mirror of
https://github.com/microsoft/graphrag.git
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a2647da473
* Flatten compute_communities config * Remove cluster strategy type * Flatten create_base_text_units config * Move cluster seed to config default, leave as None in functions * Remove "prechunked" logic * Remove hard-coded encoding model * Remove unused variables * Strongly type embed_config * Simplify layout_graph config * Semver * Fix integration test * Fix config unit tests: ignore new config defaults * Remove pipeline integ test
66 lines
1.7 KiB
Python
66 lines
1.7 KiB
Python
# Copyright (c) 2024 Microsoft Corporation.
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# Licensed under the MIT License
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from graphrag.index.run.utils import create_run_context
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from graphrag.index.workflows.v1.create_base_text_units import (
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build_steps,
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workflow_name,
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)
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from .util import (
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compare_outputs,
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get_config_for_workflow,
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get_workflow_output,
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load_input_tables,
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load_test_table,
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)
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async def test_create_base_text_units():
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input_tables = load_input_tables(inputs=[])
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expected = load_test_table(workflow_name)
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context = create_run_context(None, None, None)
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config = get_config_for_workflow(workflow_name)
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# test data was created with 4o, so we need to match the encoding for chunks to be identical
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config["chunks"].encoding_model = "o200k_base"
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steps = build_steps(config)
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await get_workflow_output(
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input_tables,
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{
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"steps": steps,
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},
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context,
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)
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actual = await context.runtime_storage.get("base_text_units")
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compare_outputs(actual, expected)
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async def test_create_base_text_units_with_snapshot():
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input_tables = load_input_tables(inputs=[])
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context = create_run_context(None, None, None)
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config = get_config_for_workflow(workflow_name)
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# test data was created with 4o, so we need to match the encoding for chunks to be identical
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config["chunks"].encoding_model = "o200k_base"
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config["snapshot_transient"] = True
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steps = build_steps(config)
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await get_workflow_output(
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input_tables,
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{
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"steps": steps,
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},
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context,
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)
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assert context.storage.keys() == ["create_base_text_units.parquet"], (
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"Text unit snapshot keys differ"
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)
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