README.md

jaris/ │ ├── graph_core.py # GraphManager: adds nodes, edges, snapshots ├── context_encoder.py # ContextEncoder: semantic + numeric encoding ├── visualizer.py # Visualizer: Matplotlib + Pyvis graph views ├── logger.py # Logger: history, acronym logs, version tracking ├── feedback_loop.py # FeedbackManager: edge weight learning │ ├── jaris_notebook.ipynb # Jupyter notebook: interactive brainspace ├── demo_data/ # (Optional) Seed acronyms, example contexts └── README.md # Documentation overview import networkx as nx

class GraphManager: def init(self): self.graph = nx.Graph()

def add_acronym_node(self, acronym, meanings, context="", relevance=1.0, related_nodes_weights=None):
    if acronym not in self.graph:
        self.graph.add_node(acronym, type='acronym', meanings=meanings, context=context, relevance=relevance)

    if related_nodes_weights:
        for related_node, weight in related_nodes_weights.items():
            self.graph.add_edge(acronym, related_node, weight=weight)

def add_edge(self, node1, node2, weight=1.0):
    self.graph.add_edge(node1, node2, weight=weight)

def get_neighbors(self, node):
    return list(self.graph.neighbors(node))

def get_node_data(self, node):
    return self.graph.nodes.get(node, {})

def snapshot_graph(self, filename="graph_snapshot.gml"):
    nx.write_gml(self.graph, filename)