How to Enhance Your dbt Project With Large Language Models

This story was originally published on HackerNoon at: https://hackernoon.com/how-to-enhance-your-dbt-project-with-large-language-models . Automatically solve typical Natural Language Processing tasks for your text data using LLM for as cheap as $10 per 1M rows, staying in your dbt environment Check more stories related to programming at: https://hackernoon.com/c/programming . You can also check exclusive content about #dbt , #llm , #python-project , #chatgpt-integration , #how-to-set-up-a-dbt-project , #openai-api-integration , #hackernoon-top-story , #natural-language-processing , and more. This story was written by: @klimmy . Learn more about this writer by checking @klimmy's about page, and for more stories, please visit hackernoon.com . You can automatically solve typical Natural Language Processing tasks (classification, sentiment analysis, etc.) for your text data using LLM for as cheap as $10 per 1M rows (it depends on the task and the model), staying in your dbt environment. Instructions, details, and code are below