Open-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and agent workflows with explicit control over retrieval, routing, memory, and generation. Built for scalable agents, RAG, multimodal applications, semantic search, and conversational systems.

LLM-powered framework for deep document understanding, semantic retrieval, and context-aware answers using RAG paradigm.

Easy-to-use and powerful LLM and SLM library with awesome model zoo.

大规模中文自然语言处理语料 Large Scale Chinese Corpus for NLP

SoTA production-ready AI retrieval system. Agentic Retrieval-Augmented Generation (RAG) with a RESTful API.

An open source library for deep learning end-to-end dialog systems and chatbots.

农业知识图谱(AgriKG)：农业领域的信息检索，命名实体识别，关系抽取，智能问答，辅助决策

Transformers for Information Retrieval, Text Classification, NER, QA, Language Modelling, Language Generation, T5, Multi-Modal, and Conversational AI

State of the Art Natural Language Processing

AdalFlow: The library to build & auto-optimize LLM applications.

OP Vault ChatGPT: Give ChatGPT long-term memory using the OP Stack (OpenAI + Pinecone Vector Database). Upload your own custom knowledge base files (PDF, txt, epub, etc) using a simple React frontend.

Rust native ready-to-use NLP pipelines and transformer-based models (BERT, DistilBERT, GPT2,...)

FAQ-based Question Answering System

The Self-Coding System for Your App — Alan AI SDK for Web

Dealing with all unstructured data, such as reverse image search, audio search, molecular search, video analysis, question and answer systems, NLP, etc.

Self-contained Machine Learning and Natural Language Processing library in Go

Datasets, SOTA results of every fields of Chinese NLP

北京航空航天大学大数据高精尖中心自然语言处理研究团队开展了智能问答的研究与应用总结。包括基于知识图谱的问答（KBQA），基于文本的问答系统（TextQA），基于表格的问答系统（TableQA）、基于视觉的问答系统（VisualQA）和机器阅读理解（MRC）等，每类任务分别对学术界和工业界进行了相关总结。

A collection of research on knowledge graphs

Efficient Retrieval Augmentation and Generation Framework

:house_with_garden: Fast & easy transfer learning for NLP. Harvesting language models for the industry. Focus on Question Answering.

knowledge graph知识图谱,从零开始构建知识图谱

Bi-directional Attention Flow (BiDAF) network is a multi-stage hierarchical process that represents context at different levels of granularity and uses a bi-directional attention flow mechanism to achieve a query-aware context representation without early summarization.

Awesome & Marvelous Amas

NLP DNN Toolkit - Building Your NLP DNN Models Like Playing Lego

从无到有构建一个电影知识图谱，并基于该KG，开发一个简易的KBQA程序。

【C++ 面试 + C++ 学习指南】 一份涵盖大部分 C++ 程序员所需要掌握的核心知识。

List of software that allows searching the web with the assistance of AI: https://hf.co/spaces/felladrin/awesome-ai-web-search

End-to-end neural table-text understanding models.

📙 PHP 面试知识点汇总