proposal (#14729)

libs/community/Makefile

@@ -41,7 +41,7 @@ lint lint_diff lint_package lint_tests:
 	poetry run ruff .
 	[ "$(PYTHON_FILES)" = "" ] || poetry run ruff format $(PYTHON_FILES) --diff
 	[ "$(PYTHON_FILES)" = "" ] || poetry run ruff --select I $(PYTHON_FILES)
-	[ "$(PYTHON_FILES)" = "" ] || mkdir -p $(MYPY_CACHE) || poetry run mypy $(PYTHON_FILES) --cache-dir $(MYPY_CACHE)
+	[ "$(PYTHON_FILES)" = "" ] || (mkdir -p $(MYPY_CACHE); poetry run mypy $(PYTHON_FILES) --cache-dir $(MYPY_CACHE))
 
 format format_diff:
 	poetry run ruff format $(PYTHON_FILES)

libs/community/langchain_community/callbacks/labelstudio_callback.py

@@ -2,7 +2,7 @@ import os
 import warnings
 from datetime import datetime
 from enum import Enum
-from typing import Any, Dict, List, Optional, Tuple, Union
+from typing import Any, Dict, List, Optional, Sequence, Tuple, Union
 from uuid import UUID
 
 from langchain_core.agents import AgentAction, AgentFinish
@@ -224,7 +224,7 @@ class LabelStudioCallbackHandler(BaseCallbackHandler):
             raise ValueError(error_message)
 
     def add_prompts_generations(
-        self, run_id: str, generations: List[List[Generation]]
+        self, run_id: str, generations: Sequence[Sequence[Generation]]
     ) -> None:
         # Create tasks in Label Studio
         tasks = []

libs/community/langchain_community/llms/vertexai.py

@@ -34,7 +34,6 @@ if TYPE_CHECKING:
 # This is for backwards compatibility
 # We can remove after `langchain` stops importing it
 _response_to_generation = None
-completion_with_retry = None
 stream_completion_with_retry = None
 
 

libs/core/Makefile

@@ -42,7 +42,7 @@ lint lint_diff lint_package lint_tests:
 	[ "$(PYTHON_FILES)" = "" ] || poetry run ruff format $(PYTHON_FILES) --diff
 	[ "$(PYTHON_FILES)" = "" ] || poetry run ruff --select I $(PYTHON_FILES)
 	[ "$(PYTHON_FILES)" = "" ] || poetry run mypy $(PYTHON_FILES)
-	[ "$(PYTHON_FILES)" = "" ] || mkdir $(MYPY_CACHE) || poetry run mypy $(PYTHON_FILES) --cache-dir $(MYPY_CACHE)
+	[ "$(PYTHON_FILES)" = "" ] || (mkdir -p $(MYPY_CACHE); poetry run mypy $(PYTHON_FILES) --cache-dir $(MYPY_CACHE))
 
 format format_diff:
 	poetry run ruff format $(PYTHON_FILES)

libs/core/langchain_core/language_models/chat_models.py

@@ -377,7 +377,10 @@ class BaseChatModel(BaseLanguageModel[BaseMessage], ABC):
                     run_managers[i].on_llm_error(e, response=LLMResult(generations=[]))
                 raise e
         flattened_outputs = [
-            LLMResult(generations=[res.generations], llm_output=res.llm_output)
+            LLMResult(
+                generations=[res.generations],
+                llm_output=res.llm_output,
+            )
             for res in results
         ]
         llm_output = self._combine_llm_outputs([res.llm_output for res in results])
@@ -425,7 +428,7 @@ class BaseChatModel(BaseLanguageModel[BaseMessage], ABC):
             batch_size=len(messages),
         )
 
-        results = await asyncio.gather(
+        results_and_exceptions = await asyncio.gather(
             *[
                 self._agenerate_with_cache(
                     m,
@@ -437,42 +440,29 @@ class BaseChatModel(BaseLanguageModel[BaseMessage], ABC):
             ],
             return_exceptions=True,
         )
-        exceptions = []
-        for i, res in enumerate(results):
-            if isinstance(res, BaseException):
-                if run_managers:
-                    await run_managers[i].on_llm_error(
-                        res, response=LLMResult(generations=[])
-                    )
-                exceptions.append(res)
-        if exceptions:
-            if run_managers:
-                await asyncio.gather(
-                    *[
-                        run_manager.on_llm_end(
-                            LLMResult(
-                                generations=[res.generations], llm_output=res.llm_output
-                            )
-                        )
-                        for run_manager, res in zip(run_managers, results)
-                        if not isinstance(res, Exception)
-                    ]
-                )
-            raise exceptions[0]
-        flattened_outputs = [
-            LLMResult(generations=[res.generations], llm_output=res.llm_output)
-            for res in results
-        ]
-        llm_output = self._combine_llm_outputs([res.llm_output for res in results])
-        generations = [res.generations for res in results]
-        output = LLMResult(generations=generations, llm_output=llm_output)
-        await asyncio.gather(
-            *[
-                run_manager.on_llm_end(flattened_output)
-                for run_manager, flattened_output in zip(
-                    run_managers, flattened_outputs
+        # report results and errors
+        if run_managers:
+            jobs = [
+                run_manager.on_llm_error(res, response=LLMResult(generations=[]))
+                if isinstance(res, BaseException)
+                else run_manager.on_llm_end(
+                    LLMResult(generations=[res.generations], llm_output=res.llm_output)
                 )
+                for run_manager, res in zip(run_managers, results_and_exceptions)
             ]
+            await asyncio.gather(*jobs)
+
+        # raise first exception, if any
+        for res in results_and_exceptions:
+            if isinstance(res, BaseException):
+                raise res
+
+        # compute return value
+        results = cast(List[ChatResult], results_and_exceptions)
+
+        output = LLMResult(
+            generations=[res.generations for res in results],
+            llm_output=self._combine_llm_outputs([res.llm_output for res in results]),
         )
         if run_managers:
             output.run = [

libs/core/langchain_core/language_models/llms.py

@@ -143,7 +143,7 @@ def update_cache(
     """Update the cache and get the LLM output."""
     llm_cache = get_llm_cache()
     for i, result in enumerate(new_results.generations):
-        existing_prompts[missing_prompt_idxs[i]] = result
+        existing_prompts[missing_prompt_idxs[i]] = list(result)
         prompt = prompts[missing_prompt_idxs[i]]
         if llm_cache is not None:
             llm_cache.update(prompt, llm_string, result)
@@ -819,7 +819,7 @@ class BaseLLM(BaseLanguageModel[str], ABC):
                 raise ValueError(
                     "Asked to cache, but no cache found at `langchain.cache`."
                 )
-            run_managers = await asyncio.gather(
+            run_managers_gather = await asyncio.gather(
                 *[
                     callback_manager.on_llm_start(
                         dumpd(self),
@@ -834,13 +834,13 @@ class BaseLLM(BaseLanguageModel[str], ABC):
                     )
                 ]
             )
-            run_managers = [r[0] for r in run_managers]
+            run_managers = [r[0] for r in run_managers_gather]
             output = await self._agenerate_helper(
                 prompts, stop, run_managers, bool(new_arg_supported), **kwargs
             )
             return output
         if len(missing_prompts) > 0:
-            run_managers = await asyncio.gather(
+            run_managers_gather = await asyncio.gather(
                 *[
                     callback_managers[idx].on_llm_start(
                         dumpd(self),
@@ -853,7 +853,7 @@ class BaseLLM(BaseLanguageModel[str], ABC):
                     for idx in missing_prompt_idxs
                 ]
             )
-            run_managers = [r[0] for r in run_managers]
+            run_managers = [r[0] for r in run_managers_gather]
             new_results = await self._agenerate_helper(
                 missing_prompts, stop, run_managers, bool(new_arg_supported), **kwargs
             )

libs/core/langchain_core/messages/base.py

@@ -39,7 +39,7 @@ class BaseMessage(Serializable):
     def __add__(self, other: Any) -> ChatPromptTemplate:
         from langchain_core.prompts.chat import ChatPromptTemplate
 
-        prompt = ChatPromptTemplate(messages=[self])
+        prompt = ChatPromptTemplate(messages=[self], input_variables=[])
         return prompt + other
 
 
@@ -136,6 +136,7 @@ class BaseMessageChunk(BaseMessage):
                 additional_kwargs=self._merge_kwargs_dict(
                     self.additional_kwargs, other.additional_kwargs
                 ),
+                type=self.type,
             )
         else:
             raise TypeError(

libs/core/langchain_core/output_parsers/base.py

@@ -8,8 +8,8 @@ from typing import (
     Any,
     Dict,
     Generic,
-    List,
     Optional,
+    Sequence,
     Type,
     TypeVar,
     Union,
@@ -31,7 +31,7 @@ class BaseLLMOutputParser(Generic[T], ABC):
     """Abstract base class for parsing the outputs of a model."""
 
     @abstractmethod
-    def parse_result(self, result: List[Generation], *, partial: bool = False) -> T:
+    def parse_result(self, result: Sequence[Generation], *, partial: bool = False) -> T:
         """Parse a list of candidate model Generations into a specific format.
 
         Args:
@@ -43,7 +43,7 @@ class BaseLLMOutputParser(Generic[T], ABC):
         """
 
     async def aparse_result(
-        self, result: List[Generation], *, partial: bool = False
+        self, result: Sequence[Generation], *, partial: bool = False
     ) -> T:
         """Parse a list of candidate model Generations into a specific format.
 
@@ -206,7 +206,7 @@ class BaseOutputParser(
                 run_type="parser",
             )
 
-    def parse_result(self, result: List[Generation], *, partial: bool = False) -> T:
+    def parse_result(self, result: Sequence[Generation], *, partial: bool = False) -> T:
         """Parse a list of candidate model Generations into a specific format.
 
         The return value is parsed from only the first Generation in the result, which
@@ -233,7 +233,7 @@ class BaseOutputParser(
         """
 
     async def aparse_result(
-        self, result: List[Generation], *, partial: bool = False
+        self, result: Sequence[Generation], *, partial: bool = False
     ) -> T:
         """Parse a list of candidate model Generations into a specific format.
 

libs/core/langchain_core/outputs/chat_generation.py

@@ -18,7 +18,7 @@ class ChatGeneration(Generation):
     type: Literal["ChatGeneration"] = "ChatGeneration"  # type: ignore[assignment]
     """Type is used exclusively for serialization purposes."""
 
-    @root_validator
+    @root_validator()
     def set_text(cls, values: Dict[str, Any]) -> Dict[str, Any]:
         """Set the text attribute to be the contents of the message."""
         try:

libs/core/langchain_core/outputs/chat_result.py

@@ -1,15 +1,20 @@
-from typing import List, Optional
+from typing import Optional, Sequence
 
 from langchain_core.outputs.chat_generation import ChatGeneration
-from langchain_core.pydantic_v1 import BaseModel
+from langchain_core.pydantic_v1 import BaseModel, root_validator
 
 
 class ChatResult(BaseModel):
     """Class that contains all results for a single chat model call."""
 
-    generations: List[ChatGeneration]
+    generations: Sequence[ChatGeneration]
     """List of the chat generations. This is a List because an input can have multiple 
         candidate generations.
     """
     llm_output: Optional[dict] = None
     """For arbitrary LLM provider specific output."""
+
+    @root_validator(pre=True)
+    def validate_environment(cls, values: dict) -> dict:
+        values["generations"] = list(values.get("generations", ()))
+        return values

libs/core/langchain_core/outputs/llm_result.py

@@ -1,17 +1,17 @@
 from __future__ import annotations
 
 from copy import deepcopy
-from typing import List, Optional
+from typing import List, Optional, Sequence
 
 from langchain_core.outputs.generation import Generation
 from langchain_core.outputs.run_info import RunInfo
-from langchain_core.pydantic_v1 import BaseModel
+from langchain_core.pydantic_v1 import BaseModel, root_validator
 
 
 class LLMResult(BaseModel):
     """Class that contains all results for a batched LLM call."""
 
-    generations: List[List[Generation]]
+    generations: Sequence[Sequence[Generation]]
     """List of generated outputs. This is a List[List[]] because
     each input could have multiple candidate generations."""
     llm_output: Optional[dict] = None
@@ -19,6 +19,11 @@ class LLMResult(BaseModel):
     run: Optional[List[RunInfo]] = None
     """List of metadata info for model call for each input."""
 
+    @root_validator(pre=True)
+    def validate_environment(cls, values: dict) -> dict:
+        values["generations"] = [list(g) for g in values.get("generations", ())]
+        return values
+
     def flatten(self) -> List[LLMResult]:
         """Flatten generations into a single list.
 

libs/core/langchain_core/prompts/base.py

@@ -40,7 +40,7 @@ class BasePromptTemplate(RunnableSerializable[Dict, PromptValue], ABC):
     If not provided, all variables are assumed to be strings."""
     output_parser: Optional[BaseOutputParser] = None
     """How to parse the output of calling an LLM on this formatted prompt."""
-    partial_variables: Mapping[str, Union[str, Callable[[], str]]] = Field(
+    partial_variables: Mapping[str, Union[Any, Callable[[], Any]]] = Field(
         default_factory=dict
     )
 
@@ -137,8 +137,7 @@ class BasePromptTemplate(RunnableSerializable[Dict, PromptValue], ABC):
     def _merge_partial_and_user_variables(self, **kwargs: Any) -> Dict[str, Any]:
         # Get partial params:
         partial_kwargs = {
-            k: v if isinstance(v, str) else v()
-            for k, v in self.partial_variables.items()
+            k: v() if callable(v) else v for k, v in self.partial_variables.items()
         }
         return {**partial_kwargs, **kwargs}
 

libs/core/langchain_core/prompts/chat.py

@@ -8,6 +8,7 @@ from typing import (
     Callable,
     Dict,
     List,
+    Literal,
     Optional,
     Sequence,
     Set,
@@ -151,7 +152,7 @@ class BaseStringMessagePromptTemplate(BaseMessagePromptTemplate, ABC):
     def from_template(
         cls: Type[MessagePromptTemplateT],
         template: str,
-        template_format: str = "f-string",
+        template_format: Literal["f-string", "jinja2"] = "f-string",
         partial_variables: Optional[Dict[str, Any]] = None,
         **kwargs: Any,
     ) -> MessagePromptTemplateT:
@@ -396,9 +397,9 @@ class ChatPromptTemplate(BaseChatPromptTemplate):
             )
     """
 
-    input_variables: List[str]
+    input_variables: List[str] = Field(default_factory=list)
     """List of input variables in template messages. Used for validation."""
-    messages: List[MessageLike]
+    messages: Sequence[MessageLike]
     """List of messages consisting of either message prompt templates or messages."""
     validate_template: bool = False
     """Whether or not to try validating the template."""
@@ -418,18 +419,19 @@ class ChatPromptTemplate(BaseChatPromptTemplate):
             Combined prompt template.
         """
         # Allow for easy combining
+        messages = list(self.messages)
         if isinstance(other, ChatPromptTemplate):
-            return ChatPromptTemplate(messages=self.messages + other.messages)
+            return ChatPromptTemplate(messages=messages + list(other.messages))
         elif isinstance(
             other, (BaseMessagePromptTemplate, BaseMessage, BaseChatPromptTemplate)
         ):
-            return ChatPromptTemplate(messages=self.messages + [other])
+            return ChatPromptTemplate(messages=messages + [other])
         elif isinstance(other, (list, tuple)):
             _other = ChatPromptTemplate.from_messages(other)
-            return ChatPromptTemplate(messages=self.messages + _other.messages)
+            return ChatPromptTemplate(messages=messages + list(_other.messages))
         elif isinstance(other, str):
             prompt = HumanMessagePromptTemplate.from_template(other)
-            return ChatPromptTemplate(messages=self.messages + [prompt])
+            return ChatPromptTemplate(messages=messages + [prompt])
         else:
             raise NotImplementedError(f"Unsupported operand type for +: {type(other)}")
 
@@ -446,7 +448,7 @@ class ChatPromptTemplate(BaseChatPromptTemplate):
         Returns:
             Validated values.
         """
-        messages = values["messages"]
+        messages = list(values["messages"])
         input_vars = set()
         input_types: Dict[str, Any] = values.get("input_types", {})
         for message in messages:
@@ -656,11 +658,13 @@ class ChatPromptTemplate(BaseChatPromptTemplate):
         Args:
             message: representation of a message to append.
         """
-        self.messages.append(_convert_to_message(message))
+        self.messages = list(self.messages) + [_convert_to_message(message)]
 
     def extend(self, messages: Sequence[MessageLikeRepresentation]) -> None:
         """Extend the chat template with a sequence of messages."""
-        self.messages.extend([_convert_to_message(message) for message in messages])
+        self.messages = list(self.messages) + [
+            _convert_to_message(message) for message in messages
+        ]
 
     @overload
     def __getitem__(self, index: int) -> MessageLike:

libs/core/langchain_core/prompts/pipeline.py

@@ -3,7 +3,7 @@ from typing import Any, Dict, List, Tuple
 from langchain_core.prompt_values import PromptValue
 from langchain_core.prompts.base import BasePromptTemplate
 from langchain_core.prompts.chat import BaseChatPromptTemplate
-from langchain_core.pydantic_v1 import root_validator
+from langchain_core.pydantic_v1 import Field, root_validator
 
 
 def _get_inputs(inputs: dict, input_variables: List[str]) -> dict:
@@ -27,6 +27,8 @@ class PipelinePromptTemplate(BasePromptTemplate):
     """The final prompt that is returned."""
     pipeline_prompts: List[Tuple[str, BasePromptTemplate]]
     """A list of tuples, consisting of a string (`name`) and a Prompt Template."""
+    input_variables: List[str] = Field(default_factory=list)
+    """A list of the names of the variables the prompt template expects."""
 
     @classmethod
     def get_lc_namespace(cls) -> List[str]:

libs/core/langchain_core/prompts/prompt.py

@@ -212,7 +212,7 @@ class PromptTemplate(StringPromptTemplate):
         cls,
         template: str,
         *,
-        template_format: str = "f-string",
+        template_format: Literal["f-string", "jinja2"] = "f-string",
         partial_variables: Optional[Dict[str, Any]] = None,
         **kwargs: Any,
     ) -> PromptTemplate:

libs/core/langchain_core/runnables/base.py

@@ -2245,12 +2245,12 @@ class RunnableGenerator(Runnable[Input, Output]):
         ] = None,
     ) -> None:
         if atransform is not None:
-            self._atransform = atransform
+            self._atransform: Callable = atransform
 
         if inspect.isasyncgenfunction(transform):
             self._atransform = transform
         elif inspect.isgeneratorfunction(transform):
-            self._transform = transform
+            self._transform: Callable = transform
         else:
             raise TypeError(
                 "Expected a generator function type for `transform`."

libs/core/langchain_core/runnables/configurable.py

@@ -382,6 +382,7 @@ class RunnableConfigurableAlternatives(DynamicRunnable[Input, Output]):
             which=self.which,
             default=self.default.configurable_fields(**kwargs),
             alternatives=self.alternatives,
+            prefix_keys=self.prefix_keys,
         )
 
     def _prepare(

libs/core/langchain_core/tools.py

@@ -7,7 +7,18 @@ import warnings
 from abc import abstractmethod
 from functools import partial
 from inspect import signature
-from typing import Any, Awaitable, Callable, Dict, List, Optional, Tuple, Type, Union
+from typing import (
+    Any,
+    Awaitable,
+    Callable,
+    Dict,
+    List,
+    Optional,
+    Tuple,
+    Type,
+    Union,
+    cast,
+)
 
 from langchain_core.callbacks import (
     AsyncCallbackManager,
@@ -547,7 +558,8 @@ class Tool(BaseTool):
         self, name: str, func: Optional[Callable], description: str, **kwargs: Any
     ) -> None:
         """Initialize tool."""
-        super(Tool, self).__init__(
+        # TODO: fix typing issue
+        super(Tool, self).__init__(  # type: ignore[call-arg]
             name=name, func=func, description=description, **kwargs
         )
 
@@ -722,7 +734,7 @@ class StructuredTool(BaseTool):
             name=name,
             func=func,
             coroutine=coroutine,
-            args_schema=_args_schema,
+            args_schema=cast(Type[BaseModel], _args_schema),
             description=description,
             return_direct=return_direct,
             **kwargs,

libs/core/langchain_core/tracers/base.py

@@ -133,7 +133,7 @@ class BaseTracer(BaseCallbackHandler, ABC):
             child_execution_order=execution_order,
             run_type="llm",
             tags=tags or [],
-            name=name,
+            name=name,  # type: ignore[arg-type]  # TODO: Fix typing
         )
         self._start_trace(llm_run)
         self._on_llm_start(llm_run)
@@ -258,7 +258,7 @@ class BaseTracer(BaseCallbackHandler, ABC):
             child_execution_order=execution_order,
             child_runs=[],
             run_type=run_type or "chain",
-            name=name,
+            name=name,  # type: ignore[arg-type]  # TODO: fix typing
             tags=tags or [],
         )
         self._start_trace(chain_run)
@@ -336,7 +336,7 @@ class BaseTracer(BaseCallbackHandler, ABC):
             child_runs=[],
             run_type="tool",
             tags=tags or [],
-            name=name,
+            name=name,  # type: ignore[arg-type]  # TODO: fix typing
         )
         self._start_trace(tool_run)
         self._on_tool_start(tool_run)

libs/core/langchain_core/tracers/langchain.py

@@ -131,7 +131,7 @@ class LangChainTracer(BaseTracer):
             child_execution_order=execution_order,
             run_type="llm",
             tags=tags,
-            name=name,
+            name=name,  # type: ignore[arg-type]  # TODO: fix typing
         )
         self._start_trace(chat_model_run)
         self._on_chat_model_start(chat_model_run)

libs/core/langchain_core/tracers/langchain_v1.py

@@ -1,8 +1,9 @@
 from __future__ import annotations
 
+import datetime
 import logging
 import os
-from typing import Any, Dict, Optional, Union
+from typing import Any, Dict, Optional, Union, cast
 
 import requests
 
@@ -60,29 +61,30 @@ class LangChainTracerV1(BaseTracer):
             else:
                 raise ValueError("No prompts found in LLM run inputs")
             return LLMRun(
-                uuid=str(run.id) if run.id else None,
+                uuid=str(run.id) if run.id else "",
                 parent_uuid=str(run.parent_run_id) if run.parent_run_id else None,
                 start_time=run.start_time,
-                end_time=run.end_time,
+                end_time=cast(datetime.datetime, run.end_time),
                 extra=run.extra,
                 execution_order=run.execution_order,
                 child_execution_order=run.child_execution_order,
-                serialized=run.serialized,
+                serialized=run.serialized or {},
                 session_id=session.id,
                 error=run.error,
                 prompts=prompts,
-                response=run.outputs if run.outputs else None,
+                # TODO: Fix type error.
+                response=run.outputs if run.outputs else None,  # type: ignore[arg-type]
             )
         if run.run_type == "chain":
             child_runs = [self._convert_to_v1_run(run) for run in run.child_runs]
             return ChainRun(
-                uuid=str(run.id) if run.id else None,
+                uuid=str(run.id) if run.id else "",
                 parent_uuid=str(run.parent_run_id) if run.parent_run_id else None,
                 start_time=run.start_time,
-                end_time=run.end_time,
+                end_time=cast(datetime.datetime, run.end_time),
                 execution_order=run.execution_order,
                 child_execution_order=run.child_execution_order,
-                serialized=run.serialized,
+                serialized=run.serialized or {},
                 session_id=session.id,
                 inputs=run.inputs,
                 outputs=run.outputs,
@@ -97,13 +99,13 @@ class LangChainTracerV1(BaseTracer):
         if run.run_type == "tool":
             child_runs = [self._convert_to_v1_run(run) for run in run.child_runs]
             return ToolRun(
-                uuid=str(run.id) if run.id else None,
+                uuid=str(run.id) if run.id else "",
                 parent_uuid=str(run.parent_run_id) if run.parent_run_id else None,
                 start_time=run.start_time,
-                end_time=run.end_time,
+                end_time=cast(datetime.datetime, run.end_time),
                 execution_order=run.execution_order,
                 child_execution_order=run.child_execution_order,
-                serialized=run.serialized,
+                serialized=run.serialized or {},
                 session_id=session.id,
                 action=str(run.serialized),
                 tool_input=run.inputs.get("input", ""),

libs/core/langchain_core/utils/formatting.py

@@ -8,7 +8,7 @@ class StrictFormatter(Formatter):
 
     def check_unused_args(
         self,
-        used_args: Sequence[Union[int, str]],
+        used_args: Sequence[Union[int, str]],  # type: ignore[override]  # TODO: fix
         args: Sequence,
         kwargs: Mapping[str, Any],
     ) -> None:

libs/core/poetry.lock

@@ -1216,52 +1216,49 @@ files = [
 
 [[package]]
 name = "mypy"
-version = "0.991"
+version = "1.7.1"
 description = "Optional static typing for Python"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
-mypy-extensions = ">=0.4.3"
+mypy-extensions = ">=1.0.0"
 tomli = {version = ">=1.1.0", markers = "python_version < \"3.11\""}
-typing-extensions = ">=3.10"
+typing-extensions = ">=4.1.0"
 
 [package.extras]
 dmypy = ["psutil (>=4.0)"]
 install-types = ["pip"]
-python2 = ["typed-ast (>=1.4.0,<2)"]
+mypyc = ["setuptools (>=50)"]
 reports = ["lxml"]
 
 [[package]]
@@ -2287,28 +2284,28 @@ files = [
 
 [[package]]
 name = "ruff"
-version = "0.1.6"
+version = "0.1.8"
 description = "An extremely fast Python linter and code formatter, written in Rust."
 optional = false
 python-versions = ">=3.7"
 files = [
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+    {file = "ruff-0.1.8.tar.gz", hash = "sha256:f7ee467677467526cfe135eab86a40a0e8db43117936ac4f9b469ce9cdb3fb62"},
 ]
 
 [[package]]
@@ -2734,4 +2731,4 @@ extended-testing = ["jinja2"]
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.8.1,<4.0"
-content-hash = "64fa7ef31713835d12d5213f04b52adf7423299d023f9558b8b4e65ce1e5262f"
+content-hash = "ef8b5b1a303d9cd9b5740991c9ae5d37727663548373324565312a1d33cfda5b"

libs/core/pyproject.toml

@@ -24,15 +24,15 @@ jinja2 = {version = "^3", optional = true}
 optional = true
 
 [tool.poetry.group.lint.dependencies]
-ruff = "^0.1.5"
+ruff = "^0.1.8"
 
 [tool.poetry.group.typing]
 optional = true
 
 [tool.poetry.group.typing.dependencies]
-mypy = "^0.991"
-types-pyyaml = "^6.0.12.2"
-types-requests = "^2.28.11.5"
+mypy = "^1.7.1"
+types-pyyaml = ">=5.3"
+types-requests = "^2"
 types-jinja2 = "^2.11.9"
 
 [tool.poetry.group.dev]

libs/core/tests/unit_tests/prompts/test_prompt.py

@@ -118,8 +118,11 @@ def test_prompt_invalid_template_format() -> None:
     template = "This is a {foo} test."
     input_variables = ["foo"]
     with pytest.raises(ValueError):
+        # Intentional bad argument.
         PromptTemplate(
-            input_variables=input_variables, template=template, template_format="bar"
+            input_variables=input_variables,
+            template=template,
+            template_format="bar",  # type: ignore[arg-type]
         )
 
 

libs/langchain/Makefile

@@ -62,7 +62,7 @@ lint lint_diff lint_package lint_tests:
 	poetry run ruff .
 	[ "$(PYTHON_FILES)" = "" ] || poetry run ruff format $(PYTHON_FILES) --diff
 	[ "$(PYTHON_FILES)" = "" ] || poetry run ruff --select I $(PYTHON_FILES)
-	[ "$(PYTHON_FILES)" = "" ] || mkdir $(MYPY_CACHE) || poetry run mypy $(PYTHON_FILES) --cache-dir $(MYPY_CACHE)
+	[ "$(PYTHON_FILES)" = "" ] || (mkdir -p $(MYPY_CACHE); poetry run mypy $(PYTHON_FILES) --cache-dir $(MYPY_CACHE))
 
 format format_diff:
 	[ "$(PYTHON_FILES)" = "" ] || poetry run ruff format $(PYTHON_FILES)

libs/langchain/langchain/agents/output_parsers/openai_functions.py

@@ -1,7 +1,7 @@
 import asyncio
 import json
 from json import JSONDecodeError
-from typing import List, Union
+from typing import Sequence, Union
 
 from langchain_core.agents import AgentAction, AgentActionMessageLog, AgentFinish
 from langchain_core.exceptions import OutputParserException
@@ -78,7 +78,7 @@ class OpenAIFunctionsAgentOutputParser(AgentOutputParser):
         )
 
     def parse_result(
-        self, result: List[Generation], *, partial: bool = False
+        self, result: Sequence[Generation], *, partial: bool = False
     ) -> Union[AgentAction, AgentFinish]:
         if not isinstance(result[0], ChatGeneration):
             raise ValueError("This output parser only works on ChatGeneration output")
@@ -86,7 +86,7 @@ class OpenAIFunctionsAgentOutputParser(AgentOutputParser):
         return self._parse_ai_message(message)
 
     async def aparse_result(
-        self, result: List[Generation], *, partial: bool = False
+        self, result: Sequence[Generation], *, partial: bool = False
     ) -> Union[AgentAction, AgentFinish]:
         return await asyncio.get_running_loop().run_in_executor(
             None, self.parse_result, result

libs/langchain/langchain/agents/output_parsers/openai_tools.py

@@ -1,7 +1,7 @@
 import asyncio
 import json
 from json import JSONDecodeError
-from typing import List, Union
+from typing import List, Sequence, Union
 
 from langchain_core.agents import AgentAction, AgentActionMessageLog, AgentFinish
 from langchain_core.exceptions import OutputParserException
@@ -85,7 +85,7 @@ class OpenAIToolsAgentOutputParser(MultiActionAgentOutputParser):
         return "openai-tools-agent-output-parser"
 
     def parse_result(
-        self, result: List[Generation], *, partial: bool = False
+        self, result: Sequence[Generation], *, partial: bool = False
     ) -> Union[List[AgentAction], AgentFinish]:
         if not isinstance(result[0], ChatGeneration):
             raise ValueError("This output parser only works on ChatGeneration output")
@@ -93,7 +93,7 @@ class OpenAIToolsAgentOutputParser(MultiActionAgentOutputParser):
         return parse_ai_message_to_openai_tool_action(message)
 
     async def aparse_result(
-        self, result: List[Generation], *, partial: bool = False
+        self, result: Sequence[Generation], *, partial: bool = False
     ) -> Union[List[AgentAction], AgentFinish]:
         return await asyncio.get_running_loop().run_in_executor(
             None, self.parse_result, result

libs/langchain/langchain/chains/flare/base.py

@@ -48,7 +48,7 @@ class _ResponseChain(LLMChain):
 
     @abstractmethod
     def _extract_tokens_and_log_probs(
-        self, generations: List[Generation]
+        self, generations: Sequence[Generation]
     ) -> Tuple[Sequence[str], Sequence[float]]:
         """Extract tokens and log probs from response."""
 
@@ -63,7 +63,7 @@ class _OpenAIResponseChain(_ResponseChain):
     )
 
     def _extract_tokens_and_log_probs(
-        self, generations: List[Generation]
+        self, generations: Sequence[Generation]
     ) -> Tuple[Sequence[str], Sequence[float]]:
         tokens = []
         log_probs = []

libs/langchain/langchain/output_parsers/ernie_functions.py

@@ -1,6 +1,6 @@
 import copy
 import json
-from typing import Any, Dict, List, Optional, Type, Union
+from typing import Any, Dict, Optional, Sequence, Type, Union
 
 import jsonpatch
 
@@ -23,7 +23,9 @@ class OutputFunctionsParser(BaseGenerationOutputParser[Any]):
     args_only: bool = True
     """Whether to only return the arguments to the function call."""
 
-    def parse_result(self, result: List[Generation], *, partial: bool = False) -> Any:
+    def parse_result(
+        self, result: Sequence[Generation], *, partial: bool = False
+    ) -> Any:
         generation = result[0]
         if not isinstance(generation, ChatGeneration):
             raise OutputParserException(
@@ -61,7 +63,9 @@ class JsonOutputFunctionsParser(BaseCumulativeTransformOutputParser[Any]):
     def _diff(self, prev: Optional[Any], next: Any) -> Any:
         return jsonpatch.make_patch(prev, next).patch
 
-    def parse_result(self, result: List[Generation], *, partial: bool = False) -> Any:
+    def parse_result(
+        self, result: Sequence[Generation], *, partial: bool = False
+    ) -> Any:
         if len(result) != 1:
             raise OutputParserException(
                 f"Expected exactly one result, but got {len(result)}"
@@ -131,7 +135,9 @@ class JsonKeyOutputFunctionsParser(JsonOutputFunctionsParser):
     key_name: str
     """The name of the key to return."""
 
-    def parse_result(self, result: List[Generation], *, partial: bool = False) -> Any:
+    def parse_result(
+        self, result: Sequence[Generation], *, partial: bool = False
+    ) -> Any:
         res = super().parse_result(result, partial=partial)
         if partial and res is None:
             return None
@@ -158,7 +164,9 @@ class PydanticOutputFunctionsParser(OutputFunctionsParser):
             )
         return values
 
-    def parse_result(self, result: List[Generation], *, partial: bool = False) -> Any:
+    def parse_result(
+        self, result: Sequence[Generation], *, partial: bool = False
+    ) -> Any:
         _result = super().parse_result(result)
         if self.args_only:
             pydantic_args = self.pydantic_schema.parse_raw(_result)  # type: ignore
@@ -175,6 +183,8 @@ class PydanticAttrOutputFunctionsParser(PydanticOutputFunctionsParser):
     attr_name: str
     """The name of the attribute to return."""
 
-    def parse_result(self, result: List[Generation], *, partial: bool = False) -> Any:
+    def parse_result(
+        self, result: Sequence[Generation], *, partial: bool = False
+    ) -> Any:
         result = super().parse_result(result)
         return getattr(result, self.attr_name)

libs/langchain/langchain/output_parsers/openai_functions.py

@@ -1,6 +1,6 @@
 import copy
 import json
-from typing import Any, Dict, List, Optional, Type, Union
+from typing import Any, Dict, Optional, Sequence, Type, Union
 
 import jsonpatch
 from langchain_core.exceptions import OutputParserException
@@ -20,7 +20,9 @@ class OutputFunctionsParser(BaseGenerationOutputParser[Any]):
     args_only: bool = True
     """Whether to only return the arguments to the function call."""
 
-    def parse_result(self, result: List[Generation], *, partial: bool = False) -> Any:
+    def parse_result(
+        self, result: Sequence[Generation], *, partial: bool = False
+    ) -> Any:
         generation = result[0]
         if not isinstance(generation, ChatGeneration):
             raise OutputParserException(
@@ -58,7 +60,9 @@ class JsonOutputFunctionsParser(BaseCumulativeTransformOutputParser[Any]):
     def _diff(self, prev: Optional[Any], next: Any) -> Any:
         return jsonpatch.make_patch(prev, next).patch
 
-    def parse_result(self, result: List[Generation], *, partial: bool = False) -> Any:
+    def parse_result(
+        self, result: Sequence[Generation], *, partial: bool = False
+    ) -> Any:
         if len(result) != 1:
             raise OutputParserException(
                 f"Expected exactly one result, but got {len(result)}"
@@ -126,7 +130,9 @@ class JsonKeyOutputFunctionsParser(JsonOutputFunctionsParser):
     key_name: str
     """The name of the key to return."""
 
-    def parse_result(self, result: List[Generation], *, partial: bool = False) -> Any:
+    def parse_result(
+        self, result: Sequence[Generation], *, partial: bool = False
+    ) -> Any:
         res = super().parse_result(result, partial=partial)
         if partial and res is None:
             return None
@@ -153,7 +159,9 @@ class PydanticOutputFunctionsParser(OutputFunctionsParser):
             )
         return values
 
-    def parse_result(self, result: List[Generation], *, partial: bool = False) -> Any:
+    def parse_result(
+        self, result: Sequence[Generation], *, partial: bool = False
+    ) -> Any:
         _result = super().parse_result(result)
         if self.args_only:
             pydantic_args = self.pydantic_schema.parse_raw(_result)  # type: ignore
@@ -170,6 +178,8 @@ class PydanticAttrOutputFunctionsParser(PydanticOutputFunctionsParser):
     attr_name: str
     """The name of the attribute to return."""
 
-    def parse_result(self, result: List[Generation], *, partial: bool = False) -> Any:
+    def parse_result(
+        self, result: Sequence[Generation], *, partial: bool = False
+    ) -> Any:
         result = super().parse_result(result)
         return getattr(result, self.attr_name)

libs/langchain/langchain/output_parsers/openai_tools.py

@@ -1,6 +1,6 @@
 import copy
 import json
-from typing import Any, List, Type
+from typing import Any, List, Sequence, Type
 
 from langchain_core.exceptions import OutputParserException
 from langchain_core.output_parsers import (
@@ -13,7 +13,9 @@ from langchain_core.pydantic_v1 import BaseModel
 class JsonOutputToolsParser(BaseGenerationOutputParser[Any]):
     """Parse tools from OpenAI response."""
 
-    def parse_result(self, result: List[Generation], *, partial: bool = False) -> Any:
+    def parse_result(
+        self, result: Sequence[Generation], *, partial: bool = False
+    ) -> Any:
         generation = result[0]
         if not isinstance(generation, ChatGeneration):
             raise OutputParserException(
@@ -45,7 +47,9 @@ class JsonOutputKeyToolsParser(JsonOutputToolsParser):
     key_name: str
     """The type of tools to return."""
 
-    def parse_result(self, result: List[Generation], *, partial: bool = False) -> Any:
+    def parse_result(
+        self, result: Sequence[Generation], *, partial: bool = False
+    ) -> Any:
         results = super().parse_result(result)
         return [res["args"] for res in results if results["type"] == self.key_name]
 
@@ -55,7 +59,9 @@ class PydanticToolsParser(JsonOutputToolsParser):
 
     tools: List[Type[BaseModel]]
 
-    def parse_result(self, result: List[Generation], *, partial: bool = False) -> Any:
+    def parse_result(
+        self, result: Sequence[Generation], *, partial: bool = False
+    ) -> Any:
         results = super().parse_result(result)
         name_dict = {tool.__name__: tool for tool in self.tools}
         return [name_dict[res["type"]](**res["args"]) for res in results]

libs/partners/google-genai/Makefile

@@ -36,7 +36,7 @@ lint lint_diff lint_package lint_tests:
 	./scripts/lint_imports.sh
 	poetry run ruff .
 	[ "$(PYTHON_FILES)" = "" ] || poetry run ruff format $(PYTHON_FILES) --diff
-	[ "$(PYTHON_FILES)" = "" ] || poetry run mypy $(PYTHON_FILES)
+	[ "$(PYTHON_FILES)" = "" ] || (mkdir -p $(MYPY_CACHE); poetry run mypy $(PYTHON_FILES) --cache-dir $(MYPY_CACHE))
 
 format format_diff:
 	poetry run ruff format $(PYTHON_FILES)