diff --git a/.github/workflows/python-test.yml b/.github/workflows/python-test.yml index 982c2e2284..e2ed035406 100644 --- a/.github/workflows/python-test.yml +++ b/.github/workflows/python-test.yml @@ -90,6 +90,36 @@ jobs: source kserve/.venv/bin/activate pytest --cov=kserve ./kserve + # ----------------------------------------Kserve Pydantic V1 Unit Tests-------------------------------------------- + - name: Setup kserve pydantic v1 directory + run: | + mkdir -p python/kserve-pydantic-v1 + cp -r python/kserve/* python/kserve-pydantic-v1 + cd python/kserve-pydantic-v1 + # update the lock file without installing dependencies + poetry update "pydantic<2.0" --lock + - name: Load cached kserve pydantic v1 venv + id: cached-kserve-pydantic-v1-dependencies + uses: actions/cache@v3 + with: + path: python/kserve-pydantic-v1/.venv + key: kserve-pydantic-v1-venv-${{ steps.setup-python.outputs.python-version }}-${{ hashFiles('**/kserve-pydantic-v1/poetry.lock') }} + # install kserve pydantic v1 dependencies if cache does not exist + - name: Install kserve pydantic v1 dependencies + if: steps.cached-kserve-pydantic-v1-dependencies.outputs.cache-hit != 'true' + run: | + cd python/kserve-pydantic-v1 + make install_dependencies + - name: Install kserve pydantic v1 + run: | + cd python/kserve-pydantic-v1 + make dev_install + - name: Test kserve pydantic v1 + run: | + cd python + source kserve-pydantic-v1/.venv/bin/activate + pytest --cov=kserve ./kserve-pydantic-v1 + # ----------------------------------------Sklearn Server Unit Tests------------------------------------------------ # load cached sklearn venv if cache exists - name: Load cached sklearn venv diff --git a/python/aiffairness/poetry.lock b/python/aiffairness/poetry.lock index 263dd63177..7e4c70260e 100644 --- a/python/aiffairness/poetry.lock +++ b/python/aiffairness/poetry.lock @@ -19,87 +19,87 @@ scipy = "*" [[package]] name = "aiohttp" -version = "3.9.3" +version = "3.9.5" description = "Async http client/server 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+3940,13 @@ test = ["Cython (>=0.29.36,<0.30.0)", "aiohttp (==3.9.0b0)", "aiohttp (>=3.8.1)" [[package]] name = "virtualenv" -version = "20.25.1" +version = "20.25.3" description = "Virtual Python Environment builder" optional = false python-versions = ">=3.7" files = [ - {file = "virtualenv-20.25.1-py3-none-any.whl", hash = "sha256:961c026ac520bac5f69acb8ea063e8a4f071bcc9457b9c1f28f6b085c511583a"}, - {file = "virtualenv-20.25.1.tar.gz", hash = "sha256:e08e13ecdca7a0bd53798f356d5831434afa5b07b93f0abdf0797b7a06ffe197"}, + {file = "virtualenv-20.25.3-py3-none-any.whl", hash = "sha256:8aac4332f2ea6ef519c648d0bc48a5b1d324994753519919bddbb1aff25a104e"}, + {file = "virtualenv-20.25.3.tar.gz", hash = "sha256:7bb554bbdfeaacc3349fa614ea5bff6ac300fc7c335e9facf3a3bcfc703f45be"}, ] [package.dependencies] @@ -3776,7 +3955,7 @@ filelock = ">=3.12.2,<4" platformdirs = ">=3.9.1,<5" [package.extras] -docs = ["furo (>=2023.7.26)", "proselint (>=0.13)", "sphinx (>=7.1.2)", "sphinx-argparse (>=0.4)", "sphinxcontrib-towncrier (>=0.2.1a0)", "towncrier (>=23.6)"] +docs = ["furo (>=2023.7.26)", "proselint (>=0.13)", "sphinx (>=7.1.2,!=7.3)", "sphinx-argparse (>=0.4)", "sphinxcontrib-towncrier (>=0.2.1a0)", "towncrier (>=23.6)"] test = ["covdefaults (>=2.3)", "coverage (>=7.2.7)", "coverage-enable-subprocess (>=1)", "flaky (>=3.7)", "packaging (>=23.1)", "pytest (>=7.4)", "pytest-env (>=0.8.2)", "pytest-freezer (>=0.4.8)", "pytest-mock (>=3.11.1)", "pytest-randomly (>=3.12)", "pytest-timeout (>=2.1)", "setuptools (>=68)", "time-machine (>=2.10)"] [[package]] diff --git a/python/kserve/kserve/protocol/rest/v2_datamodels.py b/python/kserve/kserve/protocol/rest/v2_datamodels.py index 48255d5449..6b69d751d4 100644 --- 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 diff --git 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