GPT function calling in a nutshell
AI Summary
Summary: GPT Function Calling
- Introduction to GPT Function Calling
- GPT is like a brain in the cloud accessible via apps or API.
- GPT functions are a recent addition, allowing enhanced capabilities.
- The video aims to clarify GPT functions with code examples.
- Basic Code Scaffolding
- JavaScript code with OpenAI key, model selection, and question logging.
- GPT’s Limitations and Functions
- GPT cannot access the internet or file systems by default.
- Functions allow GPT to perform tasks beyond its sandbox, like checking weather.
- Implementing Functions in Code
- Functions are declared in the request body.
- GPT is informed about available functions and their specifications using JSON schema.
- GPT requests function execution, which must be performed externally.
- Looping for Multiple Function Calls
- Code must handle multiple function calls, like checking weather in different cities.
- A loop is implemented to keep interacting with GPT until it finishes processing.
- The loop checks for a “finished reason” to determine if GPT is done.
- Extending Functionality
- New functions (e.g., saving files) can be added.
- GPT can generate code to streamline the process.
- Use Cases for Functions
- Functions can be used to augment GPT’s responses or to ensure structured responses.
- Structured responses are useful for database insertion or API integration.
- Forcing Function Calls
- GPT can be forced to call a specific function to ensure a predictable response format.
- This is controlled by setting a parameter in the request.
- Conclusion
- GPT function calling is useful for enhancing capabilities and obtaining structured data.
- The video provided examples of augmenting GPT’s capabilities and structuring responses for integration purposes.