```

import torch
from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig
from sentence_transformers import SentenceTransformer
from llama_index.core import Settings, VectorStoreIndex, SimpleDirectoryReader, PromptTemplate
from llama_index.llms.huggingface import HuggingFaceLLM
from llama_index.embeddings.huggingface import HuggingFaceEmbedding

documents = SimpleDirectoryReader("../Datasets/Merged").load_data()

def completion_to_prompt(completion):
    return f"<|system|>\n</s>\n<|user|>\n{completion}</s>\n<|assistant|>\n"

def messages_to_prompt(messages):
    prompt = """You are an expert in blockchain technologies and blockchain patterns.\n
    Your answer should be returned in the following format/ \n
    Summary: \n
    Context: \n
    Problem: \n
    Forces: \n
    Solution: \n
    Benefits: \n
    Drawbacks: \n
    Related patterns: \n
    Known uses: \n

    The context will be provided and you should base your answer on it.
    """
    for message in messages:
        if message.role == "system":
            prompt += f"<|system|>\n{message.content}</s>\n"
        elif message.role == "user":
            prompt += f"<|user|>\n{message.content}</s>\n"
        elif message.role == "assistant":
            prompt += f"<|assistant|>\n{message.content}</s>\n"
    if not prompt.startswith("<|system|>\n"):
        prompt = "<|system|>\n</s>\n" + prompt

    prompt = prompt + "<|assistant|>\n"

    return prompt
)