RLAMA - AI SDKs and Libraries Tool

Overview

RLAMA is an open-source tool for building Retrieval-Augmented Generation (RAG) document question-answering pipelines that run against local Ollama models. It provides both a command-line interface (CLI) and an API server so teams can ingest, manage, and query document collections while keeping model execution on-premises. RLAMA focuses on connecting document indexing and retrieval with local generative models, enabling private, low-latency RAG workflows for internal knowledge bases, manuals, and reports. According to the project repository (https://github.com/dontizi/rlama), RLAMA is released under the Apache-2.0 license and is intended for users who want a lightweight RAG orchestration layer that delegates embedding and generation to locally hosted Ollama models. The project exposes tooling to create and manage retrieval indices, run queries routed to local models, and operate an API server for programmatic integration. With a small contributor base but active maintenance (latest commit listed on the repository), RLAMA is suited for engineering teams that need an auditable, on-prem RAG stack that integrates with Ollama-based language models.

GitHub Statistics

• Stars: 1,090
• Forks: 75
• Contributors: 3
• License: Apache-2.0
• Primary Language: Go
• Last Updated: 2025-08-09T16:24:37Z
• Latest Release: v0.1.39

The GitHub repository (https://github.com/dontizi/rlama) shows moderate community interest with 1,090 stars and 75 forks, licensed under Apache-2.0. The project has a small core contributor set (3 contributors) which suggests a compact maintainer team. The repository's last commit is dated 2025-08-09T16:24:37Z, indicating recent activity and ongoing maintenance. Overall, the project appears actively maintained but has a small developer community; contributions and issue activity can be checked on the repo for up-to-date engagement metrics.

Installation

Install via docker:

git clone https://github.com/dontizi/rlama.git

cd rlama

Refer to the repository README for build and run instructions specific to your environment (Docker, local Python, or other supported setups).

Key Features

• CLI for ingesting and querying document collections via local RAG workflows.
• API server exposing endpoints to query documents and manage RAG pipelines programmatically.
• Native integration with local Ollama models for on-prem embeddings and text generation.
• Document management tools to create, update, and remove indexed document collections.
• Open-source Apache-2.0 license enabling auditability and on-prem enterprise deployments.

Community

RLAMA has moderate community interest (1,090 GitHub stars, 75 forks) and a small maintainer team (3 contributors). Recent repository activity (last commit 2025-08-09) indicates ongoing maintenance. For support and feedback, open issues or pull requests on the GitHub repository and review the project README and issue tracker for usage examples, troubleshooting, and contribution guidelines.

Key Information

• Category: SDKs and Libraries
• Type: AI SDKs and Libraries Tool