putuwaw/mammates-model-serving

By putuwaw

•Updated almost 3 years ago

Serving Services for All ML Model

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putuwaw/mammates-model-serving repository overview

⁠ml-model-serving

Serving Services for All ML Model using FastAPI and Docker.

⁠ML Model 🤖

Here is the list of ML Model that we use in this project:

⁠Features 💡

Using ML Model Serving, you can:

Get prediction from our ML model for predicting food category, rating, and price.
Get food recommendation from our ML model by given user_id.
Get status and metadata from our ML model.

⁠Prerequisites 📋

Python⁠ 3.10 or higher
FastAPI⁠ 0.104.1 or higher
Docker⁠ 24.0.7 or higher
Docker Compose⁠ 2.15.1 or higher

⁠Usage ✨

Actually, if you already have Docker and Docker Compose, you just need the compose.yml⁠ file.

You can run this app with Docker Compose.

docker compose up

Now, you can access the app on http://localhost:8080⁠
For doing prediction or get food recommendation, please read the API Endpoints⁠ section.

⁠Development 💻

If you want to develop the model serving, you can follow this step:

Clone the repository:

git clone https://github.com/MamMates/ml-model-serving.git

Create and activate virtual environment:

python -m venv venv
source venv/bin/activate

Install dependencies:

pip install -r requirements.txt

To develop the FastAPI services, you can modify the compose.yml file, change the image in app services to build:

- image: putuwaw/mammates-model-serving
+ build: .

Run the app:

docker compose up --build

Now, you can access the app on http://localhost:8080⁠
You can also run the test using pytest:

pytest

⁠API Endpoints 📡

List of available endpoints:

⁠GET

GET / - Get hello world.

Response

{
  "status": true,
  "code": 200,
  "message": "OK",
  "data": {
    "message": "Hello World"
  }
}

GET /recommendation - Get food recommendation (top 5).

Name	Params	Required	Type	Description
`user_id`	Query	required	`integer`	The id of user. Example `14`

Response

{
  "status": true,
  "code": 200,
  "message": "OK",
  "data": {
    "food_id": [13, 14, 12, 2, 18]
  }
}

GET /model/{model_name} - Get status and metadata from model.

Name	Params	Required	Type	Description
`model_name`	Path	required	`string`	The name of model. Example `food_clf`

Response

{
  "status": true,
  "code": 200,
  "message": "OK",
  "data": {
    "status": {
      "model_version_status": [
        {
          "version": "1",
          "state": "AVAILABLE",
          "status": {
            "error_code": "OK",
            "error_message": ""
          }
        }
      ]
    },
    "metadata": {
      "model_spec": {
        "name": "food_clf",
        "signature_name": "",
        "version": "1"
      },
      "metadata": {
        "signature_def": {
          "signature_def": {
            "serving_default": {
              "inputs": {
                "input_2": {
                  "dtype": "DT_FLOAT",
                  "tensor_shape": {
                    "dim": [
                      {
                        "size": "-1",
                        "name": ""
                      },
                      {
                        "size": "150",
                        "name": ""
                      },
                      {
                        "size": "150",
                        "name": ""
                      },
                      {
                        "size": "3",
                        "name": ""
                      }
                    ],
                    "unknown_rank": false
                  },
                  "name": "serving_default_input_2:0"
                }
              },
              "outputs": {
                "dense": {
                  "dtype": "DT_FLOAT",
                  "tensor_shape": {
                    "dim": [
                      {
                        "size": "-1",
                        "name": ""
                      },
                      {
                        "size": "10",
                        "name": ""
                      }
                    ],
                    "unknown_rank": false
                  },
                  "name": "StatefulPartitionedCall:0"
                }
              },
              "method_name": "tensorflow/serving/predict",
              "defaults": {}
            },
            "__saved_model_init_op": {
              "inputs": {},
              "outputs": {
                "__saved_model_init_op": {
                  "dtype": "DT_INVALID",
                  "tensor_shape": {
                    "dim": [],
                    "unknown_rank": true
                  },
                  "name": "NoOp"
                }
              },
              "method_name": "",
              "defaults": {}
            }
          }
        }
      }
    }
  }
}

⁠POST

POST /predict - Predict category, rating, and price of image.

Name	Params	Required	Type	Description
`province`	Query	required	`string`	The province of seller. Example `Bali`
`environment`	Query	optional	`string`	The environment of seller. Default `campus`.
`name`	Query	optional	`string`	The name of food. Default `null`. Example `donat ubi mawar`
`image`	Body	required	`file`	The image to predict

Response

{
  "status": true,
  "code": 200,
  "message": "OK",
  "data": {
    "category": 2,
    "rating": 3,
    "price": 10000
  }
}

⁠License 📝

This project is licensed under the MIT License. See the LICENSE⁠ file for details.

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