muapi-workflow — Автоматизация и управление AI рабочими процессами

--- slug: muapi-workflow-skill name: muapi-workflow version: "0.1.0" description: Build, run, and visualize multi-step AI generation workflows. The AI architect translates natural language descriptions into connected node graphs — chain image generation, video creation, enhancement, and editing into automated pipelines. acceptLicenseTerms: true --- # 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: ```bash 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. ```bash muapi workflow discover --output-json ``` 2. **Match (Internal Reasoning)**: Use your LLM capabilities to analyze the `name`, `category`, and `description` fields of the returned workflows. Find the best match for the user's intent. 3. **Analyze**: If you find a promising candidate, inspect its structure to ensure it has the necessary nodes and parameters. ```bash muapi workflow get <workflow_id> ``` **CRITICAL RULE**: The output of `muapi workflow get` will include an "API Inputs" table. You MUST read this table to understand what inputs are required. 4. **Choose & Confirm & Prompt User**: - If one workflow is a perfect match, you MUST ask the user to provide the exact values for the required API inputs before executing it. **Never invent or guess input values (like prompts, URLs, etc.) on your own.** - If multiple workflows are highly relevant, present the options to the user with their descriptions and ask them to confirm which one to use, and also ask for the required inputs. - If no workflow matches the user's complex request, offer to **architect** a new one using `muapi workflow create`. ### Example Agent Reasoning > "The user wants a product promo video. I fetched the catalog using `discover`. I see two potential workflows: > 1. `wf_123`: 'Product promo with background music' > 2. `wf_456`: 'Simple video gen' > I will analyze `wf_123` with `get`. It has the required nodes. I will suggest `wf_123` or just run it if the match is precise." --- ## Protocol: Building a Workflow ### Step 1 — Describe your pipeline ```bash 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 ```bash # Rich ASCII node graph in the terminal muapi workflow get <workflow_id> # Or raw JSON muapi workflow get <workflow_id> --output-json ``` ### Step 3 — Run it ```bash # Run with specific inputs muapi workflow execute <workflow_id> --input "node1.prompt=a glowing crystal cave at midnight" # Use --download to pull results locally muapi workflow execute <workflow_id> --input "node1.prompt=a sunset" --download ./outputs ``` ### Step 4 — Discovery (Optional) If you want to reuse an existing workflow instead of creating a new one: ```bash # Search by keywords muapi workflow discover "ugc video" ``` ### Step 5 — Interactive Execution Run a workflow and have the CLI prompt you for each required input: ```bash muapi workflow run-interactive <workflow_id> ``` --- ## Workflow Examples ### Image Pipelines ```bash # 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 ```bash # 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 ```bash # Add a step muapi workflow edit <id> --prompt "add a face-swap step after the image generation" # Swap a model muapi workflow edit <id> --prompt "change the video model from kling to veo3" ``` --- ## CLI Reference ```bash # 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 <id> # Execute with inputs muapi workflow execute <id> --input "node1.prompt=a sunset" # Monitor a run muapi workflow status <run_id> # Get outputs muapi workflow outputs <run_id> --download ./results # Edit with AI muapi workflow edit <id> --prompt "add lipsync at the end" # Rename / delete muapi workflow rename <id> --name "Product Pipeline v2" muapi workflow delete <id> ``` --- ## 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 - Workflows can contain any combination of muapi.ai nodes (image, video, audio, enhance, edit) - Node outputs are automatically wired as inputs to downstream nodes - `--sync` mode waits up to 120s for generation; use `--async` for complex workflows and poll separately - Run timeouts: 10 minutes maximum per workflow execution