2-stage pipeline locks character faces across scenes without LoRA

A 2-stage image pipeline uses a text-to-image model to create a canonical base image, then an image-edit model to generate new scenes while preserving identity. This approach avoids seed drift and heavy LoRA training, making it suitable for production apps. The pipeline is deployable with an async job queue and serverless GPU setup.