ТЗ: Стриминговый чат-интерфейс с ИИ-ассистентом на Vercel AI SDK и Markdown рендерингом

// app/api/chat/route.ts
import { NextRequest } from 'next/server'

export const dynamic = 'force-dynamic'

export async function POST(req: NextRequest) {
  const { messages } = await req.json()
  const apiKey = process.env.GEMINI_API_KEY

  if (!apiKey) {
    return new Response('API key not configured', { status: 500 })
  }

  // Запрос к LLM со стримингом
  const response = await fetch(
    `https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash:streamGenerateContent?alt=sse&key=${apiKey}`,
    {
      method: 'POST',
      headers: { 'Content-Type': 'application/json' },
      body: JSON.stringify({
        contents: messages.map((m: { role: string; content: string }) => ({
          role: m.role === 'user' ? 'user' : 'model',
          parts: [{ text: m.content }]
        })),
        generationConfig: {
          thinkingConfig: { thinkingBudget: 0 },
          maxOutputTokens: 2048
        }
      }),
      signal: req.signal // Проброс отмены клиента
    }
  )

  const reader = response.body?.getReader()
  const encoder = new TextEncoder()
  const decoder = new TextDecoder()

  const stream = new ReadableStream({
    async start(controller) {
      if (!reader) {
        controller.close()
        return
      }

      let buffer = ''
      try {
        while (true) {
          const { done, value } = await reader.read()
          if (done) break

          buffer += decoder.decode(value, { stream: true })
          const lines = buffer.split('\n')
          buffer = lines.pop() || ''

          for (const line of lines) {
            const trimmed = line.trim()
            if (!trimmed.startsWith('data:')) continue
            const dataStr = trimmed.slice(5).trim()
            if (dataStr === '[DONE]') continue

            try {
              const parsed = JSON.parse(dataStr)
              const text = parsed.candidates?.[0]?.content?.parts?.[0]?.text
              if (text) controller.enqueue(encoder.encode(text))
            } catch {}
          }
        }
      } catch (err) {
        controller.error(err)
      } finally {
        controller.close()
      }
    }
  })

  return new Response(stream, {
    headers: { 'Content-Type': 'text/plain; charset=utf-8' }
  })
}