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110 lines
3.0 KiB
Python
110 lines
3.0 KiB
Python
# Copyright (c) 2024 Microsoft Corporation.
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# Licensed under the MIT License
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import pytest
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from graphrag.callbacks.noop_verb_callbacks import NoopVerbCallbacks
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from graphrag.config.create_graphrag_config import create_graphrag_config
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from graphrag.config.enums import LLMType
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from graphrag.index.operations.summarize_communities.community_reports_extractor.community_reports_extractor import (
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CommunityReportResponse,
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FindingModel,
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)
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from graphrag.index.run.derive_from_rows import ParallelizationError
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from graphrag.index.workflows.create_final_community_reports import (
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run_workflow,
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workflow_name,
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)
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from graphrag.utils.storage import load_table_from_storage
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from .util import (
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compare_outputs,
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create_test_context,
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load_test_table,
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)
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MOCK_RESPONSES = [
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CommunityReportResponse(
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title="<report_title>",
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summary="<executive_summary>",
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rating=2,
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rating_explanation="<rating_explanation>",
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findings=[
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FindingModel(
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summary="<insight_1_summary>", explanation="<insight_1_explanation"
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),
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FindingModel(
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summary="<insight_2_summary>", explanation="<insight_2_explanation"
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),
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],
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)
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]
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MOCK_LLM_CONFIG = {
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"type": LLMType.StaticResponse,
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"responses": MOCK_RESPONSES,
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"parse_json": True,
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}
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async def test_create_final_community_reports():
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expected = load_test_table(workflow_name)
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context = await create_test_context(
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storage=[
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"create_final_nodes",
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"create_final_covariates",
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"create_final_relationships",
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"create_final_entities",
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"create_final_communities",
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]
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)
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config = create_graphrag_config()
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config.community_reports.strategy = {
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"type": "graph_intelligence",
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"llm": MOCK_LLM_CONFIG,
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}
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await run_workflow(
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config,
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context,
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NoopVerbCallbacks(),
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)
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actual = await load_table_from_storage(workflow_name, context.storage)
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assert len(actual.columns) == len(expected.columns)
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# only assert a couple of columns that are not mock - most of this table is LLM-generated
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compare_outputs(actual, expected, columns=["community", "level"])
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# assert a handful of mock data items to confirm they get put in the right spot
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assert actual["rank"][:1][0] == 2
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assert actual["rank_explanation"][:1][0] == "<rating_explanation>"
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async def test_create_final_community_reports_missing_llm_throws():
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context = await create_test_context(
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storage=[
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"create_final_nodes",
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"create_final_covariates",
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"create_final_relationships",
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"create_final_entities",
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"create_final_communities",
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]
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)
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config = create_graphrag_config()
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config.community_reports.strategy = {
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"type": "graph_intelligence",
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}
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with pytest.raises(ParallelizationError):
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await run_workflow(
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config,
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context,
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NoopVerbCallbacks(),
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)
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