RLAMA - AI Developer Tools Tool

Overview

RLAMA is an AI-driven document question-answering tool that connects to local Ollama models. It provides a CLI and API server to create, manage, and interact with Retrieval-Augmented Generation (RAG) systems for processing and querying documents.

Key Features

• Connects to local Ollama models for model inference.
• Create and manage Retrieval-Augmented Generation (RAG) systems.
• Process and query documents for document-level question answering.
• Provides both CLI and API server interfaces.
• Integrates ingestion and query workflows for document RAG.

Ideal Use Cases

• Local document question-answering and knowledge retrieval.
• Prototyping RAG systems with local models.
• Embedding and searching internal documents via API or CLI.
• Building self-hosted knowledge-base query services.

Getting Started

• Clone the RLAMA repository from the project's GitHub URL.
• Install prerequisites and dependencies listed in the repository README.
• Run the CLI to initialize a RAG project and ingest documents.
• Start the API server to expose query endpoints.
• Point RLAMA at local Ollama models for inference.

Pricing

Pricing or hosting details are not disclosed in the project repository; consult the GitHub page for license and deployment information.

Limitations

• Requires access to local Ollama models for inference.
• Designed for self-hosted deployments; no hosted service indicated.

Key Information

• Category: Developer Tools
• Type: AI Developer Tools Tool