Jenkins AI Assistant
RAG-Powered Documentation Search System
Saksham Beri
Student
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13-01-2026
Submitted
The Problem
Jenkins documentation is extensive, fragmented, and difficult to navigate during real engineering workflows. Developers often spend significant time searching across documentation pages, blogs, and outdated examples to find reliable answers.
The Solution
This project implements a full-stack AI assistant that allows users to ask natural-language questions about Jenkins and receive context-aware answers grounded in official Jenkins documentation.
About This Project
This is a Jenkins AI Assistant to answer Jenkins questions using only official Jenkins documentation, no hallucinations, no generic LLM responses. Highlights :- - End-to-end RAG pipeline on raw Jenkins docs - Custom ingestion: scrape → clean → chunk → embed → FAISS - FastAPI backend with auth, sessions, and PostgreSQL - Jenkinsfile upload + context-aware querying - Dockerized, reproducible setup This project helped us understand production trade-offs in RAG systems, not just prompts.