| # kagglex-final-project |
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| 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/). |
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| 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. |
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| ## Pre-requisites |
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| - 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 |
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| ## Install and run |
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| 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.** |
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| ```bash |
| pip install -r requirements.txt |
| ``` |
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| ### Interactive session via CLI app |
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| ```bash |
| python main.py |
| ``` |
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| ### Interactive session via Streamlit app |
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| ```bash |
| streamlit run main.py |
| ``` |
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