Update app.py

app.py

@@ -1,7 +1,59 @@
+import json
 import gradio as gr
+from transformers import AutoModelWithLMHead, AutoTokenizer
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+from transformers import pipeline
 
-def greet(name):
-    return "Hello " + name + "!!"
+tokenizer = AutoTokenizer.from_pretrained("sumedh/t5-base-amazonreviews")
+model = AutoModelForSeq2SeqLM.from_pretrained("sumedh/t5-base-amazonreviews")
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
+
+def summarize_conversation(conversation, slider_value):
+
+    summarizer = pipeline("summarization", model="philschmid/bart-large-cnn-samsum")
+    summarized_conversation = summarizer(conversation.strip(), min_length=int(slider_value))
+
+    return summarized_conversation[0]["summary_text"]
+
+
+def change_textbox(choice):    
+
+    with open('examples.json') as json_file:
+        examples = json.load(json_file)
+
+    if choice == "Customer Dialog AmazonHelp":
+        return gr.update(lines=8, visible=True, value=str(examples["dialog_1"]))
+    elif choice == "Customer Dialog XBoxSupport":
+        return gr.update(lines=8, visible=True, value=str(examples["dialog_2"]))
+    elif choice == "Customer Dialog AppleSupport":
+        return gr.update(lines=8, visible=True, value=str(examples["dialog_3"]))
+    elif choice == "Fridge: Ice maker is not working":
+        return gr.update(lines=8, visible=True, value=str(examples["text_ice_maker_not_working"]))
+    elif choice == "Troubleshooting Iphone":
+        return gr.update(lines=8, visible=True, value=str(examples["text_iphone_troubleshooting"]))
+    else:
+        return gr.update(lines=8, visible=True, value="")
+
+
+with gr.Blocks() as demo:
+    
+    radio = gr.Radio(
+        ["Free Text Input", "Customer Dialog AmazonHelp", "Customer Dialog XBoxSupport", "Customer Dialog AppleSupport", "Fridge: Ice maker is not working", "Troubleshooting Iphone"], label="What should the AI summarize?"
+    )
+    text = gr.Textbox(lines=2, interactive=True, placeholder="Your text here...")
+    output = gr.Textbox(lines=2, interactive=True, placeholder="Your result here...")
+
+    radio.change(fn=change_textbox, inputs=radio, outputs=text)
+    slider_value = gr.Slider(minimum=20, maximum=142, value=42, randomize=False, label="Minimal length of summary.")
+    button_clear = gr.Button("Clear")
+    button_1 = gr.Button("Summarize")
+    
+    button_1.click(fn=summarize_conversation, inputs=[text, slider_value], outputs=output)
+
+    button_clear.click(
+        lambda: [c.update(value=None) for c in [text, output]],
+        inputs=[],
+        outputs=[text, output]
+    )
+
+demo.launch(share=True)