The LangChain library assists developers in building applications that are powered by large language models (LLMs) by providing a framework for connecting LLMs to other data sources. Pinecone is an efficient vector database that can store and retrieve vector data, such as text documents, while Streamlit is an open-source Python library that can create and share custom web apps for machine learning and data science. Combining these technologies results in a full-stack LLM app that can be quickly deployed. In this tutorial, the author demonstrates how to deploy a question-answering app using LangChain, Pinecone, and Streamlit. The process involves uploading vectors to Pinecone and deploying the app on Streamlit. The article provides instructions on how to accomplish these tasks step by step.
source update: Deploying a Langchain Large Language Model (LLM) with Streamlit &… – Towards AI
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