Llmware
Provides a unified framework for building enterprise Retrieval-Augmented Generation (RAG) pipelines with small, specialized models.
About
Llmware offers a comprehensive and unified framework designed for rapidly building enterprise-grade LLM applications, including RAG and Agent systems. It uniquely combines integrated components for the full lifecycle of connecting knowledge sources to generative AI models with a vast catalog of over 50 small, specialized models. These models are fine-tuned for critical enterprise tasks such as fact-based question-answering, classification, summarization, and extraction, enabling private, secure, and cost-effective deployment within enterprise knowledge environments. The framework is optimized for local deployment and can often run without a GPU server, making it highly accessible for developers.
Key Features
- "Prompt with Sources" functionality for combining knowledge retrieval with LLM inference and fact-checking
- Robust Library for ingesting, organizing, and indexing diverse knowledge sources (parse, text chunk, embed)
- Advanced Query capabilities with text, semantic, hybrid, metadata, and custom filters
- Extensive Model Catalog with 150+ models, including 50+ RAG-optimized specialized models
- Unified framework for building LLM-based applications (RAG, Agents)
- 13,773 GitHub stars
Use Cases
- Automating enterprise processes requiring fact-based question-answering, classification, or summarization
- Building secure and privately deployable enterprise RAG pipelines
- Developing specialized LLM-based agents for complex tasks
