Popular GitHub Repositories for Metrics Databases

For developers, who are building real-time data-driven applications, Redis is the preferred, fastest, and most feature-rich cache, data structure server, and document and vector query engine.

AI's query engine - Platform for building AI that can learn and answer questions over large scale federated data.

Low-code platform for building business applications. Connect to databases, cloud storages, GraphQL, API endpoints, Airtable, Google sheets, OpenAI, etc and build apps using drag and drop application builder. Built using JavaScript/TypeScript. ?

? 1Panel offers an intuitive web interface for managing websites, files, containers, databases and LLMs within a Linux server.

? Open source LLM engineering platform: LLM Observability, metrics, evals, prompt management, playground, datasets. Integrates with OpenTelemetry, Langchain, OpenAI SDK, LiteLLM, and more. ?YC W23

The LLM Evaluation Framework

Gen AI Toolbox for Databases is an open source server that makes it easier to build Gen AI tools for interacting with databases.

Evidently is ??an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.

Brings SQL and AI together.

Python SDK for AI agent monitoring, LLM cost tracking, benchmarking, and more. Integrates with most LLMs and agent frameworks including OpenAI Agents SDK, CrewAI, Langchain, Autogen, AG2, and CamelAI

High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently.

《大模型白盒子构建指南》：一个全手搓的Tiny-Universe

HelixDB is a powerful, graph-vector database built in Rust for millisecond query latency and ease of use.

Open-source tools for prompt testing and experimentation, with support for both LLMs (e.g. OpenAI, LLaMA) and vector databases (e.g. Chroma, Weaviate, LanceDB).

mean Average Precision - This code evaluates the performance of your neural net for object recognition.

Quantized Attention that achieves speedups of 2.1-3.1x and 2.7-5.1x compared to FlashAttention2 and xformers, respectively, without lossing end-to-end metrics across various models.

A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.

Machine learning metrics for distributed, scalable PyTorch applications.

Basic Utilities for PyTorch Natural Language Processing (NLP)

The universal tool suite for vector database management. Manage Pinecone, Chroma, Qdrant, Weaviate and more vector databases with ease.