from typing import Any, Dict, Optional, Callable, get_type_hints from pydantic import BaseModel, validate_call from phi.utils.log import logger class Function(BaseModel): """Model for Functions""" # The name of the function to be called. # Must be a-z, A-Z, 0-9, or contain underscores and dashes, with a maximum length of 64. name: str # A description of what the function does, used by the model to choose when and how to call the function. description: Optional[str] = None # The parameters the functions accepts, described as a JSON Schema object. # To describe a function that accepts no parameters, provide the value {"type": "object", "properties": {}}. parameters: Dict[str, Any] = {"type": "object", "properties": {}} entrypoint: Optional[Callable] = None # If True, the arguments are sanitized before being passed to the function. sanitize_arguments: bool = True def to_dict(self) -> Dict[str, Any]: return self.model_dump(exclude_none=True, include={"name", "description", "parameters"}) @classmethod def from_callable(cls, c: Callable) -> "Function": from inspect import getdoc from phi.utils.json_schema import get_json_schema parameters = {"type": "object", "properties": {}} try: # logger.info(f"Getting type hints for {c}") type_hints = get_type_hints(c) # logger.info(f"Type hints for {c}: {type_hints}") # logger.info(f"Getting JSON schema for {type_hints}") parameters = get_json_schema(type_hints) # logger.info(f"JSON schema for {c}: {parameters}") # logger.debug(f"Type hints for {c.__name__}: {type_hints}") except Exception as e: logger.warning(f"Could not parse args for {c.__name__}: {e}") return cls( name=c.__name__, description=getdoc(c), parameters=parameters, entrypoint=validate_call(c), ) def get_type_name(self, t): name = str(t) if "list" in name or "dict" in name: return name else: return t.__name__ def get_definition_for_prompt(self) -> Optional[str]: """Returns a function definition that can be used in a prompt.""" import json if self.entrypoint is None: return None type_hints = get_type_hints(self.entrypoint) return_type = type_hints.get("return", None) returns = None if return_type is not None: returns = self.get_type_name(return_type) function_info = { "name": self.name, "description": self.description, "arguments": self.parameters.get("properties", {}), "returns": returns, } return json.dumps(function_info, indent=2) def get_definition_for_prompt_dict(self) -> Optional[Dict[str, Any]]: """Returns a function definition that can be used in a prompt.""" if self.entrypoint is None: return None type_hints = get_type_hints(self.entrypoint) return_type = type_hints.get("return", None) returns = None if return_type is not None: returns = self.get_type_name(return_type) function_info = { "name": self.name, "description": self.description, "arguments": self.parameters.get("properties", {}), "returns": returns, } return function_info class FunctionCall(BaseModel): """Model for Function Calls""" # The function to be called. function: Function # The arguments to call the function with. arguments: Optional[Dict[str, Any]] = None # The result of the function call. result: Optional[Any] = None # The ID of the function call. call_id: Optional[str] = None # Error while parsing arguments or running the function. error: Optional[str] = None def get_call_str(self) -> str: """Returns a string representation of the function call.""" if self.arguments is None: return f"{self.function.name}()" trimmed_arguments = {} for k, v in self.arguments.items(): if isinstance(v, str) and len(v) > 100: trimmed_arguments[k] = "..." else: trimmed_arguments[k] = v call_str = f"{self.function.name}({', '.join([f'{k}={v}' for k, v in trimmed_arguments.items()])})" return call_str def execute(self) -> bool: """Runs the function call. @return: True if the function call was successful, False otherwise. """ if self.function.entrypoint is None: return False logger.debug(f"Running: {self.get_call_str()}") # Call the function with no arguments if none are provided. if self.arguments is None: try: self.result = self.function.entrypoint() return True except Exception as e: logger.warning(f"Could not run function {self.get_call_str()}") logger.exception(e) self.result = str(e) return False try: self.result = self.function.entrypoint(**self.arguments) return True except Exception as e: logger.warning(f"Could not run function {self.get_call_str()}") logger.exception(e) self.result = str(e) return False