Open source tools and frameworks for AI/ML engineering.
ML observability toolkit for Arize AI
A comprehensive Python toolkit for interacting with and configuring Arize AI use cases. Features model management, monitoring, custom metrics, LLM features, data integration from cloud storage and databases, and an optional prompt optimization extension. Built with 92% test coverage and CI/CD automation.
AI-powered research assistant
An intelligent research assistant that finds, analyzes, and synthesizes academic papers from arXiv. Features persistent memory with Mem0, automatic intent detection, dynamic planning with step-by-step execution, and Phoenix integration for comprehensive observability.
Template for agentic systems and LLM workflows
A production-ready template for developing agentic systems, LLM workflows, and professional demos. Includes web interface, Phoenix observability, Docker-based deployment, and modular architecture supporting multiple LLM providers and agentic frameworks.
Multi-framework LLM implementation comparison
A comparative implementation project demonstrating the same LLM application across seven orchestration frameworks: OpenAI Direct, CrewAI, LangGraph, Pydantic AI, LiteLLM, DSPy, and Groq. Each implementation includes Phoenix observability, Docker containerization, and conversation memory.