Get up and running quickly with an AI agent application on AWS using Bedrock AgentCore
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Updated
Sep 17, 2025 - Python
Get up and running quickly with an AI agent application on AWS using Bedrock AgentCore
A comprehensive framework to create, test, and benchmark Retrieval-Augmented Generation (RAG) pipelines, supporting multiple architectures (e.g., Graph RAG and Agentic RAG), document splitters, embedding models, vectorstores, retrievers, rerankers, and LLM providers, with an interactive Gradio UI and experiment logging.
A Multi-Modal Agentic RAG pipeline designed to handle unstructured documents containing tables, charts, and images. It integrates Docling and ElasticSearch for structured indexing, and leverages LangGraph for agent-based reasoning and dynamic query reformulation.
This project is a multi-agent system for stock analysis, built using the Google AI SDK (assumed to be Google ADK) and the Alpha Vantage API. It processes stock-related queries through five modular sub-agents, supporting both natural language and structured inputs. The system provides insights into stock price movements, recent news, and analysis.
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