Verba 1.0 and Ollama: local RAG setup tutorial

Uploaded on May 16, 2024, this tutorial covers Verba 1.0 and its Ollama integration. It explains how a RAG application retrieves document chunks from a vector database and includes them in a model's prompt. The presenters describe Verba as an open source way to build a chatbot around your own data.

The local LLM setup uses an already running Ollama instance. The walkthrough specifies its URL and a model name in an environment file, starts Verba and opens the interface at localhost:8000. It then imports the Verba README with a selected reader, chunker and Ollama embedder. The presenter says the resulting answer was generated locally and that no data left the device; that claim applies to the demonstrated configuration.

The installation section covers pip, installation from source and Docker Compose. It calls for Python 3.10 or later and a virtual environment for the Python route, or an installed and running Docker instance for the container route. These steps describe the 2024 release rather than a verified current installation procedure.

Verba 1.0 also introduces browser-cached conversations, ingestion logs, visibility into the exact context sent to the model and appearance settings. Separate examples cover company documentation and a healthcare showcase using Google Gemini and Weaviate. The healthcare example contains three patient cases and demonstrates retrieval, without establishing clinical reliability.