool_schema(self.openai_tool_schema)
return self.openai_tool_schema["function"]["description"]
def set_function_description(self, description: str) -> None:
r"""Sets the description of the function in the OpenAI tool schema.
Args:
description (str): The description for the function.
"""
self.openai_tool_schema["function"]["description"] = description
def get_parameter_description(self, param_name: str) -> str:
r"""Gets the description of a specific parameter from the function
schema.
Args:
param_name (str): The name of the parameter to get the
description.
Returns:
str: The description of the specified parameter.
"""
self.validate_openai_tool_schema(self.openai_tool_schema)
return self.openai_tool_schema["function"]["parameters"]["properties"][
param_name
]["description"]
def set_parameter_description(
self,
param_name: str,
description: str,
) -> None:
r"""Sets the description for a specific parameter in the function
schema.
Args:
param_name (str): The name of the parameter to set the description
for.
description (str): The description for the parameter.
"""
self.openai_tool_schema["function"]["parameters"]["properties"][
param_name
]["description"] = description
def get_parameter(self, param_name: str) -> Dict[str, Any]:
r"""Gets the schema for a specific parameter from the function schema.
Args:
param_name (str): The name of the parameter to get the schema.
Returns:
Dict[str, Any]: The schema of the specified parameter.
"""
self.validate_openai_tool_schema(self.openai_tool_schema)
return self.openai_tool_schema["function"]["parameters"]["properties"][
param_name
]
def set_parameter(self, param_name: str, value: Dict[str, Any]):
r"""Sets the schema for a specific parameter in the function schema.
Args:
param_name (str): The name of the parameter to set the schema for.
value (Dict[str, Any]): The schema to set for the parameter.
"""
try:
JSONValidator.check_schema(value)
except SchemaError as e:
raise e
self.openai_tool_schema["function"]["parameters"]["properties"][
param_name
] = value
@property
def parameters(self) -> Dict[str, Any]:
r"""Getter method for the property :obj:`parameters`.
Returns:
Dict[str, Any]: the dictionary containing information of
parameters of this function.
"""
self.validate_openai_tool_schema(self.openai_tool_schema)
return self.openai_tool_schema["function"]["parameters"]["properties"]
@parameters.setter
def parameters(self, value: Dict[str, Any]) -> None:
r"""Setter method for the property :obj:`parameters`. It will
firstly check if the input parameters schema is valid. If invalid,
the method will raise :obj:`jsonschema.exceptions.SchemaError`.
Args:
value (Dict[str, Any]): the new dictionary value for the
function's parameters.
"""
try:
JSONValidator.check_schema(value)
except SchemaError as e:
raise e
self.openai_tool_schema["function"]["parameters"]["properties"] = value