An open-source visual programming environment for battle-testing prompts to LLMs.
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AI-native database built for LLM applications, providing incredibly fast vector and full-text search.
Open-source project that supports deploying, serving, monitoring, or operating AI and machine-learning systems.
A project to make it easier to use large external knowledge bases with LLMs.
A python package that integrates an LLM copilot inside the keras model development workflow.
Deploy and scale machine learning models on Kubernetes. Built for LLMs, embeddings, and speech-to-text.
KubeStellar Console supports deploying, serving, monitoring, or operating AI and machine-learning systems.
A lightweight framework for building LLM-based agents.
FastAPI framework to build production-grade LLM applications.
Serverless LLM apps on Production with Jina AI Cloud (Archived).
Discover the large language models examples with insights on business adoption, language model training, and influential models.
Open-source project that supports deploying, serving, monitoring, or operating AI and machine-learning systems.
LiteLLM provides machine-learning models, research, training resources, or evaluation tools.
A hub of integrations for LlamaIndex including data loaders, tools, vector databases, LLMs and more.
Psst, kid, want some cheap and small LLMs?
Provides a central interface to connect your LLM's with external data.
LlamaIndex is a data framework for your LLM applications.
A data framework for building LLM applications over external data.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Build agents which are controlled by LLMs.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Research on evaluation of LLMs conducted by Microsoft Research and other collaborated institutes. (Updated at: 2023/10).
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.