Add Publisher v2 + 5 extracted skills
Publisher fixes: - Checkout new branch before push (was pushing main ref) - Verify files staged before commit - Handle duplicate files gracefully - Clean error reporting per stage Skills merged to main: - mcp-server-setup (from pipeshub-ai) - research-pipeline (from Blacknode) - multi-agent-sequential-workflow (from Fast-LLM-Agent-MCP) - unifai-workflow-execution (from UnifAI) - code-review-agent-workflow (from AgentKit)
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---
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name: unifai-workflow-execution
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version: 1.0.0
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description: Execute a multi-agent workflow on the UnifAI platform using a specified
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blueprint and user prompt.
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inputs:
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- blueprint_id or blueprint_name
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- user_shortcut
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- user_question
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steps:
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- 'Step 1: Resolve the blueprint ID from either direct ID or name lookup (resolve_blueprint_id
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method)'
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- 'Step 2: Create a new session from the blueprint (create_session method)'
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- 'Step 3: Submit the session for background execution with the user prompt (submit_session
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method)'
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- 'Step 4: Poll session status until execution completes (poll_session_status method)'
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outputs:
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- session_id
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- workflow_id
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tags: []
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metadata:
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source_repo: https://github.com/redhat-community-ai-tools/UnifAI.git
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extracted_at: ''
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confidence: 0.95
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---
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# unifai-workflow-execution
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Execute a multi-agent workflow on the UnifAI platform using a specified blueprint and user prompt.
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## Setup
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**Dependencies:**
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```text
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pip install requests urllib3
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```
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**Setup steps:**
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1. Install required dependencies using pip install requests urllib3
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1. Ensure the environment variables are set correctly (BLUEPRINT_ID, BLUEPRINT_NAME, USER_SHORTCUT, POLLING_INTERVAL, UNIFAI_BASE_URL)
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## Key Files
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- `scripts/execution_workflow.py - Main script for workflow execution`
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## Steps
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1. Step 1: Resolve the blueprint ID from either direct ID or name lookup (resolve_blueprint_id method)
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2. Step 2: Create a new session from the blueprint (create_session method)
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3. Step 3: Submit the session for background execution with the user prompt (submit_session method)
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4. Step 4: Poll session status until execution completes (poll_session_status method)
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## Implementation Details
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```python
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resolve_blueprint_id(client: UnifAIClient) -> str
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{...}
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# Resolve the blueprint ID from either direct ID or name lookup.
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```
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```python
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create_session(client: UnifAIClient, blueprint_id: str) -> str
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{...}
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# Create a new session from the blueprint.
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```
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```python
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submit_session(client: UnifAIClient, session_id: str) -> dict
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{...}
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# Submit the session for background execution with the user prompt.
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```
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## Inputs
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- blueprint_id or blueprint_name
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- user_shortcut
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- user_question
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## Outputs
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- session_id
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- workflow_id
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## Failure Modes
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- Blueprint name not found or not unique - error during blueprint resolution
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- Session creation fails - error from API response
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- Session submission fails - error from API response
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- Polling session status fails - error from API response
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## Source
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Extracted from: [https://github.com/redhat-community-ai-tools/UnifAI.git](https://github.com/redhat-community-ai-tools/UnifAI.git)
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Confidence: 0.95
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