Add Skill: graph-based-node-workflow
Extracted from: https://github.com/temiroff/Blacknode.git Score: 1.0
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# Examples: graph-based-node-workflow
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## Usage Example
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```python
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# How to use this skill
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# Inputs: bn.Graph() - the graph container for the workflow, Node definitions (Literal, Text, LLMAgent, Concat, Output, etc.) with specified inputs and outputs, Edge connections mapping from_port to to_port between nodes
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# Process: Step 1: Initialize a bn.Graph() instance to serve as the workflow container → Step 2: Define individual nodes with their required inputs and outputs (e.g., Literal for data, LLMAgent for inference, Concat for combining, Output for final results) → Step 3: Create edges connecting nodes by specifying source from_port and destination to_port for each data flow
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# Outputs: Executed workflow results stored in the graph's output nodes, Cooked graph ready for inspection, replay, or deployment, Potential error states if node dependencies are missing or ports don't match
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```
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