wehub-resource-sync
66 lines
2.1 KiB
Swift
66 lines
2.1 KiB
Swift
//
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// LLMState.swift
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// MNNLLMiOS
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//
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// Created by 游薪渝(揽清) on 2025/1/15.
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//
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import ExyteChat
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import UIKit
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actor LLMState {
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private var isProcessing: Bool = false
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func setProcessing(_ value: Bool) {
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isProcessing = value
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}
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func getProcessing() -> Bool {
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return isProcessing
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}
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func processContent(_ content: String, llm: LLMInferenceEngineWrapper?, showPerformance _: Bool, completion: @escaping (String) -> Void) {
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llm?.processInput(content, withOutput: completion, showPerformance: true)
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}
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/// Processes multimodal (text + images) content using the MultimodalPrompt API.
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/// - Parameters:
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/// - content: Prompt template containing <img>placeholder</img> tags.
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/// - images: Dictionary mapping placeholder keys to UIImage instances.
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/// - llm: Inference engine wrapper.
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/// - showPerformance: Whether to output performance statistics.
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/// - completion: Streaming output callback.
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func processMultimodalContent(
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_ content: String,
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images: [String: UIImage],
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llm: LLMInferenceEngineWrapper?,
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showPerformance: Bool,
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completion: @escaping (String) -> Void
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) {
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llm?.processMultimodalInput(
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content,
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images: images,
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withOutput: completion,
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showPerformance: showPerformance
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)
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}
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/// Processes a batch of prompts and returns their responses.
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///
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/// This method delegates batch processing to the underlying inference engine wrapper.
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/// Responses are returned in the same order as the input prompts.
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/// - Parameters:
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/// - prompts: An array of prompt strings to process.
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/// - llm: The inference engine wrapper instance to use.
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/// - completion: A closure invoked with an array of response strings.
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func processBatchTestContent(_ prompts: [String], llm: LLMInferenceEngineWrapper?, completion: @escaping ([String]) -> Void) {
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guard let llm = llm else {
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completion([])
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return
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}
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llm.processBatchPrompts(prompts) { responses in
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completion(responses)
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}
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}
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}
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