Starter Flask App - OpenAI Example

This repo is a starter flask app for teaching purposes.

This particular variant was made to demonstrate how to use flask with the OpenAI.

For a more basic introduction, see Starter Flask App.

How to Clone This Repo

1. If you haven't already, set up git.
2. Click the green "Code" button in the top right corner of this page.
3. Copy the URL in the dropdown.
4. Open your terminal and navigate to the directory where you want to clone this repo.
5. Run the following command:

   git clone <URL>

   

How to Run the Flask App Locally

1. If you don't already, install python and pip. If you're not sure if you have python installed, try running it locally in your command line with python --version.

2. Navigate to the directory where you cloned this repo.

3. Run the following command to install the required packages:

   pip install -r requirements.txt

4. Get an (OpenAI API Key)[https://openai.com/index/openai-api/] and set it to the environment variable OPENAI_API_KEY.

   OPENAI_API_KEY="sk-..."

5. Run the following command to start the flask app defined in the app.py file:

   flask run

   

6. Open your browser and navigate to http://127.0.0.1:5000 to see the app running locally.

How This App Works

This app is a minimal server/client web application that template rendering, form submission, a database, and OpenAI to collect and summarize feedback from students.

It has two entry points:

• /
• /summarize_feedback

Below is a sequence diagram explaining how it works with two students feedback, Alice and Bobs.

sequenceDiagram
   autonumber
    participant Alice
    participant Bob
    participant MrP as Mr. P
    participant Server
    participant Database
    participant OpenAI as OpenAI LLM

    Alice->>Server: GET /
    Server->>Alice: index.html
    Alice->>Server: POST "Alice's Feedback" to /feedback
    Server->>Database: INSERT "Alice's Feedback" ...
    Server->>Alice: thanks.html

    Bob->>Server: GET /
    Server->>Bob: index.html
    Bob->>Server: POST "Bob's Feedback" to /feedback
    Server->>Database: INSERT "Bob's Feedback" ...
    Server->>Bob: thanks.html

    MrP->>Server: Get /summarize_feedback
    Database->>Server: SELECT feedback ...
    Server->>OpenAI: "Summarize feedback ..."
    OpenAI->>Server: "The summary is.."
    Server->>MrP: summary.html, "The summary is..."

Loading

Steps

1. Alice navigates her web browser to the root web page, this is a GET request to the / URL (the root).
2. The server returns index.html, a page to fill out her feedback.
3. Alice fills out the form and clicks "Submit", this forms a POST request with her feedback to the /feedback URL.
4. The server inserts Alice's feedback into the database.
5. The server returns the thanks.html page to Alice
6. Bob navigates his web browser to the root web page, this is a GET request to the / URL (the root).
7. The server returns index.html, a page to fill out his feedback.
8. Bob fills out the form and clicks "Submit", this forms a POST request with his feedback to the /feedback URL.
9. The server inserts Bob's feedback into the database.
10. The server returns the thanks.html page to Bob
11. Mr. P navigates his web browser to the /summarize_feedback URL
12. The server fetches all feedback (Alice and Bob's) from the database
13. The server uses the OpenAI client to make a request to OpenAI's LLM promt-engineering it to summarize the feedback.
14. The OpenAI LLM generates a summary and returns it to the server.
15. The Server renders the summarize.html template with the summary inside it and returns it to Mr. P