Evaluate LLM Tool-Calling Capabilities
Evaluate LLM function/tool calling with promptfoo. Test and improve AI agent capabilities.
Why it matters
Assess and validate the ability of Large Language Models to effectively utilize external tools and functions. This asset helps ensure your LLMs can reliably interact with and leverage other services.
Outcomes
What it gets done
Test LLM function calling accuracy.
Evaluate tool execution success rates.
Benchmark LLM's ability to select and use appropriate tools.
Generate reports on tool-use performance.
Install
Add it to your toolbox
Run in your project directory:
curl -fsSL https://spark.entire.vc/get/pfoo-tool-use | bash Capabilities
What this chain does
Test LLM function calling accuracy.
Evaluate tool execution success rates.
Benchmark LLM's ability to select and use appropriate tools.
Generate reports on tool-use performance.
Overview
Tool Use
What it does
This promptfoo example demonstrates how to evaluate an LLM's function or tool calling capabilities. It provides a framework for testing an AI's ability to correctly identify and utilize external tools based on user prompts.
How it connects
Use this when you need to rigorously test and validate an LLM's proficiency in function calling or tool use, crucial for building AI agents that interact with external systems. Do not use if your goal is simple text generation without tool interaction.
Source README
This example demonstrates how to evaluate LLM function/tool calling capabilities using promptfoo.
Discussion
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