MLOps challenge

This is a small minimal AI inference API for image classification.

Development Requirements

• Python3.11.0
• Pip
• Poetry (Python Package Manager)

Installation

python3.11 -m venv venv # 3.12 works as well
source venv/bin/activate
make install

Runnning Localhost

make run

Deploy app

make deploy

Running Tests

make test

Usecase

POST /predict

A POST request can be made using the following command:

curl -X POST -H "Content-Type: application/json" -d '{"image": "Image Content goes Here"}' http://localhost:5000/predict

This returns a JSON response of the following form:

{"response": "class_name"}

POST /predict-form-data

A POST request can be made such that the image is sent as multipart/form-data using the --form option. The request can be done using the following command:

curl --location 'http://localhost:5000/predict-form-data' \
--form 'image=@"file_path_of_image.jpeg"'

This returns a JSON response of the following form:

{"response": "class_name"}

Access Swagger Documentation

http://localhost:5000/docs

Access Redocs Documentation

http://localhost:5000/redoc

M.L Model Environment

MODEL_PATH=./ml/model/
MODEL_NAME=densenet121

Project structure

Files related to application are in the app or tests directories. Application parts are:

app
|
| # Fast-API stuff
├── api                 - web related stuff.
│   └── routes          - web routes.
├── core                - application configuration, startup events, logging.
├── models              - Data models for this application.
├── services            - logic that is not just crud related.
├── main-aws-lambda.py  - [Optional] FastAPI application for AWS Lambda creation and configuration.
└── main.py             - FastAPI application creation and configuration.
|
│
├── notebooks        - Jupyter notebooks. Naming convention is a number (for ordering),
|
├── ml               - AI related logic for AI models and classes
│
└── tests            - pytest

AWS

Deploying inference service to AWS Lambda

Authenticate

1. Install awscli and sam-cli
2. aws configure

Deploy to Lambda

1. Run sam build
2. Run `sam deploy --guiChange this portion for other types of models

Add the correct type hinting when completed

aws cloudformation delete-stack --stack-name <STACK_NAME_ON_CREATION>

Made by https://github.com/arthurhenrique/cookiecutter-fastapi/graphs/contributors with ❤️

References

This pipeline was generated using the Cookiecutter python module. The AI-based classification relies on the PyTorch framework.