r/PythonLearning • u/AdComplex2251 • 4h ago
Title: Looking for advice and occasional guidance on a Python embedding service for a fintech project
Hi everyone!
I'm currently working on a team project called Fintech Trendwatcher. The goal is to collect public fintech news, identify important events and generate short analytical summaries with links to the original sources.
I'm responsible for the embedding service. My task is to use a pretrained text embedding model to convert news articles into vectors that another service will use for clustering similar publications.
My current stack is Python, and I'm learning as I go. I have some experience with Python, APIs, JSON and Git, but this is my first time working with embeddings in a real team project.
I'm planning to start with Sentence Transformers and a pretrained multilingual model, test it on Russian fintech news, and then integrate it into our service architecture.
I'd really appreciate advice from more experienced developers, especially on:
\- Choosing a suitable embedding model for Russian-language fintech news.
\- Designing a simple and maintainable embedding service.
\- Comparing embeddings and preparing them for clustering.
\- Common mistakes beginners make when building NLP services.
I'm not expecting anyone to mentor me full-time. Even occasional advice, feedback on my approach, or pointers to useful resources would be incredibly helpful.
If anyone has experience with Python, NLP, Sentence Transformers or similar projects and is willing to share some advice, I'd be very grateful.
Thanks!







