Run Rag Chatbot Workflows With Verba

---
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:
- [![PyPi downloads](https://static.pepy.tech/personalized-badge/goldenverba?period=total&units=international_system&left_color=grey&right_color=orange&left_text=pip%20downloads)](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/)