mlops

The collaboration workspace for Machine Learning

📊 llm.report is an open-source logging and analytics platform for OpenAI: Log your ChatGPT API requests, analyze costs, and improve your prompts.

CodeProject.AI Server is a self contained service that software developers can include in, and distribute with, their applications in order to augment their apps with the power of AI.

Neum AI is a best-in-class framework to manage the creation and synchronization of vector embeddings at large scale.

Deploy any AI model, agent, database, RAG, and pipeline locally or remotely in minutes

Notebooks, code samples, sample apps, and other resources that demonstrate how to use, develop and manage machine learning and generative AI workflows using Google Cloud Vertex AI.

A 10-week, 30-minutes-a-day roadmap for LLM inference serving and optimization. vLLM, SGLang, quantization, speculative decoding, benchmarking.

Cookiecutter template for FastAPI projects using: Machine Learning, uv, Github Actions and Pytests

Ollama for classical ML models. AOT compiler that turns XGBoost, LightGBM, scikit-learn, CatBoost & ONNX models into native C99 inference code. One command to load, one command to serve. 336x faster than Python inference.

Deprecated historical repo. Superlinked now develops SIE, a self-hosted inference engine for embeddings, reranking, OCR, extraction, and document processing.

skops is a Python library helping you share your scikit-learn based models and put them in production

Smoothly Manage Multiple LLMs (OpenAI, Anthropic, Azure) and Image Models (Dall-E, SDXL), Speed Up Responses, and Ensure Non-Stop Reliability.

A curated list of MLSecOps tools and resources for securing machine learning and AI systems - adversarial ML defense, LLM security, AI red teaming, model scanning, supply-chain protection, and MLOps pipeline security.

A work in progress to build out solutions in Rust for MLOPs

mlops template

Here lies the resources and topics necessary for the role of Data Scientist and Machine Learning

A tiny yet powerful LLM inference system tailored for researching purpose. vLLM-equivalent performance with only 2k lines of code (2% of vLLM).

The production framework for Predictive and Generative AI. Serve any model as an API in one line, with OpenAI/Anthropic/Ollama-compatible endpoints, a built-in chat UI, and native MCP.

an MLOps/LLMOps platform

Python SDK for healthcare AI — typed, validated FHIR tools for agents, real-time EHR connectivity, production deployment ✨ 🏥