philpher0x/vectrain

Vectrain is a high-performance, modular, plug-and-play RAG pipeline that ingests data, generates vector embeddings, and stores them in vector databases for semantic search, recommendations, and analytics.

32
/ 100
Emerging

This tool helps developers transform raw text data, like customer reviews or product descriptions, into numerical 'vector embeddings' that power smart search, recommendations, and analytics. It takes data streams from sources like Kafka or REST endpoints, processes them through an embedding model, and then stores these embeddings in vector databases. Developers or MLOps engineers would use this to build and manage the data backend for AI applications.

No commits in the last 6 months.

Use this if you are a developer building an application that needs to perform semantic search, power recommendations, or analyze large volumes of unstructured text data using vector embeddings.

Not ideal if you need a fully managed, no-code solution for generating embeddings or if your application requires a different set of data sources, embedding models, or vector databases than what is currently supported.

semantic-search recommendation-systems MLOps data-pipelines AI-application-development
Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 5 / 25
Maturity 15 / 25
Community 10 / 25

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Stars

14

Forks

2

Language

Go

License

MIT

Last pushed

Sep 26, 2025

Commits (30d)

0

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