gistfile1.txt

import hashlib
import numpy as np
import pennylane as qml
from datetime import datetime
import nltk
from textblob import TextBlob
from concurrent.futures import ThreadPoolExecutor
import time
import json
import logging

logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

class QuantumCommunicationNode:
    def __init__(self, config):
        self.node_id = config["node_id"]
        self.entanglement_key = self.generate_entanglement_key(config["entanglement_key"])
        self.dev = qml.device('default.qubit', wires=10)
        self.chunk_size = config.get("chunk_size", 100)
        self.llama_prompts = config.get("llama_prompts", {})

    def generate_entanglement_key(self, key):
        key_input = f"{self.node_id}-{datetime.now().isoformat()}"
        return hashlib.sha256(key_input.encode()).hexdigest()

    @qml.qnode(self.dev)
    def quantum_entanglement_circuit(self, chunks):
        for i, chunk in enumerate(chunks):
            self.prepare_chunk_state(chunk, i)
        for i in range(len(chunks) - 1):
            qml.CNOT(wires=[i, i + 1])
        return [qml.expval(qml.PauliZ(i)) for i in range(len(chunks))]

    def prepare_chunk_state(self, chunk, wire):
        for char in chunk:
            qml.RY(ord(char) * np.pi / 256, wires=wire)

    def quantum_entangle_message(self, message):
        sentiment = self.analyze_sentiment(message)
        chunks = self.quantum_chunk_message(message, sentiment)
        quantum_states = self.quantum_entanglement_circuit(chunks)
        return quantum_states, chunks

    def analyze_sentiment(self, message):
        analysis = TextBlob(message)
        return (analysis.sentiment.polarity + 1) / 2

    def quantum_chunk_message(self, message, sentiment):
        chunk_length = int(self.chunk_size * sentiment)
        return [message[i:i + chunk_length] for i in range(0, len(message), chunk_length)]

    def llama2_generate_dynamic_prompt(self, message):
        base_prompt = self.llama_prompts.get("base_prompt", "")
        current_time = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
        sentiment = self.analyze_sentiment(message)
        tone = "positive" if sentiment > 0.5 else "neutral" if sentiment > 0 else "negative"
        dynamic_prompt = f"{base_prompt} [Time: {current_time}] [Tone: {tone}] {message[:550]}"
        return dynamic_prompt

class QuantumNodeIDGenerator:
    def __init__(self, num_wires=5):
        self.dev = qml.device('default.qubit', wires=num_wires)

    @qml.qnode(self.dev)
    def quantum_circuit(self, inputs):
        for i in range(len(inputs)):
            qml.RY(inputs[i], wires=i)
        for i in range(len(inputs) - 1):
            qml.CNOT(wires=[i, i + 1])
        return [qml.expval(qml.PauliZ(i)) for i in range(len(inputs))]

    def generate_name(self, seed):
        hashed_seed = hashlib.sha256(seed.encode()).hexdigest()
        inputs = np.array([ord(c) for c in hashed_seed[:5]])
        quantum_results = self.quantum_circuit(inputs)
        name = ''.join([chr(int((val + 1) * 128)) for val in quantum_results])
        return name

class AdvancedTokenizer:
    def tokenize(self, message):
        tokens = nltk.word_tokenize(message)
        tagged_tokens = nltk.pos_tag(tokens)
        return self.inject_custom_tokens(tagged_tokens)

    def inject_custom_tokens(self, tagged_tokens, quantum_states):
        custom_tokens = []
        for word, tag in tagged_tokens:
            if tag.startswith('VB'):
                custom_tokens.append('[action]')
            if 'time' in word.lower():
                custom_tokens.append('[time]')
            if 'important' in word.lower():
                custom_tokens.append('[important]')
            custom_tokens.append(word)

        # Inject quantum entanglement tokens
        for state in quantum_states:
            entanglement_token = '[entangled]' if state > 0 else '[not_entangled]'
            custom_tokens.append(entanglement_token)

        return custom_tokens

class Bot:
    def __init__(self, name, quantum_generator, config):
        self.name = name
        self.quantum_generator = quantum_generator
        self.tokenizer = AdvancedTokenizer()
        self.node = QuantumCommunicationNode(config)

    def generate_node_id(self):
        seed = f"{self.name}-{datetime.now().isoformat()}"
        return self.quantum_generator.generate_name(seed)

    def prepare_message(self, raw_message):
        tokenized_message = self.tokenizer.tokenize(raw_message)
        return ' '.join(tokenized_message)

    def communicate(self, other_bot):
        try:
            node_id = self.generate_node_id()
            raw_message = f"Node {self.name} to {other_bot.name}: {node_id}"
            quantum_states, chunks = self.node.quantum_entangle_message(raw_message)
            processed_message = self.tokenizer.tokenize(raw_message)
            entangled_tokens = self.tokenizer.inject_custom_tokens(processed_message, quantum_states)
            dynamic_prompt = self.node.llama2_generate_dynamic_prompt(' '.join(entangled_tokens))
            logger.info(f"Sending from {self.name} to {other_bot.name}: {dynamic_prompt}")
        except Exception as e:
            logger.error(f"Error in bot communication: {e}")

def main():
    try:
        with open('config.json', 'r') as file:
            config = json.load(file)

        quantum_generator = QuantumNodeIDGenerator()
        bot1 = Bot("Bot1", quantum_generator, config["node1"])
        bot2 = Bot("Bot2", quantum_generator, config["node2"])

        max_workers = config.get("max_workers", 2)
        with ThreadPoolExecutor(max_workers=max_workers) as executor:
            executor.submit(bot1.communicate, bot2)
            executor.submit(bot2.communicate, bot1)
    except Exception as e:
        logger.error(f"Error in main execution: {e}")

if __name__ == "__main__":
    main()