garvitsachdeva/SpindleFlow-RL
fix: remove root app.py — HF defaults to app.py over app_file setting
fix: downgrade sdk_version 1.44.0→1.40.0 — HF health check compatibility
diag: minimal 5-line app + disable usage stats — isolate Starting issue
fix: cache_resource warm-up — spinner flushes before heavy imports block
diag: print checkpoints + visible loading banner; expose errors to stderr
fix: call set_page_config before heavy imports; patch duplicate call
fix: use exec() wrapper — eliminates double set_page_config crash
fix: set_page_config before heavy import; cache_resource spinner; no-op patch
fix: importlib wrapper with correct __file__; remove garbage files
diag: wrap module-level imports to surface crash error
fix: move streamlit_app.py to root; fix sys.path for new location
fix: use app.py as Streamlit entry point (HF default)
diag: minimal test to confirm Space runs our file
fix: add openenv back; catch BaseException to surface crash cause
blog added
fix: use importlib to load demo app + streamlit config.toml
fix: catch startup errors and display them instead of crash-looping
fix: use exec() to run demo app with correct __file__ context
fix: add root streamlit_app.py entry point; HF was running default demo
feat: add Training Space link to Training tab; fix Space URL in app.py
deploy: Streamlit Space setup + button-triggered training
final commits
fix: quality demo
trained evironment UI fixes
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
