Create app.py

app.py

@@ -0,0 +1,72 @@
+import pandas as pd
+import numpy as np
+import streamlit as st
+
+from transformers import AutoModelForQuestionAnswering, AutoTokenizer, pipeline
+
+model_name = "deepset/roberta-base-squad2"
+
+# a) Get predictions
+nlp = pipeline('question-answering', model=model_name, tokenizer=model_name)
+
+# b) Load model & tokenizer
+model = AutoModelForQuestionAnswering.from_pretrained(model_name)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+
+
+suspicious_words = [
+    "robbery", "crime", "exchange", "extortion", "threat", "suspicious", "fraud", "laundering",
+    "illegal", "contraband", "smuggling", "burglary", "assault", "hijacking", "kidnapping", "ransom",
+    "hostage", "terrorism", "homicide", "murder", "manslaughter", "weapon", "gun", "explosive", "bomb", "knives",
+    "threaten", "blackmail", "intimidate", "menace", "harassment", "stalking", "kidnap", "abduction", "guns", "bombs",
+    "abuse", "trafficking", "prostitution", "pimping", "drug", "narcotic", "cocaine", "heroin", "methamphetamine",
+    "amphetamine", "opiate", "meth", "gang", "gangster", "mafia", "racket", "extort", "embezzle", "corruption",
+    "bribe", "scam", "forgery", "counterfeit", "fraudulent", "cybercrime", "hacker", "phishing", "identity", "theft",
+    "credit card", "fraud", "identity", "fraud", "ponzi", "scheme", "pyramid", "scheme", "money", "scam", "swindle", "deception",
+    "conspiracy", "scheme", "plot", "coercion", "corrupt", "criminal", "felony", "misdemeanor", "felon", "fugitive",
+    "wanted", "arson", "arsonist", "arsony", "stolen", "steal", "loot", "heist", "launder", "hitman", "racketeer",
+    "hijack", "smuggle", "terrorist", "kidnapper", "perpetrator", "ringleader", "prowler", "vigilante", "sabotage",
+    "saboteur", "suicide", "discreet", "hide", "action", "profile", "alert", "vigilant", "clandestine", "riot", "arms", "deal"
+]
+
+
+q = ["","",""]
+a = ["","",""]
+
+
+q[0] = "What event is going to take place?"
+q[1] = "Where is it going to happen"
+q[2] = "What time is it going to happen?"
+
+
+QA_input = [{} for i in range(3)]
+res = [{} for i in range(3)]
+
+
+sentence=st.text_area("Enter your sentence")
+
+for i in range(3):
+  QA_input[i] = {
+    'question': q[i],
+    'context': sentence
+  }
+  res[i] = nlp(QA_input[i])
+  a[i] = res[i]['answer']
+
+a1 = a[0].lower()
+a1s = set(a1.split())
+sus = set(suspicious_words)
+cw = a1s.intersection(sus)
+
+if len(cw) != 0:
+  st.write("The crime detected is: ",a[0])
+  if len(a[1]) != 0:
+    st.write("The location of crime detected is: ",a[1])
+  elif len(a[1]) == 0:
+    st.write("No location detected")
+  if len(a[2]) != 0:
+    st.write("The time of crime detected is: ",a[2])
+  elif len(a[2]) == 0:
+    st.write("No time detected")
+elif len(cw) == 0:
+  st.write("No crime detected")