Update app.py
Browse files
app.py
CHANGED
@@ -6,6 +6,7 @@ import re
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import time
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import requests
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from PIL import Image
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HF_SPACES_API_KEY = st.secrets["HF_token"]
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@@ -148,7 +149,7 @@ list_of_pronouns = ["I", "you", "he", "she", "it", "we", "they", "me", "him", "h
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"one", "other", "several", "some", "somebody", "someone", "something"]
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#---------------------------------------------------------------
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# @st.cache
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def
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import re
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def remove_special_chars(text):
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# Remove special characters that are not in between numbers
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@@ -349,21 +350,7 @@ def claim(text):
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pass
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df['where'][j] = "<sep>".join(where)
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data=df[["claim","who","what","why","when","where"]].copy()
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return data
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#-------------------------------------------------------------------------
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# @st.cache
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def split_ws(input_list, delimiter="<sep>"):
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output_list = []
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for item in input_list:
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split_item = item.split(delimiter)
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for sub_item in split_item:
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sub_item = sub_item.strip()
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if sub_item:
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output_list.append(sub_item)
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return output_list
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#--------------------------------------------------------------------------
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# @st.cache
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@@ -372,336 +359,81 @@ def calc_rouge_l_score(list_of_evidence, list_of_ans):
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scores = scorer.score(' '.join(list_of_evidence), ' '.join(list_of_ans))
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return scores['rougeL'].fmeasure
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#-------------------------------------------------------------------------
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else:
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return question
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#------------------------------------------------------------------------
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# @st.cache
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def gen_qa_who(df):
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list_of_ques_who=[]
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list_of_ans_who=[]
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list_of_evidence_answer_who=[]
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rouge_l_scores=[]
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for i,row in df.iterrows():
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srl=df["who"][i]
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claim=df['claim'][i]
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answer= split_ws(df["who"])
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evidence=df["evidence"][i]
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if srl!="":
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try:
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for j in range(0,len(answer)):
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question_ids = model_load_qg(answer[j],claim)
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question_ids = rephrase_question_who(question_ids)
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list_of_ques_who.append(f"""Q{j+1} :\n {question_ids}""")
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list_of_ans_who.append(f"""Claim :\n {answer[j]}""")
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answer_evidence = model_load_qa(question_ids,evidence)
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if answer_evidence.lower() in evidence.lower():
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list_of_evidence_answer_who.append(f"""Answer retrieved from evidence :\n {answer_evidence}""")
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else:
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answer_evidence=""
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list_of_evidence_answer_who.append(f"""No mention of 'who'in any related documents.""")
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threshold = 0.2
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list_of_pairs = [(answer_evidence, answer[j])]
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rouge_l_score = calc_rouge_l_score(answer_evidence, answer[j])
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if rouge_l_score >= threshold:
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verification_status = '✅ Verified Valid'
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elif rouge_l_score == 0:
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verification_status = '❔ Not verifiable'
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else:
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verification_status = '❌ Verified False'
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rouge_l_scores.append(verification_status)
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except:
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pass
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else:
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list_of_ques_who="No claims"
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list_of_ans_who=""
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list_of_evidence_answer_who="No mention of 'who'in any related documents."
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rouge_l_scores="❔ Not verifiable"
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return list_of_ques_who,list_of_ans_who,list_of_evidence_answer_who,rouge_l_scores
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#------------------------------------------------------------
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# @st.cache
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def rephrase_question_what(question):
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if not question.lower().startswith("what"):
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words = question.split()
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words[0] = "What"
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return " ".join(words)
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else:
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return question
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#----------------------------------------------------------
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# @st.cache
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def gen_qa_what(df):
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list_of_ques_what=[]
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list_of_ans_what=[]
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list_of_evidence_answer_what=[]
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rouge_l_scores=[]
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for i,row in df.iterrows():
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srl=df["what"][i]
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claim=df['claim'][i]
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answer= split_ws(df["what"])
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evidence=df["evidence"][i]
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if srl!="":
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try:
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for j in range(0,len(answer)):
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question_ids = model_load_qg(answer[j],claim)
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question_ids = rephrase_question_what(question_ids)
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list_of_ques_what.append(f"""Q{j+1}:{question_ids}""")
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list_of_ans_what.append(f"""Claim :\n {answer[j]}""")
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answer_evidence = model_load_qa(question_ids,evidence)
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if answer_evidence.lower() in evidence.lower():
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list_of_evidence_answer_what.append(f"""Answer retrieved from evidence :\n {answer_evidence}""")
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else:
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answer_evidence=""
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list_of_evidence_answer_what.append(f"""No mention of 'what'in any related documents.""")
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threshold = 0.2
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list_of_pairs = [(answer_evidence, answer[j])]
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rouge_l_score = calc_rouge_l_score(answer_evidence, answer[j])
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if rouge_l_score >= threshold:
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verification_status = '✅ Verified Valid'
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elif rouge_l_score == 0:
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verification_status = '❔ Not verifiable'
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else:
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verification_status = '❌ Verified False'
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rouge_l_scores.append(verification_status)
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except:
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pass
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else:
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if not question.lower().startswith("why"):
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words = question.split()
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words[0] = "Why"
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return " ".join(words)
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else:
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return question
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#---------------------------------------------------------
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# @st.cache
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def gen_qa_why(df):
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list_of_ques_why=[]
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list_of_ans_why=[]
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list_of_evidence_answer_why=[]
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rouge_l_scores=[]
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for i,row in df.iterrows():
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srl=df["why"][i]
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claim=df['claim'][i]
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answer= split_ws(df["why"])
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evidence=df["evidence"][i]
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if srl!="":
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try:
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for j in range(0,len(answer)):
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question_ids = model_load_qg(answer[j],claim)
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question_ids = rephrase_question_why(question_ids)
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list_of_ques_why.append(f"""Q{j+1}:{question_ids}""")
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list_of_ans_why.append(f"""Claim :\n {answer[j]}""")
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answer_evidence = model_load_qa(question_ids,evidence)
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if answer_evidence.lower() in evidence.lower():
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list_of_evidence_answer_why.append(f"""Answer retrieved from evidence :\n {answer_evidence}""")
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else:
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answer_evidence=""
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list_of_evidence_answer_why.append(f"""No mention of 'why'in any related documents.""")
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threshold = 0.2
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list_of_pairs = [(answer_evidence, answer[j])]
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rouge_l_score = calc_rouge_l_score(answer_evidence, answer[j])
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if rouge_l_score >= threshold:
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verification_status = '✅ Verified Valid'
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elif rouge_l_score == 0:
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verification_status = '❔ Not verifiable'
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else:
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verification_status = '❌ Verified False'
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rouge_l_scores.append(verification_status)
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except:
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pass
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else:
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#---------------------------------------------------------
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# @st.cache
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def rephrase_question_when(question):
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if not question.lower().startswith("when"):
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words = question.split()
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words[0] = "When"
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return " ".join(words)
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else:
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return question
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#---------------------------------------------------------
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# @st.cache
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def gen_qa_when(df):
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list_of_ques_when=[]
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list_of_ans_when=[]
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list_of_evidence_answer_when=[]
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rouge_l_scores=[]
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for i,row in df.iterrows():
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srl=df["when"][i]
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claim=df['claim'][i]
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answer= split_ws(df["when"])
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evidence=df["evidence"][i]
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if srl!="":
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try:
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for j in range(0,len(answer)):
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question_ids = model_load_qg(answer[j],claim)
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question_ids = rephrase_question_when(question_ids)
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list_of_ques_when.append(f"""Q{j+1}:{question_ids}""")
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list_of_ans_when.append(f"""Claim :\n {answer[j]}""")
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answer_evidence = model_load_qa(question_ids,evidence)
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if answer_evidence.lower() in evidence.lower():
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list_of_evidence_answer_when.append(f"""Answer retrieved from evidence :\n {answer_evidence}""")
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else:
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answer_evidence=""
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list_of_evidence_answer_when.append(f"""No mention of 'when'in any related documents.""")
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threshold = 0.2
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list_of_pairs = [(answer_evidence, answer[j])]
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rouge_l_score = calc_rouge_l_score(answer_evidence, answer[j])
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if rouge_l_score >= threshold:
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verification_status = '✅ Verified Valid'
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elif rouge_l_score == 0:
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verification_status = '❔ Not verifiable'
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else:
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verification_status = '❌ Verified False'
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rouge_l_scores.append(verification_status)
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except:
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pass
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else:
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list_of_ques_when="No claims"
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list_of_ans_when=""
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list_of_evidence_answer_when="No mention of 'when'in any related documents."
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rouge_l_scores="❔ Not verifiable"
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return list_of_ques_when,list_of_ans_when,list_of_evidence_answer_when,rouge_l_scores
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#------------------------------------------------------
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# @st.cache
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def rephrase_question_where(question):
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if not question.lower().startswith("where"):
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words = question.split()
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words[0] = "Where"
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return " ".join(words)
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else:
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return question
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#------------------------------------------------------
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# @st.cache
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def gen_qa_where(df):
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list_of_ques_where=[]
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list_of_ans_where=[]
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list_of_evidence_answer_where=[]
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rouge_l_scores=[]
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for i,row in df.iterrows():
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srl=df["where"][i]
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claim=df['claim'][i]
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answer= split_ws(df["where"])
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evidence=df["evidence"][i]
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if srl!="":
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try:
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for j in range(0,len(answer)):
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question_ids = model_load_qg(answer[j],claim)
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question_ids = rephrase_question_where(question_ids)
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list_of_ques_where.append(f"""Q{j+1}:{question_ids}""")
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list_of_ans_where.append(f"""Claim :\n {answer[j]}""")
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answer_evidence = model_load_qa(question_ids,evidence)
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if answer_evidence.lower() in evidence.lower():
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list_of_evidence_answer_where.append(f"""Answer retrieved from evidence :\n {answer_evidence}""")
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else:
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answer_evidence=""
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list_of_evidence_answer_where.append(f"""No mention of 'where'in any related documents.""")
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threshold = 0.2
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list_of_pairs = [(answer_evidence, answer[j])]
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rouge_l_score = calc_rouge_l_score(answer_evidence, answer[j])
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if rouge_l_score >= threshold:
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verification_status = '✅ Verified Valid'
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elif rouge_l_score == 0:
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verification_status = '❔ Not verifiable'
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else:
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verification_status = '❌ Verified False'
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rouge_l_scores.append(verification_status)
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except:
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pass
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else:
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list_of_ques_where="No claims"
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list_of_ans_where=""
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list_of_evidence_answer_where="No mention of 'where'in any related documents."
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rouge_l_scores="❔ Not verifiable"
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return list_of_ques_where,list_of_ans_where,list_of_evidence_answer_where,rouge_l_scores
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#------------------------------------------------------
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if claim_text and evidence_text:
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st.caption(':green[Kindly hold on for a few minutes while the QA pairs are being generated]')
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for i in range(len(lst5[0])):
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output5.append(lst5[0][i])
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output5.append(lst5[1][i])
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output5.append(lst5[2][i])
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output5.append(lst5[3][i])
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max_rows = max(len(output1), len(output2), len(output3), len(output4), len(output5))
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final_df = pd.DataFrame(columns=['Who Claims', 'What Claims', 'When Claims', 'Where Claims', 'Why Claims'])
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# add the data to the dataframe
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final_df['Who Claims'] = output1 + [''] * (max_rows - len(output1))
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final_df['What Claims'] = output2 + [''] * (max_rows - len(output2))
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final_df['When Claims'] = output3 + [''] * (max_rows - len(output3))
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final_df['Where Claims'] = output4 + [''] * (max_rows - len(output4))
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final_df['Why Claims'] = output5 + [''] * (max_rows - len(output5))
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st.write(f"""Claim : {claim_text}""")
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st.write(f"""Evidence : {evidence_text}""")
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st.table(final_df)
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import time
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import requests
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from PIL import Image
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import itertools
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HF_SPACES_API_KEY = st.secrets["HF_token"]
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"one", "other", "several", "some", "somebody", "someone", "something"]
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#---------------------------------------------------------------
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# @st.cache
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def srl(text):
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import re
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def remove_special_chars(text):
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# Remove special characters that are not in between numbers
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pass
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df['where'][j] = "<sep>".join(where)
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return who,what,when,where,why
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#--------------------------------------------------------------------------
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# @st.cache
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scores = scorer.score(' '.join(list_of_evidence), ' '.join(list_of_ans))
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return scores['rougeL'].fmeasure
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#-------------------------------------------------------------------------
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def qa_list_gen(claim,srl,evidence):
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list_of_qa_pipeline=[]
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for index,answer_claim in enumerate(combined_list):
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question = model_load_qg(answer_claim,claim)
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answer_evidence = model_load_qa(question,evidence)
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if answer_evidence.lower() in evidence.lower():
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pass
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else:
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+
answer_evidence=""
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+
threshold = 0.2
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+
list_of_pairs = [(answer_evidence, answer_claim)]
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+
rouge_l_score = calc_rouge_l_score(answer_evidence, answer_claim)
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+
if rouge_l_score >= threshold:
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+
verification_status = '✅ Verified Valid'
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+
elif rouge_l_score == 0:
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+
verification_status = '❔ Not verifiable'
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378 |
else:
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379 |
+
verification_status = '❌ Verified False'
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380 |
+
qa_pipeline=[question,answer_claim,answer_evidence,verification_status]
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381 |
+
list_of_qa_pipeline.append(qa_pipeline)
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382 |
+
return list_of_qa_pipeline
|
383 |
+
|
384 |
+
#-------------------------------------------------------------------------
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385 |
|
386 |
+
|
387 |
if claim_text and evidence_text:
|
388 |
st.caption(':green[Kindly hold on for a few minutes while the QA pairs are being generated]')
|
389 |
+
srl_list = list(itertools.chain(*[list(s) for s in srl(claim_text)]))
|
390 |
+
qa_list=qa_list_gen(claim_text,srl_list,evidence)
|
391 |
+
list_who = []
|
392 |
+
list_what = []
|
393 |
+
list_when = []
|
394 |
+
list_where = []
|
395 |
+
list_why = []
|
396 |
+
list_misc = []
|
397 |
+
|
398 |
+
for item in qa_list:
|
399 |
+
question = item[0]
|
400 |
+
if any(x in question.lower() for x in ['who', 'what', 'when', 'where', 'why']):
|
401 |
+
if 'who' in question.lower():
|
402 |
+
list_who.append(item)
|
403 |
+
elif 'what' in question.lower():
|
404 |
+
list_what.append(item)
|
405 |
+
elif 'when' in question.lower():
|
406 |
+
list_when.append(item)
|
407 |
+
elif 'where' in question.lower():
|
408 |
+
list_where.append(item)
|
409 |
+
elif 'why' in question.lower():
|
410 |
+
list_why.append(item)
|
411 |
+
else:
|
412 |
+
list_misc.append(item)
|
413 |
+
lists = [list_who, list_when, list_why, list_where, list_what]
|
414 |
+
|
415 |
+
for i in range(len(lists)):
|
416 |
+
if not lists[i]:
|
417 |
+
lists[i].extend([["No claims", "", f"No mention of '{['who', 'when', 'why', 'where', 'what'][i]}' in any related documents.", "❔ Not verifiable"]])
|
418 |
+
|
419 |
+
final_df = pd.DataFrame(columns=['Who Claims', 'What Claims', 'When Claims', 'Where Claims', 'Why Claims', 'Misc Claims'])
|
420 |
+
|
421 |
+
all_items_who = [item for item_list in list_who for item in item_list]
|
422 |
+
all_items_what = [item for item_list in list_what for item in item_list]
|
423 |
+
all_items_when = [item for item_list in list_when for item in item_list]
|
424 |
+
all_items_where = [item for item_list in list_where for item in item_list]
|
425 |
+
all_items_why = [item for item_list in list_why for item in item_list]
|
426 |
+
all_items_misc = [item for item_list in list_misc for item in item_list]
|
427 |
+
|
428 |
+
|
429 |
+
max_rows = max(len(all_items_who), len(all_items_what), len(all_items_when), len(all_items_where), len(all_items_why), len(all_items_misc))
|
430 |
+
|
431 |
+
final_df['Who Claims'] = all_items_who + [''] * (max_rows - len(all_items_who))
|
432 |
+
final_df['What Claims'] = all_items_what + [''] * (max_rows - len(all_items_what))
|
433 |
+
final_df['When Claims'] = all_items_when + [''] * (max_rows - len(all_items_when))
|
434 |
+
final_df['Where Claims'] = all_items_where + [''] * (max_rows - len(all_items_where))
|
435 |
+
final_df['Why Claims'] = all_items_why + [''] * (max_rows - len(all_items_why))
|
436 |
+
final_df['Misc Claims'] = all_items_misc + [''] * (max_rows - len(all_items_misc))
|
|
|
|
|
|
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|
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|
|
|
|
|
437 |
st.write(f"""Claim : {claim_text}""")
|
438 |
st.write(f"""Evidence : {evidence_text}""")
|
439 |
st.table(final_df)
|