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A technical walkthrough demonstrates using LangChain with Amazon Bedrock Managed Knowledge Bases to compare standard single-shot retrieval (Retrieve API) and multi-step agentic retrieval (AgenticRetrieveStream API). The post explains architecture, IAM permissions, boto3 version requirements (agentic_retrieve_stream requires boto3 >= 1.43.32), and trade-offs including cost and trace event inspection.
Condé Nast partnered with the AWS Generative AI Innovation Center to build a multimodal video discovery system using TwelveLabs' Marengo embeddings via Amazon Bedrock and indexed in Amazon OpenSearch Service. The decoupled architecture — embedding generation on Bedrock and low-latency k-NN search on OpenSearch — enables intent-based, image-driven, and timestamped searches across transcripts, audio, and visuals, reducing average discovery time from ~250 minutes to under 2 minutes per task.
OpenCode, an open-source terminal-native AI coding agent, can connect to open-weight models via Amazon Bedrock so inference runs securely in a customer’s AWS account without per-seat fees or separate infrastructure. The post demonstrates multi-model workflows (examples: Moonshot AI Kimi K3, OpenAI GPT-OSS 120B, NVIDIA Nemotron 3 Super 120B), and highlights Bedrock features such as regional data-residency profiles, AWS security controls, flexible pricing tiers, and high default throughput limits.
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