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GitHub - arthur-ai/bench: A tool for evaluating LLMs

DeepEval — It’s a tool for easy and efficient LLM testing. Deepeval aims to make writing tests for LLM applications (such as RAG) as easy as writing Python unit tests.

dstack is an open-source toolkit and orchestration engine for running GPU workloads. It's designed for development, training, and deployment of gen AI models on any cloud.

Supported providers: AWS, GCP, Azure, Lambda, TensorDock, Vast.ai, and DataCrunch.

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• [2024/01] dstack 0.14.0: OpenAI-compatible endpoints preview (Release)


• [2023/12] dst

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Mem0: The Memory Layer for Personalized AI

Mem0 provides a smart, self-improving memory layer for Large Language Models, enabling personalized AI experiences across applications.

Note: The Mem0 repository now also includes the Embedchain project. We continue to maintain and support Embedchain ❤️. You can find the Embedchain codebase in the embedchai

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HoneyHive is a collaboration platform to test and evaluate, monitor and debug your LLM apps, from prototype to production. It enables you to continuously improve LLM apps in production with human feedback, quantitative rigour and safety best-practices.

Dify is an LLM application development platform that has helped built over 100,000 applications. It integrates BaaS and LLMOps, covering the essential tech stack for building generative AI-native applications, including a built-in RAG engine. Dify allows you to deploy your own version of Assistants API and GPTs, based on any LLMs.

Using our Cloud S... See more