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91f4d120b6
- hooks.py: use git rev-parse --git-path hooks so install/status/uninstall work in linked worktrees where .git is a file not a directory (fixes #865) - build.py: prune degree-0 code nodes after graph assembly to remove bundled/synthetic symbols with no connections (fixes #728) - skill.md: restore explicit rule prohibiting file_type:"rationale" nodes and remind model to store rationale as an attribute instead (fixes #751) Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
52 lines
2.4 KiB
Python
52 lines
2.4 KiB
Python
# assemble node+edge dicts into a NetworkX graph, preserving edge direction
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from __future__ import annotations
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import sys
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import networkx as nx
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from .validate import validate_extraction
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def build_from_json(extraction: dict) -> nx.Graph:
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errors = validate_extraction(extraction)
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# Dangling edges (stdlib/external imports) are expected - only warn about real schema errors.
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real_errors = [e for e in errors if "does not match any node id" not in e]
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if real_errors:
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print(f"[graphify] Extraction warning ({len(real_errors)} issues): {real_errors[0]}", file=sys.stderr)
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G = nx.Graph()
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for node in extraction.get("nodes", []):
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G.add_node(node["id"], **{k: v for k, v in node.items() if k != "id"})
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node_set = set(G.nodes())
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for edge in extraction.get("edges", []):
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src, tgt = edge["source"], edge["target"]
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if src not in node_set or tgt not in node_set:
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continue # skip edges to external/stdlib nodes - expected, not an error
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attrs = {k: v for k, v in edge.items() if k not in ("source", "target")}
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# Preserve original edge direction - undirected graphs lose it otherwise,
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# causing display functions to show edges backwards.
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attrs["_src"] = src
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attrs["_tgt"] = tgt
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G.add_edge(src, tgt, **attrs)
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hyperedges = extraction.get("hyperedges", [])
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if hyperedges:
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G.graph["hyperedges"] = hyperedges
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# Strip degree-0 code nodes — they are bundled/synthetic symbols with no
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# connections and only inflate god-node centrality and clustering noise.
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# Document, paper, and image nodes are kept even when isolated since they
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# may be leaf concepts intentionally referenced by the skill.
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isolated_code = [
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n for n in list(G.nodes())
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if G.degree(n) == 0 and G.nodes[n].get("file_type") == "code"
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]
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G.remove_nodes_from(isolated_code)
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return G
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def build(extractions: list[dict]) -> nx.Graph:
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"""Merge multiple extraction results into one graph."""
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combined: dict = {"nodes": [], "edges": [], "input_tokens": 0, "output_tokens": 0}
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for ext in extractions:
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combined["nodes"].extend(ext.get("nodes", []))
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combined["edges"].extend(ext.get("edges", []))
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combined["input_tokens"] += ext.get("input_tokens", 0)
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combined["output_tokens"] += ext.get("output_tokens", 0)
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return build_from_json(combined)
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