Download run.py from aiflows/ParseFeedbackFlowModule: direct link, hf CLI and curl.
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https://huggingface.co/aiflows/ParseFeedbackFlowModule/resolve/main/run.py
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hf download hf://aiflows/ParseFeedbackFlowModule/run.py
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curl -L -o run.py https://huggingface.co/aiflows/ParseFeedbackFlowModule/resolve/main/run.py
1.26 kB
| import os | |
| import hydra | |
| from aiflows.messages import InputMessage | |
| 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 in order to disable caching | |
| # clear_cache() # Uncomment this line to clear the cache | |
| logging.set_verbosity_debug() | |
| logging.auto_set_dir() | |
| dependencies = [ | |
| {"url": "aiflows/ParseFeedbackFlowModule", "revision": "main"}, | |
| ] | |
| from aiflows import flow_verse | |
| flow_verse.sync_dependencies(dependencies) | |
| if __name__ == "__main__": | |
| current_dir = os.getcwd() | |
| cfg_path = os.path.join(current_dir, "ParseFeedbackAtomicFlow.yaml") | |
| cfg = read_yaml_file(cfg_path) | |
| # ~~~ instantiating the flow and input data ~~~ | |
| ParseFeedbackFlow = hydra.utils.instantiate(cfg, _recursive_=False, _convert_="partial") | |
| input_data = { | |
| "temp_code_file_location": os.path.join(current_dir, "example_code_file.py") | |
| } | |
| input_message = InputMessage.build( | |
| data_dict=input_data, | |
| src_flow="Launcher", | |
| dst_flow=ParseFeedbackFlow.name | |
| ) | |
| # ~~~ calling the flow ~~~ | |
| output_message = ParseFeedbackFlow(input_message) | |
| print(output_message.data) |