config.py

import os
from dataclasses import dataclass
from pathlib import Path

from dotenv import load_dotenv

load_dotenv()


@dataclass
class Env:
    model_name: str
    embeddings_model_name: str
    openai_api_key: str
    openai_endpoint: str
    openai_api_version: str
    site_url: str
    welcome_site_url: str
    site_repo: str
    welcome_site_repo: str
    github_user: str
    github_pat: str
    local_path: str
    vector_db_path: str
    chunk_size: int
    token_limit: int
    repos_path: str
    model_temperature: float
    log_level: str
    verbose: bool
    history_length: int
    mistral_endpoint: str
    mistral_key: str

    def __init__(self):
        self.rabbitmq_host = os.getenv("RABBITMQ_HOST", "")
        self.rabbitmq_user = os.getenv("RABBITMQ_USER", "")
        self.rabbitmq_password = os.getenv("RABBITMQ_PASSWORD", "")
        self.rabbitmq_input_queue = os.getenv("RABBITMQ_QUEUE", "")
        self.rabbitmq_result_queue = os.getenv("RABBITMQ_RESULT_QUEUE", "")
        self.rabbitmq_exchange = os.getenv("RABBITMQ_EVENT_BUS_EXCHANGE", "")
        self.rabbitmq_result_routing_key = os.getenv("RABBITMQ_RESULT_ROUTING_KEY", "")

        self.model_name = os.getenv("LLM_DEPLOYMENT_NAME", "")
        self.embeddings_model_name = os.getenv("EMBEDDINGS_DEPLOYMENT_NAME", "")
        self.openai_api_key = os.getenv("AZURE_OPENAI_API_KEY", "")
        self.openai_endpoint = os.getenv("AZURE_OPENAI_ENDPOINT", "")
        self.openai_api_version = os.getenv("OPENAI_API_VERSION", "")

        self.site_url = os.getenv("AI_SOURCE_WEBSITE", "")
        self.welcome_site_url = os.getenv("AI_SOURCE_WEBSITE2", "")

        self.site_repo = f"https://{os.getenv('AI_GITHUB_PAT', '')}@{os.getenv('AI_WEBSITE_REPO', '')}"
        self.welcome_site_repo = f"https://{os.getenv('AI_GITHUB_PAT', '')}@{os.getenv('AI_WEBSITE_REPO2', '')}"

        self.github_user = os.getenv("AI_GITHUB_USER", "")
        self.github_pat = os.getenv("AI_GITHUB_PAT", "")
        self.local_path = os.getenv("AI_LOCAL_PATH", "")
        self.vector_db_path = os.path.join(self.local_path, "vectordb")
        self.chunk_size = int(os.getenv("CHUNK_SIZE", "3000"))
        self.token_limit = int(os.getenv("TOKEN_LIMIT", "2000"))
        self.log_level = os.getenv("LOG_LEVEL", "INFO")
        self.verbose = self.log_level == "DEBUG"

        self.model_temperature = float(os.getenv("AI_MODEL_TEMPERATURE", "0.4"))
        self.history_length = int(os.getenv("HISTORY_LENGTH", "20"))

        self.repos_path = os.path.join(self.local_path, "repos", ".")

        self.mistral_endpoint = os.getenv("AZURE_MISTRAL_ENDPOINT", "")
        self.mistral_key = os.getenv("AZURE_MISTRAL_API_KEY", "")

        Path(self.repos_path).mkdir(parents=True, exist_ok=True)


env = Env()