Add User_Logs For Group Coursework

app.py

@@ -1,12 +1,17 @@
 import streamlit as st
 
 from emotion_model import emotion_predict
+from pre_processing_data import user_capture
 
 name = st.text_input("Enter your sentence here")
 if (st.button('Submit')):
     result = name.title()
     try:
         result_check = emotion_predict(result)
+        try:
+            user_capture(result, result_check)
+        except Exception as E:
+            print(E)
     except Exception as E:
         result_check = "Error"
         print(E)

pre_processing_data.py

@@ -3,7 +3,9 @@ import spacy
 import nltk
 import pickle
 import subprocess
+import pandas as pd
 
+from datetime import datetime
 from nltk.corpus import stopwords
 from nltk.tokenize import RegexpTokenizer
 from keras_preprocessing.sequence import pad_sequences
@@ -82,3 +84,15 @@ def preprocessing_data(string_text):
     string_output = [w for w in string_output if not w in stop_words]
     string_output = " ".join(string_output)
     return string_output
+
+
+def user_capture(user_input, emotion_predict):
+    dataframe_capture = pd.read_csv('user_logs.csv')
+    user_input_logs = pd.DataFrame({
+        "user_input": [user_input],
+        "emotion_predict": [emotion_predict],
+        "time_logs": [datetime.now()],
+    })
+
+    dataframe_capture = pd.concat([dataframe_capture, user_input_logs], ignore_index=True)
+    dataframe_capture.to_csv("user_logs.csv", index=False)

user_logs.csv

@@ -0,0 +1,7 @@
+user_input,emotion_predict,time_logs
+now you can see me as a manager,"""approval""",2023-05-04 18:57:29.276523
+"I love you so much, babe","""love""",2023-05-04 18:57:46.411772
+"I miss you so much, babe","""sadness""",2023-05-04 18:57:53.579631
+"I likes your dress, babe","""neutral""",2023-05-04 18:58:15.954185
+"I like your dress, babe","""neutral""",2023-05-04 18:58:26.430269
+I dont think this is a good idea,"""gratitude""",2023-05-04 18:58:47.154434