feat: Group DataPoints into NodeSets (#680)

<!-- .github/pull_request_template.md -->

## Description
<!-- Provide a clear description of the changes in this PR -->

## DCO Affirmation
I affirm that all code in every commit of this pull request conforms to
the terms of the Topoteretes Developer Certificate of Origin.

---------

Co-authored-by: lxobr <122801072+lxobr@users.noreply.github.com>
Co-authored-by: Boris <boris@topoteretes.com>
Co-authored-by: Boris Arzentar <borisarzentar@gmail.com>

cognee/api/v1/add/add.py

@@ -1,4 +1,4 @@
-from typing import Union, BinaryIO
+from typing import Union, BinaryIO, List, Optional
 from cognee.modules.users.models import User
 from cognee.modules.pipelines import Task
 from cognee.tasks.ingestion import ingest_data, resolve_data_directories
@@ -9,8 +9,9 @@ async def add(
     data: Union[BinaryIO, list[BinaryIO], str, list[str]],
     dataset_name: str = "main_dataset",
     user: User = None,
+    node_set: Optional[List[str]] = None,
 ):
-    tasks = [Task(resolve_data_directories), Task(ingest_data, dataset_name, user)]
+    tasks = [Task(resolve_data_directories), Task(ingest_data, dataset_name, user, node_set)]
 
     await cognee_pipeline(
         tasks=tasks, datasets=dataset_name, data=data, user=user, pipeline_name="add_pipeline"

cognee/infrastructure/databases/vector/chromadb/ChromaDBAdapter.py

@@ -1,12 +1,11 @@
-from cognee.shared.logging_utils import get_logger
-from typing import Dict, List, Optional, Any
-import os
 import json
 from uuid import UUID
-
+from typing import List, Optional
 from chromadb import AsyncHttpClient, Settings
 
 from cognee.exceptions import InvalidValueError
+from cognee.shared.logging_utils import get_logger
+from cognee.modules.storage.utils import get_own_properties
 from cognee.infrastructure.engine.utils import parse_id
 from cognee.infrastructure.engine import DataPoint
 from cognee.infrastructure.databases.vector.models.ScoredResult import ScoredResult
@@ -134,7 +133,7 @@ class ChromaDBAdapter(VectorDBInterface):
 
         metadatas = []
         for data_point in data_points:
-            metadata = data_point.model_dump()
+            metadata = get_own_properties(data_point)
             metadatas.append(process_data_for_chroma(metadata))
 
         await collection.upsert(

cognee/infrastructure/databases/vector/lancedb/LanceDBAdapter.py

@@ -312,6 +312,12 @@ class LanceDBAdapter(VectorDBInterface):
                 models_list = get_args(field_config.annotation)
                 if any(hasattr(model, "model_fields") for model in models_list):
                     related_models_fields.append(field_name)
+                elif models_list and any(get_args(model) is DataPoint for model in models_list):
+                    related_models_fields.append(field_name)
+                elif models_list and any(
+                    submodel is DataPoint for submodel in get_args(models_list[0])
+                ):
+                    related_models_fields.append(field_name)
 
             elif get_origin(field_config.annotation) == Optional:
                 model = get_args(field_config.annotation)

cognee/infrastructure/engine/models/DataPoint.py

@@ -1,10 +1,9 @@
-from datetime import datetime, timezone
-from typing import Optional, Any, Dict
-from uuid import UUID, uuid4
-
-from pydantic import BaseModel, Field
-from typing_extensions import TypedDict
 import pickle
+from uuid import UUID, uuid4
+from pydantic import BaseModel, Field
+from datetime import datetime, timezone
+from typing_extensions import TypedDict
+from typing import Optional, Any, Dict, List
 
 
 # Define metadata type
@@ -27,6 +26,7 @@ class DataPoint(BaseModel):
     topological_rank: Optional[int] = 0
     metadata: Optional[MetaData] = {"index_fields": []}
     type: str = Field(default_factory=lambda: DataPoint.__name__)
+    belongs_to_set: Optional[List["DataPoint"]] = None
 
     def __init__(self, **data):
         super().__init__(**data)

cognee/modules/data/models/Data.py

@@ -20,6 +20,7 @@ class Data(Base):
     owner_id = Column(UUID, index=True)
     content_hash = Column(String)
     external_metadata = Column(JSON)
+    node_set = Column(JSON, nullable=True)  # Store NodeSet as JSON list of strings
     token_count = Column(Integer)
     created_at = Column(DateTime(timezone=True), default=lambda: datetime.now(timezone.utc))
     updated_at = Column(DateTime(timezone=True), onupdate=lambda: datetime.now(timezone.utc))
@@ -44,5 +45,6 @@ class Data(Base):
             "rawDataLocation": self.raw_data_location,
             "createdAt": self.created_at.isoformat(),
             "updatedAt": self.updated_at.isoformat() if self.updated_at else None,
+            "nodeSet": self.node_set,
             # "datasets": [dataset.to_json() for dataset in self.datasets]
         }

cognee/modules/data/processing/document_types/Document.py

@@ -1,4 +1,4 @@
-from typing import Optional
+from typing import Optional, List
 from cognee.infrastructure.engine import DataPoint
 from cognee.modules.chunking.Chunker import Chunker
 

cognee/modules/engine/models/__init__.py

@@ -2,3 +2,4 @@ from .Entity import Entity
 from .EntityType import EntityType
 from .TableRow import TableRow
 from .TableType import TableType
+from .node_set import NodeSet

cognee/modules/engine/models/node_set.py

@@ -0,0 +1,8 @@
+from cognee.infrastructure.engine import DataPoint
+
+
+class NodeSet(DataPoint):
+    """NodeSet data point."""
+
+    name: str
+    metadata: dict = {"index_fields": ["name"]}

cognee/modules/visualization/cognee_network_visualization.py

@@ -1,18 +1,17 @@
-from cognee.shared.logging_utils import get_logger
-import networkx as nx
-import json
 import os
+import json
+import networkx
 
+from cognee.shared.logging_utils import get_logger
 from cognee.infrastructure.files.storage import LocalStorage
 
-
 logger = get_logger()
 
 
 async def cognee_network_visualization(graph_data, destination_file_path: str = None):
     nodes_data, edges_data = graph_data
 
-    G = nx.DiGraph()
+    G = networkx.DiGraph()
 
     nodes_list = []
     color_map = {
@@ -184,8 +183,8 @@ async def cognee_network_visualization(graph_data, destination_file_path: str =
     </html>
     """
 
-    html_content = html_template.replace("{nodes}", json.dumps(nodes_list, default=str))
-    html_content = html_content.replace("{links}", json.dumps(links_list, default=str))
+    html_content = html_template.replace("{nodes}", json.dumps(nodes_list))
+    html_content = html_content.replace("{links}", json.dumps(links_list))
 
     if not destination_file_path:
         home_dir = os.path.expanduser("~")

cognee/notebooks/github_analysis_step_by_step.ipynb

@@ -0,0 +1,37 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "initial_id",
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    ""
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 2
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython2",
+   "version": "2.7.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

cognee/tasks/documents/classify_documents.py

@@ -8,6 +8,8 @@ from cognee.modules.data.processing.document_types import (
     TextDocument,
     UnstructuredDocument,
 )
+from cognee.modules.engine.models.node_set import NodeSet
+from cognee.modules.engine.utils.generate_node_id import generate_node_id
 
 EXTENSION_TO_DOCUMENT_CLASS = {
     "pdf": PdfDocument,  # Text documents
@@ -49,6 +51,29 @@ EXTENSION_TO_DOCUMENT_CLASS = {
 }
 
 
+def update_node_set(document):
+    """Extracts node_set from document's external_metadata."""
+    try:
+        external_metadata = json.loads(document.external_metadata)
+    except json.JSONDecodeError:
+        return
+
+    if not isinstance(external_metadata, dict):
+        return
+
+    if "node_set" not in external_metadata:
+        return
+
+    node_set = external_metadata["node_set"]
+    if not isinstance(node_set, list):
+        return
+
+    document.belongs_to_set = [
+        NodeSet(id=generate_node_id(f"NodeSet:{node_set_name}"), name=node_set_name)
+        for node_set_name in node_set
+    ]
+
+
 async def classify_documents(data_documents: list[Data]) -> list[Document]:
     """
     Classifies a list of data items into specific document types based on file extensions.
@@ -67,6 +92,7 @@ async def classify_documents(data_documents: list[Data]) -> list[Document]:
             mime_type=data_item.mime_type,
             external_metadata=json.dumps(data_item.external_metadata, indent=4),
         )
+        update_node_set(document)
         documents.append(document)
 
     return documents

cognee/tasks/documents/extract_chunks_from_documents.py

@@ -40,6 +40,7 @@ async def extract_chunks_from_documents(
         document_token_count = 0
         for document_chunk in document.read(max_chunk_size=max_chunk_size, chunker_cls=chunker):
             document_token_count += document_chunk.chunk_size
+            document_chunk.belongs_to_set = document.belongs_to_set
             yield document_chunk
 
         await update_document_token_count(document.id, document_token_count)

cognee/tasks/ingestion/ingest_data.py

@@ -1,7 +1,8 @@
-from typing import Any, List
-
 import dlt
 import s3fs
+import json
+import inspect
+from typing import Union, BinaryIO, Any, List, Optional
 import cognee.modules.ingestion as ingestion
 from cognee.infrastructure.databases.relational import get_relational_engine
 from cognee.modules.data.methods import create_dataset, get_dataset_data, get_datasets_by_name
@@ -12,13 +13,13 @@ from cognee.modules.users.permissions.methods import give_permission_on_document
 from .get_dlt_destination import get_dlt_destination
 from .save_data_item_to_storage import save_data_item_to_storage
 
-from typing import Union, BinaryIO
-import inspect
 
 from cognee.api.v1.add.config import get_s3_config
 
 
-async def ingest_data(data: Any, dataset_name: str, user: User):
+async def ingest_data(
+    data: Any, dataset_name: str, user: User, node_set: Optional[List[str]] = None
+):
     destination = get_dlt_destination()
 
     if not user:
@@ -68,9 +69,12 @@ async def ingest_data(data: Any, dataset_name: str, user: User):
                     "mime_type": file_metadata["mime_type"],
                     "content_hash": file_metadata["content_hash"],
                     "owner_id": str(user.id),
+                    "node_set": json.dumps(node_set) if node_set else None,
                 }
 
-    async def store_data_to_dataset(data: Any, dataset_name: str, user: User):
+    async def store_data_to_dataset(
+        data: Any, dataset_name: str, user: User, node_set: Optional[List[str]] = None
+    ):
         if not isinstance(data, list):
             # Convert data to a list as we work with lists further down.
             data = [data]
@@ -107,6 +111,10 @@ async def ingest_data(data: Any, dataset_name: str, user: User):
                         await session.execute(select(Data).filter(Data.id == data_id))
                     ).scalar_one_or_none()
 
+                    ext_metadata = get_external_metadata_dict(data_item)
+                    if node_set:
+                        ext_metadata["node_set"] = node_set
+
                     if data_point is not None:
                         data_point.name = file_metadata["name"]
                         data_point.raw_data_location = file_metadata["file_path"]
@@ -114,7 +122,8 @@ async def ingest_data(data: Any, dataset_name: str, user: User):
                         data_point.mime_type = file_metadata["mime_type"]
                         data_point.owner_id = user.id
                         data_point.content_hash = file_metadata["content_hash"]
-                        data_point.external_metadata = (get_external_metadata_dict(data_item),)
+                        data_point.external_metadata = ext_metadata
+                        data_point.node_set = json.dumps(node_set) if node_set else None
                         await session.merge(data_point)
                     else:
                         data_point = Data(
@@ -125,7 +134,8 @@ async def ingest_data(data: Any, dataset_name: str, user: User):
                             mime_type=file_metadata["mime_type"],
                             owner_id=user.id,
                             content_hash=file_metadata["content_hash"],
-                            external_metadata=get_external_metadata_dict(data_item),
+                            external_metadata=ext_metadata,
+                            node_set=json.dumps(node_set) if node_set else None,
                             token_count=-1,
                         )
 
@@ -150,7 +160,7 @@ async def ingest_data(data: Any, dataset_name: str, user: User):
 
     db_engine = get_relational_engine()
 
-    file_paths = await store_data_to_dataset(data, dataset_name, user)
+    file_paths = await store_data_to_dataset(data, dataset_name, user, node_set)
 
     # Note: DLT pipeline has its own event loop, therefore objects created in another event loop
     # can't be used inside the pipeline

examples/python/simple_node_set_example.py

@@ -0,0 +1,44 @@
+import os
+import asyncio
+import cognee
+from cognee.api.v1.visualize.visualize import visualize_graph
+from cognee.shared.logging_utils import get_logger, ERROR
+
+text_a = """
+    AI is revolutionizing financial services through intelligent fraud detection
+    and automated customer service platforms.
+    """
+
+text_b = """
+    Advances in AI are enabling smarter systems that learn and adapt over time.
+    """
+
+text_c = """
+    MedTech startups have seen significant growth in recent years, driven by innovation
+    in digital health and medical devices.
+    """
+
+node_set_a = ["AI", "FinTech"]
+node_set_b = ["AI"]
+node_set_c = ["MedTech"]
+
+
+async def main():
+    await cognee.prune.prune_data()
+    await cognee.prune.prune_system(metadata=True)
+
+    await cognee.add(text_a, node_set=node_set_a)
+    await cognee.add(text_b, node_set=node_set_b)
+    await cognee.add(text_c, node_set=node_set_c)
+    await cognee.cognify()
+
+    visualization_path = os.path.join(
+        os.path.dirname(__file__), "./.artifacts/graph_visualization.html"
+    )
+    await visualize_graph(visualization_path)
+
+
+if __name__ == "__main__":
+    logger = get_logger(level=ERROR)
+    loop = asyncio.new_event_loop()
+    asyncio.run(main())