Update app.py

app.py

@@ -1,3 +1,5 @@
+                    
+                    
 import streamlit as st
 from transformers import pipeline
 import re
@@ -27,6 +29,34 @@ def query_evidence(payload):
 	response = requests.post(API_URL_evidence, headers=headers_evidence, json=payload)
 	return response.json()
 
+#--------------------------------------------------------------------------------------------
+def model_load_qg(answer,claim):
+    FACT_TO_GENERATE_QUESTION_FROM = f"""{answer} [SEP] {claim}"""
+    while True:
+        try:
+            question_ids = query({"inputs":FACT_TO_GENERATE_QUESTION_FROM, 
+                                "num_beams":5, 
+                                "early_stopping":True,
+                                "min_length": 100,
+                                "wait_for_model":True})[0]['generated_text'].capitalize()
+            break
+        except:
+            time.sleep(1)
+    return  question_ids
+                    
+def model_load_qa(question_ids,evidence):                    
+
+    # Wait until the model is loaded
+    while True:
+        try:
+            input_evidence = f"answer_the_next_question_from_context: {question_ids} context: {evidence}"
+            answer_evidence = query_evidence({"inputs":input_evidence,"truncation":True,"wait_for_model":True})[0]['generated_text']
+            break
+        except:
+            time.sleep(1)
+    return answer_evidence   
+
+
 #-----------------------------------------------------------
 st.title('Welcome to :blue[FACTIFY - 5WQA] ') 
 
@@ -363,23 +393,14 @@ def gen_qa_who(df):
         claim=df['claim'][i]
         answer= split_ws(df["who"])
         evidence=df["evidence"][i]
-        time.sleep(5)
         if srl!="":
             try:
                 for j in range(0,len(answer)):
-                    FACT_TO_GENERATE_QUESTION_FROM = f"""{answer[j]} [SEP] {claim}"""
-                    #FACT_TO_GENERATE_QUESTION_FROM = f"""generate_who_based_question_from_context_using_the_next_answer:{answer[j]} [SEP] context:{claim}"""
-                    #time.sleep(10)
-                    question_ids = query({"inputs":FACT_TO_GENERATE_QUESTION_FROM, 
-                              "num_beams":5, 
-                              "early_stopping":True,
-                                         "min_length": 100,"wait_for_model":True})[0]['generated_text'].capitalize()
+                    question_ids = model_load_qg(answer[j],claim)
                     question_ids = rephrase_question_who(question_ids)
                     list_of_ques_who.append(f"""Q{j+1} :\n {question_ids}""")
                     list_of_ans_who.append(f"""Claim :\n {answer[j]}""")
-                    input_evidence = f"answer_the_next_question_from_context: {question_ids} context: {evidence}"
-                    time.sleep(5)
-                    answer_evidence = query_evidence({"inputs":input_evidence,"truncation":True,"wait_for_model":True})[0]['generated_text']
+                    answer_evidence = model_load_qa(question_ids,evidence)
                     if answer_evidence.lower() in evidence.lower():
                         list_of_evidence_answer_who.append(f"""Answer retrieved from evidence :\n {answer_evidence}""")
                     else:
@@ -424,22 +445,14 @@ def gen_qa_what(df):
         claim=df['claim'][i]
         answer= split_ws(df["what"])
         evidence=df["evidence"][i]
-        time.sleep(5)
         if srl!="":
             try:
                 for j in range(0,len(answer)):
-                    FACT_TO_GENERATE_QUESTION_FROM = f"""{answer[j]} [SEP] context:{claim}"""
-                    #time.sleep(10)
-                    question_ids = query({"inputs":FACT_TO_GENERATE_QUESTION_FROM, 
-                              "num_beams":5, 
-                              "early_stopping":True,
-                                         "min_length": 100,"wait_for_model":True})[0]['generated_text'].capitalize()
+                    question_ids = model_load_qg(answer[j],claim)
                     question_ids = rephrase_question_what(question_ids)
                     list_of_ques_what.append(f"""Q{j+1}:{question_ids}""")
                     list_of_ans_what.append(f"""Claim :\n {answer[j]}""")
-                    input_evidence = f"answer_the_next_question_from_context: {question_ids} context: {evidence}"
-                    time.sleep(5)
-                    answer_evidence = query_evidence({"inputs":input_evidence,"truncation":True,"wait_for_model":True})[0]['generated_text']
+                    answer_evidence = model_load_qa(question_ids,evidence)
                     if answer_evidence.lower() in evidence.lower():
                         list_of_evidence_answer_what.append(f"""Answer retrieved from evidence :\n {answer_evidence}""")
                         
@@ -486,22 +499,14 @@ def gen_qa_why(df):
         claim=df['claim'][i]
         answer= split_ws(df["why"])
         evidence=df["evidence"][i]
-        time.sleep(5)
         if srl!="":
             try:
                 for j in range(0,len(answer)):
-                    FACT_TO_GENERATE_QUESTION_FROM = f"""{answer[j]} [SEP] {claim}"""
-                    #time.sleep(10)
-                    question_ids = query({"inputs":FACT_TO_GENERATE_QUESTION_FROM, 
-                              "num_beams":5, 
-                              "early_stopping":True,
-                                         "min_length": 100,"wait_for_model":True})[0]['generated_text'].capitalize()
+                    question_ids = model_load_qg(answer[j],claim)
                     question_ids = rephrase_question_why(question_ids)
                     list_of_ques_why.append(f"""Q{j+1}:{question_ids}""")
                     list_of_ans_why.append(f"""Claim :\n {answer[j]}""")
-                    input_evidence = f"answer_the_next_question_from_context: {question_ids} context: {evidence}"
-                    time.sleep(5)
-                    answer_evidence = query_evidence({"inputs":input_evidence,"truncation":True,"wait_for_model":True})[0]['generated_text']
+                    answer_evidence = model_load_qa(question_ids,evidence)
                     if answer_evidence.lower() in evidence.lower():
                         list_of_evidence_answer_why.append(f"""Answer retrieved from evidence :\n {answer_evidence}""")
                     else:
@@ -547,22 +552,14 @@ def gen_qa_when(df):
         claim=df['claim'][i]
         answer= split_ws(df["when"])
         evidence=df["evidence"][i]
-        time.sleep(5)
         if srl!="":
             try:
                 for j in range(0,len(answer)):
-                    FACT_TO_GENERATE_QUESTION_FROM = f"""{answer[j]} [SEP] {claim}"""
-                    #time.sleep(10)
-                    question_ids = query({"inputs":FACT_TO_GENERATE_QUESTION_FROM, 
-                              "num_beams":5, 
-                              "early_stopping":True,
-                                         "min_length": 100,"wait_for_model":True})[0]['generated_text'].capitalize()
+                    question_ids = model_load_qg(answer[j],claim)
                     question_ids = rephrase_question_when(question_ids)
                     list_of_ques_when.append(f"""Q{j+1}:{question_ids}""")
                     list_of_ans_when.append(f"""Claim :\n {answer[j]}""")
-                    input_evidence = f"answer_the_next_question_from_context: {question_ids} context: {evidence}"
-                    time.sleep(5)
-                    answer_evidence = query_evidence({"inputs":input_evidence,"truncation":True,"wait_for_model":True})[0]['generated_text']
+                    answer_evidence = model_load_qa(question_ids,evidence)
                     if answer_evidence.lower() in evidence.lower():
                         list_of_evidence_answer_when.append(f"""Answer retrieved from evidence :\n {answer_evidence}""")
                     else:
@@ -608,22 +605,14 @@ def gen_qa_where(df):
         claim=df['claim'][i]
         answer= split_ws(df["where"])
         evidence=df["evidence"][i]
-        time.sleep(5)
         if srl!="":
             try:
                 for j in range(0,len(answer)):
-                    FACT_TO_GENERATE_QUESTION_FROM = f"""{answer[j]} [SEP] {claim}"""
-                    time.sleep(10)
-                    question_ids = query({"inputs":FACT_TO_GENERATE_QUESTION_FROM, 
-                              "num_beams":5, 
-                              "early_stopping":True,
-                                         "min_length": 100,"wait_for_model":True})[0]['generated_text'].capitalize()
+                    question_ids = model_load_qg(answer[j],claim)
                     question_ids = rephrase_question_where(question_ids)
                     list_of_ques_where.append(f"""Q{j+1}:{question_ids}""")
                     list_of_ans_where.append(f"""Claim :\n {answer[j]}""")
-                    input_evidence = f"answer_the_next_question_from_context: {question_ids} context: {evidence}"
-                    time.sleep(5)
-                    answer_evidence = query_evidence({"inputs":input_evidence,"truncation":True,"wait_for_model":True})[0]['generated_text']
+                    answer_evidence = model_load_qa(question_ids,evidence)
                     if answer_evidence.lower() in evidence.lower():
                         list_of_evidence_answer_where.append(f"""Answer retrieved from evidence :\n {answer_evidence}""")
                     else:
@@ -650,44 +639,7 @@ def gen_qa_where(df):
 #------------------------------------------------------    
 
 
-#------------------------------------------------------------  
-# if claim_text:
-#     if evidence_text:
-#         df=claim(claim_text)
-#         df["evidence"]=evidence_text
-#         final_df = pd.DataFrame(columns=['Who Claims', 'What Claims', 'When Claims', 'Where Claims', 'Why Claims'])
-
-        
-#         final_df["Who Claims"]=gen_qa_who(df)
-#         final_df["What Claims"]=gen_qa_what(df)
-#         final_df["When Claims"]=gen_qa_when(df)
-#         final_df["Where Claims"]=gen_qa_where(df)
-#         final_df["Why Claims"]=gen_qa_why(df)
-#         st.table(final_df)
-#         st.write(df["claim"])
-#         st.write(df["evidence"])
-#         # st.write(gen_qa_who(df))
-#         # st.table(final_df)
-
-# if claim_text and evidence_text:
-#     st.write("You entered: ", claim_text)
-#     st.write("You entered: ", evidence_text)
-#     st.caption(':green[Kindly hold on for a few minutes while the QA pairs are being generated]')
-#     df=claim(claim_text)
-#     df["evidence"]=evidence_text
-    # final_df = pd.DataFrame(columns=['Who Claims', 'What Claims', 'When Claims', 'Where Claims', 'Why Claims'])
-    # final_df["Who Claims"]=gen_qa_who(df)
-    # final_df["What Claims"]=gen_qa_what(df)
-    # final_df["When Claims"]=gen_qa_when(df)
-    # final_df["Where Claims"]=gen_qa_where(df)
-    # final_df["Why Claims"]=gen_qa_why(df)
-    # st.table(final_df)
-    # st.write(df["claim"])
-    # st.write(df["evidence"])
-
 if claim_text and evidence_text:
-    # st.write("You entered: ", claim_text)
-    # st.write("You entered: ", evidence_text)
     st.caption(':green[Kindly hold on for a few minutes while the QA pairs are being generated]')
     df=claim(claim_text)
     df["evidence"]=evidence_text
@@ -752,7 +704,4 @@ if claim_text and evidence_text:
     final_df['Why Claims'] = output5 + [''] * (max_rows - len(output5))  
     st.write(f"""Claim : {claim_text}""")
     st.write(f"""Evidence : {evidence_text}""")  
-    st.table(final_df)
-    # st.write(df["claim"])
-    # st.write(df["evidence"])    
-
+    st.table(final_df)