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0e1a6e3770
* unified search app added to graphrag repository * ignore print statements * update words for unified-search * fix lint errors * fix lint error * fix module name --------- Co-authored-by: Gaudy Blanco <gaudy-microsoft@MacBook-Pro-m4-Gaudy-For-Work.local>
79 lines
2.5 KiB
Python
79 lines
2.5 KiB
Python
# Copyright (c) 2024 Microsoft Corporation.
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# Licensed under the MIT License
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"""Loader module."""
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import json
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import logging
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import os
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from knowledge_loader.data_sources.blob_source import (
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BlobDatasource,
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load_blob_file,
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load_blob_prompt_config,
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)
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from knowledge_loader.data_sources.default import (
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LISTING_FILE,
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blob_account_name,
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local_data_root,
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)
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from knowledge_loader.data_sources.local_source import (
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LocalDatasource,
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load_local_prompt_config,
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)
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from knowledge_loader.data_sources.typing import DatasetConfig, Datasource
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logging.basicConfig(level=logging.INFO)
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logging.getLogger("azure").setLevel(logging.WARNING)
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logger = logging.getLogger(__name__)
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def _get_base_path(
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dataset: str | None, root: str | None, extra_path: str | None = None
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) -> str:
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"""Construct and return the base path for the given dataset and extra path."""
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return os.path.join( # noqa: PTH118
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os.path.dirname(os.path.realpath(__file__)), # noqa: PTH120
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root if root else "",
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dataset if dataset else "",
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*(extra_path.split("/") if extra_path else []),
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)
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def create_datasource(dataset_folder: str) -> Datasource:
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"""Return a datasource that reads from a local or blob storage parquet file."""
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if blob_account_name is not None and blob_account_name != "":
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return BlobDatasource(dataset_folder)
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base_path = _get_base_path(dataset_folder, local_data_root)
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return LocalDatasource(base_path)
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def load_dataset_listing() -> list[DatasetConfig]:
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"""Load dataset listing file."""
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datasets = []
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if blob_account_name is not None and blob_account_name != "":
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try:
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blob = load_blob_file(None, LISTING_FILE)
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datasets_str = blob.getvalue().decode("utf-8")
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if datasets_str:
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datasets = json.loads(datasets_str)
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except Exception as e: # noqa: BLE001
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print(f"Error loading dataset config: {e}") # noqa T201
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return []
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else:
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base_path = _get_base_path(None, local_data_root, LISTING_FILE)
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with open(base_path, "r") as file: # noqa: UP015, PTH123
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datasets = json.load(file)
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return [DatasetConfig(**d) for d in datasets]
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def load_prompts(dataset: str) -> dict[str, str]:
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"""Return the prompts configuration for a specific dataset."""
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if blob_account_name is not None and blob_account_name != "":
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return load_blob_prompt_config(dataset)
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base_path = _get_base_path(dataset, local_data_root, "prompts")
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return load_local_prompt_config(base_path)
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