Create app.py

app.py

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+
+import gradio as gr
+from summarizer import TransformerSummarizer, Summarizer
+
+title = "Summarizer"
+description = """
+This is a demo of a text summarization NN - based on GPT-2, XLNet, BERT, 
+works with English (and a few other languages too, these are SOTA NN after all).
+"""
+
+NN_OPTIONS_LIST = ["mean", "max", "min", "median"]
+NN_LIST = ["GPT-2", "XLNet", "BERT"]
+
+
+def start_fn(article_input: str, reduce_option="mean", model_type='GPT-2') -> str:
+    """
+    GPT-2 based solution, input full text, output summarized text
+    :param model_type:
+    :param reduce_option:
+    :param article_input:
+    :return summarized article_output:
+    """
+    if model_type == "GPT-2":
+        GPT2_model = TransformerSummarizer(transformer_type="GPT2", transformer_model_key="gpt2-medium",
+                                           reduce_option=reduce_option)
+        full = ''.join(GPT2_model(article_input, min_length=60))
+        return full
+    elif model_type == "XLNet":
+        XLNet_model = TransformerSummarizer(transformer_type="XLNet", transformer_model_key="xlnet-base-cased",
+                                            reduce_option=reduce_option)
+        full = ''.join(XLNet_model(article_input, min_length=60))
+        return full
+
+    elif model_type == "BERT":
+        BERT_model = Summarizer(reduce_option=reduce_option)
+        full = ''.join(BERT_model(article_input, min_length=60))
+        return full
+
+
+face = gr.Interface(fn=start_fn,
+                    inputs=[gr.inputs.Textbox(lines=2, placeholder="Paste article here.", label='Input Article'),
+                            gr.inputs.Dropdown(NN_OPTIONS_LIST, label="Summarize mode"),
+                            gr.inputs.Dropdown(NN_LIST, label="Selected NN")],
+                    outputs=gr.inputs.Textbox(lines=2, placeholder="Summarized article here.", label='Summarized '
+                                                                                                     'Article'),
+                    title=title,
+                    description=description, )
+face.launch(server_name="0.0.0.0", share=True