Remove old README content and add deployment script for Hugging Face Spaces

README.md

@@ -1,16 +1,3 @@
-<!---
-title: ReView
-emoji: 📚
-colorFrom: green
-colorTo: blue
-sdk: gradio
-sdk_version: 6.9.0
-app_file: interface/Demo.py
-pinned: true
-license: mit
-short_description: Visualize and analyze scientific peer reviews
---->
-
 This is the repository of ReView: A Tool for Visualizing and Analyzing Scientific Reviews. [Code](https://github.com/sina1138/glimpse-ui) | [Hugging Face Spaces](https://huggingface.co/spaces/Sina1138/ReView)
 <!-- [Paper]() | -->
 

deploy_hf.sh

@@ -0,0 +1,43 @@
+#!/bin/bash
+set -e
+
+# Deploy to HuggingFace Spaces
+# Adds YAML frontmatter to README.md on a temporary branch, pushes, then cleans up.
+
+# Ensure clean working tree
+if ! git diff --quiet || ! git diff --cached --quiet; then
+    echo "Error: Working tree not clean. Commit or stash your changes first."
+    exit 1
+fi
+
+CURRENT_BRANCH=$(git rev-parse --abbrev-ref HEAD)
+
+# Create temporary deploy branch
+git checkout -b _hf_deploy
+
+# Replace README.md with HF Spaces metadata
+cat > README.md << 'EOF'
+---
+title: ReView
+emoji: 📚
+colorFrom: green
+colorTo: blue
+sdk: gradio
+sdk_version: 6.9.0
+app_file: interface/Demo.py
+pinned: true
+license: mit
+short_description: Visualize and analyze scientific peer reviews
+---
+EOF
+
+# Commit and push
+git add README.md
+git commit -m "Add HF Spaces metadata for deployment"
+git push space _hf_deploy:main --force
+
+# Clean up
+git checkout "$CURRENT_BRANCH"
+git branch -D _hf_deploy
+
+echo "Deployed to HF Spaces successfully!"

readme.md

@@ -1,100 +0,0 @@
-This is the repository of ReView: A Tool for Visualizing and Analyzing Scientific Reviews. [Code](https://github.com/sina1138/glimpse-ui) | [Hugging Face Spaces](https://huggingface.co/spaces/Sina1138/ReView)
-<!-- [Paper]() | -->
-
-<!-- ## Cloning this repository
-
-This project uses Git submodules. To clone including all submodules, run:
-```bash
-git clone --recurse-submodules https://github.com/Sina1138/glimpse-ui.git
-```
-If you already cloned without submodules, run:
-```git submodule update --init --recursive``` -->
-
-## Installation
-
-- Since this project was built with Python 3.10, first create the following virtual environment:
-``` bash
-module load miniconda/3
-conda create -n ReView python=3.10
-```
-- Second, activate the environment and install pytorch:
-``` bash
-conda activate ReView 
-```
-
-- In the next step, make sure you have git-lfs package and install git lfs, since it is used in this repo for the preprocessed dataset:
-``` bash
-conda install git-lfs
-git lfs install 
-```
-
-- Finally, all remaining required packages could be installed with the requirements file:
-
-``` bash
-pip install -r requirements.txt
-```
-
-- (Optional) To enable fetching reviews directly from OpenReview links in the Interactive tab:
-``` bash
-pip install openreview-py
-```
-
-## Running Interface Locally
-
-To run this interface locally, first, make sure `gradio` and all the requirements are installed in your environment. Then, you can run the following for a local instance of the interface:
-```bash
-python interface/Demo.py
-```
-
-> **Note:** Do not use `gradio ./interface/Demo.py` (hot-reload mode), as it is currenlty incompatible with the interface's dynamic UI.
-
-Additionally, you can edit the last line of code for a shareable link of your local instance as desired (change `demo.launch(share=False)` to `demo.launch(share=True)`)
-
-## Introduction and Instructions
-
-For an up-to-date, concise, and brief introduction of the interface, you can check out the "Introduction" tab of the ReView app [here](https://huggingface.co/spaces/Sina1138/ReView)
-
-## Data Processing Pipeline
-
-All data processing scripts live in the `pipeline/` directory:
-
-| File | Purpose |
-|------|---------|
-| `pipeline/run_scoring.py` | Unified end-to-end pipeline orchestrator |
-| `pipeline/process_new_data.sh` | Shell entry point (forwards to `run_scoring.py`) |
-| `pipeline/fetch_iclr_data.py` | Fetch reviews from OpenReview API |
-| `pipeline/preprocess_data.py` | Text cleaning and preprocessing |
-| `pipeline/run_glimpse_scoring.py` | GLIMPSE consensuality/agreement scoring |
-| `pipeline/run_polarity_scoring.py` | Polarity/sentiment scoring |
-| `pipeline/run_topic_scoring.py` | Topic/aspect scoring |
-| `pipeline/scored_reviews_builder.py` | Integrate all scores into final dataset |
-| `pipeline/config.py` | Centralized configuration |
-
-The pipeline auto-detects available years from the `data/` directory. To process data for any year:
-
-```bash
-# Fetch data for a new year
-python pipeline/fetch_iclr_data.py --year 2026
-
-# Run the full scoring pipeline (auto-detects all available years)
-./pipeline/process_new_data.sh
-
-# Or run for a specific year
-./pipeline/process_new_data.sh --year 2026
-```
-
-## Performance
-
-Since this project was built for deployment on Hugging Face Spaces, it is optimized to run on CPU. However, if better performance is needed, you can run this interface on a CUDA-enabled device and profit from the improved performance of the models in the interactive page. The code is set up to automatically use CUDA if available.
-
-
-# Information for Hugging Face Spaces
----
-title: ReView
-emoji: 📝
-colorFrom: blue
-colorTo: green
-sdk: gradio
-app_file: interface/Demo.py
-pinned: true
----