Q-A-Chatbot-System-for-E-learning-Company

Purpose

Developed a chatbot Q&A system for e-learning company, to provide instant and accurate answers to learners' questions, enhancing their learning experience

Description:

Designed and developed a chatbot Q&A system leveraging Google PaLM and Langchain, with a userfriendly Streamlit interface. Utilized Hugging Face Instructor Embeddings for text embeddings and FAISS for vector database management. This chatbot system enables learners to ask questions and receive answers in real-time, improving learner engagement and reducing support queries (Streamlit, Langchain, Google Palm LLM, FAISS, RAG (Retrieval-Augmented-Generation), PyCharm)

Project Highlights

• Use a real CSV file of FAQs that Ed - company 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

  Tools

• Langchain + Google Palm: LLM based Q&A

• Streamlit: UI

• Huggingface instructor embeddings: Text embeddings

• FAISS: Vector databse

Project Structure

• main.py: The main Streamlit application script.
• langchain_helper.py: This has all the langchain code
• requirements.txt: A list of required Python packages for the project.
• .env: Configuration file for storing your Google API key.