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15 lines
618 B
Python
15 lines
618 B
Python
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from pathlib import Path
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from haystack.document_stores import InMemoryDocumentStore
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from haystack.pipeline_utils import build_indexing_pipeline
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# We support many different databases. Here we load a simple and lightweight in-memory document store.
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document_store = InMemoryDocumentStore()
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# Let's now build indexing pipeline that indexes PDFs and text files from a test folder.
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indexing_pipeline = build_indexing_pipeline(
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document_store=document_store, embedding_model="sentence-transformers/all-mpnet-base-v2"
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)
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result = indexing_pipeline.run(files=list(Path("../../test/test_files").iterdir()))
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print(result)
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