mutaician/Tea-Knowledge-Assistant

Retrieval-augmented question-answering system that unifies Wikipedia’s comprehensive tea content with Kenya-specific guidelines from the Tea Board of Kenya # Tea-Knowledge-Assistant Retrieval-augmented question-answering system that unifies Wikipedia’s comprehensive tea content with Kenya-specific guidelines from the Tea Board of Kenya ## Problem Statement Accessing reliable, Kenya-relevant knowledge on tea cultivation, processing, and regulation is difficult because key information is fragmented across sources. Farmers and students often rely on Wikipedia for general knowledge, while critical guidance—such as greenleaf quality requirements and cultivation manuals—is published by the Tea Board of Kenya in long PDFs or notices. Manually searching through these documents is slow and makes it harder to find answers to practical questions like pest control methods, harvesting standards, or processing differences. ## Suggested Solution The Tea Knowledge Assistant is a retrieval-augmented question-answering system that unifies Wikipedia’s comprehensive tea content with Kenya-specific guidelines from the Tea Board of Kenya. By embedding Wikipedia articles (e.g., Tea, Tea processing, Tea production in Kenya) and summarizing key Tea Board documents (cultivation manuals, quality requirements, regulations), the assistant provides quick, cited answers to user queries. This setup ensures global background knowledge while highlighting Kenya’s local standards and practices. ## Impact For farmers: easy access to cultivation and quality requirement details without sifting through long PDFs. For students: structured answers combining global tea knowledge with local Kenyan context. For researchers/policy makers: a consolidated, conversational entry point into scattered but critical resources. ## Why RAG fits Because the knowledge is scattered across Wikipedia pages and government publications, a retrieval-based system ensures answers are grounded in the most relevant text chunks, reducing noise and making critical guidance more discoverable. ## Technical Architecture ### Core Components - **Document Ingestion**: PDF processing …