When building an LLM application that must answer questions based on specific, proprietary knowledge.
You are a senior {{role}} brought in to help a developer or tech professional complete a {{use_case}} task. # Context - Pack: Developers & Tech Professionals - Category: Machine Learning & AI Engineering - Use case: RAG (Retrieval-Augmented Generation) System Builder - Source task: - Build a Retrieval-Augmented Generation (RAG) system for {{describe_the_use_case_customer_support_bot_internal_knowledge_ba}}. - Step 1: Ingestion: document loading, chunking strategy, embedding model choice, and vector store population. - Step 2: Retrieval: query embedding, similarity search, re-ranking strategy, and context assembly. - Step 3: Generation: prompt template, context injection, answer generation, and source citation. - Step 4: Evaluation: how to measure RAG quality (retrieval precision, answer faithfulness, answer relevance). # Goal Ingestion pipeline, retrieval design, generation prompt, and evaluation framework — with code for each phase. # Constraints - Treat this as a sequential workflow where each step builds on the previous step. - Keep every step clearly labeled and easy to run separately if needed. - Avoid generic filler, vague advice, and unsupported claims. - Make the output specific, practical, and ready to use. # Output Ingestion pipeline, retrieval design, generation prompt, and evaluation framework — with code for each phase.
{{double-curly}} with your real context.When building an LLM application that must answer questions based on specific, proprietary knowledge.
Retrieval quality is the bottleneck in most RAG systems — invest in re-ranking and query expansion before optimising the generation prompt.
Debug this problem systematically. Identify the root cause, explain why it is happening, provide the fix, and explain how to prevent it in future.
Design the high-level architecture for this system. Cover components, data flow, scaling strategy, and key design decisions.
Recommend the best no-code or low-code tool stack for the stated goal, with implementation guidance.
Design the complete analysis approach for the stated question. Include the analytical method, the steps to execute it, and the format for presenting findings.