Ingest a bounded document set into Verba, configure retrieval and model providers, then review grounded chatbot answers before handing context to an agent workflow.
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Added September 2, 2026
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---
name: "Run RAG chatbot workflows with Verba"
slug: "run-rag-chatbot-workflows-with-verba"
description: "Ingest a bounded document set into Verba, configure retrieval and model providers, then review grounded chatbot answers before handing context to an agent workflow."
github_stars: 7716
verification: "security_reviewed"
source: "https://github.com/weaviate/Verba"
author: "Weaviate"
publisher_type: "open-source organization"
category: "Data Extraction & Transformation"
framework: "Multi-Framework"
tool_ecosystem:
github_repo: "weaviate/Verba"
github_stars: 7716
---
# Run RAG chatbot workflows with Verba
Ingest a bounded document set into Verba, configure retrieval and model providers, then review grounded chatbot answers before handing context to an agent workflow.
## Prerequisites
Verba, Python 3.10 through 3.12 or Docker, Weaviate embedded/cloud/Docker deployment, configured model and embedding provider keys as needed.
## Installation
Use the upstream install or setup path that matches your environment:
- pip install goldenverba
Requirements and caveats from upstream:
- [Quickstart: Deploy with Docker](#how-to-install-verba-with-docker)
- | Docker Support | ✅ | Verba is deployable via Docker |
Basic usage or getting-started notes:
- [](https://pypi.org/project/goldenverba/)...
- [✨ Getting Started with Verba](#getting-started-with-verba)
- Source: https://github.com/weaviate/Verba
- Extracted from upstream docs: https://raw.githubusercontent.com/weaviate/Verba/HEAD/README.md
## Documentation
- https://github.com/weaviate/Verba
## Source
- [Agent Skill Exchange](https://agentskillexchange.com/skills/run-rag-chatbot-workflows-with-verba/)