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Agent System Setup with Claude Agents SDK

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Linked challenge: AI Policy Argument Generation Agent

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Linked challenge

AI Policy Argument Generation Agent

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Initialize your Python environment and set up the Claude Agents SDK. Define a `PolicyAnalyzer` agent and a `RhetoricGenerator` agent. The `PolicyAnalyzer` should have access to tools for document retrieval from Azure Cognitive Search. The `RhetoricGenerator` should specialize in crafting persuasive language based on analysis. Provide the initial Python code for defining these agents and their basic roles.

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Linked challenge

AI Policy Argument Generation Agent

Develop an advanced AI agent system using the Claude Agents SDK to assist in complex policy negotiations, drawing inspiration from the SAG-AFTRA talks regarding an 'AI tax' on synthetic actors. This challenge requires building a system capable of analyzing diverse policy documents, legal texts, and economic data to generate well-reasoned arguments and counter-arguments for specific stakeholders, such as labor unions and production studios. The core of the solution will be a multi-agent workflow orchestrated by the Claude Agents SDK, leveraging Claude 3.5 Sonnet for its robust reasoning and document understanding capabilities. The agents will be tasked with identifying key points of contention, forecasting potential impacts of proposed policies, and synthesizing persuasive rhetoric. Evaluation of the generated arguments will be conducted using Gentrace, focusing on logical coherence, factual accuracy, and persuasive strength. The system will rely on Azure Blob Storage and Azure Cognitive Search for efficient storage and retrieval of relevant policy documents and background information.

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