搜索结果：官方

Cognee is an open-source framework for building sophisticated AI memory applications with hybrid architecture combining graphs, vectors, and structured data, enabling persistent, structured memory for AI agents. 原文翻译： Cognee 是一个开源框架，用于构建复杂的 AI 记忆应用程序，采用结合图、向量和结构化数据的混合架构，为 AI 智能体提供持久化、结构化的记忆能力。

This article explores Generative Engine Optimization (GEO), analyzing its core mechanisms, the current industry landscape dominated by 'black-hat' and 'gray-hat' practices that pollute AI data sources, and providing a responsible framework for 'white-hat' GEO. It offers a consumer defense guide against AI marketing traps and discusses future trends, including the 'ask-and-buy' model and the strategic importance of influencing pre-training data.

This article introduces a Chinese translation project for the book 'Build a Large Language Model (From Scratch)', providing a comprehensive guide for developers to understand and implement LLMs from the ground up, including practical code and insights into future AI trends. 原文翻译： 本文介绍了《Build a Large Language Model (From Scratch)》一书的中文翻译项目，为开发者提供了从零开始理解和实现大语言模型的全面指南，包含实践代码和对未来AI趋势的见解。

This article explores Generative Engine Optimization (GEO), analyzing its core principles, the current industry landscape of 'white hat' vs. 'black hat' practices, and future trends. It provides a defensive guide for consumers against AI marketing traps and outlines responsible GEO frameworks for brands. 原文翻译： 本文深入探讨生成式引擎优化（GEO），分析其核心原理、当前行业“白帽”与“黑帽”实践现状及未来趋势。它为消费者提供了防范AI营销陷阱的防御指南，并为品牌概述了负责任的GEO框架。

This article demystifies the core engineering concepts behind LLM API calls, focusing on Tokenization, Context Window management, and decoding parameters (Temperature, Top-p, Top-k). It provides practical guidance for optimizing performance, managing costs, and avoiding common pitfalls in production environments, especially within complex architectures like RAG and Agent workflows. 原文翻译： 本文揭秘了LLM API调用背后的核心工程概念，重点阐述了Token化、上下文窗口管理以及解码参数（Temperature、Top-p、Top-k）。它为优化性能、管理成本以及避免在生产环境（尤其是在RAG和Agent工作流等复杂架构中）的常见陷阱提供了实用指南。

DeepSeek作为国产开源大模型，在“百模大战”中以极致技术专注和开源策略脱颖而出，提供高性能、免费商用的模型，显著降低了AI技术使用门槛。 原文翻译： DeepSeek, as a domestic open-source large model, stands out in the "Hundred-Model War" with its extreme technical focus and open-source strategy. It delivers high-performance, free-for-commercial-use models, significantly lowering the barrier to AI technology adoption.

GLM-5 is Zhipu AI's flagship base model designed for Agentic Engineering, achieving state-of-the-art (SOTA) performance in open-source coding and agent capabilities. It excels in complex system engineering and long-range agent tasks, with real-world programming experience comparable to Claude Opus 4.5, making it an ideal foundation for general-purpose agent assistants. 原文翻译： GLM-5是智谱AI面向Agentic Engineering打造的旗舰基座模型，在开源Coding与Agent能力上取得SOTA表现。擅长复杂系统工程与长程Agent任务，真实编程场景使用体感逼近Claude Opus 4.5，是通用Agent助手的理想基座。

NexaSDK is a high-performance local inference framework that enables developers to run the latest multimodal AI models on NPU, GPU, and CPU across multiple platforms with minimal energy consumption and maximum speed. 原文翻译： NexaSDK是一个高性能本地推理框架，让开发者能够在NPU、GPU和CPU上以最低能耗和最高速度运行最新的多模态AI模型，支持跨多个平台。

This article provides a comprehensive 2026 guide for Chinese users to access and utilize Google's Gemini models, particularly Gemini 3 Pro, overcoming regional access barriers through platforms like n.myliang.cn. It covers practical applications in multimodal tasks, AI-assisted office work, programming, and SEO optimization. 原文翻译： 本文为国内用户提供了一份全面的2026年指南，介绍如何通过n.myliang.cn等平台访问和使用谷歌Gemini模型（特别是Gemini 3 Pro），以克服地域访问限制。内容涵盖多模态任务、AI辅助办公、编程和SEO优化等实际应用。

DeepAgents is LangChain's latest open-source framework designed to simplify the development of complex, multi-step AI agents by providing built-in capabilities for task planning, virtual file systems, and subagent collaboration, enabling developers to build more robust and capable agents with less code. 原文翻译： DeepAgents是LangChain最新推出的开源框架，旨在简化复杂多步骤AI智能体的开发，通过提供任务规划、虚拟文件系统和子智能体协作等内置能力，使开发者能够用更少的代码构建更强大、更可靠的智能体。