@gaodes/pi-graphify

@gaodes/pi-graphify

Turn any folder of files (code, docs, papers, images, video) into a queryable knowledge graph with community detection, an honest audit trail, and three outputs: interactive HTML, GraphRAG-ready JSON, and a plain-language GRAPH_REPORT.md.

Source · npm

Inspired by graphify — the AI coding assistant skill. This extension wraps graphify's Python CLI for native Pi integration.

It also bundles a graphify skill (skills/graphify/SKILL.md) for full-pipeline orchestration. Use /skill:graphify when you want the guided multi-step workflow; use the tools and /graphify command for fast operational calls.

Tools

Tool	Description
graphify_build	Build a knowledge graph from a directory (full pipeline: detect → extract → cluster → visualize)
graphify_query	Query the graph — BFS for broad context, DFS for tracing specific paths
graphify_path	Find the shortest path between two concepts in the graph
graphify_explain	Plain-language explanation of a node — everything connected to it
graphify_add	Fetch a URL and add it to the corpus, then update the graph
graphify_update	Incremental update — re-extract only changed files
graphify_watch	Watch a directory for changes, auto-rebuild graph on code edits
graphify_cluster	Re-run community detection on an existing graph (no re-extraction)
graphify_extract	Headless LLM extraction for CI — supports claude, kimi, openai, gemini, ollama, bedrock backends
graphify_export_callflow	Generate self-contained Mermaid architecture/call-flow HTML from graph.json
graphify_upgrade	Check for and install graphifyy CLI updates via uv

Commands

Command	Description
/graphify	Single entry point with autocomplete for all subcommands and flags

Subcommands and flags

/graphify <path>                              # build graph (full pipeline)
/graphify <path> --mode deep                  # thorough extraction, richer INFERRED edges
/graphify <path> --update                     # incremental — re-extract only changed files
/graphify <path> --cluster-only               # rerun clustering on existing graph
/graphify <path> --no-viz                     # skip visualization, just report + JSON
/graphify <path> --obsidian                   # generate Obsidian vault
/graphify <path> --svg                        # export graph.svg
/graphify <path> --graphml                    # export for Gephi / yEd
/graphify <path> --neo4j                      # generate cypher.txt for Neo4j
/graphify <path> --callflow                   # generate callflow architecture HTML

/graphify query "<question>"                  # BFS traversal — broad context
/graphify query "<question>" --dfs            # DFS — trace a specific path
/graphify query "<question>" --budget 1500    # cap answer at N tokens
/graphify path "ConceptA" "ConceptB"          # shortest path between two concepts
/graphify explain "ConceptName"               # plain-language explanation of a node
/graphify add <url>                           # fetch URL, save to ./raw, update graph
/graphify add <url> --author "Name"           # tag who wrote it
/graphify update <path>                       # incremental update
/graphify watch <path>                        # watch folder, auto-rebuild on changes
/graphify cluster                             # rerun clustering on existing graph
/graphify hook install                        # install git hooks for auto-rebuild
/graphify hook uninstall                      # remove git hooks
/graphify hook status                         # check hook status
/graphify extract <path>                      # headless LLM extraction for CI
/graphify extract <path> --backend claude     # specify LLM backend
/graphify extract <path> --backend kimi       # Kimi AI backend
/graphify extract <path> --backend openai     # OpenAI backend
/graphify extract <path> --backend gemini     # Google Gemini backend
/graphify extract <path> --backend ollama     # Ollama (local) backend
/graphify extract <path> --backend bedrock    # AWS Bedrock backend
/graphify extract <path> --max-workers 4      # limit parallel workers
/graphify extract <path> --token-budget 4096  # cap tokens per LLM call
/graphify extract <path> --api-timeout 300    # HTTP timeout in seconds
/graphify uninstall                           # remove graphify from all platforms
/graphify uninstall --purge                   # also delete graphify-out/

Prerequisites

• Python 3.10+
• graphifyy package (auto-installed on first run): pip install graphifyy or uv tool install graphifyy

Install

pi install @gaodes/pi-graphify

Configuration

Key: pi-graphify in prime-settings.json (legacy graphify key auto-migrates on load).

Setting	Type	Default	Description
enabled	boolean	true	Enable/disable the extension
pythonPath	string	"python3"	Path to Python interpreter
outputDir	string	"graphify-out"	Output directory name
statusbar	object	built-in defaults	Optional pi-statusbar widget settings
autoContext.enabled	boolean	true	Enable Graphify auto-context hooks
autoContext.augmentSearchResults	boolean	true	Append Graphify hint to search tool results
autoContext.queryBudget	number	1200	Budget hint for graphify_query follow-up usage

Auto-context behavior

When graphify-out/graph.json exists in the current project, pi-graphify:

• injects a concise [Graphify active] system-prompt hint on before_agent_start (once per session)
• appends a short [Graphify] hint to grep, ffgrep, find, and fffind tool results, suggesting graphify_query for structural questions

Notes:

• This is Pi-native behavior in this extension; upstream graphify pi install installs the Graphify skill but does not install these Pi runtime hooks.
• Auto-context hooks stay idle in projects where <outputDir>/graph.json is missing.

Git tracking policy

The extension's .gitignore ignores the entire graphify-out/ directory. Graph output is regenerated on each build and should not be committed to the repository.

If you want to track graph output for documentation purposes, override in your project's .gitignore:

!graphify-out/
!graphify-out/graph.json

Note: Earlier versions of pi-graphify tracked graphify-out/ files and selectively ignored cache/temp entries. As of v0.1.6, the entire directory is ignored for cleaner repository state.

Reliability

All child-process invocations (Python CLI, inline scripts) run through a bounded exec adapter that caps stdout/stderr at 1 MiB by default. This prevents V8 heap exhaustion when graph operations produce multi-MB output — the root cause of the exit-code 32102 (OOM) crash in earlier versions.

Key safety features:

• Output budgets: 256 KiB for queries, 1 MiB for general operations, 2 MiB for JSON parsing
• Large-graph guard: graphs exceeding 10 MiB bypass the inline Python rebuild and fall back to the CLI directly
• Signal-death handling: child processes killed by signals are reported as failures (exit code 1), not silent successes
• LRU cache bounding: auto-context augmentation caches cap at 256 entries

Source

• Canonical: ~/agents/primecodex/packages/pi-graphify/
• GitLab: agents/primecodex/packages/pi-graphify
• GitHub: github.com/gaodes/pi-graphify