Video Slicer Serverless API
Video Slicer
~39.74s
POST /v2/video-slicer · submit + poll 1# pip install "segmind>=1.1.0"
2# export SEGMIND_API_KEY="YOUR_API_KEY"
3from segmind import SegmindClient, InferenceFailed, InferenceTimeout
4
5# Async (v2) — recommended for long-running / video models.
6# run() blocks up to 600s; submit_async + job.wait(timeout=...) sets a longer
7# deadline and keeps the request_id so you can re-poll later.
8client = SegmindClient() # reads SEGMIND_API_KEY
9payload = {
10 "video": "https://segmind-sd-models.s3.amazonaws.com/display_images/liveportrait-output.mp4",
11 "time_range": "00:00:02 - 00:00:03",
12}
13job = client.submit_async("video-slicer", **payload)
14print(job.request_id) # available immediately
15try:
16 result = job.wait(timeout=900, interval=2.0)
17 print(result["status"]) # COMPLETED
18 print(result.get("output")) # model output (e.g. video URL)
19except InferenceTimeout as e:
20 print("still running:", e.request_id) # re-poll later with this id
21except InferenceFailed as e:
22 print("failed:", e.detail)
23
24# Fast models (<=600s) can use the one-liner instead:
25# result = segmind.run("video-slicer", **payload) 1# pip install "segmind>=1.1.0"
2# export SEGMIND_API_KEY="YOUR_API_KEY"
3from segmind import SegmindClient, InferenceFailed, InferenceTimeout
4
5# Async (v2) — recommended for long-running / video models.
6# run() blocks up to 600s; submit_async + job.wait(timeout=...) sets a longer
7# deadline and keeps the request_id so you can re-poll later.
8client = SegmindClient() # reads SEGMIND_API_KEY
9payload = {
10 "video": "https://segmind-sd-models.s3.amazonaws.com/display_images/liveportrait-output.mp4",
11 "time_range": "00:00:02 - 00:00:03",
12}
13job = client.submit_async("video-slicer", **payload)
14print(job.request_id) # available immediately
15try:
16 result = job.wait(timeout=900, interval=2.0)
17 print(result["status"]) # COMPLETED
18 print(result.get("output")) # model output (e.g. video URL)
19except InferenceTimeout as e:
20 print("still running:", e.request_id) # re-poll later with this id
21except InferenceFailed as e:
22 print("failed:", e.detail)
23
24# Fast models (<=600s) can use the one-liner instead:
25# result = segmind.run("video-slicer", **payload)API Endpoint
POST
https://api.segmind.com/v1/video-slicerParameters
time_rangerequiredstringTime range slice in format HH:MM:SS
Default:
"00:00:02 - 00:00:03"videorequiredstring (uri)URL of the video to be sliced
Default:
"https://segmind-sd-models.s3.amazonaws.com/display_images/liveportrait-output.mp4"Response Type
Returns: Video
Asynchronous requests (v2)
Use Async for video, long-running (>~60s), or high-concurrency workloads; Sync is simplest for fast image & LLM calls. Async submits a request and you poll it to completion.
- 1
POST /v2/video-slicerSubmit — returns request_id, status_url, response_url
- 2
GET /v2/requests/{id}/statusPoll — until COMPLETED or FAILED
- 3
GET /v2/requests/{id}Result — final response body
Status states
QUEUED— Accepted, waiting for a worker
PROCESSING— Running on a worker
COMPLETED— Done — result body is ready
FAILED— Errored (incl. content/RAI blocks)
- A FAILED request is served as HTTP 422 — the body still carries the error detail.
- An unknown or expired request_id returns HTTP 404.
- Results are retained for 1 hour, then expire.
- Content / RAI blocks surface as FAILED, not a separate state.
- Track completion by polling the status endpoint.
Common Error Codes
The API returns standard HTTP status codes. Detailed error messages are provided in the response body.
400
Bad Request
Invalid parameters or request format
401
Unauthorized
Missing or invalid API key
403
Forbidden
Insufficient permissions
404
Not Found
Model or endpoint not found
406
Insufficient Credits
Not enough credits to process request
429
Rate Limited
Too many requests
500
Server Error
Internal server error
502
Bad Gateway
Service temporarily unavailable
504
Timeout
Request timed out