import json
import subprocess

from gpt_engineer.ai import AI
from gpt_engineer.chat_to_files import to_files
from gpt_engineer.db import DBs
from gpt_engineer.chat_to_files import parse_chat


def setup_sys_prompt(dbs):
    return dbs.identity["generate"] + "\nUseful to know:\n" + dbs.identity["philosophy"]


def run(ai: AI, dbs: DBs):
    """Run the AI on the main prompt and save the results"""
    messages = ai.start(
        setup_sys_prompt(dbs),
        dbs.input["main_prompt"],
    )
    to_files(messages[-1]["content"], dbs.workspace)
    return messages


def clarify(ai: AI, dbs: DBs):
    """
    Ask the user if they want to clarify anything and save the results to the workspace
    """
    messages = [ai.fsystem(dbs.identity["qa"])]
    user = dbs.input["main_prompt"]
    while True:
        messages = ai.next(messages, user)

        if messages[-1]["content"].strip().lower().startswith("no"):
            break

        print()
        user = input('(answer in text, or "q" to move on)\n')
        print()

        if not user or user == "q":
            break

        user += (
            "\n\n"
            "Is anything else unclear? If yes, only answer in the form:\n"
            "{remaining unclear areas} remaining questions.\n"
            "{Next question}\n"
            'If everything is sufficiently clear, only answer "no".'
        )

    print()
    return messages


def gen_spec(ai: AI, dbs: DBs):
    """
    Generate a spec from the main prompt + clarifications and save the results to the workspace
    """
    messages = [
        ai.fsystem(setup_sys_prompt(dbs)),
        ai.fsystem(f"Instructions: {dbs.input['main_prompt']}"),
    ]

    messages = ai.next(messages, dbs.identity["spec"])
    messages = ai.next(messages, dbs.identity["respec"])
    messages = ai.next(messages, dbs.identity["spec"])

    dbs.memory["specification"] = messages[-1]["content"]

    return messages


def pre_unit_tests(ai: AI, dbs: DBs):
    """
    Generate unit tests based on the specification, that should work.
    """
    messages = [
        ai.fsystem(setup_sys_prompt(dbs)),
        ai.fuser(f"Instructions: {dbs.input['main_prompt']}"),
        ai.fuser(f"Specification:\n\n{dbs.memory['specification']}"),
    ]

    messages = ai.next(messages, dbs.identity["unit_tests"])

    dbs.memory["unit_tests"] = messages[-1]["content"]
    to_files(dbs.memory["unit_tests"], dbs.workspace)

    return messages


def run_clarified(ai: AI, dbs: DBs):
    # get the messages from previous step

    messages = [
        ai.fsystem(setup_sys_prompt(dbs)),
        ai.fuser(f"Instructions: {dbs.input['main_prompt']}"),
        ai.fuser(f"Specification:\n\n{dbs.memory['specification']}"),
        ai.fuser(f"Unit tests:\n\n{dbs.memory['unit_tests']}"),
    ]
    messages = ai.next(messages, dbs.identity["use_qa"])
    to_files(messages[-1]["content"], dbs.workspace)
    return messages


def execute_workspace(ai: AI, dbs: DBs):
    messages = gen_entrypoint(ai, dbs)
    execute_entrypoint(ai, dbs)
    return messages


def execute_entrypoint(ai, dbs):
    command = dbs.workspace["run.sh"]

    print("Do you want to execute this code?")
    print()
    print(command)
    print()
    print('If yes, press enter. If no, type "no"')
    print()
    if input() == "no":
        print("Ok, not executing the code.")
    print("Executing the code...")
    print()
    subprocess.run("bash run.sh", shell=True, cwd=dbs.workspace.path)
    return []


def gen_entrypoint(ai, dbs):
    messages = ai.start(
        system=(
            f"You will get information about a codebase that is currently on disk in the current folder.\n"
            "From this you will answer with one code block that includes all the necessary macos terminal commands to "
            "a) install dependencies "
            "b) run all necessary parts of the codebase (in parallell if necessary).\n"
            "Do not install globally. Do not use sudo.\n"
            "Do not explain the code, just give the commands.\n"
        ),
        user="Information about the codebase:\n\n" + dbs.workspace["all_output.txt"],
    )
    print()
    [[lang, command]] = parse_chat(messages[-1]["content"])
    assert lang in ["", "bash", "sh"]
    dbs.workspace["run.sh"] = command
    return messages


# Different configs of what steps to run
STEPS = {
    "default": [gen_spec, pre_unit_tests, run_clarified, execute_workspace],
    "benchmark": [gen_spec, pre_unit_tests, run_clarified, gen_entrypoint],
    "simple": [run, execute_workspace],
    "clarify": [clarify, run_clarified, gen_entrypoint],
    "execute_only": [execute_entrypoint],
}

# Future steps that can be added:
# self_reflect_and_improve_files,
# add_tests
# run_tests_and_fix_files,
# improve_based_on_in_file_feedback_comments