sede-open/Fleming

Fleming repo to run semantic search models on databricks on CPU.

46
/ 100
Emerging

This project helps data professionals efficiently manage and query semantic search models on Databricks. You can input raw text data to create a search index, then train, register, and serve a semantic search model. This allows for powerful information retrieval and data discovery within your Databricks environment, especially useful for those working with large codebases or documentation.

Use this if you need to build, deploy, and query semantic search capabilities on Databricks using CPU resources to optimize costs, particularly for tasks like finding relevant code snippets or project documentation.

Not ideal if you don't use Databricks or require GPU acceleration for extremely large-scale, real-time semantic search operations.

data-discovery semantic-search MLOps Databricks information-retrieval
No Package No Dependents
Maintenance 10 / 25
Adoption 5 / 25
Maturity 16 / 25
Community 15 / 25

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Stars

14

Forks

5

Language

TypeScript

License

Apache-2.0

Last pushed

Mar 01, 2026

Commits (30d)

0

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