A low code AI chat assistant that utilizes Flowise and LLMs for for real-time question answering.
This use case explores how Flowise, a low-code AI orchestration tool, can be leveraged to develop an AI-powered Chat Assistant for real-time question answering and food safety intelligence retrieval. By integrating Large Language Models (LLMs) with Retrieval-Augmented Generation (RAG), vector databases, and in-memory memory mechanisms, this system provides users with context-aware, accurate, and transparent responses.
We used this system to create FOODAKAI’s assistant-an assistant capable of answering our clients questions on how to how the FOODAKAI platform. The Chat Assistant was built using Flowise, an open-source UI for LangChain, and deployed on Render, ensuring accessibility and ease of use.
src/ --> includes the Flowise configuration and any custom components used in the project.