Flux Inpaint Serverless API

Flux Inpainting is a powerful image editing tool designed to effortlessly edit and enhance your images. It's perfect for tasks like removing unwanted objects, restoring damaged photos, and creating artistic effects.

~28.48s
PlaygroundAPI
Pricing
POST /v2/flux-inpaint · submit + poll
 1# pip install "segmind>=1.1.0"
 2# export SEGMIND_API_KEY="YOUR_API_KEY"
 3import segmind
 4
 5# Async (v2): submit to the queue and block until COMPLETED.
 6# run() returns the final result dict (600s deadline, 1.0s poll by default).
 7result = segmind.run(
 8    "flux-inpaint",
 9    base64=False,
10    guidance_scale=3.5,
11    image="https://segmind-sd-models.s3.amazonaws.com/display_images/flux-inapint-ip.jpg",
12    image_format="jpeg",
13    mask="https://segmind-sd-models.s3.amazonaws.com/display_images/flux-inpaint-mask.jpeg",
14    negative_prompt="bad quality, painting, blur",
15    num_inference_steps=25,
16    prompt="huge ship sailing",
17    quality=95,
18    sampler="euler",
19    samples=1,
20    scheduler="simple",
21    seed=12467,
22    strength=0.9,
23)
24print(result["status"])                      # COMPLETED
25print(result.get("output"))                  # model output (e.g. media URL)
26print(result["metrics"]["inference_time"])   # server compute seconds
27
28# --- Or submit + poll manually (track request_id, control the cadence) ---
29from segmind import SegmindClient, InferenceFailed, InferenceTimeout
30
31client = SegmindClient()                      # reads SEGMIND_API_KEY
32payload = {
33    "base64": False,
34    "guidance_scale": 3.5,
35    "image": "https://segmind-sd-models.s3.amazonaws.com/display_images/flux-inapint-ip.jpg",
36    "image_format": "jpeg",
37    "mask": "https://segmind-sd-models.s3.amazonaws.com/display_images/flux-inpaint-mask.jpeg",
38    "negative_prompt": "bad quality, painting, blur",
39    "num_inference_steps": 25,
40    "prompt": "huge ship sailing",
41    "quality": 95,
42    "sampler": "euler",
43    "samples": 1,
44    "scheduler": "simple",
45    "seed": 12467,
46    "strength": 0.9,
47}
48job = client.submit_async("flux-inpaint", **payload)
49print(job.request_id)                         # available immediately
50try:
51    result = job.wait(timeout=600, interval=1.0)
52except InferenceTimeout as e:
53    print("still running:", e.request_id)
54except InferenceFailed as e:
55    print("failed:", e.detail)

API Endpoint

POSThttps://api.segmind.com/v1/flux-inpaint

Parameters

imagerequired
string (uri)

Input image

Default: "https://segmind-sd-models.s3.amazonaws.com/display_images/flux-inapint-ip.jpg"
maskrequired
string (uri)

Mask image

Default: "https://segmind-sd-models.s3.amazonaws.com/display_images/flux-inpaint-mask.jpeg"
promptrequired
string

Description of the image to be generated

Default: "huge ship sailing"
base64optional
boolean

Output as base64 encoded string

Default: false
guidance_scaleoptional
number

Guidance scale for the generation

Default: 3.5Range: 1 - 10
image_formatoptional
string

Output image format

Default: "jpeg"
Allowed values :
"jpeg""png""webp"
negative_promptoptional
string

Description of what to avoid in the image

Default: "bad quality, painting, blur"
num_inference_stepsoptional
integer

Number of inference steps

Default: 25Range: 10 - 75
qualityoptional
integer

Image quality setting for output

Default: 95Range: 10 - 100
sampleroptional
string

Sampling method for image generation

Default: "euler"
Allowed values (26 total):
"euler""euler_cfg_pp""euler_ancestra""leuler_ancestral_cfg_pp""heun""heunpp2""dpm_2""dpm_2_ancestral""lms""dpm_fast"+16 more
samplesoptional
integer

Number of samples to generate

Default: 1Range: 1 - 4
scheduleroptional
string

Scheduler for image generation

Default: "simple"
seedoptional
integer

Random seed for generation

Default: 12467
strengthoptional
number

Strength of the effect applied

Default: 0.9Range: 0 - 1

Response Type

Returns: Image

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. 1
    POST /v2/flux-inpaint

    Submit — returns request_id, status_url, response_url

  2. 2
    GET /v2/requests/{id}/status

    Poll — until COMPLETED or FAILED

  3. 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