cloud-function.py

#This code defines a Google Cloud Function named prune_graph. Its primary goal is to maintain the efficiency and relevance of the object graph that your robot is building and using for navigation and decision-making.

from google.cloud import storage
from datetime import datetime, timedelta
import networkx as nx
import json

def prune_graph(data, context):
    """Cloud Function to prune stale nodes and edges from the object graph."""

    # 1. Access graph data
    storage_client = storage.Client()
    bucket = storage_client.bucket('your-bucket-name')  # Replace with your bucket name
    blob = bucket.blob('graph_data.json')  # Replace with your file name
    graph_data = json.loads(blob.download_as_string())

    # 2. Identify stale nodes and edges
    threshold = timedelta(hours=24)  # Adjust the threshold as needed
    now = datetime.utcnow()
    graph = nx.node_link_graph(graph_data) 
    stale_nodes = []
    for node_id, node_data in graph.nodes(data=True):
        if 'timestamp' in node_data and now - datetime.fromisoformat(node_data['timestamp']) > threshold:
            stale_nodes.append(node_id)

    # Similarly, identify stale edges (if needed)
    # ...

    # 3. Delete stale nodes and edges
    graph.remove_nodes_from(stale_nodes)
    # ... (Remove stale edges if identified)

    # 4. Update the graph data
    updated_graph_data = nx.node_link_data(graph)
    blob.upload_from_string(json.dumps(updated_graph_data))

    print("Graph pruned successfully!")