Google tool for building, testing, and experimenting with Gemini prompts, models, and API workflows.
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Framework for building applications with LLMs and Transformers (e.g. agents, semantic search, question-answering).
"building applications with LLMs through composability".
A lightweight framework for building LLM-based agents.
Levity is the hub for building and scaling AI automations, designed for complex logistics workflows.
A data framework for building LLM applications over external data.
LLMFlows is a framework for building simple, explicit, and transparent LLM applications such as chatbots, question-answering systems, and agents.
A low-code framework for building custom AI models like LLMs and other deep neural networks. opensource.
Magic is an AI company that is working toward building safe AGI to accelerate humanity’s progress on the world’s most important problems.
Open source applied AI lab building next-gen devtools.
Building AGI with our mission Intelligence with Everyone. Global leader in multi-modal models and AI-native products with over 200 million users.
A Repository Containing Classification, Clustering, Regression, Recommender Notebooks with illustration to make them.
An open source, serverless framework for building intelligent agents and APIs in Go or AssemblyScript (a TypeScript-like language).
CEA-List's CAD framework for designing and simulating Deep Neural Network, and building full DNN-based applications on embedded platforms.
An open-source framework by NVIDIA for building speech AI systems, including automatic speech recognition and text-to-speech. opensource.
Open-source platform for building AI agent networks with multi-protocol support (WebSocket, gRPC, HTTP, MCP, A2A). opensource.
Fast and simple framework for building and running distributed applications.
Org profile for Stable Diffusion concepts library on Hugging Face, the AI community building the future.
No-code, automation workflow tool for building Generative AI media applications.
An MLOps/LLMOps platform for model building, evaluation, and fine-tuning.
A model-driven approach to building AI agents in just a few lines of code.
A simple Python library for building and testing recommender systems.
A neuro-symbolic framework for building applications with LLMs at the core.
Creates, rewrites or summarizes written content with language models.