story-generator/supabase/functions/process-audio/index.ts

import { serve } from 'https://deno.land/std@0.168.0/http/server.ts'
import { createClient } from 'https://esm.sh/@supabase/supabase-js@2'
import { Configuration, OpenAIApi } from 'https://esm.sh/openai@3.1.0'

// Configurar OpenAI
const openaiConfig = new Configuration({
  apiKey: Deno.env.get('OPENAI_API_KEY')
})
const openai = new OpenAIApi(openaiConfig)

// Configurar Supabase
const supabaseUrl = Deno.env.get('SUPABASE_URL')
const supabaseAnonKey = Deno.env.get('SUPABASE_ANON_KEY')
const supabase = createClient(supabaseUrl, supabaseAnonKey)

serve(async (req) => {
  try {
    // Extrair dados do webhook
    const { record } = await req.json()
    const { id, audio_url, story_id } = record

    // Atualizar status para processing
    await supabase
      .from('story_recordings')
      .update({ status: 'processing' })
      .eq('id', id)

    // Buscar texto original da história
    const { data: storyData } = await supabase
      .from('stories')
      .select('content')
      .eq('id', story_id)
      .single()

    const originalText = storyData.content.pages[0].text

    // 1. Transcrever áudio com Whisper
    const audioResponse = await fetch(audio_url)
    const audioBlob = await audioResponse.blob()
    
    const transcription = await openai.createTranscription(
      audioBlob,
      'whisper-1',
      'pt',
      'verbose_json'
    )

    // 2. Analisar com GPT-4
    const analysis = await openai.createChatCompletion({
      model: "gpt-4",
      messages: [
        {
          role: "system",
          content: `Você é um especialista em análise de leitura infantil. 
          Analise a transcrição comparando com o texto original.
          Forneça uma análise detalhada em formato JSON com métricas de 0-100.`
        },
        {
          role: "user",
          content: `
          Texto Original: "${originalText}"
          Transcrição: "${transcription.data.text}"
          
          Analise e retorne um JSON com:
          {
            "metrics": {
              "fluency": number,
              "pronunciation": number,
              "accuracy": number,
              "comprehension": number
            },
            "feedback": {
              "strengths": string[],
              "improvements": string[],
              "suggestions": string
            },
            "details": {
              "wordsPerMinute": number,
              "pauseCount": number,
              "errorCount": number,
              "selfCorrections": number
            }
          }`
        }
      ]
    })

    const analysisResult = JSON.parse(analysis.data.choices[0].message.content)

    // 3. Atualizar registro com resultados
    await supabase
      .from('story_recordings')
      .update({
        transcription: transcription.data.text,
        metrics: analysisResult.metrics,
        feedback: analysisResult.feedback,
        details: analysisResult.details,
        status: 'analyzed',
        processed_at: new Date().toISOString()
      })
      .eq('id', id)

    return new Response(
      JSON.stringify({ success: true }),
      { headers: { 'Content-Type': 'application/json' } }
    )

  } catch (error) {
    console.error('Erro:', error)

    // Atualizar registro com erro
    if (error.record?.id) {
      await supabase
        .from('story_recordings')
        .update({
          status: 'error',
          error_message: error.message
        })
        .eq('id', error.record.id)
    }

    return new Response(
      JSON.stringify({ error: error.message }),
      { status: 500, headers: { 'Content-Type': 'application/json' } }
    )
  }
})