# Copyright 2024 the LlamaFactory team.
#
# 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.

import json
import re
from abc import ABC, abstractmethod
from dataclasses import dataclass, field
from typing import Any, Dict, List, Literal, Optional, Sequence, Set, Tuple, Union


SLOTS = Sequence[Union[str, Set[str], Dict[str, str]]]


DEFAULT_TOOL_PROMPT = (
    "You have access to the following tools:\n{tool_text}"
    "Use the following format if using a tool:\n"
    "```\n"
    "Action: tool name (one of [{tool_names}]).\n"
    "Action Input: the input to the tool, in a JSON format representing the kwargs "
    """(e.g. ```{{"input": "hello world", "num_beams": 5}}```).\n"""
    "```\n"
)


GLM4_TOOL_PROMPT = (
    "你是一个名为 GLM-4 的人工智能助手。你是基于智谱AI训练的语言模型 GLM-4 模型开发的，"
    "你的任务是针对用户的问题和要求提供适当的答复和支持。{tool_text}"
)


def default_tool_formatter(tools: List[Dict[str, Any]]) -> str:
    tool_text = ""
    tool_names = []
    for tool in tools:
        param_text = ""
        for name, param in tool["parameters"]["properties"].items():
            required = ", required" if name in tool["parameters"].get("required", []) else ""
            enum = ", should be one of [{}]".format(", ".join(param["enum"])) if param.get("enum", None) else ""
            items = (
                ", where each item should be {}".format(param["items"].get("type", "")) if param.get("items") else ""
            )
            param_text += "  - {name} ({type}{required}): {desc}{enum}{items}\n".format(
                name=name,
                type=param.get("type", ""),
                required=required,
                desc=param.get("description", ""),
                enum=enum,
                items=items,
            )

        tool_text += "> Tool Name: {name}\nTool Description: {desc}\nTool Args:\n{args}\n".format(
            name=tool["name"], desc=tool.get("description", ""), args=param_text
        )
        tool_names.append(tool["name"])

    return DEFAULT_TOOL_PROMPT.format(tool_text=tool_text, tool_names=", ".join(tool_names))


def default_tool_extractor(content: str) -> Union[str, List[Tuple[str, str]]]:
    regex = re.compile(r"Action:\s*([a-zA-Z0-9_]+)\s*Action Input:\s*(.+?)(?=\s*Action:|\s*$)", re.DOTALL)
    action_match: List[Tuple[str, str]] = re.findall(regex, content)
    if not action_match:
        return content

    results = []
    for match in action_match:
        tool_name = match[0].strip()
        tool_input = match[1].strip().strip('"').strip("```")
        try:
            arguments = json.loads(tool_input)
            results.append((tool_name, json.dumps(arguments, ensure_ascii=False)))
        except json.JSONDecodeError:
            return content

    return results


def glm4_tool_formatter(tools: List[Dict[str, Any]]) -> str:
    tool_text = ""
    for tool in tools:
        tool_text += "\n\n## {name}\n\n{body}\n在调用上述函数时，请使用 Json 格式表示调用的参数。".format(
            name=tool["name"], body=json.dumps(tool, indent=4, ensure_ascii=False)
        )

    return GLM4_TOOL_PROMPT.format(tool_text=tool_text)


def glm4_tool_extractor(content: str) -> Union[str, List[Tuple[str, str]]]:
    if "\n" not in content:
        return content

    tool_name, tool_input = content.split("\n", maxsplit=1)
    try:
        arguments = json.loads(tool_input)
    except json.JSONDecodeError:
        return content

    return [(tool_name, json.dumps(arguments, ensure_ascii=False))]


@dataclass
class Formatter(ABC):
    slots: SLOTS = field(default_factory=list)
    tool_format: Optional[Literal["default", "glm4"]] = None

    @abstractmethod
    def apply(self, **kwargs) -> SLOTS: ...

    def extract(self, content: str) -> Union[str, List[Tuple[str, str]]]:
        raise NotImplementedError


@dataclass
class EmptyFormatter(Formatter):
    def __post_init__(self):
        has_placeholder = False
        for slot in filter(lambda s: isinstance(s, str), self.slots):
            if re.search(r"\{\{[a-zA-Z_][a-zA-Z0-9_]*\}\}", slot):
                has_placeholder = True

        if has_placeholder:
            raise ValueError("Empty formatter should not contain any placeholder.")

    def apply(self, **kwargs) -> SLOTS:
        return self.slots


@dataclass
class StringFormatter(Formatter):
    def __post_init__(self):
        has_placeholder = False
        for slot in filter(lambda s: isinstance(s, str), self.slots):
            if re.search(r"\{\{[a-zA-Z_][a-zA-Z0-9_]*\}\}", slot):
                has_placeholder = True

        if not has_placeholder:
            raise ValueError("A placeholder is required in the string formatter.")

    def apply(self, **kwargs) -> SLOTS:
        elements = []
        for slot in self.slots:
            if isinstance(slot, str):
                for name, value in kwargs.items():
                    if not isinstance(value, str):
                        raise RuntimeError("Expected a string, got {}".format(value))

                    slot = slot.replace("{{" + name + "}}", value, 1)
                elements.append(slot)
            elif isinstance(slot, (dict, set)):
                elements.append(slot)
            else:
                raise RuntimeError("Input must be string, set[str] or dict[str, str], got {}".format(type(slot)))

        return elements


@dataclass
class FunctionFormatter(Formatter):
    def __post_init__(self):
        has_name, has_args = False, False
        for slot in filter(lambda s: isinstance(s, str), self.slots):
            if "{{name}}" in slot:
                has_name = True
            if "{{arguments}}" in slot:
                has_args = True

        if not has_name or not has_args:
            raise ValueError("Name and arguments placeholders are required in the function formatter.")

    def apply(self, **kwargs) -> SLOTS:
        content = kwargs.pop("content")
        functions: List[Tuple[str, str]] = []
        try:
            tool_calls = json.loads(content)
            if not isinstance(tool_calls, list):  # parallel function call
                tool_calls = [tool_calls]

            for tool_call in tool_calls:
                functions.append((tool_call["name"], json.dumps(tool_call["arguments"], ensure_ascii=False)))

        except json.JSONDecodeError:
            functions = []

        elements = []
        for name, arguments in functions:
            for slot in self.slots:
                if isinstance(slot, str):
                    slot = slot.replace("{{name}}", name).replace("{{arguments}}", arguments)
                    elements.append(slot)
                elif isinstance(slot, (dict, set)):
                    elements.append(slot)
                else:
                    raise RuntimeError("Input must be string, set[str] or dict[str, str], got {}".format(type(slot)))

        return elements


@dataclass
class ToolFormatter(Formatter):
    def __post_init__(self):
        if self.tool_format == "default":
            self._tool_formatter = default_tool_formatter
            self._tool_extractor = default_tool_extractor
        elif self.tool_format == "glm4":
            self._tool_formatter = glm4_tool_formatter
            self._tool_extractor = glm4_tool_extractor
        else:
            raise ValueError("Tool format was not found.")

    def apply(self, **kwargs) -> SLOTS:
        content = kwargs.pop("content")
        try:
            tools = json.loads(content)
            return [self._tool_formatter(tools) if len(tools) != 0 else ""]
        except json.JSONDecodeError:
            return [""]

    def extract(self, content: str) -> Union[str, List[Tuple[str, str]]]:
        return self._tool_extractor(content)