Create AI assistants for education integrated in your Learning Management System
LAMB (Learning Assistants Manager and Builder) is an open-source web platform that enables educators to design, test, and publish AI-based learning assistants into your Learning Management System (LMS like Moodle) without writing any code. It functions as a visual "teaching chatbot builder" that seamlessly combines large language models (GPT-4, Mistral, local models) with your own educational materials.
Developed by Marc Alier and Juanan Pereira, professors and researchers at the Universitat Politècnica de Catalunya (UPC) and Universidad del País Vasco (UPV/EHU), LAMB addresses the critical need for educational AI tools that maintain student privacy while providing powerful, context-aware learning support.
Design assistants that stay grounded on your chosen subject area, ensuring responses are always educationally appropriate and contextually relevant.
Upload educational materials (PDF, Word, Markdown) and LAMB automatically processes them with:
- Flexible data model that preserves context and relationships
- Semantic embeddings optimized for educational search
- Custom metadata support for each document
- Adaptive processing for different content structures
- RAG (Retrieval Augmented Generation) integration
- The students will access the Learning Assitants as Learning Activities within the LMS Course
- No user information is shared with AI model providers
- Can run on open source and open weights models running on your compute
- Secure, self-hosted solution
Seamlessly integrate with Moodle and other Learning Management Systems through LTI (Learning Tools Interoperability) standard - publish your assistant as an external tool with just a few clicks.
- Works with OpenAI API compatible models
- Ollama inetgration
- One-click model switching
- Model-agnostic architecture
- Debug mode showing complete prompts
- Citation tracking with source references
Built-in support for Basque, Catalan, Spanish, and English, with easy extensibility for additional languages.
- Export/import assistants in JSON format
LAMB is designed for:
- 📖 Teachers and Trainers: Create virtual assistants focused on specific curricula without technical expertise
- 🏫 Educational Institutions: Integrate AI into existing LMS platforms while maintaining data sovereignty
- 💡 Innovation Teams: Experiment with different LLMs through a unified management interface
- 🔬 Researchers: Study AI in education with complete control over the learning environment
LAMB features a modular, extensible architecture:
- Backend: FastAPI-based server handling assistant management, LTI integration, and model orchestration
- Frontend: Modern Svelte 5 application providing intuitive UI for assistant creation and management
- Knowledge Base Server: Dedicated service for document ingestion and vector search
- Integration Layer: Bridges with Open WebUI for model management https://github.com/open-webui/open-webui
For the easiest setup experience, we recommend using Docker Compose to run all LAMB services:
📘 Docker Installation Guide - One-command deployment with all services configured
For development or custom deployments:
📘 Complete Installation Guide - Step-by-step manual setup for all components
LAMB requires four main services:
- Open WebUI Server (port 8080) - Model management interface
- LAMB Knowledge Base Server (port 9090) - Document processing and vector search
- LAMB Backend Server (port 9099) - Core API and business logic
- Frontend Application (port 5173) - Web interface
Visit our official website for:
- User guides and tutorials
- Feature documentation
- Educational resources
- Community support
Comprehensive documentation is available in the /Documentation directory:
- Backend Architecture
- Frontend Development Guide
- Knowledge Base Integration
- Multi-Organization Setup
- Database Schema
- Final Setup Guide
lamb/
├── backend/ # FastAPI backend server
│ ├── lamb/ # Core LAMB functionality
│ ├── creator_interface/# Assistant creation interface
│ └── utils/ # Utility functions
├── frontend/ # Svelte 5 frontend
│ └── svelte-app/ # Main web application
├── lamb-kb-server/ # Knowledge base server
├── Documentation/ # Project documentation
└── docker-compose.yaml # Container orchestration
We welcome contributions! LAMB is an open-source project that thrives on community involvement. Areas where you can help:
- 📝 Documentation improvements
- 🌍 Translations to new languages
- 🔌 New LMS integrations
- 🤖 Additional model support
- 🐛 Bug fixes and testing
Please see our Contributing Guide for details.
LAMB is licensed under the GNU General Public License v3.0 (GPL v3).
Copyright (c) 2024-2025 Marc Alier (UPC) @granludo & Juanan Pereira (UPV/EHU) @juananpe
See LICENSE for full details.
If you use LAMB in your research, please cite our work:
LAMB: An open-source software framework to create artificial intelligence assistants deployed and integrated into learning management systems
- Authors: Marc Alier, Juanan Pereira, Francisco José García-Peñalvo, Maria Jose Casañ, Jose Cabré
- Journal: Computer Standards & Interfaces
- Volume: 92
- Pages: 103940
- Publication Date: March 2025
- DOI: 10.1016/j.csi.2024.103940
- Direct Link: ScienceDirect Article
@article{ALIER2024103940,
title = {LAMB: An open-source software framework to create artificial intelligence assistants deployed and integrated into learning management systems},
journal = {Computer Standards \& Interfaces},
volume = {92},
pages = {103940},
year = {2025},
issn = {0920-5489},
doi = {https://doi.org/10.1016/j.csi.2024.103940},
url = {https://www.sciencedirect.com/science/article/pii/S0920548924001090},
author = {Marc Alier and Juanan Pereira and Francisco Jos{\'e} Garc{\'i}a-Pe{\~n}alvo and Maria Jose Casan and Jose Cabr{\'e}}
}We acknowledge the valuable contributions and research collaboration from the authors and researchers who have worked on LAMB:
- Juanan Pereira (Universidad del País Vasco, UPV/EHU) - Co-Lead & Principal Researcher
- Marc Alier (Universitat Politècnica de Catalunya, UPC) - Co-Lead & Principal Researcher
- Francisco José García-Peñalvo - Advisor and Senior Researcher
- Maria Jose Casañ (Universitat Politècnica de Catalunya, UPC) - Research Contributor & Developer
- Ariadna Maria LLorens (Universitat Politècnica de Catalunya, UPC) - Research Contributor
- Jose Cabré (Universitat Politècnica de Catalunya, UPC) - Research Contributor
- David Lopez Alvarez (Universitat Politècnica de Catalunya, UPC) - Research Contributor
- Universidad del País Vasco (UPV/EHU) - Research institution and development partner
- Universitat Politècnica de Catalunya (UPC) - Research institution and development partner
- Barcelona School of Informatics (https://fib.upc.edu)
- Institut de Ciències de l'Educació - ICE (https://ice.upc.edu)
- Department of Service and Information System Engineering. ESSI (http://essi.upc.edu)
- Universidad de Salamanca - Grial Research Group
- Open WebUI Project - (https://github.com/open-webui/) Advanced chatbot web interface integration, and a lot of design descisions borrowed from the openwebui pipelines project.
- TSugi Project (https://www.tsugi.org) Used in early Lamb implementations for LTI provider support. Many thanks to Dr. Chuck (Charles Severance) for his support and inspiration.
- TEEM Conference - (https://teemconference.eu) The TEEM conference has a vibrant community of researchers working on multidisciplinary fields connected to technology and education. The LAMB project was born on a coffe break conversation after the "Managing Generative AI in educational settings", we lost control of it :-) .
- Teaching Community - Early adopters and beta testers:
- https://tknika.eus/en/ Basque VET Applied Research Centre
- All Contributors - For their dedication to improving education through technology
- Universitat Politecnica de Cataluya. Galaxia d'Aprenentatge projecte PROPER, Factulat d'Informatica de Barcelona (2024-2025).
- Departament de Recerca i Universitats de la Generalitat de Catalunya through the 2021 SGR 01412 research groups award (2021-2025).
- Universidad del País Vasco/Euskal Herriko Unibertsitatea through the contract GIU21/037 under the program “Convocatoria para la Concesión de Ayudas a los Grupos de Investigación en la Universidad del País Vasco/Euskal Herriko Unibertsitatea (2021)
LAMB proudly adheres to the Safe AI in Education Manifesto - a comprehensive framework for ethical, secure, and educationally-aligned AI deployment.
The Safe AI in Education Manifesto outlines 7 core principles for responsible AI use in education:
- Human Oversight - AI complements, never replaces, human educators
- Privacy Protection - Student data confidentiality and security
- Educational Alignment - AI supports institutional strategies and learning objectives
- Didactic Integration - Seamless integration with teaching methodologies
- Accuracy & Explainability - Reliable, source-attributed information
- Transparent Interfaces - Clear communication of AI limitations and capabilities
- Ethical Training - Models trained with educational ethics and transparency
LAMB is designed from the ground up to embody these principles:
- 🔍 Human Oversight: All assistants are created and managed by educators with full control over behavior and content
- 🔒 Privacy-First: Self-hosted architecture keeps all student data within institutional control
- 📚 Educational Focus: Specialized subject tutors stay grounded in educational content and objectives
- 🧠 Didactic Integration: Seamless LTI integration with Moodle and other LMS platforms
- 📖 Source Attribution: Automatic citations and references to source materials
- 💬 Transparent Communication: Clear assistant responses with educational context and limitations
- 🎓 Ethical Foundation: Open-source, academically-developed with research collaboration
As signatories to the manifesto, LAMB's core team members are committed to advancing ethical AI in education. LAMB represents a practical implementation of manifesto principles in action.
- Project Leads: Marc Alier (UPC), Juanan Pereira (UPV/EHU)
- Research: Academic collaborations and research partnerships
- GitHub: https://github.com/Lamb-Project/lamb
- Issues: GitHub Issues
- Website: http://www.lamb-project.org
LAMB - Empowering educators to create intelligent, privacy-respecting AI assistants for enhanced learning experiences.