Open-Deep-Research-workflow-on-Dify
Deep Research workflow on Dify: cascaded multi-source search → outline → cited long-form report. Credited in Awesome-Dify-Workflow.
Retrieval-augmented generation (RAG) makes a language model answer from your own documents. The text is split into chunks, turned into vectors and stored in an index, and the most relevant chunks are added to the prompt when a question comes in. The projects here cover the whole pipeline or one part of it: document parsing, vector search, or a complete question-answering app.
Answer quality in RAG depends mostly on retrieval, not on the model. Compare how each project handles difficult documents such as PDFs, tables and scans, whether it supports hybrid search that combines keywords with vectors and re-ranking, and whether it shows which sources an answer came from.
Deep Research workflow on Dify: cascaded multi-source search → outline → cited long-form report. Credited in Awesome-Dify-Workflow.
VeritasGraph — open-source Knowledge Graph & GraphRAG framework on GitHub. Build multi-hop reasoning, ontology-aware retrieval, and verifiable attribution over your own data. Nodes, edges, RDF, linked-data — runs locally or in the cloud.
A TypeScript sample app for the Retrieval Augmented Generation pattern running on Azure, using Azure AI Search for retrieval and Azure OpenAI and LangChain large language models (LLMs) to power ChatGPT-style and Q&A experiences.
"Hyper-RAG: Combating LLM Hallucinations using Hypergraph-Driven Retrieval-Augmented Generation" by Yifan Feng, Hao Hu, Shihui Ying, Xingliang Hou, Shiquan Liu, Mingyuan Yang, Junchang Li, Shaoyi Du, Nanning Zheng, Han Hu, and Yue Gao.
Use LLMs to robustly extract web data
Alice is a voice-first desktop AI assistant application built with Vue.js, Vite, and Electron. Advanced memory system, function calling, MCP support, optional fully local use, and more.
台灣法律 MCP 伺服器 + CLI(免費、免註冊、免 API key):2,250 萬筆裁判書、行政函釋、憲法法庭裁判,附引用查核。Free Taiwan legal MCP server for Claude/ChatGPT/Codex — bring your own LLM, retrieval-only.
Foam-Agent: An end-to-end, composable multi-agent framework for automating CFD simulations in OpenFOAM. NeurIPS 2025 Machine Learning and the Physical Sciences Workshop.
A practical AI agents handbook covering agent systems, agentic workflows, LangGraph, MCP/A2A, context engineering, agent memory, evaluation, observability, and multi-agent architecture. Current trend focus: Gemini Interactions API and managed agents, emerging agent runtimes, and production AI workflow patterns.
smart-llm-loader is a lightweight yet powerful Python package that transforms any document into LLM-ready chunks. Spend less time on preprocessing headaches and more time building what matters. From RAG systems to chatbots to document Q&A, SmartLLMLoader handles the heavy lifting so you can focus on creating exceptional AI applications.
An intentionally vulnerable OWASP LLM Top 10 training platform for AI Security, Prompt Injection, RAG Security, Agent Security, and GenAI penetration testing.
LLMInternSkill: LLM internship resume and job-search Codex Skill for resume polish, JD tailoring, evidence guard, interview grilling, and Project Scout. 大模型实习简历与求职工具箱。
Illuminate your data. Agent framework turning natural language into SQL, charts, dashboards and reports.
The RAG Experiment Accelerator is a versatile tool designed to expedite and facilitate the process of conducting experiments and evaluations using Azure Cognitive Search and RAG pattern.
Open-source AI real estate search with RAG, vector search, multi-provider LLMs, FastAPI, Next.js, ChromaDB, and a live demo.
BookWith – A New Reading Experience with AI. A next-generation conversational reading platform that goes beyond traditional e-book readers
ChatClaw: Get OpenClaw-like knowledge base personal AI agent in 5 mins. Sandbox-secured, ultra-small 30MB installer for macOS & Windows (install in 1 min). Connects to WhatsApp, Telegram, Slack, Discord, Gmail, DingTalk, WeChat Work, QQ, Feishu. Built-in Skill Market, Knowledge Base, Memory, MCP, Scheduled Tasks. Developed in Go ,run
A free, self-paced 24-week AI engineering course: Python, machine learning, LLMs, RAG, fine-tuning, agents and MCP, Azure and Vertex and Bedrock, and Databricks. 43 runnable notebooks, one continuous case study. MIT licensed, no signup. By Zorost Intelligence AI Lab.
A desktop-first literature manager for PDF reading, translation, paper overviews, and AI agent workflows.
Open-sourced course notes for Artificial Intelligence and Data Science related topics, prepared in LaTeX