A fast, copy‑paste‑friendly starter to explore MoRE ideas: route tokens to experts and apply adaptive recursion based on importance. Use a clean CLI, YAML config, and runnable examples to prototype quickly.
- Research-ready: minimal but opinionated scaffolding for MoRE experiments
- Runs in 30 seconds: config + CLI + example, no extra glue code
- Copy‑paste first: real commands and snippets below
- Install uv:
curl -LsSf https://astral.sh/uv/install.sh | sh- One-time project setup (creates .venv and installs deps):
uv venv && . .venv/bin/activate && uv pip install -r requirements.txt- Fallback (pip):
pip install -r requirements.txtRequires Python 3.9+.
- CLI (with uv):
uv run -m more demo --name "Ada"- Routing demo (with uv):
uv run -m more route --scores 0.2 0.5 0.8 0.95 --threshold 0.5 --max-depth 4- Zero‑setup one‑liner (uv will provision deps on the fly):
uv run --with pyyaml -m more demo --name "Ada"- Programmatic (inside repo):
from more.core import load_config, intro_message, assign_experts_and_recursions
cfg = load_config("config.yaml")
print(intro_message(cfg, name="Ada"))
print(assign_experts_and_recursions([0.2, 0.5, 0.8, 0.95], cfg.routing_threshold, cfg.max_recursion_depth))- Config knobs:
# config.yaml
project:
name: "MoRE"
default_name: "Researcher"
messages:
greeting: "Hello"
routing:
threshold: 0.5
max_depth: 4uv run -m more route --scores 0.1 0.3 0.7 0.9
# → score=0.10 -> expert=0 depth=1
# score=0.30 -> expert=1 depth=2
# score=0.70 -> expert=2 depth=3
# score=0.90 -> expert=3 depth=4- Run the example script:
uv run examples/quickstart.py.
├── more/
│ ├── __init__.py
│ ├── __main__.py # enables `python -m more`
│ ├── cli.py # argparse CLI with demo + route
│ └── core.py # config, intro_message, toy expert/recursion routing
├── examples/
│ └── quickstart.py # MoRE demo example
├── config.yaml # routing/defaults
├── requirements.txt # minimal runtime deps (PyYAML)
├── CONTRIBUTING.md # short contributor guide
└── README.md
- MoRE‑themed CLI to kickstart routing/recursion experiments
- YAML config for thresholds and depth
- Importable API for notebooks and benchmarking
If this saves you time, ⭐️ the repo and send a PR with your improvements!