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Until now, limit=0 in vector search meant that there is no limit and we
should return everything. This caused confusion and errors, so now it is
reworked so that limit=None means no limit on the search. If someone
puts limit=0, there will be no results returned, as it makes more sense
and is less error prone.
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Basically, when the LLM Model is not specified, we put
`openai/gpt-4o-mini` as the model name. In litellm's `model_cost` map,
there is no such entry. There is however `gpt-4o-mini`, so when that is
specified for example, this log doesn't appear.
My solution was to just move this from info log to debug log, if it is
not a critical error. We could also change the default name, if it
doesn't break anything else.
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Updated installation instructions and usage examples in README.
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## Description
Temporary fix for MCP on main
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## Changes Made
Update Cognee version for MCP
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Added a CI test to make sure fastembed works as intended.
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## Description
Ontology notebook fix
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Ontology notebook fix
## Testing
manual
## Screenshots/Videos (if applicable)
None
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None
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Adds abstraction for OntologyResolvers and matching mechanism
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Adds ontology abstraction + matching resolver logic to support multiple
solutions
## Testing
Testing of changes is done using manual testing and ci/cd tests
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None
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None
## Additional Notes
None
## DCO Affirmation
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