llmware

llmware is an open source framework for building enterprise knowledge-based RAG pipelines and local LLM applications.

Llmware is a unified framework for building local, private, and secure LLM-based applications optimized for AI PCs, edge, and self-hosted deployments. It includes a model catalog with over 300 prepackaged models, including fine-tuned SLIM, Bling, Dragon, and Industry-Bert models, as well as support for major cloud models like OpenAI, Anthropic, and Google. The platform features an integrated RAG pipeline for document parsing, text chunking, embedding, and creating scalable knowledge bases. It supports various inferencing technologies such as GGUF, OpenVINO, ONNXRuntime, and PyTorch across Windows, Mac, and Linux platforms. Designed for enterprise process automation, it enables developers to build sustainable and cost-effective AI solutions using a small compute footprint.

llmware at a glance

Best for: Software engineer
Runs on: macOS, Windows, Linux, API, self-hosted, open source
Pricing: Free
Released: September 2023
Category: AI coding tool
Website: github.com/llmware-ai/llmware

Key features

Model Catalog with 300+ models
Library for ingesting, organizing, and indexing knowledge
Query libraries with text, semantic, hybrid, and metadata filters
Prompt with Sources for combining retrieval with inference
RAG-optimized 1-7B parameter models
Simple-to-scale database options
Agents with function calls and SLIM models

Use it for

Build enterprise RAG pipelines
Analyze contracts and complex documents
Process invoices and extract key-value data
Run voice transcription with WhisperCPP
Convert natural language queries to CSV

Alternatives to llmware

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LangChain4j — Integrates LLMs and vector stores directly into Java applications.
Mesh LLM — Run large local models across multiple machines through one OpenAI-compatible endpoint.
MLC LLM — Enables native optimization and deployment of AI models across platforms.
OpenLLM — It simplifies infrastructure management and optimizes inference speed and cost.
LightLLM — It delivers high-speed inference and serving performance for large language models.
WebLLM — Runs high-performance language models directly inside web browsers.
LMQL — It enables modularized, constraint-based prompting with portable code.
Langroid — Simplifies multi-agent orchestration and app development with intuitive abstractions.
LLM CLI — It enables command-line interaction with remote APIs and local machine models.

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