Create app.py

app.py

@@ -0,0 +1,49 @@
+import gradio as gr
+import openai
+from transformers import pipeline
+from newspaper import Article
+
+openai.api_key = os.getenv('api_token')
+
+def extract_article_text(url):
+    USER_AGENT = 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10.15; rv:78.0) Gecko/20100101 Firefox/78.0'
+    config = Config()
+    config.browser_user_agent = USER_AGENT
+    config.request_timeout = 10
+
+    article = Article(url, config=config)
+    article.download()
+    article.parse()
+    text = article.text
+    return text
+
+summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
+
+def generate_explanation(concept):
+    model_engine = "text-davinci-003"
+    prompt = f"Explain {concept} to a 10-year old in simple terms."
+    response = openai.Completion.create(engine=model_engine, prompt=prompt, max_tokens=2048)
+    return response.choices[0].text.strip()
+
+def article_or_concept(input_type, article_data,concept_data):
+    if input_type == "Article":
+        summary = summarizer(article_data, max_length=100)
+        explanation = generate_explanation(summary[0]['summary_text'])
+        print (summary)
+        return explanation
+    else:
+        explanation = generate_explanation(concept_data)
+        return explanation
+
+article_url_input = gr.inputs.Textbox(label="Enter article URL:")
+concept_input = gr.inputs.Textbox(label="Enter a concept:")
+
+input_type = gr.inputs.Dropdown(choices=["Article", "Concept"], label="Select input type:")
+
+output_text = gr.outputs.Textbox(label="Explanation:")
+
+interface = gr.Interface(fn=article_or_concept, inputs=[input_type, article_url_input, concept_input], outputs=output_text, title="Machine Learning Granny",
+  theme = 'huggingface',
+  description="Input either a ML article URL or a concept to receive an explanation that even a grandmother can understand.")
+
+interface.launch(debug=True)