Harry Potter and the Elastic Python Clients
summary
Builds a Harry Potter book search app that actually ingests cleaned text, creates index mappings, and enriches every sentence with sentiment labels and 768‑dim embeddings, demonstrating Elastic Search Python client and Eland pipelines that load Hugging Face embeddings into the cluster. Shows concrete queries: filter by sentiment to list most negative/positive quotes, run vector nearest‑neighbor and hybrid semantic+keyword searches, and uses observability to monitor ingestion and inference; demo glitches appear during live code but the pipelines and hybrid search results complete and return interpretable hits.
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chapters (5)
- 0:00Elastic Python Clients intro
- 4:03Elastic Python clients overview
- 8:12Search Harry Potter data
- 13:53Semantic search with embeddings
- 22:51Summary
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