ToolAI.io · Chaîne GitHub
Découvrez les nouveaux projets AI open source ajoutés sur GitHub, avec les informations du dépôt, les instructions de configuration, les licences et les ressources associées.
Données du dépôt public
microsoft/agent-framework
An open-source framework for building, orchestrating, and evaluating AI agents across Python and .NET.
huggingface/smolagents
A lightweight Python library for building agents that use tools and execute code to solve tasks.
CrewAIInc/crewAI
A Python framework for coordinating role-based AI agents and structured task workflows.
dottxt-ai/outlines
A library for generating structured, constrained outputs from language models.
stanfordnlp/dspy
A framework for programming and optimizing language-model pipelines instead of hand-tuning prompts.
huggingface/trl
A library for post-training transformer models with supervised fine-tuning and preference-optimization methods.
typesafe-ai/typesafe-sdk-python
Connect Python services to the TypeSafe API using typed questions and results. The repository provides the client library rather than model weights.
NVIDIA/warp
Compiles typed Python functions into compute kernels with geometry, physics and differentiable programming capabilities for simulation and machine learning.
zai-org/GLM-OCR
An OCR project for tables, formulas and complex layouts, with hosted and self-hosted pipelines, a CLI and a Python SDK.
PaddlePaddle/PaddleSpeech
A PaddlePaddle-based speech toolkit covering speech recognition, text-to-speech, punctuation restoration, and other audio tasks, with command-line, Python interface, and service examples.
google-deepmind/mujoco
A multijoint contact dynamics engine maintained by Google DeepMind, providing model description, physics stepping, an interactive viewer, and a Python interface. It is suitable for developing robotics, control, and reinforcement learning environments.
hydra-ecosystem/hydra
A configuration framework for Python applications that manages experiments through configuration composition, command-line overrides, and multirun execution. It is suitable for organizing data, model, and training parameters into reusable configuration structures.
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