Images, video and audio

For images and video, query the model catalog with your key and inspect the exact endpoint, parameters and example. For audio, use the model-selection guidance below. Availability and options depend on the model and deployment; one model need not support all media types. Examples require Python 3 and the requests package (python -m pip install requests). Set LAZU_API_KEY and the model variables below.

Generate an image

Set LAZU_IMAGE_MODEL to a model supporting /v1/images/generations. The response can include data[].url or data[].b64_json; handle the actual returned form. Size, quality and output format depend on the model. Do not assume generated URLs are permanent.

import os
import requests
 
origin = os.environ.get("LAZU_API_ORIGIN", "https://api.lazu.ai").rstrip("/")
response = requests.post(origin + "/v1/images/generations",
    headers={"Authorization": "Bearer " + os.environ["LAZU_API_KEY"]},
    json={"model": os.environ["LAZU_IMAGE_MODEL"], "prompt": "A blue ceramic cup"},
    timeout=180)
response.raise_for_status()
print(response.json()["data"])

Submit and poll a video

Set LAZU_VIDEO_MODEL to a model supporting /v1/videos. A successful submission returns HTTP 202 and a job ID. Poll the same job with the same key: pending and running are not final; succeeded provides artifact information, and failed includes an error. A local wait timeout does not cancel or fail the job. Save the ID and resume polling; do not submit another paid job just because the wait ended.

import os
import time
import requests
 
origin = os.environ.get("LAZU_API_ORIGIN", "https://api.lazu.ai").rstrip("/")
headers = {"Authorization": "Bearer " + os.environ["LAZU_API_KEY"]}
response = requests.post(origin + "/v1/videos", headers=headers,
    json={"model": os.environ["LAZU_VIDEO_MODEL"], "prompt": "Ocean waves at sunrise"},
    timeout=180)
response.raise_for_status()
job_id = response.json()["id"]
print("Save job ID:", job_id, flush=True)
deadline = time.monotonic() + 600
while time.monotonic() < deadline:
    response = requests.get(origin + "/v1/videos/" + job_id,
                            headers=headers, timeout=30)
    if response.status_code in (429, 503):
        retry_after = response.headers.get("Retry-After", "5")
        delay = float(retry_after) if retry_after.isdecimal() else 5
        if delay >= deadline - time.monotonic():
            print("Still waiting; resume GET for job:", job_id)
            break
        time.sleep(max(1, delay))
        continue
    response.raise_for_status()
    job = response.json()
    if job["status"] == "succeeded":
        print(job.get("artifact", {}))
        break
    if job["status"] == "failed":
        raise RuntimeError(job.get("error", {"message": "Video failed"}))
    time.sleep(5)
else:
    print("Still waiting; resume GET for job:", job_id)
# A local timeout does not cancel the remote job. Keep job_id for later GETs.

Generate speech or transcribe audio

Set LAZU_AUDIO_MODEL to a speech model and LAZU_VOICE to a supported voice. /v1/audio/speech returns binary audio, not JSON. For transcription, choose a compatible model and upload a local audio file to /v1/audio/transcriptions as multipart data. These are separate model capabilities.

The catalog currently has no speech/transcription endpoint types. Audio modality alone cannot identify either capability. Obtain the exact model ID, endpoint and supported voice from your deployment operator or Lazu support, and confirm that the model is accessible to your API key. Do not select these models by audio modality alone. Set LAZU_TRANSCRIPTION_MODEL to the confirmed transcription model and LAZU_AUDIO_FILE to your local audio path.

import os
from pathlib import Path
import requests
 
origin = os.environ.get("LAZU_API_ORIGIN", "https://api.lazu.ai").rstrip("/")
headers = {"Authorization": "Bearer " + os.environ["LAZU_API_KEY"]}
response = requests.post(origin + "/v1/audio/speech", headers=headers,
    json={"model": os.environ["LAZU_AUDIO_MODEL"], "input": "Hello from Lazu",
          "voice": os.environ["LAZU_VOICE"], "response_format": "mp3"}, timeout=180)
response.raise_for_status()
Path("speech.mp3").write_bytes(response.content)

import os
import requests
 
origin = os.environ.get("LAZU_API_ORIGIN", "https://api.lazu.ai").rstrip("/")
with open(os.environ["LAZU_AUDIO_FILE"], "rb") as audio:
    response = requests.post(origin + "/v1/audio/transcriptions",
        headers={"Authorization": "Bearer " + os.environ["LAZU_API_KEY"]},
        data={"model": os.environ["LAZU_TRANSCRIPTION_MODEL"]},
        files={"file": audio}, timeout=180)
response.raise_for_status()
print(response.json())

Errors and results

On failure, preserve the request or job ID and inspect the error code. If submission times out before a job ID arrives, check the video job list (GET /v1/videos) or contact support before resubmitting. For a succeeded job, use artifact.url when available; if only artifact.file_id is returned, retrieve it through the Files API. Reconcile charges through Billing.

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