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This project demonstrates a Retrieval-Augmented Generation (RAG) pipeline using LangChain, Pinecone, and Google's Generative AI. It processes documents, generates embeddings, stores them in a Pinecone ...
Using the above, we set up an RAG pipeline using the LangChain framework. It creates a custom prompt with instructions and placeholders, incorporates a retriever for context, and leverages a language ...
Retrieval-Augmented Generation (RAG) is an AI architecture that enhances the capabilities of Large Language ... We’ll embed the text chunks using a pre-trained model and store them in a Chroma vector ...
The Langchain Agent UI, powered by the open source CoAgent framework, is reshaping how developers approach the creation of AI agents. By seamlessly integrating critical components such as memory ...
LangChain, the agentic AI pioneer, introduced the term “ambient agents” on January 14. The technology that LangChain develops includes its eponymous open source LangChain framework that ...
To gain competitive advantage from gen AI, enterprises need to be able to add their own expertise to off-the-shelf systems. Yet standard enterprise data stores aren't a good fit to train large ...