66 lines
1.7 KiB
Markdown
66 lines
1.7 KiB
Markdown
# privateGPT with Llama 2 Uncensored
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> Note: this example is a simplified version of [PrivateGPT](https://github.com/imartinez/privateGPT) that works with Llama 2 Uncensored.
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### Setup
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```shell
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pip install -r requirements.txt
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```
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### Getting WeWork's latest quarterly report
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```
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curl https://d18rn0p25nwr6d.cloudfront.net/CIK-0001813756/975b3e9b-268e-4798-a9e4-2a9a7c92dc10.pdf -o source_documents/wework.pdf
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```
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### Ingesting data
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```shell
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python ingest.py
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```
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Output should look like this:
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```shell
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Creating new vectorstore
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Loading documents from source_documents
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Loading new documents: 100%|██████████████████████| 1/1 [00:01<00:00, 1.73s/it]
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Loaded 1 new documents from source_documents
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Split into 90 chunks of text (max. 500 tokens each)
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Creating embeddings. May take some minutes...
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Using embedded DuckDB with persistence: data will be stored in: db
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Ingestion complete! You can now run privateGPT.py to query your documents
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```
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### Ask Questions!
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```shell
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python privateGPT.py
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Enter a query: How many locations does WeWork have?
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> Answer (took 17.7 s.):
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As of June 2023, WeWork has 777 locations worldwide, including 610 Consolidated Locations (as defined in the section entitled Key Performance Indicators).
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```
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## Adding your own data
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Put any and all your files into the `source_documents` directory
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The supported extensions are:
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- `.csv`: CSV,
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- `.docx`: Word Document,
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- `.doc`: Word Document,
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- `.enex`: EverNote,
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- `.eml`: Email,
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- `.epub`: EPub,
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- `.html`: HTML File,
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- `.md`: Markdown,
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- `.msg`: Outlook Message,
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- `.odt`: Open Document Text,
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- `.pdf`: Portable Document Format (PDF),
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- `.pptx` : PowerPoint Document,
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- `.ppt` : PowerPoint Document,
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- `.txt`: Text file (UTF-8),
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