Summary
In this chapter, we discussed the integration of GenAI models into real-world applications that require a systematic approach. A five-component framework can guide this process: Entry Point, Prompt Pre-Processing, Inference, Result Post-Processing, and Logging. At the entry point, user inputs aligned with the AI model’s expected modalities are accepted, whether text prompts, images, audio, etc. Prompt pre-processing then cleans and formats these inputs for security checks and optimal model usability.
The core inference component then runs the prepared inputs through the integrated GenAI models to produce outputs. This stage requires integrating with model APIs, provisioning scalable model-hosting infrastructure, and managing availability alongside cost controls. Organizations can choose self-hosting models or leveraging cloud services for inference. After inference, result post-processing techniques filter inappropriate content, select ideal outputs from multiple...
