Jorge Demetrio Sobieski Teixeira

Great initiative, Abhishek. One angle worth baking in early: the most robust signal usually is not in perception (blinking, lip-sync) but in the frequency domain. GANs and diffusion leave a periodic upsampling fingerprint in the spectrum that a 2D FFT plus a radial average collapses into a single score. Pairing that with Error Level Analysis for splicing and a face-landmark check (MediaPipe) gives you an ensemble that degrades gracefully instead of one brittle model. I put together a Python walkthrough of exactly this ensemble over on Meu Universo Nerd if it helps your build.

Nice walkthrough on the SSE setup. One thing worth flagging for anyone wiring the client side with the new SDK 2.0.0: if the server speaks Streamable HTTP but your client uses the legacy SSE transport, listTools() just comes back empty with no error. Same trap if you call it before initialize(), since the handshake is what makes the server advertise its tools. I put together a wrong-vs-right breakdown (pure SDK, Spring AI and Quarkus) over on Meu Universo Nerd if anyone wants the full code.