Function calling with the Gemini API

Key Concepts

• Function calling: Connecting language models (Gemini) with external systems and APIs.
• Function declarations: Blueprints that define the functions Gemini can use, including their names, descriptions, parameters, and actions.
• JSON: Data format used to represent function calls and their parameters.
• Multi-turn conversations: Interactive experiences where Gemini can make function calls, get results, and use those results in subsequent turns.

1. Introduction to Function Calling

• Function calling is a powerful feature of the Gemini API that allows language models to interact with external systems and APIs.
• It enables Gemini to use tools like searching a database, controlling smart home devices, or booking flights through natural language.
• The core idea is to make language models more actionable by allowing them to generate structured data representing function calls.

2. How Function Calling Works

• Gemini generates structured data (JSON) that represents a function call, essentially sending instructions to another program.
• Instead of just providing text, Gemini can instruct the user to run specific functions with specific inputs.
• Example: A chatbot booking appointments. Gemini understands the user's request and generates the JSON to call a scheduling API with time, date, and participant details.

3. Defining Functions with Function Declarations

• To use function calling, you need to define the functions Gemini can use through function declarations.
• Function declarations are like instruction manuals for Gemini, specifying the tools it can use and how to use them.
• These declarations include the function's name, description, parameters it accepts, and what it does.
• The video references a simplified example from the Gemini documentation for adding entities to a database.

4. Using Function Declarations in Requests

• Function declarations are passed to Gemini as part of the request.
• Gemini analyzes the prompt and determines if it needs to call a function.
• If a function call is needed, Gemini generates the appropriate function call JSON based on the declarations.
• Important: Gemini does not execute the functions. The user needs to write code to execute the functions. Gemini only determines which function to call and what inputs to provide.

5. Multi-Turn Conversations

• Function calling becomes more powerful in multi-turn conversations.
• Gemini can make a function call, get the result, and use that result in the next turn of the conversation.
• Example: Finding restaurants. Gemini calls a function to get the user's location, uses that location to search a restaurant database, and presents the user with a list of options.

6. Conclusion

• Function calling is a game changer for natural language model applications.
• It allows for the creation of truly interactive and powerful experiences by connecting Gemini to external systems.
• The video encourages viewers to check out the links in the description for more detailed examples and tutorials.