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# AGENTS.md
## Repository Overview
An opinionated list of Python frameworks, libraries, tools, and resources. Published at [awesome-python.com](https://awesome-python.com/).
## Entry Guidelines
**Refer to [CONTRIBUTING.md](CONTRIBUTING.md)** for acceptance criteria, quality requirements, rejection rules, and entry format. Apply these rules whenever adding or removing an entry, whether reviewing a PR or committing directly.
## Structure
- **README.md**: Source of truth for catalog entries and README sponsor placements. Hierarchical categories with alphabetically ordered entries.
- **CONTRIBUTING.md**: Submission guidelines and review criteria.
- **SPONSORSHIP.md**: Sponsor tiers, placement rules, and the editorial-independence policy. `website/templates/sponsorship.html` separately defines which sponsorship content appears on the published website page.
- **website/**: Static site generator that builds awesome-python.com from README.md.
- `build.py`: Parses README.md and renders HTML via Jinja2 templates.
- `fetch_github_stars.py`: Fetches star counts into `website/data/`.
- `readme_parser.py`: Markdown-to-structured-data parser.
- `templates/`, `static/`: Jinja2 templates and CSS/JS assets.
- `tests/`: Pytest tests for the build pipeline.
- **Makefile**: `make install`, `make build`, `make preview`, `make test`, `make lint`, `make format`, `make typecheck`, `make fetch_github_stars`.
- **pyproject.toml**: Uses `uv` for dependency management. Python >=3.13.
## Key Rules
- Alphabetical ordering within categories is mandatory.
- Quality over quantity. Only "awesome" projects.
- One project per PR.
- One entry per commit when adding or deleting entries. Format, wording, or categorization changes across multiple entries may be bundled in a single commit.
- README.md is the source of truth for catalog entries and README sponsor placements; treat `SPONSORSHIP.md` and `website/templates/sponsorship.html` as separate sponsorship content surfaces.

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@ -165,6 +165,7 @@ _Libraries for building AI applications, LLM integrations, and autonomous agents
- [vllm](https://github.com/vllm-project/vllm) - A high-throughput and memory-efficient inference and serving engine for LLMs.
- Speech
- [openai-whisper](https://github.com/openai/whisper) - A general-purpose automatic speech recognition model trained on 680k hours of multilingual and multitask supervised data.
- [funasr](https://github.com/modelscope/FunASR) - Industrial-grade speech recognition toolkit with 170x realtime speed, 50+ languages, speaker diarization, and emotion detection.
- [vibevoice](https://github.com/microsoft/VibeVoice) - A family of open-source voice AI models from Microsoft for text-to-speech and long-form speech recognition.
- [voxcpm](https://github.com/OpenBMB/VoxCPM) - A tokenizer-free text-to-speech foundation model for multilingual speech generation and voice cloning.
@ -190,6 +191,7 @@ _Libraries for Machine Learning. Also see [awesome-machine-learning](https://git
- [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.
- [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.
- [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.
@ -435,6 +437,7 @@ _Libraries for connecting and operating databases._
_Databases implemented in Python._
- [chdb](https://github.com/chdb-io/chdb) - In-process OLAP SQL engine with the full ClickHouse dialect, zero-copy pandas/Arrow interop, and federation to remote ClickHouse clusters via `remoteSecure()`.
- [chromadb](https://github.com/chroma-core/chroma) - An open-source embedding database for building AI applications with embeddings and semantic search.
- [duckdb](https://github.com/duckdb/duckdb) - An in-process SQL OLAP database management system; optimized for analytics and fast queries, similar to SQLite but for analytical workloads.
- [pickledb](https://github.com/patx/pickledb) - A simple and lightweight key-value store for Python.
@ -1122,6 +1125,7 @@ _Libraries for programming with hardware._
- [bleak](https://github.com/hbldh/bleak) - A cross platform Bluetooth Low Energy Client for Python using asyncio.
- [jumpstarter](https://github.com/jumpstarter-dev/jumpstarter) - A hardware-in-the-loop testing framework with a Python client library for automated testing on real and virtual hardware.
- [pynput](https://github.com/moses-palmer/pynput) - A library to control and monitor input devices.
- [synology-api](https://github.com/N4S4/synology-api) - Python wrapper for Synology NAS APIs: Surveillance Station, File Station, Download Station, Docker, and 50+ other endpoints.
### Microsoft Windows