Function handleStream

tools/model-gateway/server.mjs:250–429

(body, res, config)

}

async function handleStream(body, res, config) {
  const upstreamBody = anthropicToOpenAI(body, true, config)
  const upstreamResponse = await fetch(
    joinUrl(config.upstreamBaseUrl, config.upstreamChatPath),
    {
      method: 'POST',
      headers: buildUpstreamHeaders(config),
      body: JSON.stringify(upstreamBody),
    },
  )

  if (!upstreamResponse.ok || !upstreamResponse.body) {
    const text = await upstreamResponse.text()
    res.statusCode = upstreamResponse.status
    res.setHeader('content-type', 'application/json')
    res.end(text)
    return
  }

  res.writeHead(200, {
    'content-type': 'text/event-stream; charset=utf-8',
    'cache-control': 'no-cache, no-transform',
    connection: 'keep-alive',
  })

  const state = {
    messageId: `msg_${crypto.randomUUID().replace(/-/g, '')}`,
    textStarted: false,
    textIndex: 0,
    text: '',
    finishReason: null,
    usage: { input_tokens: 0, output_tokens: 0 },
    toolCalls: new Map(),
  }

  writeSse(res, 'message_start', {
    type: 'message_start',
    message: {
      id: state.messageId,
      type: 'message',
      role: 'assistant',
      model: body.model,
      content: [],
      stop_reason: null,
      stop_sequence: null,
      usage: state.usage,
    },
  })

  const decoder = new TextDecoder('utf8')
  let buffer = ''

  for await (const chunk of upstreamResponse.body) {
    buffer += decoder.decode(chunk, { stream: true })
    const parts = buffer.split('\n\n')
    buffer = parts.pop() ?? ''

    for (const part of parts) {