"""A simple script to run a Flow that can be used for development and debugging."""

import os

import hydra

import aiflows
from aiflows.flow_launchers import FlowLauncher
from aiflows.utils.general_helpers import read_yaml_file

from aiflows import logging
from aiflows.flow_cache import CACHING_PARAMETERS, clear_cache

CACHING_PARAMETERS.do_caching = False  # Set to True to enable caching
# clear_cache() # Uncomment this line to clear the cache

logging.set_verbosity_debug()

dependencies = [
    {"url": "aiflows/LCToolFlowModule", "revision": os.getcwd()},
]
from aiflows import flow_verse
flow_verse.sync_dependencies(dependencies)

if __name__ == "__main__":

    root_dir = "."
    cfg_path = os.path.join(root_dir, "demo.yaml")
    cfg = read_yaml_file(cfg_path)
    flow_with_interfaces = {
        "flow": hydra.utils.instantiate(cfg['flow'], _recursive_=False, _convert_="partial"),
        "input_interface": (
            None
            if getattr(cfg, "input_interface", None) is None
            else hydra.utils.instantiate(cfg['input_interface'], _recursive_=False)
        ),
        "output_interface": (
            None
            if getattr(cfg, "output_interface", None) is None
            else hydra.utils.instantiate(cfg['output_interface'], _recursive_=False)
        ),
    }

    # ~~~ Get the data ~~~
    # This can be a list of samples
    data = {"id": 0, "query": "Michael Jordan age"}  # Add your data here

    # ~~~ Run inference ~~~
    path_to_output_file = None
    # path_to_output_file = "output.jsonl"  # Uncomment this line to save the output to disk

    _, outputs = FlowLauncher.launch(
        flow_with_interfaces=flow_with_interfaces,
        data=data,
        path_to_output_file=path_to_output_file,
    )

    # ~~~ Print the output ~~~
    flow_output_data = outputs[0]
    print(flow_output_data)