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assignment-3c.py

+import random   # library for generating random numbers
+import nltk     # library for working with human language 
+from nltk.tokenize import word_tokenize     # A function from NLTK for breaking words down
+from nltk import ConditionalFreqDist   # A class from NLTK for representing the conditional frequency distribution of a set.
+nltk.download('punkt')      # models used by word_tokenize to tokenize words.
+
+def probs_model(text):  # takes text as input
+    words = word_tokenize(text)  # split words
+    bigrams = list(nltk.bigrams(words))  # pairs of consecutive words
+    cond_freq_dist = ConditionalFreqDist(bigrams)  # conditional frequency of the 2 words
+    return cond_freq_dist
+
+# probs_model is the representation of the conditional probs.
+
+def generate_sentence(model, initial_word, length):  # takes in the representation of the conditional probs, seed word, and sentence length
+    sentence = [initial_word]
+
+#Iterates to generate the next word based on the conditional probabilities until the sentence length is reached.
+    for _ in range(length - 1):
+        next_words = model[sentence[-1]]
+        if not next_words:
+            break  # If there are no next words, end the sentence
+        next_word = random.choice(list(next_words))
+        sentence.append(next_word)
+
+    return ' '.join(sentence) #combine the generated words into a single string
+
+if __name__ == '__main__':
+    input_text = "In the sweet town of Candyland, there lived a marshmallow named Mallow. Mallow had a unique passion ? a love for Alan Turing's work on computers and artificial intelligence. Instead of bouncing with other candies, Mallow spent its days reading Turing's papers and dreaming of marshmallow-powered machines. Mallow's friends couldn't quite understand its fascination, but they embraced Mallow's uniqueness. One day, Mallow surprised everyone by creating a tiny marshmallow computer that could solve candy puzzles. The town marveled at Mallow's ingenuity, and Mallow's love for Turing's work became a source of inspiration for Candyland. And so, Mallow, the marshmallow with a Turing twist, continued to blend sweetness with technology, making Candyland a tastier and smarter place."
+
+    model = probs_model(input_text)
+
+    seed_word = "Alan"  # Select any word as the starting point
+    sentence_length = 15  # desired sentence length
+
+    generated_sentence = generate_sentence(model, seed_word, sentence_length)
+
+    # Print the input text and the generated sentence.
+    print("Input text:", input_text)
+    print(f"Given seed word: '{seed_word}', Generated sentence: {generated_sentence}")