What is RLAMA?

Rlama is a document question-answering tool designed for efficient interaction with local Ollama models. It allows users to create, manage, and engage with retrieval-augmented generation (RAG) systems tailored to document needs. The tool supports multiple document formats, including PDFs, Markdown, and text files, and offers intelligent parsing for seamless retrieval.

With offline functionality, Rlama ensures data is processed locally, maintaining privacy and security. Key features also include smart document chunking for optimal context retrieval and document watching, which automatically updates RAG systems as documents change.

Users can operate Rlama through a command-line interface, making it suitable for technical documentation queries, research assistance, and creating secure knowledge bases. The system is customizable, with support for various embedding models, enhancing its utility across diverse user scenarios.

⭐ Key features

RLAMA core features and benefits include the following:

✔️ Document question-answering.
✔️ Support for multiple document formats.
✔️ Intelligent parsing.
✔️ Command-line interface.
✔️ Customizable with various embedding models.

⚙️ Use cases & applications

✔️ Efficiently retrieve and answer questions from a large technical documentation repository using Rlama, allowing team members to access information quickly without sifting through endless documents.
✔️ Create a personalized knowledge base by integrating Rlama with your company’s documents, automatically updating it as new information becomes available and ensuring the security of sensitive data.
✔️ Utilize Rlama for academic research assistance, enabling students to query relevant sections of PDF papers and Markdown notes, thus enhancing their learning experience and productivity.

🙋‍♂️ Who is it for?

RLAMA can be useful for the following user groups:

Knowledge workers

Researchers

Data analysts

It professionals

Business managers

Security-conscious users

ℹ️ Find more & support

RLAMA provides an API that developers can use for programmatic access which makes it easy to integrate it with other tools or within your own applications.

You can also find more information, get support and follow RLAMA updates on the following channels: