llama-stack-mirror/llama_stack/providers/inline/ios/inference/LocalInferenceImpl/SystemPrompts.swift
Ashwin Bharambe ef0736527d
feat(tools)!: substantial clean up of "Tool" related datatypes (#3627)
This is a sweeping change to clean up some gunk around our "Tool"
definitions.

First, we had two types `Tool` and `ToolDef`. The first of these was a
"Resource" type for the registry but we had stopped registering tools
inside the Registry long back (and only registered ToolGroups.) The
latter was for specifying tools for the Agents API. This PR removes the
former and adds an optional `toolgroup_id` field to the latter.

Secondly, as pointed out by @bbrowning in
https://github.com/llamastack/llama-stack/pull/3003#issuecomment-3245270132,
we were doing a lossy conversion from a full JSON schema from the MCP
tool specification into our ToolDefinition to send it to the model.
There is no necessity to do this -- we ourselves aren't doing any
execution at all but merely passing it to the chat completions API which
supports this. By doing this (and by doing it poorly), we encountered
limitations like not supporting array items, or not resolving $refs,
etc.

To fix this, we replaced the `parameters` field by `{ input_schema,
output_schema }` which can be full blown JSON schemas.

Finally, there were some types in our llama-related chat format
conversion which needed some cleanup. We are taking this opportunity to
clean those up.

This PR is a substantial breaking change to the API. However, given our
window for introducing breaking changes, this suits us just fine. I will
be landing a concurrent `llama-stack-client` change as well since API
shapes are changing.
2025-10-02 15:12:03 -07:00

89 lines
2.7 KiB
Swift

import Foundation
import LlamaStackClient
func convertToNativeSwiftType(_ value: Any) -> Any {
switch value {
case let number as NSNumber:
if CFGetTypeID(number) == CFBooleanGetTypeID() {
return number.boolValue
}
if floor(number.doubleValue) == number.doubleValue {
return number.intValue
}
return number.doubleValue
case let string as String:
return string
case let array as [Any]:
return array.map(convertToNativeSwiftType)
case let dict as [String: Any]:
return dict.mapValues(convertToNativeSwiftType)
case is NSNull:
return NSNull()
default:
return value
}
}
public class SystemDefaultGenerator {
public init() {}
public func gen() -> PromptTemplate {
let templateStr = """
Cutting Knowledge Date: December 2023
Today Date: {{ today }}
"""
let dateFormatter = DateFormatter()
dateFormatter.dateFormat = "dd MMMM yyyy"
return PromptTemplate(
template: templateStr,
data: ["today": dateFormatter.string(from: Date())]
)
}
}
public class FunctionTagCustomToolGenerator {
public init() {}
public func gen(customTools: [Components.Schemas.ToolDefinition]) throws -> PromptTemplate {
// TODO: required params
// TODO: {{#unless @last}},{{/unless}}
let templateStr = """
You are an expert in composing functions. You are given a question and a set of possible functions.
Based on the question, you will need to make one or more function/tool calls to achieve the purpose.
If none of the function can be used, point it out. If the given question lacks the parameters required by the function,
also point it out. You should only return the function call in tools call sections.
If you decide to invoke any of the function(s), you MUST put it in the format of [func_name1(params_name1=params_value1, params_name2=params_value2...), func_name2(params)]
You SHOULD NOT include any other text in the response.
Here is a list of functions in JSON format that you can invoke.
[
{% for t in custom_tools %}
{
"name": "{{t.tool_name}}",
"description": "{{t.description}}",
"input_schema": { {{t.input_schema}} }
}
{{/let}}
{% endfor -%}
]
"""
let encoder = JSONEncoder()
return PromptTemplate(
template: templateStr,
data: ["custom_tools": try customTools.map {
let data = try encoder.encode($0)
let obj = try JSONSerialization.jsonObject(with: data)
return convertToNativeSwiftType(obj)
}]
)
}
}