Update app.py

app.py

@@ -2,6 +2,13 @@ import gradio as gr
 import pandas as pd
 from retrieval import *
 import os
+from transformers import AutoModelForQuestionAnswering, AutoTokenizer, pipeline
+
+model_name = "deepset/deberta-v3-large-squad2"
+
+# a) Get predictions
+nlp = pipeline('question-answering', model=model_name, tokenizer=model_name)
+
 
 
 hf_writer = gr.HuggingFaceDatasetSaver('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', "Pavankalyan/chitti_data")
@@ -20,7 +27,12 @@ def chitti(query):
             repeated_answers_indices.append(sorted_indices[i])
     for idx in repeated_answers_indices:
         answers_re_table.pop(idx)
-    return [answers_re_table[0],answers_re_table[1]]
+        
+    QA_input = {'question': query,'context': answers_re_table[0]}
+    res1 = str(nlp(QA_input))
+    QA_input = {'question': query,'context': answers_re_table[1]}
+    res2 = str(nlp(QA_input))
+    return [res1,res2]
 
 demo = gr.Interface(
     fn=chitti,