Yes, Amazon Bedrock can be used to build multi-modal applications that accept both image and text input or generate multi-modal output. Bedrock provides access to foundation models like Claude 3 (Anthropic) and Titan Multimodal (Amazon), which support image and text input, along with models like Stable Diffusion (Stability AI) for image generation. These capabilities allow developers to combine multiple models in a single workflow, enabling applications that process or generate mixed media.
For input handling, models like Claude 3 accept images as base64-encoded strings alongside text prompts. For example, a developer could build an application where users upload a product photo and ask, “What defects are visible here?” The image is encoded into base64 and included in the API request body with the text prompt. Claude 3 analyzes both inputs and returns a text response identifying defects. Similarly, Titan Multimodal can accept an image and generate descriptive text, such as alt text for accessibility. Developers interact with these models via Bedrock’s unified API using AWS SDKs like Boto3. Each model has specific parameters—Claude 3 requires specifying the MIME type and image data in the messages array, while Titan uses a inputImage field—so formatting requests correctly is key.
For multi-modal output, developers can chain models. A text-to-image model like Stable Diffusion generates images from text prompts, while text-based models like Claude produce summaries or analysis. For instance, an app could take a text prompt like “Describe and visualize a futuristic city,” first using Claude to create a detailed description, then passing that text to Stable Diffusion to generate an image. Bedrock’s API allows separate calls to each model, and developers orchestrate these steps using serverless services like AWS Lambda or workflows with Step Functions. While Bedrock handles scaling and infrastructure, developers must manage input/output transformations, such as resizing images to meet model constraints (e.g., Claude 3’s 5MB limit) or encoding/decoding media. This approach enables applications like interactive design tools or medical imaging analysis systems that blend visual and textual reasoning.