"""Decorator for creating a run tree from functions.""" from __future__ import annotations import asyncio import contextlib import contextvars import datetime import functools import inspect import logging import uuid import warnings from contextvars import copy_context from typing import ( TYPE_CHECKING, Any, AsyncGenerator, AsyncIterator, Awaitable, Callable, Dict, Generator, Generic, Iterator, List, Literal, Mapping, Optional, Protocol, Sequence, Set, Tuple, Type, TypedDict, TypeVar, Union, cast, overload, runtime_checkable, ) from typing_extensions import Annotated, ParamSpec, TypeGuard, get_args, get_origin from langsmith import client as ls_client from langsmith import run_trees, schemas, utils from langsmith._internal import _aiter as aitertools from langsmith.env import _runtime_env if TYPE_CHECKING: from types import TracebackType from langchain_core.runnables import Runnable LOGGER = logging.getLogger(__name__) _PARENT_RUN_TREE = contextvars.ContextVar[Optional[run_trees.RunTree]]( "_PARENT_RUN_TREE", default=None ) _PROJECT_NAME = contextvars.ContextVar[Optional[str]]("_PROJECT_NAME", default=None) _TAGS = contextvars.ContextVar[Optional[List[str]]]("_TAGS", default=None) _METADATA = contextvars.ContextVar[Optional[Dict[str, Any]]]("_METADATA", default=None) _TRACING_ENABLED = contextvars.ContextVar[Optional[Union[bool, Literal["local"]]]]( "_TRACING_ENABLED", default=None ) _CLIENT = contextvars.ContextVar[Optional[ls_client.Client]]("_CLIENT", default=None) _CONTEXT_KEYS: Dict[str, contextvars.ContextVar] = { "parent": _PARENT_RUN_TREE, "project_name": _PROJECT_NAME, "tags": _TAGS, "metadata": _METADATA, "enabled": _TRACING_ENABLED, "client": _CLIENT, } def get_current_run_tree() -> Optional[run_trees.RunTree]: """Get the current run tree.""" return _PARENT_RUN_TREE.get() def get_tracing_context( context: Optional[contextvars.Context] = None, ) -> Dict[str, Any]: """Get the current tracing context.""" if context is None: return { "parent": _PARENT_RUN_TREE.get(), "project_name": _PROJECT_NAME.get(), "tags": _TAGS.get(), "metadata": _METADATA.get(), "enabled": _TRACING_ENABLED.get(), "client": _CLIENT.get(), } return {k: context.get(v) for k, v in _CONTEXT_KEYS.items()} @contextlib.contextmanager def tracing_context( *, project_name: Optional[str] = None, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, parent: Optional[Union[run_trees.RunTree, Mapping, str, Literal[False]]] = None, enabled: Optional[Union[bool, Literal["local"]]] = None, client: Optional[ls_client.Client] = None, **kwargs: Any, ) -> Generator[None, None, None]: """Set the tracing context for a block of code. Args: project_name: The name of the project to log the run to. Defaults to None. tags: The tags to add to the run. Defaults to None. metadata: The metadata to add to the run. Defaults to None. parent: The parent run to use for the context. Can be a Run/RunTree object, request headers (for distributed tracing), or the dotted order string. Defaults to None. client: The client to use for logging the run to LangSmith. Defaults to None, enabled: Whether tracing is enabled. Defaults to None, meaning it will use the current context value or environment variables. """ if kwargs: # warn warnings.warn( f"Unrecognized keyword arguments: {kwargs}.", DeprecationWarning, ) current_context = get_tracing_context() parent_run = ( _get_parent_run({"parent": parent or kwargs.get("parent_run")}) if parent is not False else None ) if parent_run is not None: tags = sorted(set(tags or []) | set(parent_run.tags or [])) metadata = {**parent_run.metadata, **(metadata or {})} enabled = enabled if enabled is not None else current_context.get("enabled") _set_tracing_context( { "parent": parent_run, "project_name": project_name, "tags": tags, "metadata": metadata, "enabled": enabled, "client": client, } ) try: yield finally: _set_tracing_context(current_context) # Alias for backwards compatibility get_run_tree_context = get_current_run_tree def is_traceable_function(func: Any) -> TypeGuard[SupportsLangsmithExtra[P, R]]: """Check if a function is @traceable decorated.""" return ( _is_traceable_function(func) or (isinstance(func, functools.partial) and _is_traceable_function(func.func)) or (hasattr(func, "__call__") and _is_traceable_function(func.__call__)) ) def ensure_traceable( func: Callable[P, R], *, name: Optional[str] = None, metadata: Optional[Mapping[str, Any]] = None, tags: Optional[List[str]] = None, client: Optional[ls_client.Client] = None, reduce_fn: Optional[Callable[[Sequence], dict]] = None, project_name: Optional[str] = None, process_inputs: Optional[Callable[[dict], dict]] = None, process_outputs: Optional[Callable[..., dict]] = None, ) -> SupportsLangsmithExtra[P, R]: """Ensure that a function is traceable.""" if is_traceable_function(func): return func return traceable( name=name, metadata=metadata, tags=tags, client=client, reduce_fn=reduce_fn, project_name=project_name, process_inputs=process_inputs, process_outputs=process_outputs, )(func) def is_async(func: Callable) -> bool: """Inspect function or wrapped function to see if it is async.""" return inspect.iscoroutinefunction(func) or ( hasattr(func, "__wrapped__") and inspect.iscoroutinefunction(func.__wrapped__) ) class LangSmithExtra(TypedDict, total=False): """Any additional info to be injected into the run dynamically.""" name: Optional[str] """Optional name for the run.""" reference_example_id: Optional[ls_client.ID_TYPE] """Optional ID of a reference example.""" run_extra: Optional[Dict] """Optional additional run information.""" parent: Optional[Union[run_trees.RunTree, str, Mapping]] """Optional parent run, can be a RunTree, string, or mapping.""" run_tree: Optional[run_trees.RunTree] # TODO: Deprecate """Optional run tree (deprecated).""" project_name: Optional[str] """Optional name of the project.""" metadata: Optional[Dict[str, Any]] """Optional metadata for the run.""" tags: Optional[List[str]] """Optional list of tags for the run.""" run_id: Optional[ls_client.ID_TYPE] """Optional ID for the run.""" client: Optional[ls_client.Client] """Optional LangSmith client.""" on_end: Optional[Callable[[run_trees.RunTree], Any]] """Optional callback function to be called when the run ends.""" R = TypeVar("R", covariant=True) P = ParamSpec("P") @runtime_checkable class SupportsLangsmithExtra(Protocol, Generic[P, R]): """Implementations of this Protoc accept an optional langsmith_extra parameter. Args: *args: Variable length arguments. langsmith_extra (Optional[LangSmithExtra): Optional dictionary of additional parameters for Langsmith. **kwargs: Keyword arguments. Returns: R: The return type of the callable. """ def __call__( self, *args: P.args, langsmith_extra: Optional[LangSmithExtra] = None, **kwargs: P.kwargs, ) -> R: """Call the instance when it is called as a function. Args: *args: Variable length argument list. langsmith_extra: Optional dictionary containing additional parameters specific to Langsmith. **kwargs: Arbitrary keyword arguments. Returns: R: The return value of the method. """ ... @overload def traceable( func: Callable[P, R], ) -> SupportsLangsmithExtra[P, R]: ... @overload def traceable( run_type: ls_client.RUN_TYPE_T = "chain", *, name: Optional[str] = None, metadata: Optional[Mapping[str, Any]] = None, tags: Optional[List[str]] = None, client: Optional[ls_client.Client] = None, reduce_fn: Optional[Callable[[Sequence], dict]] = None, project_name: Optional[str] = None, process_inputs: Optional[Callable[[dict], dict]] = None, process_outputs: Optional[Callable[..., dict]] = None, _invocation_params_fn: Optional[Callable[[dict], dict]] = None, ) -> Callable[[Callable[P, R]], SupportsLangsmithExtra[P, R]]: ... def traceable( *args: Any, **kwargs: Any, ) -> Union[Callable, Callable[[Callable], Callable]]: """Trace a function with langsmith. Args: run_type: The type of run (span) to create. Examples: llm, chain, tool, prompt, retriever, etc. Defaults to "chain". name: The name of the run. Defaults to the function name. metadata: The metadata to add to the run. Defaults to None. tags: The tags to add to the run. Defaults to None. client: The client to use for logging the run to LangSmith. Defaults to None, which will use the default client. reduce_fn: A function to reduce the output of the function if the function returns a generator. Defaults to None, which means the values will be logged as a list. Note: if the iterator is never exhausted (e.g. the function returns an infinite generator), this will never be called, and the run itself will be stuck in a pending state. project_name: The name of the project to log the run to. Defaults to None, which will use the default project. process_inputs: Custom serialization / processing function for inputs. Defaults to None. process_outputs: Custom serialization / processing function for outputs. Defaults to None. Returns: Union[Callable, Callable[[Callable], Callable]]: The decorated function. Note: - Requires that LANGSMITH_TRACING_V2 be set to 'true' in the environment. Examples: Basic usage: .. code-block:: python @traceable def my_function(x: float, y: float) -> float: return x + y my_function(5, 6) @traceable async def my_async_function(query_params: dict) -> dict: async with httpx.AsyncClient() as http_client: response = await http_client.get( "https://api.example.com/data", params=query_params, ) return response.json() asyncio.run(my_async_function({"param": "value"})) Streaming data with a generator: .. code-block:: python @traceable def my_generator(n: int) -> Iterable: for i in range(n): yield i for item in my_generator(5): print(item) Async streaming data: .. code-block:: python @traceable async def my_async_generator(query_params: dict) -> Iterable: async with httpx.AsyncClient() as http_client: response = await http_client.get( "https://api.example.com/data", params=query_params, ) for item in response.json(): yield item async def async_code(): async for item in my_async_generator({"param": "value"}): print(item) asyncio.run(async_code()) Specifying a run type and name: .. code-block:: python @traceable(name="CustomName", run_type="tool") def another_function(a: float, b: float) -> float: return a * b another_function(5, 6) Logging with custom metadata and tags: .. code-block:: python @traceable( metadata={"version": "1.0", "author": "John Doe"}, tags=["beta", "test"] ) def tagged_function(x): return x**2 tagged_function(5) Specifying a custom client and project name: .. code-block:: python custom_client = Client(api_key="your_api_key") @traceable(client=custom_client, project_name="My Special Project") def project_specific_function(data): return data project_specific_function({"data": "to process"}) Manually passing langsmith_extra: .. code-block:: python @traceable def manual_extra_function(x): return x**2 manual_extra_function(5, langsmith_extra={"metadata": {"version": "1.0"}}) """ run_type = cast( ls_client.RUN_TYPE_T, ( args[0] if args and isinstance(args[0], str) else (kwargs.pop("run_type", None) or "chain") ), ) if run_type not in _VALID_RUN_TYPES: warnings.warn( f"Unrecognized run_type: {run_type}. Must be one of: {_VALID_RUN_TYPES}." f" Did you mean @traceable(name='{run_type}')?" ) if len(args) > 1: warnings.warn( "The `traceable()` decorator only accepts one positional argument, " "which should be the run_type. All other arguments should be passed " "as keyword arguments." ) if "extra" in kwargs: warnings.warn( "The `extra` keyword argument is deprecated. Please use `metadata` " "instead.", DeprecationWarning, ) reduce_fn = kwargs.pop("reduce_fn", None) container_input = _ContainerInput( # TODO: Deprecate raw extra extra_outer=kwargs.pop("extra", None), name=kwargs.pop("name", None), metadata=kwargs.pop("metadata", None), tags=kwargs.pop("tags", None), client=kwargs.pop("client", None), project_name=kwargs.pop("project_name", None), run_type=run_type, process_inputs=kwargs.pop("process_inputs", None), invocation_params_fn=kwargs.pop("_invocation_params_fn", None), ) outputs_processor = kwargs.pop("process_outputs", None) _on_run_end = functools.partial( _handle_container_end, outputs_processor=outputs_processor ) if kwargs: warnings.warn( f"The following keyword arguments are not recognized and will be ignored: " f"{sorted(kwargs.keys())}.", DeprecationWarning, ) def decorator(func: Callable): func_sig = inspect.signature(func) func_accepts_parent_run = func_sig.parameters.get("run_tree", None) is not None func_accepts_config = func_sig.parameters.get("config", None) is not None @functools.wraps(func) async def async_wrapper( *args: Any, langsmith_extra: Optional[LangSmithExtra] = None, **kwargs: Any, ) -> Any: """Async version of wrapper function.""" run_container = await aitertools.aio_to_thread( _setup_run, func, container_input=container_input, langsmith_extra=langsmith_extra, args=args, kwargs=kwargs, ) try: accepts_context = aitertools.asyncio_accepts_context() if func_accepts_parent_run: kwargs["run_tree"] = run_container["new_run"] if not func_accepts_config: kwargs.pop("config", None) fr_coro = func(*args, **kwargs) if accepts_context: function_result = await asyncio.create_task( # type: ignore[call-arg] fr_coro, context=run_container["context"] ) else: # Python < 3.11 with tracing_context( **get_tracing_context(run_container["context"]) ): function_result = await fr_coro except BaseException as e: # shield from cancellation, given we're catching all exceptions await asyncio.shield( aitertools.aio_to_thread(_on_run_end, run_container, error=e) ) raise e await aitertools.aio_to_thread( _on_run_end, run_container, outputs=function_result ) return function_result @functools.wraps(func) async def async_generator_wrapper( *args: Any, langsmith_extra: Optional[LangSmithExtra] = None, **kwargs: Any ) -> AsyncGenerator: run_container = await aitertools.aio_to_thread( _setup_run, func, container_input=container_input, langsmith_extra=langsmith_extra, args=args, kwargs=kwargs, ) results: List[Any] = [] try: if func_accepts_parent_run: kwargs["run_tree"] = run_container["new_run"] # TODO: Nesting is ambiguous if a nested traceable function is only # called mid-generation. Need to explicitly accept run_tree to get # around this. if not func_accepts_config: kwargs.pop("config", None) async_gen_result = func(*args, **kwargs) # Can't iterate through if it's a coroutine accepts_context = aitertools.asyncio_accepts_context() if inspect.iscoroutine(async_gen_result): if accepts_context: async_gen_result = await asyncio.create_task( async_gen_result, context=run_container["context"] ) # type: ignore else: # Python < 3.11 with tracing_context( **get_tracing_context(run_container["context"]) ): async_gen_result = await async_gen_result async for item in _process_async_iterator( generator=async_gen_result, run_container=run_container, is_llm_run=( run_container["new_run"].run_type == "llm" if run_container["new_run"] else False ), accepts_context=accepts_context, results=results, ): yield item except BaseException as e: await asyncio.shield( aitertools.aio_to_thread( _on_run_end, run_container, error=e, outputs=_get_function_result(results, reduce_fn), ) ) raise e await aitertools.aio_to_thread( _on_run_end, run_container, outputs=_get_function_result(results, reduce_fn), ) @functools.wraps(func) def wrapper( *args: Any, langsmith_extra: Optional[LangSmithExtra] = None, **kwargs: Any, ) -> Any: """Create a new run or create_child() if run is passed in kwargs.""" run_container = _setup_run( func, container_input=container_input, langsmith_extra=langsmith_extra, args=args, kwargs=kwargs, ) func_accepts_parent_run = ( inspect.signature(func).parameters.get("run_tree", None) is not None ) try: if func_accepts_parent_run: kwargs["run_tree"] = run_container["new_run"] if not func_accepts_config: kwargs.pop("config", None) function_result = run_container["context"].run(func, *args, **kwargs) except BaseException as e: _on_run_end(run_container, error=e) raise e _on_run_end(run_container, outputs=function_result) return function_result @functools.wraps(func) def generator_wrapper( *args: Any, langsmith_extra: Optional[LangSmithExtra] = None, **kwargs: Any ) -> Any: run_container = _setup_run( func, container_input=container_input, langsmith_extra=langsmith_extra, args=args, kwargs=kwargs, ) func_accepts_parent_run = ( inspect.signature(func).parameters.get("run_tree", None) is not None ) results: List[Any] = [] function_return: Any = None try: if func_accepts_parent_run: kwargs["run_tree"] = run_container["new_run"] if not func_accepts_config: kwargs.pop("config", None) generator_result = run_container["context"].run(func, *args, **kwargs) function_return = yield from _process_iterator( generator_result, run_container, is_llm_run=run_type == "llm", results=results, ) if function_return is not None: results.append(function_return) except BaseException as e: _on_run_end( run_container, error=e, outputs=_get_function_result(results, reduce_fn), ) raise e _on_run_end(run_container, outputs=_get_function_result(results, reduce_fn)) return function_return # "Stream" functions (used in methods like OpenAI/Anthropic's SDKs) # are functions that return iterable responses and should not be # considered complete until the streaming is completed @functools.wraps(func) def stream_wrapper( *args: Any, langsmith_extra: Optional[LangSmithExtra] = None, **kwargs: Any ) -> Any: trace_container = _setup_run( func, container_input=container_input, langsmith_extra=langsmith_extra, args=args, kwargs=kwargs, ) try: if func_accepts_parent_run: kwargs["run_tree"] = trace_container["new_run"] if not func_accepts_config: kwargs.pop("config", None) stream = trace_container["context"].run(func, *args, **kwargs) except Exception as e: _on_run_end(trace_container, error=e) raise if hasattr(stream, "__iter__"): return _TracedStream(stream, trace_container, reduce_fn) elif hasattr(stream, "__aiter__"): # sync function -> async iterable (unexpected) return _TracedAsyncStream(stream, trace_container, reduce_fn) # If it's not iterable, end the trace immediately _on_run_end(trace_container, outputs=stream) return stream @functools.wraps(func) async def async_stream_wrapper( *args: Any, langsmith_extra: Optional[LangSmithExtra] = None, **kwargs: Any ) -> Any: trace_container = await aitertools.aio_to_thread( _setup_run, func, container_input=container_input, langsmith_extra=langsmith_extra, args=args, kwargs=kwargs, ) try: if func_accepts_parent_run: kwargs["run_tree"] = trace_container["new_run"] if not func_accepts_config: kwargs.pop("config", None) stream = await func(*args, **kwargs) except Exception as e: await aitertools.aio_to_thread(_on_run_end, trace_container, error=e) raise if hasattr(stream, "__aiter__"): return _TracedAsyncStream(stream, trace_container, reduce_fn) elif hasattr(stream, "__iter__"): # Async function -> sync iterable return _TracedStream(stream, trace_container, reduce_fn) # If it's not iterable, end the trace immediately await aitertools.aio_to_thread(_on_run_end, trace_container, outputs=stream) return stream if inspect.isasyncgenfunction(func): selected_wrapper: Callable = async_generator_wrapper elif inspect.isgeneratorfunction(func): selected_wrapper = generator_wrapper elif is_async(func): if reduce_fn: selected_wrapper = async_stream_wrapper else: selected_wrapper = async_wrapper else: if reduce_fn: selected_wrapper = stream_wrapper else: selected_wrapper = wrapper setattr(selected_wrapper, "__langsmith_traceable__", True) sig = inspect.signature(selected_wrapper) if not sig.parameters.get("config"): sig = sig.replace( parameters=[ *( param for param in sig.parameters.values() if param.kind != inspect.Parameter.VAR_KEYWORD ), inspect.Parameter( "config", inspect.Parameter.KEYWORD_ONLY, default=None ), *( param for param in sig.parameters.values() if param.kind == inspect.Parameter.VAR_KEYWORD ), ] ) selected_wrapper.__signature__ = sig # type: ignore[attr-defined] return selected_wrapper # If the decorator is called with no arguments, then it's being used as a # decorator, so we return the decorator function if len(args) == 1 and callable(args[0]) and not kwargs: return decorator(args[0]) # Else it's being used as a decorator factory, so we return the decorator return decorator class trace: """Manage a LangSmith run in context. This class can be used as both a synchronous and asynchronous context manager. Args: name (str): Name of the run. run_type (ls_client.RUN_TYPE_T, optional): Type of run (e.g., "chain", "llm", "tool"). Defaults to "chain". inputs (Optional[Dict], optional): Initial input data for the run. Defaults to None. project_name (Optional[str], optional): Project name to associate the run with. Defaults to None. parent (Optional[Union[run_trees.RunTree, str, Mapping]], optional): Parent run. Can be a RunTree, dotted order string, or tracing headers. Defaults to None. tags (Optional[List[str]], optional): List of tags for the run. Defaults to None. metadata (Optional[Mapping[str, Any]], optional): Additional metadata for the run. Defaults to None. client (Optional[ls_client.Client], optional): LangSmith client for custom settings. Defaults to None. run_id (Optional[ls_client.ID_TYPE], optional): Preset identifier for the run. Defaults to None. reference_example_id (Optional[ls_client.ID_TYPE], optional): Associates run with a dataset example. Only for root runs in evaluation. Defaults to None. exceptions_to_handle (Optional[Tuple[Type[BaseException], ...]], optional): Exception types to ignore. Defaults to None. extra (Optional[Dict], optional): Extra data to send to LangSmith. Use 'metadata' instead. Defaults to None. Examples: Synchronous usage: .. code-block:: python >>> with trace("My Operation", run_type="tool", tags=["important"]) as run: ... result = "foo" # Perform operation ... run.metadata["some-key"] = "some-value" ... run.end(outputs={"result": result}) Asynchronous usage: .. code-block:: python >>> async def main(): ... async with trace("Async Operation", run_type="tool", tags=["async"]) as run: ... result = "foo" # Await async operation ... run.metadata["some-key"] = "some-value" ... # "end" just adds the outputs and sets error to None ... # The actual patching of the run happens when the context exits ... run.end(outputs={"result": result}) >>> asyncio.run(main()) Handling specific exceptions: .. code-block:: python >>> import pytest >>> import sys >>> with trace("Test", exceptions_to_handle=(pytest.skip.Exception,)): ... if sys.platform == "win32": # Just an example ... pytest.skip("Skipping test for windows") ... result = "foo" # Perform test operation """ def __init__( self, name: str, run_type: ls_client.RUN_TYPE_T = "chain", *, inputs: Optional[Dict] = None, extra: Optional[Dict] = None, project_name: Optional[str] = None, parent: Optional[Union[run_trees.RunTree, str, Mapping]] = None, tags: Optional[List[str]] = None, metadata: Optional[Mapping[str, Any]] = None, client: Optional[ls_client.Client] = None, run_id: Optional[ls_client.ID_TYPE] = None, reference_example_id: Optional[ls_client.ID_TYPE] = None, exceptions_to_handle: Optional[Tuple[Type[BaseException], ...]] = None, attachments: Optional[schemas.Attachments] = None, **kwargs: Any, ): """Initialize the trace context manager. Warns if unsupported kwargs are passed. """ if kwargs: warnings.warn( "The `trace` context manager no longer supports the following kwargs: " f"{sorted(kwargs.keys())}.", DeprecationWarning, ) self.name = name self.run_type = run_type self.inputs = inputs self.attachments = attachments self.extra = extra self.project_name = project_name self.parent = parent # The run tree is deprecated. Keeping for backwards compat. # Will fully merge within parent later. self.run_tree = kwargs.get("run_tree") self.tags = tags self.metadata = metadata self.client = client self.run_id = run_id self.reference_example_id = reference_example_id self.exceptions_to_handle = exceptions_to_handle self.new_run: Optional[run_trees.RunTree] = None self.old_ctx: Optional[dict] = None def _setup(self) -> run_trees.RunTree: """Set up the tracing context and create a new run. This method initializes the tracing context, merges tags and metadata, creates a new run (either as a child of an existing run or as a new root run), and sets up the necessary context variables. Returns: run_trees.RunTree: The newly created run. """ self.old_ctx = get_tracing_context() enabled = utils.tracing_is_enabled(self.old_ctx) outer_tags = _TAGS.get() outer_metadata = _METADATA.get() client_ = self.client or self.old_ctx.get("client") parent_run_ = _get_parent_run( { "parent": self.parent, "run_tree": self.run_tree, "client": client_, } ) tags_ = sorted(set((self.tags or []) + (outer_tags or []))) metadata = { **(self.metadata or {}), **(outer_metadata or {}), "ls_method": "trace", } extra_outer = self.extra or {} extra_outer["metadata"] = metadata project_name_ = _get_project_name(self.project_name) if parent_run_ is not None and enabled: self.new_run = parent_run_.create_child( name=self.name, run_id=self.run_id, run_type=self.run_type, extra=extra_outer, inputs=self.inputs, tags=tags_, attachments=self.attachments, ) else: self.new_run = run_trees.RunTree( name=self.name, id=ls_client._ensure_uuid(self.run_id), reference_example_id=ls_client._ensure_uuid( self.reference_example_id, accept_null=True ), run_type=self.run_type, extra=extra_outer, project_name=project_name_ or "default", inputs=self.inputs or {}, tags=tags_, client=client_, # type: ignore attachments=self.attachments or {}, ) if enabled is True: self.new_run.post() if enabled: _TAGS.set(tags_) _METADATA.set(metadata) _PARENT_RUN_TREE.set(self.new_run) _PROJECT_NAME.set(project_name_) _CLIENT.set(client_) return self.new_run def _teardown( self, exc_type: Optional[Type[BaseException]], exc_value: Optional[BaseException], traceback: Optional[TracebackType], ) -> None: """Clean up the tracing context and finalize the run. This method handles exceptions, ends the run if necessary, patches the run if it's not disabled, and resets the tracing context. Args: exc_type: The type of the exception that occurred, if any. exc_value: The exception instance that occurred, if any. traceback: The traceback object associated with the exception, if any. """ if self.new_run is None: return if exc_type is not None: if self.exceptions_to_handle and issubclass( exc_type, self.exceptions_to_handle ): tb = None else: tb = utils._format_exc() tb = f"{exc_type.__name__}: {exc_value}\n\n{tb}" self.new_run.end(error=tb) if self.old_ctx is not None: enabled = utils.tracing_is_enabled(self.old_ctx) if enabled is True: self.new_run.patch() _set_tracing_context(self.old_ctx) else: warnings.warn("Tracing context was not set up properly.", RuntimeWarning) def __enter__(self) -> run_trees.RunTree: """Enter the context manager synchronously. Returns: run_trees.RunTree: The newly created run. """ return self._setup() def __exit__( self, exc_type: Optional[Type[BaseException]] = None, exc_value: Optional[BaseException] = None, traceback: Optional[TracebackType] = None, ) -> None: """Exit the context manager synchronously. Args: exc_type: The type of the exception that occurred, if any. exc_value: The exception instance that occurred, if any. traceback: The traceback object associated with the exception, if any. """ self._teardown(exc_type, exc_value, traceback) async def __aenter__(self) -> run_trees.RunTree: """Enter the context manager asynchronously. Returns: run_trees.RunTree: The newly created run. """ ctx = copy_context() result = await aitertools.aio_to_thread(self._setup, __ctx=ctx) # Set the context for the current thread _set_tracing_context(get_tracing_context(ctx)) return result async def __aexit__( self, exc_type: Optional[Type[BaseException]] = None, exc_value: Optional[BaseException] = None, traceback: Optional[TracebackType] = None, ) -> None: """Exit the context manager asynchronously. Args: exc_type: The type of the exception that occurred, if any. exc_value: The exception instance that occurred, if any. traceback: The traceback object associated with the exception, if any. """ ctx = copy_context() if exc_type is not None: await asyncio.shield( aitertools.aio_to_thread( self._teardown, exc_type, exc_value, traceback, __ctx=ctx ) ) else: await aitertools.aio_to_thread( self._teardown, exc_type, exc_value, traceback, __ctx=ctx ) _set_tracing_context(get_tracing_context(ctx)) def _get_project_name(project_name: Optional[str]) -> Optional[str]: prt = _PARENT_RUN_TREE.get() return ( # Maintain tree consistency first _PROJECT_NAME.get() or (prt.session_name if prt else None) # Then check the passed in value or project_name # fallback to the default for the environment or utils.get_tracer_project() ) def as_runnable(traceable_fn: Callable) -> Runnable: """Convert a function wrapped by the LangSmith @traceable decorator to a Runnable. Args: traceable_fn (Callable): The function wrapped by the @traceable decorator. Returns: Runnable: A Runnable object that maintains a consistent LangSmith tracing context. Raises: ImportError: If langchain module is not installed. ValueError: If the provided function is not wrapped by the @traceable decorator. Example: >>> @traceable ... def my_function(input_data): ... # Function implementation ... pass >>> runnable = as_runnable(my_function) """ try: from langchain_core.runnables import RunnableConfig, RunnableLambda from langchain_core.runnables.utils import Input, Output except ImportError as e: raise ImportError( "as_runnable requires langchain-core to be installed. " "You can install it with `pip install langchain-core`." ) from e if not is_traceable_function(traceable_fn): try: fn_src = inspect.getsource(traceable_fn) except Exception: fn_src = "" raise ValueError( f"as_runnable expects a function wrapped by the LangSmith" f" @traceable decorator. Got {traceable_fn} defined as:\n{fn_src}" ) class RunnableTraceable(RunnableLambda): """Converts a @traceable decorated function to a Runnable. This helps maintain a consistent LangSmith tracing context. """ def __init__( self, func: Callable, afunc: Optional[Callable[..., Awaitable[Output]]] = None, ) -> None: wrapped: Optional[Callable[[Input], Output]] = None awrapped = self._wrap_async(afunc) if is_async(func): if awrapped is not None: raise TypeError( "Func was provided as a coroutine function, but afunc was " "also provided. If providing both, func should be a regular " "function to avoid ambiguity." ) wrapped = cast(Callable[[Input], Output], self._wrap_async(func)) elif is_traceable_function(func): wrapped = cast(Callable[[Input], Output], self._wrap_sync(func)) if wrapped is None: raise ValueError( f"{self.__class__.__name__} expects a function wrapped by" " the LangSmith" f" @traceable decorator. Got {func}" ) super().__init__( wrapped, cast( Optional[Callable[[Input], Awaitable[Output]]], awrapped, ), ) @staticmethod def _wrap_sync( func: Callable[..., Output], ) -> Callable[[Input, RunnableConfig], Output]: """Wrap a synchronous function to make it asynchronous.""" def wrap_traceable(inputs: dict, config: RunnableConfig) -> Any: run_tree = run_trees.RunTree.from_runnable_config(cast(dict, config)) return func(**inputs, langsmith_extra={"run_tree": run_tree}) return cast(Callable[[Input, RunnableConfig], Output], wrap_traceable) @staticmethod def _wrap_async( afunc: Optional[Callable[..., Awaitable[Output]]], ) -> Optional[Callable[[Input, RunnableConfig], Awaitable[Output]]]: """Wrap an async function to make it synchronous.""" if afunc is None: return None if not is_traceable_function(afunc): raise ValueError( "RunnableTraceable expects a function wrapped by the LangSmith" f" @traceable decorator. Got {afunc}" ) afunc_ = cast(Callable[..., Awaitable[Output]], afunc) async def awrap_traceable(inputs: dict, config: RunnableConfig) -> Any: run_tree = run_trees.RunTree.from_runnable_config(cast(dict, config)) return await afunc_(**inputs, langsmith_extra={"run_tree": run_tree}) return cast( Callable[[Input, RunnableConfig], Awaitable[Output]], awrap_traceable ) return RunnableTraceable(traceable_fn) ## Private Methods and Objects _VALID_RUN_TYPES = { "tool", "chain", "llm", "retriever", "embedding", "prompt", "parser", } class _TraceableContainer(TypedDict, total=False): """Typed response when initializing a run a traceable.""" new_run: Optional[run_trees.RunTree] project_name: Optional[str] outer_project: Optional[str] outer_metadata: Optional[Dict[str, Any]] outer_tags: Optional[List[str]] on_end: Optional[Callable[[run_trees.RunTree], Any]] context: contextvars.Context class _ContainerInput(TypedDict, total=False): """Typed response when initializing a run a traceable.""" extra_outer: Optional[Dict] name: Optional[str] metadata: Optional[Dict[str, Any]] tags: Optional[List[str]] client: Optional[ls_client.Client] reduce_fn: Optional[Callable] project_name: Optional[str] run_type: ls_client.RUN_TYPE_T process_inputs: Optional[Callable[[dict], dict]] invocation_params_fn: Optional[Callable[[dict], dict]] def _container_end( container: _TraceableContainer, outputs: Optional[Any] = None, error: Optional[BaseException] = None, ) -> None: """End the run.""" run_tree = container.get("new_run") if run_tree is None: # Tracing not enabled return outputs_ = outputs if isinstance(outputs, dict) else {"output": outputs} error_ = None if error: stacktrace = utils._format_exc() error_ = f"{repr(error)}\n\n{stacktrace}" run_tree.end(outputs=outputs_, error=error_) if utils.tracing_is_enabled() is True: run_tree.patch() on_end = container.get("on_end") if on_end is not None and callable(on_end): try: on_end(run_tree) except BaseException as e: LOGGER.warning(f"Failed to run on_end function: {e}") def _collect_extra(extra_outer: dict, langsmith_extra: LangSmithExtra) -> dict: run_extra = langsmith_extra.get("run_extra", None) if run_extra: extra_inner = {**extra_outer, **run_extra} else: extra_inner = extra_outer return extra_inner def _get_parent_run( langsmith_extra: LangSmithExtra, config: Optional[dict] = None, ) -> Optional[run_trees.RunTree]: parent = langsmith_extra.get("parent") if isinstance(parent, run_trees.RunTree): return parent if isinstance(parent, dict): return run_trees.RunTree.from_headers( parent, client=langsmith_extra.get("client"), # Precedence: headers -> cvar -> explicit -> env var project_name=_get_project_name(langsmith_extra.get("project_name")), ) if isinstance(parent, str): dort = run_trees.RunTree.from_dotted_order( parent, client=langsmith_extra.get("client"), # Precedence: cvar -> explicit -> env var project_name=_get_project_name(langsmith_extra.get("project_name")), ) return dort run_tree = langsmith_extra.get("run_tree") if run_tree: return run_tree crt = get_current_run_tree() if _runtime_env.get_langchain_core_version() is not None: if rt := run_trees.RunTree.from_runnable_config( config, client=langsmith_extra.get("client") ): # Still need to break ties when alternating between traceable and # LanChain code. # Nesting: LC -> LS -> LS, we want to still use LS as the parent # Otherwise would look like LC -> {LS, LS} (siblings) if ( not crt # Simple LC -> LS # Let user override if manually passed in or invoked in a # RunnableSequence. This is a naive check. or (config is not None and config.get("callbacks")) # If the LangChain dotted order is more nested than the LangSmith # dotted order, use the LangChain run as the parent. # Note that this condition shouldn't be triggered in later # versions of core, since we also update the run_tree context # vars when updating the RunnableConfig context var. or rt.dotted_order > crt.dotted_order ): return rt return crt def _setup_run( func: Callable, container_input: _ContainerInput, langsmith_extra: Optional[LangSmithExtra] = None, args: Any = None, kwargs: Any = None, ) -> _TraceableContainer: """Create a new run or create_child() if run is passed in kwargs.""" extra_outer = container_input.get("extra_outer") or {} metadata = container_input.get("metadata") tags = container_input.get("tags") client = container_input.get("client") run_type = container_input.get("run_type") or "chain" outer_project = _PROJECT_NAME.get() langsmith_extra = langsmith_extra or LangSmithExtra() name = langsmith_extra.get("name") or container_input.get("name") client_ = langsmith_extra.get("client", client) or _CLIENT.get() parent_run_ = _get_parent_run( {**langsmith_extra, "client": client_}, kwargs.get("config") ) project_cv = _PROJECT_NAME.get() selected_project = ( project_cv # From parent trace or ( parent_run_.session_name if parent_run_ else None ) # from parent run attempt 2 (not managed by traceable) or langsmith_extra.get("project_name") # at invocation time or container_input["project_name"] # at decorator time or utils.get_tracer_project() # default ) reference_example_id = langsmith_extra.get("reference_example_id") id_ = langsmith_extra.get("run_id") if not parent_run_ and not utils.tracing_is_enabled(): utils.log_once( logging.DEBUG, "LangSmith tracing is not enabled, returning original function.", ) return _TraceableContainer( new_run=None, project_name=selected_project, outer_project=outer_project, outer_metadata=None, outer_tags=None, on_end=langsmith_extra.get("on_end"), context=copy_context(), ) id_ = id_ or str(uuid.uuid4()) signature = inspect.signature(func) name_ = name or utils._get_function_name(func) docstring = func.__doc__ extra_inner = _collect_extra(extra_outer, langsmith_extra) outer_metadata = _METADATA.get() outer_tags = _TAGS.get() context = copy_context() metadata_ = { **(langsmith_extra.get("metadata") or {}), **(outer_metadata or {}), } context.run(_METADATA.set, metadata_) metadata_.update(metadata or {}) metadata_["ls_method"] = "traceable" extra_inner["metadata"] = metadata_ inputs, attachments = _get_inputs_and_attachments_safe(signature, *args, **kwargs) invocation_params_fn = container_input.get("invocation_params_fn") if invocation_params_fn: try: invocation_params = { k: v for k, v in invocation_params_fn(inputs).items() if v is not None } if invocation_params and isinstance(invocation_params, dict): metadata_.update(invocation_params) except BaseException as e: LOGGER.error(f"Failed to infer invocation params for {name_}: {e}") process_inputs = container_input.get("process_inputs") if process_inputs: try: inputs = process_inputs(inputs) except BaseException as e: LOGGER.error(f"Failed to filter inputs for {name_}: {e}") tags_ = (langsmith_extra.get("tags") or []) + (outer_tags or []) context.run(_TAGS.set, tags_) tags_ += tags or [] if parent_run_ is not None: new_run = parent_run_.create_child( name=name_, run_type=run_type, serialized={ "name": name, "signature": str(signature), "doc": docstring, }, inputs=inputs, tags=tags_, extra=extra_inner, run_id=id_, attachments=attachments, ) else: new_run = run_trees.RunTree( id=ls_client._ensure_uuid(id_), name=name_, serialized={ "name": name, "signature": str(signature), "doc": docstring, }, inputs=inputs, run_type=run_type, reference_example_id=ls_client._ensure_uuid( reference_example_id, accept_null=True ), project_name=selected_project, # type: ignore[arg-type] extra=extra_inner, tags=tags_, client=client_, # type: ignore attachments=attachments, ) if utils.tracing_is_enabled() is True: try: new_run.post() except BaseException as e: LOGGER.error(f"Failed to post run {new_run.id}: {e}") response_container = _TraceableContainer( new_run=new_run, project_name=selected_project, outer_project=outer_project, outer_metadata=outer_metadata, outer_tags=outer_tags, on_end=langsmith_extra.get("on_end"), context=context, ) context.run(_PROJECT_NAME.set, response_container["project_name"]) context.run(_PARENT_RUN_TREE.set, response_container["new_run"]) return response_container def _handle_container_end( container: _TraceableContainer, outputs: Optional[Any] = None, error: Optional[BaseException] = None, outputs_processor: Optional[Callable[..., dict]] = None, ) -> None: """Handle the end of run.""" try: if outputs_processor is not None: outputs = outputs_processor(outputs) _container_end(container, outputs=outputs, error=error) except BaseException as e: LOGGER.warning(f"Unable to process trace outputs: {repr(e)}") def _is_traceable_function(func: Any) -> bool: return getattr(func, "__langsmith_traceable__", False) def _get_inputs( signature: inspect.Signature, *args: Any, **kwargs: Any ) -> Dict[str, Any]: """Return a dictionary of inputs from the function signature.""" bound = signature.bind_partial(*args, **kwargs) bound.apply_defaults() arguments = dict(bound.arguments) arguments.pop("self", None) arguments.pop("cls", None) for param_name, param in signature.parameters.items(): if param.kind == inspect.Parameter.VAR_KEYWORD: # Update with the **kwargs, and remove the original entry # This is to help flatten out keyword arguments if param_name in arguments: arguments.update(arguments[param_name]) arguments.pop(param_name) return arguments def _get_inputs_safe( signature: inspect.Signature, *args: Any, **kwargs: Any ) -> Dict[str, Any]: try: return _get_inputs(signature, *args, **kwargs) except BaseException as e: LOGGER.debug(f"Failed to get inputs for {signature}: {e}") return {"args": args, "kwargs": kwargs} def _is_attachment(param: inspect.Parameter) -> bool: return param.annotation == schemas.Attachment or ( get_origin(param.annotation) == Annotated and any(arg == schemas.Attachment for arg in get_args(param.annotation)) ) def _attachment_args_helper(signature: inspect.Signature) -> Set[str]: return { name for name, param in signature.parameters.items() if _is_attachment(param) } @functools.lru_cache(maxsize=1000) def _cached_attachment_args(signature: inspect.Signature) -> Set[str]: return _attachment_args_helper(signature) def _attachment_args(signature: inspect.Signature) -> Set[str]: # Caching signatures fails if there's unhashable default values. try: return _cached_attachment_args(signature) except TypeError: return _attachment_args_helper(signature) def _get_inputs_and_attachments_safe( signature: inspect.Signature, *args: Any, **kwargs: Any ) -> Tuple[dict, schemas.Attachments]: try: inferred = _get_inputs(signature, *args, **kwargs) attachment_args = _attachment_args(signature) if attachment_args: inputs, attachments = {}, {} for k, v in inferred.items(): if k in attachment_args: attachments[k] = v else: inputs[k] = v return inputs, attachments return inferred, {} except BaseException as e: LOGGER.warning(f"Failed to get inputs for {signature}: {e}") return {"args": args, "kwargs": kwargs}, {} def _set_tracing_context(context: Dict[str, Any]): """Set the tracing context.""" for k, v in context.items(): var = _CONTEXT_KEYS[k] var.set(v) def _process_iterator( generator: Iterator[T], run_container: _TraceableContainer, is_llm_run: bool, # Results is mutated results: List[Any], ) -> Generator[T, None, Any]: try: while True: item: T = run_container["context"].run(next, generator) # type: ignore[arg-type] if is_llm_run and run_container["new_run"]: run_container["new_run"].add_event( { "name": "new_token", "time": datetime.datetime.now( datetime.timezone.utc ).isoformat(), "kwargs": {"token": item}, } ) results.append(item) yield item except StopIteration as e: return e.value async def _process_async_iterator( generator: AsyncIterator[T], run_container: _TraceableContainer, *, is_llm_run: bool, accepts_context: bool, results: List[Any], ) -> AsyncGenerator[T, None]: try: while True: if accepts_context: item = await asyncio.create_task( # type: ignore[call-arg, var-annotated] aitertools.py_anext(generator), # type: ignore[arg-type] context=run_container["context"], ) else: # Python < 3.11 with tracing_context(**get_tracing_context(run_container["context"])): item = await aitertools.py_anext(generator) if is_llm_run and run_container["new_run"]: run_container["new_run"].add_event( { "name": "new_token", "time": datetime.datetime.now( datetime.timezone.utc ).isoformat(), "kwargs": {"token": item}, } ) results.append(item) yield item except StopAsyncIteration: pass T = TypeVar("T") class _TracedStreamBase(Generic[T]): """Base class for traced stream objects.""" def __init__( self, stream: Union[Iterator[T], AsyncIterator[T]], trace_container: _TraceableContainer, reduce_fn: Optional[Callable] = None, ): self.__ls_stream__ = stream self.__ls_trace_container__ = trace_container self.__ls_completed__ = False self.__ls_reduce_fn__ = reduce_fn self.__ls_accumulated_output__: list[T] = [] self.__is_llm_run__ = ( trace_container["new_run"].run_type == "llm" if trace_container["new_run"] else False ) def __getattr__(self, name: str): return getattr(self.__ls_stream__, name) def __dir__(self): return list(set(dir(self.__class__) + dir(self.__ls_stream__))) def __repr__(self): return f"Traceable({self.__ls_stream__!r})" def __str__(self): return str(self.__ls_stream__) def __del__(self): try: if not self.__ls_completed__: self._end_trace() except BaseException: pass try: self.__ls_stream__.__del__() except BaseException: pass def _end_trace(self, error: Optional[BaseException] = None): if self.__ls_completed__: return try: if self.__ls_reduce_fn__: reduced_output = self.__ls_reduce_fn__(self.__ls_accumulated_output__) else: reduced_output = self.__ls_accumulated_output__ _container_end( self.__ls_trace_container__, outputs=reduced_output, error=error ) finally: self.__ls_completed__ = True class _TracedStream(_TracedStreamBase, Generic[T]): """A wrapper for synchronous stream objects that handles tracing.""" def __init__( self, stream: Iterator[T], trace_container: _TraceableContainer, reduce_fn: Optional[Callable] = None, ): super().__init__( stream=stream, trace_container=trace_container, reduce_fn=reduce_fn ) self.__ls_stream__ = stream self.__ls__gen__ = _process_iterator( self.__ls_stream__, self.__ls_trace_container__, is_llm_run=self.__is_llm_run__, results=self.__ls_accumulated_output__, ) def __next__(self) -> T: try: return next(self.__ls__gen__) except StopIteration: self._end_trace() raise def __iter__(self) -> Iterator[T]: try: yield from self.__ls__gen__ except BaseException as e: self._end_trace(error=e) raise else: self._end_trace() def __enter__(self): return self.__ls_stream__.__enter__() def __exit__(self, exc_type, exc_val, exc_tb): try: return self.__ls_stream__.__exit__(exc_type, exc_val, exc_tb) finally: self._end_trace(error=exc_val if exc_type else None) class _TracedAsyncStream(_TracedStreamBase, Generic[T]): """A wrapper for asynchronous stream objects that handles tracing.""" def __init__( self, stream: AsyncIterator[T], trace_container: _TraceableContainer, reduce_fn: Optional[Callable] = None, ): super().__init__( stream=stream, trace_container=trace_container, reduce_fn=reduce_fn ) self.__ls_stream__ = stream self.__ls_gen = _process_async_iterator( generator=self.__ls_stream__, run_container=self.__ls_trace_container__, is_llm_run=self.__is_llm_run__, accepts_context=aitertools.asyncio_accepts_context(), results=self.__ls_accumulated_output__, ) async def _aend_trace(self, error: Optional[BaseException] = None): ctx = copy_context() await asyncio.shield( aitertools.aio_to_thread(self._end_trace, error, __ctx=ctx) ) _set_tracing_context(get_tracing_context(ctx)) async def __anext__(self) -> T: try: return cast(T, await aitertools.py_anext(self.__ls_gen)) except StopAsyncIteration: await self._aend_trace() raise async def __aiter__(self) -> AsyncIterator[T]: try: async for item in self.__ls_gen: yield item except BaseException: await self._aend_trace() raise else: await self._aend_trace() async def __aenter__(self): return await self.__ls_stream__.__aenter__() async def __aexit__(self, exc_type, exc_val, exc_tb): try: return await self.__ls_stream__.__aexit__(exc_type, exc_val, exc_tb) finally: await self._aend_trace() def _get_function_result(results: list, reduce_fn: Callable) -> Any: if results: if reduce_fn is not None: try: return reduce_fn(results) except BaseException as e: LOGGER.error(e) return results else: return results