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The Flask server is served by Gunicorn, and Nginx acts as a load balancer to distribute requests. The ReactJS client communicates with the Flask API.\n\n## Deployment\n\n### Prerequisites\n\nMake sure you have Docker and Docker Compose installed on your machine.\n\n### Deployment:\n\n2. Build and run containers:\n\n    ```bash\n    docker compose up -d --build\n    ```\n\n    This command builds the images, starts containers\n\n3. To stop and remove containers:\n\n    ```bash\n    docker compose down\n    ```\n\n4. View running containers:\n\n    ```bash\n    docker ps\n    ```\n\n### Development\n\nFor developing there is no need to use Docker.\n\n#### Frontend\n\nFor client, it needs to change `API_BASE_URL` to LOCALHOST\n\nTo start client frontend, run:\n\n```bash\nnpm install \u0026\u0026 npm start\n```\n\n#### Backend\n\nTo start flask servers, navigate to each server directory (`/server/{falsk, model, test}`) and run:\n\n```bash\npip install -r requirements.txt\nflask run || python3 server/[servername]/[main_file].py\n```\n\n## Fine-tuning\n\n1. Edit config for fine-tuning in `data/config.json`\n\n2. Check laoding and format\n\n```bash\npython3 data/fine_tuning_data_validation.py\n```\n3. Start fine-tuning\n\n```bash\npython3 data/fine_tuning.py\n```\n\nConvert yaml to jsonl:\n\n```bash\npython3 convert_yaml_to_jsonl.py train_data.yaml train_data.jsonl\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fxkrejc70%2Fpython-tutor","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fxkrejc70%2Fpython-tutor","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fxkrejc70%2Fpython-tutor/lists"}