diff --git a/libs/langchain/langchain/schema/runnable/base.py b/libs/langchain/langchain/schema/runnable/base.py index d660132767c..c7dd38865fa 100644 --- a/libs/langchain/langchain/schema/runnable/base.py +++ b/libs/langchain/langchain/schema/runnable/base.py @@ -217,6 +217,13 @@ class Runnable(Generic[Input, Output], ABC): """ return RunnableBinding(bound=self, kwargs=kwargs) + def map(self) -> Runnable[List[Input], List[Output]]: + """ + Return a new Runnable that maps a list of inputs to a list of outputs, + by calling invoke() with each input. + """ + return RunnableEach(bound=self) + def with_fallbacks( self, fallbacks: Sequence[Runnable[Input, Output]], @@ -1360,6 +1367,39 @@ class RunnableLambda(Runnable[Input, Output]): return self._call_with_config(self.func, input, config) +class RunnableEach(Serializable, Runnable[List[Input], List[Output]]): + """ + A runnable that delegates calls to another runnable + with each element of the input sequence. + """ + + bound: Runnable[Input, Output] + + class Config: + arbitrary_types_allowed = True + + @property + def lc_serializable(self) -> bool: + return True + + @property + def lc_namespace(self) -> List[str]: + return self.__class__.__module__.split(".")[:-1] + + def bind(self, **kwargs: Any) -> RunnableEach[Input, Output]: + return RunnableEach(bound=self.bound.bind(**kwargs)) + + def invoke( + self, input: List[Input], config: Optional[RunnableConfig] = None + ) -> List[Output]: + return self.bound.batch(input, config) + + async def ainvoke( + self, input: List[Input], config: Optional[RunnableConfig] = None, **kwargs: Any + ) -> List[Output]: + return await self.bound.abatch(input, config, **kwargs) + + class RunnableBinding(Serializable, Runnable[Input, Output]): """ A runnable that delegates calls to another runnable with a set of kwargs. diff --git a/libs/langchain/langchain/utilities/openapi.py b/libs/langchain/langchain/utilities/openapi.py index 34224a2bbf0..16dd5b680b3 100644 --- a/libs/langchain/langchain/utilities/openapi.py +++ b/libs/langchain/langchain/utilities/openapi.py @@ -54,7 +54,7 @@ if _PYDANTIC_MAJOR_VERSION == 1: try: from openapi_schema_pydantic import OpenAPI except ImportError: - OpenAPI = object + OpenAPI = object # type: ignore class OpenAPISpec(OpenAPI): """OpenAPI Model that removes mis-formatted parts of the spec.""" diff --git a/libs/langchain/tests/unit_tests/schema/runnable/__snapshots__/test_runnable.ambr b/libs/langchain/tests/unit_tests/schema/runnable/__snapshots__/test_runnable.ambr index 11e554a9cc4..828227fd308 100644 --- a/libs/langchain/tests/unit_tests/schema/runnable/__snapshots__/test_runnable.ambr +++ b/libs/langchain/tests/unit_tests/schema/runnable/__snapshots__/test_runnable.ambr @@ -464,6 +464,141 @@ Run(id=UUID('00000000-0000-4000-8000-000000000000'), name='RunnableSequence', start_time=FakeDatetime(2023, 1, 1, 0, 0), run_type='chain', end_time=FakeDatetime(2023, 1, 1, 0, 0), extra={}, error=None, serialized={'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'runnable', 'RunnableSequence'], 'kwargs': {'first': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nice assistant.', 'template_format': 'f-string', 'partial_variables': {}}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': ['question'], 'template': '{question}', 'template_format': 'f-string', 'partial_variables': {}}}}}], 'input_variables': ['question']}}, 'middle': [{'lc': 1, 'type': 'not_implemented', 'id': ['langchain', 'chat_models', 'fake', 'FakeListChatModel']}, {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'output_parsers', 'list', 'CommaSeparatedListOutputParser'], 'kwargs': {}}, {'lc': 1, 'type': 'not_implemented', 'id': ['langchain', 'schema', 'runnable', 'base', 'RunnableLambda']}, {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nicer assistant.', 'template_format': 'f-string', 'partial_variables': {}}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': ['question'], 'template': '{question}', 'template_format': 'f-string', 'partial_variables': {}}}}}], 'input_variables': ['question']}}, {'lc': 1, 'type': 'not_implemented', 'id': ['langchain', 'chat_models', 'fake', 'FakeListChatModel']}], 'last': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'output_parsers', 'list', 'CommaSeparatedListOutputParser'], 'kwargs': {}}}}, events=[{'name': 'start', 'time': FakeDatetime(2023, 1, 1, 0, 0)}, {'name': 'end', 'time': FakeDatetime(2023, 1, 1, 0, 0)}], inputs={'question': 'What is your name?'}, outputs={'output': ['baz', 'qux']}, reference_example_id=None, parent_run_id=None, tags=[], execution_order=None, child_execution_order=None, child_runs=[Run(id=UUID('00000000-0000-4000-8000-000000000001'), name='ChatPromptTemplate', start_time=FakeDatetime(2023, 1, 1, 0, 0), run_type='prompt', end_time=FakeDatetime(2023, 1, 1, 0, 0), extra={}, error=None, serialized={'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nice assistant.', 'template_format': 'f-string', 'partial_variables': {}}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': ['question'], 'template': '{question}', 'template_format': 'f-string', 'partial_variables': {}}}}}], 'input_variables': ['question']}}, events=[{'name': 'start', 'time': FakeDatetime(2023, 1, 1, 0, 0)}, {'name': 'end', 'time': FakeDatetime(2023, 1, 1, 0, 0)}], inputs={'question': 'What is your name?'}, outputs={'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'ChatPromptValue'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'SystemMessage'], 'kwargs': {'content': 'You are a nice assistant.', 'additional_kwargs': {}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'HumanMessage'], 'kwargs': {'content': 'What is your name?', 'additional_kwargs': {}}}]}}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=[], execution_order=None, child_execution_order=None, child_runs=[]), Run(id=UUID('00000000-0000-4000-8000-000000000002'), name='FakeListChatModel', start_time=FakeDatetime(2023, 1, 1, 0, 0), run_type='llm', end_time=FakeDatetime(2023, 1, 1, 0, 0), extra={'invocation_params': {'responses': ['foo, bar'], '_type': 'fake-list-chat-model', 'stop': None}, 'options': {'stop': None}}, error=None, serialized={'lc': 1, 'type': 'not_implemented', 'id': ['langchain', 'chat_models', 'fake', 'FakeListChatModel']}, events=[{'name': 'start', 'time': FakeDatetime(2023, 1, 1, 0, 0)}, {'name': 'end', 'time': FakeDatetime(2023, 1, 1, 0, 0)}], inputs={'prompts': ['System: You are a nice assistant.\nHuman: What is your name?']}, outputs={'generations': [[{'text': 'foo, bar', 'generation_info': None, 'message': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'AIMessage'], 'kwargs': {'content': 'foo, bar'}}}]], 'llm_output': None, 'run': None}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=[], execution_order=None, child_execution_order=None, child_runs=[]), Run(id=UUID('00000000-0000-4000-8000-000000000003'), name='CommaSeparatedListOutputParser', start_time=FakeDatetime(2023, 1, 1, 0, 0), run_type='parser', end_time=FakeDatetime(2023, 1, 1, 0, 0), extra={}, error=None, serialized={'lc': 1, 'type': 'constructor', 'id': ['langchain', 'output_parsers', 'list', 'CommaSeparatedListOutputParser'], 'kwargs': {}}, events=[{'name': 'start', 'time': FakeDatetime(2023, 1, 1, 0, 0)}, {'name': 'end', 'time': FakeDatetime(2023, 1, 1, 0, 0)}], inputs={'input': AIMessage(content='foo, bar', additional_kwargs={}, example=False)}, outputs={'output': ['foo', 'bar']}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=[], execution_order=None, child_execution_order=None, child_runs=[]), Run(id=UUID('00000000-0000-4000-8000-000000000004'), name='RunnableLambda', start_time=FakeDatetime(2023, 1, 1, 0, 0), run_type='chain', end_time=FakeDatetime(2023, 1, 1, 0, 0), extra={}, error=None, serialized={'lc': 1, 'type': 'not_implemented', 'id': ['langchain', 'schema', 'runnable', 'base', 'RunnableLambda']}, events=[{'name': 'start', 'time': FakeDatetime(2023, 1, 1, 0, 0)}, {'name': 'end', 'time': FakeDatetime(2023, 1, 1, 0, 0)}], inputs={'input': ['foo', 'bar']}, outputs={'question': 'foobar'}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=[], execution_order=None, child_execution_order=None, child_runs=[]), Run(id=UUID('00000000-0000-4000-8000-000000000005'), name='ChatPromptTemplate', start_time=FakeDatetime(2023, 1, 1, 0, 0), run_type='prompt', end_time=FakeDatetime(2023, 1, 1, 0, 0), extra={}, error=None, serialized={'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nicer assistant.', 'template_format': 'f-string', 'partial_variables': {}}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': ['question'], 'template': '{question}', 'template_format': 'f-string', 'partial_variables': {}}}}}], 'input_variables': ['question']}}, events=[{'name': 'start', 'time': FakeDatetime(2023, 1, 1, 0, 0)}, {'name': 'end', 'time': FakeDatetime(2023, 1, 1, 0, 0)}], inputs={'question': 'foobar'}, outputs={'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'ChatPromptValue'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'SystemMessage'], 'kwargs': {'content': 'You are a nicer assistant.', 'additional_kwargs': {}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'HumanMessage'], 'kwargs': {'content': 'foobar', 'additional_kwargs': {}}}]}}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=[], execution_order=None, child_execution_order=None, child_runs=[]), Run(id=UUID('00000000-0000-4000-8000-000000000006'), name='FakeListChatModel', start_time=FakeDatetime(2023, 1, 1, 0, 0), run_type='llm', end_time=FakeDatetime(2023, 1, 1, 0, 0), extra={'invocation_params': {'responses': ['baz, qux'], '_type': 'fake-list-chat-model', 'stop': None}, 'options': {'stop': None}}, error=None, serialized={'lc': 1, 'type': 'not_implemented', 'id': ['langchain', 'chat_models', 'fake', 'FakeListChatModel']}, events=[{'name': 'start', 'time': FakeDatetime(2023, 1, 1, 0, 0)}, {'name': 'end', 'time': FakeDatetime(2023, 1, 1, 0, 0)}], inputs={'prompts': ['System: You are a nicer assistant.\nHuman: foobar']}, outputs={'generations': [[{'text': 'baz, qux', 'generation_info': None, 'message': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'AIMessage'], 'kwargs': {'content': 'baz, qux'}}}]], 'llm_output': None, 'run': None}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=[], execution_order=None, child_execution_order=None, child_runs=[]), Run(id=UUID('00000000-0000-4000-8000-000000000007'), name='CommaSeparatedListOutputParser', start_time=FakeDatetime(2023, 1, 1, 0, 0), run_type='parser', end_time=FakeDatetime(2023, 1, 1, 0, 0), extra={}, error=None, serialized={'lc': 1, 'type': 'constructor', 'id': ['langchain', 'output_parsers', 'list', 'CommaSeparatedListOutputParser'], 'kwargs': {}}, events=[{'name': 'start', 'time': FakeDatetime(2023, 1, 1, 0, 0)}, {'name': 'end', 'time': FakeDatetime(2023, 1, 1, 0, 0)}], inputs={'input': AIMessage(content='baz, qux', additional_kwargs={}, example=False)}, outputs={'output': ['baz', 'qux']}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=[], execution_order=None, child_execution_order=None, child_runs=[])]), ]) # --- +# name: test_each + ''' + { + "lc": 1, + "type": "constructor", + "id": [ + "langchain", + "schema", + "runnable", + "RunnableSequence" + ], + "kwargs": { + "first": { + "lc": 1, + "type": "constructor", + "id": [ + "langchain", + "prompts", + "chat", + "ChatPromptTemplate" + ], + "kwargs": { + "messages": [ + { + "lc": 1, + "type": "constructor", + "id": [ + "langchain", + "prompts", + "chat", + "SystemMessagePromptTemplate" + ], + "kwargs": { + "prompt": { + "lc": 1, + "type": "constructor", + "id": [ + "langchain", + "prompts", + "prompt", + "PromptTemplate" + ], + "kwargs": { + "input_variables": [], + "template": "You are a nice assistant.", + "template_format": "f-string", + "partial_variables": {} + } + } + } + }, + { + "lc": 1, + "type": "constructor", + "id": [ + "langchain", + "prompts", + "chat", + "HumanMessagePromptTemplate" + ], + "kwargs": { + "prompt": { + "lc": 1, + "type": "constructor", + "id": [ + "langchain", + "prompts", + "prompt", + "PromptTemplate" + ], + "kwargs": { + "input_variables": [ + "question" + ], + "template": "{question}", + "template_format": "f-string", + "partial_variables": {} + } + } + } + } + ], + "input_variables": [ + "question" + ] + } + }, + "middle": [ + { + "lc": 1, + "type": "not_implemented", + "id": [ + "langchain", + "llms", + "fake", + "FakeStreamingListLLM" + ] + }, + { + "lc": 1, + "type": "constructor", + "id": [ + "runnable", + "test_runnable", + "FakeSplitIntoListParser" + ], + "kwargs": {} + } + ], + "last": { + "lc": 1, + "type": "constructor", + "id": [ + "langchain", + "schema", + "runnable", + "RunnableEach" + ], + "kwargs": { + "bound": { + "lc": 1, + "type": "not_implemented", + "id": [ + "langchain", + "llms", + "fake", + "FakeStreamingListLLM" + ] + } + } + } + } + } + ''' +# --- # name: test_llm_with_fallbacks[llm_chain_with_fallbacks] ''' { diff --git a/libs/langchain/tests/unit_tests/schema/runnable/test_runnable.py b/libs/langchain/tests/unit_tests/schema/runnable/test_runnable.py index 7b80489243f..544b42da693 100644 --- a/libs/langchain/tests/unit_tests/schema/runnable/test_runnable.py +++ b/libs/langchain/tests/unit_tests/schema/runnable/test_runnable.py @@ -27,7 +27,7 @@ from langchain.schema.messages import ( HumanMessage, SystemMessage, ) -from langchain.schema.output_parser import StrOutputParser +from langchain.schema.output_parser import BaseOutputParser, StrOutputParser from langchain.schema.retriever import BaseRetriever from langchain.schema.runnable import ( RouterRunnable, @@ -171,11 +171,21 @@ async def test_default_method_implementations(mocker: MockerFixture) -> None: assert spy.call_args_list == [ mocker.call( "hello", - dict(metadata={"key": "value"}, tags=[], callbacks=None, _locals={}), + dict( + metadata={"key": "value"}, + tags=[], + callbacks=None, + _locals={}, + ), ), mocker.call( "wooorld", - dict(metadata={"key": "value"}, tags=[], callbacks=None, _locals={}), + dict( + metadata={"key": "value"}, + tags=[], + callbacks=None, + _locals={}, + ), ), ] @@ -1076,3 +1086,53 @@ async def test_llm_with_fallbacks( assert await runnable.abatch(["hi", "hey", "bye"]) == ["bar"] * 3 assert list(await runnable.ainvoke("hello")) == list("bar") assert dumps(runnable, pretty=True) == snapshot + + +class FakeSplitIntoListParser(BaseOutputParser[List[str]]): + """Parse the output of an LLM call to a comma-separated list.""" + + @property + def lc_serializable(self) -> bool: + return True + + def get_format_instructions(self) -> str: + return ( + "Your response should be a list of comma separated values, " + "eg: `foo, bar, baz`" + ) + + def parse(self, text: str) -> List[str]: + """Parse the output of an LLM call.""" + return text.strip().split(", ") + + +def test_each_simple() -> None: + """Test that each() works with a simple runnable.""" + parser = FakeSplitIntoListParser() + assert parser.invoke("first item, second item") == ["first item", "second item"] + assert parser.map().invoke(["a, b", "c"]) == [["a", "b"], ["c"]] + assert parser.map().map().invoke([["a, b", "c"], ["c, e"]]) == [ + [["a", "b"], ["c"]], + [["c", "e"]], + ] + + +def test_each(snapshot: SnapshotAssertion) -> None: + prompt = ( + SystemMessagePromptTemplate.from_template("You are a nice assistant.") + + "{question}" + ) + first_llm = FakeStreamingListLLM(responses=["first item, second item, third item"]) + parser = FakeSplitIntoListParser() + second_llm = FakeStreamingListLLM(responses=["this", "is", "a", "test"]) + + chain = prompt | first_llm | parser | second_llm.map() + + assert dumps(chain, pretty=True) == snapshot + output = chain.invoke({"question": "What up"}) + assert output == ["this", "is", "a"] + + assert (parser | second_llm.map()).invoke("first item, second item") == [ + "test", + "this", + ]