OptionaldescriptionDescription of the function.
For reference, the description is very important property to teach
the purpose of the function to the LLM (Language Large Model), and
LLM actually determines which function to call by the description.
Also, when the LLM conversates with the user, the description is
used to explain the function to the user. Therefore, the description
property has the highest priority, and you have to consider it.
Representative name of the function.
Parameters of the function.
Validate function of the arguments.
You know what? LLM (Large Language Model) like OpenAI takes a lot of
mistakes when composing arguments in function calling. Even though
number like simple type is defined in the parameters schema,
LLM often fills it just by a string typed value.
In that case, you have to give a validation feedback to the LLM by
using this validate function. The validate function will return
detailed information about every type errors about the arguments.
And in my experience, OpenAI's gpt-4o-mini model tends to construct
an invalid function calling arguments at the first trial about 50% of
the time. However, if correct it through this validate function,
the success rate soars to 99% at the second trial, and I've never
failed at the third trial.
If you've separated parameters, use the IMcpLlmFunction.ISeparated.validate function instead when validating the LLM composed arguments.
In that case, This
validatefunction would be meaningful only when you've merged the LLM and human composed arguments by McpLlm.mergeParameters function.
Arguments to validate
Validation result
MCP LLM function.
IMcpLlmFunctionis an interface representing a function metadata of MCP (Model Context Protocol), which has been designed for the LLM (Language Large Model) function calling, instead of providingmcp_serversproperty to the LLM vendor API.It contains the target function's metadata name, parameters and description. You can put these properties to the LLM vendor API to let the LLM know the function's purpose and how to call it.
Also, it contains validate function, which is used to validate the function arguments generated by AI agent. It is very important to the LLM function calling, because LLM like OpenAI takes a lot of mistakes when composing arguments in function calling. Even though
numberlike simple type is defined in the parameters schema, LLM often fills it just by astringtyped value.Author
Jeongho Nam - https://github.com/samchon
Author
Byeongjin Oh - https://github.com/sunrabbit123