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@ -134,10 +134,10 @@ _Libraries for building AI applications, LLM integrations, and autonomous agents
- Agent Skills
- [django-ai-plugins](https://github.com/vintasoftware/django-ai-plugins) - Django backend agent skills for Django, DRF, Celery, and Django-specific code review.
- [graphify](https://github.com/safishamsi/graphify) - Turn any folder of code, SQL schemas, R scripts, shell scripts, docs, papers, images, or videos into a queryable knowledge graph.
- [graphify](https://github.com/safishamsi/graphify) - Turn any folder of code, SQL schemas, docs, papers, images, or videos into a queryable knowledge graph.
- [nuwa-skill](https://github.com/alchaincyf/nuwa-skill/blob/main/README_EN.md) - Nuwa distills the thinking of anyone — let Musk, Naval, Munger, and Feynman work for you.
- [sentry-skills](https://github.com/getsentry/skills) - Python-focused engineering skills for code review, debugging, and backend workflows.
- [trailofbits-skills](https://github.com/trailofbits/skills) - Python-friendly security skills for auditing, testing, and safer backend development. Also [skills-curated](https://github.com/trailofbits/skills-curated).
- [trailofbits-skills](https://github.com/trailofbits/skills) - Python-friendly security skills for auditing, testing, and safer backend development.
- Orchestration
- [ag2](https://github.com/ag2ai/ag2) - An open-source AgentOS for multi-agent orchestration and building agentic AI systems.
- [autogen](https://github.com/microsoft/autogen) - A programming framework for building agentic AI applications.
@ -192,7 +192,7 @@ _Libraries for Machine Learning. Also see [awesome-machine-learning](https://git
- [mindsdb](https://github.com/mindsdb/minds-platform) - MindsDB is an open source AI layer for existing databases that allows you to effortlessly develop, train and deploy state-of-the-art machine learning models using standard queries.
- [pgmpy](https://github.com/pgmpy/pgmpy) - A Python library for probabilistic graphical models and Bayesian networks.
- [scikit-learn](https://github.com/scikit-learn/scikit-learn) - The most popular Python library for Machine Learning with extensive documentation and community support.
- * [scikit-lego](https://github.com/koaning/scikit-lego) - A collection of lego bricks for scikit-learn pipelines.
- - [scikit-lego](https://github.com/koaning/scikit-lego) - A collection of lego bricks for scikit-learn pipelines.
- [spark.ml](https://github.com/apache/spark) - [Apache Spark](https://spark.apache.org/)'s scalable [Machine Learning library](https://spark.apache.org/docs/latest/ml-guide.html) for distributed computing.
- [TabGAN](https://github.com/Diyago/Tabular-data-generation) - Synthetic tabular data generation using GANs, Diffusion Models, and LLMs.
- [timesfm](https://github.com/google-research/timesfm) - A pretrained foundation model from Google Research for time-series forecasting.