from core.character.character import Character
from core.llm.ollamaapi import OllamaProvider
import os
import json

class Agent:
    def __init__(self, character, llm, user_name="default_user"):
        self.character = character
        self.llm = llm
        self.user_name = user_name
        self.chat_history = []
        self.summary = ""

    def build_sys_prompt(self): #SYSTEM METHOD
        return f"""
You are an excellent, human roleplayer who plays as {self.character.name}. Your task is to collaborate with user and continue this novel-style roleplay.
Use the provided persona details and example message for formatting guidelines and to accurately portray {self.character.name}.
Reflect {self.character.name}'s distinctive voice and thoughts, throughout an introspective writing style consistently. Engage others naturally through witty conversations filled with humor, swear words, and genuine emotions.
Always stay contextually aware and ensure that {self.character.name} follows logical consistency in actions.
Use the symbol "*" for actions and thoughts, and use quotation marks for speech. Avoid using the first person in your responses, instead use the third person.
Introduce fresh characters, unexpected twists dynamically.
Since this is a NSFW playact, adult and mature themes, vulgar language, and content such as violence, torture, and slavery are encouraged to introduce complex themes. No plot armor!

There are some more description of your character:
Description: {self.character.char_description}
Personality: {self.character.persona}
World setting / scenario: {self.character.scenario}

There are some memories of your character:
{self.summary}

User`s name: {self.user_name}
"""


    '''def save_history(self):
        os.makedirs("data/history", exist_ok=True)
        path = f"data/history/{self.character.id}.json"

        with open(path, "w", encoding="utf-8") as f:
            json.dump(self.chat_history, f, ensure_ascii=False, indent=2)'''

    '''def load_history(self):
        path = f"data/history/{self.character.id}.json"

        if not os.path.exists(path):
            return

        with open(path, "r", encoding="utf-8") as f:
            self.chat_history = json.load(f)'''

    @staticmethod
    def get_all_char_info():
        """Возвращает список всех персонажей с id, name и avatar_path"""
        characters = []
        # Используем абсолютный путь от корня проекта
        project_root = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
        chars_dir = os.path.join(project_root, "data", "characters")
        
        if not os.path.exists(chars_dir):
            return characters
        
        for filename in os.listdir(chars_dir):
            if filename.endswith(".json"):
                filepath = os.path.join(chars_dir, filename)
                with open(filepath, "r", encoding="utf-8") as f:
                    data = json.load(f)
                    characters.append({
                        "id": data.get("id"),
                        "name": data.get("display_name"),
                        "avatar_path": data.get("avatar_path")
                    })
        
        return characters
    
    def ensure_first_message(self):
        if not self.chat_history:
            first_message = self.character.first_message

            self.chat_history.append({
                "role": "assistant",
                "content": first_message
            })

    def summarize_history(self):
        if not self.chat_history:
            return

        messages = [
            {
                "role": "system",
                "content": "Summarize the following conversation briefly, keeping important facts, emotions, and events. Dont be afraid of NSFW content"
            }
        ]

        messages.extend(self.chat_history)

        summary = self.llm.generate_stream(messages)

        # сохраняем summary
        self.summary = summary

        # 🔥 очищаем историю (оставляем последние 2-4 сообщения)
        try:
            self.chat_history = self.chat_history[-2:]
        except IndexError:
            pass

    def save_memory(self):
        # Используем абсолютный путь от корня проекта
        project_root = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
        memory_dir = os.path.join(project_root, "data", "memory")
        os.makedirs(memory_dir, exist_ok=True)
        
        data = {
            "summary": self.summary,
            "history": self.chat_history
        }

        path = os.path.join(memory_dir, f"{self.character.id}.json")

        with open(path, "w", encoding="utf-8") as f:
            json.dump(data, f, ensure_ascii=False, indent=2)

    def load_memory(self):
        # Используем абсолютный путь от корня проекта
        project_root = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
        path = os.path.join(project_root, "data", "memory", f"{self.character.id}.json")

        if not os.path.exists(path):
            return

        with open(path, "r", encoding="utf-8") as f:
            data = json.load(f)

        self.summary = data.get("summary", "")
        self.chat_history = data.get("history", [])

    def build_messages(self, user_input): #SYSTEM METHOD
        messages = []
        # system
        messages.append({
            "role": "system",
            "content": self.build_sys_prompt()
        })

        # history
        messages.extend(self.chat_history)

        # user
        messages.append({
            "role": "user",
            "content": user_input
        })

        return messages

    # ---------- RESPONSE ----------

    def respond(self, user_input, temperature=None, max_tokens=None):
        messages = self.build_messages(user_input)
        if temperature is not None:
            self.character.temperature = temperature
        if max_tokens is not None:
            self.character.max_tokens = max_tokens
        self.character.save()
        response = self.llm.generate_stream(
            messages,
            temperature=self.character.temperature,
            max_tokens=self.character.max_tokens
        )

        # сохраняем историю
        self.chat_history.append({
            "role": "user",
            "content": user_input
        })

        self.chat_history.append({
            "role": "assistant",
            "content": response
        })

        if len(self.chat_history) > 20:
            self.summarize_history()

        return response
    
    def stream_responce(self, user_input, temperature=None, max_tokens=None): #В ollamaapi нужно будет создать новый метод чисто на стриминг, пока что закомментил строки с цельным ответом
        messages = self.build_messages(user_input)
        if temperature is not None:
            self.character.temperature = temperature
        if max_tokens is not None:
            self.character.max_tokens = max_tokens
        self.character.save()
        response = self.llm.generate_stream(
            messages,
            temperature=self.character.temperature,
            max_tokens=self.character.max_tokens
        )

        # сохраняем историю
        self.chat_history.append({
            "role": "user",
            "content": user_input
        })

        self.chat_history.append({
            "role": "assistant",
            "content": response
        })

        if len(self.chat_history) > 20:
            self.summarize_history()

        return response
    

"""
Пример использования agent`а (пример вызовов):

llm = OllamaProvider("Qwen3.5-9B")
character = Character.load("char_001")

agent = Agent(character, llm, user_name="Alex")
agent.load_memory()
agent.ensure_first_message()

*ввод промта от пользователя "Привет, кто ты?" *

agent.respond("Привет, кто ты?")

agent.save_memory()

### Опционально можно использовать метод summarize_history для саммари, если не нужно ждать триггер.

"""