feat(api): chore: pydantic & fastapi upgrade

Upgrade pydantic and fastapi to latest.

- pydantic~=2.4.2
- fastapi~=103.2
- fastapi-events~=0.9.1

**Big Changes**

There are a number of logic changes needed to support pydantic v2. Most changes are very simple, like using the new methods to serialized and deserialize models, but there are a few more complex changes.

**Invocations**

The biggest change relates to invocation creation, instantiation and validation.

Because pydantic v2 moves all validation logic into the rust pydantic-core, we may no longer directly stick our fingers into the validation pie.

Previously, we (ab)used models and fields to allow invocation fields to be optional at instantiation, but required when `invoke()` is called. We directly manipulated the fields and invocation models when calling `invoke()`.

With pydantic v2, this is much more involved. Changes to the python wrapper do not propagate down to the rust validation logic - you have to rebuild the model. This causes problem with concurrent access to the invocation classes and is not a free operation.

This logic has been totally refactored and we do not need to change the model any more. The details are in `baseinvocation.py`, in the `InputField` function and `BaseInvocation.invoke_internal()` method.

In the end, this implementation is cleaner.

**Invocation Fields**

In pydantic v2, you can no longer directly add or remove fields from a model.

Previously, we did this to add the `type` field to invocations.

**Invocation Decorators**

With pydantic v2, we instead use the imperative `create_model()` API to create a new model with the additional field. This is done in `baseinvocation.py` in the `invocation()` wrapper.

A similar technique is used for `invocation_output()`.

**Minor Changes**

There are a number of minor changes around the pydantic v2 models API.

**Protected `model_` Namespace**

All models' pydantic-provided methods and attributes are prefixed with `model_` and this is considered a protected namespace. This causes some conflict, because "model" means something to us, and we have a ton of pydantic models with attributes starting with "model_".

Forunately, there are no direct conflicts. However, in any pydantic model where we define an attribute or method that starts with "model_", we must tell set the protected namespaces to an empty tuple.

```py
class IPAdapterModelField(BaseModel):
    model_name: str = Field(description="Name of the IP-Adapter model")
    base_model: BaseModelType = Field(description="Base model")

    model_config = ConfigDict(protected_namespaces=())
```

**Model Serialization**

Pydantic models no longer have `Model.dict()` or `Model.json()`.

Instead, we use `Model.model_dump()` or `Model.model_dump_json()`.

**Model Deserialization**

Pydantic models no longer have `Model.parse_obj()` or `Model.parse_raw()`, and there are no `parse_raw_as()` or `parse_obj_as()` functions.

Instead, you need to create a `TypeAdapter` object to parse python objects or JSON into a model.

```py
adapter_graph = TypeAdapter(Graph)
deserialized_graph_from_json = adapter_graph.validate_json(graph_json)
deserialized_graph_from_dict = adapter_graph.validate_python(graph_dict)
```

**Field Customisation**

Pydantic `Field`s no longer accept arbitrary args.

Now, you must put all additional arbitrary args in a `json_schema_extra` arg on the field.

**Schema Customisation**

FastAPI and pydantic schema generation now follows the OpenAPI version 3.1 spec.

This necessitates two changes:
- Our schema customization logic has been revised
- Schema parsing to build node templates has been revised

The specific aren't important, but this does present additional surface area for bugs.

**Performance Improvements**

Pydantic v2 is a full rewrite with a rust backend. This offers a substantial performance improvement (pydantic claims 5x to 50x depending on the task). We'll notice this the most during serialization and deserialization of sessions/graphs, which happens very very often - a couple times per node.

I haven't done any benchmarks, but anecdotally, graph execution is much faster. Also, very larges graphs - like with massive iterators - are much, much faster.

invokeai/app/services/shared/graph.py

@@ -5,7 +5,7 @@ import itertools
 from typing import Annotated, Any, Optional, Union, get_args, get_origin, get_type_hints
 
 import networkx as nx
-from pydantic import BaseModel, root_validator, validator
+from pydantic import BaseModel, ConfigDict, field_validator, model_validator
 from pydantic.fields import Field
 
 # Importing * is bad karma but needed here for node detection
@@ -235,7 +235,8 @@ class CollectInvocationOutput(BaseInvocationOutput):
 class CollectInvocation(BaseInvocation):
     """Collects values into a collection"""
 
-    item: Any = InputField(
+    item: Optional[Any] = InputField(
+        default=None,
         description="The item to collect (all inputs must be of the same type)",
         ui_type=UIType.CollectionItem,
         title="Collection Item",
@@ -250,8 +251,8 @@ class CollectInvocation(BaseInvocation):
         return CollectInvocationOutput(collection=copy.copy(self.collection))
 
 
-InvocationsUnion = Union[BaseInvocation.get_invocations()]  # type: ignore
-InvocationOutputsUnion = Union[BaseInvocationOutput.get_all_subclasses_tuple()]  # type: ignore
+InvocationsUnion: Any = BaseInvocation.get_invocations_union()
+InvocationOutputsUnion: Any = BaseInvocationOutput.get_outputs_union()
 
 
 class Graph(BaseModel):
@@ -378,13 +379,13 @@ class Graph(BaseModel):
                 raise NodeNotFoundError(f"Edge destination node {edge.destination.node_id} does not exist in the graph")
 
             # output fields are not on the node object directly, they are on the output type
-            if edge.source.field not in source_node.get_output_type().__fields__:
+            if edge.source.field not in source_node.get_output_type().model_fields:
                 raise NodeFieldNotFoundError(
                     f"Edge source field {edge.source.field} does not exist in node {edge.source.node_id}"
                 )
 
             # input fields are on the node
-            if edge.destination.field not in destination_node.__fields__:
+            if edge.destination.field not in destination_node.model_fields:
                 raise NodeFieldNotFoundError(
                     f"Edge destination field {edge.destination.field} does not exist in node {edge.destination.node_id}"
                 )
@@ -395,24 +396,24 @@ class Graph(BaseModel):
             raise CyclicalGraphError("Graph contains cycles")
 
         # Validate all edge connections are valid
-        for e in self.edges:
+        for edge in self.edges:
             if not are_connections_compatible(
-                self.get_node(e.source.node_id),
-                e.source.field,
-                self.get_node(e.destination.node_id),
-                e.destination.field,
+                self.get_node(edge.source.node_id),
+                edge.source.field,
+                self.get_node(edge.destination.node_id),
+                edge.destination.field,
             ):
                 raise InvalidEdgeError(
-                    f"Invalid edge from {e.source.node_id}.{e.source.field} to {e.destination.node_id}.{e.destination.field}"
+                    f"Invalid edge from {edge.source.node_id}.{edge.source.field} to {edge.destination.node_id}.{edge.destination.field}"
                 )
 
         # Validate all iterators & collectors
         # TODO: may need to validate all iterators & collectors in subgraphs so edge connections in parent graphs will be available
-        for n in self.nodes.values():
-            if isinstance(n, IterateInvocation) and not self._is_iterator_connection_valid(n.id):
-                raise InvalidEdgeError(f"Invalid iterator node {n.id}")
-            if isinstance(n, CollectInvocation) and not self._is_collector_connection_valid(n.id):
-                raise InvalidEdgeError(f"Invalid collector node {n.id}")
+        for node in self.nodes.values():
+            if isinstance(node, IterateInvocation) and not self._is_iterator_connection_valid(node.id):
+                raise InvalidEdgeError(f"Invalid iterator node {node.id}")
+            if isinstance(node, CollectInvocation) and not self._is_collector_connection_valid(node.id):
+                raise InvalidEdgeError(f"Invalid collector node {node.id}")
 
         return None
 
@@ -594,7 +595,7 @@ class Graph(BaseModel):
 
     def _get_input_edges_and_graphs(
         self, node_path: str, prefix: Optional[str] = None
-    ) -> list[tuple["Graph", str, Edge]]:
+    ) -> list[tuple["Graph", Union[str, None], Edge]]:
         """Gets all input edges for a node along with the graph they are in and the graph's path"""
         edges = list()
 
@@ -636,7 +637,7 @@ class Graph(BaseModel):
 
     def _get_output_edges_and_graphs(
         self, node_path: str, prefix: Optional[str] = None
-    ) -> list[tuple["Graph", str, Edge]]:
+    ) -> list[tuple["Graph", Union[str, None], Edge]]:
         """Gets all output edges for a node along with the graph they are in and the graph's path"""
         edges = list()
 
@@ -817,15 +818,15 @@ class GraphExecutionState(BaseModel):
         default_factory=dict,
     )
 
-    @validator("graph")
+    @field_validator("graph")
     def graph_is_valid(cls, v: Graph):
         """Validates that the graph is valid"""
         v.validate_self()
         return v
 
-    class Config:
-        schema_extra = {
-            "required": [
+    model_config = ConfigDict(
+        json_schema_extra=dict(
+            required=[
                 "id",
                 "graph",
                 "execution_graph",
@@ -836,7 +837,8 @@ class GraphExecutionState(BaseModel):
                 "prepared_source_mapping",
                 "source_prepared_mapping",
             ]
-        }
+        )
+    )
 
     def next(self) -> Optional[BaseInvocation]:
         """Gets the next node ready to execute."""
@@ -910,7 +912,7 @@ class GraphExecutionState(BaseModel):
             input_collection = getattr(input_collection_prepared_node_output, input_collection_edge.source.field)
             self_iteration_count = len(input_collection)
 
-        new_nodes = list()
+        new_nodes: list[str] = list()
         if self_iteration_count == 0:
             # TODO: should this raise a warning? It might just happen if an empty collection is input, and should be valid.
             return new_nodes
@@ -920,7 +922,7 @@ class GraphExecutionState(BaseModel):
 
         # Create new edges for this iteration
         # For collect nodes, this may contain multiple inputs to the same field
-        new_edges = list()
+        new_edges: list[Edge] = list()
         for edge in input_edges:
             for input_node_id in (n[1] for n in iteration_node_map if n[0] == edge.source.node_id):
                 new_edge = Edge(
@@ -1179,18 +1181,18 @@ class LibraryGraph(BaseModel):
         description="The outputs exposed by this graph", default_factory=list
     )
 
-    @validator("exposed_inputs", "exposed_outputs")
-    def validate_exposed_aliases(cls, v):
+    @field_validator("exposed_inputs", "exposed_outputs")
+    def validate_exposed_aliases(cls, v: list[Union[ExposedNodeInput, ExposedNodeOutput]]):
         if len(v) != len(set(i.alias for i in v)):
             raise ValueError("Duplicate exposed alias")
         return v
 
-    @root_validator
+    @model_validator(mode="after")
     def validate_exposed_nodes(cls, values):
-        graph = values["graph"]
+        graph = values.graph
 
         # Validate exposed inputs
-        for exposed_input in values["exposed_inputs"]:
+        for exposed_input in values.exposed_inputs:
             if not graph.has_node(exposed_input.node_path):
                 raise ValueError(f"Exposed input node {exposed_input.node_path} does not exist")
             node = graph.get_node(exposed_input.node_path)
@@ -1200,7 +1202,7 @@ class LibraryGraph(BaseModel):
                 )
 
         # Validate exposed outputs
-        for exposed_output in values["exposed_outputs"]:
+        for exposed_output in values.exposed_outputs:
             if not graph.has_node(exposed_output.node_path):
                 raise ValueError(f"Exposed output node {exposed_output.node_path} does not exist")
             node = graph.get_node(exposed_output.node_path)
@@ -1212,4 +1214,6 @@ class LibraryGraph(BaseModel):
         return values
 
 
-GraphInvocation.update_forward_refs()
+GraphInvocation.model_rebuild(force=True)
+Graph.model_rebuild(force=True)
+GraphExecutionState.model_rebuild(force=True)