# !pip uninstall -y transformers
# !pip install transformers==4.49.0

from transformers import pipeline

summarizer = pipeline(
    "summarization",
    model="facebook/bart-large-cnn"
)

def summarize_text(text):

    summary = summarizer(
        text,
        max_length=150,
        min_length=50,
        do_sample=False
    )

    return summary[0]['summary_text']


text = """
Natural language processing (NLP) is a field of artificial intelligence
that focuses on the interaction between computers and humans through
natural language. The ultimate goal of NLP is to enable computers to
understand, interpret, and generate human language in a way that is
valuable. NLP techniques are used in many applications, such as speech
recognition, sentiment analysis, machine translation, and chatbot
functionality. Machine learning algorithms play a significant role in
NLP, as they help computers to learn from vast amounts of language data
and improve their ability to process and generate text.

However, NLP still faces many challenges, such as handling ambiguity,
understanding context, and processing complex linguistic structures.
Advances in NLP have been driven by deep learning models, such as
transformers, which have significantly improved the performance of many
NLP tasks.
"""

summarized_text = summarize_text(text)

print("Original Text:\n")
print(text)

print("\nSummarized Text:\n")
print(summarized_text)