Practicum: Earn a Certificate for building an AI-powered Search Engine

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Programming Challenge

The reference script is found on llm-tutorial-series. Download the script named ai-search-engine.py.

Use code snippets provided in the course material:

• Build Search Engines in the Age of AI on Sectors Bulletin

You need to complete either Exercise 1 or Exercise 2 successfully.
Find the following markers in the provided ai-search-engine.py.:

# Challenge (1) or (2)

You can do both Challenges, but only the one with the best score is taken. Modify the code to work in Google Colab notebook, and submit only a link to your Google Colab notebook. Ensure all cells are successfully executed.

For Exercise 1:

• Check out the Challenge (1) in match_input_to_valid_subsector_slug. Complete this function such that this function can be used completely functionally. Demonstrate that it works in your Colab notebook.

# assuming valid_subsector_slugs exists.
match_input_to_valid_subsector_slug(valid_subsector_slugs, user_input, 80)

For Exercise 2:

• Check out the Challenge (2) in the main function. Right now the script executes ticker search (company's stock symbol, 4-character long) but not sector search. Modify this to allow for sector search, such that:

chat("bmri") -> returns complete information on bmri, including its last closing price 
chat("banks") -> returns complete information on the banking sectors

If you're residing in Singapore / Malaysia, you are allowed to adapt the question to use financial stock data from Bursa Malaysia / Singapore Exchange pulled from Sectors Financial API (read the documentation).

Completing either (1) or (2) will earn you a Passing grade.

You can discuss, and ask for help in Discord, but please do not share your answers or plagiarize. You are only cheating yourself off an education.

Submission Format

To submit your completed exercise, open a new Discussion under 'Practicum: Generative AI', and paste a link to the completed work. This should be a Google Colab notebook. The output of each cell must be shown, whether they are intermediary steps or not. Make sure to 'Run All' from top to bottom before saving your work.

Specify your name and first 4 letters of your email at the top of your notebook for me to identify you.
Example: Samuel Chan | samu (if my email is indeed [email protected])

🔴 IMPORTANT: DO NOT SHARE YOUR SECRETS. USE from google.colab import userdata to read your environment variables. Under no circumstance should you secret keys be ever visible. An inclusion of your key in the notebook will automatically disqualify your work, and for your own benefit, I will promptly remove your thread here on GitHub so that your keys are not stolen.

Alternative Passing Criteria

Not all participants of this workshop are of a technical background, and are able to write Python code at this level yet. To be more accomodating of beginners and non-technical participants, I have prepared an alternative challenge for you.

I will still need you to demonstrate that you have learned the concepts as intended by the workshop, so I will ask you to write either a short paragraph of your key takeaways or provide 4 - 5 bullet points summarizing your learnings or insights from the workshop.

Challenge (3):

Write up 4 - 5 bullet points on your key takeaways from this Search Engine in the Age of AI workshop.
You can include your thoughts on any key points, or any insight that you found particularly interesting.

Tag Supertype or myself (if on LinkedIn) or @sectorsapp (if on Instagram) in your post so that I am alerted to it and can review your submission.