import os
from langchain.text_splitter import (
    CharacterTextSplitter,
    RecursiveCharacterTextSplitter,
    SentenceTransformersTokenTextSplitter,
    TextSplitter,
    TokenTextSplitter,
)
from langchain_community.document_loaders import TextLoader
from langchain_community.vectorstores import Chroma
from langchain_openai import OpenAIEmbeddings

# Define the directory containing the text file
current_dir = os.path.dirname(os.path.abspath(__file__))
file_path = os.path.join(current_dir, "books", "romeo_and_juliet.txt")
db_dir = os.path.join(current_dir, "db")

# Check if the text file exists
if not os.path.exists(file_path):
    raise FileNotFoundError(
        f"The file {file_path} does not exist. Please check the path."
    )

# Read the text content from the file
loader = TextLoader(file_path)
documents = loader.load()

import os

from dotenv import load_dotenv
from langchain.chains import create_history_aware_retriever, create_retrieval_chain
from langchain.chains.combine_documents import create_stuff_documents_chain
from langchain_community.vectorstores import Chroma
from langchain_core.messages import HumanMessage, SystemMessage
from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
from langchain_openai import ChatOpenAI, OpenAIEmbeddings

# Load environment variables from .env
load_dotenv()

# Define the persistent directory
current_dir = os.path.dirname(os.path.abspath(__file__))
persistent_directory = os.path.join(current_dir, "db", "chroma_db_with_metadata")