python scripts/aihub_cli.py configure --token "bvk_your_token_here"


Do not commit tokens to git.

## Core usage

### List presets

```bash
python scripts/aihub_cli.py presets

Trigger a workflow

python scripts/aihub_cli.py run \
  --type "其他：AI自生成互动" \
  --inputs '{"query":"请生成一个最简单的互动组件配置：一个只有标题、说明文字和单个确认按钮的教学互动卡片，主题是牛顿第二定律。"}'

Query status

python scripts/aihub_cli.py status <runId>

Fetch outputs

python scripts/aihub_cli.py outputs <runId>

Long-running workflows: prefer script polling, not LLM polling

For Dify/self-hosted AIHub, a workflow may run for minutes or more than an hour. Do not keep an LLM session alive just to wait.

Preferred pattern:

Use run to trigger the workflow and capture runId
Return/store the runId immediately
Hand off waiting to the CLI/script layer
Only use an LLM again when you need to interpret or summarize the final outputs

Recommended polling patterns

Short synchronous polling

Use only for short workflows.

python scripts/aihub_cli.py poll \
  --type "计算题" \
  --inputs '{"node_list":"[]","style_render":"","global_context":"{}","style_theme":""}' \
  --interval 5 \
  --timeout 300

Long asynchronous polling

For long workflows, use watch with a sparse backoff schedule so the script does the waiting instead of the LLM.

Recommended schedules:

Balanced: 120,300,600,1200,2400,3600
Long-job conservative: 300,600,1200,2400,3600
Very long jobs: 300,600,1200,2400,3600,3600,3600

Example:

python scripts/aihub_cli.py watch <runId> --schedule 300,600,1200,2400,3600

This means poll after 5m, then 10m, then 20m, then 40m, then hourly.

Background watcher pattern

When a caller needs non-blocking execution:

Trigger with run
Save runId plus caller context (issue/task/document/message target)
Start a background watcher process using watch, or enqueue the run into scripts/aihub_watcher.py
When the watcher sees succeeded, fetch outputs and hand them to the next system
When the watcher sees failed, report the error and stop

This pattern is reusable for:

Paperclip
cron jobs
local automation
future non-Paperclip agents

Generic watcher queue

Use the bundled watcher script when you need a reusable, non-LLM polling queue:

python scripts/aihub_watcher.py enqueue <runId> --label "job name" --schedule 300,600,1200,2400,3600
python scripts/aihub_watcher.py once
python scripts/aihub_watcher.py daemon --interval 60

The watcher stores state in ~/.aihub-agent/watch-jobs.json and is intentionally upstream-agnostic: it tracks run status and outputs, but does not assume Paperclip or any specific callback target.

Workflow selection

Use references/workflow-presets.md when you need the exact public workflowType input fields required to call /workflows/run correctly. Use references/workflow-inventory.md when you need the broader local workflow archive, orchestration chain, or registry/local snapshot differences. Use references/api-endpoints.md when you need the raw HTTP contract.

Quick rule:

Free-form interactive generation → 其他：AI自生成互动
Structured quiz/data tasks → pick the specific preset
Full orchestration entrypoints like 互动游戏生产总线 and 互动游戏生产基座 are documented in workflow-presets.md as advanced appId-only workflows, not public workflowType presets.
For 其他：AI自生成互动, note that the registry snapshot maps it to Web互动生产-Agent版, while the local workflow archive currently contains Web互动生产-互动组件v2-workfolw.yml as the closest artifact.
If unsure, inspect presets first and choose the most specific matching workflow

Failure handling

If a workflow does not finish in the current polling window:

do not call it a failure automatically
report/run-store the runId
leave it to the watcher to continue polling later

Treat these separately:

token/auth failure
trigger failure
run failed
run still running
outputs not ready yet

Expected outputs

Most workflows return an outputs.config object or equivalent structured payload. For large outputs:

summarize the result for humans
store or hand off the raw JSON separately
avoid dumping huge JSON blobs into normal chat replies unless explicitly asked

aihub-workflow-agent

AIHub Workflow Agent

Base URL

Authentication