- sequential(2000) goes from 8.4s to 4.1s
- replace UUID(str).bytes with faster binascii.unhexlify, and do it only
once per step
- find only the first active trigger, instead of the full list
- use a dedicated function for checking active trigger
## Description
This PR enhances the state-model documentation by adding comprehensive
examples for advanced Pydantic usage in LangGraph. It addresses issue
#2745 regarding the need for better documentation of Pydantic schema
behavior.
### Changes
- Added new section on Advanced Pydantic Model Usage
- Added examples for serialization behavior with nested models
- Added section on runtime type coercion with examples
- Added documentation for proper message type handling (BaseMessage vs
AnyMessage)
- Updated Pydantic error URLs to latest version
### Related Issues
Closes#2745
### Testing
- All notebook cells have been executed and outputs verified
- Examples demonstrate proper usage patterns
- Error cases are properly documented
### Documentation
The changes are documentation-focused and include:
- New examples for complex Pydantic models
- Runtime coercion behavior examples
- Message type handling best practices
### Reviewers
@eyurtsev
- sequential(2000) goes from 8.4s to 4.7s
- replace UUID(str).bytes with simpler str.encode()
- find only the first active trigger, instead of the full list
- use a dedicated function for checking active trigger
- Was O(n^2) due to individual channels created for every conditional
edge, including the default cond edge created for Command
- Now using a single channel per node for all conditional edge / command
triggers, reducing to linear complexity
- Improves run time on sequential(200) from 1.8s to 0.14s
- Previously the global resume value was passed to subgraphs without
being consumed
- This would result in two parallel subgraph calls being able to use the
same resume value
- Note this behavior can't be implemented over the wire, that will be
fixed in future PR
Closes#3398
- Was O(n^2) due to individual channels created for every conditional edge, including the default cond edge created for Command
- Now using a single channel per node for all conditional edge / command triggers, reducing to linear complexity
- Improves run time on sequential(200) from 1.8s to 0.14s
- Previously the global resume value was passed to subgraphs without being consumed
- This would result in two parallel subgraph calls being able to use the same resume value
- Note this behavior can't be implemented over the wire, that will be fixed in future PR
- Need to use a single operation to check if present and remove item
from list
- This doesn't fix the separate issue that parallel tasks claiming a
single interrupt value have somewhat undefined behavior (in the sense
that they will race to be the first to take it). That will be fixed in a
future PR
Closes#3875
- Need to use a single operation to check if present and remove item from list
- This doesn't fix the separate issue that parallel tasks claiming a single interrupt value have somewhat undefined behavior (in the sense that they will race to be the first to take it). That will be fixed in a future PR
