Workflow

AI Workflow Builder

Chain any combination of muapi.ai generation steps into automated pipelines. The AI architect converts your plain-language description into a runnable node graph.

Prerequisites

Always ensure the muapi CLI is up-to-date before running any commands. Reinstall from source at the start of every session:

pip install --upgrade /path/to/muapi-cli

Replace /path/to/muapi-cli with the actual path to the muapi-cli directory in the workspace (the directory containing pyproject.toml).

Core Operations

1. Generate (generate-workflow.sh) — AI architect creates a workflow from a description 2. Discover (discover-workflow.sh) — Find a relevant existing workflow by natural language 3. Edit (generate-workflow.sh --workflow-id) — Modify an existing workflow with a prompt 4. Interactive Run (interactive-run.sh) — Prompt for inputs and execute a workflow 5. Run (run-workflow.sh) — Execute a workflow, poll node-by-node, collect outputs 6. CLI (muapi workflow) — Full CRUD + visualization directly from the terminal

Agent Guided Discovery & Selection

As an AI agent, you have the ability to read and understand the purpose of available workflows to select the best one for the user's task (e.g., "create a UGC video").

1. Discover: Fetch the catalog of available workflows and their descriptions in JSON format.

   muapi workflow discover --output-json
   

   muapi workflow get 
   

Example Agent Reasoning

Protocol: Building a Workflow

Step 1 — Describe your pipeline

muapi workflow create "take a text prompt, generate an image with flux-dev, then upscale it to 4K"

The architect returns a workflow with a unique ID and a node graph. Save the ID.

Step 2 — Inspect and visualize

# Rich ASCII node graph in the terminal
muapi workflow get 
Or raw JSON
muapi workflow get  --output-json

Step 3 — Run it

# Run with specific inputs
muapi workflow execute  \
  --input "node1.prompt=a glowing crystal cave at midnight"
Use --download to pull results locally
muapi workflow execute  \
  --input "node1.prompt=a sunset" \
  --download ./outputs

Step 4 — Discovery (Optional)

# Search by keywords
muapi workflow discover "ugc video"

Step 5 — Interactive Execution

muapi workflow run-interactive 

Workflow Examples

Image Pipelines

# Text → Image → Upscale
muapi workflow create "take a text prompt, generate with flux-dev, upscale the result"
Text → Image → Background removal → Product shot
muapi workflow create "generate a product image with hidream, remove background, create professional product shot"

Video Pipelines

# Text → Video
muapi workflow create "generate a 10-second cinematic video from a text prompt using kling-master"
Image → Video → Lipsync
muapi workflow create "animate an input image with seedance, then apply lipsync from an audio file"

Editing an Existing Workflow

# Add a step
muapi workflow edit  --prompt "add a face-swap step after the image generation"
Swap a model
muapi workflow edit  --prompt "change the video model from kling to veo3"

CLI Reference

# List all your workflows
muapi workflow list
Browse templates
muapi workflow templates
Generate new workflow
muapi workflow create "text → flux image → upscale → face swap"
Visualize a workflow
muapi workflow get 
Execute with inputs
muapi workflow execute  --input "node1.prompt=a sunset"
Monitor a run
muapi workflow status 
Get outputs
muapi workflow outputs  --download ./results
Edit with AI
muapi workflow edit  --prompt "add lipsync at the end"
Rename / delete
muapi workflow rename  --name "Product Pipeline v2"
muapi workflow delete 

MCP Tools (for AI agents)

| Tool | Description | |------|-------------| | muapi_workflow_list | List user's workflows | | muapi_workflow_create | AI architect: prompt → workflow | | muapi_workflow_get | Get workflow definition + node graph | | muapi_workflow_execute | Run with specific inputs | | muapi_workflow_status | Node-by-node run status | | muapi_workflow_outputs | Final output URLs |

Constraints

Always ensure the muapi CLI is up-to-date before running any commands. Reinstall from source at the start of every session:

pip install --upgrade /path/to/muapi-cli

Replace /path/to/muapi-cli with the actual path to the muapi-cli directory in the workspace (the directory containing pyproject.toml).