import os

import fire
import yaml

from talk_codebase.llm import create_vector_store, send_question


def get_config():
    home_dir = os.path.expanduser("~")
    config_path = os.path.join(home_dir, ".config.yaml")
    if os.path.exists(config_path):
        with open(config_path, "r") as f:
            config = yaml.safe_load(f)
    else:
        config = {}
    return config


def save_config(config):
    home_dir = os.path.expanduser("~")
    config_path = os.path.join(home_dir, ".config.yaml")
    with open(config_path, "w") as f:
        yaml.dump(config, f)


def configure():
    config = get_config()
    api_key = input("🤖 Enter your OpenAI API key: ")
    model_name = input("🤖 Enter your model name (default: gpt-3.5-turbo): ") or "gpt-3.5-turbo"
    config["api_key"] = api_key
    config["model_name"] = model_name
    save_config(config)


def chat(root_dir):
    try:
        config = get_config()
        api_key = config.get("api_key")
        model_name = config.get("model_name")
        if not (api_key and model_name):
            configure()
            chat(root_dir)
        vector_store = create_vector_store(root_dir, api_key)
        while True:
            question = input("👉 ")
            if not question:
                print("🤖 Please enter a question.")
                continue
            if question.lower() in ('exit', 'quit'):
                break
            send_question(question, vector_store, api_key, model_name)
    except KeyboardInterrupt:
        print("\n🤖 Bye!")
    except Exception as e:
        if str(e) == "<empty message>":
            print("🤖 Please configure your API key.")
            configure()
            chat(root_dir)
        else:
            print(f"🤖 Error: {e}")


def main():
    fire.Fire({
        "chat": chat,
        "configure": configure,
    })


if __name__ == "__main__":
    main()