RithikaChalam commited on
Commit
9aa1428
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verified ·
1 Parent(s): 210c56c

link to mom_phrases.txt

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Files changed (1) hide show
  1. app.py +4 -4
app.py CHANGED
@@ -7,12 +7,12 @@ import torch
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  # STEP 2 FROM SEMANTIC SEARCH
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  # Open the water_cycle.txt file in read mode with UTF-8 encoding
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- with open("scholar_bot_knowledge.txt", "r", encoding="utf-8") as file:
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  # Read the entire contents of the file and store it in a variable
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- scholar_bot_text = file.read()
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  # Print the text below
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- print(scholar_bot_text)
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  # STEP 3 FROM SEMANTIC SEARCH
@@ -43,7 +43,7 @@ def preprocess_text(text):
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  return cleaned_chunks
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  # Call the preprocess_text function and store the result in a cleaned_chunks variable
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- cleaned_chunks = preprocess_text(scholar_bot_text) # Complete this line
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  #STEP 4 FROM SEMANTIC SEARCH
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  # Load the pre-trained embedding model that converts text to vectors
 
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  # STEP 2 FROM SEMANTIC SEARCH
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  # Open the water_cycle.txt file in read mode with UTF-8 encoding
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+ with open("mom_phrases.txt", "r", encoding="utf-8") as file:
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  # Read the entire contents of the file and store it in a variable
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+ phrases_text = file.read()
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  # Print the text below
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+ print(phrases_text)
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  # STEP 3 FROM SEMANTIC SEARCH
 
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  return cleaned_chunks
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  # Call the preprocess_text function and store the result in a cleaned_chunks variable
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+ cleaned_chunks = preprocess_text(phrases_text) # Complete this line
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  #STEP 4 FROM SEMANTIC SEARCH
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  # Load the pre-trained embedding model that converts text to vectors