docs: add AI and Agents category with autoresearch

New category for LLM integrations, agent frameworks, and AI applications.
Move agno, instructor, langchain, llama_index, praisonai, pydantic-ai,
ragflow from Machine Learning. Add autoresearch (karpathy).

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
This commit is contained in:
Vinta Chen
2026-03-19 01:45:24 +08:00
parent 9761bac1e0
commit 46caf8cec4

View File

@@ -7,6 +7,7 @@ An opinionated list of awesome Python frameworks, libraries, tools, software and
# Categories
- [Admin Panels](#admin-panels)
- [AI and Agents](#ai-and-agents)
- [Algorithms and Design Patterns](#algorithms-and-design-patterns)
- [ASGI Servers](#asgi-servers)
- [Asynchronous Programming](#asynchronous-programming)
@@ -103,6 +104,19 @@ _Libraries for administrative interfaces._
- [jet-bridge](https://github.com/jet-admin/jet-bridge) - Admin panel framework for any application with nice UI (ex Jet Django).
- [wooey](https://github.com/wooey/wooey) - A Django app which creates automatic web UIs for Python scripts.
## AI and Agents
_Libraries for building AI applications, LLM integrations, and autonomous agents._
- [agno](https://github.com/agno-agi/agno) - Open-source Python library for building AI agents and agentic systems.
- [autoresearch](https://github.com/karpathy/autoresearch) - AI agents running autonomous research experiments on single-GPU LLM training.
- [instructor](https://github.com/567-labs/instructor) - A library for extracting structured data from LLMs, powered by Pydantic.
- [langchain](https://github.com/langchain-ai/langchain) - Building applications with LLMs through composability.
- [llama_index](https://github.com/run-llama/llama_index) - A data framework for your LLM application.
- [praisonai](https://github.com/MervinPraison/PraisonAI) - Production-ready Multi-AI Agents framework with self-reflection, 100+ LLM support, MCP integration, and agentic workflows.
- [pydantic-ai](https://github.com/pydantic/pydantic-ai) - A Python agent framework for building generative AI applications with structured schemas.
- [ragflow](https://github.com/infiniflow/ragflow) - An open-source RAG engine for document understanding and question answering with LLMs.
## Algorithms and Design Patterns
_Python implementation of data structures, algorithms and design patterns. Also see [awesome-algorithms](https://github.com/tayllan/awesome-algorithms)._
@@ -714,20 +728,13 @@ _Libraries for generating and working with logs._
_Libraries for Machine Learning. Also see [awesome-machine-learning](https://github.com/josephmisiti/awesome-machine-learning#python)._
- [agno](https://github.com/agno-agi/agno) - Open-source Python library for building AI agents and agentic systems.
- [diffusers](https://github.com/huggingface/diffusers) - A library that provides pretrained diffusion models for generating and editing images, audio, and video.
- [feature_engine](https://github.com/feature-engine/feature_engine) - sklearn compatible API with the widest toolset for feature engineering and selection.
- [gym](https://github.com/openai/gym) - A toolkit for developing and comparing reinforcement learning algorithms.
- [h2o](https://github.com/h2oai/h2o-3) - Open Source Fast Scalable Machine Learning Platform.
- [instructor](https://github.com/567-labs/instructor) - A library for extracting structured data from LLMs, powered by Pydantic.
- [langchain](https://github.com/langchain-ai/langchain) - Building applications with LLMs through composability.
- [llama_index](https://github.com/run-llama/llama_index) - A data framework for your LLM application.
- [metrics](https://github.com/benhamner/Metrics) - Machine learning evaluation metrics.
- [mindsdb](https://github.com/mindsdb/mindsdb) - 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.
- [praisonai](https://github.com/MervinPraison/PraisonAI) - Production-ready Multi-AI Agents framework with self-reflection, 100+ LLM support, MCP integration, and agentic workflows.
- [pydantic-ai](https://github.com/pydantic/pydantic-ai) - A Python agent framework for building generative AI applications with structured schemas.
- [ragflow](https://github.com/infiniflow/ragflow) - An open-source RAG engine for document understanding and question answering with LLMs.
- [rasa](https://github.com/RasaHQ/rasa) - An open-source machine learning framework for automated text and voice-based conversations.
- [scikit-learn](https://github.com/scikit-learn/scikit-learn) - The most popular Python library for Machine Learning with extensive documentation and community support.
- [spark.ml](http://spark.apache.org/docs/latest/ml-guide.html) - [Apache Spark](http://spark.apache.org/)'s scalable Machine Learning library for distributed computing.