LLM 模型排行

Make Opus 4.8 (or any Claude model) work like Claude Fable 5 — a Claude Code skill + guard hooks (plan gate, model ceiling, per-task enforcement) for Fable-5-grade discipline: plan, self-verify, and route sub-agents, without Fable 5.

Top 10 Claude Prompt Optimization Frameworks 2026

Best Prompt Engineering Tools for 2026 AI Workflow Optimization

Robust and fast topic models with sentence-transformers.

Anaxa 是一个面向科研工作流的开源智能体系统。它不是单纯的聊天机器人，也不是无人监管的自动发论文机器，而是把文献检索、证据审计、实验执行、论文写作、同行评审式检查和最终产物打包放进同一个可追踪的研究生命周期中。

Examples and tutorials for building AI applications with watsonx.ai Flows Engine

Circuitron: Agentic PCB Design Accelerator — Generate, plan, and layout circuits from natural language prompts.

Multi-Agent,MCP,RAG,SpringAI1.0.0,RE-ACT

Ask questions about your Obsidian notes using local AI. Privacy-first RAG with Ollama, LM Studio, or any OpenAI-compatible server. Obsidian plugin + Docker + PyPI.

Own your AI memory — import ChatGPT, Claude and Gemini exports, see what each AI knows about you. Checkpoint/restore and cross-model continuity for agents.

AI World Generator 2026: Create Self-Evolving Maps & Stories

Official Neuron AI Laravel SDK

[RAG训练营] u.geekbang.org/subject/airag/1009927 这是我用Cursor自行制作的RAG Framework，好处是可以掌控RAG每一个环节的教学细节。

A Survey of Personalization: From RAG to Agent

Build Enterprise RAG (Retriver Augmented Generation) Pipelines to tackle various Generative AI use cases with LLM's by simply plugging componants like Lego pieces.

Advanced document extraction and chunking techniques for retrieval augmented generation that is aware of the layout of documents. Increases knowledge retrieval accuracy and provides control for retrieved knowledge context management

Simulate AI Personas in Social Feeds with Real-Time Chat Bots 2026

VT.ai - multimodal AI chat app with dynamic conversation routing

LocalChat is a ChatGPT-like chat that runs on your computer

This repository guides you through the process of building a GPT-style Large Language Model (LLM) from scratch using PyTorch. The structure and approach are inspired by the book Build a Large Language Model (From Scratch) by Sebastian Raschka.