Popular GitHub Repositories for Kafka Consumer

:robot: The free, Open Source alternative to OpenAI, Claude and others. Self-hosted and local-first. Drop-in replacement for OpenAI, running on consumer-grade hardware. No GPU required. Runs gguf, transformers, diffusers and many more models architectures. Features: Generate Text, Audio, Video, Images, Voice Cloning, Distributed, P2P inference

Python ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG.

Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. ?Docker-friendly.?Always in sync with Sharepoint, Google Drive, S3, Kafka, PostgreSQL, real-time data APIs, and more.

PipelineAI

Alink is the Machine Learning algorithm platform based on Flink, developed by the PAI team of Alibaba computing platform.

Run Mixtral-8x7B models in Colab or consumer desktops

Trench — Open-Source Analytics Infrastructure. A single production-ready Docker image built on ClickHouse, Kafka, and Node.js for tracking events, page views. Easily build product analytics dashboards, LLM RAGs, observability platforms, or any other analytics product.

Metering and Billing for AI, API and DevOps. Collect and aggregate millions of usage events in real-time and enable usage-based billing.

Machine Learning Platform and Recommendation Engine built on Kubernetes

High performance Rust stream processing engine seamlessly integrates AI capabilities, providing powerful real-time data processing and intelligent analysis.

Compare the performance of different LLM that can be deployed locally on consumer hardware. Run yourself with Colab WebUI.

This project contains examples which demonstrate how to deploy analytic models to mission-critical, scalable production environments leveraging Apache Kafka and its Streams API. Models are built with Python, H2O, TensorFlow, Keras, DeepLearning4 and other technologies.

In this repository, I have developed the entire server-side principal architecture for real-time stock market prediction with Machine Learning. I have used Tensorflow.js for constructing ml model architecture, and Kafka for real-time data streaming and pipelining.

Modular e-commerce backend with a GraphQL gateway and gRPC microservices for accounts, products, orders, and recommendations.

Classify Kaggle Consumer Finance Complaints into 11 classes. Build the model with CNN (Convolutional Neural Network) and Word Embeddings on Tensorflow.

LangStream. Event-Driven Developer Platform for Building and Running LLM AI Apps. Powered by Kubernetes and Kafka.

Real Time Big Data / IoT Machine Learning (Model Training and Inference) with HiveMQ (MQTT), TensorFlow IO and Apache Kafka - no additional data store like S3, HDFS or Spark required

Cross platform C++ library focusing on optimized machine translation on the consumer-grade device.

? Open Source App Framework to build streaming apps with real-time data - ? Build real-time data pipelines and make real-time data universally accessible - ? Join historical and real-time data in the stream to create smarter ML and AI applications. - ? Standardize complex data ingestion and stream data to apps with pre-built connectors

Multimodal Question Answering in the Medical Domain: A summary of Existing Datasets and Systems