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Connect an Ace Data Cloud chat model to Dify, then use it in an LLM node, Chatflow, or Agent. You need a Dify workspace where you are an owner or administrator, an Ace Data Cloud API key, and access to the selected model.

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Choose the installation path

The Ace Data Cloud provider is awaiting review. It is not currently confirmed as a searchable, published Marketplace entry or a default-installed provider. Use the official compatibility provider for the available installation path. The retired collection of first-party Dify tool plugins is not required.

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Prepare an API key

  1. Sign in to the Ace Data Cloud console. Activate the chat service you want to use and check its current balance and model pricing.
  2. Create a key in Credentials. A service key is limited to its service; a global key can be used across services that your account can access. For an initial gpt-4.1-mini test, use a key authorized for that chat model.
  3. Store the key in Dify’s provider credential settings. Keys are shared within the Dify workspace; use a separate development key when testing. Do not put a key in prompts, screenshots, workflow exports, or source control.
Dify’s model credits do not pay for requests made with your Ace Data Cloud key. Those requests use your Ace Data Cloud account balance.

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Configure the available compatibility provider

Open Integrations → Model Provider. In versions with the older navigation, open Settings → Model Providers. Install OpenAI-API-compatible, then choose Add Model. The Base URL ends in /v1. Dify appends /chat/completions; do not append it yourself or use /openai/v1. The initial token limits are conservative test settings, not claims about the model’s maximum capacity. Leave optional reasoning, web search, structured output, image input, and tool-calling options disabled for the first text test. Save the model. The compatibility provider may send a small model request while validating the credentials, which can consume API usage.

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Use the Ace Data Cloud provider after publication

Once the named provider is available, install Ace Data Cloud from the official Marketplace. On its provider card, choose Add Model, enter the exact model ID and API key, and set context and output limits within the model’s documented limits. You do not enter a Base URL: the plugin uses https://api.acedata.cloud/v1/chat/completions. The submitted provider validates the key and model ID with a read-only /v1/models request. Saving it does not generate a paid answer, but also does not prove that your balance, model entitlement, or every optional feature will work. Confirm those with a short real request. Both paths in this guide use Chat Completions. Do not select image-generation, embedding, or Messages-only models, such as claude-opus-5-5 and claude-sonnet-5-5, for this configuration. A model appearing in /v1/models does not establish support for this protocol or for every optional feature.

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Run your first workflow

Create a blank Workflow and connect these nodes:
  1. In Start, add a required text input named question.
  2. In LLM, select the provider and gpt-4.1-mini. Set the user prompt to the Start → question variable using the variable picker. Set maximum output tokens to 64 and turn retries off for this first check.
  3. In Output (called End in older versions), add an output named answer and select LLM → text as its value. A successful workflow without an Output node may return no data to its caller.
  4. Run a preview with the question Reply only DIFY_OK. Confirm that the LLM node succeeds, the output contains DIFY_OK, and the run reports token usage.
  5. For a Chatflow, use an Answer node instead of Output and insert LLM → text. Publish only after preview and usage checks succeed.

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Enable tools or images

Enable Tool calling only for a model that supports it. Enable Streaming tool calls separately when supported. Use the configured model in an Agent node and add one appropriate tool. In the run trace, verify the tool name and arguments, the tool result, and the final answer. Tool selection and a successful final response are separate checks. Enable Image input only for a vision-capable model. Add a small image through Dify’s supported file input and ask a simple question about it. Treat a successful text request as text validation only; it does not validate images, structured output, or other features.

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Check usage and cost

After the first request, open Ace Data Cloud usage. Filter by the test key and time window. Match the model, status, and request details to the Dify run, then check the recorded deduction. Save a request or trace ID for support without sharing the API key. Charges are recorded in Credits. Their USD value is Credits × (package price / package amount) using your current package. The named provider reports token usage but does not publish a fixed USD estimate; Dify can display zero estimated cost even when the API request is billable. The Ace Data Cloud usage record is authoritative. Retries, loops, and Agent tool turns can each result in additional model requests.

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Troubleshoot

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Validation scope and maintenance

The submitted provider passed unit tests, official package and serverless installation checks, and a real packaged-CLI call. gpt-4.1-mini was also verified for text, streaming tool calls, and tool-result continuation. This does not certify full Dify Community Edition/Cloud UI installation, Marketplace publication, every model, or every optional feature. Keep the provider updated through Dify’s plugin manager. Recheck model IDs and prices when changing models, and validate a small workflow before applying an update to production. For support, use the provider repository or dev@acedata.cloud. For protocol details, see Chat Completions and Dify’s model provider documentation.