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DeepSeek V4 预览版于2026年4月发布，提供Pro（1.6T参数）和Flash（284B参数）两个版本，均支持1M tokens上下文和领先的Agent能力。其核心Agent能力包括Function Calling（支持并行/嵌套工具调用）、长上下文记忆、思考模式（推理增强）、结构化输出、多模态理解及主流Agent框架适配。API兼容OpenAI接口，支持流式/非流式调用。典型应用覆盖

RAG-Anything is an all-in-one RAG framework developed by HKUDS at the University of Hong Kong, open-sourced on GitHub. It aims to enhance LLM performance by integrating retrieval and generation, addre

free-claude-code is an open-source project that enables free use of Claude Code by proxying requests to free or low-cost model services like NVIDIA NIM, while retaining Claude Code's full engineering

Chip Huyen's blog covers key topics in AI engineering, including common pitfalls in building generative AI applications, agents, generative AI platforms, and LLM research challenges. The content is highly relevant for technical professionals building production AI systems. 原文翻译：Chip Huyen的博客涵盖了AI工程的关键主题，包括构建生成式AI应用的常见陷阱、智能体、生成式AI平台以及LLM研究挑战。内容对构建生产级AI系统的技术专业人士极具参考价值。

This article presents a local hybrid RAG pattern combining lexical retrieval, ONNX-based semantic embeddings, and Foundry Local chat model for offline AI assistants. It covers architecture, implementation, and best practices for graceful degradation when semantic path fails. 原文翻译：本文介绍了一种本地混合RAG模式，结合词法检索、基于ONNX的语义嵌入和Foundry Local聊天模型，用于离线AI助手。涵盖架构、实现和最佳实践，确保语义路径不可用时优雅降级。

Ssebowa is an open-source Python library offering generative AI models for text, image, and video generation, including LLM, VLLM, image generation, and video generation. It supports fine-tuning with

RAG-Anything is a lightweight RAG system based on LightRAG, designed for multimodal document processing (PDF, images, tables, formulas, etc.). It provides end-to-end parsing, multimodal understanding,

This book focuses on Generative Engine Optimization (GEO), starting from the underlying logic of the 'Answer Economy' and discussing a trust-centric growth model in the AI era. It is divided into four

This article explains the critical importance of structured outputs in LLM workflows, detailing how to implement them from scratch using JSON and Pydantic, and through the Gemini SDK, to build reliabl

This handbook provides comprehensive guidance for developers on ensuring structured outputs from Large Language Models (LLMs), covering tools, techniques, and best practices for reliable programmatic