Streaming Mindmap Rendering

3. Streaming & Parsing Logic

The core of this skill is efficiently handling the stream and parsing potentially incomplete data.

Data Formats

Mind Elixir supports two main formats:

1. JSON (Native): Hierarchical tree structure. Hard to stream because JSON is invalid until complete.
2. Plain Text (Recommended for Streaming): Indentation-based or markdown-list-based text. Easier to parse partially.

Plain Text Format Example

- Root Node
  - Child Node 1
    - Child Node 1-1
    - Child Node 1-2
    - Child Node 1-3
    - }:2 Summary of first two nodes
  - Child Node 2
    - Child Node 2-1 [^id1]
    - Child Node 2-2 [^id2]
    - Child Node 2-3 {color: "#e87a90"}
    - > [^id1] <-Bidirectional Link-> [^id2]
  - Child Node 3
    - Child Node 3-1 [^id3]
    - Child Node 3-2 [^id4]
    - Child Node 3-3 [^id5]
    - > [^id3] >-Unidirectional Link-> [^id4]
    - > [^id3] <-Unidirectional Link-< [^id5]
  - Child Node 4
    - Child Node 4-1 [^id6]
    - Child Node 4-2 [^id7]
    - Child Node 4-3 [^id8]
    - } Summary of all previous nodes
    - Child Node 4-4
  - > [^id1] <-Link position is not restricted, as long as the id can be found during rendering-> [^id8]

Parsing Implementation

Use mind-elixir/plaintextConverter (or a custom parser) to convert text to the Mind Elixir JSON format.

import { plaintextToMindElixir } from 'mind-elixir/plaintextConverter'

// Helper to clean Markdown code blocks if your stream includes them
function cleanStreamContent(content: string): string {
  return content
    .replace(/^```[\w]*\n?/gm, '')
    .replace(/```$/gm, '')
    .trim()
}

// State hooks in your parent component
const [mindmapData, setMindmapData] = useState<MindElixirData | null>(null)
const accumulatedText = useRef('')
const lastRenderTime = useRef(0)

// Streaming function (Generic Example)
async function startStreaming(url: string) {
  const response = await fetch(url)
  const reader = response.body?.getReader()
  const decoder = new TextDecoder()

  if (!reader) return

  while (true) {
    const { done, value } = await reader.read()
    if (done) break

    const chunk = decoder.decode(value)
    accumulatedText.current += chunk

    // Throttle updates to avoid freezing the UI
    const now = Date.now()
    if (now - lastRenderTime.current > 500) {
      // 500ms throttle
      updateMindmap()
      lastRenderTime.current = now
    }
  }

  // Final update
  updateMindmap()
}

function updateMindmap() {
  try {
    const cleanText = cleanStreamContent(accumulatedText.current)
    const data = plaintextToMindElixir(cleanText)
    setMindmapData(data) // This triggers the useEffect in MindmapRenderer
  } catch (e) {
    // Ignore parse errors from incomplete chunks
    console.warn('Partial parse error ignored')
  }
}

4. Optimization Tips

• Throttling: Do not re-parse and re-render on every single byte. Use a throttle (e.g., 200-500ms).
• Stable Root: Ensure the parsing logic maintains a stable root ID if possible, to prevent the whole graph from flashing.
• Scroll to Last: To follow the generation, you can programmatically scroll to the last added node.

// Scroll to last node (inside MindmapRenderer update effect)
const lastNode = findLastNode(data.nodeData) // Implement traversal to find last node
if (lastNode?.id) {
  const nodeEle = meRef.current.findEle(lastNode.id)
  if (nodeEle) meRef.current.scrollIntoView(nodeEle)
}

5. Integrating with AI Prompts

When generating mindmaps with LLMs, instruct the model to use the plaintext format.