import json
import io
import os
import pandas as pd
from datetime import datetime
import json
from assistants import Assistant 
import glob

def get_current_datetime():
    return datetime.now()

class ConversationManager:
    def __init__(self, client, user, asst_id):
        self.user = user
        self.assistants = {'general': Assistant(asst_id, self)}
        self.client = client
        self.user_personal_memory = None
        self.current_thread = self.create_thread()

        self.state = {'date': pd.Timestamp.now().date()}

        print("[Init State]:", self.state)

    def create_thread(self):
        # Check if a thread already exists for the current month, if yes, return it
        user_interaction_guidelines =self.user.user_interaction_guidelines
        thread = self.client.beta.threads.create()

        # Create an (empty, for now) 'UserPersonalMemory' vector store to store information on users events/state/etc.
        self.user_personal_memory = self.client.beta.vector_stores.create(name="UserPersonalMemory", \
            metadata={
                "description": "Personal events and emotional states of the user for personalized assistance and reminders of upcoming events.",
                "user_id": self.user.user_id,
                "categories": "events,tasks,emotions,goals",
                "created_at": str(datetime.now()),
                "updated_at": str(datetime.now()),
                "tags": "personal,emotional_state,upcoming_events,goals",
                "source": "Mementos shared by user",
            })


        self.system_message = self.add_message_to_thread(thread.id, "assistant", f"\
                                You are coaching:\n\n{user_interaction_guidelines}\n\n\
                                Be mindful of this information at all times in order to \
                                be as personalised as possible when conversing. Ensure to \
                                follow the conversation guidelines and flow provided. Use the \
                                current state of the conversation to adhere to the flow.\n\n \
                                ** You are now in the Introduction state. **")
        return thread

    def _get_current_thread_history(self, remove_system_message=True, msg=None):
        if not remove_system_message:
            return [{"role": msg.role, "content": msg.content[0].text.value} for msg in self.client.beta.threads.messages.list(self.current_thread.id, order="asc")]
        if msg:
            return [{"role": msg.role, "content": msg.content[0].text.value} for msg in self.client.beta.threads.messages.list(self.current_thread.id, order="asc", after=msg.id)][1:]
        return [{"role": msg.role, "content": msg.content[0].text.value} for msg in self.client.beta.threads.messages.list(self.current_thread.id, order="asc")][1:] # remove the system message

    def add_message_to_thread(self, thread_id, role, content):
        message = self.client.beta.threads.messages.create(
            thread_id=thread_id,
            role=role,
            content=content
        )
        return message
        # else:
        #     raise ValueError("Thread ID not found.")

    def _get_thread_messages(self, thread):
        return self.client.beta.threads.messages.list(thread.id, order="asc")
    
    def _run_current_thread(self, text):
        thread = self.current_thread

        # if you have more than 1 assistant
        # need to select assistant
        response = self.assistants['general'].process(thread, text)   
        return response 
    
    def _send_hidden_message(self, text):
        msg = self.add_message_to_thread(self.current_thread.id, "user", text)
        self._run_current_thread(text)
        # delete message
        self.client.beta.threads.messages.delete(message_id=msg.id, thread_id=self.current_thread.id)


class User:
    def __init__(self, user_id, user_info, client, asst_id):
        self.user_id = user_id
        self.client = client
        self.asst_id = asst_id
        # self.user_info = user_info
        # self.events = None
        self.user_interaction_guidelines = self.generate_user_interaction_guidelines(user_info, client)
        # self.coaching_plans = {}

        self.conversations = ConversationManager(client, self, asst_id)

    def reset(self):
        self.conversations = ConversationManager(self.client, self, self.asst_id)

    def generate_user_interaction_guidelines(self, user_info, client):
        prompt = f"Using the users information:\n\n{user_info}\n\n generate a \
            user summary that describes how best to interact with the user to create a personalized \
            and targeted chat experience. Include all the information above and based on that information \
            list several sample conversation topics and questions that will engage the user."

        response = client.chat.completions.create(
            model="gpt-4o-mini",
            messages=[
                {"role": "system", "content": "You are an expert at building profile documents containing rich user insights."},
                {"role": "user", "content": prompt}
            ],
            temperature=0.2
        )
        return response.choices[0].message.content
    
    def update_conversation_state(self, stage, last_interaction):
        self.conversation_state['stage'] = stage
        self.conversation_state['last_interaction'] = last_interaction

    def _get_current_thread(self):
        return self.conversations.current_thread

    def send_message(self, text):
        run = self.conversations._run_current_thread(text)
        return run
        # print("[Response]:", response)

    def get_messages(self, exclude_system_msg=True):
        if not exclude_system_msg:
            return self.conversations._get_current_thread_history(False)
        else:
            return list(filter(lambda x: not x['content'].startswith("** It is a new day:") or not x['content'].startswith("Pay attention to the current state you are in"), self.conversations._get_current_thread_history(exclude_system_msg)))
        
    def change_date(self, date):
        print(f"[Changing Date]:  {self.conversations.state['date']} -> {date}")
        self.conversations.state['date'] = date
        self.conversations._send_hidden_message(f"** It is a new day: {date} **")
        print("[Date Updated]:", self.conversations.state['date'])
        return self.get_messages()
    
    def __hash__(self) -> int:
        return hash(self.user_id)
    
    def _infer_follow_ups(self, created, context):
        prompt = f"Infer the date of the next follow-up for the user based on the created date:{created} and the context:{context}"

        response = self.client.chat.completions.create(
            model="gpt-4o-mini",
            messages=[
                {"role": "system", "content": "You are an expert at estimating when to follow up events with users. Only output a single string representing the follow up date i.e. 'YYYY-MM-dd'"},
                {"role": "user", "content": prompt}
            ],
            temperature=0.2
        )
        return response.choices[0].message.content

    def infer_memento_follow_ups(self):
        mementos_path = f"mementos/to_upload/{self.user_id}/*.json"
        
        for file_path in glob.glob(mementos_path):
            with open(file_path, 'r+') as file:
                data = json.load(file)
                infered_follow_up = self._infer_follow_ups(data['created'], data['context'])
                print(f"[Infered Follow Up]: {infered_follow_up}")
                data['follow_up_on'] = infered_follow_up
                file.seek(0)
                json.dump(data, file, indent=4)
                file.truncate()
    
    def change_assistant(self, asst_id):
        self.asst_id = asst_id
        self.conversations.assistants['general'] = Assistant(self.asst_id, self.conversations)
        return self