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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 ...

春节前幻方量化发布的大模型DeepSeek-R1，一经亮相便迅速炸场AI领域，全球的企业管理者、创业者、项目经理、分析师乃至相关部门领导人都现身说法，感慨DeepSeek-R1在大模型领域取得的突破性进展。

本文重点介绍大模型意图识别能力在智能电视核心链路中的落地过程和思考，对比了基础模型、RAG 、以及7b模型微调三种方案的优缺点。 业务背景 ...

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 ...

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 ...