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https://github.com/khoj-ai/khoj.git
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76562f4250
* Initial version - setup a file-push architecture for generating embeddings with Khoj * Use state.host and state.port for configuring the URL for the indexer * Fix parsing of PDF files * Read markdown files from streamed data and update unit tests * On application startup, load in embeddings from configurations files, rather than regenerating the corpus based on file system * Init: refactor indexer/batch endpoint to support a generic file ingestion format * Add features to better support indexing from files sent by the desktop client * Initial commit with Electron application - Adds electron app * Add import for pymupdf, remove import for pypdf * Allow user to configure khoj host URL * Remove search type configuration from index.html * Use v1 path for current indexer routes
97 lines
3.3 KiB
Python
97 lines
3.3 KiB
Python
# Standard Packages
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import json
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import os
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import base64
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# Internal Packages
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from khoj.processor.pdf.pdf_to_jsonl import PdfToJsonl
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from khoj.utils.fs_syncer import get_pdf_files
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from khoj.utils.rawconfig import TextContentConfig
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def test_single_page_pdf_to_jsonl():
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"Convert single page PDF file to jsonl."
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# Act
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# Extract Entries from specified Pdf files
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# Read singlepage.pdf into memory as bytes
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with open("tests/data/pdf/singlepage.pdf", "rb") as f:
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pdf_bytes = base64.b64encode(f.read()).decode("utf-8")
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data = {"tests/data/pdf/singlepage.pdf": pdf_bytes}
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entries, entry_to_file_map = PdfToJsonl.extract_pdf_entries(pdf_files=data)
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# Process Each Entry from All Pdf Files
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jsonl_string = PdfToJsonl.convert_pdf_maps_to_jsonl(
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PdfToJsonl.convert_pdf_entries_to_maps(entries, entry_to_file_map)
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)
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jsonl_data = [json.loads(json_string) for json_string in jsonl_string.splitlines()]
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# Assert
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assert len(jsonl_data) == 1
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def test_multi_page_pdf_to_jsonl():
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"Convert multiple pages from single PDF file to jsonl."
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# Act
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# Extract Entries from specified Pdf files
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with open("tests/data/pdf/multipage.pdf", "rb") as f:
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pdf_bytes = base64.b64encode(f.read()).decode("utf-8")
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data = {"tests/data/pdf/multipage.pdf": pdf_bytes}
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entries, entry_to_file_map = PdfToJsonl.extract_pdf_entries(pdf_files=data)
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# Process Each Entry from All Pdf Files
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jsonl_string = PdfToJsonl.convert_pdf_maps_to_jsonl(
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PdfToJsonl.convert_pdf_entries_to_maps(entries, entry_to_file_map)
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)
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jsonl_data = [json.loads(json_string) for json_string in jsonl_string.splitlines()]
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# Assert
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assert len(jsonl_data) == 6
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def test_get_pdf_files(tmp_path):
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"Ensure Pdf files specified via input-filter, input-files extracted"
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# Arrange
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# Include via input-filter globs
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group1_file1 = create_file(tmp_path, filename="group1-file1.pdf")
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group1_file2 = create_file(tmp_path, filename="group1-file2.pdf")
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group2_file1 = create_file(tmp_path, filename="group2-file1.pdf")
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group2_file2 = create_file(tmp_path, filename="group2-file2.pdf")
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# Include via input-file field
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file1 = create_file(tmp_path, filename="document.pdf")
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# Not included by any filter
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create_file(tmp_path, filename="not-included-document.pdf")
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create_file(tmp_path, filename="not-included-text.txt")
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expected_files = set(
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[os.path.join(tmp_path, file.name) for file in [group1_file1, group1_file2, group2_file1, group2_file2, file1]]
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)
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# Setup input-files, input-filters
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input_files = [tmp_path / "document.pdf"]
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input_filter = [tmp_path / "group1*.pdf", tmp_path / "group2*.pdf"]
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pdf_config = TextContentConfig(
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input_files=input_files,
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input_filter=[str(path) for path in input_filter],
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compressed_jsonl=tmp_path / "test.jsonl",
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embeddings_file=tmp_path / "test_embeddings.jsonl",
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)
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# Act
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extracted_pdf_files = get_pdf_files(pdf_config)
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# Assert
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assert len(extracted_pdf_files) == 5
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assert set(extracted_pdf_files.keys()) == expected_files
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# Helper Functions
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def create_file(tmp_path, entry=None, filename="document.pdf"):
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pdf_file = tmp_path / filename
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pdf_file.touch()
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if entry:
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pdf_file.write_text(entry)
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return pdf_file
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