Add app.py, update readme

README.md

@@ -9,5 +9,21 @@ app_file: app.py
 pinned: false
 license: cc-by-4.0
 ---
+# COMPASS Pathways Two-dimensional Sentiment Model
+
+<div align="center">
+
+[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
+[![Pre-commit](https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=white)](https://github.com/compasspathways/Sentiment2D/blob/main/.pre-commit-config.yaml)
+[![License: CC BY 4.0](https://img.shields.io/badge/License-CC_BY_4.0-lightgrey.svg)](https://creativecommons.org/licenses/by/4.0/)
+
+A package for computing the two-dimensional sentiment scores and a Jupyter notebook for replicating the analysis described in the paper "[Psilocybin Therapy for Treatment Resistant Depression: Prediction of Clinical Outcome by Natural Language Processing](https://psyarxiv.com/kh3cx/)".
+
+</div>
+
+
+
+## Citation
+
+Please cite our paper titled "Psilocybin Therapy for Treatment Resistant Depression: Prediction of Clinical Outcome by Natural Language Processing". ([preprint](https://psyarxiv.com/kh3cx/))
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -0,0 +1,30 @@
+import gradio as gr
+import pandas as pd
+from sentiment2d import Sentiment2D
+
+s2d = Sentiment2D()
+
+history = []
+
+FONT_COLOR = '#666666'
+FILL_COLOR = 'rgb(.7,.7,.7)'
+
+def sentiment(text, clear_history):
+    global history
+    valence, arousal = s2d(text)
+    #res = f"{text}: valence={valence:0.3f}, arousal={arousal:0.3f}"
+    res = dict(text=text, valence=valence, arousal=arousal, words=len(text.split()))
+    if clear_history:
+        history = []
+    history.append(res)
+    df = pd.DataFrame(history)
+    res_txt = [f"{r['text']}: valence={r['valence']:0.3f}, arousal={r['arousal']:0.3f}" for r in history]
+    return "\n".join(res_txt), df
+
+iface = gr.Interface(fn=sentiment, 
+                     inputs=[gr.Textbox(lines=1, placeholder="Text for 2d sentiment..."), "checkbox"], 
+                     outputs=["text", 
+                              gr.ScatterPlot(x="valence", y="arousal", tooltip="text", size="words",
+                                             x_lim=[-1.05, 1.05], y_lim=[-1.05, 1.05])])
+iface.launch()
+

requirements.txt

@@ -0,0 +1,2 @@
+git+https://github.com/compasspathways/Sentiment2D
+