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AstraFlow星图

Product information, use cases, and access for AstraFlow星图.

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VerifiedSeptember 7, 2026

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What is AstraFlow星图?

AstraFlow Xingtu is UCloud’s model aggregation platform for developers and teams that need to work with multiple AI models through one service. It brings together language, image, and video capabilities for applications such as conversation, reasoning, code generation, visual understanding, and multimedia creation. Users can select models from a shared platform and adapt the model choice to the needs of each project.

The platform uses a unified API key for access and follows the OpenAI API protocol, so existing integrations can be connected with limited configuration changes. Its client also brings local AI workspaces such as OpenCode, Claude Code, and Codex into the same developer-oriented workflow. It is suited to developers comparing model options, building AI features, or connecting model inference to an existing application or service.

Key features of AstraFlow星图

  • Unified Model Access

    Xingtu brings mainstream language models from multiple providers behind a shared access point. Developers can use one API key and specify a model ID when sending requests, which is useful for applications that need to select, compare, or switch between model providers.

  • Multimodal Capabilities

    The platform covers conversation, reasoning, code generation, long-context processing, image generation, image-to-image work, visual understanding, and video generation. Teams can combine the relevant models for text-based tasks as well as image and video workflows.

  • OpenAI-Compatible API

    Xingtu is compatible with the OpenAI API protocol and supports integration patterns used by the OpenAI Python SDK, LangChain, and LlamaIndex. Developers connect an existing program by configuring the service endpoint, API key, and model identifier, making it suitable for embedding model access into application code or developer tools.

  • Ongoing Model Updates

    The platform continues to add and update available models, while its model center and models API can be used to inspect the current catalog. This centralized directory is useful for developers who need to follow new releases, test different reasoning or vision options, and avoid maintaining separate provider interfaces for every experiment.