# Contains only NLP zero-shot classification function codes! import sqlite3 from flask import g from transformers import pipeline # Set up zero-shot classification pipeline classifier = pipeline("zero-shot-classification", model="facebook/bart-large-mnli") # The main "breakdown" functionality. Performs NLP using zero-shot! def breakdown(userStory): # The results are stored into a dictionary variable with predifined labels processedStory = classifier(userStory, candidate_labels=["developer", "tester", "project manager", "system admin"]) # Extract labels and scores scores = processedStory['scores'] labels = processedStory['labels'] # As the index of a score is always equal to its associated label, # We only need to index of the score to find correct label. maxScoreIndex = scores.index(max(scores)) # Gets the index of the highest score/accuracy maxLabel = labels[maxScoreIndex] # Gets the associated label name # Return labels return maxLabel # Function to grab all contents in the "Breakdown" table (except for unique ids) # If adding any additional attributes to the table, this has to be updated accordingly def getBreakdownContents(): db = getattr(g, '_database', None) # Gets the _database attribute from the 'g' object. If it does not exist, returns 'None' if db is None: db = g._database = sqlite3.connect('Refineverse.db') # If db is None, create a new connection for db and g._database. cursor = db.cursor() # Creates a cursor object to handle data cursor.execute("SELECT user_story, assignedLabel FROM Breakdown") # The cursor executes the query rows = cursor.fetchall() # Stores the results of fetchall() into a variable return rows # Function to insert a new row into the "Breakdown" table # Using "with" for the connection here seems important, as otherwise it results in an exception def insertBreakdownRow(user_story, assigned_label): with sqlite3.connect('Refineverse.db') as conn: # 'With' will automatically take care of closing and opening the connection cursor = conn.cursor() cursor.execute("INSERT INTO Breakdown (user_story, assignedLabel) VALUES (?, ?)", (user_story, assigned_label)) conn.commit()