Boost Your Code's Efficiency: Introducing Semantic Cache with Qdrant

• semantic_cache

  1 4 5.4 Python

  Semantic caching for Python Functions

In fact, the idea of semantic_cache was born in an effort to avoid reimplementing one or another data processing function that might be quite expensive to compute. Inefficiency is going to happen all over again, when call to that function with same or very similar arguments is reproduced. That's the time semantic_cache comes into play!

• qdrant

  141 17,943 9.9 Rust

  Qdrant - High-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/

  

I took Qdrant for this project. The reason was that Qdrant stands for high-performance vector search, the best choice against use cases like finding similar function calls based on semantic similarity. Qdrant is not only powerful but also scalable to support a variety of advanced search features that are greatly useful to nuanced caching mechanisms like ours.

• InfluxDB

  www.influxdata.com featured

  Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

  

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