mirror of
https://github.com/OpenHands/OpenHands.git
synced 2025-12-26 13:52:43 +08:00
0380070e98
* move agent to langchains_agent * remove old .env * remove the old agent folder * add preliminary version of Agent abstraction * add preliminary version of the main.py * merge controlloop and main into a Agent class * add init * fix json import * fix missing arg * get langchains_agent working after abstraction * rename `research` to `agenthub` * rename: rename research to agenthub --------- Co-authored-by: huybery <huybery@gmail.com>
123 lines
3.6 KiB
Python
123 lines
3.6 KiB
Python
from abc import ABC, abstractmethod
|
|
from typing import List, Dict, Type
|
|
from dataclasses import dataclass
|
|
from enum import Enum
|
|
|
|
|
|
class Role(Enum):
|
|
USER = "user" # the user
|
|
ASSISTANT = "assistant" # the agent
|
|
ENVIRONMENT = "environment" # the environment (e.g., bash shell, web browser, etc.)
|
|
|
|
|
|
@dataclass
|
|
class Message:
|
|
"""
|
|
This data class represents a message sent by an agent to another agent or user.
|
|
"""
|
|
|
|
role: Role
|
|
content: str
|
|
# TODO: add more fields as needed
|
|
|
|
|
|
class Agent(ABC):
|
|
"""
|
|
This abstract base class is an general interface for an agent dedicated to
|
|
executing a specific instruction and allowing human interaction with the
|
|
agent during execution.
|
|
It tracks the execution status and maintains a history of interactions.
|
|
"""
|
|
|
|
_registry: Dict[str, Type['Agent']] = {}
|
|
|
|
def __init__(
|
|
self,
|
|
instruction: str,
|
|
max_steps: int = 100
|
|
):
|
|
self.instruction = instruction
|
|
self.max_steps = max_steps
|
|
|
|
self._complete = False
|
|
self._history: List[Message] = [Message(Role.USER, instruction)]
|
|
|
|
@property
|
|
def complete(self) -> bool:
|
|
"""
|
|
Indicates whether the current instruction execution is complete.
|
|
|
|
Returns:
|
|
- complete (bool): True if execution is complete; False otherwise.
|
|
"""
|
|
return self._complete
|
|
|
|
@property
|
|
def history(self) -> List[str]:
|
|
"""
|
|
Provides the history of interactions or state changes since the instruction was initiated.
|
|
|
|
Returns:
|
|
- history (List[str]): A list of strings representing the history.
|
|
"""
|
|
return self._history
|
|
|
|
@abstractmethod
|
|
def run(self) -> None:
|
|
"""
|
|
Starts the execution of the assigned instruction. This method should
|
|
be implemented by subclasses to define the specific execution logic.
|
|
"""
|
|
pass
|
|
|
|
@abstractmethod
|
|
def chat(self, message: str) -> None:
|
|
"""
|
|
Optional method for interactive communication with the agent during its execution. Implementations
|
|
can use this method to modify the agent's behavior or state based on chat inputs.
|
|
|
|
Parameters:
|
|
- message (str): The chat message or command.
|
|
"""
|
|
pass
|
|
|
|
def reset(self) -> None:
|
|
"""
|
|
Resets the agent's execution status and clears the history. This method can be used
|
|
to prepare the agent for restarting the instruction or cleaning up before destruction.
|
|
|
|
"""
|
|
self.instruction = None
|
|
self._complete = False
|
|
self._history = []
|
|
|
|
@classmethod
|
|
def register(cls, name: str, agent_cls: Type['Agent']):
|
|
"""
|
|
Registers an agent class in the registry.
|
|
|
|
Parameters:
|
|
- name (str): The name to register the class under.
|
|
- agent_cls (Type['Agent']): The class to register.
|
|
"""
|
|
if name in cls._registry:
|
|
raise ValueError(f"Agent class already registered under '{name}'.")
|
|
cls._registry[name] = agent_cls
|
|
|
|
@classmethod
|
|
def create_instance(cls, name: str, instruction: str) -> 'Agent':
|
|
"""
|
|
Creates an instance of a registered agent class based on the given name.
|
|
|
|
Parameters:
|
|
- name (str): The name of the agent class to instantiate.
|
|
- instruction (str): The instruction for the new agent instance.
|
|
|
|
Returns:
|
|
- An instance of the specified agent class.
|
|
"""
|
|
if name not in cls._registry:
|
|
raise ValueError(f"No agent class registered under '{name}'.")
|
|
agent_cls = cls._registry[name]
|
|
return agent_cls(instruction)
|