Day 25: Advanced Prompting for RAG - System Prompts That Prevent Hallucination скачать в хорошем качестве

Day 25: Advanced Prompting for RAG - System Prompts That Prevent Hallucination

Today’s Build We’re building a sophisticated prompt engineering framework that transforms raw retrieval into reliable answers: Grounding-enforced system prompts that force LLMs to stay within retrieved context boundaries Irrelevance detection layer that tests whether the LLM can reject off-topic contexts Citation-tracking mechanism that maps every answer claim back to source chunks Prompt template library with domain-specific patterns (legal, medical, financial) Automated adversarial testing that intentionally injects misleading context This builds directly on L24’s modular LangChain pipeline by replacing generic prompts with production-grade grounding strategies. We’re taking the RetrievalQA chain and teaching it to say “I don’t know” when context is insufficient—the hardest problem in RAG systems. This enables L26’s multi-turn conversations by establishing the grounding discipline that prevents context drift across dialogue turns.