fix: install nvidia-cudnn-cu12 alongside CUDA torch (removes --no-deps)

fix: force-reinstall CUDA torch before gradio import; populate logs on page load

fix: eliminate API leaks in training loop, set 30k steps for A100

Fix CPU training + 1902ms step speed bottleneck

fix: push reward curve + logs every 10k steps, not just at training end

perf: add encode+step benchmark to logs, validate CUDA speed

perf: force ST to CUDA, disable LLM tasks, reduce to 100k steps

feat: integrate trained RecurrentPPO policy into Streamlit demo UI

fix: force-install CUDA torch in app.py before training starts

fix: remove torch from requirements to preserve pre-installed CUDA torch

fix: install CUDA-enabled torch for GPU spaces

pre-deployment fixes for HF Spaces

Update Cell 1 & 2 with user-verified working versions

Bulletproof Cell 1: check .git dir, rm partial clone, correct REPO path

Fix REPO path: clone root is /content/kuchbhi not /content/kuchbhi/spindleflow-rl

Rewrite train_colab.py: clean cells, fix audioop-lts, log file, reward curve

Remove Colab notebook — using plain .py script instead

Fix Cell 1: skip audioop-lts on Python < 3.13 (Colab uses 3.12)

Add Colab notebook: 8 runnable cells, both secrets, log + curve

Final Colab training script: log file, fixed reward curve, 100k steps

Add HF Hub push cell + fix pip deps in Colab training script

Remove gr.Timer: caused C-level crash with no Python output

Fix logs not showing: use file-based state instead of in-memory globals

Add auto-refresh timer and dark theme CSS

Fix theme/css: keep in Blocks(), not launch()

Improve Gradio UI: fix theme, add CSS, clean up layout

Fix create_repo naming error with huggingface_hub 1.x

Fix gradio/huggingface_hub version conflict on Python 3.13

Add audioop-lts for Python 3.13 pydub fix (cache bust)

Add startup diagnostics

Upgrade to gradio 5 for Python 3.13 compatibility

Fix Python 3.13 audioop: use audioop-lts

Fix Python 3.13 audioop compatibility

Add HF Space configuration to README

SpindleFlow RL — periodic push + log persistence