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Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
Agent Laboratory is an end-to-end autonomous research workflow meant to assist you as the human researcher toward implementing your research ideas
Full stack, modern web application template. Using FastAPI, React, SQLModel, PostgreSQL, Docker, GitHub Actions, automatic HTTPS and more.
Hands-On Graph Neural Networks Using Python, published by Packt
EMNLP 2024 Findings "Schema-Driven Information Extraction from Heterogeneous Tables"
"LightRAG: Simple and Fast Retrieval-Augmented Generation"
MoviE Text Audio QA (MetaQA): a benchmark dataset for question answering
🤱🏻 Turn any webpage into a desktop app with Rust. 🤱🏻 利用 Rust 轻松构建轻量级多端桌面应用
Leveraging Large Language Models for Concept Graph Recovery and Question Answering in NLP Education
Official Implementation of 'Evaluating Large Language Models with Educational Knowledge Graphs: Challenges with Prerequisite Relationships and Multi-Hop Reasoning'
KAG is a logical form-guided reasoning and retrieval framework based on OpenSPG engine and LLMs. It is used to build logical reasoning and factual Q&A solutions for professional domain knowledge ba…
This is the official github repo of Think-on-Graph (ICLR 2024). If you are interested in our work or willing to join our research team in Shenzhen, please feel free to contact us by email (xuchengj…
[EMNLP 2024: Demo Oral] RAGLAB: A Modular and Research-Oriented Unified Framework for Retrieval-Augmented Generation
🔍 An LLM-based Multi-agent Framework of Web Search Engine (like Perplexity.ai Pro and SearchGPT)
Code and data for the ECIR 2024 full paper titled "DREQ: Document Re-Ranking Using Entity-based Query Understanding"
A Python client for the Neo4j Graph Data Science (GDS) library
🔥 Turn entire websites into LLM-ready markdown or structured data. Scrape, crawl and extract with a single API.
🚀🤖 Crawl4AI: Open-source LLM Friendly Web Crawler & Scraper
ChatPilot: Chat Agent Web UI，实现Chat对话前端，支持Google搜索、文件网址对话（RAG）、代码解释器功能，复现了Kimi Chat(文件，拖进来；网址，发出来)。
This includes the original implementation of SELF-RAG: Learning to Retrieve, Generate and Critique through self-reflection by Akari Asai, Zeqiu Wu, Yizhong Wang, Avirup Sil, and Hannaneh Hajishirzi.
Repository for "MultiHop-RAG: A Dataset for Evaluating Retrieval-Augmented Generation Across Documents" (COLM 2024)
Neo4j graph construction from unstructured data
Examples and guides for using the GLM APIs
A modular graph-based Retrieval-Augmented Generation (RAG) system