A communication fidelity benchmark for multi-agent AI systems. Measuring per-hop information degradation in LLM agent chains.
Project description
FidelityBench
A communication fidelity benchmark for multi-agent AI systems. Part of Qualixar | Author: Varun Pratap Bhardwaj Coming soon. Follow github.com/qualixar/fidelitybench for updates.
License
MIT
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
fidelitybench-0.0.1.tar.gz
(1.4 kB
view details)
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 fidelitybench-0.0.1.tar.gz.
File metadata
- Download URL: fidelitybench-0.0.1.tar.gz
- Upload date:
- Size: 1.4 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.12.12
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
5f52c243944cfef17db60b07a58b7cc9830f9a727af686c5dea5c249de4c2cb0
|
|
| MD5 |
21ceecd4de962db4c04a151e48414a3d
|
|
| BLAKE2b-256 |
dd3ae23186a9388cbe2280217807faa93b55318fceb9f25c5ff1be405fd988f0
|
File details
Details for the file fidelitybench-0.0.1-py3-none-any.whl.
File metadata
- Download URL: fidelitybench-0.0.1-py3-none-any.whl
- Upload date:
- Size: 1.7 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.12.12
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
40fabb8446498b82db2565774abe88e1f32de37c3e27caef4824137bcb13841f
|
|
| MD5 |
c7f9a95014f77f8f89b6afbfa8a281d3
|
|
| BLAKE2b-256 |
a0e3b341c9d61a8a4c11e398f482e3abbe8268e5a3f33caaca4fac615a29c4d7
|
