BACKEND STYLOMATE DOCUMENTATION

Arsitektur Code

Dalam Arsitektur yang dibangun untuk membangun sebuah backend aplikasi stylomate menggunakan MVC (Model View Controller), dengan pendekatan clean code arsitektur dan juga monolitic berikut adalah code bagian backend dari aplikasi staylo mate:

- config
- controller
- repository
- service
- model
- router
main.py
.env

Instalation and Implementation

Hal yang perlu dilakukan untuk menjalankan code ini pastikan instalasi python di laptop atau komputer anda. berikut adalah langkah pertama:

git clone https://github.com/codename-error/stylomate-be.git

Selanjutnya ke dalam direktory yang sudah di tentukan

cd stylemate-be

selanjutnya adalah melakukan instalasi package

pip install -t requirements.txt

selanjutnya adalah menjalankan dengan menjalankan berikut di terminal anda:

uvicorn main:app --reload

setelah berhasil maka port default dari project ini adalah 8000

Enpoint RestAPI

URI = http://localhost:8000/

diikuti dengan Enpoint setelahnya, contoh = http://localhost:8000/v2/login

Login

End Poin : /v2/login

Methode : POST

Request:

{
  "email": "string",
  "password": "string"
}

Response:

• 200 → OK

{
  "message": "User registered successfully",
  "user": {
    "user": "",
    "access_token": ""
    "token_type": "bearer"
  }
}

• 500 → Internal Server Error

Register

Endpoint: /v2/register

Methode : POST

request Body:

{
  "username": "string",
  "email": "string",
  "password": "string",
  "validate_password": "string",
  "profile_picture": "string",
  "preference": [
    "string"
  ],
  "image_model": "string"
}

response Body:

• 200 → OK

{
  "message": "User registered successfully",
  "user": {
    "user": "",
    "access_token": ""
    "token_type": "bearer"
  }
}

• 500 → Internal Server Error

Preference

Endpoint: /v2/user/preference

Methode: PUT

request Body:

{
  "username": "string",
  "profile_picture": "string",
  "preference": [
    "string"
  ],
  "image_model": "string"
}

response Body:

• 201 → Created
• 400 → internal server error

Image Model

Endpoint : /v2/user/image_model

Methode: PUT

request_body:

from-data
file *string($binary)

Response Body:

• 201 Created
• 400 Not Found

Wardrobe

1. Get wardrobe

 End point: /wardrobe

method: GET

Response:

{    "message": "Succesfult Get Wardrobe item",    
	"data": [
		{"type": "T-Shirt",
		"length": "Hip",
		"id": 1,
		"category": "Top",
		"image_url":base64,
		"color": "White",           
		"pattern": "Plain"}
]
}

2. Update Wardrobe

method: PUT

params:

/id → wardobe/1

body:

class UpdateClothesModel(BaseModel):
type: Optional[str] = None
category: Optional[str] = None
color: Optional[str] = None
pattern: Optional[str] = None
length: Optional[str] = None
image_base64: Optional[str] = None

Response: 202 → No Conten

3. Delete Wardrobe

 methode: DELETE

params:

/id → wardobe/1

Response:

202 → No Content

4. Create Clothes

 methode: POST

body:

multipart/form data: file image (jpg/png)

response:

201 → created

Style Me

1. Recomendation

 Endpoint : /v2/recomendation

Methode: POST

Request Body:

{
  "id": 0,
  "kondisi": "string",
  "activity": "string"
}

Response:

• 200 → OK
• 400 → Not Found

2. Styleme for category

 Endpoint : /v2/styleme/category

Methode : GET

Request Body:

{
  "category": "string"
}

input = ["Top"/ "Bottom"]

Response Body:

• 200 → Oke
• 500 → Internal Server Error

3. Style Me random

 Endpoint : /v2/styleme/random

Methode: GET

Request Body:

{
  "cari": "string"
}

input = ["Top" / "Bottom" / "None"]

Response Body:

• 200 → Ok
• 500 → Internal Server error

4. Get Item Style By Id

 Endpoint : /v2/styleme/{id}

Methode: GET

Parameters:

id = ....(int)

Response Body

• 200 → Ok
• 500 → Internal Server Error

Stylo Ai

1. Upload Link

 Endpoint : /v2/url

Methode: GET

Request Body:

Form Data 

Response Body:

• 200 → OK
• 500 → Internal Server Error

2. Get Wardrobe

  Endpoint : /v2/stylo/wardrobe

Methode: GET

response Body:

{    "message": "Succesfult Get Wardrobe item",    
	"data": [
		{"type": "T-Shirt",
		"length": "Hip",
		"id": 1,
		"category": "Top",
		"image_url":base64,
		"color": "White",           
		"pattern": "Plain"}
]
}

3. Generate AI

 Endpoint: /v2/styloai

Methode: POST

Request Body:

{
	"image": base64,
	"image": base64
}

response Body:

hasilnya image