BlackBoard MUSic Engine
BbMuse is an open-source platform-independent Python framework and backend for interactive AI systems based on the good old concept of blackboard systems. It aims to fill the gap between ad hoc multi-agent systems that require complex manual "wiring" and monolithic neural models that act as opaque "black boxes". By adapting a modern blackboard architecture from real-time robotics, we create a system where real-time musical composition is treated as a distributed hierarchical decision-making process.
Links
-
conference paper introducing BbMuse and its main concepts.
-
conference paper presenting BbLearn: an AI extension for BbMuse living in the same repo.
Installation and first-run experience
To comfortably install via PyPI, use: pip install bbmuse
To install locally (e.g., if cloned from GitHub), use: pip install -e . (from inside the cloned directory)
To quickly test your installation, run: bbmuse tests/DummyProject/ --quit-after 5
For additional usage, run: bbmuse --help
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file bbmuse-0.2.0.tar.gz.
File metadata
- Download URL: bbmuse-0.2.0.tar.gz
- Upload date:
- Size: 33.5 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via:
twine/7.0.0 CPython/3.12.13
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
e073d86a3a917a91521bff175bc5f8655fd856fc374e25b08513b040bec94e0c
|
|
| MD5 |
c3ba06f2dcb6bf06ccddd8bfe1b95358
|
|
| BLAKE2b-256 |
3b4734e0b13555af4c7d8d4f397e98d27a96a914790393567cb0c2bacebdfa57
|
File details
Details for the file bbmuse-0.2.0-py3-none-any.whl.
File metadata
- Download URL: bbmuse-0.2.0-py3-none-any.whl
- Upload date:
- Size: 43.4 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via:
twine/7.0.0 CPython/3.12.13
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
00cad4858234fb4211ccab7a5e2a25cd95bc60f582efcaa26fcd213de12d62f3
|
|
| MD5 |
623ff42bcdbddeabc48f94911644601d
|
|
| BLAKE2b-256 |
5ec2a02d4378632d2e07a7b8dcd17b7434a0495b356b1b0393fae071f3703248
|