Build a Serverless Image Editing Agent with Bedrock AgentCore
AWS ML Blog · rss · 2026-07-08
This article details how to build a serverless natural language image editing Agent using Amazon Bedrock AgentCore Harness. Users can upload photos and describe modifications in natural language, and the Agent will invoke underlying models to complete the edits.
Core Architecture & Capabilities:
- Configuration-Driven: Define an Agent with memory, tool routing, and observability via API parameters without writing complex Python orchestration code.
- Dynamic Model & Role Switching: Supports on-demand model switching during conversations (e.g., Haiku for chitchat, Sonnet for image editing) and dynamic injection of industry-specific system prompts.
- AgentCore Memory: Retains 30 days of conversation history server-side, ensuring context continuity across sessions and model switches.
- MCP Tool Gateway: Exposes three Lambda-based image processing tools via Model Context Protocol (MCP), automatically selected and invoked by the model based on user intent.
- Low-Cost Post-Processing: Uses InvokeAgentRuntimeCommand to run Shell scripts directly within micro-VMs to add watermarks, avoiding large model token consumption.
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