Get the DeepSeek API key (refer to previous steps).

Confirm API functions (such as text generation, data analysis, etc.).

Download and install MindMaster (supports Windows, Mac, iOS, Android and other platforms).

Determine the text content to import from DeepSeek (such as text returned by the API, analysis results, etc.).

Call the DeepSeek API using a programming language such as Python or a tool such as Postman.

Sample code (Python):

Save the text content returned by the API as a text file (such as output.txt).

1. Open MindMaster and create a new mind map.

2. Open the saved text file (such as output.txt).

3. Copy the text content and paste it into the MindMaster node.

4. Adjust node hierarchy and format as needed.

1. In MindMaster, click File > Import.

2. Select "Text File" (such as output.txt).

3. MindMaster will automatically convert text content into mind map nodes.

4. Adjust node hierarchy and layout.

1. Convert the text content returned by DeepSeek to Markdown format (such as using title #, list-, etc.).

2. Save as .md file.

3. In MindMaster, click File > Import > Markdown File.

4. MindMaster will automatically generate mind maps based on the Markdown level.

Adjust the node level according to the content logic.

Modify node color, font, icon, etc.

Use relationship lines to connect related nodes.

Export to image, PDF or MindMaster format.

Share with team members or clients.

Write a script (such as Python) to convert the text content returned by the DeepSeek API directly into a format supported by MindMaster (such as .mm or .md).

Example: parse the JSON data returned by the API into Markdown format and save it as a .md file.

Use automation tools such as Zapier or IFTTT to connect DeepSeek with MindMaster to achieve automatic import.

Pay attention to the call frequency and data volume limits of the DeepSeek API.

Ensure that the imported text content is formatted clearly and facilitates MindMaster parsing.

Regularly back up mind map files to avoid data loss.