A self-hosted address and synthetic test-profile generator for 27 countries and regions, built from real open-data streets, administrative areas, coordinates, and postcodes. Supports multilingual output, IP-nearby generation, map previews, and API access.
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DeepEval is a simple-to-use, open-source LLM evaluation framework, for evaluating large-language model systems. It is similar to Pytest but specialized for unit testing LLM apps. , which use LLM-as-a-judge and other NLP models that run locally on your machine.
#1710 · +17 · 1d ·GitHub
Build, test, and deploy ML-driven trading strategies, from data sourcing to live execution.
Scientific hypothesis-discovery workbench: grounded hypothesis-evidence graphs, synthetic literature with planted causal chains, generate-debate-evolve loops over pluggable offline adapters, Elo tournaments recovering planted skill order, paraphrase dedup, Bayesian evidence…
> This repository contains the DATAMIMIC Community Edition (CE). MIT-licensed, Python-native, MCP-ready. > > CE is fully usable standalone for deterministic synthetic data generation and model-based pseudonymization.