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## Description
<!-- Provide a clear description of the changes in this PR -->
- 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
## 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.
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## 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.
## 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
<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
## 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>
