# ========= Copyright 2023-2025 @ CAMEL-AI.org. All Rights Reserved. =========
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ========= Copyright 2023-2025 @ CAMEL-AI.org. All Rights Reserved. =========
import random
import warnings
from typing import Any, Dict, List, Optional, Sequence, Tuple, Union

from colorama import Fore

from camel.agents.chat_agent import ChatAgent
from camel.memories import AgentMemory
from camel.messages import BaseMessage
from camel.models import BaseModelBackend
from camel.responses import ChatAgentResponse
from camel.types import ModelPlatformType, ModelType
from camel.utils import get_first_int, print_text_animated

# AgentOps decorator setting
try:
    import os

    if os.getenv("AGENTOPS_API_KEY") is not None:
        from agentops import track_agent
    else:
        raise ImportError
except (ImportError, AttributeError):
    from camel.utils import track_agent


@track_agent(name="CriticAgent")
class CriticAgent(ChatAgent):
    r"""A class for the critic agent that assists in selecting an option.

    Args:
        system_message (Union[BaseMessage, str], optional): The system message
            for the chat agent. (default: :obj:`None`)
        model (Union[BaseModelBackend, Tuple[str, str], str, ModelType,
            Tuple[ModelPlatformType, ModelType], List[BaseModelBackend],
            List[str], List[ModelType], List[Tuple[str, str]],
            List[Tuple[ModelPlatformType, ModelType]]], optional):
            The model backend(s) to use. Can be a single instance,
            a specification (string, enum, tuple), or a list of instances
            or specifications to be managed by `ModelManager`. If a list of
            specifications (not `BaseModelBackend` instances) is provided,
            they will be instantiated using `ModelFactory`. (default:
            :obj:`ModelPlatformType.DEFAULT` with `ModelType.DEFAULT`)
        message_window_size (int, optional): The maximum number of previous
            messages to include in the context window. If `None`, no windowing
            is performed. (default: :obj:`6`)
        retry_attempts (int, optional): The number of retry attempts if the
            critic fails to return a valid option. (default: :obj:`2`)
        verbose (bool, optional): Whether to print the critic's messages.
        logger_color (Any): The color of the menu options displayed to the
            user. (default: :obj:`Fore.MAGENTA`)
    """

    def __init__(
        self,
        system_message: Optional[Union[BaseMessage, str]] = None,
        model: Optional[
            Union[
                BaseModelBackend,
                Tuple[str, str],
                str,
                ModelType,
                Tuple[ModelPlatformType, ModelType],
                List[BaseModelBackend],
                List[str],
                List[ModelType],
                List[Tuple[str, str]],
                List[Tuple[ModelPlatformType, ModelType]],
            ]
        ] = None,
        memory: Optional[AgentMemory] = None,
        message_window_size: int = 6,
        retry_attempts: int = 2,
        verbose: bool = False,
        logger_color: Any = Fore.MAGENTA,
    ) -> None:
        super().__init__(
            system_message,
            model=model,
            memory=memory,
            message_window_size=message_window_size,
        )
        self.options_dict: Dict[str, str] = dict()
        self.retry_attempts = retry_attempts
        self.verbose = verbose
        self.logger_color = logger_color

    def flatten_options(self, messages: Sequence[BaseMessage]) -> str:
        r"""Flattens the options to the critic.

        Args:
            messages (Sequence[BaseMessage]): A list of `BaseMessage` objects.

        Returns:
            str: A string containing the flattened options to the critic.
        """
        options = [message.content for message in messages]
        flatten_options = (
            f"> Proposals from "
            f"{messages[0].role_name} ({messages[0].role_type}). "
            "Please choose an option:\n"
        )
        for index, option in enumerate(options):
            flatten_options += f"Option {index + 1}:\n{option}\n\n"
            self.options_dict[str(index + 1)] = option
        format = (
            f"Please first enter your choice ([1-{len(self.options_dict)}]) "
            "and then your explanation and comparison: "
        )
        return flatten_options + format

    def get_option(self, input_message: BaseMessage) -> str:
        r"""Gets the option selected by the critic.

        Args:
            input_message (BaseMessage): A `BaseMessage` object representing
                the input message.

        Returns:
            str: The option selected by the critic.
        """
        # TODO: Add support for editing options by the critic.
        msg_content = input_message.content
        i = 0
        while i < self.retry_attempts:
            critic_response = self.step(input_message)

            if critic_response.msgs is None or len(critic_response.msgs) == 0:
                raise RuntimeError("Got None critic messages.")
            if critic_response.terminated:
                raise RuntimeError("Critic step failed.")

            critic_msg = critic_response.msg
            if self.verbose:
                print_text_animated(
                    self.logger_color + "\n> Critic response: "
                    f"\x1b[3m{critic_msg.content}\x1b[0m\n"
                )
            choice = self.parse_critic(critic_msg)

            if choice in self.options_dict:
                return self.options_dict[choice]
            else:
                input_message = BaseMessage(
                    role_name=input_message.role_name,
                    role_type=input_message.role_type,
                    meta_dict=input_message.meta_dict,
                    content="> Invalid choice. Please choose again.\n"
                    + msg_content,
                )
                i += 1
        warnings.warn(
            "Critic failed to get a valid option. "
            f"After {self.retry_attempts} attempts. "
            "Returning a random option."
        )
        return random.choice(list(self.options_dict.values()))

    def parse_critic(self, critic_msg: BaseMessage) -> Optional[str]:
        r"""Parses the critic's message and extracts the choice.

        Args:
            critic_msg (BaseMessage): A `BaseMessage` object representing the
                critic's response.

        Returns:
            Optional[str]: The critic's choice as a string, or None if the
                message could not be parsed.
        """
        choice = str(get_first_int(critic_msg.content))
        return choice

    def reduce_step(
        self,
        input_messages: Sequence[BaseMessage],
    ) -> ChatAgentResponse:
        r"""Performs one step of the conversation by flattening options to the
        critic, getting the option, and parsing the choice.

        Args:
            input_messages (Sequence[BaseMessage]): A list of BaseMessage
                objects.

        Returns:
            ChatAgentResponse: A `ChatAgentResponse` object includes the
                critic's choice.
        """
        meta_chat_message = BaseMessage(
            role_name=input_messages[0].role_name,
            role_type=input_messages[0].role_type,
            meta_dict=input_messages[0].meta_dict,
            content="",
        )

        flatten_options = self.flatten_options(input_messages)
        if self.verbose:
            print_text_animated(
                self.logger_color + f"\x1b[3m{flatten_options}\x1b[0m\n"
            )
        input_msg = meta_chat_message.create_new_instance(flatten_options)

        option = self.get_option(input_msg)
        output_msg = meta_chat_message.create_new_instance(option)

        # TODO: The return `info` can be improved.
        return ChatAgentResponse(
            msgs=[output_msg],
            terminated=False,
            info={},
        )

    def clone(self, with_memory: bool = False) -> 'CriticAgent':
        r"""Creates a new instance of :obj:`CriticAgent` with the same
        configuration as the current instance.

        Args:
            with_memory (bool): Whether to copy the memory (conversation
                history) to the new agent. If True, the new agent will have
                the same conversation history. If False, the new agent will
                have a fresh memory with only the system message.
                (default: :obj:`False`)

        Returns:
            CriticAgent: A new instance of :obj:`CriticAgent` with the same
                configuration.
        """
        # Create a new instance with the same configuration
        # If with_memory is True, set system_message to None
        # If with_memory is False, use the original system message
        # To avoid duplicated system memory.
        system_message = None if with_memory else self._original_system_message

        new_agent = CriticAgent(
            system_message=system_message,
            model=self.model_backend.models,  # Pass the existing model_backend
            memory=None,  # clone memory later
            message_window_size=getattr(self.memory, "window_size", 6),
            retry_attempts=self.retry_attempts,
            verbose=self.verbose,
            logger_color=self.logger_color,
        )

        # Copy memory if requested
        if with_memory:
            # Get all records from the current memory
            context_records = self.memory.retrieve()
            # Write them to the new agent's memory
            for context_record in context_records:
                new_agent.memory.write_record(context_record.memory_record)

        # Copy CriticAgent-specific attributes
        new_agent.options_dict = self.options_dict.copy()

        return new_agent
