Hi, Thank you for contributing! You may also want to look at working with RunInference, for example:
https://beam.apache.org/releases/pydoc/current/apache_beam.ml.inference.vllm_inference.html#module-apache_beam.ml.inference.vllm_inference Cheers Reza On Sun, 1 Dec 2024 at 14:55, LDesire <two_som...@icloud.com> wrote: > Hi Ganesh, > I'm very excited to see this new PTransform for Beam's Java SDK. > Thank you for sharing this valuable contribution. > > Best regards > > > > 2024. 12. 1. 오후 11:46, Ganesh <ganeshsivakuma...@gmail.com> 작성: > > Hi All, > > I've been working on a custom Ptransform that integrates large language > models as a PTransform in an Apache beam pipeline using Langchain. > > The aim of this integration is to leverage the capabilities of LLMs for > data processing and transformations of unstructured data. > It treats language models as PTransform block in a data pipeline. The > transform takes a prompt that has instructions on what to do with the input > element, The LLM applies the instruction on the element and the model's > output is returned as a Pcollection. > > It uses langchian to interact with the models as it provides a common > interface for interacting with multiple model providers. > I'm excited to share langchian-beam Ptransform with the beam community. > Would like to hear your thoughts and feedback. > > Repository link - https://github.com/Ganeshsivakumar/langchain-beam > > > Thanks, > Ganesh. > > >
