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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()) | |