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5ff2d3c76d
* add fnllm; remove llm folder * remove llm unit tests * update imports * update imports * formatting * enable autosave * update mockllm * update community reports extractor * move most llm usage to fnllm * update type issues * fix unit tests * type updates * update dictionary * semver * update llm construction, get integration tests working * load from llmparameters model * move ruff settings to ruff.toml * add gitattributes file * ignore ruff.toml spelling * update .gitattributes * update gitignore * update config construction * update prompt var usage * add cache adapter * use cache adapter in embeddings calls * update embedding strategy * add fnllm * add pytest-dotenv * fix some verb tests * get verbtests running * update ruff.toml for vscode * enable ruff native server in vscode * update artifact inspecting code * remove local-test update * use string.replace instead of string.format in community reprots etxractor * bump timeout * revert ruff.toml, vscode settings for another pr * revert cspell config * revert gitignore * remove json-repair, update fnllm * use fnllm generic type interfaces * update load_llm to use target models * consolidate chat parameters * add 'extra_attributes' prop to community report response * formatting * update fnllm * formatting * formatting * Add defaults to some llm params to avoid null on params hash * Formatting --------- Co-authored-by: Alonso Guevara <alonsog@microsoft.com> Co-authored-by: Josh Bradley <joshbradley@microsoft.com>
106 lines
2.9 KiB
Python
106 lines
2.9 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 datashaper.errors import VerbParallelizationError
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from graphrag.config.enums import LLMType
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from graphrag.index.graph.extractors.community_reports.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.workflows.v1.create_final_community_reports 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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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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input_tables = load_input_tables([
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"workflow:create_final_nodes",
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"workflow:create_final_covariates",
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"workflow:create_final_relationships",
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"workflow:create_final_entities",
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"workflow:create_final_communities",
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])
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expected = load_test_table(workflow_name)
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config = get_config_for_workflow(workflow_name)
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config["create_community_reports"]["strategy"]["llm"] = MOCK_LLM_CONFIG
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steps = build_steps(config)
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actual = 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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)
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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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input_tables = load_input_tables([
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"workflow:create_final_nodes",
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"workflow:create_final_covariates",
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"workflow:create_final_relationships",
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"workflow:create_final_entities",
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"workflow:create_final_communities",
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])
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config = get_config_for_workflow(workflow_name)
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# deleting the llm config results in a default mock injection in run_graph_intelligence
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del config["create_community_reports"]["strategy"]["llm"]
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steps = build_steps(config)
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with pytest.raises(VerbParallelizationError):
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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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)
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