> ## Documentation Index
> Fetch the complete documentation index at: https://docs.zgi.cn/llms.txt
> Use this file to discover all available pages before exploring further.

# Workflow

> Multi-step AI task orchestration — triggers, execution engine, variable management

The workflow engine is the execution backbone of ZGI agents. It turns visual node graphs into reliable, production-grade AI pipelines.

## Execution Engine

Workflow execution uses **SSE (Server-Sent Events) streaming**, delivering each node's results in real-time. The frontend can display step-by-step progress:

```
Node 1 [Start] ✓ → Node 2 [Knowledge Retrieval] ✓ → Node 3 [LLM Analysis] ⏳ → Node 4 [Output]
```

Each node execution event is pushed to the client, including:

* Node ID and name
* Execution status (running / success / failed)
* Execution duration
* Output variables and values

## Production-Grade Reliability

ZGI workflows are designed for production, not just demos:

* **Assertions** — Define validation rules per node (e.g., "retrieval must return citations", "output must match JSON schema")
* **Retry** — Failed nodes auto-retry with configurable limits and backoff
* **Fallback** — When retries exhaust, degrade gracefully (e.g., output a "pending review" list instead of failing silently)

## Workflow Lifecycle

1. **Draft** — Edit and save on the visual canvas. Auto-saved every 30 seconds.
2. **Debug** — Test with sample inputs. SSE streams node-by-node execution in the debug panel.
3. **Publish** — One-click publish generates a version number and makes the workflow available via API or chat.
4. **Monitor** — View run history, execution logs, token consumption, and error rates.

## Example: Contract Review Workflow

```
[Start: Upload Contract]
    → [OCR Parse Document]
    → [Knowledge Retrieval: Legal Clauses]
    → [LLM: Risk Analysis]
    → [Conditional Branch: Risk Level]
        ├── High Risk → [Notify Legal Team via Webhook]
        └── Low Risk → [Generate Report]
    → [End: Return Structured Report with Citations]
```