The jamwithai/production-agentic-rag-course project is a broad educational resource for building production-grade Retrieval-Augmented Generation (RAG) systems, focusing on the arXiv Paper Curator as a case study.
Source: Official README and linked documentation View on GitHub →This project is being discussed because its hands-on approach to building RAG systems, addressing the gap in practical, industry-aligned RAG education. Its unique technical choices include a focus on solid search foundations, integration of advanced AI techniques, and a modular architecture that allows for scalability and adaptability.
Source: Official README and linked documentationThe project provides a structured learning path for building RAG systems, starting from infrastructure setup to deploying a fully functional research assistant system.
Source: Official README and linked documentationIncorporates LangGraph for intelligent decision-making, document grading, query rewriting, and out-of-domain detection, enhancing the RAG system's capabilities.
Source: Official README and linked documentationEnables mobile access to the RAG system through a Telegram bot, providing a conversational interface for users.
Source: Official README and linked documentationThe architecture follows a modular design, with distinct components for data ingestion, search, retrieval, and presentation. It use Docker Compose for containerization, FastAPI for RESTful APIs, PostgreSQL for data storage, OpenSearch for search capabilities, and Airflow for workflow orchestration.
Source: Official repository tree and dependency filesfastapidocker-composeopensearch-pypsycopg2-binaryalembicopensearch-pyrequestshttpxdoclingpython-dateutilsentence-transformersgradiolangfuseredispython-telegram-botlanggraphlangchainlangchain-corelangchain-communitylangchain-ollamaThe project is suitable for developers and technical learners interested in AI engineering, particularly those looking to master RAG systems. It is useful for building research assistants, academic paper curators, and other applications requiring advanced information retrieval and AI integration.
Source: Official README and linked documentationweek7.0 (2025-11-26): Week 7: Agentic RAG with LangGraph and Telegram Bot
Source: Official releasesThe jamwithai/production-agentic-rag-course project is a tool for those seeking to gain hands-on experience in building advanced RAG systems. It is particularly suited for developers and learners with an interest in AI and information retrieval, offering a structured and practical approach to mastering RAG technologies.
Source: Official repository