Building a chatbot with Fivetran and LangChain

This text provides a detailed guide on building an automated helpdesk chatbot using Zendesk data hosted in an S3 data lake, Python, OpenAI's GPT-4, ChromaDB for vector database and LangChain API. The process involves setting up a connector from the source to the destination using Fivetran, extracting, transforming and vectorizing relevant data from the data repository, loading it into a vector database, setting up a user interface that can accept prompts and search for relevant context from the vector database, and having the retrieval model send augmented prompts to the foundation model and generate responses. The tutorial also covers how to run and tune the app using Streamlit.