fnikol

4 ms·

1. 1.▲
   We are trending on #3 globally on GitHub (yesterday #9)(superduperdb.com)

   2 points by fnikol 3y ago|1 comments
2. 2.▲
   by fnikol 3y ago

   We are very happy that other developers also see the pain points of complex ETL and MLOps pipelines, specialized vector databases, and want to get rid of the need to move your data all over the place when building AI applications. A big tha
3. 3.▲
   by fnikol 3y ago

   Indeed both frameworks support model chaining. However, achieving goals like "training your LLM" or enabling "real-time inference" requires more than just pipelines. For that, we have invested in enhancing compatibility
4. 4.▲
   by fnikol 3y ago

   All things aside, it's a framework for building data workflows in Python. Like taking the data from that source (e.g., SQL), processing them (e.g., pytorch or openai), and storing the results somewhere (e.g., data on Mongo metadata on