From 572968fee361c4e9d813de6bd8c02420afef250b Mon Sep 17 00:00:00 2001 From: Eugene Yurtsev Date: Fri, 29 Sep 2023 12:37:09 -0400 Subject: [PATCH] Using langchain input types (#11204) Using langchain input type --- libs/langserve/langserve/client.py | 38 +- libs/langserve/langserve/serialization.py | 94 ++++ libs/langserve/langserve/server.py | 82 ++- libs/langserve/langserve/validation.py | 100 +--- libs/langserve/poetry.lock | 518 +++++++++--------- libs/langserve/pyproject.toml | 2 +- .../tests/unit_tests/test_encoders.py | 122 +++++ .../tests/unit_tests/test_server_client.py | 58 +- .../tests/unit_tests/test_validation.py | 106 ---- 9 files changed, 602 insertions(+), 518 deletions(-) create mode 100644 libs/langserve/langserve/serialization.py create mode 100644 libs/langserve/tests/unit_tests/test_encoders.py diff --git a/libs/langserve/langserve/client.py b/libs/langserve/langserve/client.py index 994d7e27b6..d1d68a9202 100644 --- a/libs/langserve/langserve/client.py +++ b/libs/langserve/langserve/client.py @@ -9,7 +9,6 @@ from urllib.parse import urljoin import httpx from langchain.callbacks.tracers.log_stream import RunLogPatch from langchain.load.dump import dumpd -from langchain.load.load import load, loads from langchain.schema.runnable import Runnable from langchain.schema.runnable.config import ( RunnableConfig, @@ -19,6 +18,8 @@ from langchain.schema.runnable.config import ( ) from langchain.schema.runnable.utils import Input, Output +from langserve.serialization import simple_dumpd, simple_loads + def _without_callbacks(config: Optional[RunnableConfig]) -> RunnableConfig: """Evict callbacks from the config since those are definitely not supported.""" @@ -111,6 +112,7 @@ class RemoteRunnable(Runnable[Input, Output]): self.url = url self.sync_client = httpx.Client(base_url=url, timeout=timeout) self.async_client = httpx.AsyncClient(base_url=url, timeout=timeout) + # Register cleanup handler once RemoteRunnable is garbage collected weakref.finalize(self, _close_clients, self.sync_client, self.async_client) @@ -121,13 +123,13 @@ class RemoteRunnable(Runnable[Input, Output]): response = self.sync_client.post( "/invoke", json={ - "input": dumpd(input), + "input": simple_dumpd(input), "config": _without_callbacks(config), "kwargs": kwargs, }, ) _raise_for_status(response) - return load(response.json())["output"] + return simple_loads(response.text)["output"] def invoke( self, input: Input, config: Optional[RunnableConfig] = None, **kwargs: Any @@ -142,13 +144,13 @@ class RemoteRunnable(Runnable[Input, Output]): response = await self.async_client.post( "/invoke", json={ - "input": dumpd(input), + "input": simple_dumpd(input), "config": _without_callbacks(config), "kwargs": kwargs, }, ) _raise_for_status(response) - return load(response.json())["output"] + return simple_loads(response.text)["output"] async def ainvoke( self, input: Input, config: Optional[RunnableConfig] = None, **kwargs: Any @@ -180,13 +182,13 @@ class RemoteRunnable(Runnable[Input, Output]): response = self.sync_client.post( "/batch", json={ - "inputs": dumpd(inputs), + "inputs": simple_dumpd(inputs), "config": _config, "kwargs": kwargs, }, ) _raise_for_status(response) - return load(response.json())["output"] + return simple_loads(response.text)["output"] def batch( self, @@ -222,13 +224,13 @@ class RemoteRunnable(Runnable[Input, Output]): response = await self.async_client.post( "/batch", json={ - "inputs": dumpd(inputs), + "inputs": simple_dumpd(inputs), "config": _config, "kwargs": kwargs, }, ) _raise_for_status(response) - return load(response.json())["output"] + return simple_loads(response.text)["output"] async def abatch( self, @@ -259,11 +261,11 @@ class RemoteRunnable(Runnable[Input, Output]): run_manager = callback_manager.on_chain_start( dumpd(self), - dumpd(input), + simple_dumpd(input), name=config.get("run_name"), ) data = { - "input": dumpd(input), + "input": simple_dumpd(input), "config": _without_callbacks(config), "kwargs": kwargs, } @@ -283,7 +285,7 @@ class RemoteRunnable(Runnable[Input, Output]): ) as event_source: for sse in event_source.iter_sse(): if sse.event == "data": - chunk = loads(sse.data) + chunk = simple_loads(sse.data) yield chunk if final_output: @@ -313,11 +315,11 @@ class RemoteRunnable(Runnable[Input, Output]): run_manager = await callback_manager.on_chain_start( dumpd(self), - dumpd(input), + simple_dumpd(input), name=config.get("run_name"), ) data = { - "input": dumpd(input), + "input": simple_dumpd(input), "config": _without_callbacks(config), "kwargs": kwargs, } @@ -334,7 +336,7 @@ class RemoteRunnable(Runnable[Input, Output]): ) as event_source: async for sse in event_source.aiter_sse(): if sse.event == "data": - chunk = loads(sse.data) + chunk = simple_loads(sse.data) yield chunk if final_output: @@ -383,11 +385,11 @@ class RemoteRunnable(Runnable[Input, Output]): run_manager = await callback_manager.on_chain_start( dumpd(self), - dumpd(input), + simple_dumpd(input), name=config.get("run_name"), ) data = { - "input": dumpd(input), + "input": simple_dumpd(input), "config": _without_callbacks(config), "kwargs": kwargs, "include_names": include_names, @@ -410,7 +412,7 @@ class RemoteRunnable(Runnable[Input, Output]): ) as event_source: async for sse in event_source.aiter_sse(): if sse.event == "data": - data = loads(sse.data) + data = simple_loads(sse.data) chunk = RunLogPatch(*data["ops"]) yield chunk diff --git a/libs/langserve/langserve/serialization.py b/libs/langserve/langserve/serialization.py new file mode 100644 index 0000000000..1942db6878 --- /dev/null +++ b/libs/langserve/langserve/serialization.py @@ -0,0 +1,94 @@ +"""Serialization module for Well Known LangChain objects. + +Specialized JSON serialization for well known LangChain objects that +can be expected to be frequently transmitted between chains. +""" +import json +from typing import Any, Union + +from langchain.prompts.base import StringPromptValue +from langchain.prompts.chat import ChatPromptValueConcrete +from langchain.schema.document import Document +from langchain.schema.messages import ( + AIMessage, + AIMessageChunk, + ChatMessage, + ChatMessageChunk, + FunctionMessage, + FunctionMessageChunk, + HumanMessage, + HumanMessageChunk, + SystemMessage, + SystemMessageChunk, +) +from pydantic import BaseModel, ValidationError + + +class WellKnownLCObject(BaseModel): + """A well known LangChain object.""" + + __root__: Union[ + Document, + HumanMessage, + SystemMessage, + ChatMessage, + FunctionMessage, + AIMessage, + HumanMessageChunk, + SystemMessageChunk, + ChatMessageChunk, + FunctionMessageChunk, + AIMessageChunk, + StringPromptValue, + ChatPromptValueConcrete, + ] + + +# Custom JSON Encoder +class _LangChainEncoder(json.JSONEncoder): + """Custom JSON Encoder that can encode pydantic objects as well.""" + + def default(self, obj) -> Any: + if isinstance(obj, BaseModel): + return obj.dict() + return super().default(obj) + + +# Custom JSON Decoder +class _LangChainDecoder(json.JSONDecoder): + """Custom JSON Decoder that handles well known LangChain objects.""" + + def __init__(self, *args: Any, **kwargs: Any) -> None: + """Initialize the LangChainDecoder.""" + super().__init__(object_hook=self.decoder, *args, **kwargs) + + def decoder(self, value) -> Any: + """Decode the value.""" + if isinstance(value, dict): + try: + obj = WellKnownLCObject.parse_obj(value) + return obj.__root__ + except ValidationError: + return {key: self.decoder(v) for key, v in value.items()} + elif isinstance(value, list): + return [self.decoder(item) for item in value] + else: + return value + + +# PUBLIC API + + +def simple_dumpd(obj: Any) -> Any: + """Convert the given object to a JSON serializable object.""" + return json.loads(json.dumps(obj, cls=_LangChainEncoder)) + + +def simple_dumps(obj: Any) -> str: + """Dump the given object as a JSON string.""" + return json.dumps(obj, cls=_LangChainEncoder) + + +def simple_loads(s: str) -> Any: + """Load the given JSON string.""" + return json.loads(s, cls=_LangChainDecoder) diff --git a/libs/langserve/langserve/server.py b/libs/langserve/langserve/server.py index 0a43449027..54e264be60 100644 --- a/libs/langserve/langserve/server.py +++ b/libs/langserve/langserve/server.py @@ -1,31 +1,31 @@ +from inspect import isclass from typing import ( Any, AsyncIterator, Dict, List, + Literal, Mapping, Sequence, Type, Union, ) -from langchain.load.dump import dumpd, dumps -from langchain.load.load import load from langchain.schema.runnable import Runnable from typing_extensions import Annotated try: from pydantic.v1 import BaseModel except ImportError: - from pydantic import BaseModel + from pydantic import BaseModel, create_model +from langserve.serialization import simple_dumpd, simple_dumps from langserve.validation import ( create_batch_request_model, create_invoke_request_model, create_runnable_config_model, create_stream_log_request_model, create_stream_request_model, - replace_lc_object_types, ) try: @@ -66,6 +66,31 @@ class BatchResponse(BaseModel): """ +def _unpack_input(validated_model: BaseModel) -> Any: + """Unpack the decoded input from the validated model.""" + if hasattr(validated_model, "__root__"): + return validated_model.__root__ + else: + return validated_model + + +_MODEL_REGISTRY = {} + + +def _resolve_input_type(input_type: Union[Type, BaseModel]) -> BaseModel: + if isclass(input_type) and issubclass(input_type, BaseModel): + input_type_ = input_type + else: + input_type_ = create_model("Input", __root__=(input_type, ...)) + + hash_ = input_type_.schema_json() + + if hash_ not in _MODEL_REGISTRY: + _MODEL_REGISTRY[hash_] = input_type_ + + return _MODEL_REGISTRY[hash_] + + # PUBLIC API @@ -74,7 +99,7 @@ def add_routes( runnable: Runnable, *, path: str = "", - input_type: Type = Any, + input_type: Union[Type, Literal["auto"], BaseModel] = "auto", config_keys: Sequence[str] = (), ) -> None: """Register the routes on the given FastAPI app or APIRouter. @@ -83,9 +108,9 @@ def add_routes( app: The FastAPI app or APIRouter to which routes should be added. runnable: The runnable to wrap, must not be stateful. path: A path to prepend to all routes. - input_type: Optional type to define a schema for the input part of the request. - If not provided, any input that can be de-serialized with LangChain's - serializer will be accepted. + input_type: type to use for input validation. + Default is "auto" which will use the InputType of the runnable. + User is free to provide a custom type annotation. config_keys: list of config keys that will be accepted, by default no config keys are accepted. """ @@ -98,19 +123,22 @@ def add_routes( "Use `pip install sse_starlette` to install." ) - input_type = replace_lc_object_types(input_type) + if input_type == "auto": + input_type_ = _resolve_input_type(runnable.input_schema) + else: + input_type_ = _resolve_input_type(input_type) namespace = path or "" model_namespace = path.strip("/").replace("/", "_") config = create_runnable_config_model(model_namespace, config_keys) - InvokeRequest = create_invoke_request_model(model_namespace, input_type, config) - BatchRequest = create_batch_request_model(model_namespace, input_type, config) + InvokeRequest = create_invoke_request_model(model_namespace, input_type_, config) + BatchRequest = create_batch_request_model(model_namespace, input_type_, config) # Stream request is the same as invoke request, but with a different response type - StreamRequest = create_stream_request_model(model_namespace, input_type, config) + StreamRequest = create_stream_request_model(model_namespace, input_type_, config) StreamLogRequest = create_stream_log_request_model( - model_namespace, input_type, config + model_namespace, input_type_, config ) @app.post( @@ -124,25 +152,25 @@ def add_routes( # Request is first validated using InvokeRequest which takes into account # config_keys as well as input_type. # After validation, the input is loaded using LangChain's load function. - input = load(request.dict()["input"]) config = _project_dict(request.config, config_keys) - output = await runnable.ainvoke(input, config=config, **request.kwargs) - return InvokeResponse(output=dumpd(output)) + output = await runnable.ainvoke( + _unpack_input(request.input), config=config, **request.kwargs + ) + + return InvokeResponse(output=simple_dumpd(output)) # @app.post(f"{namespace}/batch", response_model=BatchResponse) async def batch(request: Annotated[BatchRequest, BatchRequest]) -> BatchResponse: """Invoke the runnable with the given inputs and config.""" - # Request is first validated using InvokeRequest which takes into account - # config_keys as well as input_type. - # After validation, the input is loaded using LangChain's load function. - inputs = load(request.dict()["inputs"]) if isinstance(request.config, list): config = [_project_dict(config, config_keys) for config in request.config] else: config = _project_dict(request.config, config_keys) + inputs = [_unpack_input(input_) for input_ in request.inputs] output = await runnable.abatch(inputs, config=config, **request.kwargs) - return BatchResponse(output=dumpd(output)) + + return BatchResponse(output=simple_dumpd(output)) @app.post(f"{namespace}/stream") async def stream( @@ -152,17 +180,17 @@ def add_routes( # Request is first validated using InvokeRequest which takes into account # config_keys as well as input_type. # After validation, the input is loaded using LangChain's load function. - input = load(request.dict()["input"]) + input_ = _unpack_input(request.input) config = _project_dict(request.config, config_keys) async def _stream() -> AsyncIterator[dict]: """Stream the output of the runnable.""" async for chunk in runnable.astream( - input, + input_, config=config, **request.kwargs, ): - yield {"data": dumps(chunk), "event": "data"} + yield {"data": simple_dumps(chunk), "event": "data"} yield {"event": "end"} return EventSourceResponse(_stream()) @@ -175,13 +203,13 @@ def add_routes( # Request is first validated using InvokeRequest which takes into account # config_keys as well as input_type. # After validation, the input is loaded using LangChain's load function. - input = load(request.dict()["input"]) + input_ = _unpack_input(request.input) config = _project_dict(request.config, config_keys) async def _stream_log() -> AsyncIterator[dict]: """Stream the output of the runnable.""" async for run_log_patch in runnable.astream_log( - input, + input_, config=config, include_names=request.include_names, include_types=request.include_types, @@ -193,7 +221,7 @@ def add_routes( ): # Temporary adapter yield { - "data": dumps({"ops": run_log_patch.ops}), + "data": simple_dumps({"ops": run_log_patch.ops}), "event": "data", } yield {"event": "end"} diff --git a/libs/langserve/langserve/validation.py b/libs/langserve/langserve/validation.py index c0e2a43f6c..591eb23b93 100644 --- a/libs/langserve/langserve/validation.py +++ b/libs/langserve/langserve/validation.py @@ -1,13 +1,11 @@ -import typing -from typing import Any, List, Optional, Sequence, Type, Union, get_args, get_origin +from typing import List, Optional, Sequence, Type, Union -from langchain.load.serializable import Serializable from langchain.schema.runnable import RunnableConfig try: from pydantic.v1 import BaseModel, Field, create_model except ImportError: - from pydantic import BaseModel, Field, create_model, validator + from pydantic import BaseModel, Field, create_model from typing_extensions import TypedDict @@ -104,97 +102,3 @@ def create_stream_log_request_model( ) stream_log_request.update_forward_refs() return stream_log_request - - -_TYPE_REGISTRY = {} -_SEEN_NAMES = set() - - -def _create_lc_object_validator(expected_id: Sequence[str]) -> Type[BaseModel]: - """Create a validator for lc objects. - - An LCObject is used to validate LangChain objects in dict representation. - - The model is associated with a validator that checks that the id of the LCObject - matches the expected id. This is used to ensure that the LCObject is of the - correct type. - - For OpenAPI docs to work, each unique LCObject must have a unique name. - The models are added to the registry to avoid creating duplicate models. - - Args: - model_id: The expected id of the LCObject. - - Returns: - A pydantic model that can be used to validate LCObjects. - """ - expected_id = tuple(expected_id) - model_id = tuple(["pydantic"]) + expected_id - if model_id in _TYPE_REGISTRY: - return _TYPE_REGISTRY[model_id] - - model_name = model_id[-1] - - if model_name in _SEEN_NAMES: - # Use fully qualified name - _name = ".".join(model_id) - else: - _name = model_name - if _name in _SEEN_NAMES: - raise AssertionError(f"Duplicate model name: {_name}") - - _SEEN_NAMES.add(model_name) - - class LCObject(BaseModel): - id: List[str] - lc: Any - type: str - kwargs: Any - - @validator("id", allow_reuse=True) - def validate_id_namespace(cls, id: Sequence[str]) -> None: - """Validate that the LCObject is one of the allowed types.""" - if tuple(id) != expected_id: - raise ValueError(f"LCObject id {id} is not allowed: {model_id}") - return id - - # Update the name of the model to make it unique. - model = create_model(_name, __base__=LCObject) - - _TYPE_REGISTRY[model_id] = model - return model - - -def replace_lc_object_types(type_annotation: typing.Any) -> typing.Any: - """Recursively replaces all LangChain objects with a serialized representation. - - Args: - type_annotation: The type annotation to replace. - - Returns: - The type annotation with all LCObject types replaced. - """ - origin = get_origin(type_annotation) - args = get_args(type_annotation) - - if args: - if isinstance(args, (list, tuple)): - new_args = [replace_lc_object_types(arg) for arg in args] - - if isinstance(origin, type): - if origin is list: - return typing.List[new_args[0]] - elif origin is tuple: - return typing.Tuple[tuple(new_args)] - else: - raise ValueError(f"Unknown origin type: {origin}") - else: - new_args = [replace_lc_object_types(arg) for arg in args] - return origin[tuple(new_args)] - - if isinstance(type_annotation, type): - if issubclass(type_annotation, Serializable): - lc_id = type_annotation.get_lc_namespace() + [type_annotation.__name__] - return _create_lc_object_validator(lc_id) - - return type_annotation diff --git a/libs/langserve/poetry.lock b/libs/langserve/poetry.lock index 70ce87b1ef..6db5354cba 100644 --- a/libs/langserve/poetry.lock +++ b/libs/langserve/poetry.lock @@ -419,75 +419,63 @@ files = [ [[package]] name = "cffi" -version = "1.15.1" +version = "1.16.0" description = "Foreign Function Interface for Python calling C code." optional = false -python-versions = "*" +python-versions = ">=3.8" files = [ - {file = "cffi-1.15.1-cp27-cp27m-macosx_10_9_x86_64.whl", hash = "sha256:a66d3508133af6e8548451b25058d5812812ec3798c886bf38ed24a98216fab2"}, - {file = "cffi-1.15.1-cp27-cp27m-manylinux1_i686.whl", hash = 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[tool.poetry.group.dev.dependencies] jupyterlab = "^3.6.1" diff --git a/libs/langserve/tests/unit_tests/test_encoders.py b/libs/langserve/tests/unit_tests/test_encoders.py new file mode 100644 index 0000000000..ec1c4700fb --- /dev/null +++ b/libs/langserve/tests/unit_tests/test_encoders.py @@ -0,0 +1,122 @@ +import json +from typing import Any + +import pytest +from langchain.schema.messages import ( + HumanMessage, + SystemMessage, +) + +from langserve.serialization import simple_dumps, simple_loads + + +@pytest.mark.parametrize( + "data, expected_json", + [ + # Test with python primitives + (1, 1), + ([], []), + ({}, {}), + ({"a": 1}, {"a": 1}), + ( + {"output": [HumanMessage(content="hello")]}, + { + "output": [ + { + "content": "hello", + "additional_kwargs": {}, + "type": "human", + "example": False, + } + ] + }, + ), + # Test with a single message (HumanMessage) + ( + HumanMessage(content="Hello"), + { + "additional_kwargs": {}, + "content": "Hello", + "example": False, + "type": "human", + }, + ), + # Test with a list containing mixed elements + ( + [HumanMessage(content="Hello"), SystemMessage(content="Hi"), 42, "world"], + [ + { + "additional_kwargs": {}, + "content": "Hello", + "example": False, + "type": "human", + }, + {"additional_kwargs": {}, "content": "Hi", "type": "system"}, + 42, + "world", + ], + ), + # # Attention: This test is not correct right now + # # Test with full and chunk messages + # ( + # [HumanMessage(content="Hello"), HumanMessageChunk(content="Hi")], + # [ + # { + # "additional_kwargs": {}, + # "content": "Hello", + # "example": False, + # "type": "human", + # }, + # { + # "additional_kwargs": {}, + # "content": "Hi", + # "example": False, + # "type": "human", + # }, + # ], + # ), + # # Attention: This test is not correct right now + # # Test with full and chunk messages + # ( + # [HumanMessageChunk(content="Hello"), HumanMessage(content="Hi")], + # [ + # { + # "additional_kwargs": {}, + # "content": "Hello", + # "example": False, + # "type": "human", + # }, + # { + # "additional_kwargs": {}, + # "content": "Hi", + # "example": False, + # "type": "human", + # }, + # ], + # ), + # Test with a dictionary containing mixed elements + ( + { + "message": HumanMessage(content="Greetings"), + "numbers": [1, 2, 3], + "boom": "Hello, world!", + }, + { + "message": { + "additional_kwargs": {}, + "content": "Greetings", + "example": False, + "type": "human", + }, + "numbers": [1, 2, 3], + "boom": "Hello, world!", + }, + ), + ], +) +def test_serialization(data: Any, expected_json: Any) -> None: + """Test that the LangChainEncoder encodes the data as expected.""" + # Test encoding + assert json.loads(simple_dumps(data)) == expected_json + # Test decoding + assert simple_loads(json.dumps(expected_json)) == data diff --git a/libs/langserve/tests/unit_tests/test_server_client.py b/libs/langserve/tests/unit_tests/test_server_client.py index 5bd1ada8c5..9c0b57d384 100644 --- a/libs/langserve/tests/unit_tests/test_server_client.py +++ b/libs/langserve/tests/unit_tests/test_server_client.py @@ -2,7 +2,7 @@ import asyncio from asyncio import AbstractEventLoop from contextlib import asynccontextmanager -from typing import Any, List, Optional +from typing import List, Optional, Union import httpx import pytest @@ -34,18 +34,16 @@ def event_loop(): def app(event_loop: AbstractEventLoop) -> FastAPI: """A simple server that wraps a Runnable and exposes it as an API.""" - async def add_one_or_passthrough(x: Any) -> int: + async def add_one_or_passthrough( + x: Union[int, HumanMessage] + ) -> Union[int, HumanMessage]: """Add one to int or passthrough.""" if isinstance(x, int): return x + 1 else: return x - def raise_on_call(x: int) -> int: - """Sync function server side should never be called.""" - raise AssertionError("Should not be called") - - runnable_lambda = RunnableLambda(func=raise_on_call, afunc=add_one_or_passthrough) + runnable_lambda = RunnableLambda(func=add_one_or_passthrough) app = FastAPI() try: add_routes(app, runnable_lambda) @@ -132,7 +130,6 @@ def test_invoke(client: RemoteRunnable) -> None: """Test sync invoke.""" assert client.invoke(1) == 2 assert client.invoke(HumanMessage(content="hello")) == HumanMessage(content="hello") - # Test invocation with config assert client.invoke(1, config={"tags": ["test"]}) == 2 @@ -234,6 +231,19 @@ def test_invoke_as_part_of_sequence(client: RemoteRunnable) -> None: # assert list(runnable.stream([1, 2], config={"tags": ["test"]})) == [3, 4] +def test_pydantic_root(): + from pydantic import BaseModel + + class Model(BaseModel): + __root__: str + + class Q(BaseModel): + input: Model + + # s = Model(__root__=[23]) + Q(input="hello") + + @pytest.mark.asyncio async def test_invoke_as_part_of_sequence_async(async_client: RemoteRunnable) -> None: """Test as part of a sequence. @@ -466,3 +476,35 @@ async def test_async_client_close() -> None: del runnable assert sync_client.is_closed is True assert async_client.is_closed is True + + +@pytest.mark.asyncio +async def test_openapi_docs_with_identical_runnables( + event_loop: AbstractEventLoop, mocker: MockerFixture +) -> None: + """Test client side and server side exceptions.""" + + async def add_one(x: int) -> int: + """Add one to simulate a valid function""" + return x + 1 + + server_runnable = RunnableLambda(func=add_one) + server_runnable2 = RunnableLambda(func=add_one) + + app = FastAPI() + add_routes( + app, + server_runnable, + path="/1", + ) + # Add another route that uses the same schema (inferred from runnable input schema) + add_routes( + app, + server_runnable2, + path="/2", + config_keys=["tags", "run_name"], + ) + + async with AsyncClient(app=app, base_url="http://localhost:9999") as async_client: + response = await async_client.get("/openapi.json") + assert response.status_code == 200 diff --git a/libs/langserve/tests/unit_tests/test_validation.py b/libs/langserve/tests/unit_tests/test_validation.py index 92a818ccb9..65dea8bdbe 100644 --- a/libs/langserve/tests/unit_tests/test_validation.py +++ b/libs/langserve/tests/unit_tests/test_validation.py @@ -1,10 +1,6 @@ -import typing from typing import Optional import pytest -from langchain.load.dump import dumpd -from langchain.schema import AIMessage, HumanMessage, SystemMessage -from typing_extensions import TypedDict try: from pydantic.v1 import BaseModel, ValidationError @@ -15,7 +11,6 @@ from langserve.validation import ( create_batch_request_model, create_invoke_request_model, create_runnable_config_model, - replace_lc_object_types, ) @@ -133,104 +128,3 @@ def test_validation(test_case) -> None: else: with pytest.raises(ValidationError): model(**test_case) - - -def test_replace_lc_object_types() -> None: - """Replace lc object types in a model.""" - updated_type = replace_lc_object_types(typing.List[HumanMessage]) - config = create_runnable_config_model("test", []) - invoke_request = create_invoke_request_model("namespace", updated_type, config) - invoke_request( - input=dumpd( - [ - HumanMessage(content="Hello, world!"), - HumanMessage(content="Hello, world 2!"), - ] - ) - ) - - with pytest.raises(ValidationError): - invoke_request(input=[dumpd(AIMessage(content="Hello, world!"))]) - - with pytest.raises(ValidationError): - invoke_request( - input=dumpd( - [ - AIMessage(content="Hello, world!"), - HumanMessage(content="Hello, world!"), - ] - ), - ) - - -def test_batch_request_with_lc_serialization() -> None: - """Test batch request with LC serialization.""" - - input_type = replace_lc_object_types(typing.List[HumanMessage]) - config = create_runnable_config_model("test", []) - batch_request = create_batch_request_model("namespace", input_type, config) - with pytest.raises(ValidationError): - batch_request(inputs=dumpd([[SystemMessage(content="Hello, world!")]])) - - with pytest.raises(ValidationError): - batch_request(inputs=dumpd(HumanMessage(content="Hello, world!"))) - - with pytest.raises(ValidationError): - batch_request(inputs=dumpd([HumanMessage(content="Hello, world!")])) - - batch_request(inputs=dumpd([[HumanMessage(content="Hello, world!")]])) - - -class PlaceHolderTypedDict(TypedDict): - x: int - z: HumanMessage - - -@pytest.mark.parametrize( - "type_,input,is_valid", - [ - (None, None, True), - (str, "hello", True), - (str, 123.0, True), - (float, "qwe", False), - (int, 1, True), - (int, "qwe", False), - (typing.Union[str, int], "hello", True), - (typing.Union[str, int], 3, True), - (typing.List[str], ["a", "b"], True), - (typing.List[str], ["a", None], False), - (typing.List[HumanMessage], [HumanMessage(content="hello, world!")], True), - (typing.List[HumanMessage], [SystemMessage(content="hello, world!")], False), - ( - typing.List[typing.Union[HumanMessage, SystemMessage]], - [HumanMessage(content="he"), SystemMessage(content="hello, world!")], - True, - ), - ( - typing.List[typing.Union[HumanMessage, SystemMessage]], - HumanMessage(content="hello"), - False, - ), - ( - typing.Union[ - typing.List[typing.Union[SystemMessage, HumanMessage, str]], str - ], - ["hello", "world"], - True, - ), - ], -) -def test_replace_lc_object_type( - type_: typing.Any, input: typing.Any, is_valid: bool -) -> None: - """Verify that code runs on different python versions.""" - new_type = replace_lc_object_types(type_) - - class Model(BaseModel): - input_: new_type - - if is_valid: - Model(input_=dumpd(input)) - else: - with pytest.raises(ValidationError): - Model(input_=dumpd(input))