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---------
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## Description
Adds a Neptune Analytics 'hybrid' integration layer to the Cognee.ai
memory storage layer. The following configuration will use Amazon
Neptune Analytics to store all nodes, edges, and vector embeddings for
the Cognee.ai memory conversation.
```
cognee.config.set_graph_db_config(
{
"graph_database_provider": "neptune_analytics", # Specify Neptune Analytics as provider
"graph_database_url": graph_endpoint_url, # Neptune Analytics endpoint with the format neptune-graph://<GRAPH_ID>
}
)
cognee.config.set_vector_db_config(
{
"vector_db_provider": "neptune_analytics", # Specify Neptune Analytics as provider
"vector_db_url": graph_endpoint_url, # Neptune Analytics endpoint with the format neptune-graph://<GRAPH_ID>
}
)
```
For example, see
[neptune_analytics_example.py](08a3a1d2a8/examples/database_examples/neptune_analytics_example.py)
Related: https://github.com/topoteretes/cognee-starter/pull/11
## DCO Affirmation
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## Description
Update rel db example with better info
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## Description
PR from user jspv, running it through our branch to test CI/CD
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## Description
Adds agentic procurement example
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## Description
Update migration example for upcoming blog on main branch
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## Description
Update relational db migration example so it's more understandable
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## Description
Removes graph metrics calculation from dynamic steps and ontology demos
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## Description
Delete by document.
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- Extracted run_tasks_base function into a new file run_tasks_base.py.
- Extracted four executors that execute core logic based on the task
type.
- Extracted a task handler/wrapper that safely executes the core logic
with logging and telemetry.
- Fixed the inconsistency with the batches of size 1.
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- Fixed get_no_summary_tasks and get_just_chunks_tasks to work with the
new tasks and pipelines
- Chore: fixed the pokemon example to work with the new tasks and
pipelines
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## Description
Remove outdated nodejs example, add specific versioning for mcp
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## Description
- Redirect all Cognee output to stderr for MCP ( as stdout is used to
communicate between MCP Client and server )
- Add test for CODE search type
- Resolve missing optional GUI dependency
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## Description
Add ability to migrate relational database to graph database
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## Description
Adds ontology demo 2
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## Description
Introducing scructlog.
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## Description
Temporarily remove embedding env variables for code graph action so the
action can run
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## Summary by CodeRabbit
- **Chores**
- Removed legacy secret configuration from the testing workflow to
streamline the CI process and enhance maintainability.
- **Improvements**
- Updated the argument name in the code graph pipeline for clarity.
- Enhanced the handling of results in the example script to support
asynchronous processing.
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## Description
This PR contains the ontology feature integrated into cognify
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## Summary by CodeRabbit
- **New Features**
- Enhanced ontology management with the introduction of the
`OntologyResolver` class for improved data handling and querying.
- Expanded ontology framework now provides enriched coverage of
technology and automotive domains, including new entities and
relationships.
- Updated entity models now include a validation flag to support
improved data integrity.
- Added support for specifying an ontology file path in relevant
functions to enhance flexibility.
- **Refactor**
- Streamlined integration of ontology processing across data extraction
and workflow routines.
- **Chores**
- Updated project dependencies to include `owlready2` for advanced
ontology functionality.
- **Tests**
- Introduced a new test suite for the `OntologyResolver` class to
validate its functionality under various conditions.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
<!-- .github/pull_request_template.md -->
## Description
This demo uses pydantic models and dlt to pull data from the Pokémon API
and structure it into a relational format. By feeding this structured
data into cognee, it makes searching across multiple tables easier and
more intuitive, thanks to the relational model.
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<!-- This is an auto-generated comment: release notes by coderabbit.ai
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## Summary by CodeRabbit
- **New Features**
- Introduced a comprehensive Pokémon data processing pipeline, available
as both a Python script and an interactive Jupyter Notebook.
- Enabled asynchronous operations for efficient data collection and
querying, including an integrated search functionality.
- Improved error handling and data validation during the data fetching
and processing stages for a smoother user experience.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
Co-authored-by: Vasilije <8619304+Vasilije1990@users.noreply.github.com>
