settings.py

import os
from dotenv import load_dotenv
import logging
from langchain.embeddings import (
    HuggingFaceEmbeddings,
    HuggingFaceInstructEmbeddings,
)


class CustomFormatter(logging.Formatter):
    grey = "\x1b[38;20m"
    yellow = "\x1b[33;20m"
    red = "\x1b[31;20m"
    bold_red = "\x1b[31;1m"
    reset = "\x1b[0m"
    format = "%(asctime)s - %(name)s - %(levelname)s - %(message)s (%(filename)s:%(lineno)d)"

    FORMATS = {
        logging.DEBUG: grey + format + reset,
        logging.INFO: grey + format + reset,
        logging.WARNING: yellow + format + reset,
        logging.ERROR: red + format + reset,
        logging.CRITICAL: bold_red + format + reset,
    }

    def format(self, record):
        log_fmt = self.FORMATS.get(record.levelno)
        formatter = logging.Formatter(log_fmt)
        return formatter.format(record)


logging.basicConfig(format='%(asctime)s - %(levelname)s - %(message)s', level=logging.INFO)
logger = logging.getLogger(__name__)
logger.setLevel(logging.DEBUG)

# create console handler with a higher log level
ch = logging.StreamHandler()
ch.setLevel(logging.DEBUG)

ch.setFormatter(CustomFormatter())

logger.addHandler(ch)


class Settings:
    _instance = None

    def __new__(cls):
        if cls._instance is None:
            cls._instance = super().__new__(cls)
        return cls._instance

    def __init__(self):
        load_dotenv()

        # Chat API - By default, we are assuming Oobabooga's Text Generation
        # WebUI is running
        self.root_path = os.getcwd()

        if self.root_path.endswith("app"):
            self.root_path = self.root_path[:-4]

        self.model_root_path = os.path.join(self.root_path, "models")
        self.backend_root_path = os.path.join(self.root_path, "app")

        # let's ensure the models and backend path is accurate when mounting docker volumes
        if self.root_path.startswith("/code"):
            self.model_root_path = "/models"
            self.backend_root_path = self.root_path

        # Guidance new settings
        self.test_file = os.getenv("TEST_FILE", "/data/uploads/the_trial.txt")
        self.embeddings_map = {
            **{name: HuggingFaceInstructEmbeddings for name in ["hkunlp/instructor-xl", "hkunlp/instructor-large"]},
            **{name: HuggingFaceEmbeddings for name in ["all-MiniLM-L6-v2", "sentence-t5-xxl"]},
        }
        self.persist_directory = os.getenv("PERSIST_DIRECTORY", "./persist_directory")

        self.embeddings_model = os.getenv("EMBEDDINGS_MODEL", f"{self.model_root_path}/all-MiniLM-L6-v2")

        self.chat_api_url = os.getenv("CHAT_API_URL", "http://0.0.0.0:5000/api/v1/generate")
        self.model_path = self.model_root_path + os.getenv("MODEL_PATH")
        self.guidance_reasoning_model_path = self.model_root_path  + os.getenv("GUIDANCE_REASONING_MODEL_PATH")
        self.guidance_extraction_model_path = self.model_root_path  + os.getenv("GUIDANCE_EXTRACTION_MODEL_PATH")
        

        # Where all data is stored
        self.data_path = os.getenv("DATA_PATH", f"{self.backend_root_path}/data")

        # Where short-term memory is stored
        self.memories_path = os.getenv("MEMORIES_PATH", f"{self.data_path}/memories")

        # Where uploads are saved
        self.upload_path = os.getenv("UPLOAD_PATH", f"{self.data_path}/uploads")

        # Where conversation history is stored
        self.conversation_history_path = os.getenv(
            "CONVERSATION_HISTORY_PATH",
            f"{self.data_path}/conversation_history/",
        )

        # Document store name
        self.document_store_name = os.getenv("DOCUMENT_STORE_NAME", "brainchulo_docs")
        self.conversation_store_name = os.getenv("CONVERSATION_STORE_NAME", "brainchulo_convos")

        # Default objective - If we go objective-based, this is the default
        self.default_objective = os.getenv("DEFAULT_OBJECTIVE", "Be a CEO.")

        # Database URL
        self.database_url = os.getenv("DATABASE_URL", "sqlite:///data/brainchulo.db")

        self.andromeda_url = os.getenv("ANDROMEDA_URL", "http://0.0.0.0:9000")

        self.use_flow_agents = os.getenv("USE_FLOW_AGENTS", "false") == "true"


def load_config():
    return Settings()