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# privateGPT with Llama 2 Uncensored
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> Note: this example is a slightly modified version of PrivateGPT using models such as Llama 2 Uncensored. All credit for PrivateGPT goes to Iván Martínez who is the creator of it, and you can find his GitHub repo [here](https://github.com/imartinez/privateGPT).
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### Setup
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Set up a virtual environment (optional):
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```
python3 -m venv .venv
source .venv/bin/activate
```
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Install the Python dependencies:
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```shell
pip install -r requirements.txt
```
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Pull the model you'd like to use:
```
ollama pull llama2-uncensored
```
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### Getting WeWork's latest quarterly report
```
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mkdir source_documents
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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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### Ingesting files
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```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
```
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### Ask questions
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```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).
```
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### Try a different model:
```
ollama pull llama2:13b
MODEL=llama2:13b python privateGPT.py
```
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## Adding more files
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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),