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Introducing RLAMA Chat

RLAMA

The complete AI platform for creating RAG systems and intelligent agents. Build, deploy, and manage AI-powered solutions with local models - from document Q&A to autonomous agent crews.

Project Currently Paused: This project is temporarily on hold due to our current commitments with full-time work and university studies. We're unable to dedicate time to active development at the moment, but we plan to resume when our schedule allows.

Install Now

Available for macOS, Linux, and Windows

$ rlama --version

RLAMA v0.1.29

$ rlama rag llama3 documentation ./docs

Embeddings generated successfully!

RAG system "documentation" created successfully!

$ rlama agent create researcher --role="Data Analyst"

Agent "researcher" created with RAG search tools!

$ rlama crew create research-team researcher writer

Crew "research-team" ready for collaborative tasks!

What is RLAMA?

A complete AI platform that combines RAG systems with intelligent agents, creating powerful automated workflows for any task - from document analysis to complex multi-agent collaboration.

Complete RAG Solution

Create, manage, and interact with Retrieval-Augmented Generation systems tailored to your documentation.

• Multiple document formats (.txt, .md, .pdf, etc.)
• Advanced semantic chunking strategies
• Local storage and processing with no data sent externally

AI Agents & Crews

Create specialized AI agents that can perform specific tasks or collaborate as crews to solve complex problems.

• Multiple agent roles (researcher, writer, coder, analyst)
• Agent tools (RAG search, code execution, web search)
• Collaborative workflows with sequential or parallel steps

Multi-Agent Orchestration

Orchestrate multiple agents working together in sophisticated workflows for complex automation tasks.

• Sequential workflows for step-by-step processes
• Parallel execution for concurrent task processing
• Hierarchical delegation with manager agents

Flexible Integration

Adapt RLAMA to your workflow with multiple integration options and extensive tooling support.

• HTTP API server for application integration
• Cross-platform support (macOS, Linux, Windows)
• OpenAI model support alongside Ollama

Key Features

Everything you need to build powerful RAG systems and intelligent AI agent workflows

RAG Systems

Create and manage Retrieval-Augmented Generation systems with multiple document formats.

AI Agents & Crews

Build specialized AI agents that collaborate as crews to solve complex problems.

Local Processing

100% local processing with no data sent to external servers for maximum privacy.

Intelligent Automation

Automate workflows with AI agents equipped with tools and collaborative capabilities.

Multi-Agent Workflows

Orchestrate multiple agents working together in sequential or parallel workflows.

Interactive Sessions

Chat with your RAG systems and agents through intuitive terminal interfaces.

Visual RAG Builder

Create powerful RAG systems in minutes without writing a single command

Create RAGs visually in 2 minutes

No coding required. Our intuitive interface makes RAG creation accessible to everyone.

• Easy drag-and-drop document upload
• Configure advanced settings with simple controls
• Save and share your configurations

Start building now

my-rag

Choose a name for your new RAG

Model

llama3.2

Ollama, OpenAI, or Hugging Face models

Source Type

Local Folder

Website

Source Configuration

Configure local folder source

Local Folder Path

./documents

Path to your document folder

Exclude Directories

node_modules,dist

Exclude Extensions

.log,.tmp

Process Extensions

.md,.py,.js

Chunking Settings

Controls document splitting

Strategy

Hybrid

Chunk Size

1000

Chunk Overlap

200

Generate Command

RLAMA in Action

See how simple it is to create and use RAG systems with our intuitive CLI

Create a RAG SystemInteractive Query SessionManage RAG SystemsUpdate and Version

Create a RAG System

Index a folder of documents to create a new RAG system. Supports multiple file formats and embedding models.

> Create a new RAG system named "documenta

> and indexing all documents in

rlama rag llama3 documentation ./docs

>

Processing file: docs/installation.md

Processing file: docs/commands.md

Processing file: docs/troubleshooting.pdf

Processing file: docs/api/endpoints.md

Processing file: docs/examples/basic_usage.md

Processing file: docs/examples/advanced_usage.md

Generating embeddings for 6 documents...

Embeddings generated successfully!

RAG system "documentation" created successfully!

Popular Use Cases

Discover how RLAMA powers both RAG systems and AI agent workflows

RAGPDFDOCXMD

Question: Question about docs...

Technical Documentation

Query your project documentation, manuals, and specifications with intelligent RAG systems.

LocalPrivateSecure

100% local processing

Private Knowledge Base

Create secure RAG systems for sensitive documents with full privacy and local processing.

AgentsResearchAnalysis

Command: Summarize key concepts...

Research Assistant

Deploy AI agents to query research papers, analyze data, and generate insights.

AgentsAutomationTools

Agent: Analyzing data sources...

AI Agent Workflows

Create specialized agents for coding, writing, analysis, and other automated tasks.

CrewsContentCollaboration

Multi-agent collaboration

Content Creation Crews

Orchestrate teams of AI agents for content creation, review, and publishing workflows.

WorkflowsAutomationMulti-Agent

Workflow: Sequential task execution...

Automated Workflows

Build complex multi-step workflows with agents working in sequence or parallel.

Command Reference

A complete reference of all available commands to master RLAMA

rag

Create a new RAG system from documents

rlama rag [model] [rag-name] [folder-path]

Example:rlama rag llama3 documentation ./docs

agent

Create and manage AI agents with specific roles

rlama agent [create|run|list] [agent-name] [options]

Example:rlama agent create researcher --role='Data Analyst' --tools=web_search,rag_search

crew

Create and orchestrate multi-agent crews for complex tasks

rlama crew [create|run|list] [crew-name] [agents...]

Example:rlama crew create research-team researcher writer reviewer

run

Start an interactive session with a RAG system or agent

rlama run [rag-name|agent-name|crew-name]

Example:rlama run documentation

list

List all available RAG systems, agents, and crews

rlama list [--type=rag|agents|crews]

Example:rlama list --type=agents

agent create

Create a new specialized AI agent

rlama agent create [agent-name] --role=[role] --tools=[tools]

Example:rlama agent create coder --role='Senior Developer' --tools=code_execution,rag_search

crew workflow

Define collaborative workflows between agents

rlama crew workflow [crew-name] --process=[sequential|parallel|hierarchical]

Example:rlama crew workflow content-team --process=sequential

agent tools

Manage tools available to agents (RAG search, web search, code execution)

rlama agent tools [list|add|remove] [agent-name]

Example:rlama agent tools add researcher web_search

watch

Set up directory watching for a RAG system

rlama watch [rag-name] [directory-path]

Example:rlama watch documentation ./docs

watch-off

Disable directory watching for a RAG system

rlama watch-off [rag-name]

Example:rlama watch-off documentation

check-watched

Check a RAG's watched directory for new files

rlama check-watched [rag-name]

Example:rlama check-watched documentation

api

Start API server

rlama api [--port PORT]

Example:rlama api --port 8080

update

Update RLAMA to the latest version

rlama update [--force/-f]

Example:rlama update

version

Display RLAMA version

rlama --version

Example:rlama -v

Common Issues & Solutions

Quick fixes for the most frequently encountered problems

Ollama not accessible

Text extraction problems

RAG not finding relevant information

Supported File Formats

RLAMA supports a wide variety of document formats to meet all your needs

Text

.txt

.md

.html

.json

.csv

.yaml

.yml

.xml

.org

Code

.go

.py

.js

.java

.c

.cpp

.cxx

.h

.rb

.php

.rs

.swift

.kt

.ts

.f

.F

.F90

.el

.svelte

Documents

.pdf

.docx

.doc

.rtf

.odt

.pptx

.ppt

.xlsx

.xls

.epub

Ready to streamline your document question-answering?

Install RLAMA View on GitHub

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