ollama/examples/privategpt/README.md
2023-08-11 00:18:13 -07:00

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