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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)
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- [ ] Documentation update
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- [ ] Performance improvement
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- [ ] **I have tested my changes thoroughly before submitting this PR**
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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>
115 lines
3.8 KiB
Python
115 lines
3.8 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 Employee(DataPoint):
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name: str
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role: str
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class Company(DataPoint):
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name: str
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industry: str
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employs: SkipValidation[Any] # Mixed list: employees with/without weights
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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 employees
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michael = Employee(name="Michael", role="Regional Manager")
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dwight = Employee(name="Dwight", role="Assistant to the Regional Manager")
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jim = Employee(name="Jim", role="Sales Representative")
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pam = Employee(name="Pam", role="Receptionist")
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kevin = Employee(name="Kevin", role="Accountant")
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angela = Employee(name="Angela", role="Senior Accountant")
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oscar = Employee(name="Oscar", role="Accountant")
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stanley = Employee(name="Stanley", role="Sales Representative")
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phyllis = Employee(name="Phyllis", role="Sales Representative")
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# Create Dunder Mifflin with mixed employee relationships
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dunder_mifflin = Company(
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name="Dunder Mifflin Paper Company",
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industry="Paper Sales",
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employs=[
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# Manager with high authority weight
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(Edge(weight=0.9, relationship_type="manager"), michael),
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# Sales team with performance weights
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(
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Edge(weights={"sales_performance": 0.8, "loyalty": 0.9}, relationship_type="sales"),
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dwight,
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),
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(
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Edge(
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weights={"sales_performance": 0.7, "creativity": 0.8}, relationship_type="sales"
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),
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jim,
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),
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(
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Edge(
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weights={"sales_performance": 0.6, "customer_service": 0.9},
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relationship_type="sales",
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),
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phyllis,
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),
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(
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Edge(
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weights={"sales_performance": 0.5, "experience": 0.8}, relationship_type="sales"
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),
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stanley,
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),
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# Accounting department as a group
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(
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Edge(
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weights={"department_efficiency": 0.8, "team_cohesion": 0.9},
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relationship_type="accounting",
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),
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[oscar, kevin, angela],
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),
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# Admin staff without weights (simple relationships)
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pam,
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],
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)
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all_data_points = [
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michael,
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dwight,
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jim,
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pam,
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kevin,
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angela,
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oscar,
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stanley,
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phyllis,
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dunder_mifflin,
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]
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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(path.dirname(__file__), "dunder_mifflin_graph.html")
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await visualize_graph(graph_visualization_path)
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print("Dynamic multiple edges graph has been created and visualized!")
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print(f"Visualization saved to: {graph_visualization_path}")
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print("\nTechnical features demonstrated:")
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print("- Mixed list support: weighted and unweighted relationships in single field")
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print("- Single weight edges with relationship types")
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print("- Multiple weight edges with custom metrics")
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print("- Group relationships: single edge connecting multiple nodes")
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print("- Simple relationships without edge metadata")
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print("- Flexible edge extraction from heterogeneous data structures")
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if __name__ == "__main__":
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asyncio.run(main())
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