- Hugging Face Text Embeddings Inference (TEI) cheat sheet: images, launch flags, batching limits, API calls and metricsAI & GenAI · 9 Nov 2026
- Cosine, dot product or Euclidean: choosing a vector distance metric without the math headacheAI & GenAI · 7 Nov 2026
- Embedding ingestion job fails: input too long, batch token limits, 429s and empty vectors when indexing thousands of documentsAI & GenAI · 2 Nov 2026
- Embeddings and vector search basics: what they are, how similarity works, and a small working exampleAI & GenAI · 29 Oct 2026
- RAG basics: how retrieval augmented generation works, with a minimal pipeline you can read in one sittingAI & GenAI · 29 Oct 2026
- Re-embedding a vector index when the embedding model retires - a zero-downtime switch with dual indexes and a recall checkAI & GenAI · 27 Oct 2026
- Advisory: choosing an embedding model - quality on your data, languages, dimensions, cost and lock-inAI & GenAI · 25 Oct 2026
- Optimization: lowering RAG ingestion cost - incremental indexing, deduplication and choosing when to OCRAI & GenAI · 25 Oct 2026
- Optimization: shrinking vector indexes - fewer dimensions, int8 and binary quantization, and rescoringAI & GenAI · 25 Oct 2026
- Sev1: vector search fails or returns nonsense after an embedding model changeAI & GenAI · 25 Oct 2026
- Migrating to a new embedding model without breaking searchAI & GenAI · 22 Oct 2026
- RAG answers are incomplete or off-topic: tune chunk size and overlapAI & GenAI · 22 Oct 2026
- Semantic caching for LLM apps: cut cost and latency without serving wrong answersAI & GenAI · 22 Oct 2026