A Quick Way to Prototype RAG Applications Based on LangChain
Remember the days when building a smart chatbot took months of coding?
Frameworks like LangChain have definitely streamlined development, but hundreds of lines of code can still be a hurdle for those who aren’t programmers.
Is there a simpler way ?
Photo by Ravi Palwe on Unsplash
That’s when I discovered “Lang Flow,” an open-source package that builds upon the Python version of LangChain. It lets you create an AI application without needing to write a single line of code. It provides you a canvas where you can just drag components around and link them up to build your chatbot.
In this post, we’ll use LangFlow to build a smart AI chatbot prototype in minutes. For the backend, we’ll use Ollama for embedding models and Large Language Model, meaning that the application runs locally and free of charge! Finally, we’ll convert this flow into a Streamlit application with minimal coding.
In this project, we’re going to build an AI chatbot, and let’s name it “Dinnerly —…
