75 lines
2.3 KiB
TypeScript
75 lines
2.3 KiB
TypeScript
/**
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* AI 故事分析 Composable
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* 用於分析故事並提取資產
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*/
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import { useAIProvider } from './useAIProvider'
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import { buildStoryAnalysisPrompt, type StoryAnalysisInput } from '~/utils/ai/prompts'
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import { getTextModel } from '~/utils/storage'
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import { DEFAULT_TEXT_MODEL } from '~/utils/clients/gemini-models'
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import { getVisionModel } from '~/utils/storage'
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import { DEFAULT_VISION_MODEL } from '~/utils/clients/gemini-models'
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import type { StoryAnalysis } from '~/types/storyboard'
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export function useAIStoryboardAnalysis() {
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const isLoading = ref(false)
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const error = ref<string | null>(null)
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async function analyze(input: StoryAnalysisInput): Promise<StoryAnalysis> {
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isLoading.value = true
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error.value = null
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try {
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// 如果有圖片，使用視覺模型；否則使用文字模型
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const modelName = input.styleImage
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? (getVisionModel() || DEFAULT_VISION_MODEL)
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: (getTextModel() || DEFAULT_TEXT_MODEL)
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const provider = useAIProvider(modelName)
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let prompt = buildStoryAnalysisPrompt(input)
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// 如果有風格圖片，需要傳遞圖片給 API
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if (input.styleImage) {
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// 這裡需要根據 provider 類型處理圖片
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// 暫時先傳遞文字 prompt，實際實作時需要處理圖片
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const result = await provider.analyzeCamera({
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prompt,
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image: {
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mimeType: 'image/jpeg',
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data: input.styleImage.replace(/^data:image\/\w+;base64,/, '')
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}
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})
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// 解析 JSON 結果
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const jsonMatch = result.match(/\{[\s\S]*\}/)
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if (jsonMatch) {
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return JSON.parse(jsonMatch[0]) as StoryAnalysis
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}
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throw new Error('無法解析分析結果')
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} else {
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const result = await provider.generateStoryboard(prompt)
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// 解析 JSON 結果
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const jsonMatch = result.match(/\{[\s\S]*\}/)
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if (jsonMatch) {
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return JSON.parse(jsonMatch[0]) as StoryAnalysis
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}
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throw new Error('無法解析分析結果')
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}
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} catch (err) {
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const errorMessage = err instanceof Error ? err.message : '未知錯誤'
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error.value = errorMessage
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throw err
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} finally {
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isLoading.value = false
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}
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}
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return {
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analyze,
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isLoading: readonly(isLoading),
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error: readonly(error)
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}
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}
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