![Scaling Search with Milvus: Handling Massive Datasets with Ease](https://assets.zilliz.com/large_Scaling_Search_with_Milvus_Handling_Massive_Datasets_with_Ease_2_f16d30b715.png)
Engineering
Scaling Search with Milvus: Handling Massive Datasets with Ease
A tutorial on how to scale your search engine with massive amounts of data using the Milvus vector database.
![Optimizing Multi-agent Systems with Mistral Large, Mistral Nemo, and Llama-agents](https://assets.zilliz.com/large_Optimizing_Multi_agent_Systems_with_Mistral_Large_Mistral_Nemo_and_Llama_agents_b230b29d7e.png)
Engineering
Optimizing Multi-agent Systems with Mistral Large, Mistral Nemo, and Llama-agents
Agents can handle complex tasks with minimal human intervention. Learn how to build such agents with Mistral Large, Nemo, Llama agents, and Milvus.
![Function Calling with Ollama, Llama 3.1 and Milvus](https://assets.zilliz.com/large_Function_Calling_with_Ollama_Llama_3_1_and_Milvus_80833d5c63.png)
Engineering
Function Calling with Ollama, Llama 3.1 and Milvus
A step-by-step guide on how to integrate Llama 3.1 with external tools like Milvus vector database and APIs to build powerful, context-aware applications.
![Metadata Filtering, Hybrid Search or Agent When Building Your RAG Application](https://assets.zilliz.com/large_Metadata_Filtering_Hybrid_Search_or_Agent_When_Building_Your_RAG_Application_463c7c1efb.png)
Engineering
Metadata Filtering, Hybrid Search or Agent When Building Your RAG Application
Using Metadata Filtering, Hybrid Search, and Agents, all integrated in Milvus, can enhance your RAG application.
![Simplifying Legal Research with RAG, Milvus, and Ollama](https://assets.zilliz.com/large_Simplifying_Legal_Research_with_RAG_Milvus_and_Ollama_66918c55d6.png)
Case Study
Simplifying Legal Research with RAG, Milvus, and Ollama
In this blog post, we will see how we can apply RAG to Legal data. Legal research can be time-consuming. You usually need to review a large number of documents to find the answers you need. Retrieval-Augmented Generation (RAG) can help streamline your research process.
![Building Intelligent RAG Applications with LangServe, LangGraph, and Milvus](https://assets.zilliz.com/large_June_24_Building_Intelligent_RAG_Applications_with_Lang_Serve_Lang_Graph_and_Milvus_29db4a5d23.png)
Engineering
Building Intelligent RAG Applications with LangServe, LangGraph, and Milvus
Build a RAG system using agents with LangServe, LangGraph, Llama 3, and Milvus.
![Local Agentic RAG with LangGraph and Llama 3](https://assets.zilliz.com/large_June_14_Local_Agentic_RAG_with_Lang_Graph_and_Llama3_c27c6fa8d7.png)
Engineering
Local Agentic RAG with LangGraph and Llama 3
In this blog post, we show you how to build a RAG system using agents with LangChain/ LangGraph, Llama 3, and Milvus.
![Multimodal RAG locally with CLIP and Llama3](https://assets.zilliz.com/large_May_09_Multimodal_RAG_locally_using_CLIP_and_Llama3_0a5751d3a3.png)
Engineering
Multimodal RAG locally with CLIP and Llama3
A tutorial walks you through how to build a multimodal RAG with CLIP, Llama3, and Milvus.
![Getting Started with Hybrid Search with Milvus](https://assets.zilliz.com/large_Hybrid_Search_with_Milvus_0fedf0098e.png)
Engineering
Getting Started with Hybrid Search with Milvus
In this tutorial, you will learn how to enhance your search by using Milvus 2.4's hybrid search capabilities.