https://github.com/lexiestleszek/chatwithdata
Chat with Data app (RAG implementation using Orca-Mini3b, FAISS, Streamlit)
https://github.com/lexiestleszek/chatwithdata
Last synced: 3 months ago
JSON representation
Chat with Data app (RAG implementation using Orca-Mini3b, FAISS, Streamlit)
- Host: GitHub
- URL: https://github.com/lexiestleszek/chatwithdata
- Owner: LexiestLeszek
- Created: 2023-11-29T17:29:14.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2023-11-29T20:45:32.000Z (almost 2 years ago)
- Last Synced: 2025-01-13T21:44:19.143Z (9 months ago)
- Language: Python
- Size: 12.7 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# chatwithdata
Streamlit app to chat with data (RAG implementation using Orca-Mini3b, FAISS, Streamlit). Currently only *.csv type of data. You can upload any csv file and get insights out of it.
## Setup
1. You need Python installed. If you don't have Python installed, install if from this [link](https://www.python.org/downloads/)
2. Clone the repository.
```
git clone https://github.com/LexiestLeszek/chatwithdata.git
```
3. Once cloned, go inside the repository or folder.
```
cd chatwithdata
```
4. Thanks to the GPT4ALL guys, download the model file, create "model" folder in the main directory and put the model there
```
https://gpt4all.io/models/gguf/orca-mini-3b-gguf2-q4_0.gguf
```
5. Create a virtual environment and activate it.
```
python3 -m venv .venv && source .venv/bin/activate
```
6. Install the packages from the requirements.txt file.
```
pip install -r requirements.txt
```
7. Run the streamlit app.
```
streamlit run ch.py
```
After running the streamlit command, you should now be able to access the app at http://localhost:XXXX/. Upload the csv file and happy chatting.