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# kagglex-final-project
A prototype written in Python to illustrate/demonstrate querying the Learning Path Index Dataset (see [Kaggle Dataset](https://www.kaggle.com/datasets/neomatrix369/learning-path-index-dataset) and [GitHub repo](https://github.com/neomatrix369/learning-path-index)), with the help of the OpenAI GPT technology (InstructHPT model and embeddings model), [Langchain](https://python.langchain.com/) and using [Facebook's FAISS library](https://faiss.ai/).
The end-to-end process can be learnt by going through the code base as well as by observing the console logs when using both the Streamlit and the CLI versions.
## Pre-requisites
- Python 3.8.x or above
- OpenAI API Key (see [How to get an OpenAI API Key](https://www.howtogeek.com/885918/how-to-get-an-openai-api-key/) -- note it's may not be FREE anymore)
- Install dependencies from `requirements.txt`
- Basic Command-line experience
- Basic git and GitHub experience
## Install and run
Copy the `.env_template` to `.env` in the current folder and then add your OpenAI API Key to `.env`.
**Please don't modify the `.env_template` file.**
```bash
pip install -r requirements.txt
```
### Interactive session via CLI app
```bash
python main.py
```
### Interactive session via Streamlit app
```bash
streamlit run main.py
```
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