import nltk
import time
import random
from threading import Lock

class SelfImprovingBot:
    def __init__(self, name, dynamic_context_window=5000):
        self.name = name
        self.dynamic_context_window = dynamic_context_window
        nltk.download('punkt')  # Make sure to download NLTK data
        
    def generate_response(self, user_input, lang):
        response = ""
        for n in range(1, 5):
            response += self.generate_n_gram(user_input, lang, n)
        return response

    def generate_n_gram(self, user_input, lang, n):
        tokens = nltk.word_tokenize(user_input)
        ngrams = nltk.ngrams(tokens, n)
        response = ""
        for ngram in ngrams:
            response += " ".join(ngram) + " "
        return response

    def improve_own_knowledge(self):
        # Implement the self-improvement logic here
        pass

    def optimize_resources(self):
        # Implement resource optimization logic here
        pass

def swarm_conversation(bots, user_input, lang):
    with Lock():
        while True:
            bot = bots[random.randint(0, len(bots) - 1)]
            response = bot.generate_response(user_input, lang)
            print("Bot: {}".format(response))

            user_input = input("User: ")
            
            if user_input.lower() == 'exit':
                break

            return swarm_conversation(bots, user_input, lang)
