Production-grade RAG chatbot for Universitas Atma Jaya Yogyakarta academic handbook with Streamlit, FAISS vector search, and Google Gemini 2.5 Flash.
A modular Agentic RAG built with LangGraph — learn Retrieval-Augmented Generation Agents in minutes.
The open-source agentic framework to build, orchestrate, and operate production AI agents.
Every taka Bangladesh spends, searchable in seconds in Bangla, with the receipts and red flags attached.
Open-source audio/video notebook: ask across hundreds of hours of recordings, and every answer links to the exact second it was said.
Local-first voice memory assistant — capture speech, transcribe live, and ask a private RAG chatbot grounded in what you've actually said. No cloud required.
A modular local AI agent built with Python and Ollama, featuring tool calling, memory, web search, document processing, embeddings, and RAG.
面向"面试官 × 简历主人公"场景的个人简历 RAG 问答 Agent:把简历、证书、荣誉、项目介绍放进知识库,面试官可对简历任意提问(自我介绍、项目深挖、技术八股、HR 素质、简历细节),系统以第一人称自然作答。核心设计是"宽松推理 + 诚实标注"——硬事实(数字/日期/证书名)必须来自检索,证据不足时强制标注"根据现有知识库推测"而非编造。支持多轮追问记忆、检索兜底链、置信度分级回答、访问码闸门与 IP 限流防刷。