GPT Image 1 Mini is OpenAI’s named Mini variant of the GPT Image 1 family. It accepts text and images and produces image outputs through the producer’s generation and editing workflows. Use it for ordinary creative briefs, visual concepts and changes to a supplied image where the Mini edition’s documented controls fit the task. Use Mini’s standard frame sizes and low input fidelity when preparing the task.
For a new image, describe the subject, scene, light, composition and style. For an edit, identify the required change and the source elements that should remain recognisable. A simple illustration brief can request a delivery bicycle beside a doorway, broad clean shapes and a restrained palette; a follow-up can change the background while retaining the selected composition. The documented direct workflows accept up to 32,000 prompt characters and one to ten outputs, which can provide alternatives for review.
Editing can use up to sixteen input images. Explain which image supplies the main subject, setting or treatment rather than leaving those roles ambiguous. GPT Image 1 Mini supports only low input_fidelity. The high setting available on GPT Image 1 is not an option for Mini. Input fidelity is separate from output rendering quality: choosing high-quality output does not enable a different source-preservation mode. Keep the preservation requirements explicit and inspect the relevant source details in the resulting asset.
A mask can guide a requested change to a selected area. The source and mask need the same format and dimensions, and the mask requires an alpha channel; the image-generation guide gives a requirement below 50 MB. With several source images, the mask applies to the first. A focused brief might change the colour of one object while retaining the scene’s overall framing. The mask is prompt-based guidance rather than a guaranteed geometric boundary, so check the adjacent area as well as the intended change.
The standard frame sizes are 1024 × 1024, 1536 × 1024 and 1024 × 1536 pixels, with automatic selection where supported. The rendering quality choices are low, medium, high and auto. These are separate from Mini’s low-only input fidelity. The custom high-resolution dimensions and xhigh or max levels of later GPT Image editions are not part of this Mini profile. Choose a frame that suits the placement and a quality level appropriate to a draft or final asset.
The producer supports PNG, JPEG and WebP output, with PNG as the default. JPEG and WebP can use compression from 0 to 100. Transparent, opaque and automatic backgrounds address different layout requirements; select PNG or WebP when an alpha channel is needed. A transparent object can be placed in a separate composition, while an opaque scene includes its own backdrop. Keep the selected output file rather than treating its encoded delivery representation as the final design artifact.
The producer image reference documents streaming with up to three partial images before completion. A preview can make progress visible, but only the final image should be retained as the finished result. For a sequence of edits, supply the chosen image again with the next concrete instruction. The manufacturer interface also supports batch processing.
Review the image’s lettering, layout-sensitive details and source-object appearance against the brief. GPT Image can still struggle with precise text placement, structured compositions and consistent recurring subjects across generations. Use the selected result for a narrower edit when a visible detail needs to change, keeping both the change and preservation requirements clear. The useful Mini result is a complete image for a defined creative task, prepared with the standard sizes and fidelity controls that this exact edition provides.
", "aboutText": "GPT Image 1 Mini is OpenAI’s named Mini variant of the GPT Image 1 family. It accepts text and images and produces image outputs through the producer’s generation and editing workflows. Use it for ordinary creative briefs, visual concepts and changes to a supplied image where the Mini edition’s documented controls fit the task. Use Mini’s standard frame sizes and low input fidelity when preparing the task.\n\nFor a new image, describe the subject, scene, light, composition and style. For an edit, identify the required change and the source elements that should remain recognisable. A simple illustration brief can request a delivery bicycle beside a doorway, broad clean shapes and a restrained palette; a follow-up can change the background while retaining the selected composition. The documented direct workflows accept up to 32,000 prompt characters and one to ten outputs, which can provide alternatives for review.\n\nEditing can use up to sixteen input images. Explain which image supplies the main subject, setting or treatment rather than leaving those roles ambiguous. GPT Image 1 Mini supports only low input_fidelity. The high setting available on GPT Image 1 is not an option for Mini. Input fidelity is separate from output rendering quality: choosing high-quality output does not enable a different source-preservation mode. Keep the preservation requirements explicit and inspect the relevant source details in the resulting asset.\n\nA mask can guide a requested change to a selected area. The source and mask need the same format and dimensions, and the mask requires an alpha channel; the image-generation guide gives a requirement below 50 MB. With several source images, the mask applies to the first. A focused brief might change the colour of one object while retaining the scene’s overall framing. The mask is prompt-based guidance rather than a guaranteed geometric boundary, so check the adjacent area as well as the intended change.\n\nThe standard frame sizes are 1024 × 1024, 1536 × 1024 and 1024 × 1536 pixels, with automatic selection where supported. The rendering quality choices are low, medium, high and auto. These are separate from Mini’s low-only input fidelity. The custom high-resolution dimensions and xhigh or max levels of later GPT Image editions are not part of this Mini profile. Choose a frame that suits the placement and a quality level appropriate to a draft or final asset.\n\nThe producer supports PNG, JPEG and WebP output, with PNG as the default. JPEG and WebP can use compression from 0 to 100. Transparent, opaque and automatic backgrounds address different layout requirements; select PNG or WebP when an alpha channel is needed. A transparent object can be placed in a separate composition, while an opaque scene includes its own backdrop. Keep the selected output file rather than treating its encoded delivery representation as the final design artifact.\n\nThe producer image reference documents streaming with up to three partial images before completion. A preview can make progress visible, but only the final image should be retained as the finished result. For a sequence of edits, supply the chosen image again with the next concrete instruction. The manufacturer interface also supports batch processing.\n\nReview the image’s lettering, layout-sensitive details and source-object appearance against the brief. GPT Image can still struggle with precise text placement, structured compositions and consistent recurring subjects across generations. Use the selected result for a narrower edit when a visible detail needs to change, keeping both the change and preservation requirements clear. The useful Mini result is a complete image for a defined creative task, prepared with the standard sizes and fidelity controls that this exact edition provides.", "editorialOverlay": { "copy_fields": null, "copy_sha256": null, "copy_source": null, "html_sha256": "b872b5335a2d630b4bd2bc9cf2159cc3527790646fe1cf617d2ef61a9a93a6b0", "module_sha256": "ee9dc1c50b1e6a8fb7fa062030fcb4646b9aaaeb08be513b723a5a92a7290f06", "raw_model_unchanged": true, "schema": "ailoot-native-model-editorial-v1" }, "locale": "en", "methods": [ { "html": "openai/gpt-image-1-miniGPT Image 1 Mini creates and edits images from text and visual references within the GPT Image 1 family. It supports standard output sizes, masks and common image formats, with low input fidelity rather than the high-fidelity option of GPT Image 1.
This description covers the model’s capabilities. Available in Ailoot inputs, outputs and options are listed for the selected method below.
GPT Image 1 Mini is OpenAI’s named Mini variant of the GPT Image 1 family. It accepts text and images and produces image outputs through the producer’s generation and editing workflows. Use it for ordinary creative briefs, visual concepts and changes to a supplied image where the Mini edition’s documented controls fit the task. Use Mini’s standard frame sizes and low input fidelity when preparing the task.
For a new image, describe the subject, scene, light, composition and style. For an edit, identify the required change and the source elements that should remain recognisable. A simple illustration brief can request a delivery bicycle beside a doorway, broad clean shapes and a restrained palette; a follow-up can change the background while retaining the selected composition. The documented direct workflows accept up to 32,000 prompt characters and one to ten outputs, which can provide alternatives for review.
Editing can use up to sixteen input images. Explain which image supplies the main subject, setting or treatment rather than leaving those roles ambiguous. GPT Image 1 Mini supports only low input_fidelity. The high setting available on GPT Image 1 is not an option for Mini. Input fidelity is separate from output rendering quality: choosing high-quality output does not enable a different source-preservation mode. Keep the preservation requirements explicit and inspect the relevant source details in the resulting asset.
A mask can guide a requested change to a selected area. The source and mask need the same format and dimensions, and the mask requires an alpha channel; the image-generation guide gives a requirement below 50 MB. With several source images, the mask applies to the first. A focused brief might change the colour of one object while retaining the scene’s overall framing. The mask is prompt-based guidance rather than a guaranteed geometric boundary, so check the adjacent area as well as the intended change.
The standard frame sizes are 1024 × 1024, 1536 × 1024 and 1024 × 1536 pixels, with automatic selection where supported. The rendering quality choices are low, medium, high and auto. These are separate from Mini’s low-only input fidelity. The custom high-resolution dimensions and xhigh or max levels of later GPT Image editions are not part of this Mini profile. Choose a frame that suits the placement and a quality level appropriate to a draft or final asset.
The producer supports PNG, JPEG and WebP output, with PNG as the default. JPEG and WebP can use compression from 0 to 100. Transparent, opaque and automatic backgrounds address different layout requirements; select PNG or WebP when an alpha channel is needed. A transparent object can be placed in a separate composition, while an opaque scene includes its own backdrop. Keep the selected output file rather than treating its encoded delivery representation as the final design artifact.
The producer image reference documents streaming with up to three partial images before completion. A preview can make progress visible, but only the final image should be retained as the finished result. For a sequence of edits, supply the chosen image again with the next concrete instruction. The manufacturer interface also supports batch processing.
Review the image’s lettering, layout-sensitive details and source-object appearance against the brief. GPT Image can still struggle with precise text placement, structured compositions and consistent recurring subjects across generations. Use the selected result for a narrower edit when a visible detail needs to change, keeping both the change and preservation requirements clear. The useful Mini result is a complete image for a defined creative task, prepared with the standard sizes and fidelity controls that this exact edition provides.
POST /v1/images/generationstext, imageimage| Field | Type | Requirement | Values & limits | Default |
|---|---|---|---|---|
Fieldmodel | Typestring | RequirementRequired | Values & limits openai/gpt-image-1-mini | Default— |
Fieldprompt | Typestring | RequirementRequired | Values & limits Minimum length: 1 | Default— |
Fieldaspect_ratio | Typestring | RequirementOptional | Values & limits 1:1, 3:2, 2:3, auto | Default— |
Fieldquality | Typestring | RequirementOptional | Values & limits auto, low, medium, high | Default— |
Fieldbackground | Typestring | RequirementOptional | Values & limits auto, transparent, opaque | Default— |
Fieldn | Typeinteger | RequirementOptional | Values & limits Minimum: 1 Maximum: 10 | Default— |
Fieldinput_references | Typearray | RequirementOptional | Values & limits Minimum items: 0 Maximum items: 16 | Default— |
Fieldoutput_compression | Typeinteger | RequirementOptional | Values & limits Minimum: 0 Maximum: 100 | Default— |
Fieldprovider | Typeobject | RequirementOptional | Values & limits | Default— |
| Parameter | Contract |
|---|---|
Parametercontent_type | Contractapplication/json |
Parameterrequired | Contractmodel, prompt |
Parametermaterial_types | Contracttext, image |
Lifecycle: synchronous_result_then_owned_library
GET /v1/media/tasks/{task_id} · actual returned task_id or media library record
GET /v1/media/assets/{asset_id}/content
GET /v1/media/assets
GET /v1/media/assets/{asset_id}
The displayed rates estimate the cost before generation. The final charge is calculated from the cost recorded for the original generation. Measured output duration and forecast quantities are not the final billable quantity.
Tariff references do not add request options. Supported parameters are listed for the selected method.
Match each charge to the conditions shown. Use one rate for each set of alternative configurations.
| Configuration | Rate schedule | Forecast quantity | Charge |
|---|---|---|---|
| ConfigurationBase token rates | Rate scheduleBase rate | Forecast quantity— | Charge Input · Input tokens · Estimate for comparison only — / 1K tokens Output · Output tokens · Estimate for comparison only — / 1K tokens Input · Cache read · Estimate for comparison only — / 1K tokens Input · Cache write · Estimate for comparison only — / 1K tokens Input · Cache write, 1 hour · Estimate for comparison only — / 1K tokens |
| ConfigurationEstimated generation cost | Rate schedule— | Forecast quantityone generation estimate | Charge Output · Estimated generation cost · Estimate for comparison only $0.065536 estimate before generation This estimate is not an additional charge or a fixed rate for the completed generation. |
Ailoot reserves an estimated amount before a request. After the result, it settles the final charge from measured usage. Streaming settlement uses the final usage record. How reservation and settlement work →
set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\nexport AILOOT_API_KEY\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np={'model': 'openai/gpt-image-1-mini', 'prompt': 'a red panda astronaut floating in space, studio lighting'}\n\nPath("request.json").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/images/generations \\\n -H "Authorization: Bearer $AILOOT_API_KEY" -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport base64, json, os, subprocess\nfrom pathlib import Path\nfrom urllib.parse import urlsplit, urljoin\n\ndef save_images(items):\n if not items: raise SystemExit("No completed images; retain the full response")\n for index, item in enumerate(items):\n encoded=item.get("b64_json")\n uri=item.get("url", "")\n if not encoded and uri.startswith("data:image/"):\n header, separator, encoded=uri.partition(",")\n if not separator or ";base64" not in header: raise SystemExit("Unsupported image data URI")\n if encoded:\n raw=base64.b64decode(encoded,validate=True)\n elif uri:\n uri=urljoin("https://api.ailoot.ai",uri)\n parsed=urlsplit(uri)\n if parsed.scheme!="https" or not parsed.netloc or parsed.username or parsed.password:\n raise SystemExit("Invalid returned image URL")\n owned=parsed.netloc=="api.ailoot.ai" and parsed.path.startswith("/v1/media/assets/") and parsed.path.endswith("/content")\n args=["curl","--fail-with-body","--silent","--show-error",uri]\n if owned: args += ["-H","Authorization: Bearer "+os.environ["AILOOT_API_KEY"]]\n temporary=Path(f"image-{index}.bin")\n subprocess.run(args+["-o",str(temporary)],check=True)\n raw=temporary.read_bytes()\n temporary.unlink()\n else: raise SystemExit("Image has neither bytes nor URL")\n if not raw: raise SystemExit("Empty image result")\n ext="png" if raw.startswith(b"\\x89PNG") else "jpg" if raw.startswith(b"\\xff\\xd8") else "webp" if raw[:4]==b"RIFF" and raw[8:12]==b"WEBP" else "svg" if raw.lstrip().startswith((b"<svg",b"<?xml")) else "bin"\n Path(f"image-{index}.{ext}").write_bytes(raw)\n print("Every returned image saved; complete response metadata retained")\nsave_images(json.loads(Path("result.json").read_text())["data"])\nPY_RESULT\nDownload each returned image or save its Base64 contents
GET /v1/media/tasks/{task_id}GET /v1/media/assets/{asset_id}/contentGET /v1/media/assetsGET /v1/media/assets/{asset_id}set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/media/assets \\\n -H "Authorization: Bearer $AILOOT_API_KEY" -o owned-assets.json\n# Preserve every returned asset and follow its exact signed content URL. Do not construct a signed token.\nSave every completed image; retrieve each returned URL or decode its Base64 contents.
Retain the complete response and headers, every actual output, original returned identifiers and all usage fields. Recover the original operation without submitting creation again.
Keep the returned X-Client-Request-ID for reconciliation. Read only actual returned task_id/asset_id values or the owned media library; never build a task URL from the operation ID and never resubmit creation.
| Field | Type |
|---|---|
Fieldcreated | Type |
Fielddata[].url | Type |
Fielddata[].b64_json | Type |
Fieldusage | Type |
Ailoot Ultra openai/gpt-image-1-mini, gpt-image-1-mini
/v1/images
gpt-image-1-miniGPT Image 1 Mini creates and edits images from text and visual references within the GPT Image 1 family. It supports standard output sizes, masks and common image formats, with low input fidelity rather than the high-fidelity option of GPT Image 1.
This description covers the model’s capabilities. Available in Ailoot inputs, outputs and options are listed for the selected method below.
GPT Image 1 Mini is OpenAI’s named Mini variant of the GPT Image 1 family. It accepts text and images and produces image outputs through the producer’s generation and editing workflows. Use it for ordinary creative briefs, visual concepts and changes to a supplied image where the Mini edition’s documented controls fit the task. Use Mini’s standard frame sizes and low input fidelity when preparing the task.
For a new image, describe the subject, scene, light, composition and style. For an edit, identify the required change and the source elements that should remain recognisable. A simple illustration brief can request a delivery bicycle beside a doorway, broad clean shapes and a restrained palette; a follow-up can change the background while retaining the selected composition. The documented direct workflows accept up to 32,000 prompt characters and one to ten outputs, which can provide alternatives for review.
Editing can use up to sixteen input images. Explain which image supplies the main subject, setting or treatment rather than leaving those roles ambiguous. GPT Image 1 Mini supports only low input_fidelity. The high setting available on GPT Image 1 is not an option for Mini. Input fidelity is separate from output rendering quality: choosing high-quality output does not enable a different source-preservation mode. Keep the preservation requirements explicit and inspect the relevant source details in the resulting asset.
A mask can guide a requested change to a selected area. The source and mask need the same format and dimensions, and the mask requires an alpha channel; the image-generation guide gives a requirement below 50 MB. With several source images, the mask applies to the first. A focused brief might change the colour of one object while retaining the scene’s overall framing. The mask is prompt-based guidance rather than a guaranteed geometric boundary, so check the adjacent area as well as the intended change.
The standard frame sizes are 1024 × 1024, 1536 × 1024 and 1024 × 1536 pixels, with automatic selection where supported. The rendering quality choices are low, medium, high and auto. These are separate from Mini’s low-only input fidelity. The custom high-resolution dimensions and xhigh or max levels of later GPT Image editions are not part of this Mini profile. Choose a frame that suits the placement and a quality level appropriate to a draft or final asset.
The producer supports PNG, JPEG and WebP output, with PNG as the default. JPEG and WebP can use compression from 0 to 100. Transparent, opaque and automatic backgrounds address different layout requirements; select PNG or WebP when an alpha channel is needed. A transparent object can be placed in a separate composition, while an opaque scene includes its own backdrop. Keep the selected output file rather than treating its encoded delivery representation as the final design artifact.
The producer image reference documents streaming with up to three partial images before completion. A preview can make progress visible, but only the final image should be retained as the finished result. For a sequence of edits, supply the chosen image again with the next concrete instruction. The manufacturer interface also supports batch processing.
Review the image’s lettering, layout-sensitive details and source-object appearance against the brief. GPT Image can still struggle with precise text placement, structured compositions and consistent recurring subjects across generations. Use the selected result for a narrower edit when a visible detail needs to change, keeping both the change and preservation requirements clear. The useful Mini result is a complete image for a defined creative task, prepared with the standard sizes and fidelity controls that this exact edition provides.
POST /v1/images/generationstextimage| Field | Type | Requirement | Values & limits | Default |
|---|---|---|---|---|
Fieldmodel | Typestring | RequirementRequired | Values & limits gpt-image-1-mini | Default— |
Fieldprompt | Typestring | RequirementRequired | Values & limits Maximum length: 32,000 | Default— |
Fieldsize | Typestring | RequirementOptional | Values & limits 1024x1024, 1536x1024, 1024x1536, auto | Defaultauto |
Fieldbackground | Typestring | RequirementOptional | Values & limits transparent, opaque, auto | Defaultauto |
Fieldmoderation | Typestring | RequirementOptional | Values & limits low, auto Conditions: Use auto for standard content moderation. | Default— |
Fieldn | Typeinteger | RequirementOptional | Values & limits Minimum: 1 Maximum: 10 | Default1 |
Fieldquality | Typestring | RequirementOptional | Values & limits auto, high, medium, low | Defaultauto |
Fieldoutput_compression | Typeinteger | RequirementOptional | Values & limits Minimum: 0 Maximum: 100 Conditions: Applies to JPEG and WebP output; send the documented integer value. | Default100 |
Fieldoutput_format | Typestring | RequirementOptional | Values & limits webp, png, jpeg | Defaultpng |
Fieldstream | Typeboolean | RequirementOptional | Values & limits false Conditions: This route returns one completed JSON response. | Defaultfalse |
| Parameter | Contract |
|---|---|
Parametercontent_type | Contractapplication/json |
Parameterrequired | Contractprompt, model |
Parametermaterial_types | Contracttext |
Parameteroptional | Contractsize, background, moderation, n, quality, output_compression, output_format, stream |
Parameterconditions | ContractA transparent background requires PNG or WebP., Output compression applies to JPEG or WebP., The selected method generates from text. Editing and streaming controls described for the manufacturer are separate capabilities. |
Lifecycle: synchronous_result_then_owned_library
GET /v1/media/tasks/{task_id} · actual returned task_id or media library record
GET /v1/media/assets/{asset_id}/content
GET /v1/media/assets
GET /v1/media/assets/{asset_id}
The displayed rates estimate the cost before generation. The final charge is calculated from the cost recorded for the original generation. Measured output duration and forecast quantities are not the final billable quantity.
Tariff references do not add request options. Supported parameters are listed for the selected method.
Match each charge to the conditions shown. Use one rate for each set of alternative configurations.
| Configuration | Rate schedule | Forecast quantity | Charge |
|---|---|---|---|
| ConfigurationBase token rates | Rate scheduleBase rate | Forecast quantity— | Charge Input · Input tokens · Estimate for comparison only — / 1K tokens Output · Output tokens · Estimate for comparison only — / 1K tokens Input · Cache read · Estimate for comparison only — / 1K tokens Input · Cache write · Estimate for comparison only — / 1K tokens Input · Cache write, 1 hour · Estimate for comparison only — / 1K tokens |
| ConfigurationEstimated generation cost | Rate schedule— | Forecast quantityone generation estimate | Charge Output · Estimated generation cost · Estimate for comparison only $0.065536 estimate before generation This estimate is not an additional charge or a fixed rate for the completed generation. |
Ailoot reserves an estimated amount before a request. After the result, it settles the final charge from measured usage. Streaming settlement uses the final usage record. How reservation and settlement work →
set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\nexport AILOOT_API_KEY\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np={'prompt': 'A cute baby sea otter', 'model': 'gpt-image-1-mini', 'size': '1024x1024', 'n': 1, 'background': 'auto', 'moderation': 'auto', 'output_format': 'png'}\n\nPath("request.json").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/images/generations \\\n -H "Authorization: Bearer $AILOOT_API_KEY" -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport base64, json, os, subprocess\nfrom pathlib import Path\nfrom urllib.parse import urlsplit, urljoin\n\ndef save_images(items):\n if not items: raise SystemExit("No completed images; retain the full response")\n for index, item in enumerate(items):\n encoded=item.get("b64_json")\n uri=item.get("url", "")\n if not encoded and uri.startswith("data:image/"):\n header, separator, encoded=uri.partition(",")\n if not separator or ";base64" not in header: raise SystemExit("Unsupported image data URI")\n if encoded:\n raw=base64.b64decode(encoded,validate=True)\n elif uri:\n uri=urljoin("https://api.ailoot.ai",uri)\n parsed=urlsplit(uri)\n if parsed.scheme!="https" or not parsed.netloc or parsed.username or parsed.password:\n raise SystemExit("Invalid returned image URL")\n owned=parsed.netloc=="api.ailoot.ai" and parsed.path.startswith("/v1/media/assets/") and parsed.path.endswith("/content")\n args=["curl","--fail-with-body","--silent","--show-error",uri]\n if owned: args += ["-H","Authorization: Bearer "+os.environ["AILOOT_API_KEY"]]\n temporary=Path(f"image-{index}.bin")\n subprocess.run(args+["-o",str(temporary)],check=True)\n raw=temporary.read_bytes()\n temporary.unlink()\n else: raise SystemExit("Image has neither bytes nor URL")\n if not raw: raise SystemExit("Empty image result")\n ext="png" if raw.startswith(b"\\x89PNG") else "jpg" if raw.startswith(b"\\xff\\xd8") else "webp" if raw[:4]==b"RIFF" and raw[8:12]==b"WEBP" else "svg" if raw.lstrip().startswith((b"<svg",b"<?xml")) else "bin"\n Path(f"image-{index}.{ext}").write_bytes(raw)\n print("Every returned image saved; complete response metadata retained")\nsave_images(json.loads(Path("result.json").read_text())["data"])\nPY_RESULT\nDownload each returned image or save its Base64 contents
GET /v1/media/tasks/{task_id}GET /v1/media/assets/{asset_id}/contentGET /v1/media/assetsGET /v1/media/assets/{asset_id}set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/media/assets \\\n -H "Authorization: Bearer $AILOOT_API_KEY" -o owned-assets.json\n# Preserve every returned asset and follow its exact signed content URL. Do not construct a signed token.\nSave every completed image; retrieve each returned URL or decode its Base64 contents.
Retain the complete response and headers, every actual output, original returned identifiers and all usage fields. Recover the original operation without submitting creation again.
Keep the returned X-Client-Request-ID for reconciliation. Read only actual returned task_id/asset_id values or the owned media library; never build a task URL from the operation ID and never resubmit creation.
| Field | Type |
|---|---|
Fieldcreated | Type |
Fielddata[].url | Type |
Fielddata[].b64_json | Type |
Fieldusage | Type |
Ailoot Ultra openai/gpt-image-1-mini, gpt-image-1-mini
/v1/images