Verba
Weaviate's open-source RAG app, the Golden RAGtriever (archived).
Retired
Verba appears to be discontinued or shut down — repo archived and discontinued This page is kept as an archive record and is excluded from search engines.
About
Verba, dubbed the Golden RAGtriever, was Weaviate's community-driven open-source application for retrieval-augmented generation. It offered an end-to-end interface for exploring datasets and extracting insights, with a modular pipeline where users could swap chunking strategies, retrieval techniques, and LLM providers, running locally via Ollama and Hugging Face or through Anthropic, Cohere, OpenAI, and others.
The repository has since been archived and discontinued, with Weaviate stating it will receive no further updates or security patches. It remains available for reference and forking. Included here as a historical entry; anyone starting a RAG project should choose an actively maintained alternative.
What it can do
- End-to-end RAG interface over your own datasets
- Modular pipeline: chunking, retrieval, and LLM choices
- Local or cloud deployment with Docker support
- Now archived; code available for reference and forking
Setup
Historically installed via pip install goldenverba or Docker; the repo is archived so no new deployments are advised.
Prerequisites
Was: Python environment, a Weaviate instance, and LLM provider API keys.
Use cases
Works with
Trust score — 6/10
Scored 6/10 (metrics tier, metrics-v1). Evidence: Verified via vendor site/docs/GitHub and reputable coverage, wave 95; Trending score 58/100 from researcher assessment.
Sources
Every fact above was checked against these sources. Where a claim comes from the provider and couldn't be independently verified, the text says so.