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Index and retrieve documents for vector search using Sentence Transformers and DuckDB
The article provides a comprehensive tutorial on implementing vector search and retrieval systems using Hugging Face Hub, demonstrating multiple approaches from basic searching to creating a deployabl
e web application. It covers the entire pipeline from data loading and embedding generation to deployment as a microservice, using tools like DuckDB, vicinity, and Gradio.

Reasons to Read -- Learn:

  • how to implement a complete vector search system from scratch, with practical code examples using popular tools like DuckDB, vicinity, and Gradio
  • how to deploy AI applications as web services on Hugging Face Spaces, including both the front-end interface and API accessibility
  • different vector search approaches and their trade-offs, including direct Hub querying, indexed searches with DuckDB, and using the vicinity library for better performance
  • publisher: Hugging Face – The AI community building the future.
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