Integration docs for KaleidoVid speech, video, and local LLM APIs.

x-api-key: kvid_your_prefix_your_secret

Reading Score, Shared LLM, and LTX23 Video also accept:
Authorization: Bearer kvid_your_prefix_your_secret

Browser WebSocket clients should append `api_key=<YOUR_API_KEY>`
to the `ws_url` returned by POST /api/thai-asr/sessions.

curl -sS \
  -H "x-api-key: YOUR_API_KEY" \
  "https://kaleidovid.com/api/thai-asr/config"

{
  "language": "th",
  "mode": "benchmark_spike",
  "backend": "persistent_decoder",
  "engine": "typhoon",
  "defaults": {
    "sample_rate": 16000,
    "frame_ms": 20,
    "stream_chunk_ms": 80,
    "partial_interval_ms": 40,
    "min_decode_audio_ms": 240,
    "decode_window_ms": 1600,
    "vad": true
  },
  "notes": [
    "This spike measures websocket, VAD, and partial transcript latency for Thai ASR on the 8x4090 host."
  ],
  "tenant": {
    "team_id": "team_cuid",
    "team_name": "Acme Team",
    "key_prefix": "abcd1234"
  },
  "limits": {
    "requests_per_minute": 120,
    "concurrent_sessions": 3,
    "daily_audio_seconds": 3600,
    "today_audio_seconds_used": 420
  }
}

curl -sS \
  -X POST \
  -H "Content-Type: application/json" \
  -H "x-api-key: YOUR_API_KEY" \
  -d '{
    "sample_rate": 16000,
    "frame_ms": 20,
    "partial_interval_ms": 40,
    "min_decode_audio_ms": 240,
    "decode_window_ms": 1600,
    "vad": true
  }' \
  "https://kaleidovid.com/api/thai-asr/sessions"

{
  "session_id": "e6a4c4f6c69f4ca1aa8f9b3ad8d515f0",
  "mode": "benchmark_spike",
  "language": "th",
  "engine": "typhoon",
  "backend": "persistent_decoder",
  "ws_url": "wss://kaleidovid.com/api/thai-asr/stream?session_id=e6a4c4f6c69f4ca1aa8f9b3ad8d515f0",
  "config": {
    "sample_rate": 16000,
    "frame_ms": 20,
    "partial_interval_ms": 40,
    "min_decode_audio_ms": 240,
    "decode_window_ms": 1600,
    "vad": true,
    "benchmark_label": null
  },
  "sla_targets": {
    "speech_detected_p95_ms": 60,
    "first_partial_p95_ms": 250,
    "final_after_eou_p95_ms": 800
  },
  "tenant": {
    "team_id": "team_cuid",
    "team_name": "Acme Team",
    "key_prefix": "abcd1234"
  }
}

const API_KEY = "YOUR_API_KEY";
const HTTP_BASE = "https://kaleidovid.com";

const config = await fetch(`${HTTP_BASE}/api/thai-asr/config`, {
  headers: { "x-api-key": API_KEY },
}).then(async (response) => {
  if (!response.ok) throw new Error(await response.text());
  return response.json();
});

const session = await fetch(`${HTTP_BASE}/api/thai-asr/sessions`, {
  method: "POST",
  headers: {
    "Content-Type": "application/json",
    "x-api-key": API_KEY,
  },
  body: JSON.stringify({
    sample_rate: 16000,
    frame_ms: 20,
    partial_interval_ms: 40,
    min_decode_audio_ms: 240,
    decode_window_ms: 1600,
    vad: true,
  }),
}).then(async (response) => {
  if (!response.ok) throw new Error(await response.text());
  return response.json();
});

const wsUrl = `${session.ws_url}&api_key=${encodeURIComponent(API_KEY)}`;
const socket = new WebSocket(wsUrl);

socket.onmessage = (event) => {
  const payload = JSON.parse(event.data);
  switch (payload.type) {
    case "ready":
      socket.send(JSON.stringify({
        type: "start",
        sample_rate: 16000,
        frame_ms: 20,
        partial_interval_ms: 40,
        min_decode_audio_ms: 240,
        decode_window_ms: 1600,
        vad: true,
      }));
      break;
    case "partial":
    case "stabilized_partial":
      console.log("live", payload.text);
      break;
    case "final":
      console.log("final", payload.text, payload.segments);
      break;
    case "error":
      console.error(payload.code, payload.error);
      break;
  }
};

// `pcmChunks` must contain raw PCM16LE mono audio frames.
// Do not send WAV headers after the socket is started.
for (const chunk of pcmChunks) {
  socket.send(chunk);
}

socket.send(JSON.stringify({ type: "flush" }));
socket.send(JSON.stringify({ type: "end" }));

{
  "type": "final",
  "session_id": "e6a4c4f6c69f4ca1aa8f9b3ad8d515f0",
  "engine": "typhoon",
  "backend": "persistent_decoder",
  "text": "สวัสดีครับ นี่คือการทดสอบระบบถอดเสียงภาษาไทยแบบหน่วงต่ำ",
  "segments": [
    {
      "start": 0.0,
      "end": 2.84,
      "text": "สวัสดีครับ นี่คือการทดสอบระบบถอดเสียงภาษาไทยแบบหน่วงต่ำ"
    }
  ],
  "audio_ms": 2840,
  "latency_ms": 134,
  "queue_ms": 0,
  "decode_ms": 134,
  "processing_time_ms": 133,
  "audio_duration_ms": 2840
}

curl -sS \
  -H "x-api-key: YOUR_API_KEY" \
  -F "student_audio=@student.wav" \
  -F "reference_text=สวัสดีครับ วันนี้เราจะเรียนภาษาไทย" \
  -F "student_id=student_001" \
  -F "lesson_id=lesson_01" \
  -F "language=th" \
  -F "include_pronunciation=true" \
  "https://kaleidovid.com/api/reading-score"

# pip install requests

import json
import time
import requests

ENDPOINT_URL = "https://kaleidovid.com/api/reading-score"
BASE_URL = ENDPOINT_URL.removesuffix("/api/reading-score")
API_KEY = "YOUR_API_KEY"

def read_result_or_poll(response):
    if response.status_code != 202:
        response.raise_for_status()
        return response.json()

    queued = response.json()
    status_path = queued.get("statusPath")
    if not status_path:
        return queued

    while True:
        status_response = requests.get(
            f"{BASE_URL}{status_path}",
            headers={"x-api-key": API_KEY},
            timeout=30,
        )
        status_response.raise_for_status()
        status_payload = status_response.json()
        if not status_payload.get("ready"):
            time.sleep(2)
            continue
        if status_payload.get("successful"):
            return status_payload.get("result")
        raise RuntimeError(status_payload.get("error", "Reading score failed"))

with open("student.wav", "rb") as student_audio:
    response = requests.post(
        ENDPOINT_URL,
        headers={"x-api-key": API_KEY},
        data={
            "reference_text": "สวัสดีครับ วันนี้เราจะเรียนภาษาไทย",
            "student_id": "student_001",
            "lesson_id": "lesson_01",
            "language": "th",
            "include_pronunciation": "true",
        },
        files={
            "student_audio": ("student.wav", student_audio, "audio/wav"),
        },
        timeout=300,
    )

payload = read_result_or_poll(response)
print(json.dumps(payload, ensure_ascii=False, indent=2))

curl -sS \
  -H "x-api-key: YOUR_API_KEY" \
  "https://kaleidovid.com/api/llm/v1/models"

{
  "object": "list",
  "data": [
    {
      "id": "qwen3-4b",
      "object": "model",
      "owned_by": "kaleidovid-local"
    }
  ]
}

curl -sS \
  -X POST \
  -H "Content-Type: application/json" \
  -H "x-api-key: YOUR_API_KEY" \
  -d '{
    "model": "qwen3-4b",
    "messages": [
      { "role": "system", "content": "You are a helpful assistant." },
      { "role": "user", "content": "Explain why a shared local LLM endpoint is useful." }
    ],
    "temperature": 0.4,
    "max_tokens": 256
  }' \
  "https://kaleidovid.com/api/llm/v1/chat/completions"

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://kaleidovid.com/api/llm/v1",
)

response = client.chat.completions.create(
    model="qwen3-4b",
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "Explain the API in one short paragraph."},
    ],
    temperature=0.4,
    max_tokens=256,
)

print(response.choices[0].message.content)

curl -sS \
  -X POST \
  -H "Content-Type: application/json" \
  -H "x-api-key: YOUR_API_KEY" \
  -d '{
    "model": "ltx23-standard",
    "prompt": "A cinematic product shot with gentle camera motion.",
    "image": {
      "url": "https://example.com/input.png"
    },
    "duration": 5,
    "aspect_ratio": "16:9",
    "resolution": "720p",
    "seed": -1
  }' \
  "https://kaleidovid.com/api/ltx23/v1/videos/generations"

{
  "request_id": "6bcd2f29-4b74-4479-a3b3-f71a50a77dab",
  "status": "queued",
  "model": "ltx23-standard"
}

curl -sS \
  -H "x-api-key: YOUR_API_KEY" \
  "https://kaleidovid.com/api/ltx23/v1/videos/6bcd2f29-4b74-4479-a3b3-f71a50a77dab"

{
  "request_id": "6bcd2f29-4b74-4479-a3b3-f71a50a77dab",
  "status": "done",
  "model": "ltx23-standard",
  "video": {
    "url": "/uploads/generations/ltx23/ltx23_av_20260426_abcdef.mp4"
  }
}

# pip install requests

import base64
import mimetypes
import time
from pathlib import Path

import requests

API_KEY = "YOUR_API_KEY"
BASE_URL = "https://kaleidovid.com/api/ltx23/v1"
image_path = Path("input.png")
mime_type = mimetypes.guess_type(image_path.name)[0] or "image/png"
image_data_url = (
    f"data:{mime_type};base64,"
    + base64.b64encode(image_path.read_bytes()).decode("ascii")
)

start = requests.post(
    f"{BASE_URL}/videos/generations",
    headers={"x-api-key": API_KEY},
    json={
        "model": "ltx23-standard",
        "prompt": "A cinematic product shot with gentle camera motion.",
        "image": {"url": image_data_url},
        "duration": 5,
        "aspect_ratio": "16:9",
        "resolution": "720p",
        "seed": -1,
    },
    timeout=180,
)
start.raise_for_status()
request_id = start.json()["request_id"]

while True:
    status = requests.get(f"{BASE_URL}/videos/{request_id}", headers={"x-api-key": API_KEY}, timeout=60)
    status.raise_for_status()
    payload = status.json()
    if payload["status"] in {"done", "failed", "canceled"}:
        break
    time.sleep(5)

print(payload)

{
  "request_id": "6bcd2f29-4b74-4479-a3b3-f71a50a77dab",
  "status": "failed",
  "model": "ltx23-standard",
  "error": "Remote LTX image-to-video failed: upstream message"
}