RLAMA

An open-source platform for developing document question-answering systems with local AI models, ensuring data privacy and flexibility.

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About RLAMA

RLAMA (Retrieval-Augmented Local Assistant Model Agent) is an open-source solution that integrates seamlessly with local AI models. It enables users to build, manage, and interact with RAG systems across various document formats, utilizing advanced semantic chunking, web crawling, and local storage to ensure privacy and efficiency in document question-answering applications.

How to Use

Install RLAMA via the command line. Build RAG systems by indexing document folders, perform queries interactively, and manage your systems using commands like `rlama rag`, `rlama run`, `rlama list`, and `rlama delete`. The RLAMA Unlimited version offers a visual interface for no-code RAG creation, simplifying the process further.

Features

Create, manage, and interact with RAG systems efficiently
Supports integration with OpenAI and local Ollama models
Visual RAG Builder in RLAMA Unlimited for no-code setup
Provides an HTTP API for application integration
Utilizes advanced semantic chunking techniques
Includes AI Agents and Crews for specialized tasks
Automates updates with directory watching
Supports Hugging Face models with over 45,000 GGUF options
Enables web crawling to generate RAGs directly from websites
Compatible with macOS, Linux, and Windows platforms
Handles multiple document types (.txt, .md, .pdf, etc.)
Ensures all data remains stored and processed locally, safeguarding privacy

Use Cases

Searching project documentation, manuals, and specifications
Quickly accessing research papers, textbooks, and study materials
Building secure RAG systems for sensitive or confidential documents

Best For

StudentsDevelopersTechnical writersAI engineersData scientistsResearch professionals

Pros

Supports AI Agents and Crews for complex workflows
Completely free and open-source CLI tool
Ensures 100% local data processing and storage
Includes a visual builder (RLAMA Unlimited) for no-code RAG setup
Compatible with various document formats
Integrates with local AI models like Ollama and OpenAI
Offers web crawling and directory watching features for automation

Cons

RAG may sometimes fail to retrieve relevant information
Requires command-line knowledge for CLI usage
Challenges with text extraction accuracy
Visual builder requires a subscription in RLAMA Unlimited
Potential accessibility issues with Ollama models

Pricing Plans

Choose the perfect plan. All plans include 24/7 support.

RLAMA Unlimited Monthly Subscription

$4.49 per month

No-code visual interface for rapid RAG development. Supports ecosystem growth and easy setup.

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One-Time RLAMA RAG Creation

$0.50 per RAG

Create RAGs quickly without coding using the visual builder. Ideal for small projects and testing.

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FAQs

What is RLAMA?

RLAMA is an open-source AI tool that enables building and managing document question-answering systems locally.

What functionalities does RLAMA offer?

RLAMA allows you to create, manage, and query RAG systems tailored for various document types and formats.

Which document formats are supported by RLAMA?

RLAMA supports PDFs, Markdown, plain text, and other common document formats with intelligent parsing.

Is RLAMA suitable for offline use?

Yes, RLAMA performs all processing locally without sending data to external servers, ensuring privacy.

How can I create a RAG system with RLAMA?

Use the command line with `rlama rag` or leverage the visual builder in RLAMA Unlimited for a no-code experience.