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RLAMA

RLAMA

Open-Source RAG CLI for Ollama

Website rlama.dev
Overview

What it is

Retrieval-Augmented Local Assistant Model Agent

Intent

I need it when

Deploy AI agents equipped with multiple tools (RAG search, code execution, web search) to perform specialized analysis and research tasks

RLAMA agents can be configured with specific tools and roles to perform research, data analysis, coding, and content creation. Agents can access RAG systems, execute code, and perform web searches as needed for task completion.

Query technical documentation and knowledge bases using natural language without relying on external AI services

RLAMA provides interactive chat sessions with RAG systems and agents through terminal interfaces. Users can ask questions about indexed documents and receive intelligent responses powered by local models, maintaining full data privacy.

Build retrieval-augmented generation (RAG) systems to query and analyze private documents without sending data to external servers

RLAMA enables users to create RAG systems from multiple document formats (.pdf, .docx, .md, .txt, etc.) with local processing and semantic chunking. All data remains on-device, ensuring privacy and security for sensitive documentation.

Automate complex workflows by orchestrating multiple AI agents with specialized roles working together sequentially or in parallel

RLAMA allows creation of AI agents with specific roles (researcher, writer, coder, analyst) and crews that collaborate on multi-step tasks. Users can define sequential, parallel, or hierarchical workflows for sophisticated automation without coding.

Create and manage AI-powered solutions locally across multiple operating systems without vendor lock-in

RLAMA is cross-platform (macOS, Linux, Windows), open-source, and installable via CLI. Users maintain full control over their AI infrastructure with support for multiple model providers (Ollama, OpenAI, Hugging Face) and flexible integration options.

Drop

Not a fit when

  • User requires commercial support or SLA guarantees; RLAMA is community-driven with no official support tier
  • User needs cloud-hosted solution; RLAMA requires local installation and processing
  • User lacks technical expertise to install Ollama and manage CLI commands; no GUI available for non-technical users
  • User requires proprietary model integration only; RLAMA supports Ollama, OpenAI, and Hugging Face but not all commercial APIs
  • User needs real-time web search as primary feature; web search is a secondary agent tool, not the core offering
Commercials

Pricing

Free and open-source