langchain[patch]: Compat with pydantic 2.10 (#28307)

pydantic compat 2.10 for langchain

libs/langchain/langchain/chains/api/base.py

@@ -198,7 +198,9 @@ async def acall_model(state: ChainState, config: RunnableConfig):
         api_docs: str
         question_key: str = "question"  #: :meta private:
         output_key: str = "output"  #: :meta private:
-        limit_to_domains: Optional[Sequence[str]] = Field(default_factory=list)
+        limit_to_domains: Optional[Sequence[str]] = Field(
+            default_factory=list  # type: ignore
+        )
         """Use to limit the domains that can be accessed by the API chain.
         
         * For example, to limit to just the domain `https://www.example.com`, set

libs/langchain/langchain/chains/moderation.py

@@ -38,7 +38,7 @@ class OpenAIModerationChain(Chain):
     output_key: str = "output"  #: :meta private:
     openai_api_key: Optional[str] = None
     openai_organization: Optional[str] = None
-    openai_pre_1_0: bool = Field(default=None)
+    openai_pre_1_0: bool = Field(default=False)
 
     @model_validator(mode="before")
     @classmethod

libs/langchain/langchain/memory/summary.py

@@ -3,6 +3,8 @@
 from typing import Any, Dict, List, Type
 
 from langchain_core._api import deprecated
+from langchain_core.caches import BaseCache as BaseCache  # For model_rebuild
+from langchain_core.callbacks import Callbacks as Callbacks  # For model_rebuild
 from langchain_core.chat_history import BaseChatMessageHistory
 from langchain_core.language_models import BaseLanguageModel
 from langchain_core.messages import BaseMessage, SystemMessage, get_buffer_string
@@ -131,3 +133,6 @@ def clear(self) -> None:
         """Clear memory contents."""
         super().clear()
         self.buffer = ""
+
+
+ConversationSummaryMemory.model_rebuild()

libs/langchain/langchain/memory/vectorstore_token_buffer_memory.py

@@ -109,7 +109,7 @@ class ConversationVectorStoreTokenBufferMemory(ConversationTokenBufferMemory):
     previous_history_template: str = DEFAULT_HISTORY_TEMPLATE
     split_chunk_size: int = 1000
 
-    _memory_retriever: VectorStoreRetrieverMemory = PrivateAttr(default=None)
+    _memory_retriever: VectorStoreRetrieverMemory = PrivateAttr(default=None)  # type: ignore
     _timestamps: List[datetime] = PrivateAttr(default_factory=list)
 
     @property

libs/langchain/langchain/output_parsers/fix.py

@@ -27,11 +27,12 @@ class OutputFixingParser(BaseOutputParser[T]):
     def is_lc_serializable(cls) -> bool:
         return True
 
-    parser: Annotated[BaseOutputParser[T], SkipValidation()]
+    parser: Annotated[Any, SkipValidation()]
     """The parser to use to parse the output."""
     # Should be an LLMChain but we want to avoid top-level imports from langchain.chains
-    retry_chain: Union[
-        RunnableSerializable[OutputFixingParserRetryChainInput, str], Any
+    retry_chain: Annotated[
+        Union[RunnableSerializable[OutputFixingParserRetryChainInput, str], Any],
+        SkipValidation(),
     ]
     """The RunnableSerializable to use to retry the completion (Legacy: LLMChain)."""
     max_retries: int = 1

libs/langchain/langchain/output_parsers/retry.py

@@ -57,7 +57,10 @@ class RetryOutputParser(BaseOutputParser[T]):
     parser: Annotated[BaseOutputParser[T], SkipValidation()]
     """The parser to use to parse the output."""
     # Should be an LLMChain but we want to avoid top-level imports from langchain.chains
-    retry_chain: Union[RunnableSerializable[RetryOutputParserRetryChainInput, str], Any]
+    retry_chain: Annotated[
+        Union[RunnableSerializable[RetryOutputParserRetryChainInput, str], Any],
+        SkipValidation(),
+    ]
     """The RunnableSerializable to use to retry the completion (Legacy: LLMChain)."""
     max_retries: int = 1
     """The maximum number of times to retry the parse."""
@@ -187,8 +190,11 @@ class RetryWithErrorOutputParser(BaseOutputParser[T]):
     parser: Annotated[BaseOutputParser[T], SkipValidation()]
     """The parser to use to parse the output."""
     # Should be an LLMChain but we want to avoid top-level imports from langchain.chains
-    retry_chain: Union[
-        RunnableSerializable[RetryWithErrorOutputParserRetryChainInput, str], Any
+    retry_chain: Annotated[
+        Union[
+            RunnableSerializable[RetryWithErrorOutputParserRetryChainInput, str], Any
+        ],
+        SkipValidation(),
     ]
     """The RunnableSerializable to use to retry the completion (Legacy: LLMChain)."""
     max_retries: int = 1

libs/langchain/tests/unit_tests/output_parsers/test_fix.py

@@ -50,7 +50,7 @@ def test_output_fixing_parser_parse(
         base_parser.attemp_count_before_success
     )  # Success on the (n+1)-th attempt  # noqa
     base_parser = SuccessfulParseAfterRetries(attemp_count_before_success=n)
-    parser = OutputFixingParser(
+    parser = OutputFixingParser[str](
         parser=base_parser,
         max_retries=n,  # n times to retry, that is, (n+1) times call
         retry_chain=RunnablePassthrough(),
@@ -94,7 +94,7 @@ async def test_output_fixing_parser_aparse(
         base_parser.attemp_count_before_success
     )  # Success on the (n+1)-th attempt   # noqa
     base_parser = SuccessfulParseAfterRetries(attemp_count_before_success=n)
-    parser = OutputFixingParser(
+    parser = OutputFixingParser[str](
         parser=base_parser,
         max_retries=n,  # n times to retry, that is, (n+1) times call
         retry_chain=RunnablePassthrough(),
@@ -108,7 +108,7 @@ async def test_output_fixing_parser_aparse(
 def test_output_fixing_parser_parse_fail() -> None:
     n: int = 5  # Success on the (n+1)-th attempt
     base_parser = SuccessfulParseAfterRetries(attemp_count_before_success=n)
-    parser = OutputFixingParser(
+    parser = OutputFixingParser[str](
         parser=base_parser,
         max_retries=n - 1,  # n-1 times to retry, that is, n times call
         retry_chain=RunnablePassthrough(),
@@ -122,7 +122,7 @@ def test_output_fixing_parser_parse_fail() -> None:
 async def test_output_fixing_parser_aparse_fail() -> None:
     n: int = 5  # Success on the (n+1)-th attempt
     base_parser = SuccessfulParseAfterRetries(attemp_count_before_success=n)
-    parser = OutputFixingParser(
+    parser = OutputFixingParser[str](
         parser=base_parser,
         max_retries=n - 1,  # n-1 times to retry, that is, n times call
         retry_chain=RunnablePassthrough(),
@@ -143,7 +143,9 @@ async def test_output_fixing_parser_aparse_fail() -> None:
 def test_output_fixing_parser_output_type(
     base_parser: BaseOutputParser,
 ) -> None:
-    parser = OutputFixingParser(parser=base_parser, retry_chain=RunnablePassthrough())
+    parser = OutputFixingParser[str](
+        parser=base_parser, retry_chain=RunnablePassthrough()
+    )
     assert parser.OutputType is base_parser.OutputType
 
 
@@ -176,7 +178,7 @@ def test_output_fixing_parser_parse_with_retry_chain(
     instructions = base_parser.get_format_instructions()
     object.__setattr__(base_parser, "get_format_instructions", lambda: instructions)
     # test
-    parser = OutputFixingParser(
+    parser = OutputFixingParser[str](
         parser=base_parser,
         retry_chain=retry_chain,
         legacy=False,
@@ -212,7 +214,7 @@ async def test_output_fixing_parser_aparse_with_retry_chain(
     instructions = base_parser.get_format_instructions()
     object.__setattr__(base_parser, "get_format_instructions", lambda: instructions)
     # test
-    parser = OutputFixingParser(
+    parser = OutputFixingParser[str](
         parser=base_parser,
         retry_chain=retry_chain,
         legacy=False,