Add demo

README.md

@@ -1,8 +1,8 @@
 ---
 title: Saved You A Click
-emoji: 🐨
+emoji: 📰🖱️
 colorFrom: pink
-colorTo: red
+colorTo: green
 sdk: gradio
 sdk_version: 3.0.3
 app_file: app.py

app.py

@@ -0,0 +1,56 @@
+from newspaper import Article
+import gradio as gr
+from transformers import pipeline
+
+ta_pipeline = pipeline(model="marksverdhei/unifiedqa-large-reddit-syac")
+ta_pipeline.tokenizer.model_max_length = 2048
+ta_pipeline.model.config.max_length = 300
+
+description = """
+Enter the url for a clickbait article, or the answer and content.
+We will provide the answer to the clickbait title.  
+Disclaimer: the model can generate wrong information. Read more about the model [here](https://huggingface.co/marksverdhei/unifiedqa-large-reddit-syac).
+"""
+
+
+def fetch_article_content(url):
+    article = Article(url)
+    article.download()
+    article.parse()
+    
+    if not (article.title and article.text):
+        raise Exception("Unable to fetch article. Try copy-pasting in the text fields instead.")
+
+    return article.title, article.text
+
+
+def predict(title, body):
+    title = title.lower()
+    body = body.lower()
+    input_text = title + r" \n " + body
+    output = ta_pipeline(input_text, truncation=True)
+    output_text = output[0]["generated_text"]
+    return output_text
+
+
+def predict_from_inputs(url, title, body):
+    if url:
+        title, body = fetch_article_content(url)
+
+    if title and body:
+        return title, predict(title, body)
+    else:
+        raise Exception("You must supply either url or title and body")
+
+
+gr.Interface(
+    fn=predict_from_inputs,
+    inputs=["text", "text", "text"],
+    outputs=[
+        gr.Textbox(label="title"), 
+        gr.Textbox(label="answer")
+    ],
+    
+    title="Saved you a click!", 
+    description=description,
+).launch()

requirements.txt

@@ -0,0 +1,3 @@
+newspaper3k
+gradio
+transformers