- This is an end-to-end LLM project based on Google Generative AI and Langchain. In this project I built a Q&A system based on a data from an e-learning company called codebasics (website: codebasics.io). Codebasics sells data related courses and bootcamps. They have thousands of learners who uses discord server or email to ask questions. This system will provide a streamlit based user interface for students where they can ask questions and get answers.
- Check site here
- Use a real CSV file of FAQs that Codebasics company(E-Learning platform) is using right now.
- Their human staff will use this file to assist their course learners.
- We will build an LLM based question and answer system that can reduce the workload of their human staff.
- Students should be able to use this system to ask questions directly and get answers within seconds
- FAISS
- dotenv
- streamlit
- sentence-transformer
- langchain + GoogleGenerativeAI
- Huggingface instructor embeddings: Text embeddings
- Prerequisites
- Git
- Command line familiarity
- Clone the Repository:
git clone https://github.com/NebeyouMusie/QA-System-for-E_Learning.git - Create and Activate Virtual Environment (Recommended)
python -m venv venvsource venv/bin/activate
- Navigate to the projects directory
cd ./QA-System-for-E_Learningusing your terminal - Install Libraries:
pip install -r requirements.txt
- run
streamlit run app.py - The web app will open in your browser.
- To create a knowledebase of FAQs, click on Create Knolwedge Base button. It will take some time before knowledgebase is created so please wait.
- Once knowledge base is created you will see a directory called faiss_index in your current folder
- Now you are ready to ask questions. Type your question in Question box and hit Enter
- Do you guys provide internship and also do you offer EMI payments?
- Do you have javascript course?
- Should I learn power bi or tableau?
- I've a MAC computer. Can I use powerbi on it?
- I don't see power pivot. how can I enable it?
- app.py: The main Streamlit application script.
- langchain_utils.py: This has all the langchain code
- requirements.txt: A list of required Python packages for the project.
- notebook: jupyter notebook folder
- .env: Configuration file for storing your Google API key.
- Contributions are welcomed
- Give this project a star ⭐ if you like it
- I would like to thank codebasics
- LinkedIn: Nebeyou Musie
- Gmail: nebeyoumusie@gmail.com
- Telegram: Nebeyou Musie