Gemini Quizzify

Mission

Create a quiz generator using Google Gemini, Langchain, Chroma, and Streamlit to explore LLMs and vector embeddings.

Requirements:

• Python version 3.11 or above
• Streamlit Documentation
• Google Cloud account
• Vertexai Documentation

Usage

To run the Quiz Builder:

1. Install the necessary dependencies listed in requirements.txt.
2. Run the Streamlit application by executing streamlit run xxx.py in the terminal where xxx is the name of the py file you want to run.
3. Follow the instructions provided in the user interface to interact with the Quiz Builder.

Tasks

Task 1: 🔑 Google Cloud, Vertex AI, & SDK Authentication

• Go to the Google Cloud Platform and select "Get Started for free".
• Sign in using your Google Account and complete the billing requirements.
• Create a new project.
• Navigation -> Artificial Intelligence -> Vertex AI -> Enable All Recommended APIs

Task 2: 💻 Dev Environment Setup

• Install the Google SDK using this link.
• Run the following command to initialize the SDK:

  gcloud init
  

• Sign in using your Google Account credentials.
• Select an existing project or Create a new project
• Add your Gemini authentication.json to the gitignore file

Task 3: 📥 Document Ingestion

• Install the streamlit framework

  pip install streamlit
  

• Create a file uploader using st.file_uploader() that only accepts PDF's
• Process the file using a PyPDFLoader

Task 4: 🔗 Embedding with VertexAI & Langchain

• Install the Langchain Vertex framework

  pip install langchain_google_vertexai
  

• Initialize VertexAIEmbeddings Client
• Create a function to retrieve embeddings for a single query
• Create a function to retrieve embeddings for multiple documents

Task 5: 🛠️ Data Pipeline to Chroma DB

• Create a Chroma collection from the documents processed by the DocumentProcessor (from previous tasks)
  • Split documents into chunks using Langchain's CharacterTextSplitter
  • Create the Chroma collection

Task 6: 📡 Streamlit UI for Data Ingestion

• Initialize DocumentProcessor, EmbeddingClient, and ChromaCollectionCreator from previous tasks
• Use Streamlit to capture user's inputs regarding quiz topic and desired number of questions
• Create a chroma collection from the processed documents

Task 7: 🧠 Quiz Generator Class

• Create a QuizGenerator Class
  • Create a question template
  • Enable a retriever using the vectorstore object
  • Create chain with the retriever, template, and llm as to generate a question based off of the various ingested documents

Task 8: 🔮 Generate Quiz Algorithm

• Loop the QuizGenerator and validate the questions uniqueness

Task 9: 🎓 Generate Quiz UI

• Create a Streamlit UI to visualize a question

Task 10: 🔄 Screen State Handling

• Enable the interface to handle all the quiz questions, move back and forth in the quiz, and display the correct answer and an explanation

Task 11: Preparing Submission

• A GitHub repository for the project containing all the project files.
• Loom Video to show the approach. Loom Link

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgements

Special thanks to the Radical AI team for allowing me to work on this AI Mission.