Merge branch 'master' into update-azuresearch

docs/docs/expression_language/why.ipynb

@@ -1007,7 +1007,7 @@
     "from langchain_openai import OpenAI\n",
     "from langchain_core.output_parsers import StrOutputParser\n",
     "from langchain_core.prompts import ChatPromptTemplate\n",
-    "from langchain_core.runnables import RunnablePassthrough\n",
+    "from langchain_core.runnables import RunnablePassthrough, ConfigurableField\n",
     "\n",
     "os.environ[\"LANGCHAIN_API_KEY\"] = \"...\"\n",
     "os.environ[\"LANGCHAIN_TRACING_V2\"] = \"true\"\n",

libs/community/langchain_community/cache.py

@@ -56,7 +56,7 @@
 from langchain_core.embeddings import Embeddings
 from langchain_core.language_models.llms import LLM, get_prompts
 from langchain_core.load.dump import dumps
-from langchain_core.load.load import _loads_suppress_warning
+from langchain_core.load.load import loads
 from langchain_core.outputs import ChatGeneration, Generation
 from langchain_core.utils import get_from_env
 
@@ -149,10 +149,7 @@ def _loads_generations(generations_str: str) -> Union[RETURN_VAL_TYPE, None]:
         RETURN_VAL_TYPE: A list of generations.
     """
     try:
-        generations = [
-            _loads_suppress_warning(_item_str)
-            for _item_str in json.loads(generations_str)
-        ]
+        generations = [loads(_item_str) for _item_str in json.loads(generations_str)]
         return generations
     except (json.JSONDecodeError, TypeError):
         # deferring the (soft) handling to after the legacy-format attempt
@@ -227,7 +224,7 @@ def lookup(self, prompt: str, llm_string: str) -> Optional[RETURN_VAL_TYPE]:
             rows = session.execute(stmt).fetchall()
             if rows:
                 try:
-                    return [_loads_suppress_warning(row[0]) for row in rows]
+                    return [loads(row[0]) for row in rows]
                 except Exception:
                     logger.warning(
                         "Retrieving a cache value that could not be deserialized "
@@ -398,7 +395,7 @@ def lookup(self, prompt: str, llm_string: str) -> Optional[RETURN_VAL_TYPE]:
         if results:
             for _, text in results.items():
                 try:
-                    generations.append(_loads_suppress_warning(text))
+                    generations.append(loads(text))
                 except Exception:
                     logger.warning(
                         "Retrieving a cache value that could not be deserialized "
@@ -538,9 +535,7 @@ def lookup(self, prompt: str, llm_string: str) -> Optional[RETURN_VAL_TYPE]:
         if results:
             for document in results:
                 try:
-                    generations.extend(
-                        _loads_suppress_warning(document.metadata["return_val"])
-                    )
+                    generations.extend(loads(document.metadata["return_val"]))
                 except Exception:
                     logger.warning(
                         "Retrieving a cache value that could not be deserialized "
@@ -1190,7 +1185,7 @@ def lookup(self, prompt: str, llm_string: str) -> Optional[RETURN_VAL_TYPE]:
         """Look up based on prompt and llm_string."""
         rows = self._search_rows(prompt, llm_string)
         if rows:
-            return [_loads_suppress_warning(row[0]) for row in rows]
+            return [loads(row[0]) for row in rows]
         return None
 
     def update(self, prompt: str, llm_string: str, return_val: RETURN_VAL_TYPE) -> None:

libs/community/langchain_community/chat_loaders/langsmith.py

@@ -4,7 +4,7 @@
 from typing import TYPE_CHECKING, Dict, Iterable, Iterator, List, Optional, Union, cast
 
 from langchain_core.chat_sessions import ChatSession
-from langchain_core.load.load import _load_suppress_warning
+from langchain_core.load.load import load
 
 from langchain_community.chat_loaders.base import BaseChatLoader
 
@@ -66,10 +66,8 @@ def _get_messages_from_llm_run(llm_run: "Run") -> ChatSession:
             raise ValueError(f"Run has no 'messages' inputs. Got {llm_run.inputs}")
         if not llm_run.outputs:
             raise ValueError("Cannot convert pending run")
-        messages = _load_suppress_warning(llm_run.inputs)["messages"]
-        message_chunk = _load_suppress_warning(llm_run.outputs)["generations"][0][
-            "message"
-        ]
+        messages = load(llm_run.inputs)["messages"]
+        message_chunk = load(llm_run.outputs)["generations"][0]["message"]
         return ChatSession(messages=messages + [message_chunk])
 
     @staticmethod

libs/community/langchain_community/chat_models/anyscale.py

@@ -4,10 +4,9 @@
 import logging
 import os
 import sys
-from typing import TYPE_CHECKING, Any, Dict, Optional, Set
+from typing import TYPE_CHECKING, Dict, Optional, Set
 
 import requests
-from langchain_core._api.deprecation import suppress_langchain_deprecation_warning
 from langchain_core.messages import BaseMessage
 from langchain_core.pydantic_v1 import Field, SecretStr, root_validator
 from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
@@ -73,11 +72,6 @@ def is_lc_serializable(cls) -> bool:
     available_models: Optional[Set[str]] = None
     """Available models from Anyscale API."""
 
-    def __init__(self, *kwargs: Any) -> None:
-        # bypass deprecation warning for ChatOpenAI
-        with suppress_langchain_deprecation_warning():
-            super().__init__(*kwargs)
-
     @staticmethod
     def get_available_models(
         anyscale_api_key: Optional[str] = None,

libs/community/langchain_community/chat_models/everlyai.py

@@ -3,9 +3,8 @@
 
 import logging
 import sys
-from typing import TYPE_CHECKING, Any, Dict, Optional, Set
+from typing import TYPE_CHECKING, Dict, Optional, Set
 
-from langchain_core._api.deprecation import suppress_langchain_deprecation_warning
 from langchain_core.messages import BaseMessage
 from langchain_core.pydantic_v1 import Field, root_validator
 from langchain_core.utils import get_from_dict_or_env
@@ -65,11 +64,6 @@ def is_lc_serializable(cls) -> bool:
     available_models: Optional[Set[str]] = None
     """Available models from EverlyAI API."""
 
-    def __init__(self, *kwargs: Any) -> None:
-        # bypass deprecation warning for ChatOpenAI
-        with suppress_langchain_deprecation_warning():
-            super().__init__(*kwargs)
-
     @staticmethod
     def get_available_models() -> Set[str]:
         """Get available models from EverlyAI API."""

libs/community/langchain_community/chat_models/promptlayer_openai.py

@@ -2,7 +2,6 @@
 import datetime
 from typing import Any, Dict, List, Optional
 
-from langchain_core._api.deprecation import suppress_langchain_deprecation_warning
 from langchain_core.callbacks import (
     AsyncCallbackManagerForLLMRun,
     CallbackManagerForLLMRun,
@@ -40,11 +39,6 @@ class PromptLayerChatOpenAI(ChatOpenAI):
     pl_tags: Optional[List[str]]
     return_pl_id: Optional[bool] = False
 
-    def __init__(self, *kwargs: Any) -> None:
-        # bypass deprecation warning for ChatOpenAI
-        with suppress_langchain_deprecation_warning():
-            super().__init__(*kwargs)
-
     @classmethod
     def is_lc_serializable(cls) -> bool:
         return False

libs/community/langchain_community/llms/promptlayer_openai.py

@@ -1,7 +1,6 @@
 import datetime
 from typing import Any, List, Optional
 
-from langchain_core._api.deprecation import suppress_langchain_deprecation_warning
 from langchain_core.callbacks import (
     AsyncCallbackManagerForLLMRun,
     CallbackManagerForLLMRun,
@@ -38,11 +37,6 @@ class PromptLayerOpenAI(OpenAI):
     pl_tags: Optional[List[str]]
     return_pl_id: Optional[bool] = False
 
-    def __init__(self, *kwargs: Any) -> None:
-        # bypass deprecation warning for ChatOpenAI
-        with suppress_langchain_deprecation_warning():
-            super().__init__(*kwargs)
-
     @classmethod
     def is_lc_serializable(cls) -> bool:
         return False

libs/community/pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "langchain-community"
-version = "0.0.9"
+version = "0.0.10"
 description = "Community contributed LangChain integrations."
 authors = []
 license = "MIT"
@@ -9,7 +9,7 @@ repository = "https://github.com/langchain-ai/langchain"
 
 [tool.poetry.dependencies]
 python = ">=3.8.1,<4.0"
-langchain-core = ">=0.1.7,<0.2"
+langchain-core = ">=0.1.8,<0.2"
 SQLAlchemy = ">=1.4,<3"
 requests = "^2"
 PyYAML = ">=5.3"

libs/core/langchain_core/_api/beta_decorator.py

@@ -15,6 +15,8 @@
 import warnings
 from typing import Any, Callable, Generator, Type, TypeVar
 
+from langchain_core._api.internal import is_caller_internal
+
 
 class LangChainBetaWarning(DeprecationWarning):
     """A class for issuing beta warnings for LangChain users."""
@@ -78,21 +80,60 @@ def beta(
         _addendum: str = addendum,
     ) -> T:
         """Implementation of the decorator returned by `beta`."""
+
+        def emit_warning() -> None:
+            """Emit the warning."""
+            warn_beta(
+                message=_message,
+                name=_name,
+                obj_type=_obj_type,
+                addendum=_addendum,
+            )
+
+        warned = False
+
+        def warning_emitting_wrapper(*args: Any, **kwargs: Any) -> Any:
+            """Wrapper for the original wrapped callable that emits a warning.
+
+            Args:
+                *args: The positional arguments to the function.
+                **kwargs: The keyword arguments to the function.
+
+            Returns:
+                The return value of the function being wrapped.
+            """
+            nonlocal warned
+            if not warned and not is_caller_internal():
+                warned = True
+                emit_warning()
+            return wrapped(*args, **kwargs)
+
         if isinstance(obj, type):
             if not _obj_type:
                 _obj_type = "class"
             wrapped = obj.__init__  # type: ignore
             _name = _name or obj.__name__
             old_doc = obj.__doc__
 
-            def finalize(wrapper: Callable[..., Any], new_doc: str) -> T:
+            def finalize(_: Any, new_doc: str) -> T:
                 """Finalize the annotation of a class."""
                 try:
                     obj.__doc__ = new_doc
                 except AttributeError:  # Can't set on some extension objects.
                     pass
+
+                def warn_if_direct_instance(
+                    self: Any, *args: Any, **kwargs: Any
+                ) -> Any:
+                    """Warn that the class is in beta."""
+                    nonlocal warned
+                    if not warned and type(self) is obj and not is_caller_internal():
+                        warned = True
+                        emit_warning()
+                    return wrapped(self, *args, **kwargs)
+
                 obj.__init__ = functools.wraps(obj.__init__)(  # type: ignore[misc]
-                    wrapper
+                    warn_if_direct_instance
                 )
                 return obj
 
@@ -155,28 +196,6 @@ def finalize(  # type: ignore
                 wrapper.__doc__ = new_doc
                 return wrapper
 
-        def emit_warning() -> None:
-            """Emit the warning."""
-            warn_beta(
-                message=_message,
-                name=_name,
-                obj_type=_obj_type,
-                addendum=_addendum,
-            )
-
-        def warning_emitting_wrapper(*args: Any, **kwargs: Any) -> Any:
-            """Wrapper for the original wrapped callable that emits a warning.
-
-            Args:
-                *args: The positional arguments to the function.
-                **kwargs: The keyword arguments to the function.
-
-            Returns:
-                The return value of the function being wrapped.
-            """
-            emit_warning()
-            return wrapped(*args, **kwargs)
-
         old_doc = inspect.cleandoc(old_doc or "").strip("\n")
 
         if not old_doc: