Epictetus
271f79610d
New skills: - blacknode-graph-workflow - multi-agent-workflow-execution - langgraph-agent-workflow - langgraph-multi-agent-router - three-tier-evaluation-pipeline Config: LLM pipeline uses LFM on llama.cpp (8080)
3.1 KiB
3.1 KiB
name, version, description, inputs, steps, outputs, tags, metadata
| name | version | description | inputs | steps | outputs | tags | metadata | |||||||||||||||
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| blacknode-graph-workflow | 1.0.0 | Build and execute node-based AI workflows with LLM agents and processing nodes |
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blacknode-graph-workflow
Build and execute node-based AI workflows with LLM agents and processing nodes
Setup
Dependencies:
pip install blacknode (core package) anthropic>=0.25 openai>=1.0 petgraph (for graph operations)
Setup steps:
- Install blacknode package: pip install blacknode
- Configure model API keys (NIM_API_KEY, OPENAI_API_KEY, etc.) in .env or editor
- Create a Graph instance and add nodes with inputs/outputs
- Define node connections in g._edges list
- Execute with g.cook() to run the workflow and capture results
Key Files
blacknode/blacknode.py (Graph class implementation)examples/hello_agent.py (simple LLM agent workflow)examples/converted_nvidia_nim.py (NIM model workflow)
Steps
- Initialize a blacknode.Graph instance to create the workflow structure
- Add nodes to the graph with defined inputs and outputs (e.g., Literal, LLMAgent, FileWrite)
- Define edges connecting nodes to establish data flow between them
- Execute the graph using cook() to run the workflow and generate outputs
Implementation Details
g = bn.Graph()
g._edges = [{'from': 'model', 'from_port': 'value', 'to': 'agent', 'to_port': 'model'}]
result = g.cook(output_node, 'value')
Inputs
- Model configuration (NIM_MODEL, API keys for NVIDIA NIM, OpenAI, Anthropic)
- Node definitions with specified inputs and outputs (Literal, LLMAgent, FileWrite, etc.)
- Data sources (URLs, text content, or other inputs for the workflow)
Outputs
- Processed results from the final node (e.g., printed text, written files, or generated data)
- Graph execution status and any errors encountered during execution
Failure Modes
- Missing or invalid model API key causing graph initialization failure
- Incorrect node connections or missing edge definitions leading to runtime errors
- Model not found or unavailable in the specified environment causing execution failure
- Graph edges not properly defined or mismatched causing cook() to fail
Source
Extracted from: https://github.com/temiroff/Blacknode.git Confidence: 0.95