Merge pull request #73 from biggraph/darabos-rdkit

.github/workflows/test.yaml

@@ -24,7 +24,7 @@ jobs:
         run: |
           eval `ssh-agent -s`
           ssh-add - <<< '${{ secrets.LYNXSCRIBE_DEPLOY_KEY }}'
-          uv pip install -e lynxkite-core/[dev] lynxkite-app/[dev] lynxkite-graph-analytics/[dev] lynxkite-lynxscribe/ lynxkite-pillow-example/
+          uv pip install -e lynxkite-core/[dev] -e lynxkite-app/[dev] -e lynxkite-graph-analytics/[dev] -e lynxkite-bio -e lynxkite-lynxscribe/ -e lynxkite-pillow-example/
         env:
             UV_SYSTEM_PYTHON: 1
 

README.md

@@ -14,6 +14,7 @@ original LynxKite. The primary goals of this rewrite are:
 - `lynxkite-graph-analytics`: Graph analytics plugin. The classical LynxKite experience!
 - `lynxkite-pillow`: A simple example plugin.
 - `lynxkite-lynxscribe`: A plugin for building and running LynxScribe applications.
+- `lynxkite-bio`: Bioinformatics additions for LynxKite Graph Analytics.
 - `docs`: User-facing documentation. It's shared between all packages.
 
 ## Development
@@ -25,7 +26,7 @@ uv venv
 source .venv/bin/activate
 uvx pre-commit install
 # The [dev] tag is only needed if you intend on running tests
-uv pip install -e lynxkite-core/[dev] -e lynxkite-app/[dev] -e lynxkite-graph-analytics/[dev] -e lynxkite-lynxscribe/ -e lynxkite-pillow-example/
+uv pip install -e lynxkite-core/[dev] -e lynxkite-app/[dev] -e lynxkite-graph-analytics/[dev] -e lynxkite-bio -e lynxkite-lynxscribe/ -e lynxkite-pillow-example/
 ```
 
 This also builds the frontend, hopefully very quickly. To run it:

examples/AIMO

@@ -1036,4 +1036,4 @@
       "targetHandle": "input"
     }
   ]
-}
+}

examples/Bio demo

@@ -0,0 +1,857 @@
+{
+  "env": "LynxKite Graph Analytics",
+  "nodes": [
+    {
+      "id": "Import CSV 1",
+      "type": "basic",
+      "data": {
+        "title": "Import CSV",
+        "params": {
+          "filename": "examples/drug_target_data_sample.csv",
+          "separator": "<auto>",
+          "columns": "<from file>"
+        },
+        "display": null,
+        "error": null,
+        "__execution_delay": 0.0,
+        "collapsed": null,
+        "meta": {
+          "params": {
+            "separator": {
+              "default": "<auto>",
+              "type": {
+                "type": "<class 'str'>"
+              },
+              "name": "separator"
+            },
+            "filename": {
+              "default": null,
+              "type": {
+                "type": "<class 'str'>"
+              },
+              "name": "filename"
+            },
+            "columns": {
+              "name": "columns",
+              "default": "<from file>",
+              "type": {
+                "type": "<class 'str'>"
+              }
+            }
+          },
+          "outputs": {
+            "output": {
+              "position": "right",
+              "name": "output",
+              "type": {
+                "type": "None"
+              }
+            }
+          },
+          "type": "basic",
+          "inputs": {},
+          "name": "Import CSV"
+        }
+      },
+      "position": {
+        "x": 300.92214591096035,
+        "y": 1018.8292637889027
+      },
+      "width": 200.0,
+      "height": 200.0
+    },
+    {
+      "id": "Parse SMILES 1",
+      "type": "basic",
+      "data": {
+        "title": "Parse SMILES",
+        "params": {
+          "smiles_column": "SMILES",
+          "table": "df",
+          "save_as": "mols"
+        },
+        "display": null,
+        "error": null,
+        "meta": {
+          "name": "Parse SMILES",
+          "type": "basic",
+          "params": {
+            "table": {
+              "default": "df",
+              "name": "table",
+              "type": {
+                "type": "<class 'str'>"
+              }
+            },
+            "smiles_column": {
+              "name": "smiles_column",
+              "default": "SMILES",
+              "type": {
+                "type": "<class 'str'>"
+              }
+            },
+            "save_as": {
+              "name": "save_as",
+              "type": {
+                "type": "<class 'str'>"
+              },
+              "default": "mols"
+            }
+          },
+          "inputs": {
+            "bundle": {
+              "name": "bundle",
+              "type": {
+                "type": "<class 'lynxkite_graph_analytics.lynxkite_ops.Bundle'>"
+              },
+              "position": "left"
+            }
+          },
+          "outputs": {
+            "output": {
+              "position": "right",
+              "type": {
+                "type": "None"
+              },
+              "name": "output"
+            }
+          }
+        }
+      },
+      "position": {
+        "x": 580.5892989328847,
+        "y": 1012.8823965480503
+      },
+      "width": 200.0,
+      "height": 200.0
+    },
+    {
+      "id": "Graph from molecule similarity 1",
+      "type": "basic",
+      "data": {
+        "title": "Graph from molecule similarity",
+        "params": {
+          "table": "df",
+          "average_degree": "3",
+          "mols_column": "mols"
+        },
+        "display": null,
+        "error": null,
+        "meta": {
+          "inputs": {
+            "bundle": {
+              "position": "left",
+              "name": "bundle",
+              "type": {
+                "type": "<class 'lynxkite_graph_analytics.lynxkite_ops.Bundle'>"
+              }
+            }
+          },
+          "outputs": {
+            "output": {
+              "type": {
+                "type": "None"
+              },
+              "position": "right",
+              "name": "output"
+            }
+          },
+          "type": "basic",
+          "name": "Graph from molecule similarity",
+          "params": {
+            "average_degree": {
+              "default": 10.0,
+              "type": {
+                "type": "<class 'int'>"
+              },
+              "name": "average_degree"
+            },
+            "table": {
+              "default": "df",
+              "name": "table",
+              "type": {
+                "type": "<class 'str'>"
+              }
+            },
+            "mols_column": {
+              "default": "mols",
+              "name": "mols_column",
+              "type": {
+                "type": "<class 'str'>"
+              }
+            }
+          }
+        },
+        "collapsed": null,
+        "__execution_delay": 0.0
+      },
+      "position": {
+        "x": 926.4337192214458,
+        "y": 1014.4451876264845
+      },
+      "height": 200.0,
+      "width": 200.0
+    },
+    {
+      "id": "Visualize graph 1",
+      "type": "visualization",
+      "data": {
+        "title": "Visualize graph",
+        "params": {
+          "color_nodes_by": "ORGANISM",
+          "label_by": "DRUG_NAME",
+          "color_edges_by": "similarity"
+        },
+        "display": {
+          "animationDuration": 500,
+          "animationEasingUpdate": "quinticInOut",
+          "tooltip": {
+            "show": true
+          },
+          "series": [
+            {
+              "type": "graph",
+              "lineStyle": {
+                "color": "gray",
+                "curveness": 0.3
+              },
+              "emphasis": {
+                "focus": "adjacency",
+                "lineStyle": {
+                  "width": 10
+                }
+              },
+              "label": {
+                "position": "top",
+                "formatter": "{b}"
+              },
+              "data": [
+                {
+                  "id": "0",
+                  "x": -0.13734854736037372,
+                  "y": 0.0003840689616843064,
+                  "symbolSize": 22.360679774997894,
+                  "itemStyle": {
+                    "color": "#a6cee3"
+                  },
+                  "label": {
+                    "show": true
+                  },
+                  "name": "phencyclidine",
+                  "value": "Torpedo californica"
+                },
+                {
+                  "id": "1",
+                  "x": 0.4859426303201164,
+                  "y": -0.09785193844993345,
+                  "symbolSize": 22.360679774997894,
+                  "itemStyle": {
+                    "color": "#1f78b4"
+                  },
+                  "label": {
+                    "show": true
+                  },
+                  "name": "triazolam",
+                  "value": "Homo sapiens"
+                },
+                {
+                  "id": "2",
+                  "x": -0.36490537596845657,
+                  "y": 0.655747709585604,
+                  "symbolSize": 22.360679774997894,
+                  "itemStyle": {
+                    "color": "#1f78b4"
+                  },
+                  "label": {
+                    "show": true
+                  },
+                  "name": "gentian violet",
+                  "value": "Homo sapiens"
+                },
+                {
+                  "id": "3",
+                  "x": 0.8039553347691868,
+                  "y": 0.44172015990267444,
+                  "symbolSize": 22.360679774997894,
+                  "itemStyle": {
+                    "color": "#1f78b4"
+                  },
+                  "label": {
+                    "show": true
+                  },
+                  "name": "ipratropium",
+                  "value": "Homo sapiens"
+                },
+                {
+                  "id": "4",
+                  "x": -0.7876440417604583,
+                  "y": -1.0,
+                  "symbolSize": 22.360679774997894,
+                  "itemStyle": {
+                    "color": "#1f78b4"
+                  },
+                  "label": {
+                    "show": true
+                  },
+                  "name": "deoxycholic acid",
+                  "value": "Homo sapiens"
+                }
+              ],
+              "links": [
+                {
+                  "source": "3",
+                  "target": "4",
+                  "lineStyle": {
+                    "color": "#440154"
+                  },
+                  "value": 0.8481012658227848
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+                {
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+                  "value": 0.9775280898876404
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+              ]
+            }
+          ]
+        },
+        "error": null,
+        "__execution_delay": 0.0,
+        "collapsed": null,
+        "meta": {
+          "params": {
+            "label_by": {
+              "type": {
+                "format": "node attribute"
+              },
+              "name": "label_by",
+              "default": null
+            },
+            "color_nodes_by": {
+              "type": {
+                "format": "node attribute"
+              },
+              "name": "color_nodes_by",
+              "default": null
+            },
+            "color_edges_by": {
+              "name": "color_edges_by",
+              "type": {
+                "format": "edge attribute"
+              },
+              "default": null
+            }
+          },
+          "inputs": {
+            "graph": {
+              "type": {
+                "type": "<class 'lynxkite_graph_analytics.lynxkite_ops.Bundle'>"
+              },
+              "name": "graph",
+              "position": "left"
+            }
+          },
+          "outputs": {},
+          "position": {
+            "y": 167.0,
+            "x": 883.0
+          },
+          "type": "visualization",
+          "name": "Visualize graph"
+        }
+      },
+      "position": {
+        "x": 1254.2277640235457,
+        "y": 931.9705991370125
+      },
+      "height": 314.0,
+      "width": 407.0
+    },
+    {
+      "id": "Cypher 1",
+      "type": "basic",
+      "data": {
+        "title": "Cypher",
+        "params": {
+          "save_as": "result",
+          "query": "MATCH\n  (a {ORGANISM: \"Homo sapiens\"})\n  -[r]->\n  (b {ORGANISM: \"Homo sapiens\"})\nWHERE\n  r.similarity > 0.9\nRETURN a.DRUG_NAME, b.DRUG_NAME"
+        },
+        "display": null,
+        "error": null,
+        "meta": {
+          "outputs": {
+            "output": {
+              "type": {
+                "type": "None"
+              },
+              "name": "output",
+              "position": "right"
+            }
+          },
+          "inputs": {
+            "bundle": {
+              "position": "left",
+              "name": "bundle",
+              "type": {
+                "type": "<class 'lynxkite_graph_analytics.lynxkite_ops.Bundle'>"
+              }
+            }
+          },
+          "name": "Cypher",
+          "params": {
+            "query": {
+              "default": null,
+              "name": "query",
+              "type": {
+                "format": "textarea"
+              }
+            },
+            "save_as": {
+              "type": {
+                "type": "<class 'str'>"
+              },
+              "default": "result",
+              "name": "save_as"
+            }
+          },
+          "type": "basic",
+          "position": {
+            "x": 638.0,
+            "y": 577.0
+          }
+        },
+        "collapsed": null,
+        "__execution_delay": 0.0
+      },
+      "position": {
+        "x": 1209.2024653849007,
+        "y": 1567.9825632648467
+      },
+      "height": 267.0,
+      "width": 434.0
+    },
+    {
+      "id": "View tables 1",
+      "type": "table_view",
+      "data": {
+        "title": "View tables",
+        "params": {
+          "limit": 100.0
+        },
+        "display": {
+          "dataframes": {
+            "edges": {
+              "columns": [
+                "source",
+                "target",
+                "similarity"
+              ],
+              "data": [
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+                  3.0,
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+                  1.0,
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+                [
+                  1.0,
+                  3.0,
+                  0.921875
+                ],
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+                  0.0,
+                  2.0,
+                  0.9375
+                ],
+                [
+                  1.0,
+                  4.0,
+                  0.9420289855072463
+                ],
+                [
+                  2.0,
+                  4.0,
+                  0.9589041095890412
+                ],
+                [
+                  2.0,
+                  3.0,
+                  0.9775280898876404
+                ]
+              ]
+            },
+            "nodes": {
+              "columns": [
+                "Unnamed: 0",
+                "DRUG_NAME",
+                "STRUCT_ID",
+                "TARGET_NAME",
+                "TARGET_CLASS",
+                "ACCESSION",
+                "GENE",
+                "SWISSPROT",
+                "ACT_VALUE",
+                "ACT_UNIT",
+                "ACT_TYPE",
+                "ACT_COMMENT",
+                "ACT_SOURCE",
+                "RELATION",
+                "MOA",
+                "MOA_SOURCE",
+                "ACT_SOURCE_URL",
+                "MOA_SOURCE_URL",
+                "ACTION_TYPE",
+                "TDL",
+                "ORGANISM",
+                "SMILES",
+                "InChI",
+                "InChIKey",
+                "INN",
+                "mols"
+              ],
+              "data": [
+                [
+                  9737,
+                  "phencyclidine",
+                  2121,
+                  "Acetylcholine receptor subunit alpha",
+                  "Ion channel",
+                  "P02710",
+                  "CHRNA1",
+                  "ACHA_TORCA",
+                  6.66,
+                  null,
+                  "IC50",
+                  "Displacement of [3H]PCP from nAChR in Torpedo nobiliana electric organs membranes in presence of 100 uM carbachol by scintillation counting method",
+                  "CHEMBL",
+                  "=",
+                  null,
+                  "nan",
+                  null,
+                  "nan",
+                  "nan",
+                  "nan",
+                  "Torpedo californica",
+                  "C1CCN(CC1)C1(CCCCC1)C1=CC=CC=C1",
+                  "InChI=1S/C17H25N/c1-4-10-16(11-5-1)17(12-6-2-7-13-17)18-14-8-3-9-15-18/h1,4-5,10-11H,2-3,6-9,12-15H2",
+                  "JTJMJGYZQZDUJJ-UHFFFAOYSA-N",
+                  "phencyclidine",
+                  "<rdkit.Chem.rdchem.Mol object at 0x74d424169e70>"
+                ],
+                [
+                  12934,
+                  "triazolam",
+                  2729,
+                  "GABA A receptor alpha-3/beta-2/gamma-2",
+                  "Ion channel",
+                  "P18507|P34903|P47870",
+                  "GABRG2|GABRA3|GABRB2",
+                  "GBRG2_HUMAN|GBRA3_HUMAN|GBRB2_HUMAN",
+                  8.876,
+                  null,
+                  "Ki",
+                  "nan",
+                  "WOMBAT-PK",
+                  "=",
+                  1.0,
+                  "CHEMBL",
+                  null,
+                  "https://www.ebi.ac.uk/chembl/compound/inspect/CHEMBL646",
+                  "POSITIVE ALLOSTERIC MODULATOR",
+                  "Tclin|Tclin|Tclin|Tclin|Tclin|Tclin|Tclin|Tclin|Tclin",
+                  "Homo sapiens",
+                  "CC1=NN=C2CN=C(C3=CC(Cl)=CC=C3N12)C1=C(Cl)C=CC=C1",
+                  "InChI=1S/C17H12Cl2N4/c1-10-21-22-16-9-20-17(12-4-2-3-5-14(12)19)13-8-11(18)6-7-15(13)23(10)16/h2-8H,9H2,1H3",
+                  "JOFWLTCLBGQGBO-UHFFFAOYSA-N",
+                  "triazolam",
+                  "<rdkit.Chem.rdchem.Mol object at 0x74d42416ab20>"
+                ],
+                [
+                  15266,
+                  "gentian violet",
+                  4138,
+                  "D(2) dopamine receptor",
+                  "GPCR",
+                  "P14416",
+                  "DRD2",
+                  "DRD2_HUMAN",
+                  5.975,
+                  null,
+                  "Ki",
+                  "DRUGMATRIX: Dopamine D2L radioligand binding (ligand: [3H] Spiperone)",
+                  "DRUG MATRIX",
+                  "=",
+                  null,
+                  "nan",
+                  null,
+                  "nan",
+                  "nan",
+                  "Tclin",
+                  "Homo sapiens",
+                  "CN(C)C1=CC=C(C=C1)C(C1=CC=C(C=C1)N(C)C)=C1C=CC(C=C1)=[N+](C)C",
+                  "InChI=1S/C25H30N3/c1-26(2)22-13-7-19(8-14-22)25(20-9-15-23(16-10-20)27(3)4)21-11-17-24(18-12-21)28(5)6/h7-18H,1-6H3/q+1",
+                  "LGLFFNDHMLKUMI-UHFFFAOYSA-N",
+                  "gentian violet",
+                  "<rdkit.Chem.rdchem.Mol object at 0x74d424169070>"
+                ],
+                [
+                  6488,
+                  "ipratropium",
+                  1475,
+                  "Muscarinic acetylcholine receptor M1",
+                  "GPCR",
+                  "P11229",
+                  "CHRM1",
+                  "ACM1_HUMAN",
+                  9.31,
+                  null,
+                  "Ki",
+                  "nan",
+                  "WOMBAT-PK",
+                  "=",
+                  null,
+                  "nan",
+                  null,
+                  "nan",
+                  "nan",
+                  "Tclin",
+                  "Homo sapiens",
+                  "CC(C)[N+]1(C)[C@H]2CC[C@@H]1C[C@@H](C2)OC(=O)C(CO)C1=CC=CC=C1",
+                  "InChI=1S/C20H30NO3/c1-14(2)21(3)16-9-10-17(21)12-18(11-16)24-20(23)19(13-22)15-7-5-4-6-8-15/h4-8,14,16-19,22H,9-13H2,1-3H3/q+1/t16-,17+,18+,19?,21?",
+                  "OEXHQOGQTVQTAT-BHIXFJMTSA-N",
+                  "ipratropium",
+                  "<rdkit.Chem.rdchem.Mol object at 0x74d42416a7a0>"
+                ],
+                [
+                  17453,
+                  "deoxycholic acid",
+                  4988,
+                  "G-protein coupled bile acid receptor 1",
+                  "GPCR",
+                  "Q8TDU6",
+                  "GPBAR1",
+                  "GPBAR_HUMAN",
+                  6.2,
+                  null,
+                  "EC50",
+                  "nan",
+                  "IUPHAR",
+                  "=",
+                  null,
+                  "nan",
+                  null,
+                  "nan",
+                  "AGONIST",
+                  "Tchem",
+                  "Homo sapiens",
+                  "C[C@H](CCC(O)=O)[C@H]1CC[C@H]2[C@@H]3CC[C@@H]4C[C@H](O)CC[C@]4(C)[C@H]3C[C@H](O)[C@]12C",
+                  "InChI=1S/C24H40O4/c1-14(4-9-22(27)28)18-7-8-19-17-6-5-15-12-16(25)10-11-23(15,2)20(17)13-21(26)24(18,19)3/h14-21,25-26H,4-13H2,1-3H3,(H,27,28)/t14-,15-,16-,17+,18-,19+,20+,21+,23+,24-/m1/s1",
+                  "KXGVEGMKQFWNSR-LLQZFEROSA-N",
+                  "deoxycholic acid",
+                  "<rdkit.Chem.rdchem.Mol object at 0x74d424168890>"
+                ]
+              ]
+            },
+            "result": {
+              "columns": [
+                "a.DRUG_NAME",
+                "b.DRUG_NAME"
+              ],
+              "data": [
+                [
+                  "triazolam",
+                  "gentian violet"
+                ],
+                [
+                  "triazolam",
+                  "ipratropium"
+                ],
+                [
+                  "triazolam",
+                  "deoxycholic acid"
+                ],
+                [
+                  "gentian violet",
+                  "deoxycholic acid"
+                ],
+                [
+                  "gentian violet",
+                  "ipratropium"
+                ]
+              ]
+            }
+          },
+          "relations": [
+            {
+              "df": "edges",
+              "source_column": "source",
+              "target_column": "target",
+              "source_table": "nodes",
+              "target_table": "nodes",
+              "source_key": "id",
+              "target_key": "id"
+            }
+          ],
+          "other": null
+        },
+        "error": null,
+        "meta": {
+          "params": {
+            "limit": {
+              "default": 100.0,
+              "name": "limit",
+              "type": {
+                "type": "<class 'int'>"
+              }
+            }
+          },
+          "inputs": {
+            "bundle": {
+              "name": "bundle",
+              "position": "left",
+              "type": {
+                "type": "<class 'lynxkite_graph_analytics.lynxkite_ops.Bundle'>"
+              }
+            }
+          },
+          "position": {
+            "x": 1183.0,
+            "y": 534.0
+          },
+          "name": "View tables",
+          "outputs": {},
+          "type": "table_view"
+        }
+      },
+      "position": {
+        "x": 1817.1767094971015,
+        "y": 1459.025582190881
+      },
+      "width": 322.0,
+      "height": 295.0
+    }
+  ],
+  "edges": [
+    {
+      "id": "Import CSV 1 Parse SMILES 1",
+      "source": "Import CSV 1",
+      "target": "Parse SMILES 1",
+      "sourceHandle": "output",
+      "targetHandle": "bundle"
+    },
+    {
+      "id": "Parse SMILES 1 Graph from molecule similarity 1",
+      "source": "Parse SMILES 1",
+      "target": "Graph from molecule similarity 1",
+      "sourceHandle": "output",
+      "targetHandle": "bundle"
+    },
+    {
+      "id": "Graph from molecule similarity 1 Visualize graph 1",
+      "source": "Graph from molecule similarity 1",
+      "target": "Visualize graph 1",
+      "sourceHandle": "output",
+      "targetHandle": "graph"
+    },
+    {
+      "id": "Graph from molecule similarity 1 Cypher 1",
+      "source": "Graph from molecule similarity 1",
+      "target": "Cypher 1",
+      "sourceHandle": "output",
+      "targetHandle": "bundle"
+    },
+    {
+      "id": "Cypher 1 View tables 1",
+      "source": "Cypher 1",
+      "target": "View tables 1",
+      "sourceHandle": "output",
+      "targetHandle": "bundle"
+    }
+  ]
+}

examples/Graph RAG

@@ -872,4 +872,4 @@
       "targetHandle": "edges"
     }
   ]
-}
+}

examples/Image processing

@@ -281,4 +281,4 @@
       "targetHandle": "image"
     }
   ]
-}
+}

examples/LynxScribe demo

@@ -966,4 +966,4 @@
       "targetHandle": "chat_api"
     }
   ]
-}
+}

examples/PyTorch demo

@@ -620,4 +620,4 @@
       "targetHandle": "x"
     }
   ]
-}
+}

examples/RAG chatbot app

@@ -605,4 +605,4 @@
       "targetHandle": "rag_graph"
     }
   ]
-}
+}

examples/drug_target_data_sample.csv

@@ -0,0 +1,6 @@
+Unnamed: 0,DRUG_NAME,STRUCT_ID,TARGET_NAME,TARGET_CLASS,ACCESSION,GENE,SWISSPROT,ACT_VALUE,ACT_UNIT,ACT_TYPE,ACT_COMMENT,ACT_SOURCE,RELATION,MOA,MOA_SOURCE,ACT_SOURCE_URL,MOA_SOURCE_URL,ACTION_TYPE,TDL,ORGANISM,SMILES,InChI,InChIKey,INN
+9737,phencyclidine,2121,Acetylcholine receptor subunit alpha,Ion channel,P02710,CHRNA1,ACHA_TORCA,6.66,,IC50,Displacement of [3H]PCP from nAChR in Torpedo nobiliana electric organs membranes in presence of 100 uM carbachol by scintillation counting method,CHEMBL,=,,,,,,,Torpedo californica,C1CCN(CC1)C1(CCCCC1)C1=CC=CC=C1,"InChI=1S/C17H25N/c1-4-10-16(11-5-1)17(12-6-2-7-13-17)18-14-8-3-9-15-18/h1,4-5,10-11H,2-3,6-9,12-15H2",JTJMJGYZQZDUJJ-UHFFFAOYSA-N,phencyclidine
+12934,triazolam,2729,GABA A receptor alpha-3/beta-2/gamma-2,Ion channel,P18507|P34903|P47870,GABRG2|GABRA3|GABRB2,GBRG2_HUMAN|GBRA3_HUMAN|GBRB2_HUMAN,8.876,,Ki,,WOMBAT-PK,=,1.0,CHEMBL,,https://www.ebi.ac.uk/chembl/compound/inspect/CHEMBL646,POSITIVE ALLOSTERIC MODULATOR,Tclin|Tclin|Tclin|Tclin|Tclin|Tclin|Tclin|Tclin|Tclin,Homo sapiens,CC1=NN=C2CN=C(C3=CC(Cl)=CC=C3N12)C1=C(Cl)C=CC=C1,"InChI=1S/C17H12Cl2N4/c1-10-21-22-16-9-20-17(12-4-2-3-5-14(12)19)13-8-11(18)6-7-15(13)23(10)16/h2-8H,9H2,1H3",JOFWLTCLBGQGBO-UHFFFAOYSA-N,triazolam
+15266,gentian violet,4138,D(2) dopamine receptor,GPCR,P14416,DRD2,DRD2_HUMAN,5.975,,Ki,DRUGMATRIX: Dopamine D2L radioligand binding (ligand: [3H] Spiperone),DRUG MATRIX,=,,,,,,Tclin,Homo sapiens,CN(C)C1=CC=C(C=C1)C(C1=CC=C(C=C1)N(C)C)=C1C=CC(C=C1)=[N+](C)C,"InChI=1S/C25H30N3/c1-26(2)22-13-7-19(8-14-22)25(20-9-15-23(16-10-20)27(3)4)21-11-17-24(18-12-21)28(5)6/h7-18H,1-6H3/q+1",LGLFFNDHMLKUMI-UHFFFAOYSA-N,gentian violet
+6488,ipratropium,1475,Muscarinic acetylcholine receptor M1,GPCR,P11229,CHRM1,ACM1_HUMAN,9.31,,Ki,,WOMBAT-PK,=,,,,,,Tclin,Homo sapiens,CC(C)[N+]1(C)[C@H]2CC[C@@H]1C[C@@H](C2)OC(=O)C(CO)C1=CC=CC=C1,"InChI=1S/C20H30NO3/c1-14(2)21(3)16-9-10-17(21)12-18(11-16)24-20(23)19(13-22)15-7-5-4-6-8-15/h4-8,14,16-19,22H,9-13H2,1-3H3/q+1/t16-,17+,18+,19?,21?",OEXHQOGQTVQTAT-BHIXFJMTSA-N,ipratropium
+17453,deoxycholic acid,4988,G-protein coupled bile acid receptor 1,GPCR,Q8TDU6,GPBAR1,GPBAR_HUMAN,6.2,,EC50,,IUPHAR,=,,,,,AGONIST,Tchem,Homo sapiens,C[C@H](CCC(O)=O)[C@H]1CC[C@H]2[C@@H]3CC[C@@H]4C[C@H](O)CC[C@]4(C)[C@H]3C[C@H](O)[C@]12C,"InChI=1S/C24H40O4/c1-14(4-9-22(27)28)18-7-8-19-17-6-5-15-12-16(25)10-11-23(15,2)20(17)13-21(26)24(18,19)3/h14-21,25-26H,4-13H2,1-3H3,(H,27,28)/t14-,15-,16-,17+,18-,19+,20+,21+,23+,24-/m1/s1",KXGVEGMKQFWNSR-LLQZFEROSA-N,deoxycholic acid

lynxkite-app/src/lynxkite_app/crdt.py

@@ -3,7 +3,6 @@
 import asyncio
 import contextlib
 import enum
-import pathlib
 import fastapi
 import os.path
 import pycrdt

lynxkite-app/web/package-lock.json

@@ -8,7 +8,7 @@
       "name": "lynxkite",
       "version": "0.0.0",
       "dependencies": {
-        "@esbuild/linux-x64": "^0.24.0",
+        "@esbuild/linux-x64": "^0.25.0",
         "@iconify-json/tabler": "^1.2.10",
         "@svgr/core": "^8.1.0",
         "@svgr/plugin-jsx": "^8.1.0",
@@ -632,9 +632,9 @@
       }
     },
     "node_modules/@esbuild/linux-x64": {
-      "version": "0.24.2",
-      "resolved": "https://registry.npmjs.org/@esbuild/linux-x64/-/linux-x64-0.24.2.tgz",
-      "integrity": "sha512-8Qi4nQcCTbLnK9WoMjdC9NiTG6/E38RNICU6sUNqK0QFxCYgoARqVqxdFmWkdonVsvGqWhmm7MO0jyTqLqwj0Q==",
+      "version": "0.25.0",
+      "resolved": "https://registry.npmjs.org/@esbuild/linux-x64/-/linux-x64-0.25.0.tgz",
+      "integrity": "sha512-9yl91rHw/cpwMCNytUDxwj2XjFpxML0y9HAOH9pNVQDpQrBxHy01Dx+vaMu0N1CKa/RzBD2hB4u//nfc+Sd3Cw==",
       "cpu": [
         "x64"
       ],
@@ -3055,6 +3055,23 @@
         "@esbuild/win32-x64": "0.24.2"
       }
     },
+    "node_modules/esbuild/node_modules/@esbuild/linux-x64": {
+      "version": "0.24.2",
+      "resolved": "https://registry.npmjs.org/@esbuild/linux-x64/-/linux-x64-0.24.2.tgz",
+      "integrity": "sha512-8Qi4nQcCTbLnK9WoMjdC9NiTG6/E38RNICU6sUNqK0QFxCYgoARqVqxdFmWkdonVsvGqWhmm7MO0jyTqLqwj0Q==",
+      "cpu": [
+        "x64"
+      ],
+      "dev": true,
+      "license": "MIT",
+      "optional": true,
+      "os": [
+        "linux"
+      ],
+      "engines": {
+        "node": ">=18"
+      }
+    },
     "node_modules/escalade": {
       "version": "3.2.0",
       "resolved": "https://registry.npmjs.org/escalade/-/escalade-3.2.0.tgz",

lynxkite-app/web/package.json

@@ -11,7 +11,7 @@
     "preview": "npx vite preview"
   },
   "dependencies": {
-    "@esbuild/linux-x64": "^0.24.0",
+    "@esbuild/linux-x64": "^0.25.0",
     "@iconify-json/tabler": "^1.2.10",
     "@svgr/core": "^8.1.0",
     "@svgr/plugin-jsx": "^8.1.0",

lynxkite-app/web/src/index.css

@@ -286,13 +286,19 @@ body {
   .entry-list .entry {
     display: flex;
     border-bottom: 1px solid whitesmoke;
-    padding-left: 10px;
     color: #004165;
     cursor: pointer;
     user-select: none;
-    text-decoration: none;
-    justify-content: space-between;
-    padding-right: 10px;
+
+    a {
+      text-decoration: none;
+      flex: 1;
+      padding-left: 10px;
+    }
+
+    button {
+      padding-right: 10px;
+    }
   }
 
   .entry-list .open .entry,
@@ -316,11 +322,6 @@ body {
   }
 }
 
-path.react-flow__edge-path {
-  stroke-width: 2;
-  stroke: black;
-}
-
 .react-flow__edge.selected path.react-flow__edge-path {
   outline: var(--xy-selection-border, var(--xy-selection-border-default));
   outline-offset: 10px;
@@ -354,13 +355,14 @@ path.react-flow__edge-path {
   margin-top: 10px;
 }
 
-.graph-tables, .graph-relations {
-    flex: 1;
-    padding-left: 10px;
-    padding-right: 10px; 
+.graph-tables,
+.graph-relations {
+  flex: 1;
+  padding-left: 10px;
+  padding-right: 10px;
 }
 
-.graph-table-header{
+.graph-table-header {
   display: flex;
   justify-content: space-between;
   font-weight: bold;
@@ -400,7 +402,7 @@ path.react-flow__edge-path {
   font-weight: bold;
   display: block;
   margin-bottom: 2px;
-  color: #666;  /* Lighter text for labels */
+  color: #666; /* Lighter text for labels */
 }
 
 .graph-relation-attributes input {
@@ -428,4 +430,4 @@ path.react-flow__edge-path {
 
 .add-relationship-button:hover {
   background-color: #218838;
-}
+}

lynxkite-app/web/src/workspace/Workspace.tsx

@@ -41,11 +41,11 @@ import NodeSearch, {
   type Catalog,
   type Catalogs,
 } from "./NodeSearch.tsx";
+import NodeWithGraphCreationView from "./nodes/GraphCreationNode.tsx";
 import NodeWithImage from "./nodes/NodeWithImage.tsx";
 import NodeWithParams from "./nodes/NodeWithParams";
 import NodeWithTableView from "./nodes/NodeWithTableView.tsx";
 import NodeWithVisualization from "./nodes/NodeWithVisualization.tsx";
-import NodeWithGraphCreationView from "./nodes/GraphCreationNode.tsx";
 
 export default function (props: any) {
   return (
@@ -78,6 +78,9 @@ function LynxKiteFlow() {
         if (!state.workspace) return;
         if (!state.workspace.nodes) return;
         if (!state.workspace.edges) return;
+        for (const n of state.workspace.nodes) {
+          n.dragHandle = ".bg-primary";
+        }
         setNodes([...state.workspace.nodes] as Node[]);
         setEdges([...state.workspace.edges] as Edge[]);
         for (const node of state.workspace.nodes) {
@@ -284,7 +287,18 @@ function LynxKiteFlow() {
             proOptions={{ hideAttribution: true }}
             maxZoom={3}
             minZoom={0.3}
-            defaultEdgeOptions={{ markerEnd: { type: MarkerType.Arrow } }}
+            defaultEdgeOptions={{
+              markerEnd: {
+                type: MarkerType.ArrowClosed,
+                color: "black",
+                width: 15,
+                height: 15,
+              },
+              style: {
+                strokeWidth: 2,
+                stroke: "black",
+              },
+            }}
           >
             <Controls />
             <MiniMap />

lynxkite-app/web/src/workspace/nodes/LynxKiteNode.tsx

@@ -64,7 +64,7 @@ export default function LynxKiteNode(props: LynxKiteNodeProps) {
 
   return (
     <div
-      className={`node-container·${expanded ? "expanded" : "collapsed"} `}
+      className={`node-container ${expanded ? "expanded" : "collapsed"} `}
       style={{
         width: props.width || 200,
         height: expanded ? props.height || 200 : undefined,

lynxkite-app/web/src/workspace/nodes/NodeParameter.tsx

@@ -31,7 +31,7 @@ export default function NodeParameter({
         <>
           <ParamName name={name} />
           <textarea
-            className="textarea textarea-bordered w-full max-w-xs"
+            className="textarea textarea-bordered w-full"
             rows={6}
             value={value}
             onChange={(evt) => onChange(evt.currentTarget.value, { delay: 2 })}
@@ -42,7 +42,7 @@ export default function NodeParameter({
         <>
           <ParamName name={name} />
           <select
-            className="select select-bordered w-full max-w-xs"
+            className="select select-bordered w-full"
             value={value || meta.type.enum[0]}
             onChange={(evt) => onChange(evt.currentTarget.value)}
           >
@@ -69,7 +69,7 @@ export default function NodeParameter({
         <>
           <ParamName name={name} />
           <input
-            className="input input-bordered w-full max-w-xs"
+            className="input input-bordered w-full"
             value={value || ""}
             onChange={(evt) => onChange(evt.currentTarget.value, { delay: 2 })}
             onBlur={(evt) => onChange(evt.currentTarget.value, { delay: 0 })}

lynxkite-app/web/src/workspace/nodes/NodeWithTableView.tsx

@@ -19,45 +19,45 @@ export default function NodeWithTableView(props: any) {
   const display = props.data.display?.value;
   const single =
     display?.dataframes && Object.keys(display?.dataframes).length === 1;
+  const dfs = Object.entries(display?.dataframes || {});
+  dfs.sort();
   return (
     <LynxKiteNode {...props}>
       {display && [
-        Object.entries(display.dataframes || {}).map(
-          ([name, df]: [string, any]) => (
-            <React.Fragment key={name}>
-              {!single && (
-                <div
-                  key={`${name}-header`}
-                  className="df-head"
-                  onClick={() => setOpen({ ...open, [name]: !open[name] })}
-                >
-                  {name}
-                </div>
-              )}
-              {(single || open[name]) &&
-                (df.data.length > 1 ? (
-                  <Table
-                    key={`${name}-table`}
-                    columns={df.columns}
-                    data={df.data}
-                  />
-                ) : df.data.length ? (
-                  <dl key={`${name}-dl`}>
-                    {df.columns.map((c: string, i: number) => (
-                      <React.Fragment key={`${name}-${c}`}>
-                        <dt>{c}</dt>
-                        <dd>
-                          <Markdown>{toMD(df.data[0][i])}</Markdown>
-                        </dd>
-                      </React.Fragment>
-                    ))}
-                  </dl>
-                ) : (
-                  JSON.stringify(df.data)
-                ))}
-            </React.Fragment>
-          ),
-        ),
+        dfs.map(([name, df]: [string, any]) => (
+          <React.Fragment key={name}>
+            {!single && (
+              <div
+                key={`${name}-header`}
+                className="df-head"
+                onClick={() => setOpen({ ...open, [name]: !open[name] })}
+              >
+                {name}
+              </div>
+            )}
+            {(single || open[name]) &&
+              (df.data.length > 1 ? (
+                <Table
+                  key={`${name}-table`}
+                  columns={df.columns}
+                  data={df.data}
+                />
+              ) : df.data.length ? (
+                <dl key={`${name}-dl`}>
+                  {df.columns.map((c: string, i: number) => (
+                    <React.Fragment key={`${name}-${c}`}>
+                      <dt>{c}</dt>
+                      <dd>
+                        <Markdown>{toMD(df.data[0][i])}</Markdown>
+                      </dd>
+                    </React.Fragment>
+                  ))}
+                </dl>
+              ) : (
+                JSON.stringify(df.data)
+              ))}
+          </React.Fragment>
+        )),
         Object.entries(display.others || {}).map(([name, o]) => (
           <>
             <div

lynxkite-app/web/tests/examples.spec.ts

@@ -7,6 +7,11 @@ test("LynxKite Graph Analytics example", async ({ page }) => {
   expect(await ws.isErrorFree(process.env.CI ? 2000 : 1000)).toBeTruthy();
 });
 
+test("Bio example", async ({ page }) => {
+  const ws = await Workspace.open(page, "Bio demo");
+  expect(await ws.isErrorFree()).toBeTruthy();
+});
+
 test("Pytorch example", async ({ page }) => {
   const ws = await Workspace.open(page, "PyTorch demo");
   expect(await ws.isErrorFree()).toBeTruthy();

lynxkite-app/web/tests/lynxkite.ts

@@ -113,7 +113,7 @@ export class Workspace {
     targetPosition?: { x: number; y: number },
   ) {
     // Move a box around, it is a best effort operation, the exact target position may not be reached
-    const box = await this.getBox(boxId).boundingBox();
+    const box = await this.getBox(boxId).locator(".title").boundingBox();
     if (!box) {
       return;
     }

lynxkite-bio/README.md

@@ -0,0 +1,3 @@
+# LynxKite Bio
+
+An expansion for `lynxkite-graph-analytics` that provides algorithms for biological applications.

lynxkite-bio/pyproject.toml

@@ -0,0 +1,24 @@
+[project]
+name = "lynxkite-bio"
+version = "0.1.0"
+description = "Additional boxes for LynxKite Graph Analytics that add algorithms for biology."
+readme = "README.md"
+requires-python = ">=3.11"
+dependencies = [
+    "fsspec>=2025.2.0",
+    "joblib>=1.4.2",
+    "lynxkite-core",
+    "lynxkite-graph-analytics",
+    "pandas>=2.2.3",
+    "rdkit>=2024.9.5",
+    "scipy>=1.15.2",
+]
+
+[project.optional-dependencies]
+dev = [
+    "pytest>=8.3.4",
+]
+
+[tool.uv.sources]
+lynxkite-core = { path = "../lynxkite-core" }
+lynxkite-graph-analytics = { path = "../lynxkite-graph-analytics" }

lynxkite-bio/src/lynxkite_bio/__init__.py

@@ -0,0 +1,68 @@
+"""An expansion for `lynxkite-graph-analytics` that provides algorithms for biological applications."""
+
+from lynxkite_graph_analytics import Bundle, RelationDefinition
+from lynxkite.core import ops
+import joblib
+import numpy as np
+import pandas as pd
+import rdkit.Chem
+import rdkit.Chem.rdFingerprintGenerator
+import rdkit.Chem.Fingerprints.ClusterMols
+import scipy
+
+mem = joblib.Memory("../joblib-cache")
+ENV = "LynxKite Graph Analytics"
+op = ops.op_registration(ENV)
+
+
+@op("Parse SMILES")
+def parse_smiles(bundle: Bundle, *, table="df", smiles_column="SMILES", save_as="mols"):
+    """Parse SMILES strings into RDKit molecules."""
+    df = bundle.dfs[table]
+    mols = [rdkit.Chem.MolFromSmiles(smiles) for smiles in df[smiles_column].dropna()]
+    mols = [mol for mol in mols if mol is not None]
+    bundle = bundle.copy()
+    bundle.dfs[table] = df.assign(**{save_as: mols})
+    return bundle
+
+
+def _get_similarity_matrix(mols):
+    mfpgen = rdkit.Chem.rdFingerprintGenerator.GetMorganGenerator(radius=2, fpSize=2048)
+    fps = [(0, mfpgen.GetFingerprint(mol)) for mol in mols]
+    similarity_matrix = rdkit.Chem.Fingerprints.ClusterMols.GetDistanceMatrix(
+        fps, metric=rdkit.Chem.DataStructs.TanimotoSimilarity, isSimilarity=1
+    )
+    return scipy.spatial.distance.squareform(similarity_matrix)
+
+
+@op("Graph from molecule similarity")
+def graph_from_similarity(
+    bundle: Bundle, *, table="df", mols_column="mols", average_degree=10
+):
+    """Creates edges for pairs of molecules that are the most similar."""
+    df = bundle.dfs[table]
+    mols = df[mols_column]
+    similarity_matrix = _get_similarity_matrix(mols)
+    i_idx, j_idx = np.triu_indices_from(similarity_matrix, k=1)
+    sim_values = similarity_matrix[i_idx, j_idx]
+    N = int(average_degree * len(mols))
+    top_n_idx = np.argsort(sim_values)[-N:]
+    top_n_pairs = [(i_idx[k], j_idx[k], sim_values[k]) for k in top_n_idx]
+    edges = pd.DataFrame(top_n_pairs, columns=["source", "target", "similarity"])
+    nodes = df.copy()
+    nodes.index.name = "id"
+    bundle = Bundle(
+        dfs={"edges": edges, "nodes": nodes},
+        relations=[
+            RelationDefinition(
+                df="edges",
+                source_column="source",
+                target_column="target",
+                source_table="nodes",
+                target_table="nodes",
+                source_key="id",
+                target_key="id",
+            )
+        ],
+    )
+    return bundle

lynxkite-core/pyproject.toml

@@ -10,4 +10,4 @@ dependencies = [
 [project.optional-dependencies]
 dev = [
     "pytest",
-]
+]

lynxkite-core/src/lynxkite/core/workspace.py

@@ -1,5 +1,6 @@
 """For working with LynxKite workspaces."""
 
+import json
 from typing import Optional
 import dataclasses
 import os
@@ -65,7 +66,8 @@ async def execute(ws: Workspace):
 
 def save(ws: Workspace, path: str):
     """Persist a workspace to a local file in JSON format."""
-    j = ws.model_dump_json(indent=2) + "\n"
+    j = ws.model_dump()
+    j = json.dumps(j, indent=2, sort_keys=True) + "\n"
     dirname, basename = os.path.split(path)
     os.makedirs(dirname, exist_ok=True)
     # Create temp file in the same directory to make sure it's on the same filesystem.

lynxkite-graph-analytics/src/lynxkite_graph_analytics/__init__.py

@@ -1,3 +1,3 @@
-from . import lynxkite_ops  # noqa (imported to trigger registration)
+from .lynxkite_ops import *  # noqa (imported to trigger registration)
 from . import networkx_ops  # noqa (imported to trigger registration)
 from . import pytorch_model_ops  # noqa (imported to trigger registration)

lynxkite-graph-analytics/src/lynxkite_graph_analytics/lynxkite_ops.py

@@ -83,12 +83,26 @@ class Bundle:
         # TODO: Use relations.
         graph = nx.DiGraph()
         if "nodes" in self.dfs:
-            graph.add_nodes_from(
-                self.dfs["nodes"].set_index("id").to_dict("index").items()
+            df = self.dfs["nodes"]
+            if df.index.name != "id":
+                df = df.set_index("id")
+            graph.add_nodes_from(df.to_dict("index").items())
+        if "edges" in self.dfs:
+            edges = self.dfs["edges"]
+            graph.add_edges_from(
+                [
+                    (
+                        e["source"],
+                        e["target"],
+                        {
+                            k: e[k]
+                            for k in edges.columns
+                            if k not in ["source", "target"]
+                        },
+                    )
+                    for e in edges.to_records()
+                ]
             )
-        graph.add_edges_from(
-            self.dfs["edges"][["source", "target"]].itertuples(index=False, name=None)
-        )
         return graph
 
     def copy(self):
@@ -104,7 +118,7 @@ class Bundle:
             "dataframes": {
                 name: {
                     "columns": [str(c) for c in df.columns],
-                    "data": collect(df)[:limit],
+                    "data": df_for_frontend(df, limit).values.tolist(),
                 }
                 for name, df in self.dfs.items()
             },
@@ -336,8 +350,14 @@ def _map_color(value):
 
 
 @op("Visualize graph", view="visualization")
-def visualize_graph(graph: Bundle, *, color_nodes_by: ops.NodeAttribute = None):
-    nodes = graph.dfs["nodes"].copy()
+def visualize_graph(
+    graph: Bundle,
+    *,
+    color_nodes_by: ops.NodeAttribute = None,
+    label_by: ops.NodeAttribute = None,
+    color_edges_by: ops.EdgeAttribute = None,
+):
+    nodes = df_for_frontend(graph.dfs["nodes"], 10_000)
     if color_nodes_by:
         nodes["color"] = _map_color(nodes[color_nodes_by])
     for cols in ["x y", "long lat"]:
@@ -367,15 +387,21 @@ def visualize_graph(graph: Bundle, *, color_nodes_by: ops.NodeAttribute = None):
         )
         curveness = 0.3
     nodes = nodes.to_records()
-    edges = graph.dfs["edges"].drop_duplicates(["source", "target"])
+    edges = df_for_frontend(
+        graph.dfs["edges"].drop_duplicates(["source", "target"]), 10_000
+    )
+    if color_edges_by:
+        edges["color"] = _map_color(edges[color_edges_by])
     edges = edges.to_records()
     v = {
         "animationDuration": 500,
         "animationEasingUpdate": "quinticInOut",
+        "tooltip": {"show": True},
         "series": [
             {
                 "type": "graph",
-                "roam": True,
+                # Mouse zoom/panning is disabled for now. It interacts badly with ReactFlow.
+                # "roam": True,
                 "lineStyle": {
                     "color": "gray",
                     "curveness": curveness,
@@ -386,6 +412,7 @@ def visualize_graph(graph: Bundle, *, color_nodes_by: ops.NodeAttribute = None):
                         "width": 10,
                     },
                 },
+                "label": {"position": "top", "formatter": "{b}"},
                 "data": [
                     {
                         "id": str(n.id),
@@ -394,11 +421,24 @@ def visualize_graph(graph: Bundle, *, color_nodes_by: ops.NodeAttribute = None):
                         # Adjust node size to cover the same area no matter how many nodes there are.
                         "symbolSize": 50 / len(nodes) ** 0.5,
                         "itemStyle": {"color": n.color} if color_nodes_by else {},
+                        "label": {"show": label_by is not None},
+                        "name": str(getattr(n, label_by, "")) if label_by else None,
+                        "value": str(getattr(n, color_nodes_by, ""))
+                        if color_nodes_by
+                        else None,
                     }
                     for n in nodes
                 ],
                 "links": [
-                    {"source": str(r.source), "target": str(r.target)} for r in edges
+                    {
+                        "source": str(r.source),
+                        "target": str(r.target),
+                        "lineStyle": {"color": r.color} if color_edges_by else {},
+                        "value": str(getattr(r, color_edges_by, ""))
+                        if color_edges_by
+                        else None,
+                    }
+                    for r in edges
                 ],
             },
         ],
@@ -406,12 +446,18 @@ def visualize_graph(graph: Bundle, *, color_nodes_by: ops.NodeAttribute = None):
     return v
 
 
-def collect(df: pd.DataFrame):
+def df_for_frontend(df: pd.DataFrame, limit: int) -> pd.DataFrame:
+    """Returns a DataFrame with values that are safe to send to the frontend."""
+    df = df[:limit]
     if isinstance(df, pl.LazyFrame):
         df = df.collect()
     if isinstance(df, pl.DataFrame):
-        return [[d[c] for c in df.columns] for d in df.to_dicts()]
-    return df.values.tolist()
+        df = df.to_pandas()
+    # Convert non-numeric columns to strings.
+    for c in df.columns:
+        if not pd.api.types.is_numeric_dtype(df[c]):
+            df[c] = df[c].astype(str)
+    return df
 
 
 @op("View tables", view="table_view")

lynxkite-graph-analytics/src/lynxkite_graph_analytics/pytorch_model_ops.py

@@ -72,4 +72,4 @@ ops.register_passive_op(
     inputs=[ops.Input(name="input", position="top", type="tensor")],
     outputs=[ops.Output(name="output", position="bottom", type="tensor")],
     params=[ops.Parameter.basic("times", 1, int)],
-)
+)