6、https://www.pinecone.io/learn/chunking-strategies/ Chunking Strategies for LLM Applications
(https://blog.langchain.dev/enhancing-rag-based-applications-accuracy-by-constructing-and-leveraging-knowledge-graphs/),因为它们提供了一个丰富的、相互连接的数据集,可以用于更准确和具有感知环境的数据检索。例如,在医学知识图谱中,节点可以表示症状、疾病和治疗方法,边则定义了诸如“症状为”或“治疗方法”的...
- 提出后续工作,包括持续更新、微调嵌入模型和LLM、收集用户反馈等。 - 强调了Ray和Anyscale如何帮助构建、扩展和产品化LLM应用。 《Building RAG-based LLM Applications for Production (Part 1)》 O网页链接 GitHub: github.com/ray-project/llm-applications Notebook: github.com/ray-project/llm-applications/...
This topic describes how to deploy a RAG-based LLM chatbot and how to perform model inference. Background information LLM applications have limits in generating accurate and real-time responses. Therefore, LLM applications are not applicable to scenarios that require precise information, such as ...
Expanding LLM Applications: From RAG to Agentic Systems In this comprehensive session, Staff Developer Advocate Richmond Alake explores the evolution of LLM applications, starting with RAG and progressing to developing sophisticated AI agents that leverage RAG as tools. Whether you're an...
3.Fact-based reasoning and prediction capabilities:“Based on the description of the patient’s condition, predict the most likely disease they may have.” This task tests the system’s ability to organize, collect, and retrieve information while requiring the LLM ...
所有的索引存储统一抽象为IndexStore，LLM服务作为构建索引能力依赖（文本模型、嵌入模型等）。索引存储当下支持向量存储（VectorStore）和知识图谱（Knowledge Graph）两种，保留对其他索引格式的扩展能力。知识图谱层负责知识的表示和语义抽象，数据底座是图存储（GraphStore）。当然也可以直接对接外部的知识图谱系统。最底层...
As aGoogle Cloud Partner, in this instance we refer to text-based Gemini 1.5 Pro, a large language model (LLM). Gemini 1.5 Pro automates and enhances requirements engineering, by using a retrieval system that fetches relevant document chunks from a large knowledge base, as...
We will learn how to use LlamaIndex to build a RAG-based application for Q&A over the private documents and enhance the application by incorporating a memory buffer. This will enable the LLM to generate the response using the context from both the document and previous interactions. What is ...
The evolution and adoption of large language models (LLMs) have been nothing short of revolutionary, with retrieval-based systems at the forefront of this technological leap. 大型语言模型(LLM)的演变和采用几乎是革命性的,基于检索的系统处于这一技术飞跃的前沿。