Azure API 測試頁

<script src="./azure-client.js"></script>
<script>
const result = await WebpageAzure.translate({
  text: "The API key is protected by the server.",
  to: "zh-Hant"
});
console.log(result.result[0].translations[0].text);
</script>

<script src="./azure-client.js"></script>
<script>
const audioBlob = await WebpageAzure.speak({
  text: "大家好，這是語音合成測試。",
  voice: "zh-TW-HsiaoChenNeural",
  format: "mp3"
});
const audio = new Audio(URL.createObjectURL(audioBlob));
audio.play();
</script>

<input id="audio-file" type="file" accept="audio/wav">
<script src="./azure-client.js"></script>
<script>
const file = document.querySelector("#audio-file").files[0];
const result = await WebpageAzure.recognize(file, {
  language: "zh-TW"
});
console.log(result.result.DisplayText);
</script>

<input id="image-file" type="file" accept="image/*">
<script src="./azure-client.js"></script>
<script>
const file = document.querySelector("#image-file").files[0];
const result = await WebpageAzure.vision(file, {
  features: "read,tags,objects"
});
console.log(result.result);
</script>

<input id="image-file" type="file" accept="image/*">
<script src="./azure-client.js"></script>
<script>
const textResult = await WebpageAzure.contentSafety.text({
  text: "這是一段要檢查的文字"
});

const file = document.querySelector("#image-file").files[0];
const imageResult = await WebpageAzure.contentSafety.image(file);
console.log(textResult, imageResult);
</script>

<script src="./azure-client.js"></script>
<script>
const result = await WebpageAzure.sentiment({
  language: "zh-Hant",
  text: "這個服務很好用。"
});
console.log(result.result.results.documents[0].sentiment);
</script>

<input id="document-file" type="file" accept="application/pdf,image/*">
<script src="./azure-client.js"></script>
<script>
const file = document.querySelector("#document-file").files[0];
const submitted = await WebpageAzure.document.analyze(file, {
  modelId: "prebuilt-read"
});

let job = submitted.job;
while (job.status === "running" || job.status === "notStarted") {
  await new Promise((resolve) => setTimeout(resolve, 1500));
  job = (await WebpageAzure.document.job(job.id)).job;
}
console.log(job);
</script>

<script src="./azure-client.js"></script>
<script>
const socket = await WebpageAzure.voiceLive({
  model: "gpt-realtime-mini"
});
socket.addEventListener("message", (event) => {
  console.log(JSON.parse(event.data));
});
</script>