Update app.py

app.py

@@ -1,17 +1,32 @@
 import gradio as gr
-from transformers import pipeline
+import torch
+from transformers import AutoTokenizer, RobertaForQuestionAnswering
 
-analyzer = pipeline("sentiment-analysis")
+tokenizer = AutoTokenizer.from_pretrained("tsmatz/roberta_qa_japanese")
+model = RobertaForQuestionAnswering.from_pretrained("tsmatz/roberta_qa_japanese")
 
+def answer(text, question):
+  inputs = tokenizer(question, text, add_special_tokens=True, return_tensors="pt")
+  input_ids = inputs["input_ids"].tolist()[0]
 
-def greet(name):
-    #return "Hello " + name
-    return (analyzer(name))
+  outputs = model(**inputs)
+  answer_start_scores = outputs.start_logits
+  answer_end_scores = outputs.end_logits
 
+  answer_start = torch.argmax(answer_start_scores)
+  answer_end = torch.argmax(answer_end_scores) + 1
 
-# We instantiate the Textbox class
-textbox = gr.Textbox(label="Please fill in something words:",placeholder="happy", lines=2)
+  answer = tokenizer.convert_tokens_to_string(
+      tokenizer.convert_ids_to_tokens(input_ids[answer_start:answer_end])
+  )
 
-#textbox = gr.Textbox(label="Type your name here:", placeholder="John Doe", lines=2)
+  return answer
 
-gr.Interface(fn=greet, inputs=textbox, outputs="text").launch(share=True)
+gr.Interface(
+    answer,
+    [
+        gr.Textbox(label="Text:", placeholder="Text...", lines=5),
+        gr.Textbox(label="Question:", placeholder="Question...", lines=1)
+    ],
+    "text",
+).launch()