tigranbs/search-engine-example-text-embeddings
This project has been created to demonstrate how we can build modern Search Engines using a straightforward structure of Text Embeddings (Huggingface Transformers) and a Vector Database.
This project helps software developers and engineers understand how to build a modern, intelligent search engine. It takes raw text data, processes it into numerical representations (text embeddings), and stores it in a database to enable highly relevant search results. The end-user persona is a software developer or architect looking to implement advanced search capabilities, similar to Google's, for their own applications or websites.
No commits in the last 6 months.
Use this if you are a developer looking for a practical, hands-on example to learn how to integrate text embeddings and vector databases to create a semantic search engine.
Not ideal if you are looking for a ready-to-deploy, production-optimized search solution or a simple, one-command setup.
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Language
TypeScript
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Last pushed
Jan 13, 2024
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curl "https://pt-edge.onrender.com/api/v1/quality/vector-db/tigranbs/search-engine-example-text-embeddings"
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