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AI Agents from Zero to Hero — Part 2
- AI Agents are autonomous programs that perform tasks, make decisions, and communicate with others.
- Agents organize tasks into a logical progression and adapt their strategies in dynamic environments.
- Iterations involve repeating actions with slight changes or improvements in each cycle to refine output or reach optimal solutions.
- Chains are sequences of linked actions where each step depends on the previous one, forming a continuous flow of operations.
- The tutorial demonstrates using iterations and chains for AI Agents, with Python code examples for practical application.
- Tools like YahooFinance APIs and matplotlib are utilized to download and visualize financial data.
- The article introduces a function to process model responses and handle the usage of tools by the Agent.
- By incorporating iterations, the Agent can retry actions multiple times to solve problems and adapt.
- Chains allow for a linear sequence of actions, with outputs of one step used as inputs for subsequent steps, enhancing problem-solving capabilities.
- The structured approach using iterations and chains enhances the reliability of AI Agents, enabling developers to create customized solutions for various scenarios.
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