diff --git a/.github/workflows/langchain_ci.yml b/.github/workflows/langchain_ci.yml
index 7e486fffe19..134943f6c67 100644
--- a/.github/workflows/langchain_ci.yml
+++ b/.github/workflows/langchain_ci.yml
@@ -63,6 +63,46 @@ jobs:
       langchain-core-location: ../core
     secrets: inherit
 
+  # It's possible that langchain works fine with the latest *published* langchain-core,
+  # but is broken with the langchain-core on `master`.
+  #
+  # We want to catch situations like that *before* releasing a new langchain-core, hence this test.
+  test-with-latest-langchain-core:
+    runs-on: ubuntu-latest
+    defaults:
+      run:
+        working-directory: ${{ env.WORKDIR }}
+    strategy:
+      matrix:
+        python-version:
+          - "3.8"
+          - "3.9"
+          - "3.10"
+          - "3.11"
+    name: test with unpublished langchain-core - Python ${{ matrix.python-version }}
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Set up Python ${{ matrix.python-version }} + Poetry ${{ env.POETRY_VERSION }}
+        uses: "./.github/actions/poetry_setup"
+        with:
+          python-version: ${{ matrix.python-version }}
+          poetry-version: ${{ env.POETRY_VERSION }}
+          working-directory: ${{ env.WORKDIR }}
+          cache-key: unpublished-langchain-core
+
+      - name: Install dependencies
+        shell: bash
+        run: |
+          echo "Running tests with unpublished langchain, installing dependencies with poetry..."
+          poetry install
+
+          echo "Editably installing langchain-core outside of poetry, to avoid messing up lockfile..."
+          poetry run pip install -e ../core
+
+      - name: Run tests
+        run: make test
+
   extended-tests:
     runs-on: ubuntu-latest
     defaults:
diff --git a/libs/core/langchain_core/callbacks/__init__.py b/libs/core/langchain_core/callbacks/__init__.py
index e6da4809b4e..2b5eda2c141 100644
--- a/libs/core/langchain_core/callbacks/__init__.py
+++ b/libs/core/langchain_core/callbacks/__init__.py
@@ -28,8 +28,6 @@ from langchain_core.callbacks.manager import (
     CallbackManagerForToolRun,
     ParentRunManager,
     RunManager,
-    env_var_is_set,
-    register_configure_hook,
 )
 from langchain_core.callbacks.stdout import StdOutCallbackHandler
 from langchain_core.callbacks.streaming_stdout import StreamingStdOutCallbackHandler
@@ -64,6 +62,4 @@ __all__ = [
     "AsyncCallbackManagerForChainGroup",
     "StdOutCallbackHandler",
     "StreamingStdOutCallbackHandler",
-    "env_var_is_set",
-    "register_configure_hook",
 ]
diff --git a/libs/core/langchain_core/callbacks/manager.py b/libs/core/langchain_core/callbacks/manager.py
index 1ae22a703b7..4eb223d9cda 100644
--- a/libs/core/langchain_core/callbacks/manager.py
+++ b/libs/core/langchain_core/callbacks/manager.py
@@ -3,13 +3,10 @@ from __future__ import annotations
 import asyncio
 import functools
 import logging
-import os
 import uuid
 from concurrent.futures import ThreadPoolExecutor
 from contextlib import asynccontextmanager, contextmanager
-from contextvars import ContextVar
 from typing import (
-    TYPE_CHECKING,
     Any,
     AsyncGenerator,
     Coroutine,
@@ -18,7 +15,6 @@ from typing import (
     List,
     Optional,
     Sequence,
-    Tuple,
     Type,
     TypeVar,
     Union,
@@ -26,14 +22,10 @@ from typing import (
 )
 from uuid import UUID
 
-from langsmith import utils as ls_utils
 from langsmith.run_helpers import get_run_tree_context
 from tenacity import RetryCallState
 
-from langchain_core.agents import (
-    AgentAction,
-    AgentFinish,
-)
+from langchain_core.agents import AgentAction, AgentFinish
 from langchain_core.callbacks.base import (
     BaseCallbackHandler,
     BaseCallbackManager,
@@ -48,32 +40,10 @@ from langchain_core.callbacks.stdout import StdOutCallbackHandler
 from langchain_core.documents import Document
 from langchain_core.messages import BaseMessage, get_buffer_string
 from langchain_core.outputs import ChatGenerationChunk, GenerationChunk, LLMResult
-from langchain_core.tracers import run_collector
-from langchain_core.tracers.langchain import (
-    LangChainTracer,
-)
-from langchain_core.tracers.langchain_v1 import LangChainTracerV1
-from langchain_core.tracers.schemas import TracerSessionV1
-from langchain_core.tracers.stdout import ConsoleCallbackHandler
-
-if TYPE_CHECKING:
-    from langsmith import Client as LangSmithClient
+from langchain_core.utils.env import env_var_is_set
 
 logger = logging.getLogger(__name__)
 
-tracing_callback_var: ContextVar[Optional[LangChainTracerV1]] = ContextVar(  # noqa: E501
-    "tracing_callback", default=None
-)
-
-tracing_v2_callback_var: ContextVar[Optional[LangChainTracer]] = ContextVar(  # noqa: E501
-    "tracing_callback_v2", default=None
-)
-run_collector_var: ContextVar[
-    Optional[run_collector.RunCollectorCallbackHandler]
-] = ContextVar(  # noqa: E501
-    "run_collector", default=None
-)
-
 
 def _get_debug() -> bool:
     from langchain_core.globals import get_debug
@@ -81,123 +51,6 @@ def _get_debug() -> bool:
     return get_debug()
 
 
-@contextmanager
-def tracing_enabled(
-    session_name: str = "default",
-) -> Generator[TracerSessionV1, None, None]:
-    """Get the Deprecated LangChainTracer in a context manager.
-
-    Args:
-        session_name (str, optional): The name of the session.
-          Defaults to "default".
-
-    Returns:
-        TracerSessionV1: The LangChainTracer session.
-
-    Example:
-        >>> with tracing_enabled() as session:
-        ...     # Use the LangChainTracer session
-    """
-    cb = LangChainTracerV1()
-    session = cast(TracerSessionV1, cb.load_session(session_name))
-    try:
-        tracing_callback_var.set(cb)
-        yield session
-    finally:
-        tracing_callback_var.set(None)
-
-
-@contextmanager
-def tracing_v2_enabled(
-    project_name: Optional[str] = None,
-    *,
-    example_id: Optional[Union[str, UUID]] = None,
-    tags: Optional[List[str]] = None,
-    client: Optional[LangSmithClient] = None,
-) -> Generator[LangChainTracer, None, None]:
-    """Instruct LangChain to log all runs in context to LangSmith.
-
-    Args:
-        project_name (str, optional): The name of the project.
-            Defaults to "default".
-        example_id (str or UUID, optional): The ID of the example.
-            Defaults to None.
-        tags (List[str], optional): The tags to add to the run.
-            Defaults to None.
-
-    Returns:
-        None
-
-    Example:
-        >>> with tracing_v2_enabled():
-        ...     # LangChain code will automatically be traced
-
-        You can use this to fetch the LangSmith run URL:
-
-        >>> with tracing_v2_enabled() as cb:
-        ...     chain.invoke("foo")
-        ...     run_url = cb.get_run_url()
-    """
-    if isinstance(example_id, str):
-        example_id = UUID(example_id)
-    cb = LangChainTracer(
-        example_id=example_id,
-        project_name=project_name,
-        tags=tags,
-        client=client,
-    )
-    try:
-        tracing_v2_callback_var.set(cb)
-        yield cb
-    finally:
-        tracing_v2_callback_var.set(None)
-
-
-@contextmanager
-def collect_runs() -> Generator[run_collector.RunCollectorCallbackHandler, None, None]:
-    """Collect all run traces in context.
-
-    Returns:
-        run_collector.RunCollectorCallbackHandler: The run collector callback handler.
-
-    Example:
-        >>> with collect_runs() as runs_cb:
-                chain.invoke("foo")
-                run_id = runs_cb.traced_runs[0].id
-    """
-    cb = run_collector.RunCollectorCallbackHandler()
-    run_collector_var.set(cb)
-    yield cb
-    run_collector_var.set(None)
-
-
-def _get_trace_callbacks(
-    project_name: Optional[str] = None,
-    example_id: Optional[Union[str, UUID]] = None,
-    callback_manager: Optional[Union[CallbackManager, AsyncCallbackManager]] = None,
-) -> Callbacks:
-    if _tracing_v2_is_enabled():
-        project_name_ = project_name or _get_tracer_project()
-        tracer = tracing_v2_callback_var.get() or LangChainTracer(
-            project_name=project_name_,
-            example_id=example_id,
-        )
-        if callback_manager is None:
-            cb = cast(Callbacks, [tracer])
-        else:
-            if not any(
-                isinstance(handler, LangChainTracer)
-                for handler in callback_manager.handlers
-            ):
-                callback_manager.add_handler(tracer, True)
-                # If it already has a LangChainTracer, we don't need to add another one.
-                # this would likely mess up the trace hierarchy.
-            cb = callback_manager
-    else:
-        cb = None
-    return cb
-
-
 @contextmanager
 def trace_as_chain_group(
     group_name: str,
@@ -239,6 +92,8 @@ def trace_as_chain_group(
                 res = llm.predict(llm_input, callbacks=manager)
                 manager.on_chain_end({"output": res})
     """  # noqa: E501
+    from langchain_core.tracers.context import _get_trace_callbacks
+
     cb = _get_trace_callbacks(
         project_name, example_id, callback_manager=callback_manager
     )
@@ -310,6 +165,8 @@ async def atrace_as_chain_group(
                 res = await llm.apredict(llm_input, callbacks=manager)
                 await manager.on_chain_end({"output": res})
     """  # noqa: E501
+    from langchain_core.tracers.context import _get_trace_callbacks
+
     cb = _get_trace_callbacks(
         project_name, example_id, callback_manager=callback_manager
     )
@@ -1850,88 +1707,9 @@ class AsyncCallbackManagerForChainGroup(AsyncCallbackManager):
 T = TypeVar("T", CallbackManager, AsyncCallbackManager)
 
 
-def env_var_is_set(env_var: str) -> bool:
-    """Check if an environment variable is set.
-
-    Args:
-        env_var (str): The name of the environment variable.
-
-    Returns:
-        bool: True if the environment variable is set, False otherwise.
-    """
-    return env_var in os.environ and os.environ[env_var] not in (
-        "",
-        "0",
-        "false",
-        "False",
-    )
-
-
-def _tracing_v2_is_enabled() -> bool:
-    return (
-        env_var_is_set("LANGCHAIN_TRACING_V2")
-        or tracing_v2_callback_var.get() is not None
-        or get_run_tree_context() is not None
-    )
-
-
-def _get_tracer_project() -> str:
-    run_tree = get_run_tree_context()
-    return getattr(
-        run_tree,
-        "session_name",
-        getattr(
-            # Note, if people are trying to nest @traceable functions and the
-            # tracing_v2_enabled context manager, this will likely mess up the
-            # tree structure.
-            tracing_v2_callback_var.get(),
-            "project",
-            # Have to set this to a string even though it always will return
-            # a string because `get_tracer_project` technically can return
-            # None, but only when a specific argument is supplied.
-            # Therefore, this just tricks the mypy type checker
-            str(ls_utils.get_tracer_project()),
-        ),
-    )
-
-
-_configure_hooks: List[
-    Tuple[
-        ContextVar[Optional[BaseCallbackHandler]],
-        bool,
-        Optional[Type[BaseCallbackHandler]],
-        Optional[str],
-    ]
-] = []
-
 H = TypeVar("H", bound=BaseCallbackHandler, covariant=True)
 
 
-def register_configure_hook(
-    context_var: ContextVar[Optional[Any]],
-    inheritable: bool,
-    handle_class: Optional[Type[BaseCallbackHandler]] = None,
-    env_var: Optional[str] = None,
-) -> None:
-    if env_var is not None and handle_class is None:
-        raise ValueError(
-            "If env_var is set, handle_class must also be set to a non-None value."
-        )
-    _configure_hooks.append(
-        (
-            # the typings of ContextVar do not have the generic arg set as covariant
-            # so we have to cast it
-            cast(ContextVar[Optional[BaseCallbackHandler]], context_var),
-            inheritable,
-            handle_class,
-            env_var,
-        )
-    )
-
-
-register_configure_hook(run_collector_var, False)
-
-
 def _configure(
     callback_manager_cls: Type[T],
     inheritable_callbacks: Callbacks = None,
@@ -1962,6 +1740,14 @@ def _configure(
     Returns:
         T: The configured callback manager.
     """
+    from langchain_core.tracers.context import (
+        _configure_hooks,
+        _get_tracer_project,
+        _tracing_v2_is_enabled,
+        tracing_callback_var,
+        tracing_v2_callback_var,
+    )
+
     run_tree = get_run_tree_context()
     parent_run_id = None if run_tree is None else getattr(run_tree, "id")
     callback_manager = callback_manager_cls(handlers=[], parent_run_id=parent_run_id)
@@ -2009,6 +1795,10 @@ def _configure(
     tracer_project = _get_tracer_project()
     debug = _get_debug()
     if verbose or debug or tracing_enabled_ or tracing_v2_enabled_:
+        from langchain_core.tracers.langchain import LangChainTracer
+        from langchain_core.tracers.langchain_v1 import LangChainTracerV1
+        from langchain_core.tracers.stdout import ConsoleCallbackHandler
+
         if verbose and not any(
             isinstance(handler, StdOutCallbackHandler)
             for handler in callback_manager.handlers
diff --git a/libs/core/langchain_core/globals/__init__.py b/libs/core/langchain_core/globals/__init__.py
index 923de3c2e42..e6210d53ac8 100644
--- a/libs/core/langchain_core/globals/__init__.py
+++ b/libs/core/langchain_core/globals/__init__.py
@@ -19,7 +19,7 @@ _llm_cache: Optional["BaseCache"] = None
 def set_verbose(value: bool) -> None:
     """Set a new value for the `verbose` global setting."""
     try:
-        import langchain
+        import langchain  # type: ignore[import]
 
         # We're about to run some deprecated code, don't report warnings from it.
         # The user called the correct (non-deprecated) code path and shouldn't get warnings.
@@ -47,7 +47,7 @@ def set_verbose(value: bool) -> None:
 def get_verbose() -> bool:
     """Get the value of the `verbose` global setting."""
     try:
-        import langchain
+        import langchain  # type: ignore[import]
 
         # We're about to run some deprecated code, don't report warnings from it.
         # The user called the correct (non-deprecated) code path and shouldn't get warnings.
@@ -80,7 +80,7 @@ def get_verbose() -> bool:
 def set_debug(value: bool) -> None:
     """Set a new value for the `debug` global setting."""
     try:
-        import langchain
+        import langchain  # type: ignore[import]
 
         # We're about to run some deprecated code, don't report warnings from it.
         # The user called the correct (non-deprecated) code path and shouldn't get warnings.
@@ -106,7 +106,7 @@ def set_debug(value: bool) -> None:
 def get_debug() -> bool:
     """Get the value of the `debug` global setting."""
     try:
-        import langchain
+        import langchain  # type: ignore[import]
 
         # We're about to run some deprecated code, don't report warnings from it.
         # The user called the correct (non-deprecated) code path and shouldn't get warnings.
@@ -137,7 +137,7 @@ def get_debug() -> bool:
 def set_llm_cache(value: Optional["BaseCache"]) -> None:
     """Set a new LLM cache, overwriting the previous value, if any."""
     try:
-        import langchain
+        import langchain  # type: ignore[import]
 
         # We're about to run some deprecated code, don't report warnings from it.
         # The user called the correct (non-deprecated) code path and shouldn't get warnings.
@@ -165,7 +165,7 @@ def set_llm_cache(value: Optional["BaseCache"]) -> None:
 def get_llm_cache() -> "BaseCache":
     """Get the value of the `llm_cache` global setting."""
     try:
-        import langchain
+        import langchain  # type: ignore[import]
 
         # We're about to run some deprecated code, don't report warnings from it.
         # The user called the correct (non-deprecated) code path and shouldn't get warnings.
diff --git a/libs/core/langchain_core/language_models/__init__.py b/libs/core/langchain_core/language_models/__init__.py
index c83892a2e96..16fbe8a676f 100644
--- a/libs/core/langchain_core/language_models/__init__.py
+++ b/libs/core/langchain_core/language_models/__init__.py
@@ -1,4 +1,8 @@
-from langchain_core.language_models.base import BaseLanguageModel, LanguageModelInput
+from langchain_core.language_models.base import (
+    BaseLanguageModel,
+    LanguageModelInput,
+    get_tokenizer,
+)
 from langchain_core.language_models.chat_models import BaseChatModel, SimpleChatModel
 from langchain_core.language_models.llms import LLM, BaseLLM
 
@@ -9,4 +13,5 @@ __all__ = [
     "BaseLLM",
     "LLM",
     "LanguageModelInput",
+    "get_tokenizer",
 ]
diff --git a/libs/core/langchain_core/language_models/base.py b/libs/core/langchain_core/language_models/base.py
index b15e2166221..52bea1d4736 100644
--- a/libs/core/langchain_core/language_models/base.py
+++ b/libs/core/langchain_core/language_models/base.py
@@ -17,7 +17,7 @@ from typing_extensions import TypeAlias
 
 from langchain_core.messages import AnyMessage, BaseMessage, get_buffer_string
 from langchain_core.outputs import LLMResult
-from langchain_core.prompts import PromptValue
+from langchain_core.prompt_values import PromptValue
 from langchain_core.runnables import RunnableSerializable
 from langchain_core.utils import get_pydantic_field_names
 
@@ -28,7 +28,7 @@ if TYPE_CHECKING:
 @lru_cache(maxsize=None)  # Cache the tokenizer
 def get_tokenizer() -> Any:
     try:
-        from transformers import GPT2TokenizerFast
+        from transformers import GPT2TokenizerFast  # type: ignore[import]
     except ImportError:
         raise ImportError(
             "Could not import transformers python package. "
@@ -74,8 +74,10 @@ class BaseLanguageModel(
     @property
     def InputType(self) -> TypeAlias:
         """Get the input type for this runnable."""
-        from langchain_core.prompts.chat import ChatPromptValueConcrete
-        from langchain_core.prompts.string import StringPromptValue
+        from langchain_core.prompt_values import (
+            ChatPromptValueConcrete,
+            StringPromptValue,
+        )
 
         # This is a version of LanguageModelInput which replaces the abstract
         # base class BaseMessage with a union of its subclasses, which makes
diff --git a/libs/core/langchain_core/language_models/chat_models.py b/libs/core/langchain_core/language_models/chat_models.py
index 0a1b32e444e..f64131bf487 100644
--- a/libs/core/langchain_core/language_models/chat_models.py
+++ b/libs/core/langchain_core/language_models/chat_models.py
@@ -39,7 +39,7 @@ from langchain_core.outputs import (
     LLMResult,
     RunInfo,
 )
-from langchain_core.prompts import ChatPromptValue, PromptValue, StringPromptValue
+from langchain_core.prompt_values import ChatPromptValue, PromptValue, StringPromptValue
 from langchain_core.pydantic_v1 import Field, root_validator
 from langchain_core.runnables import RunnableConfig
 
diff --git a/libs/core/langchain_core/language_models/llms.py b/libs/core/langchain_core/language_models/llms.py
index eefa1d05173..f75eb67394f 100644
--- a/libs/core/langchain_core/language_models/llms.py
+++ b/libs/core/langchain_core/language_models/llms.py
@@ -50,7 +50,7 @@ from langchain_core.language_models.base import BaseLanguageModel, LanguageModel
 from langchain_core.load import dumpd
 from langchain_core.messages import AIMessage, BaseMessage, get_buffer_string
 from langchain_core.outputs import Generation, GenerationChunk, LLMResult, RunInfo
-from langchain_core.prompts import ChatPromptValue, PromptValue, StringPromptValue
+from langchain_core.prompt_values import ChatPromptValue, PromptValue, StringPromptValue
 from langchain_core.pydantic_v1 import Field, root_validator, validator
 from langchain_core.runnables import RunnableConfig, get_config_list
 
diff --git a/libs/core/langchain_core/output_parsers/__init__.py b/libs/core/langchain_core/output_parsers/__init__.py
index 72039737be8..1bed8f58298 100644
--- a/libs/core/langchain_core/output_parsers/__init__.py
+++ b/libs/core/langchain_core/output_parsers/__init__.py
@@ -9,7 +9,7 @@ from langchain_core.output_parsers.list import (
     MarkdownListOutputParser,
     NumberedListOutputParser,
 )
-from langchain_core.output_parsers.str import StrOutputParser
+from langchain_core.output_parsers.string import StrOutputParser
 from langchain_core.output_parsers.transform import (
     BaseCumulativeTransformOutputParser,
     BaseTransformOutputParser,
diff --git a/libs/core/langchain_core/output_parsers/base.py b/libs/core/langchain_core/output_parsers/base.py
index ff21255a84c..8b569750e7f 100644
--- a/libs/core/langchain_core/output_parsers/base.py
+++ b/libs/core/langchain_core/output_parsers/base.py
@@ -17,11 +17,8 @@ from typing import (
 from typing_extensions import get_args
 
 from langchain_core.messages import AnyMessage, BaseMessage
-from langchain_core.outputs import (
-    ChatGeneration,
-    Generation,
-)
-from langchain_core.prompts.value import PromptValue
+from langchain_core.outputs import ChatGeneration, Generation
+from langchain_core.prompt_values import PromptValue
 from langchain_core.runnables import RunnableConfig, RunnableSerializable
 
 T = TypeVar("T")
diff --git a/libs/core/langchain_core/output_parsers/str.py b/libs/core/langchain_core/output_parsers/string.py
similarity index 100%
rename from libs/core/langchain_core/output_parsers/str.py
rename to libs/core/langchain_core/output_parsers/string.py
diff --git a/libs/core/langchain_core/prompt_values.py b/libs/core/langchain_core/prompt_values.py
new file mode 100644
index 00000000000..22e02e30bac
--- /dev/null
+++ b/libs/core/langchain_core/prompt_values.py
@@ -0,0 +1,76 @@
+from __future__ import annotations
+
+from abc import ABC, abstractmethod
+from typing import List, Literal, Sequence
+
+from langchain_core.load.serializable import Serializable
+from langchain_core.messages import (
+    AnyMessage,
+    BaseMessage,
+    HumanMessage,
+    get_buffer_string,
+)
+
+
+class PromptValue(Serializable, ABC):
+    """Base abstract class for inputs to any language model.
+
+    PromptValues can be converted to both LLM (pure text-generation) inputs and
+        ChatModel inputs.
+    """
+
+    @classmethod
+    def is_lc_serializable(cls) -> bool:
+        """Return whether this class is serializable."""
+        return True
+
+    @abstractmethod
+    def to_string(self) -> str:
+        """Return prompt value as string."""
+
+    @abstractmethod
+    def to_messages(self) -> List[BaseMessage]:
+        """Return prompt as a list of Messages."""
+
+
+class StringPromptValue(PromptValue):
+    """String prompt value."""
+
+    text: str
+    """Prompt text."""
+    type: Literal["StringPromptValue"] = "StringPromptValue"
+
+    def to_string(self) -> str:
+        """Return prompt as string."""
+        return self.text
+
+    def to_messages(self) -> List[BaseMessage]:
+        """Return prompt as messages."""
+        return [HumanMessage(content=self.text)]
+
+
+class ChatPromptValue(PromptValue):
+    """Chat prompt value.
+
+    A type of a prompt value that is built from messages.
+    """
+
+    messages: Sequence[BaseMessage]
+    """List of messages."""
+
+    def to_string(self) -> str:
+        """Return prompt as string."""
+        return get_buffer_string(self.messages)
+
+    def to_messages(self) -> List[BaseMessage]:
+        """Return prompt as a list of messages."""
+        return list(self.messages)
+
+
+class ChatPromptValueConcrete(ChatPromptValue):
+    """Chat prompt value which explicitly lists out the message types it accepts.
+    For use in external schemas."""
+
+    messages: Sequence[AnyMessage]
+
+    type: Literal["ChatPromptValueConcrete"] = "ChatPromptValueConcrete"
diff --git a/libs/core/langchain_core/prompts/__init__.py b/libs/core/langchain_core/prompts/__init__.py
index d0ac34a7fac..bce1fc4d5d3 100644
--- a/libs/core/langchain_core/prompts/__init__.py
+++ b/libs/core/langchain_core/prompts/__init__.py
@@ -23,9 +23,6 @@ from multiple components. Prompt classes and functions make constructing
                                                                       AIMessagePromptTemplate
                                                                       SystemMessagePromptTemplate
 
-    PromptValue --> StringPromptValue
-                    ChatPromptValue
-
 """  # noqa: E501
 from langchain_core.prompts.base import BasePromptTemplate, format_document
 from langchain_core.prompts.chat import (
@@ -33,8 +30,6 @@ from langchain_core.prompts.chat import (
     BaseChatPromptTemplate,
     ChatMessagePromptTemplate,
     ChatPromptTemplate,
-    ChatPromptValue,
-    ChatPromptValueConcrete,
     HumanMessagePromptTemplate,
     MessagesPlaceholder,
     SystemMessagePromptTemplate,
@@ -47,7 +42,13 @@ from langchain_core.prompts.few_shot_with_templates import FewShotPromptWithTemp
 from langchain_core.prompts.loading import load_prompt
 from langchain_core.prompts.pipeline import PipelinePromptTemplate
 from langchain_core.prompts.prompt import Prompt, PromptTemplate
-from langchain_core.prompts.string import StringPromptTemplate, StringPromptValue
+from langchain_core.prompts.string import (
+    StringPromptTemplate,
+    check_valid_template,
+    get_template_variables,
+    jinja2_formatter,
+    validate_jinja2,
+)
 
 __all__ = [
     "AIMessagePromptTemplate",
@@ -55,8 +56,6 @@ __all__ = [
     "BasePromptTemplate",
     "ChatMessagePromptTemplate",
     "ChatPromptTemplate",
-    "ChatPromptValue",
-    "ChatPromptValueConcrete",
     "FewShotPromptTemplate",
     "FewShotPromptWithTemplates",
     "FewShotChatMessagePromptTemplate",
@@ -65,12 +64,12 @@ __all__ = [
     "PipelinePromptTemplate",
     "Prompt",
     "PromptTemplate",
-    "PromptValue",
-    "StringPromptValue",
     "StringPromptTemplate",
     "SystemMessagePromptTemplate",
     "load_prompt",
     "format_document",
+    "check_valid_template",
+    "get_template_variables",
+    "jinja2_formatter",
+    "validate_jinja2",
 ]
-
-from langchain_core.prompts.value import PromptValue
diff --git a/libs/core/langchain_core/prompts/base.py b/libs/core/langchain_core/prompts/base.py
index 1dc9955f330..2f6e9cd8174 100644
--- a/libs/core/langchain_core/prompts/base.py
+++ b/libs/core/langchain_core/prompts/base.py
@@ -8,8 +8,8 @@ from typing import Any, Callable, Dict, List, Mapping, Optional, Type, Union
 import yaml
 
 from langchain_core.documents import Document
-from langchain_core.output_parsers import BaseOutputParser
-from langchain_core.prompts.value import PromptValue
+from langchain_core.output_parsers.base import BaseOutputParser
+from langchain_core.prompt_values import PromptValue
 from langchain_core.pydantic_v1 import BaseModel, Field, create_model, root_validator
 from langchain_core.runnables import RunnableConfig, RunnableSerializable
 
@@ -40,8 +40,10 @@ class BasePromptTemplate(RunnableSerializable[Dict, PromptValue], ABC):
 
     @property
     def OutputType(self) -> Any:
-        from langchain_core.prompts.chat import ChatPromptValueConcrete
-        from langchain_core.prompts.string import StringPromptValue
+        from langchain_core.prompt_values import (
+            ChatPromptValueConcrete,
+            StringPromptValue,
+        )
 
         return Union[StringPromptValue, ChatPromptValueConcrete]
 
diff --git a/libs/core/langchain_core/prompts/chat.py b/libs/core/langchain_core/prompts/chat.py
index 0f88ba1226f..9c3fae871c4 100644
--- a/libs/core/langchain_core/prompts/chat.py
+++ b/libs/core/langchain_core/prompts/chat.py
@@ -8,7 +8,6 @@ from typing import (
     Callable,
     Dict,
     List,
-    Literal,
     Sequence,
     Set,
     Tuple,
@@ -27,12 +26,11 @@ from langchain_core.messages import (
     ChatMessage,
     HumanMessage,
     SystemMessage,
-    get_buffer_string,
 )
+from langchain_core.prompt_values import ChatPromptValue, PromptValue
 from langchain_core.prompts.base import BasePromptTemplate
 from langchain_core.prompts.prompt import PromptTemplate
 from langchain_core.prompts.string import StringPromptTemplate
-from langchain_core.prompts.value import PromptValue
 from langchain_core.pydantic_v1 import Field, root_validator
 
 
@@ -277,33 +275,6 @@ class SystemMessagePromptTemplate(BaseStringMessagePromptTemplate):
         return SystemMessage(content=text, additional_kwargs=self.additional_kwargs)
 
 
-class ChatPromptValue(PromptValue):
-    """Chat prompt value.
-
-    A type of a prompt value that is built from messages.
-    """
-
-    messages: Sequence[BaseMessage]
-    """List of messages."""
-
-    def to_string(self) -> str:
-        """Return prompt as string."""
-        return get_buffer_string(self.messages)
-
-    def to_messages(self) -> List[BaseMessage]:
-        """Return prompt as a list of messages."""
-        return list(self.messages)
-
-
-class ChatPromptValueConcrete(ChatPromptValue):
-    """Chat prompt value which explicitly lists out the message types it accepts.
-    For use in external schemas."""
-
-    messages: Sequence[AnyMessage]
-
-    type: Literal["ChatPromptValueConcrete"] = "ChatPromptValueConcrete"
-
-
 class BaseChatPromptTemplate(BasePromptTemplate, ABC):
     """Base class for chat prompt templates."""
 
diff --git a/libs/core/langchain_core/prompts/loading.py b/libs/core/langchain_core/prompts/loading.py
index e914cbb7b48..4961519717b 100644
--- a/libs/core/langchain_core/prompts/loading.py
+++ b/libs/core/langchain_core/prompts/loading.py
@@ -6,7 +6,7 @@ from typing import Callable, Dict, Union
 
 import yaml
 
-from langchain_core.output_parsers import StrOutputParser
+from langchain_core.output_parsers.string import StrOutputParser
 from langchain_core.prompts.base import BasePromptTemplate
 from langchain_core.prompts.few_shot import FewShotPromptTemplate
 from langchain_core.prompts.prompt import PromptTemplate
diff --git a/libs/core/langchain_core/prompts/pipeline.py b/libs/core/langchain_core/prompts/pipeline.py
index cffb11bbba8..7cf13f6896b 100644
--- a/libs/core/langchain_core/prompts/pipeline.py
+++ b/libs/core/langchain_core/prompts/pipeline.py
@@ -1,8 +1,8 @@
 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.prompts.value import PromptValue
 from langchain_core.pydantic_v1 import root_validator
 
 
diff --git a/libs/core/langchain_core/prompts/string.py b/libs/core/langchain_core/prompts/string.py
index 2645ffdca51..d61660f2b8a 100644
--- a/libs/core/langchain_core/prompts/string.py
+++ b/libs/core/langchain_core/prompts/string.py
@@ -4,11 +4,10 @@ from __future__ import annotations
 import warnings
 from abc import ABC
 from string import Formatter
-from typing import Any, Callable, Dict, List, Literal, Set
+from typing import Any, Callable, Dict, List, Set
 
-from langchain_core.messages import BaseMessage, HumanMessage
+from langchain_core.prompt_values import PromptValue, StringPromptValue
 from langchain_core.prompts.base import BasePromptTemplate
-from langchain_core.prompts.value import PromptValue
 from langchain_core.utils.formatting import formatter
 
 
@@ -149,22 +148,6 @@ def get_template_variables(template: str, template_format: str) -> List[str]:
     return sorted(input_variables)
 
 
-class StringPromptValue(PromptValue):
-    """String prompt value."""
-
-    text: str
-    """Prompt text."""
-    type: Literal["StringPromptValue"] = "StringPromptValue"
-
-    def to_string(self) -> str:
-        """Return prompt as string."""
-        return self.text
-
-    def to_messages(self) -> List[BaseMessage]:
-        """Return prompt as messages."""
-        return [HumanMessage(content=self.text)]
-
-
 class StringPromptTemplate(BasePromptTemplate, ABC):
     """String prompt that exposes the format method, returning a prompt."""
 
diff --git a/libs/core/langchain_core/prompts/value.py b/libs/core/langchain_core/prompts/value.py
deleted file mode 100644
index bedbefe2e5d..00000000000
--- a/libs/core/langchain_core/prompts/value.py
+++ /dev/null
@@ -1,28 +0,0 @@
-from __future__ import annotations
-
-from abc import ABC, abstractmethod
-from typing import List
-
-from langchain_core.load.serializable import Serializable
-from langchain_core.messages import BaseMessage
-
-
-class PromptValue(Serializable, ABC):
-    """Base abstract class for inputs to any language model.
-
-    PromptValues can be converted to both LLM (pure text-generation) inputs and
-        ChatModel inputs.
-    """
-
-    @classmethod
-    def is_lc_serializable(cls) -> bool:
-        """Return whether this class is serializable."""
-        return True
-
-    @abstractmethod
-    def to_string(self) -> str:
-        """Return prompt value as string."""
-
-    @abstractmethod
-    def to_messages(self) -> List[BaseMessage]:
-        """Return prompt as a list of Messages."""
diff --git a/libs/core/langchain_core/tracers/base.py b/libs/core/langchain_core/tracers/base.py
index a8479c1a711..ce0d79ac1d4 100644
--- a/libs/core/langchain_core/tracers/base.py
+++ b/libs/core/langchain_core/tracers/base.py
@@ -9,7 +9,7 @@ from uuid import UUID
 
 from tenacity import RetryCallState
 
-from langchain_core.callbacks import BaseCallbackHandler
+from langchain_core.callbacks.base import BaseCallbackHandler
 from langchain_core.documents import Document
 from langchain_core.exceptions import TracerException
 from langchain_core.load import dumpd
diff --git a/libs/core/langchain_core/tracers/context.py b/libs/core/langchain_core/tracers/context.py
new file mode 100644
index 00000000000..c4d74a955d8
--- /dev/null
+++ b/libs/core/langchain_core/tracers/context.py
@@ -0,0 +1,226 @@
+from __future__ import annotations
+
+from contextlib import contextmanager
+from contextvars import ContextVar
+from typing import (
+    TYPE_CHECKING,
+    Any,
+    Generator,
+    List,
+    Optional,
+    Tuple,
+    Type,
+    Union,
+    cast,
+)
+from uuid import UUID
+
+from langsmith import utils as ls_utils
+from langsmith.run_helpers import get_run_tree_context
+
+from langchain_core.tracers.langchain import LangChainTracer
+from langchain_core.tracers.langchain_v1 import LangChainTracerV1
+from langchain_core.tracers.run_collector import RunCollectorCallbackHandler
+from langchain_core.tracers.schemas import TracerSessionV1
+from langchain_core.utils.env import env_var_is_set
+
+if TYPE_CHECKING:
+    from langsmith import Client as LangSmithClient
+
+    from langchain_core.callbacks.base import BaseCallbackHandler, Callbacks
+    from langchain_core.callbacks.manager import AsyncCallbackManager, CallbackManager
+
+tracing_callback_var: ContextVar[Optional[LangChainTracerV1]] = ContextVar(  # noqa: E501
+    "tracing_callback", default=None
+)
+
+tracing_v2_callback_var: ContextVar[Optional[LangChainTracer]] = ContextVar(  # noqa: E501
+    "tracing_callback_v2", default=None
+)
+run_collector_var: ContextVar[Optional[RunCollectorCallbackHandler]] = ContextVar(  # noqa: E501
+    "run_collector", default=None
+)
+
+
+@contextmanager
+def tracing_enabled(
+    session_name: str = "default",
+) -> Generator[TracerSessionV1, None, None]:
+    """Get the Deprecated LangChainTracer in a context manager.
+
+    Args:
+        session_name (str, optional): The name of the session.
+          Defaults to "default".
+
+    Returns:
+        TracerSessionV1: The LangChainTracer session.
+
+    Example:
+        >>> with tracing_enabled() as session:
+        ...     # Use the LangChainTracer session
+    """
+    cb = LangChainTracerV1()
+    session = cast(TracerSessionV1, cb.load_session(session_name))
+    try:
+        tracing_callback_var.set(cb)
+        yield session
+    finally:
+        tracing_callback_var.set(None)
+
+
+@contextmanager
+def tracing_v2_enabled(
+    project_name: Optional[str] = None,
+    *,
+    example_id: Optional[Union[str, UUID]] = None,
+    tags: Optional[List[str]] = None,
+    client: Optional[LangSmithClient] = None,
+) -> Generator[LangChainTracer, None, None]:
+    """Instruct LangChain to log all runs in context to LangSmith.
+
+    Args:
+        project_name (str, optional): The name of the project.
+            Defaults to "default".
+        example_id (str or UUID, optional): The ID of the example.
+            Defaults to None.
+        tags (List[str], optional): The tags to add to the run.
+            Defaults to None.
+
+    Returns:
+        None
+
+    Example:
+        >>> with tracing_v2_enabled():
+        ...     # LangChain code will automatically be traced
+
+        You can use this to fetch the LangSmith run URL:
+
+        >>> with tracing_v2_enabled() as cb:
+        ...     chain.invoke("foo")
+        ...     run_url = cb.get_run_url()
+    """
+    if isinstance(example_id, str):
+        example_id = UUID(example_id)
+    cb = LangChainTracer(
+        example_id=example_id,
+        project_name=project_name,
+        tags=tags,
+        client=client,
+    )
+    try:
+        tracing_v2_callback_var.set(cb)
+        yield cb
+    finally:
+        tracing_v2_callback_var.set(None)
+
+
+@contextmanager
+def collect_runs() -> Generator[RunCollectorCallbackHandler, None, None]:
+    """Collect all run traces in context.
+
+    Returns:
+        run_collector.RunCollectorCallbackHandler: The run collector callback handler.
+
+    Example:
+        >>> with collect_runs() as runs_cb:
+                chain.invoke("foo")
+                run_id = runs_cb.traced_runs[0].id
+    """
+    cb = RunCollectorCallbackHandler()
+    run_collector_var.set(cb)
+    yield cb
+    run_collector_var.set(None)
+
+
+def _get_trace_callbacks(
+    project_name: Optional[str] = None,
+    example_id: Optional[Union[str, UUID]] = None,
+    callback_manager: Optional[Union[CallbackManager, AsyncCallbackManager]] = None,
+) -> Callbacks:
+    if _tracing_v2_is_enabled():
+        project_name_ = project_name or _get_tracer_project()
+        tracer = tracing_v2_callback_var.get() or LangChainTracer(
+            project_name=project_name_,
+            example_id=example_id,
+        )
+        if callback_manager is None:
+            from langchain_core.callbacks.base import Callbacks
+
+            cb = cast(Callbacks, [tracer])
+        else:
+            if not any(
+                isinstance(handler, LangChainTracer)
+                for handler in callback_manager.handlers
+            ):
+                callback_manager.add_handler(tracer, True)
+                # If it already has a LangChainTracer, we don't need to add another one.
+                # this would likely mess up the trace hierarchy.
+            cb = callback_manager
+    else:
+        cb = None
+    return cb
+
+
+def _tracing_v2_is_enabled() -> bool:
+    return (
+        env_var_is_set("LANGCHAIN_TRACING_V2")
+        or tracing_v2_callback_var.get() is not None
+        or get_run_tree_context() is not None
+    )
+
+
+def _get_tracer_project() -> str:
+    run_tree = get_run_tree_context()
+    return getattr(
+        run_tree,
+        "session_name",
+        getattr(
+            # Note, if people are trying to nest @traceable functions and the
+            # tracing_v2_enabled context manager, this will likely mess up the
+            # tree structure.
+            tracing_v2_callback_var.get(),
+            "project",
+            # Have to set this to a string even though it always will return
+            # a string because `get_tracer_project` technically can return
+            # None, but only when a specific argument is supplied.
+            # Therefore, this just tricks the mypy type checker
+            str(ls_utils.get_tracer_project()),
+        ),
+    )
+
+
+_configure_hooks: List[
+    Tuple[
+        ContextVar[Optional[BaseCallbackHandler]],
+        bool,
+        Optional[Type[BaseCallbackHandler]],
+        Optional[str],
+    ]
+] = []
+
+
+def register_configure_hook(
+    context_var: ContextVar[Optional[Any]],
+    inheritable: bool,
+    handle_class: Optional[Type[BaseCallbackHandler]] = None,
+    env_var: Optional[str] = None,
+) -> None:
+    if env_var is not None and handle_class is None:
+        raise ValueError(
+            "If env_var is set, handle_class must also be set to a non-None value."
+        )
+    from langchain_core.callbacks.base import BaseCallbackHandler
+
+    _configure_hooks.append(
+        (
+            # the typings of ContextVar do not have the generic arg set as covariant
+            # so we have to cast it
+            cast(ContextVar[Optional[BaseCallbackHandler]], context_var),
+            inheritable,
+            handle_class,
+            env_var,
+        )
+    )
+
+
+register_configure_hook(run_collector_var, False)
diff --git a/libs/core/langchain_core/tracers/evaluation.py b/libs/core/langchain_core/tracers/evaluation.py
index 685430a5afd..b7e5dc8bc0d 100644
--- a/libs/core/langchain_core/tracers/evaluation.py
+++ b/libs/core/langchain_core/tracers/evaluation.py
@@ -11,9 +11,9 @@ from uuid import UUID
 import langsmith
 from langsmith.evaluation.evaluator import EvaluationResult, EvaluationResults
 
-from langchain_core.callbacks import manager
 from langchain_core.tracers import langchain as langchain_tracer
 from langchain_core.tracers.base import BaseTracer
+from langchain_core.tracers.context import tracing_v2_enabled
 from langchain_core.tracers.langchain import _get_executor
 from langchain_core.tracers.schemas import Run
 
@@ -115,7 +115,7 @@ class EvaluatorCallbackHandler(BaseTracer):
             if self.project_name is None:
                 eval_result = self.client.evaluate_run(run, evaluator)
                 eval_results = [eval_result]
-            with manager.tracing_v2_enabled(
+            with tracing_v2_enabled(
                 project_name=self.project_name, tags=["eval"], client=self.client
             ) as cb:
                 reference_example = (
diff --git a/libs/core/langchain_core/tracers/log_stream.py b/libs/core/langchain_core/tracers/log_stream.py
index 97bcf452b3f..7bd030691af 100644
--- a/libs/core/langchain_core/tracers/log_stream.py
+++ b/libs/core/langchain_core/tracers/log_stream.py
@@ -15,7 +15,7 @@ from typing import (
 )
 from uuid import UUID
 
-import jsonpatch
+import jsonpatch  # type: ignore[import]
 from anyio import create_memory_object_stream
 
 from langchain_core.load import load
diff --git a/libs/core/langchain_core/utils/env.py b/libs/core/langchain_core/utils/env.py
new file mode 100644
index 00000000000..45ab464ead8
--- /dev/null
+++ b/libs/core/langchain_core/utils/env.py
@@ -0,0 +1,20 @@
+from __future__ import annotations
+
+import os
+
+
+def env_var_is_set(env_var: str) -> bool:
+    """Check if an environment variable is set.
+
+    Args:
+        env_var (str): The name of the environment variable.
+
+    Returns:
+        bool: True if the environment variable is set, False otherwise.
+    """
+    return env_var in os.environ and os.environ[env_var] not in (
+        "",
+        "0",
+        "false",
+        "False",
+    )
diff --git a/libs/core/pyproject.toml b/libs/core/pyproject.toml
index b363f3f6deb..2da2d23540b 100644
--- a/libs/core/pyproject.toml
+++ b/libs/core/pyproject.toml
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "langchain-core"
-version = "0.0.2"
+version = "0.0.3"
 description = "Building applications with LLMs through composability"
 authors = []
 license = "MIT"
@@ -51,7 +51,6 @@ select = [
 ]
 
 [tool.mypy]
-ignore_missing_imports = "True"
 disallow_untyped_defs = "True"
 exclude = ["notebooks", "examples", "example_data", "langchain_core/pydantic"]
 
diff --git a/libs/core/tests/unit_tests/callbacks/__init__.py b/libs/core/tests/unit_tests/callbacks/__init__.py
new file mode 100644
index 00000000000..e69de29bb2d
diff --git a/libs/core/tests/unit_tests/callbacks/test_imports.py b/libs/core/tests/unit_tests/callbacks/test_imports.py
new file mode 100644
index 00000000000..9a9ee0eb9b8
--- /dev/null
+++ b/libs/core/tests/unit_tests/callbacks/test_imports.py
@@ -0,0 +1,37 @@
+from langchain_core.callbacks import __all__
+
+EXPECTED_ALL = [
+    "RetrieverManagerMixin",
+    "LLMManagerMixin",
+    "ChainManagerMixin",
+    "ToolManagerMixin",
+    "Callbacks",
+    "CallbackManagerMixin",
+    "RunManagerMixin",
+    "BaseCallbackHandler",
+    "AsyncCallbackHandler",
+    "BaseCallbackManager",
+    "BaseRunManager",
+    "RunManager",
+    "ParentRunManager",
+    "AsyncRunManager",
+    "AsyncParentRunManager",
+    "CallbackManagerForLLMRun",
+    "AsyncCallbackManagerForLLMRun",
+    "CallbackManagerForChainRun",
+    "AsyncCallbackManagerForChainRun",
+    "CallbackManagerForToolRun",
+    "AsyncCallbackManagerForToolRun",
+    "CallbackManagerForRetrieverRun",
+    "AsyncCallbackManagerForRetrieverRun",
+    "CallbackManager",
+    "CallbackManagerForChainGroup",
+    "AsyncCallbackManager",
+    "AsyncCallbackManagerForChainGroup",
+    "StdOutCallbackHandler",
+    "StreamingStdOutCallbackHandler",
+]
+
+
+def test_all_imports() -> None:
+    assert set(__all__) == set(EXPECTED_ALL)
diff --git a/libs/core/tests/unit_tests/example_selectors/test_imports.py b/libs/core/tests/unit_tests/example_selectors/test_imports.py
new file mode 100644
index 00000000000..cb6c9ddb52c
--- /dev/null
+++ b/libs/core/tests/unit_tests/example_selectors/test_imports.py
@@ -0,0 +1,13 @@
+from langchain_core.example_selectors import __all__
+
+EXPECTED_ALL = [
+    "BaseExampleSelector",
+    "LengthBasedExampleSelector",
+    "MaxMarginalRelevanceExampleSelector",
+    "SemanticSimilarityExampleSelector",
+    "sorted_values",
+]
+
+
+def test_all_imports() -> None:
+    assert set(__all__) == set(EXPECTED_ALL)
diff --git a/libs/core/tests/unit_tests/language_models/__init__.py b/libs/core/tests/unit_tests/language_models/__init__.py
new file mode 100644
index 00000000000..e69de29bb2d
diff --git a/libs/core/tests/unit_tests/language_models/test_imports.py b/libs/core/tests/unit_tests/language_models/test_imports.py
new file mode 100644
index 00000000000..439f940177b
--- /dev/null
+++ b/libs/core/tests/unit_tests/language_models/test_imports.py
@@ -0,0 +1,15 @@
+from langchain_core.language_models import __all__
+
+EXPECTED_ALL = [
+    "BaseLanguageModel",
+    "BaseChatModel",
+    "SimpleChatModel",
+    "BaseLLM",
+    "LLM",
+    "LanguageModelInput",
+    "get_tokenizer",
+]
+
+
+def test_all_imports() -> None:
+    assert set(__all__) == set(EXPECTED_ALL)
diff --git a/libs/core/tests/unit_tests/load/__init__.py b/libs/core/tests/unit_tests/load/__init__.py
new file mode 100644
index 00000000000..e69de29bb2d
diff --git a/libs/core/tests/unit_tests/load/test_imports.py b/libs/core/tests/unit_tests/load/test_imports.py
new file mode 100644
index 00000000000..a6e87afb5a9
--- /dev/null
+++ b/libs/core/tests/unit_tests/load/test_imports.py
@@ -0,0 +1,7 @@
+from langchain_core.load import __all__
+
+EXPECTED_ALL = ["dumpd", "dumps", "load", "loads", "Serializable"]
+
+
+def test_all_imports() -> None:
+    assert set(__all__) == set(EXPECTED_ALL)
diff --git a/libs/core/tests/unit_tests/messages/__init__.py b/libs/core/tests/unit_tests/messages/__init__.py
new file mode 100644
index 00000000000..e69de29bb2d
diff --git a/libs/core/tests/unit_tests/messages/test_imports.py b/libs/core/tests/unit_tests/messages/test_imports.py
new file mode 100644
index 00000000000..539c6bebfc7
--- /dev/null
+++ b/libs/core/tests/unit_tests/messages/test_imports.py
@@ -0,0 +1,28 @@
+from langchain_core.messages import __all__
+
+EXPECTED_ALL = [
+    "AIMessage",
+    "AIMessageChunk",
+    "AnyMessage",
+    "BaseMessage",
+    "BaseMessageChunk",
+    "ChatMessage",
+    "ChatMessageChunk",
+    "FunctionMessage",
+    "FunctionMessageChunk",
+    "HumanMessage",
+    "HumanMessageChunk",
+    "SystemMessage",
+    "SystemMessageChunk",
+    "ToolMessage",
+    "ToolMessageChunk",
+    "get_buffer_string",
+    "messages_from_dict",
+    "messages_to_dict",
+    "message_to_dict",
+    "merge_content",
+]
+
+
+def test_all_imports() -> None:
+    assert set(__all__) == set(EXPECTED_ALL)
diff --git a/libs/core/tests/unit_tests/output_parsers/__init__.py b/libs/core/tests/unit_tests/output_parsers/__init__.py
new file mode 100644
index 00000000000..e69de29bb2d
diff --git a/libs/core/tests/unit_tests/output_parsers/test_imports.py b/libs/core/tests/unit_tests/output_parsers/test_imports.py
new file mode 100644
index 00000000000..45a779225e7
--- /dev/null
+++ b/libs/core/tests/unit_tests/output_parsers/test_imports.py
@@ -0,0 +1,18 @@
+from langchain_core.output_parsers import __all__
+
+EXPECTED_ALL = [
+    "BaseLLMOutputParser",
+    "BaseGenerationOutputParser",
+    "BaseOutputParser",
+    "ListOutputParser",
+    "CommaSeparatedListOutputParser",
+    "NumberedListOutputParser",
+    "MarkdownListOutputParser",
+    "StrOutputParser",
+    "BaseTransformOutputParser",
+    "BaseCumulativeTransformOutputParser",
+]
+
+
+def test_all_imports() -> None:
+    assert set(__all__) == set(EXPECTED_ALL)
diff --git a/libs/core/tests/unit_tests/outputs/__init__.py b/libs/core/tests/unit_tests/outputs/__init__.py
new file mode 100644
index 00000000000..e69de29bb2d
diff --git a/libs/core/tests/unit_tests/outputs/test_imports.py b/libs/core/tests/unit_tests/outputs/test_imports.py
new file mode 100644
index 00000000000..d13bc45e535
--- /dev/null
+++ b/libs/core/tests/unit_tests/outputs/test_imports.py
@@ -0,0 +1,15 @@
+from langchain_core.outputs import __all__
+
+EXPECTED_ALL = [
+    "ChatGeneration",
+    "ChatGenerationChunk",
+    "ChatResult",
+    "Generation",
+    "GenerationChunk",
+    "LLMResult",
+    "RunInfo",
+]
+
+
+def test_all_imports() -> None:
+    assert set(__all__) == set(EXPECTED_ALL)
diff --git a/libs/core/tests/unit_tests/prompts/test_chat.py b/libs/core/tests/unit_tests/prompts/test_chat.py
index 1e919e28e6f..3719573a6c6 100644
--- a/libs/core/tests/unit_tests/prompts/test_chat.py
+++ b/libs/core/tests/unit_tests/prompts/test_chat.py
@@ -10,6 +10,7 @@ from langchain_core.messages import (
     SystemMessage,
     get_buffer_string,
 )
+from langchain_core.prompt_values import ChatPromptValue
 from langchain_core.prompts import PromptTemplate
 from langchain_core.prompts.chat import (
     AIMessagePromptTemplate,
@@ -17,7 +18,6 @@ from langchain_core.prompts.chat import (
     ChatMessage,
     ChatMessagePromptTemplate,
     ChatPromptTemplate,
-    ChatPromptValue,
     HumanMessagePromptTemplate,
     SystemMessagePromptTemplate,
     _convert_to_message,
diff --git a/libs/core/tests/unit_tests/prompts/test_imports.py b/libs/core/tests/unit_tests/prompts/test_imports.py
index 4f1b5dcacc0..250afa23513 100644
--- a/libs/core/tests/unit_tests/prompts/test_imports.py
+++ b/libs/core/tests/unit_tests/prompts/test_imports.py
@@ -6,14 +6,10 @@ EXPECTED_ALL = [
     "BasePromptTemplate",
     "ChatMessagePromptTemplate",
     "ChatPromptTemplate",
-    "ChatPromptValueConcrete",
     "FewShotPromptTemplate",
     "FewShotPromptWithTemplates",
     "FewShotChatMessagePromptTemplate",
     "format_document",
-    "ChatPromptValue",
-    "PromptValue",
-    "StringPromptValue",
     "HumanMessagePromptTemplate",
     "MessagesPlaceholder",
     "PipelinePromptTemplate",
@@ -22,6 +18,10 @@ EXPECTED_ALL = [
     "StringPromptTemplate",
     "SystemMessagePromptTemplate",
     "load_prompt",
+    "check_valid_template",
+    "get_template_variables",
+    "jinja2_formatter",
+    "validate_jinja2",
 ]
 
 
diff --git a/libs/core/tests/unit_tests/runnables/__snapshots__/test_runnable.ambr b/libs/core/tests/unit_tests/runnables/__snapshots__/test_runnable.ambr
index 127e7122c0a..ddaeb6c7300 100644
--- a/libs/core/tests/unit_tests/runnables/__snapshots__/test_runnable.ambr
+++ b/libs/core/tests/unit_tests/runnables/__snapshots__/test_runnable.ambr
@@ -466,7 +466,7 @@
 # ---
 # name: test_combining_sequences.3
   list([
-    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_core', 'runnables', 'RunnableSequence'], 'kwargs': {'first': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nice assistant.', 'template_format': 'f-string', 'partial_variables': {}}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', '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': ['tests', 'unit_tests', 'fake', 'chat_model', 'FakeListChatModel'], 'repr': "FakeListChatModel(responses=['foo, bar'])"}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'output_parsers', 'list', 'CommaSeparatedListOutputParser'], 'kwargs': {}}, {'lc': 1, 'type': 'not_implemented', 'id': ['langchain_core', 'runnables', 'base', 'RunnableLambda'], 'repr': "RunnableLambda(lambda x: {'question': x[0] + x[1]})"}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nicer assistant.', 'template_format': 'f-string', 'partial_variables': {}}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': ['question'], 'template': '{question}', 'template_format': 'f-string', 'partial_variables': {}}}}}], 'input_variables': ['question']}}, {'lc': 1, 'type': 'not_implemented', 'id': ['tests', 'unit_tests', 'fake', 'chat_model', 'FakeListChatModel'], 'repr': "FakeListChatModel(responses=['baz, qux'])"}], 'last': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', '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_core', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nice assistant.', 'template_format': 'f-string', 'partial_variables': {}}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', '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_core', 'prompts', 'chat', 'ChatPromptValue'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'messages', 'system', 'SystemMessage'], 'kwargs': {'content': 'You are a nice assistant.', 'additional_kwargs': {}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'messages', 'human', 'HumanMessage'], 'kwargs': {'content': 'What is your name?', 'additional_kwargs': {}}}]}}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:1'], 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': ['tests', 'unit_tests', 'fake', 'chat_model', 'FakeListChatModel'], 'repr': "FakeListChatModel(responses=['foo, bar'])"}, 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, 'type': 'ChatGeneration', 'message': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'messages', 'ai', 'AIMessage'], 'kwargs': {'content': 'foo, bar'}}}]], 'llm_output': None, 'run': None}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:2'], 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_core', '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')}, outputs={'output': ['foo', 'bar']}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:3'], execution_order=None, child_execution_order=None, child_runs=[]), Run(id=UUID('00000000-0000-4000-8000-000000000004'), name='<lambda>', 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_core', 'runnables', 'base', 'RunnableLambda'], 'repr': "RunnableLambda(lambda x: {'question': x[0] + x[1]})"}, 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=['seq:step:4'], 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_core', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nicer assistant.', 'template_format': 'f-string', 'partial_variables': {}}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', '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_core', 'prompts', 'chat', 'ChatPromptValue'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'messages', 'system', 'SystemMessage'], 'kwargs': {'content': 'You are a nicer assistant.', 'additional_kwargs': {}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'messages', 'human', 'HumanMessage'], 'kwargs': {'content': 'foobar', 'additional_kwargs': {}}}]}}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:5'], 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': ['tests', 'unit_tests', 'fake', 'chat_model', 'FakeListChatModel'], 'repr': "FakeListChatModel(responses=['baz, qux'])"}, 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, 'type': 'ChatGeneration', 'message': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'messages', 'ai', 'AIMessage'], 'kwargs': {'content': 'baz, qux'}}}]], 'llm_output': None, 'run': None}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:6'], 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_core', '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')}, outputs={'output': ['baz', 'qux']}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:7'], execution_order=None, child_execution_order=None, child_runs=[])]),
+    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_core', 'runnables', 'RunnableSequence'], 'kwargs': {'first': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nice assistant.', 'template_format': 'f-string', 'partial_variables': {}}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', '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': ['tests', 'unit_tests', 'fake', 'chat_model', 'FakeListChatModel'], 'repr': "FakeListChatModel(responses=['foo, bar'])"}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'output_parsers', 'list', 'CommaSeparatedListOutputParser'], 'kwargs': {}}, {'lc': 1, 'type': 'not_implemented', 'id': ['langchain_core', 'runnables', 'base', 'RunnableLambda'], 'repr': "RunnableLambda(lambda x: {'question': x[0] + x[1]})"}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nicer assistant.', 'template_format': 'f-string', 'partial_variables': {}}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': ['question'], 'template': '{question}', 'template_format': 'f-string', 'partial_variables': {}}}}}], 'input_variables': ['question']}}, {'lc': 1, 'type': 'not_implemented', 'id': ['tests', 'unit_tests', 'fake', 'chat_model', 'FakeListChatModel'], 'repr': "FakeListChatModel(responses=['baz, qux'])"}], 'last': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', '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_core', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nice assistant.', 'template_format': 'f-string', 'partial_variables': {}}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', '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_core', 'prompt_values', 'ChatPromptValue'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'messages', 'system', 'SystemMessage'], 'kwargs': {'content': 'You are a nice assistant.', 'additional_kwargs': {}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'messages', 'human', 'HumanMessage'], 'kwargs': {'content': 'What is your name?', 'additional_kwargs': {}}}]}}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:1'], 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': ['tests', 'unit_tests', 'fake', 'chat_model', 'FakeListChatModel'], 'repr': "FakeListChatModel(responses=['foo, bar'])"}, 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, 'type': 'ChatGeneration', 'message': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'messages', 'ai', 'AIMessage'], 'kwargs': {'content': 'foo, bar'}}}]], 'llm_output': None, 'run': None}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:2'], 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_core', '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')}, outputs={'output': ['foo', 'bar']}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:3'], execution_order=None, child_execution_order=None, child_runs=[]), Run(id=UUID('00000000-0000-4000-8000-000000000004'), name='<lambda>', 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_core', 'runnables', 'base', 'RunnableLambda'], 'repr': "RunnableLambda(lambda x: {'question': x[0] + x[1]})"}, 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=['seq:step:4'], 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_core', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nicer assistant.', 'template_format': 'f-string', 'partial_variables': {}}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', '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_core', 'prompt_values', 'ChatPromptValue'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'messages', 'system', 'SystemMessage'], 'kwargs': {'content': 'You are a nicer assistant.', 'additional_kwargs': {}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'messages', 'human', 'HumanMessage'], 'kwargs': {'content': 'foobar', 'additional_kwargs': {}}}]}}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:5'], 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': ['tests', 'unit_tests', 'fake', 'chat_model', 'FakeListChatModel'], 'repr': "FakeListChatModel(responses=['baz, qux'])"}, 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, 'type': 'ChatGeneration', 'message': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'messages', 'ai', 'AIMessage'], 'kwargs': {'content': 'baz, qux'}}}]], 'llm_output': None, 'run': None}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:6'], 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_core', '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')}, outputs={'output': ['baz', 'qux']}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:7'], execution_order=None, child_execution_order=None, child_runs=[])]),
   ])
 # ---
 # name: test_each
@@ -1053,7 +1053,7 @@
 # ---
 # name: test_prompt_with_chat_model.2
   list([
-    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_core', 'runnables', 'RunnableSequence'], 'kwargs': {'first': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nice assistant.', 'template_format': 'f-string', 'partial_variables': {}}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': ['question'], 'template': '{question}', 'template_format': 'f-string', 'partial_variables': {}}}}}], 'input_variables': ['question']}}, 'last': {'lc': 1, 'type': 'not_implemented', 'id': ['tests', 'unit_tests', 'fake', 'chat_model', 'FakeListChatModel'], 'repr': "FakeListChatModel(responses=['foo'])"}}}, 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': AIMessage(content='foo')}, 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_core', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nice assistant.', 'template_format': 'f-string', 'partial_variables': {}}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', '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_core', 'prompts', 'chat', 'ChatPromptValue'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'messages', 'system', 'SystemMessage'], 'kwargs': {'content': 'You are a nice assistant.', 'additional_kwargs': {}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'messages', 'human', 'HumanMessage'], 'kwargs': {'content': 'What is your name?', 'additional_kwargs': {}}}]}}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:1'], 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'], '_type': 'fake-list-chat-model', 'stop': None}, 'options': {'stop': None}}, error=None, serialized={'lc': 1, 'type': 'not_implemented', 'id': ['tests', 'unit_tests', 'fake', 'chat_model', 'FakeListChatModel'], 'repr': "FakeListChatModel(responses=['foo'])"}, 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', 'generation_info': None, 'type': 'ChatGeneration', 'message': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'messages', 'ai', 'AIMessage'], 'kwargs': {'content': 'foo'}}}]], 'llm_output': None, 'run': None}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:2'], execution_order=None, child_execution_order=None, child_runs=[])]),
+    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_core', 'runnables', 'RunnableSequence'], 'kwargs': {'first': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nice assistant.', 'template_format': 'f-string', 'partial_variables': {}}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': ['question'], 'template': '{question}', 'template_format': 'f-string', 'partial_variables': {}}}}}], 'input_variables': ['question']}}, 'last': {'lc': 1, 'type': 'not_implemented', 'id': ['tests', 'unit_tests', 'fake', 'chat_model', 'FakeListChatModel'], 'repr': "FakeListChatModel(responses=['foo'])"}}}, 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': AIMessage(content='foo')}, 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_core', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nice assistant.', 'template_format': 'f-string', 'partial_variables': {}}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', '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_core', 'prompt_values', 'ChatPromptValue'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'messages', 'system', 'SystemMessage'], 'kwargs': {'content': 'You are a nice assistant.', 'additional_kwargs': {}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'messages', 'human', 'HumanMessage'], 'kwargs': {'content': 'What is your name?', 'additional_kwargs': {}}}]}}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:1'], 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'], '_type': 'fake-list-chat-model', 'stop': None}, 'options': {'stop': None}}, error=None, serialized={'lc': 1, 'type': 'not_implemented', 'id': ['tests', 'unit_tests', 'fake', 'chat_model', 'FakeListChatModel'], 'repr': "FakeListChatModel(responses=['foo'])"}, 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', 'generation_info': None, 'type': 'ChatGeneration', 'message': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'messages', 'ai', 'AIMessage'], 'kwargs': {'content': 'foo'}}}]], 'llm_output': None, 'run': None}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:2'], execution_order=None, child_execution_order=None, child_runs=[])]),
   ])
 # ---
 # name: test_prompt_with_chat_model_and_parser
@@ -1173,7 +1173,7 @@
 # ---
 # name: test_prompt_with_chat_model_and_parser.1
   list([
-    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_core', 'runnables', 'RunnableSequence'], 'kwargs': {'first': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nice assistant.', 'template_format': 'f-string', 'partial_variables': {}}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', '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': ['tests', 'unit_tests', 'fake', 'chat_model', 'FakeListChatModel'], 'repr': "FakeListChatModel(responses=['foo, bar'])"}], 'last': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', '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': ['foo', 'bar']}, 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_core', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nice assistant.', 'template_format': 'f-string', 'partial_variables': {}}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', '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_core', 'prompts', 'chat', 'ChatPromptValue'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'messages', 'system', 'SystemMessage'], 'kwargs': {'content': 'You are a nice assistant.', 'additional_kwargs': {}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'messages', 'human', 'HumanMessage'], 'kwargs': {'content': 'What is your name?', 'additional_kwargs': {}}}]}}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:1'], 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': ['tests', 'unit_tests', 'fake', 'chat_model', 'FakeListChatModel'], 'repr': "FakeListChatModel(responses=['foo, bar'])"}, 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, 'type': 'ChatGeneration', 'message': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'messages', 'ai', 'AIMessage'], 'kwargs': {'content': 'foo, bar'}}}]], 'llm_output': None, 'run': None}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:2'], 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_core', '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')}, outputs={'output': ['foo', 'bar']}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:3'], execution_order=None, child_execution_order=None, child_runs=[])]),
+    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_core', 'runnables', 'RunnableSequence'], 'kwargs': {'first': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nice assistant.', 'template_format': 'f-string', 'partial_variables': {}}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', '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': ['tests', 'unit_tests', 'fake', 'chat_model', 'FakeListChatModel'], 'repr': "FakeListChatModel(responses=['foo, bar'])"}], 'last': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', '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': ['foo', 'bar']}, 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_core', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nice assistant.', 'template_format': 'f-string', 'partial_variables': {}}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', '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_core', 'prompt_values', 'ChatPromptValue'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'messages', 'system', 'SystemMessage'], 'kwargs': {'content': 'You are a nice assistant.', 'additional_kwargs': {}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'messages', 'human', 'HumanMessage'], 'kwargs': {'content': 'What is your name?', 'additional_kwargs': {}}}]}}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:1'], 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': ['tests', 'unit_tests', 'fake', 'chat_model', 'FakeListChatModel'], 'repr': "FakeListChatModel(responses=['foo, bar'])"}, 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, 'type': 'ChatGeneration', 'message': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'messages', 'ai', 'AIMessage'], 'kwargs': {'content': 'foo, bar'}}}]], 'llm_output': None, 'run': None}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:2'], 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_core', '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')}, outputs={'output': ['foo', 'bar']}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:3'], execution_order=None, child_execution_order=None, child_runs=[])]),
   ])
 # ---
 # name: test_prompt_with_chat_model_async
@@ -1286,7 +1286,7 @@
 # ---
 # name: test_prompt_with_chat_model_async.2
   list([
-    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_core', 'runnables', 'RunnableSequence'], 'kwargs': {'first': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nice assistant.', 'template_format': 'f-string', 'partial_variables': {}}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': ['question'], 'template': '{question}', 'template_format': 'f-string', 'partial_variables': {}}}}}], 'input_variables': ['question']}}, 'last': {'lc': 1, 'type': 'not_implemented', 'id': ['tests', 'unit_tests', 'fake', 'chat_model', 'FakeListChatModel'], 'repr': "FakeListChatModel(responses=['foo'])"}}}, 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': AIMessage(content='foo')}, 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_core', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nice assistant.', 'template_format': 'f-string', 'partial_variables': {}}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', '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_core', 'prompts', 'chat', 'ChatPromptValue'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'messages', 'system', 'SystemMessage'], 'kwargs': {'content': 'You are a nice assistant.', 'additional_kwargs': {}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'messages', 'human', 'HumanMessage'], 'kwargs': {'content': 'What is your name?', 'additional_kwargs': {}}}]}}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:1'], 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'], '_type': 'fake-list-chat-model', 'stop': None}, 'options': {'stop': None}}, error=None, serialized={'lc': 1, 'type': 'not_implemented', 'id': ['tests', 'unit_tests', 'fake', 'chat_model', 'FakeListChatModel'], 'repr': "FakeListChatModel(responses=['foo'])"}, 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', 'generation_info': None, 'type': 'ChatGeneration', 'message': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'messages', 'ai', 'AIMessage'], 'kwargs': {'content': 'foo'}}}]], 'llm_output': None, 'run': None}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:2'], execution_order=None, child_execution_order=None, child_runs=[])]),
+    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_core', 'runnables', 'RunnableSequence'], 'kwargs': {'first': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nice assistant.', 'template_format': 'f-string', 'partial_variables': {}}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': ['question'], 'template': '{question}', 'template_format': 'f-string', 'partial_variables': {}}}}}], 'input_variables': ['question']}}, 'last': {'lc': 1, 'type': 'not_implemented', 'id': ['tests', 'unit_tests', 'fake', 'chat_model', 'FakeListChatModel'], 'repr': "FakeListChatModel(responses=['foo'])"}}}, 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': AIMessage(content='foo')}, 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_core', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nice assistant.', 'template_format': 'f-string', 'partial_variables': {}}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', '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_core', 'prompt_values', 'ChatPromptValue'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'messages', 'system', 'SystemMessage'], 'kwargs': {'content': 'You are a nice assistant.', 'additional_kwargs': {}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'messages', 'human', 'HumanMessage'], 'kwargs': {'content': 'What is your name?', 'additional_kwargs': {}}}]}}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:1'], 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'], '_type': 'fake-list-chat-model', 'stop': None}, 'options': {'stop': None}}, error=None, serialized={'lc': 1, 'type': 'not_implemented', 'id': ['tests', 'unit_tests', 'fake', 'chat_model', 'FakeListChatModel'], 'repr': "FakeListChatModel(responses=['foo'])"}, 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', 'generation_info': None, 'type': 'ChatGeneration', 'message': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'messages', 'ai', 'AIMessage'], 'kwargs': {'content': 'foo'}}}]], 'llm_output': None, 'run': None}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:2'], execution_order=None, child_execution_order=None, child_runs=[])]),
   ])
 # ---
 # name: test_prompt_with_llm
@@ -1393,13 +1393,13 @@
 # ---
 # name: test_prompt_with_llm.1
   list([
-    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_core', 'runnables', 'RunnableSequence'], 'kwargs': {'first': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nice assistant.', 'template_format': 'f-string', 'partial_variables': {}}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': ['question'], 'template': '{question}', 'template_format': 'f-string', 'partial_variables': {}}}}}], 'input_variables': ['question']}}, 'last': {'lc': 1, 'type': 'not_implemented', 'id': ['tests', 'unit_tests', 'fake', 'llm', 'FakeListLLM'], 'repr': "FakeListLLM(responses=['foo', 'bar'])"}}}, 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': 'foo'}, 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_core', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nice assistant.', 'template_format': 'f-string', 'partial_variables': {}}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', '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_core', 'prompts', 'chat', 'ChatPromptValue'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'messages', 'system', 'SystemMessage'], 'kwargs': {'content': 'You are a nice assistant.', 'additional_kwargs': {}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'messages', 'human', 'HumanMessage'], 'kwargs': {'content': 'What is your name?', 'additional_kwargs': {}}}]}}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:1'], execution_order=None, child_execution_order=None, child_runs=[]), Run(id=UUID('00000000-0000-4000-8000-000000000002'), name='FakeListLLM', 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', 'stop': None}, 'options': {'stop': None}}, error=None, serialized={'lc': 1, 'type': 'not_implemented', 'id': ['tests', 'unit_tests', 'fake', 'llm', 'FakeListLLM'], 'repr': "FakeListLLM(responses=['foo', 'bar'])"}, 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', 'generation_info': None, 'type': 'Generation'}]], 'llm_output': None, 'run': None}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:2'], execution_order=None, child_execution_order=None, child_runs=[])]),
+    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_core', 'runnables', 'RunnableSequence'], 'kwargs': {'first': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nice assistant.', 'template_format': 'f-string', 'partial_variables': {}}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': ['question'], 'template': '{question}', 'template_format': 'f-string', 'partial_variables': {}}}}}], 'input_variables': ['question']}}, 'last': {'lc': 1, 'type': 'not_implemented', 'id': ['tests', 'unit_tests', 'fake', 'llm', 'FakeListLLM'], 'repr': "FakeListLLM(responses=['foo', 'bar'])"}}}, 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': 'foo'}, 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_core', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nice assistant.', 'template_format': 'f-string', 'partial_variables': {}}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', '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_core', 'prompt_values', 'ChatPromptValue'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'messages', 'system', 'SystemMessage'], 'kwargs': {'content': 'You are a nice assistant.', 'additional_kwargs': {}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'messages', 'human', 'HumanMessage'], 'kwargs': {'content': 'What is your name?', 'additional_kwargs': {}}}]}}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:1'], execution_order=None, child_execution_order=None, child_runs=[]), Run(id=UUID('00000000-0000-4000-8000-000000000002'), name='FakeListLLM', 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', 'stop': None}, 'options': {'stop': None}}, error=None, serialized={'lc': 1, 'type': 'not_implemented', 'id': ['tests', 'unit_tests', 'fake', 'llm', 'FakeListLLM'], 'repr': "FakeListLLM(responses=['foo', 'bar'])"}, 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', 'generation_info': None, 'type': 'Generation'}]], 'llm_output': None, 'run': None}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:2'], execution_order=None, child_execution_order=None, child_runs=[])]),
   ])
 # ---
 # name: test_prompt_with_llm.2
   list([
-    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_core', 'runnables', 'RunnableSequence'], 'kwargs': {'first': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nice assistant.', 'template_format': 'f-string', 'partial_variables': {}}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': ['question'], 'template': '{question}', 'template_format': 'f-string', 'partial_variables': {}}}}}], 'input_variables': ['question']}}, 'last': {'lc': 1, 'type': 'not_implemented', 'id': ['tests', 'unit_tests', 'fake', 'llm', 'FakeListLLM'], 'repr': "FakeListLLM(responses=['foo', 'bar'], i=1)"}}}, 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': 'bar'}, 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_core', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nice assistant.', 'template_format': 'f-string', 'partial_variables': {}}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', '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_core', 'prompts', 'chat', 'ChatPromptValue'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'messages', 'system', 'SystemMessage'], 'kwargs': {'content': 'You are a nice assistant.', 'additional_kwargs': {}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'messages', 'human', 'HumanMessage'], 'kwargs': {'content': 'What is your name?', 'additional_kwargs': {}}}]}}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:1'], execution_order=None, child_execution_order=None, child_runs=[]), Run(id=UUID('00000000-0000-4000-8000-000000000002'), name='FakeListLLM', 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', 'stop': None}, 'options': {'stop': None}}, error=None, serialized={'lc': 1, 'type': 'not_implemented', 'id': ['tests', 'unit_tests', 'fake', 'llm', 'FakeListLLM'], 'repr': "FakeListLLM(responses=['foo', 'bar'], i=1)"}, 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': 'bar', 'generation_info': None, 'type': 'Generation'}]], 'llm_output': None, 'run': None}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:2'], execution_order=None, child_execution_order=None, child_runs=[])]),
-    Run(id=UUID('00000000-0000-4000-8000-000000000003'), 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_core', 'runnables', 'RunnableSequence'], 'kwargs': {'first': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nice assistant.', 'template_format': 'f-string', 'partial_variables': {}}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': ['question'], 'template': '{question}', 'template_format': 'f-string', 'partial_variables': {}}}}}], 'input_variables': ['question']}}, 'last': {'lc': 1, 'type': 'not_implemented', 'id': ['tests', 'unit_tests', 'fake', 'llm', 'FakeListLLM'], 'repr': "FakeListLLM(responses=['foo', 'bar'], i=1)"}}}, events=[{'name': 'start', 'time': FakeDatetime(2023, 1, 1, 0, 0)}, {'name': 'end', 'time': FakeDatetime(2023, 1, 1, 0, 0)}], inputs={'question': 'What is your favorite color?'}, outputs={'output': 'foo'}, reference_example_id=None, parent_run_id=None, tags=[], execution_order=None, child_execution_order=None, child_runs=[Run(id=UUID('00000000-0000-4000-8000-000000000004'), 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_core', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nice assistant.', 'template_format': 'f-string', 'partial_variables': {}}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', '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 favorite color?'}, outputs={'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'ChatPromptValue'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'messages', 'system', 'SystemMessage'], 'kwargs': {'content': 'You are a nice assistant.', 'additional_kwargs': {}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'messages', 'human', 'HumanMessage'], 'kwargs': {'content': 'What is your favorite color?', 'additional_kwargs': {}}}]}}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000003'), tags=['seq:step:1'], execution_order=None, child_execution_order=None, child_runs=[]), Run(id=UUID('00000000-0000-4000-8000-000000000005'), name='FakeListLLM', 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', 'stop': None}, 'options': {'stop': None}}, error=None, serialized={'lc': 1, 'type': 'not_implemented', 'id': ['tests', 'unit_tests', 'fake', 'llm', 'FakeListLLM'], 'repr': "FakeListLLM(responses=['foo', 'bar'], i=1)"}, 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 favorite color?']}, outputs={'generations': [[{'text': 'foo', 'generation_info': None, 'type': 'Generation'}]], 'llm_output': None, 'run': None}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000003'), tags=['seq:step:2'], execution_order=None, child_execution_order=None, child_runs=[])]),
+    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_core', 'runnables', 'RunnableSequence'], 'kwargs': {'first': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nice assistant.', 'template_format': 'f-string', 'partial_variables': {}}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': ['question'], 'template': '{question}', 'template_format': 'f-string', 'partial_variables': {}}}}}], 'input_variables': ['question']}}, 'last': {'lc': 1, 'type': 'not_implemented', 'id': ['tests', 'unit_tests', 'fake', 'llm', 'FakeListLLM'], 'repr': "FakeListLLM(responses=['foo', 'bar'], i=1)"}}}, 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': 'bar'}, 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_core', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nice assistant.', 'template_format': 'f-string', 'partial_variables': {}}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', '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_core', 'prompt_values', 'ChatPromptValue'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'messages', 'system', 'SystemMessage'], 'kwargs': {'content': 'You are a nice assistant.', 'additional_kwargs': {}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'messages', 'human', 'HumanMessage'], 'kwargs': {'content': 'What is your name?', 'additional_kwargs': {}}}]}}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:1'], execution_order=None, child_execution_order=None, child_runs=[]), Run(id=UUID('00000000-0000-4000-8000-000000000002'), name='FakeListLLM', 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', 'stop': None}, 'options': {'stop': None}}, error=None, serialized={'lc': 1, 'type': 'not_implemented', 'id': ['tests', 'unit_tests', 'fake', 'llm', 'FakeListLLM'], 'repr': "FakeListLLM(responses=['foo', 'bar'], i=1)"}, 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': 'bar', 'generation_info': None, 'type': 'Generation'}]], 'llm_output': None, 'run': None}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:2'], execution_order=None, child_execution_order=None, child_runs=[])]),
+    Run(id=UUID('00000000-0000-4000-8000-000000000003'), 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_core', 'runnables', 'RunnableSequence'], 'kwargs': {'first': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nice assistant.', 'template_format': 'f-string', 'partial_variables': {}}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': ['question'], 'template': '{question}', 'template_format': 'f-string', 'partial_variables': {}}}}}], 'input_variables': ['question']}}, 'last': {'lc': 1, 'type': 'not_implemented', 'id': ['tests', 'unit_tests', 'fake', 'llm', 'FakeListLLM'], 'repr': "FakeListLLM(responses=['foo', 'bar'], i=1)"}}}, events=[{'name': 'start', 'time': FakeDatetime(2023, 1, 1, 0, 0)}, {'name': 'end', 'time': FakeDatetime(2023, 1, 1, 0, 0)}], inputs={'question': 'What is your favorite color?'}, outputs={'output': 'foo'}, reference_example_id=None, parent_run_id=None, tags=[], execution_order=None, child_execution_order=None, child_runs=[Run(id=UUID('00000000-0000-4000-8000-000000000004'), 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_core', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nice assistant.', 'template_format': 'f-string', 'partial_variables': {}}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', '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 favorite color?'}, outputs={'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompt_values', 'ChatPromptValue'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'messages', 'system', 'SystemMessage'], 'kwargs': {'content': 'You are a nice assistant.', 'additional_kwargs': {}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'messages', 'human', 'HumanMessage'], 'kwargs': {'content': 'What is your favorite color?', 'additional_kwargs': {}}}]}}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000003'), tags=['seq:step:1'], execution_order=None, child_execution_order=None, child_runs=[]), Run(id=UUID('00000000-0000-4000-8000-000000000005'), name='FakeListLLM', 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', 'stop': None}, 'options': {'stop': None}}, error=None, serialized={'lc': 1, 'type': 'not_implemented', 'id': ['tests', 'unit_tests', 'fake', 'llm', 'FakeListLLM'], 'repr': "FakeListLLM(responses=['foo', 'bar'], i=1)"}, 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 favorite color?']}, outputs={'generations': [[{'text': 'foo', 'generation_info': None, 'type': 'Generation'}]], 'llm_output': None, 'run': None}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000003'), tags=['seq:step:2'], execution_order=None, child_execution_order=None, child_runs=[])]),
   ])
 # ---
 # name: test_prompt_with_llm_and_async_lambda
@@ -1519,7 +1519,7 @@
 # ---
 # name: test_prompt_with_llm_and_async_lambda.1
   list([
-    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_core', 'runnables', 'RunnableSequence'], 'kwargs': {'first': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nice assistant.', 'template_format': 'f-string', 'partial_variables': {}}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', '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': ['tests', 'unit_tests', 'fake', 'llm', 'FakeListLLM'], 'repr': "FakeListLLM(responses=['foo', 'bar'])"}], 'last': {'lc': 1, 'type': 'not_implemented', 'id': ['langchain_core', 'runnables', 'base', 'RunnableLambda'], 'repr': 'RunnableLambda(afunc=...)'}}}, 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': 'foo'}, 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_core', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nice assistant.', 'template_format': 'f-string', 'partial_variables': {}}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', '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_core', 'prompts', 'chat', 'ChatPromptValue'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'messages', 'system', 'SystemMessage'], 'kwargs': {'content': 'You are a nice assistant.', 'additional_kwargs': {}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'messages', 'human', 'HumanMessage'], 'kwargs': {'content': 'What is your name?', 'additional_kwargs': {}}}]}}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:1'], execution_order=None, child_execution_order=None, child_runs=[]), Run(id=UUID('00000000-0000-4000-8000-000000000002'), name='FakeListLLM', 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', 'stop': None}, 'options': {'stop': None}}, error=None, serialized={'lc': 1, 'type': 'not_implemented', 'id': ['tests', 'unit_tests', 'fake', 'llm', 'FakeListLLM'], 'repr': "FakeListLLM(responses=['foo', 'bar'])"}, 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', 'generation_info': None, 'type': 'Generation'}]], 'llm_output': None, 'run': None}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:2'], execution_order=None, child_execution_order=None, child_runs=[]), Run(id=UUID('00000000-0000-4000-8000-000000000003'), name='passthrough', 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_core', 'runnables', 'base', 'RunnableLambda'], 'repr': 'RunnableLambda(afunc=...)'}, events=[{'name': 'start', 'time': FakeDatetime(2023, 1, 1, 0, 0)}, {'name': 'end', 'time': FakeDatetime(2023, 1, 1, 0, 0)}], inputs={'input': 'foo'}, outputs={'output': 'foo'}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:3'], execution_order=None, child_execution_order=None, child_runs=[])]),
+    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_core', 'runnables', 'RunnableSequence'], 'kwargs': {'first': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nice assistant.', 'template_format': 'f-string', 'partial_variables': {}}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', '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': ['tests', 'unit_tests', 'fake', 'llm', 'FakeListLLM'], 'repr': "FakeListLLM(responses=['foo', 'bar'])"}], 'last': {'lc': 1, 'type': 'not_implemented', 'id': ['langchain_core', 'runnables', 'base', 'RunnableLambda'], 'repr': 'RunnableLambda(afunc=...)'}}}, 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': 'foo'}, 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_core', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nice assistant.', 'template_format': 'f-string', 'partial_variables': {}}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', '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_core', 'prompt_values', 'ChatPromptValue'], 'kwargs': {'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'messages', 'system', 'SystemMessage'], 'kwargs': {'content': 'You are a nice assistant.', 'additional_kwargs': {}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain_core', 'messages', 'human', 'HumanMessage'], 'kwargs': {'content': 'What is your name?', 'additional_kwargs': {}}}]}}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:1'], execution_order=None, child_execution_order=None, child_runs=[]), Run(id=UUID('00000000-0000-4000-8000-000000000002'), name='FakeListLLM', 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', 'stop': None}, 'options': {'stop': None}}, error=None, serialized={'lc': 1, 'type': 'not_implemented', 'id': ['tests', 'unit_tests', 'fake', 'llm', 'FakeListLLM'], 'repr': "FakeListLLM(responses=['foo', 'bar'])"}, 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', 'generation_info': None, 'type': 'Generation'}]], 'llm_output': None, 'run': None}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:2'], execution_order=None, child_execution_order=None, child_runs=[]), Run(id=UUID('00000000-0000-4000-8000-000000000003'), name='passthrough', 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_core', 'runnables', 'base', 'RunnableLambda'], 'repr': 'RunnableLambda(afunc=...)'}, events=[{'name': 'start', 'time': FakeDatetime(2023, 1, 1, 0, 0)}, {'name': 'end', 'time': FakeDatetime(2023, 1, 1, 0, 0)}], inputs={'input': 'foo'}, outputs={'output': 'foo'}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:3'], execution_order=None, child_execution_order=None, child_runs=[])]),
   ])
 # ---
 # name: test_router_runnable
diff --git a/libs/core/tests/unit_tests/runnables/test_imports.py b/libs/core/tests/unit_tests/runnables/test_imports.py
new file mode 100644
index 00000000000..bd873ff57b5
--- /dev/null
+++ b/libs/core/tests/unit_tests/runnables/test_imports.py
@@ -0,0 +1,28 @@
+from langchain_core.runnables import __all__
+
+EXPECTED_ALL = [
+    "ConfigurableField",
+    "ConfigurableFieldSingleOption",
+    "ConfigurableFieldMultiOption",
+    "patch_config",
+    "RouterInput",
+    "RouterRunnable",
+    "Runnable",
+    "RunnableSerializable",
+    "RunnableBinding",
+    "RunnableBranch",
+    "RunnableConfig",
+    "RunnableGenerator",
+    "RunnableLambda",
+    "RunnableMap",
+    "RunnableParallel",
+    "RunnablePassthrough",
+    "RunnableSequence",
+    "RunnableWithFallbacks",
+    "get_config_list",
+    "add",
+]
+
+
+def test_all_imports() -> None:
+    assert set(__all__) == set(EXPECTED_ALL)
diff --git a/libs/core/tests/unit_tests/runnables/test_runnable.py b/libs/core/tests/unit_tests/runnables/test_runnable.py
index f1f591db497..6db36b5f57d 100644
--- a/libs/core/tests/unit_tests/runnables/test_runnable.py
+++ b/libs/core/tests/unit_tests/runnables/test_runnable.py
@@ -23,7 +23,6 @@ from typing_extensions import TypedDict
 from langchain_core.callbacks.manager import (
     Callbacks,
     atrace_as_chain_group,
-    collect_runs,
     trace_as_chain_group,
 )
 from langchain_core.documents import Document
@@ -39,13 +38,12 @@ from langchain_core.output_parsers import (
     CommaSeparatedListOutputParser,
     StrOutputParser,
 )
+from langchain_core.prompt_values import ChatPromptValue, StringPromptValue
 from langchain_core.prompts import (
     ChatPromptTemplate,
-    ChatPromptValue,
     HumanMessagePromptTemplate,
     MessagesPlaceholder,
     PromptTemplate,
-    StringPromptValue,
     SystemMessagePromptTemplate,
 )
 from langchain_core.pydantic_v1 import BaseModel
@@ -75,6 +73,7 @@ from langchain_core.tracers import (
     RunLog,
     RunLogPatch,
 )
+from langchain_core.tracers.context import collect_runs
 from tests.unit_tests.fake.chat_model import FakeListChatModel
 from tests.unit_tests.fake.llm import FakeListLLM, FakeStreamingListLLM
 
diff --git a/libs/core/tests/unit_tests/tracers/test_imports.py b/libs/core/tests/unit_tests/tracers/test_imports.py
new file mode 100644
index 00000000000..89e34793a53
--- /dev/null
+++ b/libs/core/tests/unit_tests/tracers/test_imports.py
@@ -0,0 +1,15 @@
+from langchain_core.tracers import __all__
+
+EXPECTED_ALL = [
+    "BaseTracer",
+    "EvaluatorCallbackHandler",
+    "LangChainTracer",
+    "ConsoleCallbackHandler",
+    "Run",
+    "RunLog",
+    "RunLogPatch",
+]
+
+
+def test_all_imports() -> None:
+    assert set(__all__) == set(EXPECTED_ALL)
diff --git a/libs/langchain/tests/unit_tests/callbacks/test_run_collector.py b/libs/core/tests/unit_tests/tracers/test_run_collector.py
similarity index 66%
rename from libs/langchain/tests/unit_tests/callbacks/test_run_collector.py
rename to libs/core/tests/unit_tests/tracers/test_run_collector.py
index 9fd031b7a82..bdbfc3c4d94 100644
--- a/libs/langchain/tests/unit_tests/callbacks/test_run_collector.py
+++ b/libs/core/tests/unit_tests/tracers/test_run_collector.py
@@ -2,12 +2,12 @@
 
 import uuid
 
-from langchain.callbacks import collect_runs
-from tests.unit_tests.llms.fake_llm import FakeLLM
+from langchain_core.tracers.context import collect_runs
+from tests.unit_tests.fake.llm import FakeListLLM
 
 
 def test_collect_runs() -> None:
-    llm = FakeLLM(queries={"hi": "hello"}, sequential_responses=True)
+    llm = FakeListLLM(responses=["hello"])
     with collect_runs() as cb:
         llm.predict("hi")
         assert cb.traced_runs
diff --git a/libs/experimental/langchain_experimental/comprehend_moderation/base_moderation.py b/libs/experimental/langchain_experimental/comprehend_moderation/base_moderation.py
index 9b97a42a00d..b9006d002b7 100644
--- a/libs/experimental/langchain_experimental/comprehend_moderation/base_moderation.py
+++ b/libs/experimental/langchain_experimental/comprehend_moderation/base_moderation.py
@@ -2,9 +2,8 @@ import uuid
 from typing import Any, Callable, Optional
 
 from langchain.callbacks.manager import CallbackManagerForChainRun
-from langchain.prompts.base import StringPromptValue
-from langchain.prompts.chat import ChatPromptValue
 from langchain.schema import AIMessage, HumanMessage
+from langchain_core.prompt_values import ChatPromptValue, StringPromptValue
 
 from langchain_experimental.comprehend_moderation.pii import ComprehendPII
 from langchain_experimental.comprehend_moderation.prompt_safety import (
diff --git a/libs/langchain/langchain/callbacks/manager.py b/libs/langchain/langchain/callbacks/manager.py
index bcd7bbd9610..81b3983e1c0 100644
--- a/libs/langchain/langchain/callbacks/manager.py
+++ b/libs/langchain/langchain/callbacks/manager.py
@@ -29,14 +29,16 @@ from langchain_core.callbacks.manager import (
     RunManager,
     ahandle_event,
     atrace_as_chain_group,
-    collect_runs,
-    env_var_is_set,
     handle_event,
-    register_configure_hook,
     trace_as_chain_group,
+)
+from langchain_core.tracers.context import (
+    collect_runs,
+    register_configure_hook,
     tracing_enabled,
     tracing_v2_enabled,
 )
+from langchain_core.utils.env import env_var_is_set
 
 from langchain.callbacks.openai_info import OpenAICallbackHandler
 from langchain.callbacks.tracers.wandb import WandbTracer
@@ -122,6 +124,6 @@ __all__ = [
     "trace_as_chain_group",
     "handle_event",
     "ahandle_event",
-    "env_var_is_set",
     "Callbacks",
+    "env_var_is_set",
 ]
diff --git a/libs/langchain/langchain/chains/llm.py b/libs/langchain/langchain/chains/llm.py
index 784de73a345..b7023dbc6a1 100644
--- a/libs/langchain/langchain/chains/llm.py
+++ b/libs/langchain/langchain/chains/llm.py
@@ -12,8 +12,8 @@ from langchain_core.load.dump import dumpd
 from langchain_core.messages import BaseMessage
 from langchain_core.output_parsers import BaseLLMOutputParser, StrOutputParser
 from langchain_core.outputs import ChatGeneration, Generation, LLMResult
-from langchain_core.prompts import BasePromptTemplate, PromptValue
-from langchain_core.prompts.prompt import PromptTemplate
+from langchain_core.prompt_values import PromptValue
+from langchain_core.prompts import BasePromptTemplate, PromptTemplate
 from langchain_core.pydantic_v1 import Extra, Field
 from langchain_core.runnables import (
     Runnable,
diff --git a/libs/langchain/langchain/chat_models/anthropic.py b/libs/langchain/langchain/chat_models/anthropic.py
index 4a2a77ef9ac..c9b396191e0 100644
--- a/libs/langchain/langchain/chat_models/anthropic.py
+++ b/libs/langchain/langchain/chat_models/anthropic.py
@@ -9,7 +9,7 @@ from langchain_core.messages import (
     SystemMessage,
 )
 from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult
-from langchain_core.prompts import PromptValue
+from langchain_core.prompt_values import PromptValue
 
 from langchain.callbacks.manager import (
     AsyncCallbackManagerForLLMRun,
diff --git a/libs/langchain/langchain/llms/anthropic.py b/libs/langchain/langchain/llms/anthropic.py
index ecf0df02568..619631c4ce7 100644
--- a/libs/langchain/langchain/llms/anthropic.py
+++ b/libs/langchain/langchain/llms/anthropic.py
@@ -13,7 +13,7 @@ from typing import (
 
 from langchain_core.language_models import BaseLanguageModel
 from langchain_core.outputs import GenerationChunk
-from langchain_core.prompts import PromptValue
+from langchain_core.prompt_values import PromptValue
 from langchain_core.pydantic_v1 import Field, SecretStr, root_validator
 from langchain_core.utils import (
     check_package_version,
diff --git a/libs/langchain/langchain/output_parsers/retry.py b/libs/langchain/langchain/output_parsers/retry.py
index 25b3a916955..6c10caaf23e 100644
--- a/libs/langchain/langchain/output_parsers/retry.py
+++ b/libs/langchain/langchain/output_parsers/retry.py
@@ -5,8 +5,8 @@ from typing import Any, TypeVar
 from langchain_core.exceptions import OutputParserException
 from langchain_core.language_models import BaseLanguageModel
 from langchain_core.output_parsers import BaseOutputParser
-from langchain_core.prompts import BasePromptTemplate, PromptValue
-from langchain_core.prompts.prompt import PromptTemplate
+from langchain_core.prompt_values import PromptValue
+from langchain_core.prompts import BasePromptTemplate, PromptTemplate
 
 NAIVE_COMPLETION_RETRY = """Prompt:
 {prompt}
diff --git a/libs/langchain/langchain/prompts/base.py b/libs/langchain/langchain/prompts/base.py
index a535e905a6a..7c20569823c 100644
--- a/libs/langchain/langchain/prompts/base.py
+++ b/libs/langchain/langchain/prompts/base.py
@@ -1,7 +1,6 @@
-from langchain_core.prompts import BasePromptTemplate
-from langchain_core.prompts.base import (
+from langchain_core.prompts import (
+    BasePromptTemplate,
     StringPromptTemplate,
-    StringPromptValue,
     check_valid_template,
     get_template_variables,
     jinja2_formatter,
@@ -13,7 +12,6 @@ __all__ = [
     "validate_jinja2",
     "check_valid_template",
     "get_template_variables",
-    "StringPromptValue",
     "StringPromptTemplate",
     "BasePromptTemplate",
 ]
diff --git a/libs/langchain/langchain/prompts/chat.py b/libs/langchain/langchain/prompts/chat.py
index fc965d11204..c44c196cf47 100644
--- a/libs/langchain/langchain/prompts/chat.py
+++ b/libs/langchain/langchain/prompts/chat.py
@@ -5,8 +5,6 @@ from langchain_core.prompts.chat import (
     BaseStringMessagePromptTemplate,
     ChatMessagePromptTemplate,
     ChatPromptTemplate,
-    ChatPromptValue,
-    ChatPromptValueConcrete,
     HumanMessagePromptTemplate,
     MessagesPlaceholder,
     SystemMessagePromptTemplate,
@@ -20,8 +18,6 @@ __all__ = [
     "HumanMessagePromptTemplate",
     "AIMessagePromptTemplate",
     "SystemMessagePromptTemplate",
-    "ChatPromptValue",
-    "ChatPromptValueConcrete",
     "BaseChatPromptTemplate",
     "ChatPromptTemplate",
 ]
diff --git a/libs/langchain/langchain/schema/__init__.py b/libs/langchain/langchain/schema/__init__.py
index 59eead3ba3f..8876b71bcd2 100644
--- a/libs/langchain/langchain/schema/__init__.py
+++ b/libs/langchain/langchain/schema/__init__.py
@@ -31,12 +31,16 @@ from langchain_core.outputs import (
     LLMResult,
     RunInfo,
 )
-from langchain_core.prompts import BasePromptTemplate, PromptValue, format_document
+from langchain_core.prompt_values import PromptValue
+from langchain_core.prompts import BasePromptTemplate, format_document
 from langchain_core.retrievers import BaseRetriever
 from langchain_core.stores import BaseStore
 
 RUN_KEY = "__run"
+
+# Backwards compatibility.
 Memory = BaseMemory
+_message_to_dict = message_to_dict
 
 __all__ = [
     "BaseCache",
@@ -56,6 +60,7 @@ __all__ = [
     "messages_from_dict",
     "messages_to_dict",
     "message_to_dict",
+    "_message_to_dict",
     "_message_from_dict",
     "get_buffer_string",
     "RunInfo",
diff --git a/libs/langchain/langchain/schema/callbacks/manager.py b/libs/langchain/langchain/schema/callbacks/manager.py
index 71e967faf2d..a459e1bb697 100644
--- a/libs/langchain/langchain/schema/callbacks/manager.py
+++ b/libs/langchain/langchain/schema/callbacks/manager.py
@@ -16,14 +16,16 @@ from langchain_core.callbacks.manager import (
     CallbackManagerForToolRun,
     ParentRunManager,
     RunManager,
-    collect_runs,
-    env_var_is_set,
     handle_event,
-    register_configure_hook,
     trace_as_chain_group,
+)
+from langchain_core.tracers.context import (
+    collect_runs,
+    register_configure_hook,
     tracing_enabled,
     tracing_v2_enabled,
 )
+from langchain_core.utils.env import env_var_is_set
 
 __all__ = [
     "tracing_enabled",
@@ -48,6 +50,6 @@ __all__ = [
     "CallbackManagerForChainGroup",
     "AsyncCallbackManager",
     "AsyncCallbackManagerForChainGroup",
-    "env_var_is_set",
     "register_configure_hook",
+    "env_var_is_set",
 ]
diff --git a/libs/langchain/langchain/schema/document.py b/libs/langchain/langchain/schema/document.py
index 8b5b254be95..b426b47b189 100644
--- a/libs/langchain/langchain/schema/document.py
+++ b/libs/langchain/langchain/schema/document.py
@@ -1,3 +1,4 @@
-from langchain_core.documents import BaseDocumentTransformer, Document
+from langchain_core.document_transformers import BaseDocumentTransformer
+from langchain_core.documents import Document
 
 __all__ = ["Document", "BaseDocumentTransformer"]
diff --git a/libs/langchain/langchain/schema/language_model.py b/libs/langchain/langchain/schema/language_model.py
index f03ee8279f2..e10ab8f92ff 100644
--- a/libs/langchain/langchain/schema/language_model.py
+++ b/libs/langchain/langchain/schema/language_model.py
@@ -1,3 +1,4 @@
 from langchain_core.language_models import BaseLanguageModel, get_tokenizer
+from langchain_core.language_models.base import _get_token_ids_default_method
 
-__all__ = ["get_tokenizer", "BaseLanguageModel"]
+__all__ = ["get_tokenizer", "BaseLanguageModel", "_get_token_ids_default_method"]
diff --git a/libs/langchain/langchain/schema/messages.py b/libs/langchain/langchain/schema/messages.py
index 7aa60748ecc..de1f3270d6d 100644
--- a/libs/langchain/langchain/schema/messages.py
+++ b/libs/langchain/langchain/schema/messages.py
@@ -13,12 +13,17 @@ from langchain_core.messages import (
     SystemMessageChunk,
     ToolMessage,
     ToolMessageChunk,
+    _message_from_dict,
     get_buffer_string,
     merge_content,
+    message_to_dict,
     messages_from_dict,
     messages_to_dict,
 )
 
+# Backwards compatibility.
+_message_to_dict = message_to_dict
+
 __all__ = [
     "get_buffer_string",
     "BaseMessage",
@@ -38,4 +43,7 @@ __all__ = [
     "ChatMessageChunk",
     "messages_to_dict",
     "messages_from_dict",
+    "_message_to_dict",
+    "_message_from_dict",
+    "message_to_dict",
 ]
diff --git a/libs/langchain/langchain/schema/output_parser.py b/libs/langchain/langchain/schema/output_parser.py
index c29648059c5..60f9e488ec8 100644
--- a/libs/langchain/langchain/schema/output_parser.py
+++ b/libs/langchain/langchain/schema/output_parser.py
@@ -1,19 +1,23 @@
+from langchain_core.exceptions import OutputParserException
 from langchain_core.output_parsers import (
     BaseCumulativeTransformOutputParser,
     BaseGenerationOutputParser,
     BaseLLMOutputParser,
     BaseOutputParser,
     BaseTransformOutputParser,
-    OutputParserException,
     StrOutputParser,
 )
 
+# Backwards compatibility.
+NoOpOutputParser = StrOutputParser
+
 __all__ = [
     "BaseLLMOutputParser",
     "BaseGenerationOutputParser",
     "BaseOutputParser",
     "BaseTransformOutputParser",
     "BaseCumulativeTransformOutputParser",
+    "NoOpOutputParser",
     "StrOutputParser",
     "OutputParserException",
 ]
diff --git a/libs/langchain/langchain/schema/prompt.py b/libs/langchain/langchain/schema/prompt.py
index 25564c2f076..8b3e3c44451 100644
--- a/libs/langchain/langchain/schema/prompt.py
+++ b/libs/langchain/langchain/schema/prompt.py
@@ -1,3 +1,3 @@
-from langchain_core.prompts import PromptValue
+from langchain_core.prompt_values import PromptValue
 
 __all__ = ["PromptValue"]
diff --git a/libs/langchain/langchain/schema/runnable/base.py b/libs/langchain/langchain/schema/runnable/base.py
index 201c1a2c816..2fc618ec639 100644
--- a/libs/langchain/langchain/schema/runnable/base.py
+++ b/libs/langchain/langchain/schema/runnable/base.py
@@ -12,6 +12,9 @@ from langchain_core.runnables.base import (
     coerce_to_runnable,
 )
 
+# Backwards compatibility.
+RunnableMap = RunnableParallel
+
 __all__ = [
     "Runnable",
     "RunnableSerializable",
@@ -23,5 +26,6 @@ __all__ = [
     "RunnableEach",
     "RunnableBindingBase",
     "RunnableBinding",
+    "RunnableMap",
     "coerce_to_runnable",
 ]
diff --git a/libs/langchain/langchain/schema/runnable/config.py b/libs/langchain/langchain/schema/runnable/config.py
index 0906d862cf3..af0179f9755 100644
--- a/libs/langchain/langchain/schema/runnable/config.py
+++ b/libs/langchain/langchain/schema/runnable/config.py
@@ -1,6 +1,7 @@
 from langchain_core.runnables.config import (
     EmptyDict,
     RunnableConfig,
+    acall_func_with_variable_args,
     call_func_with_variable_args,
     ensure_config,
     get_async_callback_manager_for_config,
@@ -18,6 +19,7 @@ __all__ = [
     "get_config_list",
     "patch_config",
     "merge_configs",
+    "acall_func_with_variable_args",
     "call_func_with_variable_args",
     "get_callback_manager_for_config",
     "get_async_callback_manager_for_config",
diff --git a/libs/langchain/langchain/schema/runnable/passthrough.py b/libs/langchain/langchain/schema/runnable/passthrough.py
index 81141a7d363..aed683d3843 100644
--- a/libs/langchain/langchain/schema/runnable/passthrough.py
+++ b/libs/langchain/langchain/schema/runnable/passthrough.py
@@ -1,7 +1,8 @@
 from langchain_core.runnables.passthrough import (
     RunnableAssign,
     RunnablePassthrough,
+    aidentity,
     identity,
 )
 
-__all__ = ["identity", "RunnablePassthrough", "RunnableAssign"]
+__all__ = ["aidentity", "identity", "RunnablePassthrough", "RunnableAssign"]
diff --git a/libs/langchain/langchain/schema/runnable/utils.py b/libs/langchain/langchain/schema/runnable/utils.py
index 020d23f5469..de3fbc616f7 100644
--- a/libs/langchain/langchain/schema/runnable/utils.py
+++ b/libs/langchain/langchain/schema/runnable/utils.py
@@ -8,9 +8,12 @@ from langchain_core.runnables.utils import (
     IsFunctionArgDict,
     IsLocalDict,
     SupportsAdd,
+    aadd,
     accepts_config,
     accepts_run_manager,
     add,
+    gated_coro,
+    gather_with_concurrency,
     get_function_first_arg_dict_keys,
     get_lambda_source,
     get_unique_config_specs,
@@ -34,4 +37,7 @@ __all__ = [
     "ConfigurableFieldMultiOption",
     "ConfigurableFieldSpec",
     "get_unique_config_specs",
+    "aadd",
+    "gated_coro",
+    "gather_with_concurrency",
 ]
diff --git a/libs/langchain/poetry.lock b/libs/langchain/poetry.lock
index f0091f29d8e..9aa8d341702 100644
--- a/libs/langchain/poetry.lock
+++ b/libs/langchain/poetry.lock
@@ -4128,13 +4128,13 @@ tests = ["pandas (>=1.4)", "pytest", "pytest-asyncio", "pytest-mock"]
 
 [[package]]
 name = "langchain-core"
-version = "0.0.1"
+version = "0.0.2"
 description = "Building applications with LLMs through composability"
 optional = false
 python-versions = ">=3.8.1,<4.0"
 files = [
-    {file = "langchain_core-0.0.1-py3-none-any.whl", hash = "sha256:cad923dd3bc39cd9fe24b9d6a9799c97719aeaafc9b19509fe1347109fcb65b3"},
-    {file = "langchain_core-0.0.1.tar.gz", hash = "sha256:488b72223e14849bf9588ed677a999b282904d1d5e1f81d12767ee1024220724"},
+    {file = "langchain_core-0.0.2-py3-none-any.whl", hash = "sha256:dd448c7887c24105761a0763bee5ec5b072de905b4fbd83d693e7a181fd63208"},
+    {file = "langchain_core-0.0.2.tar.gz", hash = "sha256:772600dfe3e707adb9055ed96797763b0de32b394eac8325bf609a7e5929dda2"},
 ]
 
 [package.dependencies]
@@ -6515,6 +6515,8 @@ files = [
     {file = "psycopg2-2.9.9-cp310-cp310-win_amd64.whl", hash = "sha256:426f9f29bde126913a20a96ff8ce7d73fd8a216cfb323b1f04da402d452853c3"},
     {file = "psycopg2-2.9.9-cp311-cp311-win32.whl", hash = "sha256:ade01303ccf7ae12c356a5e10911c9e1c51136003a9a1d92f7aa9d010fb98372"},
     {file = "psycopg2-2.9.9-cp311-cp311-win_amd64.whl", hash = "sha256:121081ea2e76729acfb0673ff33755e8703d45e926e416cb59bae3a86c6a4981"},
+    {file = "psycopg2-2.9.9-cp312-cp312-win32.whl", hash = "sha256:d735786acc7dd25815e89cc4ad529a43af779db2e25aa7c626de864127e5a024"},
+    {file = "psycopg2-2.9.9-cp312-cp312-win_amd64.whl", hash = "sha256:a7653d00b732afb6fc597e29c50ad28087dcb4fbfb28e86092277a559ae4e693"},
     {file = "psycopg2-2.9.9-cp37-cp37m-win32.whl", hash = "sha256:5e0d98cade4f0e0304d7d6f25bbfbc5bd186e07b38eac65379309c4ca3193efa"},
     {file = "psycopg2-2.9.9-cp37-cp37m-win_amd64.whl", hash = "sha256:7e2dacf8b009a1c1e843b5213a87f7c544b2b042476ed7755be813eaf4e8347a"},
     {file = "psycopg2-2.9.9-cp38-cp38-win32.whl", hash = "sha256:ff432630e510709564c01dafdbe996cb552e0b9f3f065eb89bdce5bd31fabf4c"},
@@ -6557,6 +6559,7 @@ files = [
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     {file = "psycopg2_binary-2.9.9-cp311-cp311-win_amd64.whl", hash = "sha256:b76bedd166805480ab069612119ea636f5ab8f8771e640ae103e05a4aae3e417"},
     {file = "psycopg2_binary-2.9.9-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:8532fd6e6e2dc57bcb3bc90b079c60de896d2128c5d9d6f24a63875a95a088cf"},
+    {file = "psycopg2_binary-2.9.9-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:b0605eaed3eb239e87df0d5e3c6489daae3f7388d455d0c0b4df899519c6a38d"},
     {file = "psycopg2_binary-2.9.9-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:8f8544b092a29a6ddd72f3556a9fcf249ec412e10ad28be6a0c0d948924f2212"},
     {file = "psycopg2_binary-2.9.9-cp312-cp312-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:2d423c8d8a3c82d08fe8af900ad5b613ce3632a1249fd6a223941d0735fce493"},
     {file = "psycopg2_binary-2.9.9-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:2e5afae772c00980525f6d6ecf7cbca55676296b580c0e6abb407f15f3706996"},
@@ -6565,6 +6568,8 @@ files = [
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+    {file = "psycopg2_binary-2.9.9-cp312-cp312-win32.whl", hash = "sha256:64cf30263844fa208851ebb13b0732ce674d8ec6a0c86a4e160495d299ba3c93"},
+    {file = "psycopg2_binary-2.9.9-cp312-cp312-win_amd64.whl", hash = "sha256:81ff62668af011f9a48787564ab7eded4e9fb17a4a6a74af5ffa6a457400d2ab"},
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     {file = "psycopg2_binary-2.9.9-cp37-cp37m-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:0a602ea5aff39bb9fac6308e9c9d82b9a35c2bf288e184a816002c9fae930b77"},
@@ -11080,4 +11085,4 @@ text-helpers = ["chardet"]
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.8.1,<4.0"
-content-hash = "6781b828c8bc2b08ece3cbf82be799dc0e361b9f6f9c204ddefcfee70ab0db8b"
+content-hash = "3660cb9106129dcf1a2fe157c1bdfe567923fc9ed408672bcbcb70f4345f1285"
diff --git a/libs/langchain/pyproject.toml b/libs/langchain/pyproject.toml
index a454bf6150c..b0bbafe3482 100644
--- a/libs/langchain/pyproject.toml
+++ b/libs/langchain/pyproject.toml
@@ -12,7 +12,7 @@ langchain-server = "langchain.server:main"
 
 [tool.poetry.dependencies]
 python = ">=3.8.1,<4.0"
-langchain-core = "^0.0.1"
+langchain-core = "^0.0.2"
 pydantic = ">=1,<3"
 SQLAlchemy = ">=1.4,<3"
 requests = "^2"
diff --git a/libs/langchain/tests/integration_tests/memory/test_cassandra.py b/libs/langchain/tests/integration_tests/memory/test_cassandra.py
index ec79f102bf8..131eb961139 100644
--- a/libs/langchain/tests/integration_tests/memory/test_cassandra.py
+++ b/libs/langchain/tests/integration_tests/memory/test_cassandra.py
@@ -2,7 +2,6 @@ import os
 import time
 from typing import Optional
 
-from cassandra.cluster import Cluster
 from langchain_core.messages import AIMessage, HumanMessage
 
 from langchain.memory import ConversationBufferMemory
@@ -16,6 +15,8 @@ def _chat_message_history(
     drop: bool = True,
     ttl_seconds: Optional[int] = None,
 ) -> CassandraChatMessageHistory:
+    from cassandra.cluster import Cluster
+
     keyspace = "cmh_test_keyspace"
     table_name = "cmh_test_table"
     # get db connection
diff --git a/libs/langchain/tests/integration_tests/vectorstores/test_cassandra.py b/libs/langchain/tests/integration_tests/vectorstores/test_cassandra.py
index e0c0403301f..bbe6189d48f 100644
--- a/libs/langchain/tests/integration_tests/vectorstores/test_cassandra.py
+++ b/libs/langchain/tests/integration_tests/vectorstores/test_cassandra.py
@@ -2,8 +2,6 @@
 import time
 from typing import List, Optional, Type
 
-from cassandra.cluster import Cluster
-
 from langchain.docstore.document import Document
 from langchain.vectorstores import Cassandra
 from tests.integration_tests.vectorstores.fake_embeddings import (
@@ -19,6 +17,8 @@ def _vectorstore_from_texts(
     embedding_class: Type[Embeddings] = ConsistentFakeEmbeddings,
     drop: bool = True,
 ) -> Cassandra:
+    from cassandra.cluster import Cluster
+
     keyspace = "vector_test_keyspace"
     table_name = "vector_test_table"
     # get db connection
@@ -154,12 +154,3 @@ def test_cassandra_delete() -> None:
     time.sleep(0.3)
     output = docsearch.similarity_search("foo", k=10)
     assert len(output) == 0
-
-
-# if __name__ == "__main__":
-#     test_cassandra()
-#     test_cassandra_with_score()
-#     test_cassandra_max_marginal_relevance_search()
-#     test_cassandra_add_extra()
-#     test_cassandra_no_drop()
-#     test_cassandra_delete()
diff --git a/libs/langchain/tests/unit_tests/schema/runnable/__init__.py b/libs/langchain/tests/unit_tests/schema/runnable/__init__.py
new file mode 100644
index 00000000000..e69de29bb2d
diff --git a/libs/langchain/tests/unit_tests/schema/runnable/test_base.py b/libs/langchain/tests/unit_tests/schema/runnable/test_base.py
new file mode 100644
index 00000000000..2f7c84ea5bf
--- /dev/null
+++ b/libs/langchain/tests/unit_tests/schema/runnable/test_base.py
@@ -0,0 +1,20 @@
+from langchain.schema.runnable.base import __all__
+
+EXPECTED_ALL = [
+    "Runnable",
+    "RunnableBinding",
+    "RunnableBindingBase",
+    "RunnableEach",
+    "RunnableEachBase",
+    "RunnableGenerator",
+    "RunnableLambda",
+    "RunnableMap",
+    "RunnableParallel",
+    "RunnableSequence",
+    "RunnableSerializable",
+    "coerce_to_runnable",
+]
+
+
+def test_all_imports() -> None:
+    assert set(__all__) == set(EXPECTED_ALL)
diff --git a/libs/langchain/tests/unit_tests/schema/runnable/test_branch.py b/libs/langchain/tests/unit_tests/schema/runnable/test_branch.py
new file mode 100644
index 00000000000..e5ef04f12fa
--- /dev/null
+++ b/libs/langchain/tests/unit_tests/schema/runnable/test_branch.py
@@ -0,0 +1,7 @@
+from langchain.schema.runnable.branch import __all__
+
+EXPECTED_ALL = ["RunnableBranch"]
+
+
+def test_all_imports() -> None:
+    assert set(__all__) == set(EXPECTED_ALL)
diff --git a/libs/langchain/tests/unit_tests/schema/runnable/test_config.py b/libs/langchain/tests/unit_tests/schema/runnable/test_config.py
new file mode 100644
index 00000000000..a8df9d130ba
--- /dev/null
+++ b/libs/langchain/tests/unit_tests/schema/runnable/test_config.py
@@ -0,0 +1,19 @@
+from langchain.schema.runnable.config import __all__
+
+EXPECTED_ALL = [
+    "EmptyDict",
+    "RunnableConfig",
+    "acall_func_with_variable_args",
+    "call_func_with_variable_args",
+    "ensure_config",
+    "get_async_callback_manager_for_config",
+    "get_callback_manager_for_config",
+    "get_config_list",
+    "get_executor_for_config",
+    "merge_configs",
+    "patch_config",
+]
+
+
+def test_all_imports() -> None:
+    assert set(__all__) == set(EXPECTED_ALL)
diff --git a/libs/langchain/tests/unit_tests/schema/runnable/test_configurable.py b/libs/langchain/tests/unit_tests/schema/runnable/test_configurable.py
new file mode 100644
index 00000000000..6ba54a03fe2
--- /dev/null
+++ b/libs/langchain/tests/unit_tests/schema/runnable/test_configurable.py
@@ -0,0 +1,13 @@
+from langchain.schema.runnable.configurable import __all__
+
+EXPECTED_ALL = [
+    "DynamicRunnable",
+    "RunnableConfigurableAlternatives",
+    "RunnableConfigurableFields",
+    "StrEnum",
+    "make_options_spec",
+]
+
+
+def test_all_imports() -> None:
+    assert set(__all__) == set(EXPECTED_ALL)
diff --git a/libs/langchain/tests/unit_tests/schema/runnable/test_fallbacks.py b/libs/langchain/tests/unit_tests/schema/runnable/test_fallbacks.py
new file mode 100644
index 00000000000..5851edf78b5
--- /dev/null
+++ b/libs/langchain/tests/unit_tests/schema/runnable/test_fallbacks.py
@@ -0,0 +1,7 @@
+from langchain.schema.runnable.fallbacks import __all__
+
+EXPECTED_ALL = ["RunnableWithFallbacks"]
+
+
+def test_all_imports() -> None:
+    assert set(__all__) == set(EXPECTED_ALL)
diff --git a/libs/langchain/tests/unit_tests/schema/runnable/test_history.py b/libs/langchain/tests/unit_tests/schema/runnable/test_history.py
new file mode 100644
index 00000000000..a2e23beb1ff
--- /dev/null
+++ b/libs/langchain/tests/unit_tests/schema/runnable/test_history.py
@@ -0,0 +1,7 @@
+from langchain.schema.runnable.history import __all__
+
+EXPECTED_ALL = ["RunnableWithMessageHistory"]
+
+
+def test_all_imports() -> None:
+    assert set(__all__) == set(EXPECTED_ALL)
diff --git a/libs/langchain/tests/unit_tests/schema/runnable/test_imports.py b/libs/langchain/tests/unit_tests/schema/runnable/test_imports.py
new file mode 100644
index 00000000000..516e3cee599
--- /dev/null
+++ b/libs/langchain/tests/unit_tests/schema/runnable/test_imports.py
@@ -0,0 +1,26 @@
+from langchain.schema.runnable import __all__
+
+EXPECTED_ALL = [
+    "ConfigurableField",
+    "ConfigurableFieldSingleOption",
+    "ConfigurableFieldMultiOption",
+    "patch_config",
+    "RouterInput",
+    "RouterRunnable",
+    "Runnable",
+    "RunnableSerializable",
+    "RunnableBinding",
+    "RunnableBranch",
+    "RunnableConfig",
+    "RunnableGenerator",
+    "RunnableLambda",
+    "RunnableMap",
+    "RunnableParallel",
+    "RunnablePassthrough",
+    "RunnableSequence",
+    "RunnableWithFallbacks",
+]
+
+
+def test_all_imports() -> None:
+    assert set(__all__) == set(EXPECTED_ALL)
diff --git a/libs/langchain/tests/unit_tests/schema/runnable/test_passthrough.py b/libs/langchain/tests/unit_tests/schema/runnable/test_passthrough.py
new file mode 100644
index 00000000000..c41ed684ef1
--- /dev/null
+++ b/libs/langchain/tests/unit_tests/schema/runnable/test_passthrough.py
@@ -0,0 +1,7 @@
+from langchain.schema.runnable.passthrough import __all__
+
+EXPECTED_ALL = ["RunnableAssign", "RunnablePassthrough", "aidentity", "identity"]
+
+
+def test_all_imports() -> None:
+    assert set(__all__) == set(EXPECTED_ALL)
diff --git a/libs/langchain/tests/unit_tests/schema/runnable/test_retry.py b/libs/langchain/tests/unit_tests/schema/runnable/test_retry.py
new file mode 100644
index 00000000000..581d997c251
--- /dev/null
+++ b/libs/langchain/tests/unit_tests/schema/runnable/test_retry.py
@@ -0,0 +1,7 @@
+from langchain.schema.runnable.retry import __all__
+
+EXPECTED_ALL = ["RunnableRetry"]
+
+
+def test_all_imports() -> None:
+    assert set(__all__) == set(EXPECTED_ALL)
diff --git a/libs/langchain/tests/unit_tests/schema/runnable/test_router.py b/libs/langchain/tests/unit_tests/schema/runnable/test_router.py
new file mode 100644
index 00000000000..d4a1b2122b0
--- /dev/null
+++ b/libs/langchain/tests/unit_tests/schema/runnable/test_router.py
@@ -0,0 +1,7 @@
+from langchain.schema.runnable.router import __all__
+
+EXPECTED_ALL = ["RouterInput", "RouterRunnable"]
+
+
+def test_all_imports() -> None:
+    assert set(__all__) == set(EXPECTED_ALL)
diff --git a/libs/langchain/tests/unit_tests/schema/runnable/test_utils.py b/libs/langchain/tests/unit_tests/schema/runnable/test_utils.py
new file mode 100644
index 00000000000..76eb1c3feef
--- /dev/null
+++ b/libs/langchain/tests/unit_tests/schema/runnable/test_utils.py
@@ -0,0 +1,27 @@
+from langchain.schema.runnable.utils import __all__
+
+EXPECTED_ALL = [
+    "AddableDict",
+    "ConfigurableField",
+    "ConfigurableFieldMultiOption",
+    "ConfigurableFieldSingleOption",
+    "ConfigurableFieldSpec",
+    "GetLambdaSource",
+    "IsFunctionArgDict",
+    "IsLocalDict",
+    "SupportsAdd",
+    "aadd",
+    "accepts_config",
+    "accepts_run_manager",
+    "add",
+    "gated_coro",
+    "gather_with_concurrency",
+    "get_function_first_arg_dict_keys",
+    "get_lambda_source",
+    "get_unique_config_specs",
+    "indent_lines_after_first",
+]
+
+
+def test_all_imports() -> None:
+    assert set(__all__) == set(EXPECTED_ALL)
diff --git a/libs/langchain/tests/unit_tests/schema/test_agent.py b/libs/langchain/tests/unit_tests/schema/test_agent.py
new file mode 100644
index 00000000000..00deec94fc0
--- /dev/null
+++ b/libs/langchain/tests/unit_tests/schema/test_agent.py
@@ -0,0 +1,7 @@
+from langchain.schema.agent import __all__
+
+EXPECTED_ALL = ["AgentAction", "AgentActionMessageLog", "AgentFinish"]
+
+
+def test_all_imports() -> None:
+    assert set(__all__) == set(EXPECTED_ALL)
diff --git a/libs/langchain/tests/unit_tests/schema/test_cache.py b/libs/langchain/tests/unit_tests/schema/test_cache.py
new file mode 100644
index 00000000000..73d5559a656
--- /dev/null
+++ b/libs/langchain/tests/unit_tests/schema/test_cache.py
@@ -0,0 +1,7 @@
+from langchain.schema.cache import __all__
+
+EXPECTED_ALL = ["BaseCache"]
+
+
+def test_all_imports() -> None:
+    assert set(__all__) == set(EXPECTED_ALL)
diff --git a/libs/langchain/tests/unit_tests/schema/test_chat.py b/libs/langchain/tests/unit_tests/schema/test_chat.py
new file mode 100644
index 00000000000..bfd1401a42a
--- /dev/null
+++ b/libs/langchain/tests/unit_tests/schema/test_chat.py
@@ -0,0 +1,7 @@
+from langchain.schema.chat import __all__
+
+EXPECTED_ALL = ["ChatSession"]
+
+
+def test_all_imports() -> None:
+    assert set(__all__) == set(EXPECTED_ALL)
diff --git a/libs/langchain/tests/unit_tests/schema/test_chat_history.py b/libs/langchain/tests/unit_tests/schema/test_chat_history.py
new file mode 100644
index 00000000000..9354c15a89f
--- /dev/null
+++ b/libs/langchain/tests/unit_tests/schema/test_chat_history.py
@@ -0,0 +1,7 @@
+from langchain.schema.chat_history import __all__
+
+EXPECTED_ALL = ["BaseChatMessageHistory"]
+
+
+def test_all_imports() -> None:
+    assert set(__all__) == set(EXPECTED_ALL)
diff --git a/libs/langchain/tests/unit_tests/schema/test_document.py b/libs/langchain/tests/unit_tests/schema/test_document.py
new file mode 100644
index 00000000000..895ec902cb3
--- /dev/null
+++ b/libs/langchain/tests/unit_tests/schema/test_document.py
@@ -0,0 +1,7 @@
+from langchain.schema.document import __all__
+
+EXPECTED_ALL = ["BaseDocumentTransformer", "Document"]
+
+
+def test_all_imports() -> None:
+    assert set(__all__) == set(EXPECTED_ALL)
diff --git a/libs/langchain/tests/unit_tests/schema/test_embeddings.py b/libs/langchain/tests/unit_tests/schema/test_embeddings.py
new file mode 100644
index 00000000000..df549fceffc
--- /dev/null
+++ b/libs/langchain/tests/unit_tests/schema/test_embeddings.py
@@ -0,0 +1,7 @@
+from langchain.schema.embeddings import __all__
+
+EXPECTED_ALL = ["Embeddings"]
+
+
+def test_all_imports() -> None:
+    assert set(__all__) == set(EXPECTED_ALL)
diff --git a/libs/langchain/tests/unit_tests/schema/test_exceptions.py b/libs/langchain/tests/unit_tests/schema/test_exceptions.py
new file mode 100644
index 00000000000..16341c83b4f
--- /dev/null
+++ b/libs/langchain/tests/unit_tests/schema/test_exceptions.py
@@ -0,0 +1,7 @@
+from langchain.schema.exceptions import __all__
+
+EXPECTED_ALL = ["LangChainException"]
+
+
+def test_all_imports() -> None:
+    assert set(__all__) == set(EXPECTED_ALL)
diff --git a/libs/langchain/tests/unit_tests/schema/test_imports.py b/libs/langchain/tests/unit_tests/schema/test_imports.py
index d667e3d4c10..03fff3f1285 100644
--- a/libs/langchain/tests/unit_tests/schema/test_imports.py
+++ b/libs/langchain/tests/unit_tests/schema/test_imports.py
@@ -18,6 +18,7 @@ EXPECTED_ALL = [
     "messages_from_dict",
     "messages_to_dict",
     "message_to_dict",
+    "_message_to_dict",
     "_message_from_dict",
     "get_buffer_string",
     "RunInfo",
diff --git a/libs/langchain/tests/unit_tests/schema/test_language_model.py b/libs/langchain/tests/unit_tests/schema/test_language_model.py
new file mode 100644
index 00000000000..96ae48c2f56
--- /dev/null
+++ b/libs/langchain/tests/unit_tests/schema/test_language_model.py
@@ -0,0 +1,7 @@
+from langchain.schema.language_model import __all__
+
+EXPECTED_ALL = ["BaseLanguageModel", "_get_token_ids_default_method", "get_tokenizer"]
+
+
+def test_all_imports() -> None:
+    assert set(__all__) == set(EXPECTED_ALL)
diff --git a/libs/langchain/tests/unit_tests/schema/test_memory.py b/libs/langchain/tests/unit_tests/schema/test_memory.py
new file mode 100644
index 00000000000..91af0cfac08
--- /dev/null
+++ b/libs/langchain/tests/unit_tests/schema/test_memory.py
@@ -0,0 +1,7 @@
+from langchain.schema.memory import __all__
+
+EXPECTED_ALL = ["BaseMemory"]
+
+
+def test_all_imports() -> None:
+    assert set(__all__) == set(EXPECTED_ALL)
diff --git a/libs/langchain/tests/unit_tests/schema/test_messages.py b/libs/langchain/tests/unit_tests/schema/test_messages.py
index 37523b7c759..3c13488cace 100644
--- a/libs/langchain/tests/unit_tests/schema/test_messages.py
+++ b/libs/langchain/tests/unit_tests/schema/test_messages.py
@@ -1,101 +1,29 @@
-import pytest
-from langchain_core.messages import (
-    AIMessageChunk,
-    ChatMessageChunk,
-    FunctionMessageChunk,
-    HumanMessageChunk,
-)
+from langchain.schema.messages import __all__
+
+EXPECTED_ALL = [
+    "AIMessage",
+    "AIMessageChunk",
+    "BaseMessage",
+    "BaseMessageChunk",
+    "ChatMessage",
+    "ChatMessageChunk",
+    "FunctionMessage",
+    "FunctionMessageChunk",
+    "HumanMessage",
+    "HumanMessageChunk",
+    "SystemMessage",
+    "SystemMessageChunk",
+    "ToolMessage",
+    "ToolMessageChunk",
+    "_message_from_dict",
+    "_message_to_dict",
+    "message_to_dict",
+    "get_buffer_string",
+    "merge_content",
+    "messages_from_dict",
+    "messages_to_dict",
+]
 
 
-def test_message_chunks() -> None:
-    assert AIMessageChunk(content="I am") + AIMessageChunk(
-        content=" indeed."
-    ) == AIMessageChunk(
-        content="I am indeed."
-    ), "MessageChunk + MessageChunk should be a MessageChunk"
-
-    assert (
-        AIMessageChunk(content="I am") + HumanMessageChunk(content=" indeed.")
-        == AIMessageChunk(content="I am indeed.")
-    ), "MessageChunk + MessageChunk should be a MessageChunk of same class as the left side"  # noqa: E501
-
-    assert (
-        AIMessageChunk(content="", additional_kwargs={"foo": "bar"})
-        + AIMessageChunk(content="", additional_kwargs={"baz": "foo"})
-        == AIMessageChunk(content="", additional_kwargs={"foo": "bar", "baz": "foo"})
-    ), "MessageChunk + MessageChunk should be a MessageChunk with merged additional_kwargs"  # noqa: E501
-
-    assert (
-        AIMessageChunk(
-            content="", additional_kwargs={"function_call": {"name": "web_search"}}
-        )
-        + AIMessageChunk(
-            content="", additional_kwargs={"function_call": {"arguments": "{\n"}}
-        )
-        + AIMessageChunk(
-            content="",
-            additional_kwargs={
-                "function_call": {"arguments": '  "query": "turtles"\n}'}
-            },
-        )
-        == AIMessageChunk(
-            content="",
-            additional_kwargs={
-                "function_call": {
-                    "name": "web_search",
-                    "arguments": '{\n  "query": "turtles"\n}',
-                }
-            },
-        )
-    ), "MessageChunk + MessageChunk should be a MessageChunk with merged additional_kwargs"  # noqa: E501
-
-
-def test_chat_message_chunks() -> None:
-    assert ChatMessageChunk(role="User", content="I am") + ChatMessageChunk(
-        role="User", content=" indeed."
-    ) == ChatMessageChunk(
-        role="User", content="I am indeed."
-    ), "ChatMessageChunk + ChatMessageChunk should be a ChatMessageChunk"
-
-    with pytest.raises(ValueError):
-        ChatMessageChunk(role="User", content="I am") + ChatMessageChunk(
-            role="Assistant", content=" indeed."
-        )
-
-    assert (
-        ChatMessageChunk(role="User", content="I am")
-        + AIMessageChunk(content=" indeed.")
-        == ChatMessageChunk(role="User", content="I am indeed.")
-    ), "ChatMessageChunk + other MessageChunk should be a ChatMessageChunk with the left side's role"  # noqa: E501
-
-    assert AIMessageChunk(content="I am") + ChatMessageChunk(
-        role="User", content=" indeed."
-    ) == AIMessageChunk(
-        content="I am indeed."
-    ), "Other MessageChunk + ChatMessageChunk should be a MessageChunk as the left side"  # noqa: E501
-
-
-def test_function_message_chunks() -> None:
-    assert FunctionMessageChunk(name="hello", content="I am") + FunctionMessageChunk(
-        name="hello", content=" indeed."
-    ) == FunctionMessageChunk(
-        name="hello", content="I am indeed."
-    ), "FunctionMessageChunk + FunctionMessageChunk should be a FunctionMessageChunk"
-
-    with pytest.raises(ValueError):
-        FunctionMessageChunk(name="hello", content="I am") + FunctionMessageChunk(
-            name="bye", content=" indeed."
-        )
-
-
-def test_ani_message_chunks() -> None:
-    assert AIMessageChunk(example=True, content="I am") + AIMessageChunk(
-        example=True, content=" indeed."
-    ) == AIMessageChunk(
-        example=True, content="I am indeed."
-    ), "AIMessageChunk + AIMessageChunk should be a AIMessageChunk"
-
-    with pytest.raises(ValueError):
-        AIMessageChunk(example=True, content="I am") + AIMessageChunk(
-            example=False, content=" indeed."
-        )
+def test_all_imports() -> None:
+    assert set(__all__) == set(EXPECTED_ALL)
diff --git a/libs/langchain/tests/unit_tests/schema/test_output.py b/libs/langchain/tests/unit_tests/schema/test_output.py
index a2f6e3e80e2..06746ceff57 100644
--- a/libs/langchain/tests/unit_tests/schema/test_output.py
+++ b/libs/langchain/tests/unit_tests/schema/test_output.py
@@ -1,60 +1,15 @@
-from langchain_core.messages import HumanMessageChunk
-from langchain_core.outputs import ChatGenerationChunk, GenerationChunk
+from langchain.schema.output import __all__
+
+EXPECTED_ALL = [
+    "ChatGeneration",
+    "ChatGenerationChunk",
+    "ChatResult",
+    "Generation",
+    "GenerationChunk",
+    "LLMResult",
+    "RunInfo",
+]
 
 
-def test_generation_chunk() -> None:
-    assert GenerationChunk(text="Hello, ") + GenerationChunk(
-        text="world!"
-    ) == GenerationChunk(
-        text="Hello, world!"
-    ), "GenerationChunk + GenerationChunk should be a GenerationChunk"
-
-    assert (
-        GenerationChunk(text="Hello, ")
-        + GenerationChunk(text="world!", generation_info={"foo": "bar"})
-        == GenerationChunk(text="Hello, world!", generation_info={"foo": "bar"})
-    ), "GenerationChunk + GenerationChunk should be a GenerationChunk with merged generation_info"  # noqa: E501
-
-    assert (
-        GenerationChunk(text="Hello, ")
-        + GenerationChunk(text="world!", generation_info={"foo": "bar"})
-        + GenerationChunk(text="!", generation_info={"baz": "foo"})
-        == GenerationChunk(
-            text="Hello, world!!", generation_info={"foo": "bar", "baz": "foo"}
-        )
-    ), "GenerationChunk + GenerationChunk should be a GenerationChunk with merged generation_info"  # noqa: E501
-
-
-def test_chat_generation_chunk() -> None:
-    assert ChatGenerationChunk(
-        message=HumanMessageChunk(content="Hello, ")
-    ) + ChatGenerationChunk(
-        message=HumanMessageChunk(content="world!")
-    ) == ChatGenerationChunk(
-        message=HumanMessageChunk(content="Hello, world!")
-    ), "ChatGenerationChunk + ChatGenerationChunk should be a ChatGenerationChunk"
-
-    assert (
-        ChatGenerationChunk(message=HumanMessageChunk(content="Hello, "))
-        + ChatGenerationChunk(
-            message=HumanMessageChunk(content="world!"), generation_info={"foo": "bar"}
-        )
-        == ChatGenerationChunk(
-            message=HumanMessageChunk(content="Hello, world!"),
-            generation_info={"foo": "bar"},
-        )
-    ), "GenerationChunk + GenerationChunk should be a GenerationChunk with merged generation_info"  # noqa: E501
-
-    assert (
-        ChatGenerationChunk(message=HumanMessageChunk(content="Hello, "))
-        + ChatGenerationChunk(
-            message=HumanMessageChunk(content="world!"), generation_info={"foo": "bar"}
-        )
-        + ChatGenerationChunk(
-            message=HumanMessageChunk(content="!"), generation_info={"baz": "foo"}
-        )
-        == ChatGenerationChunk(
-            message=HumanMessageChunk(content="Hello, world!!"),
-            generation_info={"foo": "bar", "baz": "foo"},
-        )
-    ), "GenerationChunk + GenerationChunk should be a GenerationChunk with merged generation_info"  # noqa: E501
+def test_all_imports() -> None:
+    assert set(__all__) == set(EXPECTED_ALL)
diff --git a/libs/langchain/tests/unit_tests/schema/test_output_parser.py b/libs/langchain/tests/unit_tests/schema/test_output_parser.py
new file mode 100644
index 00000000000..d45206f71ab
--- /dev/null
+++ b/libs/langchain/tests/unit_tests/schema/test_output_parser.py
@@ -0,0 +1,16 @@
+from langchain.schema.output_parser import __all__
+
+EXPECTED_ALL = [
+    "BaseCumulativeTransformOutputParser",
+    "BaseGenerationOutputParser",
+    "BaseLLMOutputParser",
+    "BaseOutputParser",
+    "BaseTransformOutputParser",
+    "NoOpOutputParser",
+    "OutputParserException",
+    "StrOutputParser",
+]
+
+
+def test_all_imports() -> None:
+    assert set(__all__) == set(EXPECTED_ALL)
diff --git a/libs/langchain/tests/unit_tests/schema/test_prompt.py b/libs/langchain/tests/unit_tests/schema/test_prompt.py
new file mode 100644
index 00000000000..a0d937717c6
--- /dev/null
+++ b/libs/langchain/tests/unit_tests/schema/test_prompt.py
@@ -0,0 +1,7 @@
+from langchain.schema.prompt import __all__
+
+EXPECTED_ALL = ["PromptValue"]
+
+
+def test_all_imports() -> None:
+    assert set(__all__) == set(EXPECTED_ALL)
diff --git a/libs/langchain/tests/unit_tests/schema/test_prompt_template.py b/libs/langchain/tests/unit_tests/schema/test_prompt_template.py
new file mode 100644
index 00000000000..20e2447335e
--- /dev/null
+++ b/libs/langchain/tests/unit_tests/schema/test_prompt_template.py
@@ -0,0 +1,7 @@
+from langchain.schema.prompt_template import __all__
+
+EXPECTED_ALL = ["BasePromptTemplate", "format_document"]
+
+
+def test_all_imports() -> None:
+    assert set(__all__) == set(EXPECTED_ALL)
diff --git a/libs/langchain/tests/unit_tests/schema/test_retriever.py b/libs/langchain/tests/unit_tests/schema/test_retriever.py
new file mode 100644
index 00000000000..5469dec0eb2
--- /dev/null
+++ b/libs/langchain/tests/unit_tests/schema/test_retriever.py
@@ -0,0 +1,7 @@
+from langchain.schema.retriever import __all__
+
+EXPECTED_ALL = ["BaseRetriever"]
+
+
+def test_all_imports() -> None:
+    assert set(__all__) == set(EXPECTED_ALL)
diff --git a/libs/langchain/tests/unit_tests/schema/test_storage.py b/libs/langchain/tests/unit_tests/schema/test_storage.py
new file mode 100644
index 00000000000..91196a2b00c
--- /dev/null
+++ b/libs/langchain/tests/unit_tests/schema/test_storage.py
@@ -0,0 +1,7 @@
+from langchain.schema.storage import __all__
+
+EXPECTED_ALL = ["BaseStore"]
+
+
+def test_all_imports() -> None:
+    assert set(__all__) == set(EXPECTED_ALL)
diff --git a/libs/langchain/tests/unit_tests/schema/test_vectorstore.py b/libs/langchain/tests/unit_tests/schema/test_vectorstore.py
new file mode 100644
index 00000000000..3e53f84ba1a
--- /dev/null
+++ b/libs/langchain/tests/unit_tests/schema/test_vectorstore.py
@@ -0,0 +1,7 @@
+from langchain.schema.vectorstore import __all__
+
+EXPECTED_ALL = ["VectorStore", "VectorStoreRetriever"]
+
+
+def test_all_imports() -> None:
+    assert set(__all__) == set(EXPECTED_ALL)
diff --git a/libs/langchain/tests/unit_tests/test_schema.py b/libs/langchain/tests/unit_tests/test_schema.py
index 0cb6bc92e19..c749b1ca1c8 100644
--- a/libs/langchain/tests/unit_tests/test_schema.py
+++ b/libs/langchain/tests/unit_tests/test_schema.py
@@ -21,7 +21,7 @@ from langchain_core.messages import (
     messages_to_dict,
 )
 from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, Generation
-from langchain_core.prompts import ChatPromptValueConcrete, StringPromptValue
+from langchain_core.prompt_values import ChatPromptValueConcrete, StringPromptValue
 from langchain_core.pydantic_v1 import BaseModel, ValidationError