Listen "How to Enhance Your dbt Project With Large Language Models"
Episode Synopsis
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
More episodes of the podcast Programming Tech Brief By HackerNoon
The "API First" Illusion: Why Your "Simple" Endpoints Turn Into Technical Debt (And How to Fix It)
16/12/2025
Flight Recorder: A New Go Execution Tracer
14/12/2025
The "Feynman Technique" for Algorithms: How to Stop Memorizing Code and Start Building Intuition
11/12/2025
Rust 1.78.0: What's In It?
08/12/2025
ZARZA We are Zarza, the prestigious firm behind major projects in information technology.