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