core: deprecate problematic dict() method

Author: cbornet

libs/core/langchain_core/language_models/chat_models.py

@@ -3,9 +3,9 @@
 from __future__ import annotations
 
 import asyncio
+import builtins
 import inspect
 import json
-import typing
 from abc import ABC, abstractmethod
 from collections.abc import AsyncIterator, Callable, Iterator, Sequence
 from functools import cached_property
@@ -15,6 +15,7 @@
 from pydantic import BaseModel, ConfigDict, Field
 from typing_extensions import override
 
+from langchain_core._api import deprecated
 from langchain_core.caches import BaseCache
 from langchain_core.callbacks import (
     AsyncCallbackManager,
@@ -357,7 +358,7 @@ class BaseChatModel(BaseLanguageModel[AIMessage], ABC):
     )
 
     @cached_property
-    def _serialized(self) -> dict[str, Any]:
+    def _serialized(self) -> builtins.dict[str, Any]:
         return dumpd(self)
 
     # --- Runnable methods ---
@@ -730,7 +731,10 @@ async def astream(
 
     # --- Custom methods ---
 
-    def _combine_llm_outputs(self, llm_outputs: list[dict | None]) -> dict:  # noqa: ARG002
+    def _combine_llm_outputs(
+        self,
+        llm_outputs: list[builtins.dict | None],  # noqa: ARG002
+    ) -> builtins.dict:
         return {}
 
     def _convert_cached_generations(self, cache_val: list) -> list[ChatGeneration]:
@@ -776,8 +780,8 @@ def _get_invocation_params(
         self,
         stop: list[str] | None = None,
         **kwargs: Any,
-    ) -> dict:
-        params = self.dict()
+    ) -> builtins.dict:
+        params = self.asdict()
         params["stop"] = stop
         return {**params, **kwargs}
 
@@ -842,7 +846,7 @@ def generate(
         callbacks: Callbacks = None,
         *,
         tags: list[str] | None = None,
-        metadata: dict[str, Any] | None = None,
+        metadata: builtins.dict[str, Any] | None = None,
         run_name: str | None = None,
         run_id: uuid.UUID | None = None,
         **kwargs: Any,
@@ -965,7 +969,7 @@ async def agenerate(
         callbacks: Callbacks = None,
         *,
         tags: list[str] | None = None,
-        metadata: dict[str, Any] | None = None,
+        metadata: builtins.dict[str, Any] | None = None,
         run_name: str | None = None,
         run_id: uuid.UUID | None = None,
         **kwargs: Any,
@@ -1491,18 +1495,23 @@ async def _call_async(
     def _llm_type(self) -> str:
         """Return type of chat model."""
 
-    @override
-    def dict(self, **kwargs: Any) -> dict:
+    @deprecated("1.0.2", alternative="asdict", removal="2.0")
+    def dict(self, **_kwargs: Any) -> builtins.dict[str, Any]:
+        """DEPRECATED - use `asdict()` instead.
+
+        Return a dictionary of the LLM.
+        """
+        return self.asdict()
+
+    def asdict(self) -> builtins.dict[str, Any]:
         """Return a dictionary of the LLM."""
         starter_dict = dict(self._identifying_params)
         starter_dict["_type"] = self._llm_type
         return starter_dict
 
     def bind_tools(
         self,
-        tools: Sequence[
-            typing.Dict[str, Any] | type | Callable | BaseTool  # noqa: UP006
-        ],
+        tools: Sequence[builtins.dict[str, Any] | type | Callable | BaseTool],
         *,
         tool_choice: str | None = None,
         **kwargs: Any,
@@ -1521,11 +1530,11 @@ def bind_tools(
 
     def with_structured_output(
         self,
-        schema: typing.Dict | type,  # noqa: UP006
+        schema: builtins.dict | type,
         *,
         include_raw: bool = False,
         **kwargs: Any,
-    ) -> Runnable[LanguageModelInput, typing.Dict | BaseModel]:  # noqa: UP006
+    ) -> Runnable[LanguageModelInput, builtins.dict | BaseModel]:
         """Model wrapper that returns outputs formatted to match the given schema.
 
         Args:

libs/core/langchain_core/language_models/llms.py

@@ -6,6 +6,7 @@
 from __future__ import annotations
 
 import asyncio
+import builtins
 import functools
 import inspect
 import json
@@ -32,6 +33,7 @@
 )
 from typing_extensions import override
 
+from langchain_core._api import deprecated
 from langchain_core.caches import BaseCache
 from langchain_core.callbacks import (
     AsyncCallbackManager,
@@ -298,7 +300,7 @@ class BaseLLM(BaseLanguageModel[str], ABC):
     )
 
     @functools.cached_property
-    def _serialized(self) -> dict[str, Any]:
+    def _serialized(self) -> builtins.dict[str, Any]:
         return dumpd(self)
 
     # --- Runnable methods ---
@@ -514,7 +516,7 @@ def stream(
         else:
             prompt = self._convert_input(input).to_string()
             config = ensure_config(config)
-            params = self.dict()
+            params = self.asdict()
             params["stop"] = stop
             params = {**params, **kwargs}
             options = {"stop": stop}
@@ -584,7 +586,7 @@ async def astream(
 
         prompt = self._convert_input(input).to_string()
         config = ensure_config(config)
-        params = self.dict()
+        params = self.asdict()
         params["stop"] = stop
         params = {**params, **kwargs}
         options = {"stop": stop}
@@ -839,7 +841,7 @@ def generate(
         callbacks: Callbacks | list[Callbacks] | None = None,
         *,
         tags: list[str] | list[list[str]] | None = None,
-        metadata: dict[str, Any] | list[dict[str, Any]] | None = None,
+        metadata: builtins.dict[str, Any] | list[builtins.dict[str, Any]] | None = None,
         run_name: str | list[str] | None = None,
         run_id: uuid.UUID | list[uuid.UUID | None] | None = None,
         **kwargs: Any,
@@ -972,7 +974,7 @@ def generate(
             ] * len(prompts)
             run_name_list = [cast("str | None", run_name)] * len(prompts)
         run_ids_list = self._get_run_ids_list(run_id, prompts)
-        params = self.dict()
+        params = self.asdict()
         params["stop"] = stop
         options = {"stop": stop}
         (
@@ -1114,7 +1116,7 @@ async def agenerate(
         callbacks: Callbacks | list[Callbacks] | None = None,
         *,
         tags: list[str] | list[list[str]] | None = None,
-        metadata: dict[str, Any] | list[dict[str, Any]] | None = None,
+        metadata: builtins.dict[str, Any] | list[builtins.dict[str, Any]] | None = None,
         run_name: str | list[str] | None = None,
         run_id: uuid.UUID | list[uuid.UUID | None] | None = None,
         **kwargs: Any,
@@ -1236,7 +1238,7 @@ async def agenerate(
             ] * len(prompts)
             run_name_list = [cast("str | None", run_name)] * len(prompts)
         run_ids_list = self._get_run_ids_list(run_id, prompts)
-        params = self.dict()
+        params = self.asdict()
         params["stop"] = stop
         options = {"stop": stop}
         (
@@ -1328,7 +1330,7 @@ async def _call_async(
         callbacks: Callbacks = None,
         *,
         tags: list[str] | None = None,
-        metadata: dict[str, Any] | None = None,
+        metadata: builtins.dict[str, Any] | None = None,
         **kwargs: Any,
     ) -> str:
         """Check Cache and run the LLM on the given prompt and input."""
@@ -1352,8 +1354,15 @@ def __str__(self) -> str:
     def _llm_type(self) -> str:
         """Return type of llm."""
 
-    @override
-    def dict(self, **kwargs: Any) -> dict:
+    @deprecated("1.0.2", alternative="asdict", removal="2.0")
+    def dict(self, **_kwargs: Any) -> builtins.dict[str, Any]:
+        """DEPRECATED - use `asdict()` instead.
+
+        Return a dictionary of the LLM.
+        """
+        return self.asdict()
+
+    def asdict(self) -> builtins.dict[str, Any]:
         """Return a dictionary of the LLM."""
         starter_dict = dict(self._identifying_params)
         starter_dict["_type"] = self._llm_type
@@ -1380,7 +1389,7 @@ def save(self, file_path: Path | str) -> None:
         directory_path.mkdir(parents=True, exist_ok=True)
 
         # Fetch dictionary to save
-        prompt_dict = self.dict()
+        prompt_dict = self.asdict()
 
         if save_path.suffix == ".json":
             with save_path.open("w", encoding="utf-8") as f:

libs/core/langchain_core/output_parsers/base.py

@@ -2,6 +2,7 @@
 
 from __future__ import annotations
 
+import builtins
 import contextlib
 from abc import ABC, abstractmethod
 from typing import (
@@ -13,6 +14,7 @@
 
 from typing_extensions import override
 
+from langchain_core._api import deprecated
 from langchain_core.language_models import LanguageModelOutput
 from langchain_core.messages import AnyMessage, BaseMessage
 from langchain_core.outputs import ChatGeneration, Generation
@@ -328,7 +330,12 @@ def _type(self) -> str:
         )
         raise NotImplementedError(msg)
 
-    def dict(self, **kwargs: Any) -> dict:
+    @deprecated("1.0.2", alternative="asdict", removal="2.0")
+    @override
+    def dict(self, **kwargs: Any) -> builtins.dict[str, Any]:
+        return self.asdict()
+
+    def asdict(self, **kwargs: Any) -> builtins.dict[str, Any]:
         """Return dictionary representation of output parser."""
         output_parser_dict = super().model_dump(**kwargs)
         with contextlib.suppress(NotImplementedError):

libs/core/langchain_core/prompts/base.py

@@ -2,9 +2,9 @@
 
 from __future__ import annotations
 
+import builtins
 import contextlib
 import json
-import typing
 from abc import ABC, abstractmethod
 from collections.abc import Mapping
 from functools import cached_property
@@ -20,6 +20,7 @@
 from pydantic import BaseModel, ConfigDict, Field, model_validator
 from typing_extensions import Self, override
 
+from langchain_core._api import deprecated
 from langchain_core.exceptions import ErrorCode, create_message
 from langchain_core.load import dumpd
 from langchain_core.output_parsers.base import BaseOutputParser
@@ -56,7 +57,7 @@ class BasePromptTemplate(
 
     These variables are auto inferred from the prompt and user need not provide them.
     """
-    input_types: typing.Dict[str, Any] = Field(default_factory=dict, exclude=True)  # noqa: UP006
+    input_types: builtins.dict[str, Any] = Field(default_factory=dict, exclude=True)
     """A dictionary of the types of the variables the prompt template expects.
 
     If not provided, all variables are assumed to be strings.
@@ -69,7 +70,7 @@ class BasePromptTemplate(
     Partial variables populate the template so that you don't need to pass them in every
     time you call the prompt.
     """
-    metadata: typing.Dict[str, Any] | None = None  # noqa: UP006
+    metadata: builtins.dict[str, Any] | None = None
     """Metadata to be used for tracing."""
     tags: list[str] | None = None
     """Tags to be used for tracing."""
@@ -121,7 +122,7 @@ def is_lc_serializable(cls) -> bool:
     )
 
     @cached_property
-    def _serialized(self) -> dict[str, Any]:
+    def _serialized(self) -> builtins.dict[str, Any]:
         return dumpd(self)
 
     @property
@@ -152,7 +153,7 @@ def get_input_schema(self, config: RunnableConfig | None = None) -> type[BaseMod
             field_definitions={**required_input_variables, **optional_input_variables},
         )
 
-    def _validate_input(self, inner_input: Any) -> dict:
+    def _validate_input(self, inner_input: Any) -> builtins.dict:
         if not isinstance(inner_input, dict):
             if len(self.input_variables) == 1:
                 var_name = self.input_variables[0]
@@ -186,19 +187,23 @@ def _validate_input(self, inner_input: Any) -> dict:
             )
         return inner_input
 
-    def _format_prompt_with_error_handling(self, inner_input: dict) -> PromptValue:
+    def _format_prompt_with_error_handling(
+        self,
+        inner_input: builtins.dict,
+    ) -> PromptValue:
         inner_input_ = self._validate_input(inner_input)
         return self.format_prompt(**inner_input_)
 
     async def _aformat_prompt_with_error_handling(
-        self, inner_input: dict
+        self,
+        inner_input: builtins.dict,
     ) -> PromptValue:
         inner_input_ = self._validate_input(inner_input)
         return await self.aformat_prompt(**inner_input_)
 
     @override
     def invoke(
-        self, input: dict, config: RunnableConfig | None = None, **kwargs: Any
+        self, input: builtins.dict, config: RunnableConfig | None = None, **kwargs: Any
     ) -> PromptValue:
         """Invoke the prompt.
 
@@ -224,7 +229,7 @@ def invoke(
 
     @override
     async def ainvoke(
-        self, input: dict, config: RunnableConfig | None = None, **kwargs: Any
+        self, input: builtins.dict, config: RunnableConfig | None = None, **kwargs: Any
     ) -> PromptValue:
         """Async invoke the prompt.
 
@@ -286,7 +291,9 @@ def partial(self, **kwargs: str | Callable[[], str]) -> BasePromptTemplate:
         prompt_dict["partial_variables"] = {**self.partial_variables, **kwargs}
         return type(self)(**prompt_dict)
 
-    def _merge_partial_and_user_variables(self, **kwargs: Any) -> dict[str, Any]:
+    def _merge_partial_and_user_variables(
+        self, **kwargs: Any
+    ) -> builtins.dict[str, Any]:
         # Get partial params:
         partial_kwargs = {
             k: v if not callable(v) else v() for k, v in self.partial_variables.items()
@@ -330,7 +337,15 @@ def _prompt_type(self) -> str:
         """Return the prompt type key."""
         raise NotImplementedError
 
-    def dict(self, **kwargs: Any) -> dict:
+    @deprecated("1.0.2", alternative="asdict", removal="2.0")
+    def dict(self, **kwargs: Any) -> builtins.dict[str, Any]:
+        """DEPRECATED - use `asdict()` instead.
+
+        Return a dictionary of the LLM.
+        """
+        return self.asdict(**kwargs)
+
+    def asdict(self, **kwargs: Any) -> builtins.dict[str, Any]:
         """Return dictionary representation of prompt.
 
         Args:
@@ -365,7 +380,7 @@ def save(self, file_path: Path | str) -> None:
             raise ValueError(msg)
 
         # Fetch dictionary to save
-        prompt_dict = self.dict()
+        prompt_dict = self.asdict()
         if "_type" not in prompt_dict:
             msg = f"Prompt {self} does not support saving."
             raise NotImplementedError(msg)