docs: add CanvasReasonerActivity for auto-inferring workflow connections
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2026-09-05 00:54:30 -07:00
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@@ -965,6 +965,80 @@ Response returned
--- ---
### CanvasReasonerActivity
Auto-suggest workflow connections using LLM reasoning. When you drop new activities onto the canvas, this activity analyzes them and suggests logical connections based on input/output compatibility and workflow patterns.
**Workflow Definition:**
```json
{
"id": "canvas-reason-1",
"type": "canvas-reasoner",
"label": "Auto-Connect Activities",
"data": {
"nodes": "{{ workflow.nodes }}",
"edges": "{{ workflow.edges }}",
"preserve_existing": true,
"auth_token": "{{ user.jwt_token }}"
}
}
```
**Use Cases:**
- New nodes added to canvas → automatically suggest connections
- Validate workflow design → LLM reasoning explains connections
- Redesign workflow → suggest optimal activity sequence
- Data flow analysis → ensure proper input/output matching
**How It Works:**
1. Analyzes all node types and their configurations
2. Reviews existing edges (if preserving)
3. Uses reasoning model to infer logical connections
4. Returns suggested edges with confidence score
5. Includes reasoning explanation
**Output Example:**
```json
{
"suggested_edges": [
{"source": "clone-1", "target": "analyze-1"},
{"source": "analyze-1", "target": "security-scan-1"},
{"source": "security-scan-1", "target": "report-1"}
],
"reasoning": "Clone repository first, analyze code, perform security scan, generate report. Standard code review workflow.",
"confidence": 0.92
}
```
**Fields:**
- `nodes` (required): Canvas nodes to analyze
- `edges` (required): Current edges
- `preserve_existing` (optional, default true): Keep existing edges and only suggest new ones
- `auth_token` (optional): JWT for LLM reasoning calls
**Confidence Scores:**
- 0.9-1.0: High confidence (common patterns)
- 0.7-0.9: Medium confidence (reasonable connections)
- 0.5-0.7: Low confidence (multiple valid approaches)
- <0.5: Unsure (manual review recommended)
**Integration Example:**
```
User drops 3 new nodes on canvas
Workflow calls CanvasReasonerActivity
LLM analyzes: Clone → Analyze → Report
Returns edges + reasoning
Frontend updates canvas with suggested connections
User approves/rejects suggestions
```
---
### Error Handling ### Error Handling
If LLM inference fails: If LLM inference fails: