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ragbits

Building blocks for rapid development of GenAI applications

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typescriptragpromptsdocument-searchevaluationguardrailsagentsllmsPythonoptimizationvector-storesnodepythonpython/uv

ragbits is a Python library of building blocks for rapidly developing GenAI applications, from deepsense.ai. Its topics indicate coverage of RAG pipelines, document search, prompts, vector stores, agents, guardrails, evaluation, and optimization.

You reach for it when you want composable, ready-made components for LLM and RAG application development instead of assembling everything yourself.

Use it to

  • Build RAG pipelines with document search and vector stores
  • Manage and iterate on prompts
  • Add guardrails around LLM outputs
  • Evaluate and optimize GenAI components
  • Assemble agentic workflows

For Python developers building LLM and RAG applications

Role
rag
Language
Python
Licence
MIT
Forks
143
Open issues
42
Last push
2026-05-18
Latest release
v0.2.0 · 2024-10-23
Skills shipped
2
topicsragllmpythonagentsevaluationvector-stores