AI IT Mentor

STRUCTURE

• Asynchronous FastAPI project with endpoints that can be used to upload a roadmap file generated from a gpt model to the computer

• OpenAI library for working with gpt is used

openai==1.14.2

• I use the kafka-python libraries to work with Kafka

kafka-python==2.0.2

• FastAPI service is started via Uvicorn

uvicorn==0.29.0

• The generation process from OpenAI and the file upload process takes place on the Kafka side, which is connected via docker-compose

• The configuration is located in the .env_dev file

  • To change it to another file, modify the following line in src/app.py

env.read_env('.env') -> .env set to the new env file

• The startup is done with the src/manage.py file and in this file you can add other startups before or after the services are started

import subprocess

if __name__ == "__main__":
    """
            Here you can perform actions before starting the services
    """
    server_process = subprocess.Popen(["python", "server_run.py"])
    consumer_process = subprocess.Popen(["python", "kafka_run.py"])

    server_process.wait()
    consumer_process.wait()

INSTALLATION

• I hope you already have python, pip and docker installed

• Copy this repository to your system

https://github.com/VyacheslavShrot/ai_it_mentor.git

• Install requirements.txt

pip install -r requirements.txt

• To configure the Kafka queue retention period, specify the desired number of milliseconds on a line in the "docker-compose.yml" file
  • Where 86400000 is 24 hours of queue storage

KAFKA_LOG_RETENTION_MS: "86400000"

• Create an .env file at the src level of the directory (ai_it_mentor/.env)
  • Define OPENAI_API_KEY variable to work with gpt

OPENAI_API_KEY=sk-lb...

START

• Start Docker-Compose, where services are defined to work with Kafka

docker-compose up -d

• Go to the work directory

cd src

• Start FastAPI and Kafka services

python3 manage.py

POSTMAN DOC

• https://documenter.getpostman.com/view/26500283/2sA35D63gG - Link on Postman Documentation
  • This documentation describes the possible parameters and their values