Ahmed-Elghobashy/Tutorials_booking_app

Tutorials_booking_app

Base URL

• The base URL for the API is http://localhost:3001 unless you configure it differently.

Scoring method

• the score is calculated as follows :
• we only consider tutors who teach the same subject for the same grade.
• if the tutor has slots avaiable in days that will be sufficent for the number of classes gets 10 points
• for each class if the tutor has sufficent slots for the duration and in the prefered time and prefered day gets 15 points
• for each class if the tutor has sufficent slots for the duration prefered day but not in the prefered time and gets 10 points

AI mode and conventional mode

• They both work with the same algorithm the only diffrence is how each one gets the student prefrences.
• The AI mode uses openAI version 4 with the new function calling capbilties which is utilized here to create the studentPrefrences JSON with good acuracy.
• Subjects are enumed to maths,arabic,science .
• The start and end time refer to the start and end of the prefered time in 24h format.

Endpoints

1. Match Tutors

• Endpoint: POST /match
• Description: Matches tutors based on student preferences.
• Request Payload:

  {
    "subject": "maths",
    "grade": 10,
    "classes": [
      {
        "duration": 1,
        "prefTime": [
          { "day": "monday", "slots": [14, 15] },
          { "day": "wednesday", "slots": [16, 17] }
        ]
      },
      // Additional class preferences...
    ]
  }

• Response:

  {
    "matchedTutors": [
      { "tutor": { "name": "John Doe", "subject": "maths", "grades": [10], "availability": [...] }, "fitScore": 75 },
      // Additional matched tutors...
    ]
  }

2. Generate Student Preferences using GPT

• Endpoint: POST /ai
• Description: Uses GPT to generate student preferences based on user input.
• Request Payload:

  {
    "message": "Generate student preferences for a math class."
  }

• Response:

  {
    "matchedTutors": [
      { "tutor": { "name": "Jane Doe", "subject": "maths", "grades": [10], "availability": [...] }, "fitScore": 80 },
      // Additional matched tutors...
    ]
  }

3. Add to Favorites

• Endpoint: POST /addToFav
• Description: Adds a tutor to the student's favorites.
• Request Payload:

  {
    "studentName": "Alice",
    "tutorName": "John Doe",
    "fitScore": 75
  }

• Response:

  {
    "studentName": "Alice",
    "tutorName": "John Doe",
    "fitScore": 75,
    "_id": "5f25d18aa08be327882bf84e",
    "__v": 0
  }

Data Models

Tutor Model

• Represents information about a tutor.

  {
    "name": "John Doe",
    "subject": "maths",
    "grades": [10],
    "availability": [
      { "day": "monday", "slots": [14, 15] },
      { "day": "wednesday", "slots": [16, 17] }
    ]
  }

Student Preferences Model

• Represents student preferences for matching tutors.

  {
    "subject": "maths",
    "grade": 10,
    "classes": [
      {
        "duration": 1,
        "prefTime": [
          { "day": "monday", "slots": [14, 15] },
          { "day": "wednesday", "slots": [16, 17] }
        ]
      }
    ]
  }

Favorite Tutor Model

• Represents a tutor added to a student's favorites.

  {
    "studentName": "Alice",
    "tutorName": "John Doe",
    "fitScore": 75
  }

Errors

• If an error occurs, the API will respond with an appropriate status code and an error message.

Notes

• Make sure to replace the base URL with the actual URL where the API is hosted.
• Always check the API documentation for any updates or changes.

conventional mode

AI mode