remove networkx

cognee/api/v1/add/add.py

@@ -130,7 +130,7 @@ async def add(
         - DEFAULT_USER_EMAIL: Custom default user email
         - DEFAULT_USER_PASSWORD: Custom default user password
         - VECTOR_DB_PROVIDER: "lancedb" (default), "chromadb", "qdrant", "weaviate"
-        - GRAPH_DATABASE_PROVIDER: "kuzu" (default), "neo4j", "networkx"
+        - GRAPH_DATABASE_PROVIDER: "kuzu" (default), "neo4j"
 
     Raises:
         FileNotFoundError: If specified file paths don't exist

cognee/infrastructure/databases/graph/get_graph_engine.py

@@ -21,10 +21,6 @@ async def get_graph_engine() -> GraphDBInterface:
     if hasattr(graph_client, "initialize"):
         await graph_client.initialize()
 
-    # Handle loading of graph for NetworkX
-    if config["graph_database_provider"].lower() == "networkx" and graph_client.graph is None:
-        await graph_client.load_graph_from_file()
-
     return graph_client
 
 
@@ -135,8 +131,4 @@ def create_graph_engine(
             graph_database_password=graph_database_password or None,
         )
 
-    from .networkx.adapter import NetworkXAdapter
+    raise EnvironmentError(f"Unsupported graph database provider: {graph_database_provider}")
-
-    graph_client = NetworkXAdapter(filename=graph_file_path)
-
-    return graph_client

cognee/modules/retrieval/cypher_search_retriever.py

@@ -1,6 +1,5 @@
 from typing import Any, Optional
 from cognee.infrastructure.databases.graph import get_graph_engine
-from cognee.infrastructure.databases.graph.networkx.adapter import NetworkXAdapter
 from cognee.modules.retrieval.base_retriever import BaseRetriever
 from cognee.modules.retrieval.utils.completion import generate_completion
 from cognee.modules.retrieval.exceptions import SearchTypeNotSupported, CypherSearchError
@@ -31,8 +30,7 @@ class CypherSearchRetriever(BaseRetriever):
         """
         Retrieves relevant context using a cypher query.
 
-        If the graph engine is an instance of NetworkXAdapter, raises SearchTypeNotSupported. If
+        If any error occurs during execution, logs the error and raises CypherSearchError.
-        any error occurs during execution, logs the error and raises CypherSearchError.
 
         Parameters:
         -----------
@@ -47,11 +45,6 @@ class CypherSearchRetriever(BaseRetriever):
         try:
             graph_engine = await get_graph_engine()
 
-            if isinstance(graph_engine, NetworkXAdapter):
-                raise SearchTypeNotSupported(
-                    "CYPHER search type not supported for NetworkXAdapter."
-                )
-
             result = await graph_engine.query(query)
         except Exception as e:
             logger.error("Failed to execture cypher search retrieval: %s", str(e))

cognee/modules/retrieval/natural_language_retriever.py

@@ -1,7 +1,6 @@
 from typing import Any, Optional
 import logging
 from cognee.infrastructure.databases.graph import get_graph_engine
-from cognee.infrastructure.databases.graph.networkx.adapter import NetworkXAdapter
 from cognee.infrastructure.llm.get_llm_client import get_llm_client
 from cognee.infrastructure.llm.prompts import render_prompt
 from cognee.modules.retrieval.base_retriever import BaseRetriever
@@ -108,9 +107,7 @@ class NaturalLanguageRetriever(BaseRetriever):
         """
         Retrieves relevant context using a natural language query converted to Cypher.
 
-        This method raises a SearchTypeNotSupported exception if the graph engine does not
+        This method logs errors if the execution of the retrieval fails.
-        support natural language search. It also logs errors if the execution of the retrieval
-        fails.
 
         Parameters:
         -----------
@@ -126,9 +123,6 @@ class NaturalLanguageRetriever(BaseRetriever):
         try:
             graph_engine = await get_graph_engine()
 
-            if isinstance(graph_engine, (NetworkXAdapter)):
-                raise SearchTypeNotSupported("Natural language search type not supported.")
-
             return await self._execute_cypher_query(query, graph_engine)
         except Exception as e:
             logger.error("Failed to execute natural language search retrieval: %s", str(e))

cognee/modules/visualization/cognee_network_visualization.py

@@ -1,6 +1,5 @@
 import os
 import json
-import networkx
 
 from cognee.shared.logging_utils import get_logger
 from cognee.infrastructure.files.storage import LocalStorage
@@ -11,8 +10,6 @@ logger = get_logger()
 async def cognee_network_visualization(graph_data, destination_file_path: str = None):
     nodes_data, edges_data = graph_data
 
-    G = networkx.DiGraph()
-
     nodes_list = []
     color_map = {
         "Entity": "#f47710",
@@ -44,15 +41,11 @@ async def cognee_network_visualization(graph_data, destination_file_path: str =
             pass
 
         nodes_list.append(node_info)
-        G.add_node(node_id, **node_info)
 
-    edge_labels = {}
     links_list = []
     for source, target, relation, edge_info in edges_data:
         source = str(source)
         target = str(target)
-        G.add_edge(source, target)
-        edge_labels[(source, target)] = relation
         links_list.append({"source": source, "target": target, "relation": relation})
 
     html_template = """

cognee/shared/data_models.py

@@ -284,7 +284,6 @@ class SummarizedCode(BaseModel):
 
 
 class GraphDBType(Enum):
-    NETWORKX = auto()
     NEO4J = auto()
     FALKORDB = auto()
     KUZU = auto()

cognee/shared/utils.py

@@ -7,7 +7,6 @@ import requests
 import hashlib
 from datetime import datetime, timezone
 import graphistry
-import networkx as nx
 import pandas as pd
 import matplotlib.pyplot as plt
 import http.server
@@ -146,6 +145,19 @@ async def register_graphistry():
 
 
 def prepare_edges(graph, source, target, edge_key):
+    """
+    Prepare edges data for visualization.
+
+    :param graph: Either a networkx graph or a tuple of (nodes, edges)
+    :param source: Column name for source node
+    :param target: Column name for target node
+    :param edge_key: Column name for edge key/relationship
+    :return: DataFrame with edge data
+    """
+    edge_list = []
+
+    # Handle networkx graph format (for backward compatibility)
+    if hasattr(graph, "edges"):
         edge_list = [
             {
                 source: str(edge[0]),
@@ -154,12 +166,36 @@ def prepare_edges(graph, source, target, edge_key):
             }
             for edge in graph.edges(keys=True, data=True)
         ]
+    # Handle tuple format (nodes, edges)
+    elif isinstance(graph, tuple) and len(graph) == 2:
+        nodes, edges = graph
+        edge_list = [
+            {
+                source: str(edge[0]),
+                target: str(edge[1]),
+                edge_key: str(edge[2]) if len(edge) > 2 else "relationship",
+            }
+            for edge in edges
+        ]
+    # Handle empty or invalid graph
+    else:
+        edge_list = []
 
     return pd.DataFrame(edge_list)
 
 
 def prepare_nodes(graph, include_size=False):
+    """
+    Prepare nodes data for visualization.
+
+    :param graph: Either a networkx graph or a tuple of (nodes, edges)
+    :param include_size: Whether to include size information
+    :return: DataFrame with node data
+    """
     nodes_data = []
+
+    # Handle networkx graph format (for backward compatibility)
+    if hasattr(graph, "nodes"):
         for node in graph.nodes:
             node_info = graph.nodes[node]
 
@@ -183,6 +219,32 @@ def prepare_nodes(graph, include_size=False):
 
         nodes_data.append(node_data)
 
+    # Handle tuple format (nodes, edges)
+    elif isinstance(graph, tuple) and len(graph) == 2:
+        nodes, edges = graph
+        for node_id, node_info in nodes:
+            if not node_info:
+                continue
+
+            node_data = {
+                **node_info,
+                "id": str(node_id),
+                "name": node_info.get("name", str(node_id)),
+            }
+
+            if include_size:
+                default_size = 10  # Default node size
+                larger_size = 20  # Size for nodes with specific keywords in their ID
+                keywords = ["DOCUMENT", "User"]
+                node_size = (
+                    larger_size
+                    if any(keyword in str(node_id) for keyword in keywords)
+                    else default_size
+                )
+                node_data["size"] = node_size
+
+            nodes_data.append(node_data)
+
     return pd.DataFrame(nodes_data)
 
 
@@ -191,24 +253,18 @@ async def render_graph(
 ):
     await register_graphistry()
 
-    if not isinstance(graph, nx.MultiDiGraph):
+    # Get graph data from the graph engine
     graph_engine = await get_graph_engine()
-        networkx_graph = nx.MultiDiGraph()
-
     (nodes, edges) = await graph_engine.get_graph_data()
 
-        networkx_graph.add_nodes_from(nodes)
+    # Convert to dataframes for graphistry
-        networkx_graph.add_edges_from(edges)
+    edges_df = prepare_edges(graph, "source_node", "target_node", "relationship_name")
-
+    plotter = graphistry.edges(edges_df, "source_node", "target_node")
-        graph = networkx_graph
-
-    edges = prepare_edges(graph, "source_node", "target_node", "relationship_name")
-    plotter = graphistry.edges(edges, "source_node", "target_node")
     plotter = plotter.bind(edge_label="relationship_name")
 
     if include_nodes:
-        nodes = prepare_nodes(graph, include_size=include_size)
+        nodes_df = prepare_nodes(graph, include_size=include_size)
-        plotter = plotter.nodes(nodes, "id")
+        plotter = plotter.nodes(nodes_df, "id")
 
         if include_size:
             plotter = plotter.bind(point_size="size")
@@ -241,41 +297,19 @@ async def convert_to_serializable_graph(G):
 
     (nodes, edges) = G
 
-    networkx_graph = nx.MultiDiGraph()
+    # Convert nodes to serializable format
-    networkx_graph.add_nodes_from(nodes)
+    serializable_nodes = []
-    networkx_graph.add_edges_from(edges)
+    for node_id, data in nodes:
-
-    # Create a new graph to store the serializable version
-    new_G = nx.MultiDiGraph()
-
-    # Serialize nodes
-    for node, data in networkx_graph.nodes(data=True):
         serializable_data = {k: str(v) for k, v in data.items()}
-        new_G.add_node(str(node), **serializable_data)
+        serializable_nodes.append((str(node_id), serializable_data))
 
-    # Serialize edges
+    # Convert edges to serializable format
-    for u, v, data in networkx_graph.edges(data=True):
+    serializable_edges = []
+    for u, v, data in edges:
         serializable_data = {k: str(v) for k, v in data.items()}
-        new_G.add_edge(str(u), str(v), **serializable_data)
+        serializable_edges.append((str(u), str(v), serializable_data))
 
-    return new_G
+    return (serializable_nodes, serializable_edges)
-
-
-def generate_layout_positions(G, layout_func, layout_scale):
-    """
-    Generate layout positions for the graph using the specified layout function.
-    """
-    positions = layout_func(G)
-    return {str(node): (x * layout_scale, y * layout_scale) for node, (x, y) in positions.items()}
-
-
-def assign_node_colors(G, node_attribute, palette):
-    """
-    Assign colors to nodes based on a specified attribute and a given palette.
-    """
-    unique_attrs = set(G.nodes[node].get(node_attribute, "Unknown") for node in G.nodes)
-    color_map = {attr: palette[i % len(palette)] for i, attr in enumerate(unique_attrs)}
-    return [color_map[G.nodes[node].get(node_attribute, "Unknown")] for node in G.nodes], color_map
 
 
 def embed_logo(p, layout_scale, logo_alpha, position):
@@ -309,14 +343,16 @@ def embed_logo(p, layout_scale, logo_alpha, position):
 
 def graph_to_tuple(graph):
     """
-    Converts a networkx graph to a tuple of (nodes, edges).
+    Converts a graph to a tuple of (nodes, edges).
 
-    :param graph: A networkx graph.
+    :param graph: A graph represented as a tuple of (nodes, edges).
     :return: A tuple (nodes, edges).
     """
-    nodes = list(graph.nodes(data=True))  # Get nodes with attributes
+    if isinstance(graph, tuple) and len(graph) == 2:
-    edges = list(graph.edges(data=True))  # Get edges with attributes
+        return graph
-    return (nodes, edges)
+
+    # If it's some other format, return empty tuple
+    return ([], [])
 
 
 def start_visualization_server(

cognee/tests/tasks/descriptive_metrics/metric_consistency_test.py

@@ -4,16 +4,18 @@ import asyncio
 
 
 async def check_graph_metrics_consistency_across_adapters(include_optional=False):
+    # NetworkX has been moved to the community package
+    # This test now only uses neo4j and kuzu for consistency checks
     neo4j_metrics = await get_metrics(provider="neo4j", include_optional=include_optional)
-    networkx_metrics = await get_metrics(provider="networkx", include_optional=include_optional)
+    kuzu_metrics = await get_metrics(provider="kuzu", include_optional=include_optional)
 
-    diff_keys = set(neo4j_metrics.keys()).symmetric_difference(set(networkx_metrics.keys()))
+    diff_keys = set(neo4j_metrics.keys()).symmetric_difference(set(kuzu_metrics.keys()))
     if diff_keys:
         raise AssertionError(f"Metrics dictionaries have different keys: {diff_keys}")
 
     for key, neo4j_value in neo4j_metrics.items():
-        assert networkx_metrics[key] == neo4j_value, (
+        assert kuzu_metrics[key] == neo4j_value, (
-            f"Difference in '{key}': got {neo4j_value} with neo4j and {networkx_metrics[key]} with networkx"
+            f"Difference in '{key}': got {neo4j_value} with neo4j and {kuzu_metrics[key]} with kuzu"
         )
 
 

cognee/tests/tasks/descriptive_metrics/networkx_metrics_test.py

@@ -3,5 +3,10 @@ import asyncio
 
 
 if __name__ == "__main__":
-    asyncio.run(assert_metrics(provider="networkx", include_optional=False))
+    # NetworkX has been moved to the community package
-    asyncio.run(assert_metrics(provider="networkx", include_optional=True))
+    # To run these tests, install the community networkx adapter first
+    # and update the imports accordingly
+    print("NetworkX tests have been moved to the community package")
+    print("Please install the community networkx adapter to run these tests")
+    # asyncio.run(assert_metrics(provider="networkx", include_optional=False))
+    # asyncio.run(assert_metrics(provider="networkx", include_optional=True))

cognee/tests/test_falkordb.py

@@ -99,7 +99,7 @@ async def main():
     from cognee.infrastructure.databases.graph import get_graph_config
 
     graph_config = get_graph_config()
-    assert not os.path.exists(graph_config.graph_file_path), "Networkx graph database is not empty"
+    assert not os.path.exists(graph_config.graph_file_path), "Graph database is not empty"
 
 
 if __name__ == "__main__":

cognee/tests/test_relational_db_migration.py

@@ -60,7 +60,7 @@ async def relational_db_migration():
         relationship_label = "ReportsTo"
 
     # 3. Directly verify the 'reports to' hierarchy
-    graph_db_provider = os.getenv("GRAPH_DATABASE_PROVIDER", "networkx").lower()
+    graph_db_provider = os.getenv("GRAPH_DATABASE_PROVIDER", "kuzu").lower()
 
     distinct_node_names = set()
     found_edges = set()

cognee/tests/unit/processing/utils/utils_test.py

@@ -1,6 +1,5 @@
 import os
 import pytest
-import networkx as nx
 import pandas as pd
 from unittest.mock import patch, mock_open
 from io import BytesIO
@@ -58,18 +57,27 @@ def test_get_file_content_hash_stream():
 
 
 def test_prepare_edges():
-    graph = nx.MultiDiGraph()
+    # Test with tuple format (nodes, edges)
-    graph.add_edge("A", "B", key="AB", weight=1)
+    nodes = [("A", {"name": "Node A"}), ("B", {"name": "Node B"})]
+    edges = [("A", "B", "AB", {"weight": 1})]
+    graph = (nodes, edges)
     edges_df = prepare_edges(graph, "source", "target", "key")
 
     assert isinstance(edges_df, pd.DataFrame)
     assert len(edges_df) == 1
+    assert edges_df.iloc[0]["source"] == "A"
+    assert edges_df.iloc[0]["target"] == "B"
+    assert edges_df.iloc[0]["key"] == "AB"
 
 
 def test_prepare_nodes():
-    graph = nx.Graph()
+    # Test with tuple format (nodes, edges)
-    graph.add_node(1, name="Node1")
+    nodes = [(1, {"name": "Node1"}), (2, {"name": "Node2"})]
+    edges = []
+    graph = (nodes, edges)
     nodes_df = prepare_nodes(graph)
 
     assert isinstance(nodes_df, pd.DataFrame)
-    assert len(nodes_df) == 1
+    assert len(nodes_df) == 2
+    assert nodes_df.iloc[0]["name"] == "Node1"
+    assert nodes_df.iloc[1]["name"] == "Node2"

poetry.lock

@@ -1,4 +1,4 @@
-# This file is automatically @generated by Poetry 2.1.3 and should not be changed by hand.
+# This file is automatically @generated by Poetry 2.1.2 and should not be changed by hand.
 
 [[package]]
 name = "aiobotocore"
@@ -1406,6 +1406,27 @@ files = [
     {file = "coverage-7.9.1-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:0b3496922cb5f4215bf5caaef4cf12364a26b0be82e9ed6d050f3352cf2d7ef0"},
     {file = "coverage-7.9.1-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:9565c3ab1c93310569ec0d86b017f128f027cab0b622b7af288696d7ed43a16d"},
     {file = "coverage-7.9.1-cp313-cp313t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2241ad5dbf79ae1d9c08fe52b36d03ca122fb9ac6bca0f34439e99f8327ac89f"},
+    {file = "coverage-7.9.1-cp313-cp313t-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:3bb5838701ca68b10ebc0937dbd0eb81974bac54447c55cd58dea5bca8451029"},
+    {file = "coverage-7.9.1-cp313-cp313t-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b30a25f814591a8c0c5372c11ac8967f669b97444c47fd794926e175c4047ece"},
+    {file = "coverage-7.9.1-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:2d04b16a6062516df97969f1ae7efd0de9c31eb6ebdceaa0d213b21c0ca1a683"},
+    {file = "coverage-7.9.1-cp313-cp313t-musllinux_1_2_i686.whl", hash = "sha256:7931b9e249edefb07cd6ae10c702788546341d5fe44db5b6108a25da4dca513f"},
+    {file = "coverage-7.9.1-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:52e92b01041151bf607ee858e5a56c62d4b70f4dac85b8c8cb7fb8a351ab2c10"},
+    {file = "coverage-7.9.1-cp313-cp313t-win32.whl", hash = "sha256:684e2110ed84fd1ca5f40e89aa44adf1729dc85444004111aa01866507adf363"},
+    {file = "coverage-7.9.1-cp313-cp313t-win_amd64.whl", hash = "sha256:437c576979e4db840539674e68c84b3cda82bc824dd138d56bead1435f1cb5d7"},
+    {file = "coverage-7.9.1-cp313-cp313t-win_arm64.whl", hash = "sha256:18a0912944d70aaf5f399e350445738a1a20b50fbea788f640751c2ed9208b6c"},
+    {file = "coverage-7.9.1-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:6f424507f57878e424d9a95dc4ead3fbdd72fd201e404e861e465f28ea469951"},
+    {file = "coverage-7.9.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:535fde4001b2783ac80865d90e7cc7798b6b126f4cd8a8c54acfe76804e54e58"},
+    {file = "coverage-7.9.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:02532fd3290bb8fa6bec876520842428e2a6ed6c27014eca81b031c2d30e3f71"},
+    {file = "coverage-7.9.1-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:56f5eb308b17bca3bbff810f55ee26d51926d9f89ba92707ee41d3c061257e55"},
+    {file = "coverage-7.9.1-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bfa447506c1a52271f1b0de3f42ea0fa14676052549095e378d5bff1c505ff7b"},
+    {file = "coverage-7.9.1-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:9ca8e220006966b4a7b68e8984a6aee645a0384b0769e829ba60281fe61ec4f7"},
+    {file = "coverage-7.9.1-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:49f1d0788ba5b7ba65933f3a18864117c6506619f5ca80326b478f72acf3f385"},
+    {file = "coverage-7.9.1-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:68cd53aec6f45b8e4724c0950ce86eacb775c6be01ce6e3669fe4f3a21e768ed"},
+    {file = "coverage-7.9.1-cp39-cp39-win32.whl", hash = "sha256:95335095b6c7b1cc14c3f3f17d5452ce677e8490d101698562b2ffcacc304c8d"},
+    {file = "coverage-7.9.1-cp39-cp39-win_amd64.whl", hash = "sha256:e1b5191d1648acc439b24721caab2fd0c86679d8549ed2c84d5a7ec1bedcc244"},
+    {file = "coverage-7.9.1-pp39.pp310.pp311-none-any.whl", hash = "sha256:db0f04118d1db74db6c9e1cb1898532c7dcc220f1d2718f058601f7c3f499514"},
+    {file = "coverage-7.9.1-py3-none-any.whl", hash = "sha256:66b974b145aa189516b6bf2d8423e888b742517d37872f6ee4c5be0073bd9a3c"},
+    {file = "coverage-7.9.1.tar.gz", hash = "sha256:6cf43c78c4282708a28e466316935ec7489a9c487518a77fa68f716c67909cec"},
 ]
 
 [package.dependencies]
@@ -3988,6 +4009,8 @@ python-versions = "*"
 groups = ["main"]
 files = [
     {file = "jsonpath-ng-1.7.0.tar.gz", hash = "sha256:f6f5f7fd4e5ff79c785f1573b394043b39849fb2bb47bcead935d12b00beab3c"},
+    {file = "jsonpath_ng-1.7.0-py2-none-any.whl", hash = "sha256:898c93fc173f0c336784a3fa63d7434297544b7198124a68f9a3ef9597b0ae6e"},
+    {file = "jsonpath_ng-1.7.0-py3-none-any.whl", hash = "sha256:f3d7f9e848cba1b6da28c55b1c26ff915dc9e0b1ba7e752a53d6da8d5cbd00b6"},
 ]
 
 [package.dependencies]
@@ -6231,10 +6254,10 @@ files = [
 name = "networkx"
 version = "3.4.2"
 description = "Python package for creating and manipulating graphs and networks"
-optional = false
+optional = true
 python-versions = ">=3.10"
 groups = ["main"]
-markers = "python_version == \"3.10\""
+markers = "python_version == \"3.10\" and (extra == \"llama-index\" or extra == \"deepeval\" or extra == \"docs\")"
 files = [
     {file = "networkx-3.4.2-py3-none-any.whl", hash = "sha256:df5d4365b724cf81b8c6a7312509d0c22386097011ad1abe274afd5e9d3bbc5f"},
     {file = "networkx-3.4.2.tar.gz", hash = "sha256:307c3669428c5362aab27c8a1260aa8f47c4e91d3891f48be0141738d8d053e1"},
@@ -6252,10 +6275,10 @@ test = ["pytest (>=7.2)", "pytest-cov (>=4.0)"]
 name = "networkx"
 version = "3.5"
 description = "Python package for creating and manipulating graphs and networks"
-optional = false
+optional = true
 python-versions = ">=3.11"
 groups = ["main"]
-markers = "python_version >= \"3.11\" and python_version < \"3.13\" or python_full_version == \"3.13.0\""
+markers = "python_version >= \"3.11\" and (extra == \"llama-index\" or extra == \"deepeval\" or extra == \"docs\")"
 files = [
     {file = "networkx-3.5-py3-none-any.whl", hash = "sha256:0030d386a9a06dee3565298b4a734b68589749a544acbb6c412dc9e2489ec6ec"},
     {file = "networkx-3.5.tar.gz", hash = "sha256:d4c6f9cf81f52d69230866796b82afbccdec3db7ae4fbd1b65ea750feed50037"},
@@ -7665,6 +7688,7 @@ files = [
     {file = "psycopg2_binary-2.9.10-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:bb89f0a835bcfc1d42ccd5f41f04870c1b936d8507c6df12b7737febc40f0909"},
     {file = "psycopg2_binary-2.9.10-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:f0c2d907a1e102526dd2986df638343388b94c33860ff3bbe1384130828714b1"},
     {file = "psycopg2_binary-2.9.10-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:f8157bed2f51db683f31306aa497311b560f2265998122abe1dce6428bd86567"},
+    {file = "psycopg2_binary-2.9.10-cp313-cp313-win_amd64.whl", hash = "sha256:27422aa5f11fbcd9b18da48373eb67081243662f9b46e6fd07c3eb46e4535142"},
     {file = "psycopg2_binary-2.9.10-cp38-cp38-macosx_12_0_x86_64.whl", hash = "sha256:eb09aa7f9cecb45027683bb55aebaaf45a0df8bf6de68801a6afdc7947bb09d4"},
     {file = "psycopg2_binary-2.9.10-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b73d6d7f0ccdad7bc43e6d34273f70d587ef62f824d7261c4ae9b8b1b6af90e8"},
     {file = "psycopg2_binary-2.9.10-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ce5ab4bf46a211a8e924d307c1b1fcda82368586a19d0a24f8ae166f5c784864"},
@@ -12215,4 +12239,4 @@ weaviate = ["weaviate-client"]
 [metadata]
 lock-version = "2.1"
 python-versions = ">=3.10,<=3.13"
-content-hash = "ca2a3e8260092933419793efe202d50ae7b1c6ce738750876fd5f64a31718790"
+content-hash = "817482806193782afc9c92e1644a12f10452d6e5920ed8ba9a27c3215b95fa5a"

pyproject.toml

@@ -44,7 +44,6 @@ dependencies = [
     "pypdf>=4.1.0,<6.0.0",
     "jinja2>=3.1.3,<4",
     "matplotlib>=3.8.3,<4",
-    "networkx>=3.4.2,<4",
     "lancedb==0.21.0",
     "alembic>=1.13.3,<2",
     "pre-commit>=4.0.1,<5",