feat: Research Multi-Agents with Gemini 2.0

[holtskinner]

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[holtskinner]

@lavinigam-gcp Can you please resolve the issues shown here:

https://github.com/GoogleCloudPlatform/generative-ai/actions/runs/12280024460

[ghost]

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[ghost]

This pull request introduces a significant enhancement to the multi-agent system for EV infrastructure analysis. The new ExecutionAgent orchestrates the entire pipeline, including planning, query analysis, data gathering, report generation, and visualization. The PlanningAgent has been substantially improved to handle query validation, determine visualization and search needs, and create a dynamic execution plan. The QueryAnalysisAgent uses function calling to extract entities and determine analysis parameters. The DataGatherAgent uses asynchronous operations to efficiently gather data from multiple APIs. The ReportAgent generates comprehensive reports, and now optionally enhances them with search results and citations. Finally, the VisualizeAgent creates informative visualizations for both single-city and multi-city comparisons. The code is well-structured, uses descriptive variable names, and includes helpful comments. The use of asynchronous operations and error handling significantly improves the robustness and efficiency of the system. However, the PlanningAgent's _determine_visualization_requirement and _determine_search_requirement functions currently always return True. This should be updated to dynamically determine these requirements based on the query content. Additionally, consider adding more comprehensive unit tests to cover various scenarios and edge cases. The debug messages are very helpful for troubleshooting, but they should be removed or made configurable for production environments. Overall, this is a well-executed and impactful pull request that significantly improves the functionality and usability of the multi-agent system.

[holtskinner]

Overall feedback/request. Could this be made any simpler? I understand we want to show a complex use case, but there is a lot of code here to understand.

[ghost]

The pull request introduces a significant enhancement to the multi-agent system for EV infrastructure analysis. The new ExecutionAgent orchestrates the entire pipeline, which is a substantial improvement. The code is well-structured and uses descriptive variable names. The use of asynchronous operations and error handling improves robustness and efficiency. However, there are areas for improvement. The PlanningAgent's _determine_visualization_requirement and _determine_search_requirement functions always return True. These should be updated to dynamically determine these requirements based on the query content. More comprehensive unit tests should be added to cover various scenarios and edge cases. Debug messages should be removed or made configurable for production environments. To address the author's concern about simplification, consider refactoring the code into smaller, more manageable modules. This would improve readability and maintainability. For example, the ExecutionAgent could be broken down into separate agents for each stage of the pipeline. This would make the code easier to understand and test.

[erwinh85]

Approving and merging for now. We still have some Lint errors that we will solve with an updated version.