67 lines
2.0 KiB
Markdown
67 lines
2.0 KiB
Markdown
---
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title: Graphify
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type: project
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status: active
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created: "2026-10-13"
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updated: "2026-09-26"
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tags:
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- project
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- ai-agents
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- architecture
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- obsidian
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- graphify
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- tool
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- knowledge-graph
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- pi-agent
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- showcase
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skills:
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- python
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- knowledge-graphs
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- mcp
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- subagent-orchestration
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- graph-analytics
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tools:
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- graphify (graphifyy)
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- pi-graphify
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- mcp
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- networkx
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---
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# Graphify — Overview
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## 💡 What is this project?
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Graphify turns a folder of files into a knowledge graph. It reads the files, finds
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concepts, and links them. The graph answers questions that cross many files.
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I run it on my Obsidian vault. The graph holds 2,171 nodes and 2,770 edges across
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128 communities. An AI agent reads the graph instead of all 134 notes.
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## 🌟 Key Highlights (Portfolio & Employment)
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- **Concept**: A persistent knowledge graph with an honest audit trail. Every link is tagged EXTRACTED, INFERRED, or AMBIGUOUS.
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- **Tools & Skills Showcase**: Python, NetworkX community detection, an MCP server, pi extension tools, and subagent orchestration for semantic extraction.
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- **Practical Value**: One query reads the graph instead of 134 files. The measured cost is 31 times fewer tokens per query.
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## 📐 Architecture & Flow
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```mermaid
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flowchart LR
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A["Obsidian vault<br/>134 notes"] --> B["detect + chunk"]
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B --> C["semantic extraction<br/>pi subagents"]
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C --> D["graph.json<br/>2171 nodes / 2770 edges"]
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D --> E["cluster + analyze"]
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E --> F["GRAPH_REPORT.md"]
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E --> G["graph.html"]
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D --> H["MCP server<br/>graphify-vault"]
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H --> I["AI agents<br/>query_graph"]
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```
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## 🔗 Related Notes & Links
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- **Graph data**: `/home/sam/graphify/obsidian-vault/graph.json`
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- **Interactive HTML**: `/home/sam/graphify/obsidian-vault/graph.html`
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- **Report**: `/home/sam/graphify/obsidian-vault/GRAPH_REPORT.md`
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- **Interface**: MCP server `graphify-vault` (query from any folder), plus CLI and pi tools.
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- **AI Context (Outline)**: collection `Graphify`
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