mirror of
https://github.com/safishamsi/graphify.git
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Safi
23f598f3a0
#796: add edge_data()/edge_datas() helpers in build.py that tolerate MultiGraph/MultiDiGraph; replace all G.edges[u,v] 2-tuple call sites in __main__.py, serve.py, wiki.py, export.py, analyze.py, benchmark.py; fix same pattern in 10 skill file inline heredocs #795: all 12 skill files now short-circuit on /graphify --help or -h and print the Usage block without running any pipeline steps #792 (hollow response): add _response_is_hollow() predicate in llm.py; when Ollama (or any backend) returns empty/null/whitespace content or a parsed result with no nodes/edges, rewrite finish_reason="length" so _extract_with_adaptive_retry bisects the chunk instead of silently dropping it; applied to _call_openai_compat, _call_claude, _call_bedrock Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
1265 lines
50 KiB
Python
1265 lines
50 KiB
Python
# write graph to HTML, JSON, SVG, GraphML, Obsidian vault, and Neo4j Cypher
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from __future__ import annotations
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import html as _html
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import json
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import math
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import re
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from collections import Counter
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from pathlib import Path
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import networkx as nx
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from networkx.readwrite import json_graph
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from graphify.security import sanitize_label
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from graphify.analyze import _node_community_map
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from graphify.build import edge_data
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def _obsidian_tag(name: str) -> str:
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"""Sanitize a community name for use as an Obsidian tag.
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Obsidian tags only allow alphanumerics, hyphens, underscores, and slashes.
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Spaces become underscores; everything else is stripped.
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"""
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return re.sub(r"[^a-zA-Z0-9_\-/]", "", name.replace(" ", "_"))
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def _strip_diacritics(text: str) -> str:
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import unicodedata
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nfkd = unicodedata.normalize("NFKD", text)
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return "".join(c for c in nfkd if not unicodedata.combining(c))
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def _yaml_str(s: str) -> str:
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"""Escape a value for safe embedding in a YAML double-quoted scalar (F-009).
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See `graphify.ingest._yaml_str` for the full rationale; duplicated here to
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avoid pulling the URL-fetching `ingest` module into export's dependency
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graph. Handles backslash, double-quote, all line breaks (\\n, \\r,
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U+2028, U+2029), tab, NUL, and other C0/DEL control characters that
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would otherwise let a hostile `source_file` / `community` / etc. break
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out of the YAML scalar and inject sibling keys.
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"""
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if s is None:
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return ""
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out: list[str] = []
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for ch in str(s):
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cp = ord(ch)
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if ch == "\\":
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out.append("\\\\")
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elif ch == '"':
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out.append('\\"')
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elif ch == "\n":
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out.append("\\n")
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elif ch == "\r":
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out.append("\\r")
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elif ch == "\t":
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out.append("\\t")
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elif ch == "\0":
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out.append("\\0")
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elif cp == 0x2028:
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out.append("\\L")
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elif cp == 0x2029:
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out.append("\\P")
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elif cp < 0x20 or cp == 0x7F:
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out.append(f"\\x{cp:02x}")
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else:
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out.append(ch)
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return "".join(out)
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COMMUNITY_COLORS = [
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"#4E79A7", "#F28E2B", "#E15759", "#76B7B2", "#59A14F",
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"#EDC948", "#B07AA1", "#FF9DA7", "#9C755F", "#BAB0AC",
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]
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MAX_NODES_FOR_VIZ = 5_000
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def _viz_node_limit() -> int:
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"""Return the effective viz node limit, honoring GRAPHIFY_VIZ_NODE_LIMIT env var.
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Falls back to MAX_NODES_FOR_VIZ when the env var is unset, empty, or non-integer.
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Set to 0 to disable HTML viz unconditionally (useful for CI runners).
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"""
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import os
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raw = os.environ.get("GRAPHIFY_VIZ_NODE_LIMIT")
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if raw is None or not raw.strip():
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return MAX_NODES_FOR_VIZ
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try:
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return int(raw)
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except ValueError:
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return MAX_NODES_FOR_VIZ
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def _html_styles() -> str:
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return """<style>
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* { box-sizing: border-box; margin: 0; padding: 0; }
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body { background: #0f0f1a; color: #e0e0e0; font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", sans-serif; display: flex; height: 100vh; overflow: hidden; }
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#graph { flex: 1; }
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#sidebar { width: 280px; background: #1a1a2e; border-left: 1px solid #2a2a4e; display: flex; flex-direction: column; overflow: hidden; }
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#search-wrap { padding: 12px; border-bottom: 1px solid #2a2a4e; }
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#search { width: 100%; background: #0f0f1a; border: 1px solid #3a3a5e; color: #e0e0e0; padding: 7px 10px; border-radius: 6px; font-size: 13px; outline: none; }
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#search:focus { border-color: #4E79A7; }
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#search-results { max-height: 140px; overflow-y: auto; padding: 4px 12px; border-bottom: 1px solid #2a2a4e; display: none; }
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.search-item { padding: 4px 6px; cursor: pointer; border-radius: 4px; font-size: 12px; white-space: nowrap; overflow: hidden; text-overflow: ellipsis; }
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.search-item:hover { background: #2a2a4e; }
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#info-panel { padding: 14px; border-bottom: 1px solid #2a2a4e; min-height: 140px; }
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#info-panel h3 { font-size: 13px; color: #aaa; margin-bottom: 8px; text-transform: uppercase; letter-spacing: 0.05em; }
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#info-content { font-size: 13px; color: #ccc; line-height: 1.6; }
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#info-content .field { margin-bottom: 5px; }
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#info-content .field b { color: #e0e0e0; }
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#info-content .empty { color: #555; font-style: italic; }
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.neighbor-link { display: block; padding: 2px 6px; margin: 2px 0; border-radius: 3px; cursor: pointer; font-size: 12px; white-space: nowrap; overflow: hidden; text-overflow: ellipsis; border-left: 3px solid #333; }
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.neighbor-link:hover { background: #2a2a4e; }
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#neighbors-list { max-height: 160px; overflow-y: auto; margin-top: 4px; }
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#legend-wrap { flex: 1; overflow-y: auto; padding: 12px; }
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#legend-wrap h3 { font-size: 13px; color: #aaa; margin-bottom: 10px; text-transform: uppercase; letter-spacing: 0.05em; }
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.legend-item { display: flex; align-items: center; gap: 8px; padding: 4px 0; cursor: pointer; border-radius: 4px; font-size: 12px; }
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.legend-item:hover { background: #2a2a4e; padding-left: 4px; }
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.legend-item.dimmed { opacity: 0.35; }
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.legend-dot { width: 12px; height: 12px; border-radius: 50%; flex-shrink: 0; }
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.legend-label { flex: 1; overflow: hidden; text-overflow: ellipsis; white-space: nowrap; }
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.legend-count { color: #666; font-size: 11px; }
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#stats { padding: 10px 14px; border-top: 1px solid #2a2a4e; font-size: 11px; color: #555; }
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#legend-controls { display: flex; align-items: center; gap: 8px; margin-bottom: 8px; padding: 4px 0; }
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#legend-controls label { display: flex; align-items: center; gap: 6px; cursor: pointer; font-size: 12px; color: #aaa; user-select: none; }
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#legend-controls label:hover { color: #e0e0e0; }
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.legend-cb, #select-all-cb { appearance: none; -webkit-appearance: none; width: 14px; height: 14px; border: 1.5px solid #3a3a5e; border-radius: 3px; background: #0f0f1a; cursor: pointer; position: relative; flex-shrink: 0; }
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.legend-cb:checked, #select-all-cb:checked { background: #4E79A7; border-color: #4E79A7; }
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.legend-cb:checked::after, #select-all-cb:checked::after { content: ''; position: absolute; left: 3.5px; top: 1px; width: 4px; height: 7px; border: solid #fff; border-width: 0 2px 2px 0; transform: rotate(45deg); }
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#select-all-cb:indeterminate { background: #4E79A7; border-color: #4E79A7; }
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#select-all-cb:indeterminate::after { content: ''; position: absolute; left: 2px; top: 5px; width: 8px; height: 2px; background: #fff; border: none; transform: none; }
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</style>"""
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def _hyperedge_script(hyperedges_json: str) -> str:
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return f"""<script>
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// Render hyperedges as shaded regions
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const hyperedges = {hyperedges_json};
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// afterDrawing passes ctx already transformed to network coordinate space.
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// Draw node positions raw — no manual pan/zoom/DPR math needed.
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network.on('afterDrawing', function(ctx) {{
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hyperedges.forEach(h => {{
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const positions = h.nodes
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.map(nid => network.getPositions([nid])[nid])
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.filter(p => p !== undefined);
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if (positions.length < 2) return;
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ctx.save();
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ctx.globalAlpha = 0.12;
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ctx.fillStyle = '#6366f1';
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ctx.strokeStyle = '#6366f1';
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ctx.lineWidth = 2;
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ctx.beginPath();
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// Centroid and expanded hull in network coordinates
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const cx = positions.reduce((s, p) => s + p.x, 0) / positions.length;
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const cy = positions.reduce((s, p) => s + p.y, 0) / positions.length;
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const expanded = positions.map(p => ({{
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x: cx + (p.x - cx) * 1.15,
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y: cy + (p.y - cy) * 1.15
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}}));
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ctx.moveTo(expanded[0].x, expanded[0].y);
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expanded.slice(1).forEach(p => ctx.lineTo(p.x, p.y));
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ctx.closePath();
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ctx.fill();
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ctx.globalAlpha = 0.4;
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ctx.stroke();
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// Label
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ctx.globalAlpha = 0.8;
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ctx.fillStyle = '#4f46e5';
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ctx.font = 'bold 11px sans-serif';
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ctx.textAlign = 'center';
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ctx.fillText(h.label, cx, cy - 5);
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ctx.restore();
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}});
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}});
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</script>"""
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def _html_script(nodes_json: str, edges_json: str, legend_json: str) -> str:
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return f"""<script>
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const RAW_NODES = {nodes_json};
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const RAW_EDGES = {edges_json};
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const LEGEND = {legend_json};
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// HTML-escape helper — prevents XSS when injecting graph data into innerHTML
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function esc(s) {{
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return String(s).replace(/&/g,'&').replace(/</g,'<').replace(/>/g,'>').replace(/"/g,'"').replace(/'/g,''');
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}}
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// Build vis datasets
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const nodesDS = new vis.DataSet(RAW_NODES.map(n => ({{
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id: n.id, label: n.label, color: n.color, size: n.size,
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font: n.font, title: n.title,
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_community: n.community, _community_name: n.community_name,
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_source_file: n.source_file, _file_type: n.file_type, _degree: n.degree,
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}})));
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const edgesDS = new vis.DataSet(RAW_EDGES.map((e, i) => ({{
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id: i, from: e.from, to: e.to,
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label: '',
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title: e.title,
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dashes: e.dashes,
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width: e.width,
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color: e.color,
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arrows: {{ to: {{ enabled: true, scaleFactor: 0.5 }} }},
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}})));
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const container = document.getElementById('graph');
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const network = new vis.Network(container, {{ nodes: nodesDS, edges: edgesDS }}, {{
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physics: {{
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enabled: true,
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solver: 'forceAtlas2Based',
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forceAtlas2Based: {{
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gravitationalConstant: -60,
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centralGravity: 0.005,
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springLength: 120,
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springConstant: 0.08,
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damping: 0.4,
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avoidOverlap: 0.8,
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}},
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stabilization: {{ iterations: 200, fit: true }},
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}},
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interaction: {{
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hover: true,
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tooltipDelay: 100,
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hideEdgesOnDrag: true,
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navigationButtons: false,
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keyboard: false,
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}},
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nodes: {{ shape: 'dot', borderWidth: 1.5 }},
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edges: {{ smooth: {{ type: 'continuous', roundness: 0.2 }}, selectionWidth: 3 }},
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}});
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network.once('stabilizationIterationsDone', () => {{
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network.setOptions({{ physics: {{ enabled: false }} }});
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}});
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function showInfo(nodeId) {{
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const n = nodesDS.get(nodeId);
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if (!n) return;
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const neighborIds = network.getConnectedNodes(nodeId);
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const neighborItems = neighborIds.map(nid => {{
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const nb = nodesDS.get(nid);
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const color = nb ? nb.color.background : '#555';
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return `<span class="neighbor-link" style="border-left-color:${{esc(color)}}" onclick="focusNode(${{JSON.stringify(nid)}})">${{esc(nb ? nb.label : nid)}}</span>`;
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}}).join('');
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document.getElementById('info-content').innerHTML = `
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<div class="field"><b>${{esc(n.label)}}</b></div>
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<div class="field">Type: ${{esc(n._file_type || 'unknown')}}</div>
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<div class="field">Community: ${{esc(n._community_name)}}</div>
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<div class="field">Source: ${{esc(n._source_file || '-')}}</div>
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<div class="field">Degree: ${{n._degree}}</div>
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${{neighborIds.length ? `<div class="field" style="margin-top:8px;color:#aaa;font-size:11px">Neighbors (${{neighborIds.length}})</div><div id="neighbors-list">${{neighborItems}}</div>` : ''}}
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`;
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}}
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function focusNode(nodeId) {{
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network.focus(nodeId, {{ scale: 1.4, animation: true }});
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network.selectNodes([nodeId]);
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showInfo(nodeId);
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}}
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// Track hovered node — hover detection is more reliable than click params
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let hoveredNodeId = null;
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network.on('hoverNode', params => {{
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hoveredNodeId = params.node;
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container.style.cursor = 'pointer';
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}});
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network.on('blurNode', () => {{
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hoveredNodeId = null;
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container.style.cursor = 'default';
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}});
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container.addEventListener('click', () => {{
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if (hoveredNodeId !== null) {{
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showInfo(hoveredNodeId);
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network.selectNodes([hoveredNodeId]);
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}}
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}});
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network.on('click', params => {{
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if (params.nodes.length > 0) {{
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showInfo(params.nodes[0]);
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}} else if (hoveredNodeId === null) {{
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document.getElementById('info-content').innerHTML = '<span class="empty">Click a node to inspect it</span>';
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}}
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}});
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const searchInput = document.getElementById('search');
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const searchResults = document.getElementById('search-results');
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searchInput.addEventListener('input', () => {{
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const q = searchInput.value.toLowerCase().trim();
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searchResults.innerHTML = '';
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if (!q) {{ searchResults.style.display = 'none'; return; }}
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const matches = RAW_NODES.filter(n => n.label.toLowerCase().includes(q)).slice(0, 20);
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if (!matches.length) {{ searchResults.style.display = 'none'; return; }}
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searchResults.style.display = 'block';
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matches.forEach(n => {{
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const el = document.createElement('div');
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el.className = 'search-item';
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el.textContent = n.label;
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el.style.borderLeft = `3px solid ${{n.color.background}}`;
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el.style.paddingLeft = '8px';
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el.onclick = () => {{
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network.focus(n.id, {{ scale: 1.5, animation: true }});
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network.selectNodes([n.id]);
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showInfo(n.id);
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searchResults.style.display = 'none';
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searchInput.value = '';
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}};
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searchResults.appendChild(el);
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}});
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}});
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document.addEventListener('click', e => {{
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if (!searchResults.contains(e.target) && e.target !== searchInput)
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searchResults.style.display = 'none';
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}});
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const hiddenCommunities = new Set();
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const selectAllCb = document.getElementById('select-all-cb');
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function updateSelectAllState() {{
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const total = LEGEND.length;
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const hidden = hiddenCommunities.size;
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selectAllCb.checked = hidden === 0;
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selectAllCb.indeterminate = hidden > 0 && hidden < total;
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}}
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function toggleAllCommunities(hide) {{
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document.querySelectorAll('.legend-item').forEach(item => {{
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hide ? item.classList.add('dimmed') : item.classList.remove('dimmed');
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}});
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document.querySelectorAll('.legend-cb').forEach(cb => {{
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cb.checked = !hide;
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}});
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LEGEND.forEach(c => {{
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if (hide) hiddenCommunities.add(c.cid); else hiddenCommunities.delete(c.cid);
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}});
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const updates = RAW_NODES.map(n => ({{ id: n.id, hidden: hide }}));
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nodesDS.update(updates);
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updateSelectAllState();
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}}
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const legendEl = document.getElementById('legend');
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LEGEND.forEach(c => {{
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const item = document.createElement('div');
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item.className = 'legend-item';
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const cb = document.createElement('input');
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cb.type = 'checkbox';
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cb.className = 'legend-cb';
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cb.checked = true;
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cb.addEventListener('change', (e) => {{
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e.stopPropagation();
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if (cb.checked) {{
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hiddenCommunities.delete(c.cid);
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item.classList.remove('dimmed');
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}} else {{
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hiddenCommunities.add(c.cid);
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item.classList.add('dimmed');
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}}
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const updates = RAW_NODES
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.filter(n => n.community === c.cid)
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.map(n => ({{ id: n.id, hidden: !cb.checked }}));
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nodesDS.update(updates);
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updateSelectAllState();
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}});
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item.innerHTML = `<div class="legend-dot" style="background:${{c.color}}"></div>
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<span class="legend-label">${{c.label}}</span>
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<span class="legend-count">${{c.count}}</span>`;
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item.prepend(cb);
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item.onclick = (e) => {{
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if (e.target === cb) return;
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cb.checked = !cb.checked;
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cb.dispatchEvent(new Event('change'));
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}};
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legendEl.appendChild(item);
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}});
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</script>"""
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_CONFIDENCE_SCORE_DEFAULTS = {"EXTRACTED": 1.0, "INFERRED": 0.5, "AMBIGUOUS": 0.2}
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|
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def attach_hyperedges(G: nx.Graph, hyperedges: list) -> None:
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"""Store hyperedges in the graph's metadata dict."""
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existing = G.graph.get("hyperedges", [])
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seen_ids = {h["id"] for h in existing}
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for h in hyperedges:
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if h.get("id") and h["id"] not in seen_ids:
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existing.append(h)
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seen_ids.add(h["id"])
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G.graph["hyperedges"] = existing
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|
|
|
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def _git_head() -> str | None:
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"""Return the current git HEAD commit hash, or None if not in a git repo."""
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import subprocess as _sp
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try:
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r = _sp.run(["git", "rev-parse", "HEAD"], capture_output=True, text=True, timeout=3)
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return r.stdout.strip() if r.returncode == 0 else None
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except Exception:
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return None
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|
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|
|
def to_json(G: nx.Graph, communities: dict[int, list[str]], output_path: str, *, force: bool = False, built_at_commit: str | None = None) -> bool:
|
|
# Safety check: refuse to silently shrink an existing graph (#479)
|
|
existing_path = Path(output_path)
|
|
if not force and existing_path.exists():
|
|
try:
|
|
existing_data = json.loads(existing_path.read_text(encoding="utf-8"))
|
|
existing_n = len(existing_data.get("nodes", []))
|
|
new_n = G.number_of_nodes()
|
|
if new_n < existing_n:
|
|
import sys as _sys
|
|
print(
|
|
f"[graphify] WARNING: new graph has {new_n} nodes but existing "
|
|
f"graph.json has {existing_n}. Refusing to overwrite — you may be "
|
|
f"missing chunk files from a previous session. "
|
|
f"Pass force=True to override.",
|
|
file=_sys.stderr,
|
|
)
|
|
return False
|
|
except Exception:
|
|
pass # unreadable existing file — proceed with write
|
|
|
|
node_community = _node_community_map(communities)
|
|
try:
|
|
data = json_graph.node_link_data(G, edges="links")
|
|
except TypeError:
|
|
data = json_graph.node_link_data(G)
|
|
for node in data["nodes"]:
|
|
node["community"] = node_community.get(node["id"])
|
|
node["norm_label"] = _strip_diacritics(node.get("label", "")).lower()
|
|
for link in data["links"]:
|
|
if "confidence_score" not in link:
|
|
conf = link.get("confidence", "EXTRACTED")
|
|
link["confidence_score"] = _CONFIDENCE_SCORE_DEFAULTS.get(conf, 1.0)
|
|
# Restore original edge direction. Undirected NetworkX storage may
|
|
# canonicalize endpoint order, flipping `calls` and other directional
|
|
# edges in graph.json. The build path stashes the true endpoints in
|
|
# _src/_tgt for exactly this purpose (#563).
|
|
true_src = link.pop("_src", None)
|
|
true_tgt = link.pop("_tgt", None)
|
|
if true_src is not None and true_tgt is not None:
|
|
link["source"] = true_src
|
|
link["target"] = true_tgt
|
|
data["hyperedges"] = getattr(G, "graph", {}).get("hyperedges", [])
|
|
commit = built_at_commit if built_at_commit is not None else _git_head()
|
|
if commit:
|
|
data["built_at_commit"] = commit
|
|
with open(output_path, "w", encoding="utf-8") as f: # nosec
|
|
json.dump(data, f, indent=2)
|
|
return True
|
|
|
|
|
|
def prune_dangling_edges(graph_data: dict) -> tuple[dict, int]:
|
|
"""Remove edges whose source or target node is not in the node set.
|
|
|
|
Returns the cleaned graph_data dict and the number of pruned edges.
|
|
"""
|
|
node_ids = {n["id"] for n in graph_data["nodes"]}
|
|
links_key = "links" if "links" in graph_data else "edges"
|
|
before = len(graph_data[links_key])
|
|
graph_data[links_key] = [
|
|
e for e in graph_data[links_key]
|
|
if e["source"] in node_ids and e["target"] in node_ids
|
|
]
|
|
return graph_data, before - len(graph_data[links_key])
|
|
|
|
|
|
def _cypher_escape(s: str) -> str:
|
|
"""Escape a string for safe embedding in a Cypher single-quoted literal.
|
|
|
|
Handles all characters that could prematurely terminate the literal or
|
|
inject control sequences:
|
|
- `\\` and `'` (literal terminators)
|
|
- newlines/CRs (would break the per-line statement framing)
|
|
- NUL/control bytes (defensive — Neo4j errors on raw NULs)
|
|
|
|
Also strips any leading/trailing whitespace that would let an attacker
|
|
break the `;`-terminated statement boundary used by `cypher-shell`.
|
|
Closing `}` and `)` are NOT special inside a single-quoted Cypher string,
|
|
so escaping the quote and backslash correctly is sufficient (a `}` inside
|
|
a properly-closed `'...'` literal is just a character) — but we previously
|
|
missed `\\n` / `\\r` which DO let a payload break out of the statement
|
|
line and inject a fresh MATCH/DELETE on the following line. See F-008.
|
|
"""
|
|
# First normalise: drop NUL and other C0 control chars except tab.
|
|
s = "".join(ch for ch in s if ch >= " " or ch == "\t")
|
|
return (
|
|
s.replace("\\", "\\\\")
|
|
.replace("'", "\\'")
|
|
.replace("\n", "\\n")
|
|
.replace("\r", "\\r")
|
|
)
|
|
|
|
|
|
# Restrict identifier-position values (labels and relationship types are NOT
|
|
# quoted in Cypher and so cannot be safely escaped — they must be allowlisted).
|
|
_CYPHER_IDENT_RE = re.compile(r"[^A-Za-z0-9_]")
|
|
|
|
|
|
def _cypher_label(raw: str, fallback: str) -> str:
|
|
"""Sanitise a value used in identifier position (node label / rel type).
|
|
|
|
Cypher does not provide a way to escape `:Foo` label syntax, so we must
|
|
strip everything except `[A-Za-z0-9_]` and require the result to start
|
|
with a letter; otherwise we fall back to a safe constant.
|
|
"""
|
|
cleaned = _CYPHER_IDENT_RE.sub("", raw or "")
|
|
if not cleaned or not cleaned[0].isalpha():
|
|
return fallback
|
|
return cleaned
|
|
|
|
|
|
def to_cypher(G: nx.Graph, output_path: str) -> None:
|
|
lines = ["// Neo4j Cypher import - generated by /graphify", ""]
|
|
for node_id, data in G.nodes(data=True):
|
|
label = _cypher_escape(data.get("label", node_id))
|
|
node_id_esc = _cypher_escape(node_id)
|
|
ftype = _cypher_label(
|
|
(data.get("file_type", "unknown") or "unknown").capitalize(),
|
|
"Entity",
|
|
)
|
|
lines.append(f"MERGE (n:{ftype} {{id: '{node_id_esc}', label: '{label}'}});")
|
|
lines.append("")
|
|
for u, v, data in G.edges(data=True):
|
|
rel = _cypher_label(
|
|
(data.get("relation", "RELATES_TO") or "RELATES_TO").upper(),
|
|
"RELATES_TO",
|
|
)
|
|
conf = _cypher_escape(data.get("confidence", "EXTRACTED"))
|
|
u_esc = _cypher_escape(u)
|
|
v_esc = _cypher_escape(v)
|
|
lines.append(
|
|
f"MATCH (a {{id: '{u_esc}'}}), (b {{id: '{v_esc}'}}) "
|
|
f"MERGE (a)-[:{rel} {{confidence: '{conf}'}}]->(b);"
|
|
)
|
|
with open(output_path, "w", encoding="utf-8") as f: # nosec
|
|
f.write("\n".join(lines))
|
|
|
|
|
|
def to_html(
|
|
G: nx.Graph,
|
|
communities: dict[int, list[str]],
|
|
output_path: str,
|
|
community_labels: dict[int, str] | None = None,
|
|
member_counts: dict[int, int] | None = None,
|
|
node_limit: int | None = None,
|
|
) -> None:
|
|
"""Generate an interactive vis.js HTML visualization of the graph.
|
|
|
|
Features: node size by degree, click-to-inspect panel, search box,
|
|
community filter, physics clustering by community, confidence-styled edges.
|
|
Raises ValueError if graph exceeds MAX_NODES_FOR_VIZ.
|
|
|
|
If member_counts is provided (aggregated community view), node sizes are
|
|
based on community member counts rather than graph degree.
|
|
|
|
If node_limit is set and the graph exceeds it, automatically builds an
|
|
aggregated community-level meta-graph instead of raising ValueError.
|
|
"""
|
|
limit = node_limit if node_limit is not None else _viz_node_limit()
|
|
if G.number_of_nodes() > limit:
|
|
if node_limit is not None:
|
|
# Build aggregated community meta-graph
|
|
from collections import Counter as _Counter
|
|
import networkx as _nx
|
|
print(f"Graph has {G.number_of_nodes()} nodes (above {limit} limit). Building aggregated community view...")
|
|
node_to_community = {nid: cid for cid, members in communities.items() for nid in members}
|
|
meta = _nx.Graph()
|
|
for cid, members in communities.items():
|
|
meta.add_node(str(cid), label=(community_labels or {}).get(cid, f"Community {cid}"))
|
|
edge_counts = _Counter()
|
|
for u, v in G.edges():
|
|
cu, cv = node_to_community.get(u), node_to_community.get(v)
|
|
if cu is not None and cv is not None and cu != cv:
|
|
edge_counts[(min(cu, cv), max(cu, cv))] += 1
|
|
for (cu, cv), w in edge_counts.items():
|
|
meta.add_edge(str(cu), str(cv), weight=w,
|
|
relation=f"{w} cross-community edges", confidence="AGGREGATED")
|
|
if meta.number_of_nodes() <= 1:
|
|
print("Single community - aggregated view not useful. Skipping graph.html.")
|
|
return
|
|
meta_communities = {cid: [str(cid)] for cid in communities}
|
|
mc = {cid: len(members) for cid, members in communities.items()}
|
|
to_html(meta, meta_communities, output_path,
|
|
community_labels=community_labels, member_counts=mc)
|
|
print(f"graph.html written (aggregated: {meta.number_of_nodes()} community nodes, {meta.number_of_edges()} cross-community edges)")
|
|
print("Tip: run with --obsidian for full node-level detail.")
|
|
return
|
|
raise ValueError(
|
|
f"Graph has {G.number_of_nodes()} nodes - too large for HTML viz "
|
|
f"(limit: {limit}). Use --no-viz, raise GRAPHIFY_VIZ_NODE_LIMIT, "
|
|
f"or reduce input size."
|
|
)
|
|
|
|
node_community = _node_community_map(communities)
|
|
degree = dict(G.degree())
|
|
max_deg = max(degree.values(), default=1) or 1
|
|
max_mc = (max(member_counts.values(), default=1) or 1) if member_counts else 1
|
|
|
|
# Build nodes list for vis.js
|
|
vis_nodes = []
|
|
for node_id, data in G.nodes(data=True):
|
|
cid = node_community.get(node_id, 0)
|
|
color = COMMUNITY_COLORS[cid % len(COMMUNITY_COLORS)]
|
|
label = sanitize_label(data.get("label", node_id))
|
|
deg = degree.get(node_id, 1)
|
|
if member_counts:
|
|
mc = member_counts.get(cid, 1)
|
|
size = 10 + 30 * (mc / max_mc)
|
|
font_size = 12
|
|
else:
|
|
size = 10 + 30 * (deg / max_deg)
|
|
# Only show label for high-degree nodes by default; others show on hover
|
|
font_size = 12 if deg >= max_deg * 0.15 else 0
|
|
vis_nodes.append({
|
|
"id": node_id,
|
|
"label": label,
|
|
"color": {"background": color, "border": color, "highlight": {"background": "#ffffff", "border": color}},
|
|
"size": round(size, 1),
|
|
"font": {"size": font_size, "color": "#ffffff"},
|
|
"title": _html.escape(label),
|
|
"community": cid,
|
|
"community_name": sanitize_label((community_labels or {}).get(cid, f"Community {cid}")),
|
|
"source_file": sanitize_label(str(data.get("source_file") or "")),
|
|
"file_type": data.get("file_type", ""),
|
|
"degree": deg,
|
|
})
|
|
|
|
# Build edges list. Restore original edge direction from _src/_tgt
|
|
# (stashed by build.py for exactly this reason): undirected NetworkX
|
|
# canonicalizes endpoint order, which would otherwise flip the arrow
|
|
# for `calls` and `rationale_for` in the rendered graph (#563).
|
|
vis_edges = []
|
|
for u, v, data in G.edges(data=True):
|
|
confidence = data.get("confidence", "EXTRACTED")
|
|
relation = data.get("relation", "")
|
|
true_src = data.get("_src", u)
|
|
true_tgt = data.get("_tgt", v)
|
|
vis_edges.append({
|
|
"from": true_src,
|
|
"to": true_tgt,
|
|
"label": relation,
|
|
"title": _html.escape(f"{relation} [{confidence}]"),
|
|
"dashes": confidence != "EXTRACTED",
|
|
"width": 2 if confidence == "EXTRACTED" else 1,
|
|
"color": {"opacity": 0.7 if confidence == "EXTRACTED" else 0.35},
|
|
"confidence": confidence,
|
|
})
|
|
|
|
# Build community legend data
|
|
legend_data = []
|
|
for cid in sorted((community_labels or {}).keys()):
|
|
color = COMMUNITY_COLORS[cid % len(COMMUNITY_COLORS)]
|
|
lbl = _html.escape(sanitize_label((community_labels or {}).get(cid, f"Community {cid}")))
|
|
n = member_counts.get(cid, len(communities.get(cid, []))) if member_counts else len(communities.get(cid, []))
|
|
legend_data.append({"cid": cid, "color": color, "label": lbl, "count": n})
|
|
|
|
# Escape </script> sequences so embedded JSON cannot break out of the script tag
|
|
def _js_safe(obj) -> str:
|
|
return json.dumps(obj).replace("</", "<\\/")
|
|
|
|
nodes_json = _js_safe(vis_nodes)
|
|
edges_json = _js_safe(vis_edges)
|
|
legend_json = _js_safe(legend_data)
|
|
hyperedges_json = _js_safe(getattr(G, "graph", {}).get("hyperedges", []))
|
|
title = _html.escape(sanitize_label(str(output_path)))
|
|
stats = f"{G.number_of_nodes()} nodes · {G.number_of_edges()} edges · {len(communities)} communities"
|
|
|
|
html = f"""<!DOCTYPE html>
|
|
<html lang="en">
|
|
<head>
|
|
<meta charset="UTF-8">
|
|
<title>graphify - {title}</title>
|
|
<script src="https://unpkg.com/vis-network/standalone/umd/vis-network.min.js"></script>
|
|
{_html_styles()}
|
|
</head>
|
|
<body>
|
|
<div id="graph"></div>
|
|
<div id="sidebar">
|
|
<div id="search-wrap">
|
|
<input id="search" type="text" placeholder="Search nodes..." autocomplete="off">
|
|
<div id="search-results"></div>
|
|
</div>
|
|
<div id="info-panel">
|
|
<h3>Node Info</h3>
|
|
<div id="info-content"><span class="empty">Click a node to inspect it</span></div>
|
|
</div>
|
|
<div id="legend-wrap">
|
|
<h3>Communities</h3>
|
|
<div id="legend-controls">
|
|
<label><input type="checkbox" id="select-all-cb" checked onchange="toggleAllCommunities(!this.checked)">Select All</label>
|
|
</div>
|
|
<div id="legend"></div>
|
|
</div>
|
|
<div id="stats">{stats}</div>
|
|
</div>
|
|
{_html_script(nodes_json, edges_json, legend_json)}
|
|
{_hyperedge_script(hyperedges_json)}
|
|
</body>
|
|
</html>"""
|
|
|
|
Path(output_path).write_text(html, encoding="utf-8") # nosec
|
|
|
|
|
|
# Keep backward-compatible alias - skill.md calls generate_html
|
|
generate_html = to_html
|
|
|
|
|
|
def to_obsidian(
|
|
G: nx.Graph,
|
|
communities: dict[int, list[str]],
|
|
output_dir: str,
|
|
community_labels: dict[int, str] | None = None,
|
|
cohesion: dict[int, float] | None = None,
|
|
) -> int:
|
|
"""Export graph as an Obsidian vault - one .md file per node with [[wikilinks]],
|
|
plus one _COMMUNITY_name.md overview note per community (sorted to top by underscore prefix).
|
|
|
|
Open the output directory as a vault in Obsidian to get an interactive
|
|
graph view with community colors and full-text search over node metadata.
|
|
|
|
Returns the number of node notes + community notes written.
|
|
"""
|
|
out = Path(output_dir)
|
|
out.mkdir(parents=True, exist_ok=True)
|
|
|
|
node_community = _node_community_map(communities)
|
|
|
|
# Map node_id → safe filename so wikilinks stay consistent.
|
|
# Deduplicate: if two nodes produce the same filename, append a numeric suffix.
|
|
def safe_name(label: str) -> str:
|
|
cleaned = re.sub(r'[\\/*?:"<>|#^[\]]', "", label.replace("\r\n", " ").replace("\r", " ").replace("\n", " ")).strip()
|
|
# Strip trailing .md/.mdx/.markdown so "CLAUDE.md" doesn't become "CLAUDE.md.md"
|
|
cleaned = re.sub(r"\.(md|mdx|qmd|markdown)$", "", cleaned, flags=re.IGNORECASE)
|
|
return cleaned or "unnamed"
|
|
|
|
node_filename: dict[str, str] = {}
|
|
seen_names: dict[str, int] = {}
|
|
for node_id, data in G.nodes(data=True):
|
|
base = safe_name(data.get("label", node_id))
|
|
if base in seen_names:
|
|
seen_names[base] += 1
|
|
node_filename[node_id] = f"{base}_{seen_names[base]}"
|
|
else:
|
|
seen_names[base] = 0
|
|
node_filename[node_id] = base
|
|
|
|
# Helper: compute dominant confidence for a node across all its edges
|
|
def _dominant_confidence(node_id: str) -> str:
|
|
confs = []
|
|
for u, v, edata in G.edges(node_id, data=True):
|
|
confs.append(edata.get("confidence", "EXTRACTED"))
|
|
if not confs:
|
|
return "EXTRACTED"
|
|
return Counter(confs).most_common(1)[0][0]
|
|
|
|
# Map file_type → graphify tag
|
|
_FTYPE_TAG = {
|
|
"code": "graphify/code",
|
|
"document": "graphify/document",
|
|
"paper": "graphify/paper",
|
|
"image": "graphify/image",
|
|
}
|
|
|
|
# Write one .md file per node
|
|
for node_id, data in G.nodes(data=True):
|
|
label = data.get("label", node_id)
|
|
cid = node_community.get(node_id)
|
|
community_name = (
|
|
community_labels.get(cid, f"Community {cid}")
|
|
if community_labels and cid is not None
|
|
else f"Community {cid}"
|
|
)
|
|
|
|
# Build tags for this node
|
|
ftype = data.get("file_type", "")
|
|
ftype_tag = _FTYPE_TAG.get(ftype, f"graphify/{ftype}" if ftype else "graphify/document")
|
|
dom_conf = _dominant_confidence(node_id)
|
|
conf_tag = f"graphify/{dom_conf}"
|
|
comm_tag = f"community/{_obsidian_tag(community_name)}"
|
|
node_tags = [ftype_tag, conf_tag, comm_tag]
|
|
|
|
lines: list[str] = []
|
|
|
|
# YAML frontmatter - readable in Obsidian's properties panel.
|
|
# All scalars pass through _yaml_str so a hostile source_file or
|
|
# community label cannot break out and inject sibling keys (F-009).
|
|
lines += [
|
|
"---",
|
|
f'source_file: "{_yaml_str(data.get("source_file", ""))}"',
|
|
f'type: "{_yaml_str(ftype)}"',
|
|
f'community: "{_yaml_str(community_name)}"',
|
|
]
|
|
if data.get("source_location"):
|
|
lines.append(f'location: "{_yaml_str(str(data["source_location"]))}"')
|
|
# Add tags list to frontmatter
|
|
lines.append("tags:")
|
|
for tag in node_tags:
|
|
lines.append(f" - {tag}")
|
|
lines += ["---", "", f"# {label}", ""]
|
|
|
|
# Outgoing edges as wikilinks
|
|
neighbors = list(G.neighbors(node_id))
|
|
if neighbors:
|
|
lines.append("## Connections")
|
|
for neighbor in sorted(neighbors, key=lambda n: G.nodes[n].get("label", n)):
|
|
edata = edge_data(G, node_id, neighbor)
|
|
neighbor_label = node_filename[neighbor]
|
|
relation = edata.get("relation", "")
|
|
confidence = edata.get("confidence", "EXTRACTED")
|
|
lines.append(f"- [[{neighbor_label}]] - `{relation}` [{confidence}]")
|
|
lines.append("")
|
|
|
|
# Inline tags at bottom of note body (for Obsidian tag panel)
|
|
inline_tags = " ".join(f"#{t}" for t in node_tags)
|
|
lines.append(inline_tags)
|
|
|
|
fname = node_filename[node_id] + ".md"
|
|
(out / fname).write_text("\n".join(lines), encoding="utf-8") # nosec
|
|
|
|
# Write one _COMMUNITY_name.md overview note per community
|
|
# Build inter-community edge counts for "Connections to other communities"
|
|
inter_community_edges: dict[int, dict[int, int]] = {}
|
|
for cid in communities:
|
|
inter_community_edges[cid] = {}
|
|
for u, v in G.edges():
|
|
cu = node_community.get(u)
|
|
cv = node_community.get(v)
|
|
if cu is not None and cv is not None and cu != cv:
|
|
inter_community_edges.setdefault(cu, {})
|
|
inter_community_edges.setdefault(cv, {})
|
|
inter_community_edges[cu][cv] = inter_community_edges[cu].get(cv, 0) + 1
|
|
inter_community_edges[cv][cu] = inter_community_edges[cv].get(cu, 0) + 1
|
|
|
|
# Precompute per-node community reach (number of distinct communities a node connects to)
|
|
def _community_reach(node_id: str) -> int:
|
|
neighbor_cids = {
|
|
node_community[nb]
|
|
for nb in G.neighbors(node_id)
|
|
if nb in node_community and node_community[nb] != node_community.get(node_id)
|
|
}
|
|
return len(neighbor_cids)
|
|
|
|
community_notes_written = 0
|
|
for cid, members in communities.items():
|
|
community_name = (
|
|
community_labels.get(cid, f"Community {cid}")
|
|
if community_labels and cid is not None
|
|
else f"Community {cid}"
|
|
)
|
|
n_members = len(members)
|
|
coh_value = cohesion.get(cid) if cohesion else None
|
|
|
|
lines: list[str] = []
|
|
|
|
# YAML frontmatter
|
|
lines.append("---")
|
|
lines.append("type: community")
|
|
if coh_value is not None:
|
|
lines.append(f"cohesion: {coh_value:.2f}")
|
|
lines.append(f"members: {n_members}")
|
|
lines.append("---")
|
|
lines.append("")
|
|
lines.append(f"# {community_name}")
|
|
lines.append("")
|
|
|
|
# Cohesion + member count summary
|
|
if coh_value is not None:
|
|
cohesion_desc = (
|
|
"tightly connected" if coh_value >= 0.7
|
|
else "moderately connected" if coh_value >= 0.4
|
|
else "loosely connected"
|
|
)
|
|
lines.append(f"**Cohesion:** {coh_value:.2f} - {cohesion_desc}")
|
|
lines.append(f"**Members:** {n_members} nodes")
|
|
lines.append("")
|
|
|
|
# Members section
|
|
lines.append("## Members")
|
|
for node_id in sorted(members, key=lambda n: G.nodes[n].get("label", n)):
|
|
data = G.nodes[node_id]
|
|
node_label = node_filename[node_id]
|
|
ftype = data.get("file_type", "")
|
|
source = data.get("source_file", "")
|
|
entry = f"- [[{node_label}]]"
|
|
if ftype:
|
|
entry += f" - {ftype}"
|
|
if source:
|
|
entry += f" - {source}"
|
|
lines.append(entry)
|
|
lines.append("")
|
|
|
|
# Dataview live query (improvement 2)
|
|
comm_tag_name = _obsidian_tag(community_name)
|
|
lines.append("## Live Query (requires Dataview plugin)")
|
|
lines.append("")
|
|
lines.append("```dataview")
|
|
lines.append(f"TABLE source_file, type FROM #community/{comm_tag_name}")
|
|
lines.append("SORT file.name ASC")
|
|
lines.append("```")
|
|
lines.append("")
|
|
|
|
# Connections to other communities
|
|
cross = inter_community_edges.get(cid, {})
|
|
if cross:
|
|
lines.append("## Connections to other communities")
|
|
for other_cid, edge_count in sorted(cross.items(), key=lambda x: -x[1]):
|
|
other_name = (
|
|
community_labels.get(other_cid, f"Community {other_cid}")
|
|
if community_labels and other_cid is not None
|
|
else f"Community {other_cid}"
|
|
)
|
|
other_safe = safe_name(other_name)
|
|
lines.append(f"- {edge_count} edge{'s' if edge_count != 1 else ''} to [[_COMMUNITY_{other_safe}]]")
|
|
lines.append("")
|
|
|
|
# Top bridge nodes - highest degree nodes that connect to other communities
|
|
bridge_nodes = [
|
|
(node_id, G.degree(node_id), _community_reach(node_id))
|
|
for node_id in members
|
|
if _community_reach(node_id) > 0
|
|
]
|
|
bridge_nodes.sort(key=lambda x: (-x[2], -x[1]))
|
|
top_bridges = bridge_nodes[:5]
|
|
if top_bridges:
|
|
lines.append("## Top bridge nodes")
|
|
for node_id, degree, reach in top_bridges:
|
|
node_label = node_filename[node_id]
|
|
lines.append(
|
|
f"- [[{node_label}]] - degree {degree}, connects to {reach} "
|
|
f"{'community' if reach == 1 else 'communities'}"
|
|
)
|
|
|
|
community_safe = safe_name(community_name)
|
|
fname = f"_COMMUNITY_{community_safe}.md"
|
|
(out / fname).write_text("\n".join(lines), encoding="utf-8") # nosec
|
|
community_notes_written += 1
|
|
|
|
# Improvement 4: write .obsidian/graph.json to color nodes by community in graph view
|
|
obsidian_dir = out / ".obsidian"
|
|
obsidian_dir.mkdir(exist_ok=True)
|
|
graph_config = {
|
|
"colorGroups": [
|
|
{
|
|
"query": f"tag:#community/{label.replace(' ', '_')}",
|
|
"color": {"a": 1, "rgb": int(COMMUNITY_COLORS[cid % len(COMMUNITY_COLORS)].lstrip('#'), 16)}
|
|
}
|
|
for cid, label in sorted((community_labels or {}).items())
|
|
]
|
|
}
|
|
(obsidian_dir / "graph.json").write_text(json.dumps(graph_config, indent=2), encoding="utf-8") # nosec
|
|
|
|
return G.number_of_nodes() + community_notes_written
|
|
|
|
|
|
def to_canvas(
|
|
G: nx.Graph,
|
|
communities: dict[int, list[str]],
|
|
output_path: str,
|
|
community_labels: dict[int, str] | None = None,
|
|
node_filenames: dict[str, str] | None = None,
|
|
) -> None:
|
|
"""Export graph as an Obsidian Canvas file - communities as groups, nodes as cards.
|
|
|
|
Generates a structured layout: communities arranged in a grid, nodes within
|
|
each community arranged in rows. Edges shown between connected nodes.
|
|
Opens in Obsidian as an infinite canvas with community groupings visible.
|
|
"""
|
|
# Obsidian canvas color codes (cycle through for communities)
|
|
CANVAS_COLORS = ["1", "2", "3", "4", "5", "6"] # red, orange, yellow, green, cyan, purple
|
|
|
|
def safe_name(label: str) -> str:
|
|
cleaned = re.sub(r'[\\/*?:"<>|#^[\]]', "", label.replace("\r\n", " ").replace("\r", " ").replace("\n", " ")).strip()
|
|
cleaned = re.sub(r"\.(md|mdx|qmd|markdown)$", "", cleaned, flags=re.IGNORECASE)
|
|
return cleaned or "unnamed"
|
|
|
|
# Build node_filenames if not provided (same dedup logic as to_obsidian)
|
|
if node_filenames is None:
|
|
node_filenames = {}
|
|
seen_names: dict[str, int] = {}
|
|
for node_id, data in G.nodes(data=True):
|
|
base = safe_name(data.get("label", node_id))
|
|
if base in seen_names:
|
|
seen_names[base] += 1
|
|
node_filenames[node_id] = f"{base}_{seen_names[base]}"
|
|
else:
|
|
seen_names[base] = 0
|
|
node_filenames[node_id] = base
|
|
|
|
num_communities = len(communities)
|
|
cols = math.ceil(math.sqrt(num_communities)) if num_communities > 0 else 1
|
|
rows = math.ceil(num_communities / cols) if num_communities > 0 else 1
|
|
|
|
canvas_nodes: list[dict] = []
|
|
canvas_edges: list[dict] = []
|
|
|
|
# Lay out communities in a grid
|
|
gap = 80
|
|
group_x_offsets: list[int] = []
|
|
group_y_offsets: list[int] = []
|
|
|
|
# Precompute group sizes so we can calculate offsets
|
|
sorted_cids = sorted(communities.keys())
|
|
group_sizes: dict[int, tuple[int, int]] = {}
|
|
for cid in sorted_cids:
|
|
members = communities[cid]
|
|
n = len(members)
|
|
w = max(600, 220 * math.ceil(math.sqrt(n)) if n > 0 else 600)
|
|
h = max(400, 100 * math.ceil(n / 3) + 120 if n > 0 else 400)
|
|
group_sizes[cid] = (w, h)
|
|
|
|
# Compute cumulative row heights and col widths for grid placement
|
|
# Each grid cell uses the max width/height in its col/row
|
|
col_widths: list[int] = []
|
|
row_heights: list[int] = []
|
|
for col_idx in range(cols):
|
|
max_w = 0
|
|
for row_idx in range(rows):
|
|
linear = row_idx * cols + col_idx
|
|
if linear < len(sorted_cids):
|
|
cid = sorted_cids[linear]
|
|
w, _ = group_sizes[cid]
|
|
max_w = max(max_w, w)
|
|
col_widths.append(max_w)
|
|
|
|
for row_idx in range(rows):
|
|
max_h = 0
|
|
for col_idx in range(cols):
|
|
linear = row_idx * cols + col_idx
|
|
if linear < len(sorted_cids):
|
|
cid = sorted_cids[linear]
|
|
_, h = group_sizes[cid]
|
|
max_h = max(max_h, h)
|
|
row_heights.append(max_h)
|
|
|
|
# Map from cid → (group_x, group_y, group_w, group_h)
|
|
group_layout: dict[int, tuple[int, int, int, int]] = {}
|
|
for idx, cid in enumerate(sorted_cids):
|
|
col_idx = idx % cols
|
|
row_idx = idx // cols
|
|
gx = sum(col_widths[:col_idx]) + col_idx * gap
|
|
gy = sum(row_heights[:row_idx]) + row_idx * gap
|
|
gw, gh = group_sizes[cid]
|
|
group_layout[cid] = (gx, gy, gw, gh)
|
|
|
|
# Build set of all node_ids in canvas for edge filtering
|
|
all_canvas_nodes: set[str] = set()
|
|
for members in communities.values():
|
|
all_canvas_nodes.update(members)
|
|
|
|
# Generate group and node canvas entries
|
|
for idx, cid in enumerate(sorted_cids):
|
|
members = communities[cid]
|
|
community_name = (
|
|
community_labels.get(cid, f"Community {cid}")
|
|
if community_labels and cid is not None
|
|
else f"Community {cid}"
|
|
)
|
|
gx, gy, gw, gh = group_layout[cid]
|
|
canvas_color = CANVAS_COLORS[idx % len(CANVAS_COLORS)]
|
|
|
|
# Group node
|
|
canvas_nodes.append({
|
|
"id": f"g{cid}",
|
|
"type": "group",
|
|
"label": community_name,
|
|
"x": gx,
|
|
"y": gy,
|
|
"width": gw,
|
|
"height": gh,
|
|
"color": canvas_color,
|
|
})
|
|
|
|
# Node cards inside the group - rows of 3
|
|
sorted_members = sorted(members, key=lambda n: G.nodes[n].get("label", n))
|
|
for m_idx, node_id in enumerate(sorted_members):
|
|
col = m_idx % 3
|
|
row = m_idx // 3
|
|
nx_x = gx + 20 + col * (180 + 20)
|
|
nx_y = gy + 80 + row * (60 + 20)
|
|
fname = node_filenames.get(node_id, safe_name(G.nodes[node_id].get("label", node_id)))
|
|
canvas_nodes.append({
|
|
"id": f"n_{node_id}",
|
|
"type": "file",
|
|
"file": f"{fname}.md",
|
|
"x": nx_x,
|
|
"y": nx_y,
|
|
"width": 180,
|
|
"height": 60,
|
|
})
|
|
|
|
# Generate edges - only between nodes both in canvas, cap at 200 highest-weight
|
|
all_edges_weighted: list[tuple[float, str, str, str]] = []
|
|
for u, v, edata in G.edges(data=True):
|
|
if u in all_canvas_nodes and v in all_canvas_nodes:
|
|
weight = edata.get("weight", 1.0)
|
|
relation = edata.get("relation", "")
|
|
conf = edata.get("confidence", "EXTRACTED")
|
|
label = f"{relation} [{conf}]" if relation else f"[{conf}]"
|
|
all_edges_weighted.append((weight, u, v, label))
|
|
|
|
all_edges_weighted.sort(key=lambda x: -x[0])
|
|
for weight, u, v, label in all_edges_weighted[:200]:
|
|
canvas_edges.append({
|
|
"id": f"e_{u}_{v}",
|
|
"fromNode": f"n_{u}",
|
|
"toNode": f"n_{v}",
|
|
"label": label,
|
|
})
|
|
|
|
canvas_data = {"nodes": canvas_nodes, "edges": canvas_edges}
|
|
Path(output_path).write_text(json.dumps(canvas_data, indent=2), encoding="utf-8") # nosec
|
|
|
|
|
|
def push_to_neo4j(
|
|
G: nx.Graph,
|
|
uri: str,
|
|
user: str,
|
|
password: str,
|
|
communities: dict[int, list[str]] | None = None,
|
|
) -> dict[str, int]:
|
|
"""Push graph directly to a running Neo4j instance via the Python driver.
|
|
|
|
Requires: pip install neo4j
|
|
|
|
Uses MERGE so re-running is safe - nodes and edges are upserted, not duplicated.
|
|
Returns a dict with counts of nodes and edges pushed.
|
|
"""
|
|
try:
|
|
from neo4j import GraphDatabase
|
|
except ImportError as e:
|
|
raise ImportError(
|
|
"neo4j driver not installed. Run: pip install neo4j"
|
|
) from e
|
|
|
|
node_community = _node_community_map(communities) if communities else {}
|
|
|
|
def _safe_rel(relation: str) -> str:
|
|
return re.sub(r"[^A-Z0-9_]", "_", relation.upper().replace(" ", "_").replace("-", "_")) or "RELATED_TO"
|
|
|
|
def _safe_label(label: str) -> str:
|
|
"""Sanitize a Neo4j node label to prevent Cypher injection."""
|
|
sanitized = re.sub(r"[^A-Za-z0-9_]", "", label)
|
|
return sanitized if sanitized else "Entity"
|
|
|
|
driver = GraphDatabase.driver(uri, auth=(user, password))
|
|
nodes_pushed = 0
|
|
edges_pushed = 0
|
|
|
|
with driver.session() as session:
|
|
for node_id, data in G.nodes(data=True):
|
|
props = {k: v for k, v in data.items() if isinstance(v, (str, int, float, bool))}
|
|
props["id"] = node_id
|
|
cid = node_community.get(node_id)
|
|
if cid is not None:
|
|
props["community"] = cid
|
|
ftype = _safe_label(data.get("file_type", "Entity").capitalize())
|
|
session.run(
|
|
f"MERGE (n:{ftype} {{id: $id}}) SET n += $props",
|
|
id=node_id,
|
|
props=props,
|
|
)
|
|
nodes_pushed += 1
|
|
|
|
for u, v, data in G.edges(data=True):
|
|
rel = _safe_rel(data.get("relation", "RELATED_TO"))
|
|
props = {k: v for k, v in data.items() if isinstance(v, (str, int, float, bool))}
|
|
session.run(
|
|
f"MATCH (a {{id: $src}}), (b {{id: $tgt}}) "
|
|
f"MERGE (a)-[r:{rel}]->(b) SET r += $props",
|
|
src=u,
|
|
tgt=v,
|
|
props=props,
|
|
)
|
|
edges_pushed += 1
|
|
|
|
driver.close()
|
|
return {"nodes": nodes_pushed, "edges": edges_pushed}
|
|
|
|
|
|
def to_graphml(
|
|
G: nx.Graph,
|
|
communities: dict[int, list[str]],
|
|
output_path: str,
|
|
) -> None:
|
|
"""Export graph as GraphML - opens in Gephi, yEd, and any GraphML-compatible tool.
|
|
|
|
Community IDs are written as a node attribute so Gephi can colour by community.
|
|
Edge confidence (EXTRACTED/INFERRED/AMBIGUOUS) is preserved as an edge attribute.
|
|
"""
|
|
H = G.copy()
|
|
node_community = _node_community_map(communities)
|
|
for node_id in H.nodes():
|
|
H.nodes[node_id]["community"] = node_community.get(node_id, -1)
|
|
nx.write_graphml(H, output_path)
|
|
|
|
|
|
def to_svg(
|
|
G: nx.Graph,
|
|
communities: dict[int, list[str]],
|
|
output_path: str,
|
|
community_labels: dict[int, str] | None = None,
|
|
figsize: tuple[int, int] = (20, 14),
|
|
) -> None:
|
|
"""Export graph as an SVG file using matplotlib + spring layout.
|
|
|
|
Lightweight and embeddable - works in Obsidian notes, Notion, GitHub READMEs,
|
|
and any markdown renderer. No JavaScript required.
|
|
|
|
Node size scales with degree. Community colors match the HTML output.
|
|
"""
|
|
try:
|
|
import matplotlib
|
|
matplotlib.use("Agg")
|
|
import matplotlib.pyplot as plt
|
|
import matplotlib.patches as mpatches
|
|
except ImportError as e:
|
|
raise ImportError("matplotlib not installed. Run: pip install matplotlib") from e
|
|
|
|
node_community = _node_community_map(communities)
|
|
|
|
fig, ax = plt.subplots(figsize=figsize, facecolor="#1a1a2e")
|
|
ax.set_facecolor("#1a1a2e")
|
|
ax.axis("off")
|
|
|
|
pos = nx.spring_layout(G, seed=42, k=2.0 / (G.number_of_nodes() ** 0.5 + 1))
|
|
|
|
degree = dict(G.degree())
|
|
max_deg = max(degree.values(), default=1) or 1
|
|
|
|
node_colors = [COMMUNITY_COLORS[node_community.get(n, 0) % len(COMMUNITY_COLORS)] for n in G.nodes()]
|
|
node_sizes = [300 + 1200 * (degree.get(n, 1) / max_deg) for n in G.nodes()]
|
|
|
|
# Draw edges - dashed for non-EXTRACTED
|
|
for u, v, data in G.edges(data=True):
|
|
conf = data.get("confidence", "EXTRACTED")
|
|
style = "solid" if conf == "EXTRACTED" else "dashed"
|
|
alpha = 0.6 if conf == "EXTRACTED" else 0.3
|
|
x0, y0 = pos[u]
|
|
x1, y1 = pos[v]
|
|
ax.plot([x0, x1], [y0, y1], color="#aaaaaa", linewidth=0.8,
|
|
linestyle=style, alpha=alpha, zorder=1)
|
|
|
|
nx.draw_networkx_nodes(G, pos, ax=ax, node_color=node_colors,
|
|
node_size=node_sizes, alpha=0.9)
|
|
nx.draw_networkx_labels(G, pos, ax=ax,
|
|
labels={n: G.nodes[n].get("label", n) for n in G.nodes()},
|
|
font_size=7, font_color="white")
|
|
|
|
# Legend
|
|
if community_labels:
|
|
patches = [
|
|
mpatches.Patch(
|
|
color=COMMUNITY_COLORS[cid % len(COMMUNITY_COLORS)],
|
|
label=f"{label} ({len(communities.get(cid, []))})",
|
|
)
|
|
for cid, label in sorted(community_labels.items())
|
|
]
|
|
ax.legend(handles=patches, loc="upper left", framealpha=0.7,
|
|
facecolor="#2a2a4e", labelcolor="white", fontsize=8)
|
|
|
|
plt.tight_layout()
|
|
plt.savefig(output_path, format="svg", bbox_inches="tight",
|
|
facecolor=fig.get_facecolor())
|
|
plt.close(fig)
|