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+24,9 @@ async def run_remote(self, data: DataModel) -> DataModel: class AsyncChainletNoInput(chains.ChainletBase): async def run_remote(self) -> DataModel: - return DataModel(msg="From async no input", np_array=np.full((3, 2, 1), 3)) + data = DataModel(msg="From async no input", np_array=np.full((2, 2), 3)) + print(data) + return data class AsyncChainletNoOutput(chains.ChainletBase): @@ -32,22 +34,24 @@ async def run_remote(self, data: DataModel) -> None: print(data) -class Host(chains.ChainletBase): - """Consume that reads the raw streams and parses them.""" +class HostJSON(chains.ChainletBase): + """Calls various chainlets in JSON mode.""" def __init__( self, - sync_chainlet=chains.depends(SynChainlet, use_binary=True), - async_chainlet=chains.depends(AsyncChainlet, use_binary=True), - async_chainlet_no_output=chains.depends(AsyncChainletNoOutput, use_binary=True), - async_chainlet_no_input=chains.depends(AsyncChainletNoInput, use_binary=True), + sync_chainlet=chains.depends(SynChainlet, use_binary=False), + async_chainlet=chains.depends(AsyncChainlet, use_binary=False), + async_chainlet_no_output=chains.depends( + AsyncChainletNoOutput, use_binary=False + ), + async_chainlet_no_input=chains.depends(AsyncChainletNoInput, use_binary=False), ): self._sync_chainlet = sync_chainlet self._async_chainlet = async_chainlet self._async_chainlet_no_output = async_chainlet_no_output self._async_chainlet_no_input = async_chainlet_no_input - async def run_remote(self) -> tuple[DataModel, DataModel]: + async def run_remote(self) -> tuple[DataModel, DataModel, DataModel]: a = np.ones((3, 2, 1)) data = DataModel(msg="From Host", np_array=a) sync_result = self._sync_chainlet.run_remote(data) @@ -55,22 +59,34 @@ async def run_remote(self) -> tuple[DataModel, DataModel]: async_result = await self._async_chainlet.run_remote(data) print(async_result) await self._async_chainlet_no_output.run_remote(data) - # async_no_input = await self._async_chainlet_no_input.run_remote() - # print(async_no_input) - return sync_result, async_result - # return data, async_result + async_no_input = await self._async_chainlet_no_input.run_remote() + print(async_no_input) + return sync_result, async_result, async_no_input -if __name__ == "__main__": - from truss.templates.shared import serialization +class HostBinary(chains.ChainletBase): + """Calls various chainlets in binary mode.""" - a = np.ones( - (3, 2, 1), - ) - out = serialization.truss_msgpack_serialize(a) - print(out) + def __init__( + self, + sync_chainlet=chains.depends(SynChainlet, use_binary=True), + async_chainlet=chains.depends(AsyncChainlet, use_binary=True), + async_chainlet_no_output=chains.depends(AsyncChainletNoOutput, use_binary=True), + async_chainlet_no_input=chains.depends(AsyncChainletNoInput, use_binary=True), + ): + self._sync_chainlet = sync_chainlet + self._async_chainlet = async_chainlet + self._async_chainlet_no_output = async_chainlet_no_output + self._async_chainlet_no_input = async_chainlet_no_input - print(serialization.truss_msgpack_deserialize(out)) - # data = b'\x81\xa4data\x82\xa3msg\xa9From Host\xa8np_array\x85\xc4\x02nd\xc3\xc4\x04type\xa3 tuple[DataModel, DataModel, DataModel]: + a = np.ones((3, 2, 1)) + data = DataModel(msg="From Host", np_array=a) + sync_result = self._sync_chainlet.run_remote(data) + print(sync_result) + async_result = await self._async_chainlet.run_remote(data) + print(async_result) + await self._async_chainlet_no_output.run_remote(data) + async_no_input = await self._async_chainlet_no_input.run_remote() + print(async_no_input) + return sync_result, async_result, async_no_input diff --git a/truss-chains/examples/rag/rag_chain.py b/truss-chains/examples/rag/rag_chain.py index e786432b2..1e32171fd 100644 --- a/truss-chains/examples/rag/rag_chain.py +++ b/truss-chains/examples/rag/rag_chain.py @@ -116,7 +116,7 @@ async def run_remote(self, new_bio: str, bios: list[str]) -> str: f"People from database: {bios_info}" ) resp = await self.predict_async( - inputs={ + { "messages": [{"role": "user", "content": prompt}], "stream": False, "max_new_tokens": 32, diff --git a/truss-chains/tests/test_e2e.py b/truss-chains/tests/test_e2e.py index ccb24fe68..f56f3d299 100644 --- a/truss-chains/tests/test_e2e.py +++ b/truss-chains/tests/test_e2e.py @@ -168,15 +168,20 @@ async def test_streaming_chain_local(): @pytest.mark.integration -def test_numpy_chain(): +@pytest.mark.parametrize("mode", ["json", "binary"]) +def test_numpy_chain(mode): + if mode == "json": + target = "HostBinary" + else: + target = "HostBinary" with ensure_kill_all(): examples_root = Path(__file__).parent.parent.resolve() / "examples" chain_root = examples_root / "numpy_and_binary" / "chain.py" - with framework.import_target(chain_root, "Host") as entrypoint: + with framework.import_target(chain_root, target) as entrypoint: service = remote.push( entrypoint, options=definitions.PushOptionsLocalDocker( - chain_name="integration-test-numpy", + chain_name=f"integration-test-numpy-{mode}", only_generate_trusses=False, use_local_chains_src=True, ), diff --git a/truss-chains/truss_chains/code_gen.py b/truss-chains/truss_chains/code_gen.py index 96ef2a161..1392fb307 100644 --- a/truss-chains/truss_chains/code_gen.py +++ b/truss-chains/truss_chains/code_gen.py @@ -251,9 +251,8 @@ def _stub_endpoint_body_src( E.g.: ``` - json_result = await self.predict_async( - SplitTextInput(inputs=inputs, extra_arg=extra_arg).model_dump()) - return SplitTextOutput.model_validate(json_result).output + return await self.predict_async( + SplitTextInput(inputs=inputs, extra_arg=extra_arg), SplitTextOutput).root ``` """ imports: set[str] = set() @@ -309,9 +308,8 @@ class SplitText(stub.StubBase): async def run_remote( self, inputs: shared_chainlet.SplitTextInput, extra_arg: int ) -> tuple[shared_chainlet.SplitTextOutput, int]: - json_result = await self.predict_async( - SplitTextInput(inputs=inputs, extra_arg=extra_arg).model_dump()) - return SplitTextOutput.model_validate(json_result).root + return await self.predict_async( + SplitTextInput(inputs=inputs, extra_arg=extra_arg), SplitTextOutput).root ``` """ imports = {"from truss_chains import stub"} diff --git a/truss-chains/truss_chains/definitions.py b/truss-chains/truss_chains/definitions.py index 4b9381bd3..47c853819 100644 --- a/truss-chains/truss_chains/definitions.py +++ b/truss-chains/truss_chains/definitions.py @@ -397,10 +397,22 @@ def get_asset_spec(self) -> AssetSpec: class RPCOptions(SafeModel): - """Options to customize RPCs to dependency chainlets.""" + """Options to customize RPCs to dependency chainlets. + + Args: + retries: The number of times to retry the remote chainlet in case of failures + (e.g. due to transient network issues). For streaming, retries are only made + if the request fails before streaming any results back. Failures mid-stream + not retried. + timeout_sec: Timeout for the HTTP request to this chainlet. + use_binary: whether to send data data in binary format. This can give a parsing + speedup and message size reduction (~25%) for numpy arrays. Use + ``NumpyArrayField`` as a field type on pydantic models for integration and set + this option to ``True``. For simple text data, there is no significant benefit. + """ - timeout_sec: int = DEFAULT_TIMEOUT_SEC retries: int = 1 + timeout_sec: int = DEFAULT_TIMEOUT_SEC use_binary: bool = False diff --git a/truss-chains/truss_chains/public_api.py b/truss-chains/truss_chains/public_api.py index 0a8b9c18e..f07e57cdf 100644 --- a/truss-chains/truss_chains/public_api.py +++ b/truss-chains/truss_chains/public_api.py @@ -59,8 +59,14 @@ def depends( Args: chainlet_cls: The chainlet class of the dependency. retries: The number of times to retry the remote chainlet in case of failures - (e.g. due to transient network issues). + (e.g. due to transient network issues). For streaming, retries are only made + if the request fails before streaming any results back. Failures mid-stream + not retried. timeout_sec: Timeout for the HTTP request to this chainlet. + use_binary: whether to send data data in binary format. This can give a parsing + speedup and message size reduction (~25%) for numpy arrays. Use + ``NumpyArrayField`` as a field type on pydantic models for integration and set + this option to ``True``. For simple text data, there is no significant benefit. Returns: A "symbolic marker" to be used as a default argument in a chainlet's diff --git a/truss-chains/truss_chains/pydantic_numpy.py b/truss-chains/truss_chains/pydantic_numpy.py index 5cd8db0e0..a544d88f9 100644 --- a/truss-chains/truss_chains/pydantic_numpy.py +++ b/truss-chains/truss_chains/pydantic_numpy.py @@ -1,5 +1,5 @@ import base64 -from typing import TYPE_CHECKING, Any, ClassVar, TypeVar +from typing import TYPE_CHECKING, Any, ClassVar import pydantic from pydantic.json_schema import JsonSchemaValue @@ -10,6 +10,36 @@ class NumpyArrayField: + """Wrapper class to support numpy arrays as fields on pydantic models and provide + JSON or binary serialization implementations. + + The JSON serialization exposes (data, shape, dtype), where the data is base-64 + encoded which leads to ~33% overhead. + + Usage example: + + ``` + import numpy as np + + class MyModel(pydantic.BaseModel): + my_array: NumpyArrayField + + m = MyModel(my_array=np.arange(4).reshape((2, 2))) + m.my_array_field.array += 10 # Work with the numpy array. + print(m) + # my_array=NumpyArrayField( + # shape=(2, 2), + # dtype=int64, + # data=[[10 11] [12 13]]) + m_json = m.model_dump(mode="json") + print(m_json) + # {'my_array': { + # 'data_b64': 'CgAAAAAAAAALAAAAAAAAAAwAAAAAAAAADQAAAAAAAAA=', + # 'shape': [2, 2], + # 'dtype': 'int64'}} + ``` + """ + data_key: ClassVar[str] = "data_b64" shape_key: ClassVar[str] = "shape" dtype_key: ClassVar[str] = "dtype" @@ -98,70 +128,3 @@ def __get_pydantic_json_schema__( } ) return json_schema - - -if __name__ == "__main__": - import numpy as np - from truss.templates.shared import serialization - - def model_dump_binary(data) -> bytes: - import msgpack - import msgpack_numpy as m - - m.patch() - return msgpack.packb(data, use_bin_type=True) - - _T = TypeVar("_T", bound=pydantic.BaseModel) - - def deserialize_model(data: bytes): - import msgpack - import msgpack_numpy as m - - m.patch() # Patch msgpack to support numpy arrays. - return msgpack.unpackb(data, raw=False) - - class Header(pydantic.BaseModel): - time: float = 123.45 - msg: str = "test" - - class MyModel(pydantic.BaseModel): - array: NumpyArrayField - header: Header = Header() - - class NestedModel(pydantic.BaseModel): - array_wrapper: MyModel - - # print(NestedModel.model_json_schema()) - - array = np.random.random(size=(2, 10000)) - nested_model = NestedModel(array_wrapper=MyModel(array=NumpyArrayField(array))) - - def python_roundtrip(): - data_dict = nested_model.model_dump(mode="python") - data_bytes = model_dump_binary(data_dict) - deserialize_model(data_bytes) - restored_dict = deserialize_model(data_bytes) - restored = NestedModel.model_validate(restored_dict) - return restored, len(data_bytes) - - def python_roundtrip_truss(): - data_dict = nested_model.model_dump(mode="python") - data_bytes = model_dump_binary(data_dict) - deserialize_model(data_bytes) - restored_dict = serialization.truss_msgpack_deserialize(data_bytes) - restored = NestedModel.model_validate(restored_dict) - return restored, len(data_bytes) - - def json_roundtrip(): - data_str = nested_model.model_dump_json() - restored = NestedModel.model_validate_json(data_str) - return restored, len(data_str) - - # 34.9 µs ± 191 ns per loop (mean ± std. dev. of 7 runs, 10000 loops each) - python_restored, python_len = python_roundtrip() - # 554 µs ± 4.66 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each) - json_restored, json_len = json_roundtrip() - # 554 µs ± 4.66 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each) - python_restored_truss, python_len_truss = python_roundtrip_truss() - - print(python_len, json_len, python_len / json_len) diff --git a/truss-chains/truss_chains/stub.py b/truss-chains/truss_chains/stub.py index 0e65123a2..9d3664524 100644 --- a/truss-chains/truss_chains/stub.py +++ b/truss-chains/truss_chains/stub.py @@ -41,7 +41,7 @@ _RetryPolicyT = TypeVar("_RetryPolicyT", tenacity.AsyncRetrying, tenacity.Retrying) -_InputT = TypeVar("_InputT", pydantic.BaseModel, None, Any) +_InputT = TypeVar("_InputT", pydantic.BaseModel, Any) _OutputT = TypeVar("_OutputT", bound=pydantic.BaseModel) @@ -456,10 +456,13 @@ def _make_request_params( data_key = "content" if for_httpx else "data" kwargs[data_key] = inputs.model_dump_json() headers["Content-Type"] = "application/json" - - elif inputs is not None: - kwargs["json"] = inputs - headers["Content-Type"] = "application/json" + else: # inputs is JSON dict. + if self._service_descriptor.options.use_binary: + kwargs["data"] = serialization.truss_msgpack_serialize(inputs) + headers["Content-Type"] = "application/octet-stream" + else: + kwargs["json"] = inputs + headers["Content-Type"] = "application/json" kwargs["headers"] = headers return kwargs @@ -475,10 +478,6 @@ def _response_to_pydantic( def _response_to_json(self, response: bytes) -> Any: if self._service_descriptor.options.use_binary: return serialization.truss_msgpack_deserialize(response) - # import msgpack - # import msgpack_numpy as m - # m.patch() - # return msgpack.unpackb(response, raw=False) return json.loads(response) @overload diff --git a/truss/templates/server/model_wrapper.py b/truss/templates/server/model_wrapper.py index 51d8f238b..6feea1eca 100644 --- a/truss/templates/server/model_wrapper.py +++ b/truss/templates/server/model_wrapper.py @@ -63,6 +63,7 @@ Generator[bytes, None, None], AsyncGenerator[bytes, None], "starlette.responses.Response", + pydantic.BaseModel, ] diff --git a/truss/templates/server/requirements.txt b/truss/templates/server/requirements.txt index 42766d343..924b0d8ff 100644 --- a/truss/templates/server/requirements.txt +++ b/truss/templates/server/requirements.txt @@ -7,7 +7,7 @@ fastapi==0.114.1 joblib==1.2.0 loguru==0.7.2 msgpack-numpy==0.4.8 -msgpack==1.1.0 +msgpack==1.1.0 # Numpy/msgpack versions are finniky (1.0.2 breaks), double check when changing. numpy>=1.23.5 opentelemetry-api>=1.25.0 opentelemetry-sdk>=1.25.0 diff --git a/truss/templates/server/truss_server.py b/truss/templates/server/truss_server.py index 0db99224e..8e30a884b 100644 --- a/truss/templates/server/truss_server.py +++ b/truss/templates/server/truss_server.py @@ -16,7 +16,7 @@ from fastapi import Depends, FastAPI, HTTPException, Request from fastapi.responses import ORJSONResponse, StreamingResponse from fastapi.routing import APIRoute as FastAPIRoute -from model_wrapper import InputType, ModelWrapper +from model_wrapper import InputType, ModelWrapper, OutputType from opentelemetry import propagate as otel_propagate from opentelemetry import trace from opentelemetry.sdk import trace as sdk_trace @@ -110,7 +110,6 @@ async def _parse_body( ) -> InputType: if self.is_binary(request): with tracing.section_as_event(span, "binary-deserialize"): - print(f"RECEIVING:\n{'@' * 80}\n{body_raw}\n{'@' * 80}") inputs = serialization.truss_msgpack_deserialize(body_raw) if truss_schema: try: @@ -169,7 +168,7 @@ async def predict( ) # Calls ModelWrapper which runs: preprocess, predict, postprocess. with tracing.section_as_event(span, "model-call"): - result: Union[Dict, Generator] = await model(inputs, request) + result: OutputType = await model(inputs, request) # In the case that the model returns a Generator object, return a # StreamingResponse instead. @@ -180,31 +179,42 @@ async def predict( if result.status_code >= HTTPStatus.MULTIPLE_CHOICES.value: errors.add_error_headers_to_user_response(result) return result + return self._serialize_result(result, self.is_binary(request), span) - response_headers = {} - if self.is_binary(request): - if isinstance(result, BaseModel): - with tracing.section_as_event(span, "binary-dump"): - if PYDANTIC_MAJOR_VERSION > 1: - result = result.model_dump(mode="python") - else: - result = result.dict() - - if not isinstance(result, bytes): - with tracing.section_as_event(span, "binary-serialize"): - result = serialization.truss_msgpack_serialize(result) - - response_headers["Content-Type"] = "application/octet-stream" - return Response(content=result, headers=response_headers) - else: - with tracing.section_as_event(span, "json-serialize"): - if isinstance(result, BaseModel): - content = result.json() + def _serialize_result( + self, result: OutputType, is_binary: bool, span: trace.Span + ) -> Response: + response_headers = {} + if is_binary: + if isinstance(result, BaseModel): + with tracing.section_as_event(span, "binary-dump"): + if PYDANTIC_MAJOR_VERSION > 1: + result = result.model_dump(mode="python") else: - content = json.dumps(result, cls=serialization.DeepNumpyEncoder) - - response_headers["Content-Type"] = "application/json" - return Response(content=content, headers=response_headers) + result = result.dict() + # If the result is not already serialize and not a pydantic model, it must + # be something that can be serialized with `truss_msgpack_serialize` (some + # dict / nested structure). + if not isinstance(result, bytes): + with tracing.section_as_event(span, "binary-serialize"): + result = serialization.truss_msgpack_serialize(result) + + response_headers["Content-Type"] = "application/octet-stream" + return Response(content=result, headers=response_headers) + else: + with tracing.section_as_event(span, "json-serialize"): + if isinstance(result, BaseModel): + # Note: chains has a pydantic integration for numpy arrays + # `NumpyArrayField`. `result.dict()`, passes through the array + # object which cannot be JSON serialized. + # In pydantic v2 `result.model_dump(mode="json")` could be used. + # For backwards compatibility we dump directly the JSON string. + content = result.json() + else: + content = json.dumps(result, cls=serialization.DeepNumpyEncoder) + + response_headers["Content-Type"] = "application/json" + return Response(content=content, headers=response_headers) async def schema(self, model_name: str) -> Dict: model: ModelWrapper = self._safe_lookup_model(model_name)