This educational application introduced learners to core concepts in LLM-based document summarization by combining OpenAI’s GPT models with LangChain and ChromaDB. Built as part of a generative AI curriculum, the app let users upload any PDF and receive a contextual summary based on vector similarity and LLM-powered completion.
The app highlighted the basics of retrieval-augmented generation (RAG) and provided a hands-on entry point into using vector databases and structured chains.
- Accepted user-uploaded PDFs and processed content into segmented chunks
- Embedded vector representations using LangChain + Chroma
- Generated summaries using ChatGPT via OpenAI’s API
- Built for instruction in workshops, training, and GenAI demos
Tools & Stack
Streamlit · Python · LangChain · ChromaDB · OpenAI API · Prompt Engineering
Live Demo: jpschloss-open-ai-summarizer-app.streamlit.app
GitHub Repository: JPSchloss/Open-AI-Summarizer-App