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"""A simple script to run a Flow that can be used for development and debugging."""
import os
import hydra
import flows
from flows.flow_launchers import FlowLauncher
from flows.utils.general_helpers import read_yaml_file
from flows import logging
from flows.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 flows 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)
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