An overview of deploying AI chatbots using LangChain and Streamlit, two powerful tools that simplify building and deploying language model apps with minimal coding experience.
Have you ever wanted to build your own chatbot or AI assistant app? In this overview, we will be exploring two of the most popular tools for creating and deploying impressive chatbots— Streamlit and LangChain. Even if you have zero coding experience, you’ll be able to deploy state-of-the-art large language model apps by the end by the end of this walkthrough.
In the world of AI, large language models (LLMs) have emerged as game-changers, revolutionizing how we process and understand massive amounts of text data. LangChain is a Python library that helps developers build applications combining Large Language Models with other sources of computation or knowledge. With it, you can build conversational AI systems like chatbots, semantic search engines, summarization tools, and more. It provides a simple API for using common LLMs like GPT-3.
Streamlit is an open-source Python library that allows you to quickly create web apps simply by writing Python scripts. It handles all the frontend/UI work so you can focus just on writing Python code.
In this article, we will walk you through the process of deploying LangChain apps using Streamlit.
LangChain enables the creation of autonomous AI agents that can work in groups of specialized AIs to solve complex problems. It can also reflect on its own work and improve its output. You can use it to create applications that can perform tasks such as notifying you of trends in Amazon’s stock or creating a business plan based on your ideas, interests, and skills. You can even create specialized agents such as email agents or study buddy agents.
We prepared a notion guide you can follow to program your own Streamlit chatbot, all in your browser. There is no need to install python or any software.
That’s it! With LangChain and Streamlit, you have everything you need to start building and deploying production-ready AI chatbots, semantic search engines, content generators and way more. The possibilities are endless!
LangChain and Streamlit offer various resources to help you create more complex and engaging applications. These include guides for using LangChain for tasks such as document retrieval, memory management, and creating AI agents. Reference their documentation at LangChain
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