x

libs/langchain/langchain_classic/agents/mrkl/output_parser.py

@@ -41,7 +41,9 @@ class MRKLOutputParser(AgentOutputParser):
             OutputParserException: If the output could not be parsed.
         """
         includes_answer = FINAL_ANSWER_ACTION in text
-        regex = r"Action\s*\d*\s*:[\s]*(.*?)Action\s*\d*\s*Input\s*\d*\s*:[\s]*(.*)"
+        regex = (
+            r"Action\s*\d*\s*:[\s]*(.*?)[\s]*Action\s*\d*\s*Input\s*\d*\s*:[\s]*(.*)"
+        )
         action_match = re.search(regex, text, re.DOTALL)
         if action_match and includes_answer:
             if text.find(FINAL_ANSWER_ACTION) < text.find(action_match.group(0)):

libs/langchain/langchain_classic/agents/openai_assistant/base.py

@@ -21,7 +21,7 @@ from typing_extensions import Self, override
 
 if TYPE_CHECKING:
     import openai
-    from openai.types.beta.threads import ThreadMessage
+    from openai.types.beta.threads import ThreadMessage  # type: ignore[attr-defined]
     from openai.types.beta.threads.required_action_function_tool_call import (
         RequiredActionFunctionToolCall,
     )
@@ -276,10 +276,10 @@ class OpenAIAssistantRunnable(RunnableSerializable[dict, OutputType]):
             OpenAIAssistantRunnable configured to run using the created assistant.
         """
         client = client or _get_openai_client()
-        assistant = client.beta.assistants.create(
+        assistant = client.beta.assistants.create(  # type: ignore[deprecated]
             name=name,
             instructions=instructions,
-            tools=[_get_assistants_tool(tool) for tool in tools],
+            tools=[_get_assistants_tool(tool) for tool in tools],  # type: ignore[misc]
             model=model,
         )
         return cls(assistant_id=assistant.id, client=client, **kwargs)
@@ -409,10 +409,10 @@ class OpenAIAssistantRunnable(RunnableSerializable[dict, OutputType]):
         """
         async_client = async_client or _get_openai_async_client()
         openai_tools = [_get_assistants_tool(tool) for tool in tools]
-        assistant = await async_client.beta.assistants.create(
+        assistant = await async_client.beta.assistants.create(  # type: ignore[deprecated]
             name=name,
             instructions=instructions,
-            tools=openai_tools,
+            tools=openai_tools,  # type: ignore[arg-type]
             model=model,
         )
         return cls(assistant_id=assistant.id, async_client=async_client, **kwargs)
@@ -617,7 +617,7 @@ class OpenAIAssistantRunnable(RunnableSerializable[dict, OutputType]):
                     if version_gte_1_14
                     else isinstance(
                         content,
-                        openai.types.beta.threads.MessageContentText,
+                        openai.types.beta.threads.MessageContentText,  # type: ignore[attr-defined]
                     )
                 )
                 for content in answer
@@ -771,7 +771,7 @@ class OpenAIAssistantRunnable(RunnableSerializable[dict, OutputType]):
                     if version_gte_1_14
                     else isinstance(
                         content,
-                        openai.types.beta.threads.MessageContentText,
+                        openai.types.beta.threads.MessageContentText,  # type: ignore[attr-defined]
                     )
                 )
                 for content in answer

libs/langchain/langchain_classic/agents/output_parsers/react_single_input.py

@@ -52,7 +52,9 @@ class ReActSingleInputOutputParser(AgentOutputParser):
     @override
     def parse(self, text: str) -> AgentAction | AgentFinish:
         includes_answer = FINAL_ANSWER_ACTION in text
-        regex = r"Action\s*\d*\s*:[\s]*(.*?)Action\s*\d*\s*Input\s*\d*\s*:[\s]*(.*)"
+        regex = (
+            r"Action\s*\d*\s*:[\s]*(.*?)[\s]*Action\s*\d*\s*Input\s*\d*\s*:[\s]*(.*)"
+        )
         action_match = re.search(regex, text, re.DOTALL)
         if action_match:
             if includes_answer:

libs/langchain/langchain_classic/chains/moderation.py

@@ -69,7 +69,7 @@ class OpenAIModerationChain(Chain):
             except ValueError:
                 values["openai_pre_1_0"] = True
             if values["openai_pre_1_0"]:
-                values["client"] = openai.Moderation
+                values["client"] = openai.Moderation  # type: ignore[attr-defined]
             else:
                 values["client"] = openai.OpenAI(api_key=openai_api_key)
                 values["async_client"] = openai.AsyncOpenAI(api_key=openai_api_key)

libs/langchain/langchain_classic/evaluation/embedding_distance/base.py

@@ -60,7 +60,7 @@ def _embedding_factory() -> Embeddings:
         from langchain_openai import OpenAIEmbeddings
     except ImportError:
         try:
-            from langchain_community.embeddings.openai import (
+            from langchain_community.embeddings.openai import (  # type: ignore[no-redef]
                 OpenAIEmbeddings,
             )
         except ImportError as e:
@@ -121,7 +121,7 @@ class _EmbeddingDistanceChainMixin(Chain):
             pass
 
         try:
-            from langchain_community.embeddings.openai import (
+            from langchain_community.embeddings.openai import (  # type: ignore[no-redef]
                 OpenAIEmbeddings,
             )
 

libs/langchain/langchain_classic/evaluation/loading.py

@@ -152,7 +152,7 @@ def load_evaluator(
                 from langchain_openai import ChatOpenAI
             except ImportError:
                 try:
-                    from langchain_community.chat_models.openai import (
+                    from langchain_community.chat_models.openai import (  # type: ignore[no-redef]
                         ChatOpenAI,
                     )
                 except ImportError as e:

libs/langchain/pyproject.toml

@@ -20,10 +20,10 @@ classifiers = [
     "Topic :: Software Development :: Libraries :: Python Modules",
 ]
 
-version = "1.0.2"
+version = "1.0.1"
 requires-python = ">=3.10.0,<4.0.0"
 dependencies = [
-    "langchain-core>=1.2.17,<2.0.0",
+    "langchain-core>=1.2.5,<2.0.0",
     "langchain-text-splitters>=1.1.0,<2.0.0",
     "langsmith>=0.1.17,<1.0.0",
     "pydantic>=2.7.4,<3.0.0",

libs/langchain/tests/unit_tests/agents/output_parsers/test_react_single_input.py

@@ -1,6 +1,3 @@
-import signal
-import sys
-
 import pytest
 from langchain_core.agents import AgentAction, AgentFinish
 from langchain_core.exceptions import OutputParserException
@@ -46,32 +43,3 @@ Action: search Final Answer:
 Action Input: what is the temperature in SF?"""
     with pytest.raises(OutputParserException):
         parser.invoke(_input)
-
-
-def _timeout_handler(_signum: int, _frame: object) -> None:
-    msg = "ReDoS: regex took too long"
-    raise TimeoutError(msg)
-
-
-@pytest.mark.skipif(
-    sys.platform == "win32", reason="SIGALRM is not available on Windows"
-)
-def test_react_single_input_no_redos() -> None:
-    """Regression test for ReDoS caused by catastrophic backtracking."""
-    parser = ReActSingleInputOutputParser()
-    malicious = "Action: " + " \t" * 1000 + "Action "
-    old = signal.signal(signal.SIGALRM, _timeout_handler)
-    signal.alarm(2)
-    try:
-        try:
-            parser.parse(malicious)
-        except OutputParserException:
-            pass
-        except TimeoutError:
-            pytest.fail(
-                "ReDoS detected: ReActSingleInputOutputParser.parse() "
-                "hung on crafted input"
-            )
-    finally:
-        signal.alarm(0)
-        signal.signal(signal.SIGALRM, old)

libs/langchain/tests/unit_tests/agents/test_mrkl_output_parser.py

@@ -1,6 +1,3 @@
-import signal
-import sys
-
 import pytest
 from langchain_core.agents import AgentAction, AgentFinish
 from langchain_core.exceptions import OutputParserException
@@ -82,30 +79,3 @@ def test_final_answer_after_parsable_action() -> None:
         "Parsing LLM output produced both a final answer and a parse-able action"
         in exception_info.value.args[0]
     )
-
-
-def _timeout_handler(_signum: int, _frame: object) -> None:
-    msg = "ReDoS: regex took too long"
-    raise TimeoutError(msg)
-
-
-@pytest.mark.skipif(
-    sys.platform == "win32", reason="SIGALRM is not available on Windows"
-)
-def test_mrkl_output_parser_no_redos() -> None:
-    """Regression test for ReDoS caused by catastrophic backtracking."""
-    malicious = "Action: " + " \t" * 1000 + "Action "
-    old = signal.signal(signal.SIGALRM, _timeout_handler)
-    signal.alarm(2)
-    try:
-        try:
-            mrkl_output_parser.parse(malicious)
-        except OutputParserException:
-            pass
-        except TimeoutError:
-            pytest.fail(
-                "ReDoS detected: MRKLOutputParser.parse() hung on crafted input"
-            )
-    finally:
-        signal.alarm(0)
-        signal.signal(signal.SIGALRM, old)

libs/langchain/uv.lock

@@ -2379,7 +2379,7 @@ wheels = [
 
 [[package]]
 name = "langchain-classic"
-version = "1.0.2"
+version = "1.0.1"
 source = { editable = "." }
 dependencies = [
     { name = "async-timeout", marker = "python_full_version < '3.11'" },