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## Description
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## Type of Change
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- [ ] Bug fix (non-breaking change that fixes an issue)
- [ ] New feature (non-breaking change that adds functionality)
- [ ] Breaking change (fix or feature that would cause existing
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- [ ] Documentation update
- [x] Code refactoring
- [ ] Performance improvement
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## Pre-submission Checklist
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- [ ] **I have tested my changes thoroughly before submitting this PR**
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<!-- This is an auto-generated comment: release notes by coderabbit.ai
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## Summary by CodeRabbit
* **Documentation**
* Deprecated legacy examples and added a migration guide mapping old
paths to new locations
* Added a comprehensive new-examples README detailing configurations,
pipelines, demos, and migration notes
* **New Features**
* Added many runnable examples and demos: database configs,
embedding/LLM setups, permissions and access-control, custom pipelines
(organizational, product recommendation, code analysis, procurement),
multimedia, visualization, temporal/ontology demos, and a local UI
starter
* **Chores**
* Updated CI/test entrypoints to use the new-examples layout
<sub>✏️ Tip: You can customize this high-level summary in your review
settings.</sub>
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
---------
Co-authored-by: lxobr <122801072+lxobr@users.noreply.github.com>
137 lines
4 KiB
Python
137 lines
4 KiB
Python
import asyncio
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from os import path
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from typing import Any
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from pydantic import SkipValidation
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from cognee.api.v1.visualize.visualize import visualize_graph
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from cognee.infrastructure.engine import DataPoint
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from cognee.infrastructure.engine.models.Edge import Edge
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from cognee.tasks.storage import add_data_points
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import cognee
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class Clothes(DataPoint):
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name: str
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description: str
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class Object(DataPoint):
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name: str
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description: str
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has_clothes: list[Clothes]
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class Person(DataPoint):
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name: str
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description: str
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has_items: SkipValidation[Any] # (Edge, list[Clothes])
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has_objects: SkipValidation[Any] # (Edge, list[Object])
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knows: SkipValidation[Any] # (Edge, list["Person"])
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async def main():
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# Clear the database for a clean state
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await cognee.prune.prune_data()
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await cognee.prune.prune_system(metadata=True)
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# Create clothes items
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item1 = Clothes(name="Shirt", description="A blue shirt")
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item2 = Clothes(name="Pants", description="Black pants")
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item3 = Clothes(name="Jacket", description="Leather jacket")
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# Create object with simple relationship to clothes
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object1 = Object(
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name="Closet", description="A wooden closet", has_clothes=[item1, item2, item3]
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)
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# Create people with various weighted relationships
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person1 = Person(
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name="John",
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description="A software engineer",
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# Single weight (backward compatible)
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has_items=(Edge(weight=0.8, relationship_type="owns"), [item1, item2]),
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# Simple relationship without weights
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has_objects=(Edge(relationship_type="stores_in"), [object1]),
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knows=[],
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)
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person2 = Person(
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name="Alice",
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description="A designer",
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# Multiple weights on edge
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has_items=(
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Edge(
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weights={
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"ownership": 0.9,
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"frequency_of_use": 0.7,
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"emotional_attachment": 0.8,
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"monetary_value": 0.6,
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},
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relationship_type="owns",
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),
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[item3],
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),
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has_objects=(Edge(relationship_type="uses"), [object1]),
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knows=[],
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)
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person3 = Person(
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name="Bob",
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description="A friend",
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# Mixed: single weight + multiple weights
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has_items=(
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Edge(
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weight=0.5, # Default weight
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weights={"trust_level": 0.9, "communication_frequency": 0.6},
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relationship_type="borrows",
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),
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[item1],
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),
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has_objects=[],
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knows=[],
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)
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# Create relationships between people with multiple weights
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person1.knows = (
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Edge(
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weights={
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"friendship_strength": 0.9,
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"trust_level": 0.8,
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"years_known": 0.7,
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"shared_interests": 0.6,
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},
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relationship_type="friend",
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),
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[person2, person3],
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)
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person2.knows = (
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Edge(
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weights={"professional_collaboration": 0.8, "personal_friendship": 0.6},
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relationship_type="colleague",
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),
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[person1],
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)
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all_data_points = [item1, item2, item3, object1, person1, person2, person3]
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# Add data points to the graph
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await add_data_points(all_data_points)
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# Visualize the graph
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graph_visualization_path = path.join(
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path.dirname(__file__), "weighted_graph_visualization.html"
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)
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await visualize_graph(graph_visualization_path)
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print("Graph with multiple weighted edges has been created and visualized!")
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print(f"Visualization saved to: {graph_visualization_path}")
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print("\nFeatures demonstrated:")
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print("- Single weight edges (backward compatible)")
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print("- Multiple weights on single edges")
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print("- Mixed single + multiple weights")
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print("- Hover over edges to see all weight information")
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print("- Different visual styling for single vs. multiple weighted edges")
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if __name__ == "__main__":
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asyncio.run(main())
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