44 lines
1.6 KiB
Bash
44 lines
1.6 KiB
Bash
#!/usr/bin/env bash
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# knowledge-graph-workflow.sh — S2 科研热点追踪与知识图谱 · 可复现执行脚本
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# 子赛题四「应用 GitLink 辅助科研」交付物之一
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#
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# 用法： bash knowledge-graph-workflow.sh <KEYWORDS> [OUT_DIR] [REPOS_LIMIT]
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# 示例： bash knowledge-graph-workflow.sh "deep learning,nlp" ./out 20
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set -euo pipefail
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KEYWORDS="${1:?用法: $0 <KEYWORDS> [OUT_DIR] [REPOS_LIMIT] 例如: $0 \"deep learning,nlp\" ./out 20}"
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OUT_DIR="${2:-./knowledge-graph-output}"
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REPOS_LIMIT="${3:-20}"
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# 定位仓库根（脚本位于 skills/gitlink-research-graph/examples/）
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SCRIPT_DIR="$(cd "$(dirname "$0")" && pwd)"
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REPO_ROOT="$(cd "$SCRIPT_DIR/../../.." && pwd)"
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GRAPH="$REPO_ROOT/scripts/research/graph_build.py"
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# 本地 Windows 开发可设 GITLINK_CLI=./gitlink-cli.exe；Linux/容器走 PATH 默认值
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: "${GITLINK_CLI:=gitlink-cli}"
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echo "==> 关键词: $KEYWORDS"
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echo "==> CLI: $GITLINK_CLI"
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echo "==> 仓库上限: $REPOS_LIMIT"
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mkdir -p "$OUT_DIR"
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GITLINK_CLI="$GITLINK_CLI" python "$GRAPH" \
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--keywords "$KEYWORDS" \
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--repos-limit "$REPOS_LIMIT" \
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--out "$OUT_DIR"
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echo
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echo "==> 产物："
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ls -1 "$OUT_DIR"
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echo
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echo "==> 图谱概览："
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python -c "
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import json
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d=json.load(open('$OUT_DIR/graph.json',encoding='utf-8'))
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m=d['meta']
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print(f\"节点: {m['node_count']} (repo={m['repo_count']} scholar={m['scholar_count']} topic={m['topic_count']}) 边: {m['edge_count']}\")
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print('Top 主题:', ', '.join(h['topic'] for h in d['topic_heat'][:5]))
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print('核心学者:', ', '.join(f\"{s['login']}({s['repo_count']})\" for s in d['core_scholars'][:5]))
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"
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