11 Lessons to Get Started Building AI Agents
An LLM-powered knowledge curation system that researches a topic and generates a full-length report with citations.
Open Source Deep Research Alternative to Reason and Search on Private Data. Written in Python.
Code search MCP for Claude Code. Make entire codebase the context for any coding agent.
Everything you need to know to build your own RAG application
Nexent is a zero-code platform for auto-generating agents — no orchestration, no complex drag-and-drop required. Nexent also offers powerful capabilities for agent running control, data processing and MCP tools.
拼好RAG：手搓并融合了GraphRAG、LightRAG、Neo4j-llm-graph-builder进行知识图谱构建以及搜索；整合DeepSearch技术实现私域RAG的推理；自制针对GraphRAG的评估框架| Integrate GraphRAG, LightRAG, and Neo4j-llm-graph-builder for knowledge graph construction and search. Combine DeepSearch for private RAG reasoning. Create a custom evaluation framework for GraphRAG.
Agentic-RAG explores advanced Retrieval-Augmented Generation systems enhanced with AI LLM agents.
The Next Generation AI Product Creation Platform. Complete context engineering and LLM orchestration with APIs or private deployments. Run anywhere - local, cloud, or bare metal.
YT Navigator: AI-powered YouTube content explorer that lets you search and chat with channel videos using AI agents. Extract insights from hours of content in seconds with semantic search and precise timestamps.
[Up-to-date] Awesome Agentic Deep Research Resources
Chat2Graph: Graph Native Agentic System.
RAGLight is a modular framework for Retrieval-Augmented Generation (RAG). It makes it easy to plug in different LLMs, embeddings, and vector stores, and now includes seamless MCP integration to connect external tools and data sources.
[EMNLP 2025] Awesome RAG Reasoning Resources
Connect to your customer data using any LLM and gain actionable insights. IdentityRAG creates a single comprehensive customer 360 view (golden record) by unifying, consolidating, disambiguating and deduplicating data across multiple sources through identity resolution.
Workflows are an event-driven, async-first, step-based way to control the execution flow of AI applications like agents.
📁 This repository hosts a growing collection of AI blueprint projects that run end-to-end using Jupyter notebooks, MLflow deployments, and Streamlit web apps.🛠️ All projects are built using HP AI Studio with ❤️ If you find this useful, please don’t forget to star the repository ⭐ and support our work 🚀
A clean and extensible agentic RAG system with modular implementation.
A python library for creating AI assistants with Vectara, using Agentic RAG
🔥🔥🔥 Simple way to create composable AI agents
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