The Last Show

In this assignment, you will create a full stack application with React and AWS that generates obituaries for people (fictional or otherwise). You will use ChatGPT to generate an obituary, Amazon Polly to turn the obituary into speech, and Cloudinary to store the speech and a picture of the deceased (may they rest in peace).

Architecture Overview

🦶 Steps

Make sure to see the demo video on D2L
Clone the repo
Make sure you're inside the root directory of the repo and then run npm install to install all the necessary packages
Run npm start and you should be able to see the page open up on your default browser
Add your infrastructure code in the main.tf file
Add your function code for the get-obituaries-<your-ucid> function in the functions/get-obituaries/main.py file
Add your function code for the create-obituary-<your-ucid> function in the functions/create-obituary/main.py file
Push your changes to the main branch before the deadline to be graded
This assignment has a DEMO component that's 50% of the grade

📃 Notes

You must create all your resources on AWS with Terraform. Put all your configuration in the main.tf file
You must use AWS DynamoDB for the database
You must use Lambda Function URLs for this assignment to connect your backend to the frontend
You must create 2 Lambda functions for this assignment:
- get-obituaries-<your-ucid>: to retrieve all the obituaries. Function URL only allows GET requests
- create-obituary-<your-ucid>: to create a new obituary. The function reads all the data (including the picture) from the body of the request. Function URL only allows POST requests
You must use Python to write the functions
The only external libraries allowed to be used in the functions are requests for sending HTTPS requests to ChatGPT and Cloudinary, and requests-toolbelt for decoding the body of the request received from the front-end. No other external libraries are allowed
You must use the Cloudinary Upload API and not the SDK to interact with Cloudinary. You will need to generate a signature for your requests. See how you can do it here
You must use the ChatGPT API and not the SDK to interact with ChatGPT
To interact with Cloudinary and ChatGPT, you need keys. You must use AWS Systems Manager Parameter Store and the SecureString data type to store the keys for your Cloudinary and ChatGPT accounts. The create-obituary Lambda function will read the keys from the Parameter Store using the boto3 library. The keys must not be present in your application or infra code in the repo. You can create these keys using the AWS CLI, or manually on the AWS Console. Read more about the AWS Systems Manager API here. Depending on your solution, you need one of these two methods: get_parameters or get_parameters_by_path. The Demo uses the last one
You must use Amazon Polly to turn the obituary written by ChatGPT to speech and then upload the mp3 version of that to Cloudinary. Read more about the Polly API here. What you need is the synthesize_speech method
The Demo uses the text-curie-001 model from ChatGPT. Feel free to use another model. Be careful about the cost of the model you choose!
The Demo sets the max_tokens to 600. However, you could change this number as long as it still works properly. You don't have to go over 600. Bigger numbers are more expensive!
The Demo uses the Completions API and not the Chat API, as the application doesn't need to have a continuous discussion with the model. This makes the application less expensive. However, feel free to use the Chat API instead
The Demo uses the following prompt to interact with the model: write an obituary about a fictional character named {name} who was born on {born_year} and died on {died_year}. You may use a different prompt as long as it still works
The Demo uses FlexBox for the layout. However, feel free to use another approach or framework
The Demo uses Joanna as the voice id for the speech. Feel free to use another voice id
The Demo uses the e_art:zorro enhancement from Cloudinary to create black edges for the picture. Read more here. You only need to add e_art:zorro in a certain part of the image URL
You probably need to set a bigger timeout for your Lambda function, as it takes ChatGPT a few seconds to generate an obituary. The default timeout is 3 seconds. You can set the timeout to 20
The Demo uses a font from the Google Fonts library named Satisfy to show the obituaries on the front-end,
The Demo doesn't use any external library for the front-end
In order to get the full mark, you need to DEMO your work in PERSON. You could either demo it to a TA or the instructor. Demo is 50% of the assignment

👫 Group Assignment

In case you're doing the assignment as part of a group, pay attention to the following so you won't lose any points:

Use the UCID of one team member to name the Lambdas, and the other one to name the DynamoDB table
Put the names and UCIDs of the team members in the Team-Members file
Both members must commit to the group repo. If a student has no commit after the deadline, their grade will be Zero. Things like "I sent the code over TikTok or Discord" are not acceptable. No commmit = No grade
Try to split the work as evenly as possible between team members
Both members must be present for the Demo. If you're not present, your grade will be Zero for the Demo

✔️ Things you may change

You may use a CSS framework to build the UI. The Demo only uses FlexBox
You may use a different voice id with Amazon Polly. The Demo uses Joanna
You may use a different model for your ChatGPT integration. The Demo uses text-curie-001
You may use a different prompt for the model as long as the final result is the same. The Demo uses write an obituary about a fictional character named {name} who was born on {born_year} and died on {died_year}.
You may use a different font. The Demo uses Satisfy

💰 Cost

This assignment won't cost you anything if you follow the best practices discussed in the class
Use the PROVISIONED billing mode, and only 1 RCU and WCU for your DynamoDB table as shown in the lecture notes
Don't use a memory configuration bigger than 128MB for your Lambdas. Use the lecture notes to create Lambda functions. When you don't specify the memory_size field, it will default to 128MB which is the minimum amount
Don't send a huge number of requests to your Lambdas using automated scripts. You have 1 Million free requests, and up to 3.2 million seconds of free compute time under the Free Tier
Remember to enable Free Tier notifications on your account before building anything as shown in the videos on D2L
If you go over the Free Tier (you would have to screw it up really bad, honestly), you can create a new Free AWS account and build your infrastructure there instead. Thankfully, Terraform makes that process super easy for you
Cloudinary has a generous free tier. If you don't send thousands of requests for large files, you won't have to pay anything. If you're over the free tier, you could create a new free account (will give you new keys)
ChatGPT has a free tier. If you're careful, you won't have to pay anything. If you're over the free tier, you could create a new free account (will give you new API Key)

➕ Bonus Marks

You can grab 10 extra points if you orchestrate different steps of the create-obituary Lambda function with AWS Step Functions. You would have to orchestrate 4 Lambda functions:
- generate-obituary that uses ChatGPT
- read-obituary that uses Amazon Polly
- store-files that uses Cloudinary to store both the picture and speech
- save-item that uses DynamoDB to store a new item
You must create all the infra using Terraform
Step Functions won't send you a response right away, but the app still needs to find out when the workflow is finished and add a new obituary to the front-end
No partial implementation is considered. If the implementation doesn't work properly from beginning to end, there will be no bonus marks for the assignment

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