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With AI, Everyone is a Dev. EveryDev.ai ©
    1. Home
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    3. llmware
    llmware icon

    llmware

    Retrieval-Augmented Generation
    Featured

    Open-source Python framework for building local, private RAG pipelines and agent workflows with small, specialized models.

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    At a Glance

    Pricing
    Open Source

    Self-hosted llmware framework distributed under the Apache-2.0 license.

    Engagement

    Available On

    Windows
    macOS
    Linux
    API
    SDK

    Resources

    WebsiteDocsGitHubllms.txt

    Topics

    Retrieval-Augmented GenerationAI Development LibrariesLocal Inference

    Alternatives

    Model2VecXtrieverModel2Vec-rs
    Developer
    AI BloksGreenwich, CTEst. 2022$40000 raised

    Listed Nov 2026

    About llmware

    llmware is an open-source Python framework from AI Bloks for building knowledge-based LLM applications that run locally, on edge devices or self-hosted. It combines a model catalog of 300+ models with an integrated RAG pipeline covering parsing, embedding, retrieval and prompting. It is distributed under the Apache-2.0 license and installs with pip.

    What It Is

    llmware is a developer toolkit for retrieval augmented generation and multi-step agent workflows. Its README says it is optimized for AI PCs, laptops, edge and self-hosted deployment on Windows, Mac and Linux. It supports GGUF, OpenVINO, ONNXRuntime, ONNXRuntime-QNN, WindowsLocalFoundry and PyTorch behind a common interface. Cloud models from OpenAI, Anthropic and Google are also supported.

    How the RAG Pipeline Works

    A Library is the knowledge-base container. Calling add_files routes mixed file types (pdf, pptx, docx, xlsx, txt, csv, md, json, wav, png, jpg, html) to parsers, which chunk the text and index it. Embeddings can be installed on a library with a chosen embedding model and vector database, and several can coexist. The Query class supports text, semantic, hybrid, metadata and custom-filter retrieval. Prompt with Sources packages retrieved passages or documents into model-ready context and offers post-inference evidence checks and prompt history.

    Models and Agents

    The catalog includes the llmware-finetuned SLIM, BLING, DRAGON and Industry-BERT series. SLIM models are fine-tuned for function calling, and the LLMfx agent class loads them as tools such as sentiment, extract, topics and boolean. It aggregates the results into a report and activity summary. Many models ship in quantized GGUF versions for CPU use.

    Data Stores and Setup

    Text collection databases are SQLite, MongoDB and Postgres. Supported vector databases are Milvus, PGVector, Neo4j, Redis, LanceDB, ChromaDB, Qdrant, FAISS, Pinecone and Mongo Atlas. A no-install option uses SQLite with ChromaDB. Docker Compose scripts are provided for the server-based options. OCR parsing needs optional Tesseract and Poppler packages.

    llmware - 1

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    Pricing

    OPEN SOURCE

    Open Source

    Self-hosted llmware framework distributed under the Apache-2.0 license.

    • Apache License 2.0
    • Model catalog with 300+ models
    • RAG pipeline
    • Runs locally on laptop, edge and self-hosted deployments

    Capabilities

    Key Features

    • Model catalog with 300+ models
    • RAG pipeline with document parsing, chunking and embedding
    • Text, semantic and hybrid retrieval with filters
    • Prompt with Sources and evidence checking
    • SLIM function-calling models and LLMfx agents
    • GGUF, OpenVINO, ONNXRuntime and PyTorch support
    • Support for 3 text databases and 10 vector databases
    • OCR for embedded document images
    • Whisper CPP voice transcription
    • Natural language to SQL with Slim-SQL

    Integrations

    OpenAI
    Anthropic
    Google
    Hugging Face
    Milvus
    PGVector
    Postgres
    MongoDB
    SQLite
    Neo4j
    Redis
    Qdrant
    FAISS
    LanceDB
    ChromaDB
    Pinecone
    OpenVINO
    ONNXRuntime
    LM Studio
    Ollama
    Streamlit
    Docker
    API Available
    View Docs

    Ratings & Reviews

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    Developer

    AI Bloks

    AI Bloks is the company behind the open-source llmware project. It was founded by Namee Oberst and Darren Oberst in October 2022. The company offers a Software as a Service Retrieval Augmented Generation service.

    Founded 2022
    Greenwich, CT
    $40000 raised
    11 employees

    Used by

    Accenture (AI-worker case/insight on…
    Read more about AI Bloks
    WebsiteGitHubLinkedInX / Twitter
    1 tool in directory

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