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MMSearch-R1 introduces a reinforcement learning framework that enables large multimodal models to perform efficient, on-demand searches by learning when and how to retrieve relevant information, significantly improving accuracy and reducing search overhead.
Discover how to create an intelligent AI assistant using LangChain, Gemini 2.0, and Jina Search that provides real-time, well-sourced answers to user queries.
This tutorial explores building a powerful question-answering system by integrating Tavily Search API, Chroma, Google Gemini LLMs, and LangChain, featuring hybrid retrieval, semantic caching, and advanced prompt engineering.
Google’s new AI Mode enhances search by combining generative AI with live web data, improving shopping, travel planning, and interactive research for U.S. users.
A comprehensive tutorial on integrating Dappier AI's real-time search and recommendation tools with OpenAI's chat API to build intelligent conversational applications with live data and personalized content.