Overview
What is local-rag-omscs?
local-rag-omscs is a Python service designed to bootstrap applications using concepts from Clean Architecture and SOLID principles, specifically tailored for local RAG (Retrieval-Augmented Generation) setups.
How to use local-rag-omscs?
To use local-rag-omscs, create a GitHub repository using the provided template, install necessary dependencies, and run the application using Docker commands or Make commands as specified in the documentation.
Key features of local-rag-omscs?
- Sync and Async API Documentation with FastAPI and AsyncAPI.
- Async task execution with Dramatiq.
- Websocket support using Socket.io.
- Repository pattern for databases with SQLAlchemy.
- Database migrations and fixtures support with Alembic.
- Authentication using Ory Zero Trust architecture.
- Full observability setup with OpenTelemetry.
- Example CI/CD deployment pipeline for GitLab.
Use cases of local-rag-omscs?
- Building scalable web applications with real-time features.
- Implementing complex data processing tasks asynchronously.
- Setting up a robust backend for machine learning applications.
FAQ from local-rag-omscs?
- Is local-rag-omscs suitable for production use?
Yes, it is designed with production-ready features and best practices in mind.
- What technologies does local-rag-omscs use?
It utilizes Python, FastAPI, SQLAlchemy, and Docker among others.
- How can I contribute to local-rag-omscs?
You can contribute by forking the repository, making changes, and submitting a pull request.