Python SDK for Inngest: Durable functions and workflows in Python, hosted anywhere

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A system for ingesting, chunking, and querying PDFs using Retrieval-Augmented Generation (RAG) techniques. It integrates FastAPI, Inngest, Google's Gemini API, and Qdrant for AI-powered document search and question answering.

Scheduled & background tasks will never be the same once you use Inngest. That's why I made this integration. I'm a fan.

An open-source AI-powered music lab that generates songs, lyrics, and cover art with a modern full-stack setup ⚡🎶🤖🎨

Retrieval Augmented Generation (RAG) system that processes PDF documents, stores them in a vector database, and generates contextual answers using LLM. Built with FastAPI and Inngest.

ConversePDF is an AI-powered document Q&A app that lets users upload PDFs and ask questions about them. It uses FastAPI for the backend, Streamlit for the UI, LlamaIndex to process documents and orchestrate RAG, Qdrant as a vector database to store document embeddings, and Inngest to handle background processing jobs asynchronously

An intelligent agent capable of autonomously finding relevant news articles on a given topic and compiling them into a professional, engaging newsletter. (Focus on scalability using inngest)

A powerful RAG application to upload and chat with PDFs, built with FastAPI, Inngest, Qdrant, and Streamlit.

RAG pipeline using Python