Glossary

Function Calling (LLM)

Function calling is a capability of large language models that allows them to generate structured JSON outputs matching predefined function signatures, enabling them to invoke external tools and APIs as part of their reasoning process.

Definition

Function calling is a capability of large language models that allows them to generate structured JSON outputs matching predefined function signatures, enabling them to invoke external tools and APIs as part of their reasoning process.

In Depth

Function calling was introduced to bridge the gap between natural language understanding and structured tool invocation. When an LLM supports function calling, developers define functions with names, descriptions, and parameter schemas. The model then determines when to call a function, generates the appropriate arguments as JSON, and the application executes the function and returns the result. This is the foundation of AI agent architectures where LLMs need to interact with external systems. Search APIs like Scavio provide pre-built function definitions for popular frameworks, making it trivial to add web search capabilities to any function-calling-enabled LLM.

Example Usage

Real-World Example

A developer defines a 'search_google' function with parameters for query, location, and language. When a user asks the chatbot about current events, the LLM generates a function call with the appropriate search query, the app executes it via Scavio, and the LLM summarizes the results.

Platforms

Function Calling (LLM) is relevant across the following platforms, all accessible through Scavio's unified API:

  • Google
  • Amazon
  • YouTube
  • Walmart
  • Reddit

Related Terms

Frequently Asked Questions

Function calling is a capability of large language models that allows them to generate structured JSON outputs matching predefined function signatures, enabling them to invoke external tools and APIs as part of their reasoning process.

A developer defines a 'search_google' function with parameters for query, location, and language. When a user asks the chatbot about current events, the LLM generates a function call with the appropriate search query, the app executes it via Scavio, and the LLM summarizes the results.

Function Calling (LLM) is relevant to Google, Amazon, YouTube, Walmart, Reddit. Scavio provides a unified API to access data from all of these platforms.

Function calling was introduced to bridge the gap between natural language understanding and structured tool invocation. When an LLM supports function calling, developers define functions with names, descriptions, and parameter schemas. The model then determines when to call a function, generates the appropriate arguments as JSON, and the application executes the function and returns the result. This is the foundation of AI agent architectures where LLMs need to interact with external systems. Search APIs like Scavio provide pre-built function definitions for popular frameworks, making it trivial to add web search capabilities to any function-calling-enabled LLM.

Function Calling (LLM)

Start using Scavio to work with function calling (llm) across Google, Amazon, YouTube, Walmart, and Reddit.