0Pricing
LLM Apps in Production (RAG + Vector DB + Caching) · Lesson

Cleaning and Deduplicating Source Data

Learn to clean noisy documents and remove duplicate content before ingestion so your RAG index stays small, accurate, and free of conflicting answers.

Garbage In, Garbage Out

RAG quality is capped by the quality of what you ingest. Boilerplate, HTML tags, duplicate pages, and broken encoding all pollute retrieval.

Cleaning and deduplication happen before chunking and embedding.

Common Noise Sources

Typical junk found in raw documents:

  • Navigation menus, headers, footers
  • Cookie banners and ads
  • Repeated legal disclaimers
  • Mojibake from bad encoding
  • Excess whitespace and control chars

All lessons in this course

  1. Loading Diverse Document Formats
  2. Context-Aware Chunking Strategies
  3. Metadata Management and Filtering
  4. Cleaning and Deduplicating Source Data
← Back to LLM Apps in Production (RAG + Vector DB + Caching)