# The main requirements.txt minus the data-pipeline half: this Space serves one
# clip at a time and never builds a corpus, so fastf1 / datasets / duckdb / jiwer
# are all dead weight in the image.
#
# torch is NOT pinned to the CPU wheel here, unlike the root requirements.txt.
# ZeroGPU needs the CUDA build, and its runtime requires torch >= 2.8.

# python_version 3.12 in README.md is load-bearing, not cosmetic. The ZeroGPU
# base image is Python 3.10, and scipy 1.16.3 publishes no cp310 wheel - the
# first build died on "No matching distribution found for scipy==1.16.3". The
# fix is to move the interpreter rather than to relax the pin: this file exists
# so the Space runs the versions the test suite ran, and test_space_live.py
# asserts the pipeline is byte-identical to backend/pipeline. Byte-identical
# code on a different scipy is a weaker claim than it looks.
torch==2.9.1
transformers==5.15.0
librosa==0.11.0
soundfile==0.14.0
numpy==1.26.2
scipy==1.16.3
scikit-learn==1.8.0

# Not for transcription here - the Space runs Whisper through transformers. This
# is for the Silero VAD it bundles as ONNX, which prosody needs to window over
# speech instead of over silence and channel noise.
faster-whisper==1.2.1

gradio==5.49.1

# `spaces` is deliberately NOT pinned here. The ZeroGPU builder appends its own
# `spaces==<version>` to the same pip invocation as this file, so pinning a
# different one is a hard resolver conflict and the build fails before it
# installs anything. The runtime owns that package; we import it.