chore: import upstream snapshot with attribution
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""" To enable rapid testing and prototyping, LLMWare provides a range of sample files that can be accessed
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through the Setup class, and specific methods that will pull the files from a non-restricted llmware AWS S3 bucket,
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and download the files locally in the /llmware_data/sample_files path.
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Sample files are created from public domain sources, and often developed originally by LLMWare. They are
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provided for convenience in testing. As we find or develop a good testing set, we will generally try to make it
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available so everyone can use - as a result, the sample files collection is evolving and growing all the time!
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If you have an older version, and would like to get the latest, then you can set the over_write=True option.
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"""
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import os
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from llmware.setup import Setup
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def get_llmware_sample_files():
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print (f"\n > Loading the llmware Sample Files...")
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# this call to Setup() will pull the sample files from a public S3 repo
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# the files will be placed in folders locally at the sample_files_path
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sample_files_path = Setup().load_sample_files(over_write=False)
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print(f"> Sample Files Path - {sample_files_path}")
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print(f"> Sample Folders - {os.listdir(sample_files_path)}")
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# Current Sample Files:
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#
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# AgreementsLarge = ~80 sample contracts
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# Agreements = ~15 sample employment agreements
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# UN-Resolutions-500 = 500 United Nations Resolutions (~2 years) - public repo - PDF files
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# Invoices = ~40 invoice sample documents
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# FinDocs = ~15 financial annual reports, earnings and 10Ks
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# AWS-Transcribe = ~5 AWS-transcribe JSON files
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# SmallLibrary = ~10 mixed document types for quick testing
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# Images = ~3 images for OCR processing
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# Note: these files will be updated from time-to-time - if you want to pull fresh new files
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# sample_files_path = Setup().load_sample_files(over_write=True)
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# These files were prepared by LLMWare from public domain materials or invented bespoke as examples
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# If you have any concerns about PII or the suitability or any material, please let us know
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# We reserve the right to withdraw documents at any time
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return 0
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def get_llmware_voice_sample_files():
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print (f"\n > Loading the llmware Sample Voice Files...")
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# check out the examples: Models/using-whisper-cpp-sample-files.py and
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# Use_Cases/parsing_great_speeches.py
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# this call to Setup() will pull the sample files from a public S3 repo
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# the files will be placed in folders locally at the sample voice files path
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sample_files_path = Setup().load_voice_sample_files(over_write=False,small_only=False)
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print(f"> Sample Voice Files Path - {sample_files_path}")
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print(f"> Sample Voice Folders - {os.listdir(sample_files_path)}")
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# examples - "famous_quotes" | "greatest_speeches" | "youtube_demos" | "earnings_calls"
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# -- famous_quotes - approximately 20 small .wav files with clips from old movies and speeches
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# -- greatest_speeches - approximately 60 famous historical speeches in english
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# -- youtube_videos - wav files of ~3 llmware youtube videos
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# -- earnings_calls - wav files of ~4 public company earnings calls (gathered from public investor relations)
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# These sample files are hosted in a non-restricted AWS S3 bucket, and downloaded via the Setup method
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# `load_sample_voice_files`. There are two options:
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# -- small_only = True: only pulls the 'famous_quotes' samples
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# -- small_only = False: pulls all of the samples (requires ~1.9 GB in total)
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# Please note that all of these samples have been pulled from open public domain sources, including the
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# Internet Archives, e.g., https://archive.org. These sample files are being provided solely for the purpose of
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# testing the code scripts below. Please do not use them for any other purpose.
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return 0
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if __name__ == "__main__":
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get_llmware_sample_files()
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get_llmware_voice_sample_files()
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