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Add Skill: unifai-workflow-execution

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Extracted from: https://github.com/redhat-community-ai-tools/UnifAI.git
Score: 1.0
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skills/unifai-workflow-execution/SKILL.md
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---
name: unifai-workflow-execution
version: 1.0.0
description: Execute a multi-agent workflow on the UnifAI platform using a specified
blueprint and user prompt.
description: Execute a multi-agent AI workflow defined in YAML or through the UI's
drag-and-drop editor.
inputs:
- blueprint_id or blueprint_name
- user_shortcut
- user_question
- name: blueprint_path
description: Path to the blueprint file (YAML) defining the multi-agent workflow.
- name: execution_mode
description: 'Execution mode: ''local'' or ''distributed''.'
steps:
- 'Step 1: Resolve the blueprint ID from either direct ID or name lookup (resolve_blueprint_id
method)'
- 'Step 2: Create a new session from the blueprint (create_session method)'
- 'Step 3: Submit the session for background execution with the user prompt (submit_session
method)'
- 'Step 4: Poll session status until execution completes (poll_session_status method)'
- step_name: Load Blueprint
description: Parse and validate the blueprint file to ensure it conforms to expected
structure.
- step_name: Initialize Execution Engine
description: Set up the execution engine based on the selected mode ('local' or
'distributed').
- step_name: Execute Workflow
description: Run the multi-agent workflow, streaming node-by-node output as NDJSON
over HTTP.
- step_name: Stream Results
description: Render and stream results in real time to clients subscribing to the
event stream.
outputs:
- session_id
- workflow_id
- name: execution_results
description: The output of the executed workflow, streamed as NDJSON over HTTP.
tags: []
metadata:
source_repo: https://github.com/redhat-community-ai-tools/UnifAI.git
extracted_at: ''
confidence: 0.95
confidence: 0.9
---
# unifai-workflow-execution
Execute a multi-agent workflow on the UnifAI platform using a specified blueprint and user prompt.
## Setup
**Dependencies:**
```text
pip install requests urllib3
```
**Setup steps:**
1. Install required dependencies using pip install requests urllib3
1. Ensure the environment variables are set correctly (BLUEPRINT_ID, BLUEPRINT_NAME, USER_SHORTCUT, POLLING_INTERVAL, UNIFAI_BASE_URL)
## Key Files
- `scripts/execution_workflow.py - Main script for workflow execution`
Execute a multi-agent AI workflow defined in YAML or through the UI's drag-and-drop editor.
## Steps
1. Step 1: Resolve the blueprint ID from either direct ID or name lookup (resolve_blueprint_id method)
2. Step 2: Create a new session from the blueprint (create_session method)
3. Step 3: Submit the session for background execution with the user prompt (submit_session method)
4. Step 4: Poll session status until execution completes (poll_session_status method)
## Implementation Details
```python
resolve_blueprint_id(client: UnifAIClient) -> str
{...}
# Resolve the blueprint ID from either direct ID or name lookup.
```
```python
create_session(client: UnifAIClient, blueprint_id: str) -> str
{...}
# Create a new session from the blueprint.
```
```python
submit_session(client: UnifAIClient, session_id: str) -> dict
{...}
# Submit the session for background execution with the user prompt.
```
1. {'step_name': 'Load Blueprint', 'description': 'Parse and validate the blueprint file to ensure it conforms to expected structure.'}
2. {'step_name': 'Initialize Execution Engine', 'description': "Set up the execution engine based on the selected mode ('local' or 'distributed')."}
3. {'step_name': 'Execute Workflow', 'description': 'Run the multi-agent workflow, streaming node-by-node output as NDJSON over HTTP.'}
4. {'step_name': 'Stream Results', 'description': 'Render and stream results in real time to clients subscribing to the event stream.'}
## Inputs
- blueprint_id or blueprint_name
- user_shortcut
- user_question
- {'name': 'blueprint_path', 'description': 'Path to the blueprint file (YAML) defining the multi-agent workflow.'}
- {'name': 'execution_mode', 'description': "Execution mode: 'local' or 'distributed'."}
## Outputs
- session_id
- workflow_id
- {'name': 'execution_results', 'description': 'The output of the executed workflow, streamed as NDJSON over HTTP.'}
## Failure Modes
- Blueprint name not found or not unique - error during blueprint resolution
- Session creation fails - error from API response
- Session submission fails - error from API response
- Polling session status fails - error from API response
- {'mode_name': 'Invalid Blueprint', 'description': 'Blueprint file is not valid YAML or does not conform to expected structure.'}
- {'mode_name': 'Execution Engine Initialization Failure', 'description': 'Failed to initialize the execution engine due to configuration issues or missing dependencies.'}
## Source
Extracted from: [https://github.com/redhat-community-ai-tools/UnifAI.git](https://github.com/redhat-community-ai-tools/UnifAI.git)
Confidence: 0.95
Confidence: 0.9
skills/unifai-workflow-execution/examples.md
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```python
# How to use this skill
# Inputs: blueprint_id or blueprint_name, user_shortcut, user_question
# Process: Step 1: Resolve the blueprint ID from either direct ID or name lookup (resolve_blueprint_id method) → Step 2: Create a new session from the blueprint (create_session method) → Step 3: Submit the session for background execution with the user prompt (submit_session method)
# Outputs: session_id, workflow_id
# Inputs: {'name': 'blueprint_path', 'description': 'Path to the blueprint file (YAML) defining the multi-agent workflow.'}, {'name': 'execution_mode', 'description': "Execution mode: 'local' or 'distributed'."}
# Process: {'step_name': 'Load Blueprint', 'description': 'Parse and validate the blueprint file to ensure it conforms to expected structure.'} → {'step_name': 'Initialize Execution Engine', 'description': "Set up the execution engine based on the selected mode ('local' or 'distributed')."} → {'step_name': 'Execute Workflow', 'description': 'Run the multi-agent workflow, streaming node-by-node output as NDJSON over HTTP.'}
# Outputs: {'name': 'execution_results', 'description': 'The output of the executed workflow, streamed as NDJSON over HTTP.'}
```
skills/unifai-workflow-execution/metadata.json
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{
"name": "unifai-workflow-execution",
"version": "1.0.0",
"goal": "Execute a multi-agent workflow on the UnifAI platform using a specified blueprint and user prompt.",
"goal": "Execute a multi-agent AI workflow defined in YAML or through the UI's drag-and-drop editor.",
"inputs": [
"blueprint_id or blueprint_name",
"user_shortcut",
"user_question"
{
"name": "blueprint_path",
"description": "Path to the blueprint file (YAML) defining the multi-agent workflow."
},
{
"name": "execution_mode",
"description": "Execution mode: 'local' or 'distributed'."
}
],
"steps": [
"Step 1: Resolve the blueprint ID from either direct ID or name lookup (resolve_blueprint_id method)",
"Step 2: Create a new session from the blueprint (create_session method)",
"Step 3: Submit the session for background execution with the user prompt (submit_session method)",
"Step 4: Poll session status until execution completes (poll_session_status method)"
{
"step_name": "Load Blueprint",
"description": "Parse and validate the blueprint file to ensure it conforms to expected structure."
},
{
"step_name": "Initialize Execution Engine",
"description": "Set up the execution engine based on the selected mode ('local' or 'distributed')."
},
{
"step_name": "Execute Workflow",
"description": "Run the multi-agent workflow, streaming node-by-node output as NDJSON over HTTP."
},
{
"step_name": "Stream Results",
"description": "Render and stream results in real time to clients subscribing to the event stream."
}
],
"outputs": [
"session_id",
"workflow_id"
{
"name": "execution_results",
"description": "The output of the executed workflow, streamed as NDJSON over HTTP."
}
],
"failure_modes": [
"Blueprint name not found or not unique - error during blueprint resolution",
"Session creation fails - error from API response",
"Session submission fails - error from API response",
"Polling session status fails - error from API response"
{
"mode_name": "Invalid Blueprint",
"description": "Blueprint file is not valid YAML or does not conform to expected structure."
},
{
"mode_name": "Execution Engine Initialization Failure",
"description": "Failed to initialize the execution engine due to configuration issues or missing dependencies."
}
],
"confidence": 0.95,
"explanation": "This workflow is specific to the UnifAI platform and its multi-agent system, but can be adapted for similar systems with a similar architecture.",
"confidence": 0.9,
"explanation": "This workflow is designed to execute multi-agent AI workflows defined in YAML blueprints or through the UI's drag-and-drop editor, providing real-time streaming of results.",
"source_repo": "https://github.com/redhat-community-ai-tools/UnifAI.git",
"score": 1.0
}