- no dependency on any particular encryption lib (there is no py stdlib encryption lib)
- works with any modern checkpointer, ie. those which use dumps_typed and loads_typed methods to serialize data
- backwards compatible with unencrypted data in same storage (will just be read unencrypted)
- providing easy constructor to use AES encryption through pycriptodome library, one single line of code to add it in
- other encryption libraries or algorithms (even assymetric ones) can be used by implementing the two-method CipherProtocol interface
- cipher name (eg. aes) is stored with encrypted payload for forwards compatibility
- remove usage of require_at_least_one_of, we shouldn't be enforcing presence of keys in inputs/updates, an empty dict is a valid input/update
- ensure that values that were explcitly set/assigned in pydantic model are saved even if equal to default value
While working on langchain-ai/langgraphjs#984 I ported the test I was
debugging over to python so I could compare behavior. Figured I might as
well add it to this codebase, as I don't think we had this particular
case covered previously.
- When a pydantic input schema isued but dict input is passed in
validate it once after running hidden START node. If the input is an
instance of the input model we skip validation altogether
- When entering each node we need to create a standalone instance of the
state class, but we can now skip validation, as it's now run once
elsewhere
- When a pydantic input schema isued but dict input is passed in validate it once after running hidden START node. If the input is an instance of the input model we skip validation altogether
- When entering each node we need to create a standalone instance of the state class, but we can now skip validation, as it's now run once elsewhere
Currently the version badge showing langgraph version as PyPi shield
image is linking to the shield image. It would be more intuitive to link
it to PyPi.
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Co-authored-by: vbarda <vadym@langchain.dev>
Nuno Campos