hey 👋 vector db crowd seemed like a good fit for this shipped an open source python framework for tracking LLM cost/ tokens/latency — TokenSense. runs entirely in-process, no proxy relevant here because if you're running RAG pipelines, every query usually means an embedding call + a retrieval + a generation call, and tracking cost across all three gets messy fast. this wraps your openai/anthropic/groq clients with one line and tracks every hop automatically pip install tokensense-ai also has langchain + llamaindex callback hooks since most RAG stacks run through one of those website: visualvortexcreatives.dev github: github.com/SahilSelokar/Tokensense docs: docs.visualvortexcreatives.dev curious if anyone here tracks embedding costs separately from generation costs in their pipelines — feels like a gap most tools don't handle well