ForgeRAG
✨Production-Ready RAG with Structure-Aware Reasoning, supporting pixel-precise citations and knowledge graph multi-hop reasoning.
Production-Ready RAG with Structure-Aware Reasoning, supporting pixel-precise citations and knowledge graph multi-hop reasoning.
An enterprise-grade multi-agent AI assistant platform for teams, building a "second brain" through multi-model failover, MCP protocol, and multi-channel support.
Open-source digital human agent platform that creates real-time video-callable AI agents from a single photo, with RAG knowledge import, voice cloning, and modular plugin architecture.
Next-generation personal and enterprise AI assistant platform powered by LLM, RAG, and agent loops, featuring multi-channel gateways, visual BPMN workflow orchestration, and multi-tenant isolation.
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.
Open-source enterprise AI application platform providing Agentic RAG, custom Agents, Deep Research, code execution, and multi-client access as an all-in-one generative AI gateway.
Enterprise-grade RAG Agent platform built on Java 17 + Spring Boot 3 + React 18, featuring multi-channel retrieval, intent recognition, conversation memory, model fault tolerance, and MCP tool integration.
A Pokémon-themed intelligent chat assistant powered by LangGraph multi-agent orchestration and GraphRAG technologies. Integrates Neo4j knowledge graph, Milvus vector search, and multi-source hybrid retrieval for precise Q&A with complex relationship reasoning. Also serves as a transferable template for domain-specific knowledge systems.
A curated collection of extracted system prompts from popular chatbots like ChatGPT, Claude, and Gemini, helping researchers understand the behavior boundaries of AI models。
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