mirror of
https://github.com/crewAIInc/crewAI.git
synced 2026-01-10 08:38:30 +00:00
Feat yaml config all attributes (#985)
* WIP: yaml proper mapping for agents and agent * WIP: added output_json and output_pydantic setup * WIP: core logic added, need cleanup * code cleanup * updated docs and example template to use yaml to reference agents within tasks * cleanup type errors * Update Start-a-New-CrewAI-Project.md --------- Co-authored-by: João Moura <joaomdmoura@gmail.com>
This commit is contained in:
@@ -1,6 +1,7 @@
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import inspect
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import os
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from pathlib import Path
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from typing import Any, Callable, Dict
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import yaml
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from dotenv import load_dotenv
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@@ -20,11 +21,6 @@ def CrewBase(cls):
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base_directory = Path(frame_info.filename).parent.resolve()
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break
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if base_directory is None:
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raise Exception(
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"Unable to dynamically determine the project's base directory, you must run it from the project's root directory."
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)
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original_agents_config_path = getattr(
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cls, "agents_config", "config/agents.yaml"
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)
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@@ -32,12 +28,20 @@ def CrewBase(cls):
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def __init__(self, *args, **kwargs):
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super().__init__(*args, **kwargs)
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if self.base_directory is None:
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raise Exception(
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"Unable to dynamically determine the project's base directory, you must run it from the project's root directory."
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)
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self.agents_config = self.load_yaml(
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os.path.join(self.base_directory, self.original_agents_config_path)
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)
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self.tasks_config = self.load_yaml(
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os.path.join(self.base_directory, self.original_tasks_config_path)
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)
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self.map_all_agent_variables()
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self.map_all_task_variables()
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@staticmethod
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def load_yaml(config_path: str):
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@@ -45,4 +49,138 @@ def CrewBase(cls):
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# parsedContent = YamlParser.parse(file) # type: ignore # Argument 1 to "parse" has incompatible type "TextIOWrapper"; expected "YamlParser"
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return yaml.safe_load(file)
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def _get_all_functions(self):
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return {
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name: getattr(self, name)
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for name in dir(self)
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if callable(getattr(self, name))
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}
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def _filter_functions(
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self, functions: Dict[str, Callable], attribute: str
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) -> Dict[str, Callable]:
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return {
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name: func
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for name, func in functions.items()
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if hasattr(func, attribute)
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}
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def map_all_agent_variables(self) -> None:
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all_functions = self._get_all_functions()
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llms = self._filter_functions(all_functions, "is_llm")
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tool_functions = self._filter_functions(all_functions, "is_tool")
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cache_handler_functions = self._filter_functions(
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all_functions, "is_cache_handler"
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)
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callbacks = self._filter_functions(all_functions, "is_callback")
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agents = self._filter_functions(all_functions, "is_agent")
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for agent_name, agent_info in self.agents_config.items():
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self._map_agent_variables(
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agent_name,
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agent_info,
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agents,
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llms,
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tool_functions,
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cache_handler_functions,
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callbacks,
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)
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def _map_agent_variables(
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self,
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agent_name: str,
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agent_info: Dict[str, Any],
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agents: Dict[str, Callable],
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llms: Dict[str, Callable],
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tool_functions: Dict[str, Callable],
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cache_handler_functions: Dict[str, Callable],
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callbacks: Dict[str, Callable],
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) -> None:
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if llm := agent_info.get("llm"):
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self.agents_config[agent_name]["llm"] = llms[llm]()
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if tools := agent_info.get("tools"):
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self.agents_config[agent_name]["tools"] = [
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tool_functions[tool]() for tool in tools
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]
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if function_calling_llm := agent_info.get("function_calling_llm"):
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self.agents_config[agent_name]["function_calling_llm"] = agents[
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function_calling_llm
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]()
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if step_callback := agent_info.get("step_callback"):
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self.agents_config[agent_name]["step_callback"] = callbacks[
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step_callback
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]()
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if cache_handler := agent_info.get("cache_handler"):
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self.agents_config[agent_name]["cache_handler"] = (
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cache_handler_functions[cache_handler]()
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)
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def map_all_task_variables(self) -> None:
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all_functions = self._get_all_functions()
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agents = self._filter_functions(all_functions, "is_agent")
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tasks = self._filter_functions(all_functions, "is_task")
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output_json_functions = self._filter_functions(
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all_functions, "is_output_json"
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)
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tool_functions = self._filter_functions(all_functions, "is_tool")
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callback_functions = self._filter_functions(all_functions, "is_callback")
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output_pydantic_functions = self._filter_functions(
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all_functions, "is_output_pydantic"
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)
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for task_name, task_info in self.tasks_config.items():
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self._map_task_variables(
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task_name,
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task_info,
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agents,
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tasks,
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output_json_functions,
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tool_functions,
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callback_functions,
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output_pydantic_functions,
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)
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def _map_task_variables(
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self,
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task_name: str,
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task_info: Dict[str, Any],
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agents: Dict[str, Callable],
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tasks: Dict[str, Callable],
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output_json_functions: Dict[str, Callable],
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tool_functions: Dict[str, Callable],
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callback_functions: Dict[str, Callable],
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output_pydantic_functions: Dict[str, Callable],
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) -> None:
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if context_list := task_info.get("context"):
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self.tasks_config[task_name]["context"] = [
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tasks[context_task_name]() for context_task_name in context_list
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]
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if tools := task_info.get("tools"):
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self.tasks_config[task_name]["tools"] = [
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tool_functions[tool]() for tool in tools
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]
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if agent_name := task_info.get("agent"):
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self.tasks_config[task_name]["agent"] = agents[agent_name]()
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if output_json := task_info.get("output_json"):
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self.tasks_config[task_name]["output_json"] = output_json_functions[
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output_json
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]
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if output_pydantic := task_info.get("output_pydantic"):
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self.tasks_config[task_name]["output_pydantic"] = (
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output_pydantic_functions[output_pydantic]
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)
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if callbacks := task_info.get("callbacks"):
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self.tasks_config[task_name]["callbacks"] = [
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callback_functions[callback]() for callback in callbacks
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]
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return WrappedClass
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