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Roo Code в VS Code: надёжная настройка агентного режима через единый API

Агентный режим в редакторе полезен только тогда, когда его сетевое подключение и вызовы инструментов можно наблюдать и воспроизводить. Roo Code в VS Code умеет работать через провайдера, совместимого с OpenAI API. Это позволяет отделить конфигурацию IDE от конкретной модели: редактор знает единый контракт Chat Completions, а разработчик выбирает подходящую модель в рабочем приложении Ace Data Cloud. Ниже — практический путь: создать изолированное приложение, проверить доступ обычным запросом, включить агентный сценарий и найти причину ошибки, не меняя параметры наугад. Актуальные экранные пути и описания API собраны в документации Ace Data Cloud ; стартовая страница платформы доступна на русском языке . Почему для Roo Code важен именно совместимый контракт Обычный чат и агент — разные нагрузки. В чате достаточно вернуть текст. Агенту необходимо получать структурированные вызовы функций, передавать их параметры, принимать результаты инструментов и продолжать диалог без потери конт...
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Roo Code в VS Code: надёжная настройка агентного режима через единый API

Агентный режим в редакторе полезен только тогда, когда его сетевое подключение и вызовы инструментов можно наблюдать и воспроизводить. Roo Code в VS Code умеет работать через провайдера, совместимого с OpenAI API. Это позволяет отделить конфигурацию IDE от конкретной модели: редактор знает единый контракт Chat Completions, а разработчик выбирает подходящую модель в рабочем приложении Ace Data Cloud. Ниже — практический путь: создать изолированное приложение, проверить доступ обычным запросом, включить агентный сценарий и найти причину ошибки, не меняя параметры наугад. Актуальные экранные пути и описания API собраны в документации Ace Data Cloud ; стартовая страница платформы доступна на русском языке . Почему для Roo Code важен именно совместимый контракт Обычный чат и агент — разные нагрузки. В чате достаточно вернуть текст. Агенту необходимо получать структурированные вызовы функций, передавать их параметры, принимать результаты инструментов и продолжать диалог без потери конт...
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How to Build a High-Resolution Image Workflow with the SeeDream API

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Product teams often need more than a single pretty image: they need a repeatable way to turn prompts, references, sizes, and async jobs into usable visual assets. The SeeDream Image Generation API is a practical fit for that kind of workflow because the same endpoint can handle text-to-image, image-to-image, high-resolution output, and task polling. What you can do The core endpoint in the source document is POST https://api.acedata.cloud/seedream/images . With it, you can build a small image pipeline that: Generates an image from a prompt using action: generate . Uses complete model strings such as doubao-seedream-5-0-260128 , doubao-seedream-5-0-pro-260628 , doubao-seedream-4-5-251128 , or doubao-seedream-4-0-250828 . Returns the final asset URL in data[].image_url , along with the actual pixel size . Runs long generations asynchronously by passing async: true , then polling POST https://api.acedata.cloud/seedream/tasks . Modifies existing images by passing an ima...
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How to Build a High-Resolution Image Workflow with the SeeDream API

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Product teams often need more than a single pretty image: they need a repeatable way to turn prompts, references, sizes, and async jobs into usable visual assets. The SeeDream Image Generation API is a practical fit for that kind of workflow because the same endpoint can handle text-to-image, image-to-image, high-resolution output, and task polling. What you can do The core endpoint in the source document is POST https://api.acedata.cloud/seedream/images . With it, you can build a small image pipeline that: Generates an image from a prompt using action: generate . Uses complete model strings such as doubao-seedream-5-0-260128 , doubao-seedream-5-0-pro-260628 , doubao-seedream-4-5-251128 , or doubao-seedream-4-0-250828 . Returns the final asset URL in data[].image_url , along with the actual pixel size . Runs long generations asynchronously by passing async: true , then polling POST https://api.acedata.cloud/seedream/tasks . Modifies existing images by passing an ima...
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Getting Started with Nano Banana MCP in Claude Desktop, VS Code, and Cursor

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When image work moves from a browser tab into your editor or AI client, the biggest win is not speed; it is staying in the same workflow while you ask for a generation, edit, product placement, or try-on and then inspect the result. What you can do The Nano Banana MCP Server from Ace Data Cloud connects image generation and image editing tools to MCP-capable clients such as Claude Desktop, VS Code, and Cursor. Once configured, you can ask your assistant to create or modify images directly from the conversation instead of switching to a separate web UI. The documented tool surface is intentionally small: nanobanana_generate_image generates images from text prompts. nanobanana_edit_image edits or combines existing images. nanobanana_get_task checks the status of one task. nanobanana_get_tasks_batch checks multiple task statuses in a batch. The guide also describes several practical image workflows: text-to-image generation, image editing, virtual try-on, prod...
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Getting Started with Nano Banana MCP in Claude Desktop, VS Code, and Cursor

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When image work moves from a browser tab into your editor or AI client, the biggest win is not speed; it is staying in the same workflow while you ask for a generation, edit, product placement, or try-on and then inspect the result. What you can do The Nano Banana MCP Server from Ace Data Cloud connects image generation and image editing tools to MCP-capable clients such as Claude Desktop, VS Code, and Cursor. Once configured, you can ask your assistant to create or modify images directly from the conversation instead of switching to a separate web UI. The documented tool surface is intentionally small: nanobanana_generate_image generates images from text prompts. nanobanana_edit_image edits or combines existing images. nanobanana_get_task checks the status of one task. nanobanana_get_tasks_batch checks multiple task statuses in a batch. The guide also describes several practical image workflows: text-to-image generation, image editing, virtual try-on, prod...
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How to Edit Images from Cursor with NanoBanana MCP

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When you are writing inside Cursor and realize a screenshot, product mockup, or empty-state illustration needs a quick visual pass, the usual workflow is awkward: leave the editor, open a design tool, upload assets, write a prompt somewhere else, download the result, then come back to the codebase. The NanoBanana MCP setup lets you keep that loop inside Cursor Agent mode. What you can do The NanoBanana MCP document focuses on a practical image workflow: generation and editing from an MCP server that Cursor can call over HTTP. The documented tools are nanobanana_generate_image for text-to-image generation and nanobanana_edit_image for image editing. The editing path is especially useful because it supports multiple image URLs, so an agent can reason over more than one visual input. That makes it a good fit for builder tasks such as: polishing a terminal screenshot before publishing a blog post or README; placing a product from one image into a scene from another image;...
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