BiteSizedChunks.comLearn one small thing at a time.

Course contentsShow

543What is Function Calling in LLMs
544Function Calling vs Traditional Prompting
545OpenAI Function Calling API Structure
546Writing Function Descriptions for LLMs
547JSON Schema for Function Parameters
548Making a Function Call Request
549Executing Functions and Returning Results
550Function Calling with Other Providers
551Parallel Function Calls
552Forcing and Disabling Function Calls
553Function Calling Response Formats
554Basic Error Handling in Function Calls
555Function Schema Structure and OpenAI Format
556Parameter Types and Required vs Optional Fields
557Writing Effective Function Descriptions
558Parameter Descriptions and Constraints
559Complex Parameter Schemas with Nested Objects
560Function Registry Pattern for Dynamic Tools
561Version Control for Function Definitions
562Validating Function Arguments Before Execution
563Function Grouping and Conditional Availability
564Testing and Debugging Function Definitions
565Multi-turn Conversation Flow
566Tracking Conversation State
567Sequential Tool Execution
568Handling Tool Call Results
569Conversation Continuation Logic
570Context Window Management
571Interleaving User Input
572Tool Call Dependency Resolution
573Multi-turn Timeout and Limits
574Debugging Multi-turn Flows
575Common Function Calling Errors
576Validating Function Arguments
577Graceful Degradation Strategies
578Error Messages for LLMs
579Retry Logic and Recovery
580Tool Selection Strategies
581Limiting Available Tools by Context
582Handling Ambiguous Tool Requests
583Timeout and Resource Limits
584Logging and Debugging Tool Calls

543What is Function Calling in LLMs
544Function Calling vs Traditional Prompting
545OpenAI Function Calling API Structure
546Writing Function Descriptions for LLMs
547JSON Schema for Function Parameters
548Making a Function Call Request
549Executing Functions and Returning Results
550Function Calling with Other Providers
551Parallel Function Calls
552Forcing and Disabling Function Calls
553Function Calling Response Formats
554Basic Error Handling in Function Calls
555Function Schema Structure and OpenAI Format
556Parameter Types and Required vs Optional Fields
557Writing Effective Function Descriptions
558Parameter Descriptions and Constraints
559Complex Parameter Schemas with Nested Objects
560Function Registry Pattern for Dynamic Tools
561Version Control for Function Definitions
562Validating Function Arguments Before Execution
563Function Grouping and Conditional Availability
564Testing and Debugging Function Definitions
565Multi-turn Conversation Flow
566Tracking Conversation State
567Sequential Tool Execution
568Handling Tool Call Results
569Conversation Continuation Logic
570Context Window Management
571Interleaving User Input
572Tool Call Dependency Resolution
573Multi-turn Timeout and Limits
574Debugging Multi-turn Flows
575Common Function Calling Errors
576Validating Function Arguments
577Graceful Degradation Strategies
578Error Messages for LLMs
579Retry Logic and Recovery
580Tool Selection Strategies
581Limiting Available Tools by Context
582Handling Ambiguous Tool Requests
583Timeout and Resource Limits
584Logging and Debugging Tool Calls

← AI Engineering

Lesson 576 of 1,886·14. Function Calling and Tool UsePro lesson

Validating Function Arguments

Implement robust validation of LLM-generated arguments before execution using schema checks and type coercion.

This lesson is for subscribers

You've completed the free preview. Subscribe to unlock every lesson in every course.

See pricing Back to course