feat: persist user comments per video with author and source filters

fix: drop the removed hf extra from the Dockerfile install step

feat: prepare project for Hugging Face Spaces deploy

feat: sign posted comments with a random team member

feat: localise Hub Settings and ModelBanner

feat: localise the Watch flow and stop the player from auto-playing

feat: rebuild Layout with collapsible sidebar topbar toggles and Supabase link

feat: add hand-drawn SVG icon set

chore: trim transparent padding around the SignalMod logo

feat: restyle the app with a hand-drawn sketchy aesthetic

feat: add theme context with light and dark modes

feat: add i18n context with es and en dictionaries

docs: rewrite readmes with logo description architecture and language toggle

feat: add makefile shortcuts and pnpm lockfile for faster onboarding

feat: prepare project for render free tier deployment

feat: replace youtube_hate_detector text with signalmod logo and favicon

feat: add comment composer recent activity feed and random usernames

feat: fetch 50 newest youtube comments per video sorted by time

feat: persist every prediction in supabase and expose history endpoint

feat: consolidate transformer deps as required and add supabase client

chore: add hate detector model and metrics report

feat: implement new models and improve UI, #23

fix: debug model selection, #22

feat: update UI using VITE+React without streamlit, #22

feat: update UI using VITE+React without streamlit, #22

docs: add technical reports, #16

docs: documentation, #15

fix: modify evaluation pipeline, #7

chore: update .gitignore

feat: dockerize application, #14

chore: add files on .gitignore

feat: implement unit tests, #13

Merge pull request #20 from Bootcamp-IA-P6/v2

test isolated pipeline outputs and evaluator summary append

backup stable api and model service before pipeline testing

Merge pull request #18 from Bootcamp-IA-P6/v2

feat: add streamlit base. #12

clean lfs history

feat: add new structure for augmentation. #6

feat:add new model transformers. #17

feat: add data augmentation and new optuna tuning. #6 , #9

feat: add new gap for rubric. #6

feat: add ensemble and optuna. #5 #6 #9

fix: Try new values for c=0.1 and c=0.4. #5

fix: new c=0.1 for training baseline and add custom_stopwords. #5

feat: add baseline notebook with overfitting. #5

feat: add vectorization notebook. #4

fix: change the name of the experiment. #3

feat: add preprocessing, new version. #3

feat: add preprocessing. #3