building-rag-systems

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references/DATA-LOADING.md

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Comprehensive RAG (Retrieval-Augmented Generation) system building guide covering data loading pipelines (11 source types including Word, PDF, CSV, audio, video, multimodal), data preparation (metadata enrichment, text quality enhancement, 5 chunking strategies from character to agentic), and full RAG architecture overview with Python. Use when building RAG applications, designing data ingestion pipelines, or implementing text chunking strategies. For Python language best practices, use developing-python instead. For LLMOps operational framework, use practicing-llmops. For JavaScript/LangChain.js RAG in web apps with Vercel AI SDK, see integrating-ai-web-apps.