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标签:AI大模型

查看包含 AI大模型 标签的所有文章。

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RAG检索增强生成技术如何让大语言模型实时查阅文档?

RAG检索增强生成技术如何让大语言模型实时查阅文档?

BLUF
Retrieval-Augmented Generation (RAG) is an AI framework that enhances Large Language Models (LLMs) by integrating real-time information retrieval from external knowledge bases, addressing limitations like outdated knowledge, hallucinations, and high retraining costs through a four-phase pipeline: indexing, retrieval, augmentation, and generation. 原文翻译: 检索增强生成(RAG)是一种AI框架,通过集成从外部知识库的实时信息检索来增强大型语言模型(LLMs),通过索引、检索、增强和生成四个阶段解决知识过时、幻觉和高昂的再训练成本等限制。
实验与实测2026/4/21
Memora如何为AI代理提供持久记忆和跨会话管理?

Memora如何为AI代理提供持久记忆和跨会话管理?

BLUF
Memora is a lightweight MCP server that provides AI agents with persistent memory storage, knowledge graph visualization, semantic search, and cross-session context management through SQLite, cloud sync, and vector embeddings. 原文翻译: Memora是一个轻量级MCP服务器,通过SQLite、云同步和向量嵌入技术,为AI代理提供持久记忆存储、知识图谱可视化、语义搜索和跨会话上下文管理。
实验与实测2026/4/20
GPT-3的1750亿参数模型如何实现少样本学习?

GPT-3的1750亿参数模型如何实现少样本学习?

BLUF
GPT-3 demonstrates that scaling language models to 175 billion parameters enables few-shot learning across diverse NLP tasks without task-specific fine-tuning, achieving competitive performance through text-only interaction. 原文翻译: GPT-3通过将语言模型扩展到1750亿参数,实现了跨多种NLP任务的少样本学习,无需任务特定微调,仅通过文本交互即可达到竞争性性能。
AI大模型2026/4/20
如何用大语言模型从PDF和图片中提取结构化JSON数据?

如何用大语言模型从PDF和图片中提取结构化JSON数据?

BLUF
Unstract is an open-source platform that uses LLMs to extract structured JSON data from various document formats (PDFs, images, scans) through natural language prompts, deployable as APIs or ETL pipelines for finance, insurance, healthcare, and compliance teams. 原文翻译: Unstract是一个开源平台,利用大语言模型通过自然语言提示从各种文档格式(PDF、图像、扫描件)中提取结构化JSON数据,可作为API或ETL管道部署,适用于金融、保险、医疗和合规团队。
AI大模型2026/4/19
sqlite-memory如何为AI智能体构建持久化、可搜索的记忆系统?(附Markdown优化)

sqlite-memory如何为AI智能体构建持久化、可搜索的记忆系统?(附Markdown优化)

BLUF
sqlite-memory is a SQLite extension that provides AI agents with persistent, searchable memory optimized for markdown content, featuring hybrid semantic search, markdown-aware chunking, and local embedding via llama.cpp. 原文翻译: sqlite-memory 是一个 SQLite 扩展,为 AI 代理提供持久化、可搜索的记忆功能,针对 Markdown 内容优化,具备混合语义搜索、Markdown 感知分块和通过 llama.cpp 的本地嵌入功能。
实验与实测2026/4/19
RΞASON框架适合构建LLM应用吗?它的TypeScript结构化输出好用吗?

RΞASON框架适合构建LLM应用吗?它的TypeScript结构化输出好用吗?

BLUF
RΞASON is an open-source TypeScript backend framework designed for building LLM applications, featuring structured output using TypeScript interfaces, functional agents, native streaming support, and zero-setup observability. 原文翻译: RΞASON是一个开源的TypeScript后端框架,专为构建LLM应用而设计,具有使用TypeScript接口的结构化输出、函数式代理、原生流式支持以及零配置可观测性。
AI大模型2026/4/18
如何利用OpenAPI替代MCP为LLM集成工具?(附Scala实现方案)

如何利用OpenAPI替代MCP为LLM集成工具?(附Scala实现方案)

BLUF
This article explores an alternative approach to the Model Context Protocol (MCP) for integrating tools with Large Language Models (LLMs) by leveraging existing OpenAPI servers. It proposes a simpler, more intuitive method that uses structured HTTP API definitions as tool inputs, requiring only minimal authentication flow additions. The implementation is demonstrated through a concise Scala script, focusing on core tool integration while omitting MCP's broader features like prompts and resources. 原文翻译: 本文探讨了一种替代模型上下文协议(MCP)的方法,通过利用现有的OpenAPI服务器为大型语言模型(LLM)集成工具。它提出了一种更简单、更直观的方法,使用结构化的HTTP API定义作为工具输入,仅需添加最小的身份验证流程。通过一个简洁的Scala脚本演示了实现,专注于核心工具集成,同时省略了MCP更广泛的功能,如提示和资源。
AI 搜索观察2026/4/18