mar1boroman/RedisVectorXperience
Explore cutting-edge Redis capabilities for Vector Similarity Search, Hybrid Search (Vector Similarity + Meta Search), Semantic Caching, and an advanced RAG model integrated with a Language Model (LLM) Chatbot. Unlock the full potential of Redis as a vector database with this comprehensive showcase of powerful features.
This project helps developers build applications that can quickly find similar items, recommend products, or improve AI chatbot responses. It takes various forms of text data (like blog posts or product descriptions), processes them, and makes them searchable and usable for advanced AI functions. The end-users are developers creating smart search engines, recommendation systems, or conversational AI experiences.
No commits in the last 6 months.
Use this if you are a developer looking to integrate high-performance vector search, recommendation features, or enhanced RAG models into your applications using Redis as a vector database.
Not ideal if you are an end-user without programming experience, as this is a developer-focused demonstration for building advanced search and AI capabilities.
Stars
16
Forks
3
Language
Python
License
MIT
Category
Last pushed
Jan 21, 2024
Commits (30d)
0
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