llm-for-zotero
✨An AI research assistant plugin that deeply integrates LLMs into Zotero, featuring paper chat, multi-paper comparison, Agent Mode for automated literature management, and note export to Obsidian/Logseq.
An AI research assistant plugin that deeply integrates LLMs into Zotero, featuring paper chat, multi-paper comparison, Agent Mode for automated literature management, and note export to Obsidian/Logseq.
A self-hostable AI research workspace for grounded chat, paper study, 206+ scientific skills, and 13-stage deep research execution.
A local-first AI research assistant featuring multi-LLM support, 20+ research strategies, multi-search-engine integration, and automated quality scoring for 212K+ academic sources, producing citation-backed PDF/Markdown reports via CLI, Web UI, REST API, or MCP Server.
A systematic skill library for AI Agent context management, covering fundamentals, architectural patterns, operational optimization, and evaluation systems. Compatible with Claude Code, Cursor, and other platforms. Distinguished from prompt engineering by its holistic approach to curating all information entering the model's attention budget.
An open-source collection of tutorials and runnable scripts for over 30 advanced Retrieval-Augmented Generation (RAG) techniques, including Graph RAG, Agentic RAG, and various retrieval optimization strategies, implemented primarily with LangChain.
Official code repository for the O'Reilly book "Hands-On Large Language Models". Features 12 core chapters and bonus content covering Tokens, Transformers, RAG, and Fine-tuning. Includes 300+ illustrations and runnable Jupyter Notebooks optimized for Colab and local environments.
A comprehensive AI engineering hub featuring 93+ production-ready projects with in-depth tutorials and implementations for LLMs, RAGs, AI Agents, and MCP, covering beginner to advanced skill levels.
A curated collection of resources for Long Chain-of-Thought (Long-CoT) reasoning in LLMs, featuring papers, implementations, and datasets to track the latest advancements in the field.
Project information is incomplete; verified data has been retained for future updates.
A systematic collection of reading notes for LLMs top conference papers, covering motivation and method analysis in core areas like PEFT (LoRA/QLoRA), RAG, and Agents (RoleLLM), providing structured learning paths for algorithm engineers.
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