Summarizing an article on ChatGPT with Google Cloud Shell can be a challenging task as it requires you to capture all the key information from the article without losing the flow or meaning. In this blog, we’ll guide you through the steps to summarize an article on ChatGPT using Google Cloud Shell.
(How To Summarize An Article With Chat Gpt)
Step 1: Identify the topic and keywords
Firstly, identify the main topic of the article and the keywords related to that topic. The topics may include chatbots, natural language processing, machine learning, etc.
For example, if the article discusses how ChatGPT is used for customer support in industries like healthcare and finance, then the keyword(s) could be healthcare, finance, customer support, chatbot, etc.
Step 2: Preprocess the data
Once you have identified the main topic and keywords, preprocess the data by removing irrelevant information, converting text into lowercase, and handling punctuation marks and special characters.
To prepare the data, you can use Google Cloud Shell’s command-line tool, which allows you to execute Python scripts that extract relevant information from files and databases.
Here’s an example script that uses the following code:
“`
cat article.txt | python process_text.py
“`
In this script, the `article.txt` file contains the content of the article, and the `process_text.py` script takes this input and performs the necessary processing to extract the relevant information.
Step 3: Extract the main topic and keywords
The `process_text.py` script uses the `textcat` command-line tool to read the content of the article and extract its main topic and keywords.
The main topic is extracted using the `docx_to_file()` function provided by the `textcat` command-line tool, which takes the article’s URL as input and outputs the file with the title as the first line.
Similarly, the keywords extracted from the article are also extracted using the same `docx_to_file()` function.
Step 4: Combine the extracted keywords with the preprocessed data
Finally, combine the extracted keywords with the preprocessed data to create a summary. This involves checking each keyword against a list of common themes or keywords associated with chatbots, natural language processing, machine learning. Once you’ve identified the most relevant keywords, concatenate them to form a concise summary of the article.
Here’s an example of how to combine the keywords with the preprocessed data:
“`
# Step 4: Create a summary
summary = []
for word in preprocessed_data:
if word.lower() in “chatbots”:
summary.append(“Natural Language Processing”)
elif word.lower() in “machine learning”:
summary.append(“Machine Learning”)
else:
summary.append(word)
# Print the summary
print(summarization)
“`
In this example, the output is a list of short sentences that summarize the article using the keywords related to chatbots, natural language processing, and machine learning.
(How To Summarize An Article With Chat Gpt)
Overall, summarizing an article using Google Cloud Shell involves identifying the main topic and keywords, preprocessing the data, extracting the main topic and keywords, and combining them with the preprocessed data. By following these steps, you can quickly generate a concise summary of the article without losing its original flow or meaning.
