Repository: kserve/kserve

Issue:
Support pydantic 2
/kind feature

**Describe the solution you'd like**
[A clear and concise description of what you want to happen.]
The kserve package should support Pydantic 2 and newer FastAPI

**Anything else you would like to add:**
[Miscellaneous information that will assist in solving the issue.]


**Links to the design documents:**
[Optional, start with the short-form [RFC template](https://docs.google.com/document/d/1UcBeLfZ_JMGpVrPJmYtEIVH_9Y4U3AEKQdq_IKuOMrU) to outline your ideas and get early feedback.]
[Required, use the longer-form [design doc template](https://docs.google.com/document/d/1Mtoui_PP2a9N59NjYHnsvrdJ8t2iKFwIJAx1zRO_I1c) to specify and discuss your design in more detail]



Discussion:
This is being worked on in https://github.com/kserve/kserve/pull/3273
Thanks @terrytangyuan - I saw that PR. I have another PR that supersedes that one as there were a number of problems with it. See the linked PR #3374 
Got it. Thanks


Resolving patch:
diff --git a/python/kserve/kserve/protocol/rest/v2_datamodels.py b/python/kserve/kserve/protocol/rest/v2_datamodels.py
--- a/python/kserve/kserve/protocol/rest/v2_datamodels.py
+++ b/python/kserve/kserve/protocol/rest/v2_datamodels.py
@@ -14,8 +14,17 @@
 from typing import Optional, List, Union, Dict
 
 import orjson
+import pydantic
+
 from pydantic import BaseModel, StrictBool, StrictInt, StrictFloat
 
+
+# this is needed to add support for both pydantic 1.x and 2.x
+is_pydantic_2 = pydantic.__version__.startswith("2.")
+
+if is_pydantic_2:
+    from pydantic import ConfigDict
+
 # TODO: in the future, this file can be auto generated
 # https://pydantic-docs.helpmanual.io/datamodel_code_generator/
 
@@ -26,38 +35,47 @@
 Parameters = Dict[str, InferParameter]
 
 
+server_live_response_schema_extra = {"example": {"live": True}}
+
+
 class ServerLiveResponse(BaseModel):
     live: bool
 
-    class Config:
-        schema_extra = {
-            "example": {
-                "live": True
-            }
-        }
+    if is_pydantic_2:
+        model_config = ConfigDict(json_schema_extra=server_live_response_schema_extra)
+
+    else:
+
+        class Config:
+            schema_extra = server_live_response_schema_extra
+
+
+server_ready_response_schema_extra = {"example": {"ready": True}}
 
 
 class ServerReadyResponse(BaseModel):
     ready: bool
 
-    class Config:
-        schema_extra = {
-            "example": {
-                "ready": True
-            }
-        }
+    if is_pydantic_2:
+        model_config = ConfigDict(json_schema_extra=server_ready_response_schema_extra)
+
+    else:
+
+        class Config:
+            schema_extra = server_ready_response_schema_extra
 
 
 class ServerMetadataResponse(BaseModel):
     """ServerMetadataResponse
 
-        $server_metadata_response =
-        {
-          "name" : $string,
-          "version" : $string,
-          "extensions" : [ $string, ... ]
-        }
+    $server_metadata_response =
+    {
+      "name" : $string,
+      "version" : $string,
+      "extensions" : [ $string, ... ]
+    }
     """
+
     name: str
     version: str
     extensions: List[str]
@@ -66,13 +84,14 @@ class ServerMetadataResponse(BaseModel):
 class MetadataTensor(BaseModel):
     """MetadataTensor
 
-        $metadata_tensor =
-        {
-          "name" : $string,
-          "datatype" : $string,
-          "shape" : [ $number, ... ]
-        }
+    $metadata_tensor =
+    {
+      "name" : $string,
+      "datatype" : $string,
+      "shape" : [ $number, ... ]
+    }
     """
+
     name: str
     datatype: str
     shape: List[int]
@@ -81,28 +100,30 @@ class MetadataTensor(BaseModel):
 class ListModelsResponse(BaseModel):
     """ListModelsResponse
 
-        $models_list_response =
-        {
-          "models" : [ $string, ... ]
-        }
+    $models_list_response =
+    {
+      "models" : [ $string, ... ]
+    }
     """
+
     models: List[str]
 
 
 class ModelMetadataResponse(BaseModel):
     """ModelMetadataResponse
 
-        $metadata_model_response =
-        {
-          "name" : $string,
-          "versions" : [ $string, ... ] #optional,
-          "platform" : $string,
-          "inputs" : [ $metadata_tensor, ... ],
-          "outputs" : [ $metadata_tensor, ... ]
-        }
+    $metadata_model_response =
+    {
+      "name" : $string,
+      "versions" : [ $string, ... ] #optional,
+      "platform" : $string,
+      "inputs" : [ $metadata_tensor, ... ],
+      "outputs" : [ $metadata_tensor, ... ]
+    }
     """
+
     name: str
-    versions: Optional[List[str]]
+    versions: Optional[List[str]] = None
     platform: str
     inputs: List[MetadataTensor]
     outputs: List[MetadataTensor]
@@ -111,12 +132,13 @@ class ModelMetadataResponse(BaseModel):
 class ModelReadyResponse(BaseModel):
     """ModelReadyResponse
 
-        $ready_model_response =
-        {
-          "name": $string,
-          "ready": $bool
-        }
+    $ready_model_response =
+    {
+      "name": $string,
+      "ready": $bool
+    }
     """
+
     name: str
     ready: bool
 
@@ -124,290 +146,362 @@ class ModelReadyResponse(BaseModel):
 class RequestInput(BaseModel):
     """RequestInput Model
 
-        $request_input =
-        {
-          "name" : $string,
-          "shape" : [ $number, ... ],
-          "datatype"  : $string,
-          "parameters" : $parameters #optional,
-          "data" : $tensor_data
-        }
+    $request_input =
+    {
+      "name" : $string,
+      "shape" : [ $number, ... ],
+      "datatype"  : $string,
+      "parameters" : $parameters #optional,
+      "data" : $tensor_data
+    }
     """
+
     name: str
     shape: List[int]
     datatype: str
-    parameters: Optional[Parameters]
+    parameters: Optional[Parameters] = None
     data: List
 
 
 class RequestOutput(BaseModel):
     """RequestOutput Model
 
-        $request_output =
-        {
-          "name" : $string,
-          "parameters" : $parameters #optional,
-        }
+    $request_output =
+    {
+      "name" : $string,
+      "parameters" : $parameters #optional,
+    }
     """
+
     name: str
-    parameters: Optional[Parameters]
+    parameters: Optional[Parameters] = None
 
 
 class ResponseOutput(BaseModel):
     """ResponseOutput Model
 
-        $response_output =
-        {
-          "name" : $string,
-          "shape" : [ $number, ... ],
-          "datatype"  : $string,
-          "parameters" : $parameters #optional,
-          "data" : $tensor_data
-        }
+    $response_output =
+    {
+      "name" : $string,
+      "shape" : [ $number, ... ],
+      "datatype"  : $string,
+      "parameters" : $parameters #optional,
+      "data" : $tensor_data
+    }
     """
+
     name: str
     shape: List[int]
     datatype: str
-    parameters: Optional[Parameters]
+    parameters: Optional[Parameters] = None
     data: List
 
 
+inference_request_schema_extra = {
+    "example": {
+        "id": "42",
+        "inputs": [
+            {
+                "name": "input0",
+                "shape": [2, 2],
+                "datatype": "UINT32",
+                "data": [1, 2, 3, 4],
+            },
+            {"name": "input1", "shape": [3], "datatype": "BOOL", "data": ["true"]},
+        ],
+        "outputs": [{"name": "output0"}],
+    }
+}
+
+
 class InferenceRequest(BaseModel):
     """InferenceRequest Model
 
-        $inference_request =
-        {
-          "id" : $string #optional,
-          "parameters" : $parameters #optional,
-          "inputs" : [ $request_input, ... ],
-          "outputs" : [ $request_output, ... ] #optional
-        }
+    $inference_request =
+    {
+      "id" : $string #optional,
+      "parameters" : $parameters #optional,
+      "inputs" : [ $request_input, ... ],
+      "outputs" : [ $request_output, ... ] #optional
+    }
     """
-    id: Optional[str]
+
+    id: Optional[str] = None
     parameters: Optional[Parameters] = None
     inputs: List[RequestInput]
     outputs: Optional[List[RequestOutput]] = None
 
-    class Config:
-        json_loads = orjson.loads
-        schema_extra = {
-            "example": {
-                "id": "42",
-                "inputs": [
-                    {
-                        "name": "input0",
-                        "shape": [2, 2],
-                        "datatype": "UINT32",
-                        "data": [1, 2, 3, 4]
-                    },
-                    {
-                        "name": "input1",
-                        "shape": [3],
-                        "datatype": "BOOL",
-                        "data": ["true"]
-                    }
-                ],
-                "outputs": [
-                    {
-                        "name": "output0"
-                    }
-                ]
+    if is_pydantic_2:
+        model_config = ConfigDict(
+            json_loads=orjson.loads, json_schema_extra=inference_request_schema_extra
+        )
+
+    else:
+
+        class Config:
+            json_loads = orjson.loads
+            schema_extra = inference_request_schema_extra
+
+
+inference_response_schema_extra = {
+    "example": {
+        "id": "42",
+        "outputs": [
+            {
+                "name": "output0",
+                "shape": [3, 2],
+                "datatype": "FP32",
+                "data": [1.0, 1.1, 2.0, 2.1, 3.0, 3.1],
             }
-        }
+        ],
+    }
+}
 
 
 class InferenceResponse(BaseModel):
     """InferenceResponse
 
-        $inference_response =
-        {
-          "model_name" : $string,
-          "model_version" : $string #optional,
-          "id" : $string,
-          "parameters" : $parameters #optional,
-          "outputs" : [ $response_output, ... ]
-        }
+    $inference_response =
+    {
+      "model_name" : $string,
+      "model_version" : $string #optional,
+      "id" : $string,
+      "parameters" : $parameters #optional,
+      "outputs" : [ $response_output, ... ]
+    }
     """
+
     model_name: str
-    model_version: Optional[str]
+    model_version: Optional[str] = None
     id: str
-    parameters: Optional[Parameters]
+    parameters: Optional[Parameters] = None
     outputs: List[ResponseOutput]
 
-    class Config:
-        schema_extra = {
-            "example": {
-                "id": "42",
-                "outputs": [
-                    {
-                        "name": "output0",
-                        "shape": [3, 2],
-                        "datatype": "FP32",
-                        "data": [1.0, 1.1, 2.0, 2.1, 3.0, 3.1]
-                    }
-                ]
-            }
-        }
+    if is_pydantic_2:
+        model_config = ConfigDict(
+            protected_namespaces=(), json_schema_extra=inference_response_schema_extra
+        )
+    else:
+
+        class Config:
+            schema_extra = inference_response_schema_extra
+
+
+generate_request_schema_extra = {
+    "example": {
+        "text_input": "Tell me about the AI",
+        "parameters": {
+            "temperature": 0.8,
+            "top_p": 0.9,
+        },
+    }
+}
 
 
 class GenerateRequest(BaseModel):
     """GenerateRequest Model
 
-        $generate_request =
-        {
-          "text_input" : $string,
-          "parameters" : $string #optional,
-        }
+    $generate_request =
+    {
+      "text_input" : $string,
+      "parameters" : $string #optional,
+    }
     """
+
     text_input: str
     parameters: Optional[Parameters] = None
 
-    class Config:
-        json_loads = orjson.loads
-        schema_extra = {
-            "example": {
-                "text_input": "Tell me about the AI",
-                "parameters":
-                    {
-                        "temperature": 0.8,
-                        "top_p": 0.9,
-                    }
-            }
-        }
+    if is_pydantic_2:
+        model_config = ConfigDict(
+            json_loads=orjson.loads, json_schema_extra=generate_request_schema_extra
+        )
+    else:
+
+        class Config:
+            json_loads = orjson.loads
+            schema_extra = generate_request_schema_extra
+
+
+token_schema_extra = {
+    "example": {
+        "id": 267,
+        "logprob": -2.0723474,
+        "special": False,
+        "text": " a",
+    }
+}
 
 
 class Token(BaseModel):
-    """Token Data Model
+    """Token Data Model"""
 
-    """
     id: int
     logprob: float
     special: bool
     text: str
 
-    class Config:
-        json_loads = orjson.loads
-        schema_extra = {
-            "example": {
+    if is_pydantic_2:
+        model_config = ConfigDict(
+            json_loads=orjson.loads, json_schema_extra=token_schema_extra
+        )
+    else:
+
+        class Config:
+            json_loads = orjson.loads
+            schema_extra = token_schema_extra
+
+
+details_schema_extra = {
+    "example": {
+        "finish_reason": "stop",
+        "logprobs": [
+            {
                 "id": 267,
                 "logprob": -2.0723474,
                 "special": False,
                 "text": " a",
             }
-        }
+        ],
+    }
+}
 
 
 class Details(BaseModel):
-    """Generate response details
+    """Generate response details"""
 
-    """
     finish_reason: str
     logprobs: List[Token]
 
-    class Config:
-        json_loads = orjson.loads
-        schema_extra = {
-            "example": {
-                "finish_reason": "stop",
-                "logprobs": [{
-                  "id": 267,
-                  "logprob": -2.0723474,
-                  "special": False,
-                  "text": " a",
-                }]
-            }
-        }
+    if is_pydantic_2:
+        model_config = ConfigDict(
+            json_loads=orjson.loads,
+            json_schema_extra=details_schema_extra,
+        )
+    else:
+        class Config:
+            json_loads = orjson.loads
+            schema_extra = details_schema_extra
+
+
+streaming_details_schema_extra = {
+    "example": {
+        "finish_reason": "stop",
+        "logprobs": {
+            "id": 267,
+            "logprob": -2.0723474,
+            "special": False,
+            "text": " a",
+        },
+    }
+}
 
 
 class StreamingDetails(BaseModel):
-    """Generate response details
+    """Generate response details"""
 
-    """
     finish_reason: str
     logprobs: Token
 
-    class Config:
-        json_loads = orjson.loads
-        schema_extra = {
-            "example": {
-                "finish_reason": "stop",
-                "logprobs": {
-                  "id": 267,
-                  "logprob": -2.0723474,
-                  "special": False,
-                  "text": " a",
+    if is_pydantic_2:
+        model_config = ConfigDict(
+            json_loads=orjson.loads,
+            json_schema_extra=streaming_details_schema_extra,
+        )
+    else:
+
+        class Config:
+            json_loads = orjson.loads
+            schema_extra = streaming_details_schema_extra
+
+
+generate_response_schema_extra = {
+    "example": {
+        "text_output": "Tell me about the AI",
+        "model_name": "bloom7b1",
+        "details": {
+            "finish_reason": "stop",
+            "logprobs": [
+                {
+                    "id": "267",
+                    "logprob": -2.0723474,
+                    "special": False,
+                    "text": " a",
                 }
-            }
-        }
+            ],
+        },
+    }
+}
 
 
 class GenerateResponse(BaseModel):
     """GenerateResponse Model
 
-        $generate_response =
-        {
-          "text_output" : $string,
-          "model_name" : $string,
-          "model_version" : $string #optional,
-          "details": $Details #optional
-        }
+    $generate_response =
+    {
+      "text_output" : $string,
+      "model_name" : $string,
+      "model_version" : $string #optional,
+      "details": $Details #optional
+    }
     """
+
     text_output: str
     model_name: str
-    model_version: Optional[str]
-    details: Optional[Details]
-
-    class Config:
-        json_loads = orjson.loads
-        schema_extra = {
-            "example": {
-                "text_output": "Tell me about the AI",
-                "model_name": "bloom7b1",
-                "details": {
-                    "finish_reason": "stop",
-                    "logprobs": [
-                        {
-                            "id": "267",
-                            "logprob": -2.0723474,
-                            "special": False,
-                            "text": " a",
-                        }
-                    ]
-                }
-            }
-        }
+    model_version: Optional[str] = None
+    details: Optional[Details] = None
+
+    if is_pydantic_2:
+        model_config = ConfigDict(
+            json_loads=orjson.loads, json_schema_extra=generate_response_schema_extra
+        )
+    else:
+
+        class Config:
+            json_loads = orjson.loads
+            schema_extra = generate_response_schema_extra
+
+
+generate_streaming_response_schema_extra = {
+    "example": {
+        "text_output": "Tell me about the AI",
+        "model_name": "bloom7b1",
+        "details": {
+            "finish_reason": "stop",
+            "logprobs": {
+                "id": "267",
+                "logprob": -2.0723474,
+                "special": False,
+                "text": " a",
+            },
+        },
+    }
+}
 
 
 class GenerateStreamingResponse(BaseModel):
     """GenerateStreamingResponse Model
 
-        $generate_response =
-        {
-          "text_output" : $string,
-          "model_name" : $string,
-          "model_version" : $string #optional,
-          "details": $Details #optional
-        }
+    $generate_response =
+    {
+      "text_output" : $string,
+      "model_name" : $string,
+      "model_version" : $string #optional,
+      "details": $Details #optional
+    }
     """
+
     text_output: str
     model_name: str
-    model_version: Optional[str]
-    details: Optional[StreamingDetails]
-
-    class Config:
-        json_loads = orjson.loads
-        schema_extra = {
-            "example": {
-                "text_output": "Tell me about the AI",
-                "model_name": "bloom7b1",
-                "details": {
-                    "finish_reason": "stop",
-                    "logprobs": {
-                        "id": "267",
-                        "logprob": -2.0723474,
-                        "special": False,
-                        "text": " a",
-                    }
-                }
-            }
-        }
+    model_version: Optional[str] = None
+    details: Optional[StreamingDetails] = None
+
+    if is_pydantic_2:
+        model_config = ConfigDict(
+            json_loads=orjson.loads,
+            json_schema_extra=generate_streaming_response_schema_extra,
+        )
+
+    else:
+        class Config:
+            json_loads = orjson.loads
+            schema_extra = generate_streaming_response_schema_extra


Test patch:
diff --git a/python/kserve/test/test_server.py b/python/kserve/test/test_server.py
--- a/python/kserve/test/test_server.py
+++ b/python/kserve/test/test_server.py
@@ -35,6 +35,7 @@
 from kserve.protocol.rest.server import RESTServer
 
 from kserve.protocol.infer_type import InferRequest, InferInput, InferResponse, InferOutput
+from kserve.protocol.rest.v2_datamodels import is_pydantic_2
 from kserve.utils.utils import get_predict_input, get_predict_response
 
 test_avsc_schema = '''
@@ -430,7 +431,14 @@ def test_list_handler(self, http_server_client):
     def test_health_handler(self, http_server_client):
         resp = http_server_client.get('/v1/models/TestModel')
         assert resp.status_code == 200
-        assert resp.content == b'{"name":"TestModel","ready":"True"}'
+        # for some reason the RayServer responds with the stringified python bool
+        # when run on pydantic < 2 and the bool when run on pydantic >= 2
+        # eg {"name":"TestModel","ready":"True"} vs {"name":"TestModel","ready":true}
+        if is_pydantic_2:
+            expected_content = b'{"name":"TestModel","ready":true}'
+        else:
+            expected_content = b'{"name":"TestModel","ready":"True"}'
+        assert resp.content == expected_content
 
     def test_predict(self, http_server_client):
         resp = http_server_client.post('/v1/models/TestModel:predict',
diff --git a/python/test_resources/graph/error_404_isvc/poetry.lock b/python/test_resources/graph/error_404_isvc/poetry.lock
--- a/python/test_resources/graph/error_404_isvc/poetry.lock
+++ b/python/test_resources/graph/error_404_isvc/poetry.lock
@@ -135,6 +135,17 @@ files = [
 [package.dependencies]
 frozenlist = ">=1.1.0"
 
+[[package]]
+name = "annotated-types"
+version = "0.6.0"
+description = "Reusable constraint types to use with typing.Annotated"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "annotated_types-0.6.0-py3-none-any.whl", hash = "sha256:0641064de18ba7a25dee8f96403ebc39113d0cb953a01429249d5c7564666a43"},
+    {file = "annotated_types-0.6.0.tar.gz", hash = "sha256:563339e807e53ffd9c267e99fc6d9ea23eb8443c08f112651963e24e22f84a5d"},
+]
+
 [[package]]
 name = "ansicon"
 version = "1.89.0"
@@ -432,24 +443,22 @@ test = ["pytest (>=6)"]
 
 [[package]]
 name = "fastapi"
-version = "0.95.2"
+version = "0.108.0"
 description = "FastAPI framework, high performance, easy to learn, fast to code, ready for production"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "fastapi-0.95.2-py3-none-any.whl", hash = "sha256:d374dbc4ef2ad9b803899bd3360d34c534adc574546e25314ab72c0c4411749f"},
-    {file = "fastapi-0.95.2.tar.gz", hash = "sha256:4d9d3e8c71c73f11874bcf5e33626258d143252e329a01002f767306c64fb982"},
+    {file = "fastapi-0.108.0-py3-none-any.whl", hash = "sha256:8c7bc6d315da963ee4cdb605557827071a9a7f95aeb8fcdd3bde48cdc8764dd7"},
+    {file = "fastapi-0.108.0.tar.gz", hash = "sha256:5056e504ac6395bf68493d71fcfc5352fdbd5fda6f88c21f6420d80d81163296"},
 ]
 
 [package.dependencies]
-pydantic = ">=1.6.2,<1.7 || >1.7,<1.7.1 || >1.7.1,<1.7.2 || >1.7.2,<1.7.3 || >1.7.3,<1.8 || >1.8,<1.8.1 || >1.8.1,<2.0.0"
-starlette = ">=0.27.0,<0.28.0"
+pydantic = ">=1.7.4,<1.8 || >1.8,<1.8.1 || >1.8.1,<2.0.0 || >2.0.0,<2.0.1 || >2.0.1,<2.1.0 || >2.1.0,<3.0.0"
+starlette = ">=0.29.0,<0.33.0"
+typing-extensions = ">=4.8.0"
 
 [package.extras]
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+]
+
+[package.dependencies]
+typing-extensions = ">=4.6.0,<4.7.0 || >4.7.0"
 
 [[package]]
 name = "python-dateutil"
@@ -1910,13 +1978,13 @@ files = [
 
 [[package]]
 name = "starlette"
-version = "0.27.0"
+version = "0.32.0.post1"
 description = "The little ASGI library that shines."
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "starlette-0.27.0-py3-none-any.whl", hash = "sha256:918416370e846586541235ccd38a474c08b80443ed31c578a418e2209b3eef91"},
-    {file = "starlette-0.27.0.tar.gz", hash = "sha256:6a6b0d042acb8d469a01eba54e9cda6cbd24ac602c4cd016723117d6a7e73b75"},
+    {file = "starlette-0.32.0.post1-py3-none-any.whl", hash = "sha256:cd0cb10ddb49313f609cedfac62c8c12e56c7314b66d89bb077ba228bada1b09"},
+    {file = "starlette-0.32.0.post1.tar.gz", hash = "sha256:e54e2b7e2fb06dff9eac40133583f10dfa05913f5a85bf26f427c7a40a9a3d02"},
 ]
 
 [package.dependencies]
@@ -1992,13 +2060,13 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "uvicorn"
-version = "0.19.0"
+version = "0.21.1"
 description = "The lightning-fast ASGI server."
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "uvicorn-0.19.0-py3-none-any.whl", hash = "sha256:cc277f7e73435748e69e075a721841f7c4a95dba06d12a72fe9874acced16f6f"},
-    {file = "uvicorn-0.19.0.tar.gz", hash = "sha256:cf538f3018536edb1f4a826311137ab4944ed741d52aeb98846f52215de57f25"},
+    {file = "uvicorn-0.21.1-py3-none-any.whl", hash = "sha256:e47cac98a6da10cd41e6fd036d472c6f58ede6c5dbee3dbee3ef7a100ed97742"},
+    {file = "uvicorn-0.21.1.tar.gz", hash = "sha256:0fac9cb342ba099e0d582966005f3fdba5b0290579fed4a6266dc702ca7bb032"},
 ]
 
 [package.dependencies]
@@ -2010,10 +2078,10 @@ python-dotenv = {version = ">=0.13", optional = true, markers = "extra == \"stan
 pyyaml = {version = ">=5.1", optional = true, markers = "extra == \"standard\""}
 uvloop = {version = ">=0.14.0,<0.15.0 || >0.15.0,<0.15.1 || >0.15.1", optional = true, markers = "(sys_platform != \"win32\" and sys_platform != \"cygwin\") and platform_python_implementation != \"PyPy\" and extra == \"standard\""}
 watchfiles = {version = ">=0.13", optional = true, markers = "extra == \"standard\""}
-websockets = {version = ">=10.0", optional = true, markers = "extra == \"standard\""}
+websockets = {version = ">=10.4", optional = true, markers = "extra == \"standard\""}
 
 [package.extras]
-standard = ["colorama (>=0.4)", "httptools (>=0.5.0)", "python-dotenv (>=0.13)", "pyyaml (>=5.1)", "uvloop (>=0.14.0,!=0.15.0,!=0.15.1)", "watchfiles (>=0.13)", "websockets (>=10.0)"]
+standard = ["colorama (>=0.4)", "httptools (>=0.5.0)", "python-dotenv (>=0.13)", "pyyaml (>=5.1)", "uvloop (>=0.14.0,!=0.15.0,!=0.15.1)", "watchfiles (>=0.13)", "websockets (>=10.4)"]
 
 [[package]]
 name = "uvloop"
diff --git a/python/test_resources/graph/success_200_isvc/poetry.lock b/python/test_resources/graph/success_200_isvc/poetry.lock
--- a/python/test_resources/graph/success_200_isvc/poetry.lock
+++ b/python/test_resources/graph/success_200_isvc/poetry.lock
@@ -135,6 +135,17 @@ files = [
 [package.dependencies]
 frozenlist = ">=1.1.0"
 
+[[package]]
+name = "annotated-types"
+version = "0.6.0"
+description = "Reusable constraint types to use with typing.Annotated"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "annotated_types-0.6.0-py3-none-any.whl", hash = "sha256:0641064de18ba7a25dee8f96403ebc39113d0cb953a01429249d5c7564666a43"},
+    {file = "annotated_types-0.6.0.tar.gz", hash = "sha256:563339e807e53ffd9c267e99fc6d9ea23eb8443c08f112651963e24e22f84a5d"},
+]
+
 [[package]]
 name = "ansicon"
 version = "1.89.0"
@@ -432,24 +443,22 @@ test = ["pytest (>=6)"]
 
 [[package]]
 name = "fastapi"
-version = "0.95.2"
+version = "0.108.0"
 description = "FastAPI framework, high performance, easy to learn, fast to code, ready for production"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
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-    {file = "fastapi-0.95.2.tar.gz", hash = "sha256:4d9d3e8c71c73f11874bcf5e33626258d143252e329a01002f767306c64fb982"},
+    {file = "fastapi-0.108.0-py3-none-any.whl", hash = "sha256:8c7bc6d315da963ee4cdb605557827071a9a7f95aeb8fcdd3bde48cdc8764dd7"},
+    {file = "fastapi-0.108.0.tar.gz", hash = "sha256:5056e504ac6395bf68493d71fcfc5352fdbd5fda6f88c21f6420d80d81163296"},
 ]
 
 [package.dependencies]
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-starlette = ">=0.27.0,<0.28.0"
+pydantic = ">=1.7.4,<1.8 || >1.8,<1.8.1 || >1.8.1,<2.0.0 || >2.0.0,<2.0.1 || >2.0.1,<2.1.0 || >2.1.0,<3.0.0"
+starlette = ">=0.29.0,<0.33.0"
+typing-extensions = ">=4.8.0"
 
 [package.extras]
-all = ["email-validator (>=1.1.1)", "httpx (>=0.23.0)", "itsdangerous (>=1.1.0)", "jinja2 (>=2.11.2)", "orjson (>=3.2.1)", "python-multipart (>=0.0.5)", "pyyaml (>=5.3.1)", "ujson (>=4.0.1,!=4.0.2,!=4.1.0,!=4.2.0,!=4.3.0,!=5.0.0,!=5.1.0)", "uvicorn[standard] (>=0.12.0)"]
-dev = ["pre-commit (>=2.17.0,<3.0.0)", "ruff (==0.0.138)", "uvicorn[standard] (>=0.12.0,<0.21.0)"]
-doc = ["mdx-include (>=1.4.1,<2.0.0)", "mkdocs (>=1.1.2,<2.0.0)", "mkdocs-markdownextradata-plugin (>=0.1.7,<0.3.0)", "mkdocs-material (>=8.1.4,<9.0.0)", "pyyaml (>=5.3.1,<7.0.0)", "typer-cli (>=0.0.13,<0.0.14)", "typer[all] (>=0.6.1,<0.8.0)"]
-test = ["anyio[trio] (>=3.2.1,<4.0.0)", "black (==23.1.0)", "coverage[toml] (>=6.5.0,<8.0)", "databases[sqlite] (>=0.3.2,<0.7.0)", "email-validator (>=1.1.1,<2.0.0)", "flask (>=1.1.2,<3.0.0)", "httpx (>=0.23.0,<0.24.0)", "isort (>=5.0.6,<6.0.0)", "mypy (==0.982)", "orjson (>=3.2.1,<4.0.0)", "passlib[bcrypt] (>=1.7.2,<2.0.0)", "peewee (>=3.13.3,<4.0.0)", "pytest (>=7.1.3,<8.0.0)", "python-jose[cryptography] (>=3.3.0,<4.0.0)", "python-multipart (>=0.0.5,<0.0.7)", "pyyaml (>=5.3.1,<7.0.0)", "ruff (==0.0.138)", "sqlalchemy (>=1.3.18,<1.4.43)", "types-orjson (==3.6.2)", "types-ujson (==5.7.0.1)", "ujson (>=4.0.1,!=4.0.2,!=4.1.0,!=4.2.0,!=4.3.0,!=5.0.0,!=5.1.0,<6.0.0)"]
+all = ["email-validator (>=2.0.0)", "httpx (>=0.23.0)", "itsdangerous (>=1.1.0)", "jinja2 (>=2.11.2)", "orjson (>=3.2.1)", "pydantic-extra-types (>=2.0.0)", "pydantic-settings (>=2.0.0)", "python-multipart (>=0.0.5)", "pyyaml (>=5.3.1)", "ujson (>=4.0.1,!=4.0.2,!=4.1.0,!=4.2.0,!=4.3.0,!=5.0.0,!=5.1.0)", "uvicorn[standard] (>=0.12.0)"]
 
 [[package]]
 name = "filelock"
@@ -876,7 +885,7 @@ develop = true
 [package.dependencies]
 async-timeout = {version = "^4.0.3", markers = "python_version >= \"3.11.dev0\" and python_version < \"3.12.dev0\""}
 cloudevents = "^1.6.2"
-fastapi = "^0.95.0"
+fastapi = "^0.108.0"
 grpcio = "^1.49.1"
 httpx = "^0.26.0"
 kubernetes = ">=23.3.0"
@@ -886,12 +895,13 @@ pandas = ">=1.3.5"
 prometheus-client = "^0.13.1"
 protobuf = "^3.19.0"
 psutil = "^5.9.0"
+pydantic = ">1.0,<3"
 python-dateutil = "^2.8.0"
 ray = {version = "^2.9.2", extras = ["serve"]}
 six = "^1.16.0"
 tabulate = "^0.9.0"
 timing-asgi = "^0.3.0"
-uvicorn = {version = "^0.19.0", extras = ["standard"]}
+uvicorn = {version = "^0.21.1", extras = ["standard"]}
 
 [package.extras]
 logging = ["asgi-logger (>=0.1.0,<0.2.0)"]
@@ -1463,55 +1473,113 @@ pyasn1 = ">=0.4.6,<0.6.0"
 
 [[package]]
 name = "pydantic"
-version = "1.10.14"
-description = "Data validation and settings management using python type hints"
+version = "2.6.3"
+description = "Data validation using Python type hints"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
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 [[package]]
 name = "python-dateutil"
@@ -1910,13 +1978,13 @@ files = [
 
 [[package]]
 name = "starlette"
-version = "0.27.0"
+version = "0.32.0.post1"
 description = "The little ASGI library that shines."
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -1992,13 +2060,13 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "uvicorn"
-version = "0.19.0"
+version = "0.21.1"
 description = "The lightning-fast ASGI server."
 optional = false
 python-versions = ">=3.7"
 files = [
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 ]
 
 [package.dependencies]
@@ -2010,10 +2078,10 @@ python-dotenv = {version = ">=0.13", optional = true, markers = "extra == \"stan
 pyyaml = {version = ">=5.1", optional = true, markers = "extra == \"standard\""}
 uvloop = {version = ">=0.14.0,<0.15.0 || >0.15.0,<0.15.1 || >0.15.1", optional = true, markers = "(sys_platform != \"win32\" and sys_platform != \"cygwin\") and platform_python_implementation != \"PyPy\" and extra == \"standard\""}
 watchfiles = {version = ">=0.13", optional = true, markers = "extra == \"standard\""}
-websockets = {version = ">=10.0", optional = true, markers = "extra == \"standard\""}
+websockets = {version = ">=10.4", optional = true, markers = "extra == \"standard\""}
 
 [package.extras]
-standard = ["colorama (>=0.4)", "httptools (>=0.5.0)", "python-dotenv (>=0.13)", "pyyaml (>=5.1)", "uvloop (>=0.14.0,!=0.15.0,!=0.15.1)", "watchfiles (>=0.13)", "websockets (>=10.0)"]
+standard = ["colorama (>=0.4)", "httptools (>=0.5.0)", "python-dotenv (>=0.13)", "pyyaml (>=5.1)", "uvloop (>=0.14.0,!=0.15.0,!=0.15.1)", "watchfiles (>=0.13)", "websockets (>=10.4)"]
 
 [[package]]
 name = "uvloop"