This is an end to end LLM project based on Google Palm and Langchain. We are building a Q&A system for 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.

• Use a real CSV file of FAQs that Codebasics 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

• Langchain + Google Palm: LLM based Q&A
• Streamlit: UI
• Huggingface instructor embeddings: Text embeddings
• FAISS: Vector databse

1.Clone this repository to your local machine using:

  git clone https://github.com/codebasics/langchain.git

2.Navigate to the project directory:

  cd 3_project_codebasics_q_and_a

3. Install the required dependencies using pip:

  pip install -r requirements.txt

4.Acquire an api key through makersuite.google.com and put it in .env file

  GOOGLE_API_KEY="your_api_key_here"

1. Run the Streamlit app by executing:

streamlit run main.py

2.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?

• 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.