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Many of us have encountered the "dependency hell" that comes with Python projects, especially when integrating with various services or framework. Graphrag is very strict in term of dependency version even for stable projects like pandas = "^2.2.3", matplotlib = "^3.9.3", pyyaml = "^6.0.2", httpx = "^0.28.1", ...
While we try to keep our dependencies up-to-date, we depends on other project which can not always be as reactive bumping up version numbers. In our case, the very strict graphrag restrictions are conflicting with multiple other libraries like Prefect, Supabase or GCP.
We would like to open a discussion regarding loosening up the package restrictions which we feel make integrating graphrag into real project difficult.
The first question would be: What is the rational behind only accepting the very latest release of projects when there has no been no minor/major bump or breaking changes?
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Many of us have encountered the "dependency hell" that comes with Python projects, especially when integrating with various services or framework. Graphrag is very strict in term of dependency version even for stable projects like
pandas = "^2.2.3"
,matplotlib = "^3.9.3"
,pyyaml = "^6.0.2"
,httpx = "^0.28.1"
, ...While we try to keep our dependencies up-to-date, we depends on other project which can not always be as reactive bumping up version numbers. In our case, the very strict graphrag restrictions are conflicting with multiple other libraries like Prefect, Supabase or GCP.
We would like to open a discussion regarding loosening up the package restrictions which we feel make integrating graphrag into real project difficult.
The first question would be: What is the rational behind only accepting the very latest release of projects when there has no been no minor/major bump or breaking changes?
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