omkar-sh
Follow
Lists (2)
Stars
Low latency, High Accuracy, Custom Query routers for Humans and Agents. Built by Prithivi Da
Flexible and powerful framework for managing multiple AI agents and handling complex conversations
LLaVA-CoT, a visual language model capable of spontaneous, systematic reasoning
Running load tests on a FastAPI application using Locust
o1-engineer is a command-line tool designed to assist developers in managing and interacting with their projects efficiently. Leveraging the power of OpenAI's API, this tool provides functionalitie…
Composable building blocks to build Llama Apps
NLP Projects playlist
A Python-based web-assisted large language model (LLM) search assistant using Llama.cpp
Enhance Tesseract OCR output for scanned PDFs by applying Large Language Model (LLM) corrections.
A curated list of open source repositories for AI Engineers
The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery 🧑🔬
Efficient Triton Kernels for LLM Training
Anthropic's educational courses
Demonstrates three tier architecture using 12 micro services project on AWS EKS.
AdalFlow: The library to build & auto-optimize LLM applications.
This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. RAG systems combine information retrieval with generative models to provide accurate and cont…
Example data pipeline automation with GitHub Actions
This repository contains an end-to-end data engineering project using Apache Flink, focused on performing sales analytics. The project demonstrates how to ingest, process, and analyze sales data, s…
This repository contains an Apache Flink application for real-time sales analytics built using Docker Compose to orchestrate the necessary infrastructure components, including Apache Flink, Elastic…
This repository contains the code for a realtime election voting system. The system is built using Python, Kafka, Spark Streaming, Postgres and Streamlit. The system is built using Docker Compose t…
This repository contains the necessary configuration files and DAGs (Directed Acyclic Graphs) for setting up a robust data engineering environment using Kubernetes and Apache Airflow
An end-to-end data engineering pipeline that orchestrates data ingestion, processing, and storage using Apache Airflow, Python, Apache Kafka, Apache Zookeeper, Apache Spark, and Cassandra. All comp…
In this project, we setup and end to end data engineering using Apache Spark, Azure Databricks, Data Build Tool (DBT) using Azure as our cloud provider.