Build Conversational Agents with Vector DBs - LangChain

Learn how to enhance conversational agents by integrating them with retrieval augmentation tools using Pinecone vector database and OpenAI embedding and gpt-3.5-turbo completion models. The course covers setting up the code, preparing data, creating a vector DB pipeline, indexing with OpenAI and Pinecone, querying via LangChain, building a retrieval augmented chatbot, using the conversational agent chatbot, and real-world applications of this method. The course aims to teach the integration of conversational agents with retrieval augmentation tools to improve data freshness, domain knowledge, and access to internal documentation. The intended audience includes individuals interested in artificial intelligence, chatbots, NLP, and deep learning.