FAQ¶
Does OddsFox Graph host data?¶
No. This repository is Hypertrial-owned MIT software. Documentation does not host datasets. Operators supply their own Pipeline golden mart export and local model weights.
Why is infer so slow?¶
LLM inference dominates wall-clock time. Deterministic topology skips the LLM
for template-covered events (~91% on WC2026). For residual events, prefer
--llm-backend inprocess (default) or mlx for single-machine decode speed;
use --llm-backend server --concurrency N when you want concurrent request
pipelining. See Inference backends.
Do I need Metal?¶
Metal-accelerated llama-cpp-python is recommended on Apple Silicon. CI and
CPU-only environments can install the prebuilt CPU wheel instead. See
Linux / CPU-only setup.
Are topology and markets connected?¶
Yes for markets covered by the proposition compiler. Those OUTCOME nodes
carry a formal Proposition and link into topology via REFERS_TO (plus
PRICES / COMPLEMENT / EXACTLY_ONE). Deterministic rules then add
IMPLIES / EQUIVALENT / MUTEX. Residual / unrecognized market types may
still lack propositions — see Logical layer and
Known limitations.
Where do configuration defaults live?¶
In oddsgraph/config.py. The Configuration
page mirrors those code defaults.