Verba: Building an Open Source, Modular RAG Application
Blog post from Weaviate
Retrieval Augmented Generation (RAG) is an advanced search technique that uses a Large Language Model (LLM) to help identify and summarize answers. RAG applications search for relevant sources and create personalized answers using provided data sources instead of general knowledge LLMs are trained on. Verba, the Golden RAGtriever, is an open-source tool designed to make it easy for anyone to use RAG without technical expertise. It allows users to get personalized answers from their own data and supports customization for different use cases. The architecture of Verba consists of five key steps: ReaderManager, ChunkerManager, EmbeddingManager, RetrieveManager, and GenerationManager.
| Trend | Post Mentions | Total Month Mentions | Posts | Companies | MoM |
|---|---|---|---|---|---|
| RAG | 26 | 1,224 | 185 | 59 | +5% |
| LLM | 14 | 2,684 | 354 | 134 | +1% |
| Vector Search | 8 | 2,015 | 259 | 83 | -8% |
| AI Agents | 1 | 215 | 43 | 24 | +35% |
| Data Pipeline | 1 | 512 | 131 | 59 | +43% |
| Local AI | 1 | 22 | 5 | 4 | +175% |
| Voice AI | 1 | 206 | 54 | 20 | -29% |
Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.