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How to Build an Image Editing Workflow with the OpenAI Images Edits API

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If your app already stores product photos, UI screenshots, or generated artwork as URLs, the slow part of image editing is often not the model call itself. It is the glue code around downloading files, re-uploading them, keeping reference images aligned, and preserving layout while changing only the parts you intend to change. The OpenAI Images Edits API on Ace Data Cloud gives builders a practical way to send an image, a prompt, and a model choice to one editing endpoint. The most useful path for server-side workflows is the JSON request style supported by gpt-image-2 , where the image field can be an image URL instead of a local multipart upload. What you can do The documented editing interface is built around https://api.acedata.cloud/openai/images/edits . With it, you can: Edit an existing image from a direct URL using application/json . Pass up to 16 reference images to GPT Image series models when a composition needs multiple inputs. Use gpt-image-2 for struc...
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How to Build an Image Editing Workflow with the OpenAI Images Edits API

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If your app already stores product photos, UI screenshots, or generated artwork as URLs, the slow part of image editing is often not the model call itself. It is the glue code around downloading files, re-uploading them, keeping reference images aligned, and preserving layout while changing only the parts you intend to change. The OpenAI Images Edits API on Ace Data Cloud gives builders a practical way to send an image, a prompt, and a model choice to one editing endpoint. The most useful path for server-side workflows is the JSON request style supported by gpt-image-2 , where the image field can be an image URL instead of a local multipart upload. What you can do The documented editing interface is built around https://api.acedata.cloud/openai/images/edits . With it, you can: Edit an existing image from a direct URL using application/json . Pass up to 16 reference images to GPT Image series models when a composition needs multiple inputs. Use gpt-image-2 for struc...
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How to Add Remote MCP Servers to Claude Code

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When you are coding in a terminal, the slow part is often not the code itself; it is the context switching: opening a browser to generate an image, searching for references, shortening a link, or preparing media assets for a README. Claude Code already gives you an AI assistant in the terminal. The practical next step is to connect it to remote MCP servers so the assistant can call external tools without leaving your project. What you can do The Ace Data Cloud Claude Code MCP document describes a set of managed remote MCP servers that you can add to Claude Code with HTTP transport. The listed servers cover several common builder workflows: Music: Suno for text-to-song, lyrics, covers, continuation, vocal separation, and Persona workflows. Images: Midjourney , Flux , Seedream , and NanoBanana for image generation, editing, mixing, product background replacement, Chinese prompt understanding, and related creative tasks. Video: Luma , Veo , and Seedance for video ge...
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How to Add Remote MCP Servers to Claude Code

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When you are coding in a terminal, the slow part is often not the code itself; it is the context switching: opening a browser to generate an image, searching for references, shortening a link, or preparing media assets for a README. Claude Code already gives you an AI assistant in the terminal. The practical next step is to connect it to remote MCP servers so the assistant can call external tools without leaving your project. What you can do The Ace Data Cloud Claude Code MCP document describes a set of managed remote MCP servers that you can add to Claude Code with HTTP transport. The listed servers cover several common builder workflows: Music: Suno for text-to-song, lyrics, covers, continuation, vocal separation, and Persona workflows. Images: Midjourney , Flux , Seedream , and NanoBanana for image generation, editing, mixing, product background replacement, Chinese prompt understanding, and related creative tasks. Video: Luma , Veo , and Seedance for video ge...
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How to Build Image Generation and Editing Workflows with the Nano Banana Images API

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If your app needs to turn a prompt into an image, or apply a precise edit to existing image inputs, the hard part is usually not the model call itself. It is designing a small workflow that handles inputs, tracks results, and gives you enough metadata to debug failed generations later. The Nano Banana Images API in Ace Data Cloud exposes both creation and editing through one endpoint: POST /nano-banana/images . You choose the behavior with an action field, send a prompt , and optionally pass model, image, count, resolution, aspect ratio, or callback parameters depending on the job. What you can do The API supports two core actions: generate : create images from a text prompt. edit : edit or combine existing images using image_urls plus a prompt. Both actions use the same base URL, https://api.acedata.cloud , and the same endpoint, /nano-banana/images . Authentication is done with an HTTP header: authorization: Bearer {token} . The documented request headers are accept: applicat...
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How to Build Image Generation and Editing Workflows with the Nano Banana Images API

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If your app needs to turn a prompt into an image, or apply a precise edit to existing image inputs, the hard part is usually not the model call itself. It is designing a small workflow that handles inputs, tracks results, and gives you enough metadata to debug failed generations later. The Nano Banana Images API in Ace Data Cloud exposes both creation and editing through one endpoint: POST /nano-banana/images . You choose the behavior with an action field, send a prompt , and optionally pass model, image, count, resolution, aspect ratio, or callback parameters depending on the job. What you can do The API supports two core actions: generate : create images from a text prompt. edit : edit or combine existing images using image_urls plus a prompt. Both actions use the same base URL, https://api.acedata.cloud , and the same endpoint, /nano-banana/images . Authentication is done with an HTTP header: authorization: Bearer {token} . The documented request headers are accept: applicat...
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How to Configure Continue for VS Code with an OpenAI-Compatible API

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If you use Continue in VS Code and want your assistant requests to go through an OpenAI-compatible endpoint, the important part is not only the base URL. You also need to make sure Continue sends the request through Chat Completions instead of the Responses API. This guide walks through a practical setup for using Ace Data Cloud as the OpenAI-compatible provider behind Continue for VS Code. The goal is intentionally narrow: configure one model entry, keep the token out of project files, verify that the request path is correct, and avoid the common mistake of sending traffic to the wrong API shape. What you can do With the documented Continue configuration, you can add a local model profile in VS Code that uses provider: openai , apiBase: https://api.acedata.cloud/v1 , an apiKey reference to ACEDATACLOUD_API_KEY , and useResponsesApi: false . provider: openai tells Continue to use the OpenAI-compatible provider path. apiBase: https://api.acedata.cloud/v1 points Continue at the Ace Da...
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