Epictetus
5f917f4121
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)
91 lines
3.7 KiB
Markdown
91 lines
3.7 KiB
Markdown
---
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name: research-pipeline
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version: 1.0.0
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description: Fetch a Wikipedia page, summarise its content using an AI agent, and
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write the summary to a file.
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inputs:
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- URL of the Wikipedia page
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steps:
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- 'Step 1: Import necessary modules from `_bootstrap` and `blacknode`: Run `from _bootstrap
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import NIM_MODEL, require_nim_api_key; import blacknode as bn`'
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- 'Step 2: Require NVIDIA NIM API key: Call `require_nim_api_key()` to ensure the
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API key is set.'
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- 'Step 3: Create a graph instance: Initialize `g = bn.Graph()`.'
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- 'Step 4: Add nodes for URL, HTTPGet, summarisation, and file writing: `url = g.node(''Literal'',
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value=''URL of the Wikipedia page''); fetcher = g.node(''HTTPGet''); summarise =
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g.node(''LLMAgent'', system=''You are a technical writer. Summarise the text in
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3 bullet points.'', model=NIM_MODEL); writer = g.node(''FileWrite'', path=''summary.txt'')`'
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- 'Step 5: Connect nodes with edges: `url.out(''value'') >> fetcher.inp(''url'');
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fetcher.out(''text'') >> summarise.inp(''prompt''); summarise.out(''text'') >> writer.inp(''text'')`'
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- 'Step 6: Cook the graph to execute and get output: `result = g.cook(writer, ''path'');
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print(f''Summary written to: {result}'')`'
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outputs:
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- Path of the summary file
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tags: []
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metadata:
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source_repo: https://github.com/temiroff/Blacknode.git
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extracted_at: ''
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confidence: 0.95
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---
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# research-pipeline
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Fetch a Wikipedia page, summarise its content using an AI agent, and write the summary to a file.
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## Setup
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**Dependencies:**
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```text
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pip install anthropic>=0.25 docker>=7.1 openai>=1.0
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```
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**Setup steps:**
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1. Ensure NVIDIA NIM API key is set in the environment or editor
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1. Install required dependencies: `pip install -r requirements.txt`
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## Key Files
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- `examples/research_pipeline.py - Contains the research pipeline workflow`
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## Steps
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1. Step 1: Import necessary modules from `_bootstrap` and `blacknode`: Run `from _bootstrap import NIM_MODEL, require_nim_api_key; import blacknode as bn`
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2. Step 2: Require NVIDIA NIM API key: Call `require_nim_api_key()` to ensure the API key is set.
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3. Step 3: Create a graph instance: Initialize `g = bn.Graph()`.
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4. Step 4: Add nodes for URL, HTTPGet, summarisation, and file writing: `url = g.node('Literal', value='URL of the Wikipedia page'); fetcher = g.node('HTTPGet'); summarise = g.node('LLMAgent', system='You are a technical writer. Summarise the text in 3 bullet points.', model=NIM_MODEL); writer = g.node('FileWrite', path='summary.txt')`
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5. Step 5: Connect nodes with edges: `url.out('value') >> fetcher.inp('url'); fetcher.out('text') >> summarise.inp('prompt'); summarise.out('text') >> writer.inp('text')`
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6. Step 6: Cook the graph to execute and get output: `result = g.cook(writer, 'path'); print(f'Summary written to: {result}')`
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## Implementation Details
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```python
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from _bootstrap import NIM_MODEL, require_nim_api_key; import blacknode as bn
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```
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```python
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url = g.node('Literal', value='https://en.wikipedia.org/w/api.php?action=query&prop=extracts&exintro=1&explaintext=1&titles=Houdini_(software)&format=json&formatversion=2&origin=*'); fetcher = g.node('HTTPGet'); summarise = g.node('LLMAgent', system='You are a technical writer. Summarise the text in 3 bullet points.', model=NIM_MODEL); writer = g.node('FileWrite', path='summary.txt')
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```
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```python
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url.out('value') >> fetcher.inp('url'); fetcher.out('text') >> summarise.inp('prompt'); summarise.out('text') >> writer.inp('text')
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```
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## Inputs
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- URL of the Wikipedia page
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## Outputs
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- Path of the summary file
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## Failure Modes
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- If the URL is invalid or unreachable, the HTTPGet node will fail; if the summarisation fails, the output text might be empty
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## Source
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Extracted from: [https://github.com/temiroff/Blacknode.git](https://github.com/temiroff/Blacknode.git)
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Confidence: 0.95
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