Bernt
aee0f09db8
- Datafabrik: Dockerfile fix, agentorkestrering fungerar - Vision: Identify-modell, FAISS, OCR alla testade - API: Alla 7 integrationstester passerade - Upplösare: Entitetsupplösning verifierad
104 lines
2.9 KiB
Python
104 lines
2.9 KiB
Python
#!/usr/bin/env python3
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"""
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Knowledge Graph Agent
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Bygger och uppdaterar kunskapsgrafen kontinuerligt
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"""
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import sqlite3
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import json
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from datetime import datetime
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DB_PATH = "/home/bernt/.openclaw/workspace/rivp-pilot-1/rivp.db"
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def build_knowledge_graph():
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conn = sqlite3.connect(DB_PATH)
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c = conn.cursor()
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# Hämta alla vägar och deras relationer
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c.execute('''
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SELECT r.id, r.name, r.county, r.type, r.length_km,
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COUNT(o.id) as obs_count,
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AVG(o.confidence) as avg_confidence
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FROM roads r
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LEFT JOIN observations o ON r.id = o.road_id
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GROUP BY r.id
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''')
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nodes = []
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for row in c.fetchall():
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nodes.append({
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"id": f"road-{row[0]}",
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"type": "road",
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"name": row[1],
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"county": row[2],
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"road_type": row[3],
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"length_km": row[4],
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"observation_count": row[5],
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"avg_confidence": round(row[6] or 0, 2)
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})
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# Skapa relationer mellan vägar i samma län
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edges = []
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counties = {}
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for node in nodes:
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county = node["county"]
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if county not in counties:
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counties[county] = []
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counties[county].append(node["id"])
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for county, road_ids in counties.items():
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for i in range(len(road_ids)):
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for j in range(i+1, len(road_ids)):
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edges.append({
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"source": road_ids[i],
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"target": road_ids[j],
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"type": "same_county",
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"weight": 0.5
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})
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# Hämta observationer som noder
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c.execute('''
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SELECT o.id, o.observation_type, o.severity, o.confidence,
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r.id as road_id, r.name as road_name
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FROM observations o
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JOIN roads r ON o.road_id = r.id
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LIMIT 100
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''')
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for row in c.fetchall():
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nodes.append({
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"id": f"obs-{row[0]}",
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"type": "observation",
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"observation_type": row[1],
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"severity": row[2],
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"confidence": round(row[3], 2)
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})
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edges.append({
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"source": f"obs-{row[0]}",
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"target": f"road-{row[4]}",
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"type": "observed_on",
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"weight": row[3]
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})
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conn.close()
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graph = {
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"nodes": nodes,
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"edges": edges,
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"metadata": {
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"generated": datetime.now().isoformat(),
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"node_count": len(nodes),
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"edge_count": len(edges)
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}
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}
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with open('/home/bernt/.openclaw/workspace/life-agents/knowledge_graph.json', 'w') as f:
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json.dump(graph, f, indent=2)
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return graph
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if __name__ == "__main__":
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print(f"[{datetime.now().isoformat()}] Knowledge Graph Agent")
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graph = build_knowledge_graph()
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print(f"Built graph with {graph['metadata']['node_count']} nodes and {graph['metadata']['edge_count']} edges")
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print("Knowledge graph updated.")
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