Building Agent Workflows with Gemini 2.5 Pro—Does It Hold Up?


Summary

The video discusses Gemini 2.5 Pro's coding performance and function call handling through independent benchmarks. It demonstrates using SDK for Python to automate function calling for flexibility. The model accurately processes simple queries, handles multiple function calls, and assists in trip planning with detailed information like flight details and weather forecasts. Additionally, it showcases the creation of a business intelligence dashboard for comprehensive data analysis using natural language queries and SQL execution.


Introduction to Gemini 2.5 Pro Benchmarks

Discussing the hype around Gemini 2.5 Pro based on independent benchmarks and coding performance compared to other models.

Testing Function Calling Abilities

Exploring the ability of the model to correctly handle function calls, starting with basic functions and moving towards parallel function calls for practical applications.

Integrating SDK for Python

Demonstrating the use of SDK for Python to automate function calling and enhance flexibility in executing manual functions.

Example: Weather Function Call

Implementing a function that returns weather information based on user input, showcasing the model's ability to process simple queries effectively.

Example: Multiple Function Calls

Illustrating the model's capability to handle multiple function calls, like retrieving weather and population information for different cities.

Example: Trip Planning Assistance

Utilizing sequential function calls to provide trip planning assistance, including flight details, weather forecasts, and budget estimations.

Advanced Example: Business Intelligence Dashboard

Creating a business intelligence dashboard using natural language queries, SQL execution, and structured outputs for comprehensive analysis.

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