Mentioning the points as discussed:
- For the data extraction, the user will input the data in two parts a. List of search products separated by semicolon b. Top 'n' products to be searched
- After getting the user inputs, the api call will be made which will generate the data in the form of dict like {"searchedProductName": "Hair Oil", "GeneratedProductTitle": "To be generated", "GeneratedProductDescription": "To be generated", "keywords": "[list of keywords]"}
- At last the user will check and proceed with updating the listed product data or export the table data into excel sheel.
In the above second step, it will consist of mutiple steps:
- The excel will be generated with the extracted product data.
- The data will be grouped according to the searched product name.
- The product title and description data will be combined to single data.
- The brand name will be extracted from the data and which will be removed from above combined data.
- The noise and stop words will be removed from above data.
- Using BERT algorithm, the keywords will be generated in the form of lists.
- Now this list of keywords will be used to generate title and description using chatpGPT.
OPL extracts information about the similar products and generates the best listing of the products.
python3 -m venv venv
pip install -r requierments.txt
python app.py -h
# run in headless mode
OR
python app.py -u
# prints usage
python main.py -h
# Headless mode (preferred)
Use -v flag to run in verbose/debug mode
python -v main.py -h
OR
python main.py
# Run with browser - use for debugging
pm2 start ecosystem.config.js
pm2 status
pm2 logs
pm2 monit
pm2 stop "opl api"
Swagger UI is available only in test / debug mode. Access URL - localhost:5000/api/v1/ui/ to test the API.
docker build -t opl-api-img-04052023 .
docker run --rm -v $(pwd)/logs:/app/logs -v $(pwd)/config:/app/config -v $(pwd)/controllers:/apps/controllers:ro -v $(pwd)/utils:/apps/utils:ro -d -p 5000:5432 opl-api-img-04052023
docker run --rm -v $(pwd)/logs:/app/logs -d p 5000:5432 opl-api-img-04052023
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