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| # Copyright (c) 2024 Microsoft Corporation. | |
| # Licensed under the MIT License | |
| import asyncio | |
| import os | |
| from graphrag.index import run_pipeline_with_config | |
| from graphrag.index.config import PipelineCSVInputConfig | |
| from graphrag.index.input import load_input | |
| sample_data_dir = os.path.join( | |
| os.path.dirname(os.path.abspath(__file__)), "./../_sample_data/" | |
| ) | |
| async def run_with_config(): | |
| dataset = await load_input( | |
| PipelineCSVInputConfig( | |
| file_pattern=".*\\.csv$", | |
| base_dir=sample_data_dir, | |
| source_column="author", | |
| text_column="message", | |
| timestamp_column="date(yyyyMMddHHmmss)", | |
| timestamp_format="%Y%m%d%H%M%S", | |
| title_column="message", | |
| ), | |
| ) | |
| # We're cheap, and this is an example, lets just do 10 | |
| dataset = dataset.head(2) | |
| # run the pipeline with the config, and override the dataset with the one we just created | |
| # and grab the last result from the pipeline, should be the last workflow that was run (our nodes) | |
| pipeline_path = os.path.join( | |
| os.path.dirname(os.path.abspath(__file__)), "./pipeline.yml" | |
| ) | |
| async for result in run_pipeline_with_config(pipeline_path, dataset=dataset): | |
| print(f"Workflow {result.workflow} result\n: ") | |
| print(result.result) | |
| if __name__ == "__main__": | |
| asyncio.run(run_with_config()) | |