anthropic: update pydantic (#26000)

Migrated with gritql: https://github.com/eyurtsev/migrate-pydantic

libs/partners/anthropic/langchain_anthropic/chat_models.py

@@ -49,12 +49,6 @@ from langchain_core.output_parsers import (
 )
 from langchain_core.output_parsers.base import OutputParserLike
 from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult
-from langchain_core.pydantic_v1 import (
-    BaseModel,
-    Field,
-    SecretStr,
-    root_validator,
-)
 from langchain_core.runnables import (
     Runnable,
     RunnableMap,
@@ -69,7 +63,15 @@ from langchain_core.utils import (
 )
 from langchain_core.utils.function_calling import convert_to_openai_tool
 from langchain_core.utils.pydantic import is_basemodel_subclass
-from typing_extensions import NotRequired
+from pydantic import (
+    BaseModel,
+    ConfigDict,
+    Field,
+    PrivateAttr,
+    SecretStr,
+    model_validator,
+)
+from typing_extensions import NotRequired, Self
 
 from langchain_anthropic.output_parsers import extract_tool_calls
 
@@ -114,7 +116,7 @@ def _merge_messages(
     """Merge runs of human/tool messages into single human messages with content blocks."""  # noqa: E501
     merged: list = []
     for curr in messages:
-        curr = curr.copy(deep=True)
+        curr = curr.model_copy(deep=True)
         if isinstance(curr, ToolMessage):
             if isinstance(curr.content, list) and all(
                 isinstance(block, dict) and block.get("type") == "tool_result"
@@ -383,7 +385,7 @@ class ChatAnthropic(BaseChatModel):
     Tool calling:
         .. code-block:: python
 
-            from langchain_core.pydantic_v1 import BaseModel, Field
+            from pydantic import BaseModel, Field
 
             class GetWeather(BaseModel):
                 '''Get the current weather in a given location'''
@@ -421,7 +423,7 @@ class ChatAnthropic(BaseChatModel):
 
             from typing import Optional
 
-            from langchain_core.pydantic_v1 import BaseModel, Field
+            from pydantic import BaseModel, Field
 
             class Joke(BaseModel):
                 '''Joke to tell user.'''
@@ -508,13 +510,12 @@ class ChatAnthropic(BaseChatModel):
 
     """  # noqa: E501
 
-    class Config:
+    model_config = ConfigDict(
-        """Configuration for this pydantic object."""
+        populate_by_name=True,
+    )
 
-        allow_population_by_field_name = True
+    _client: anthropic.Client = PrivateAttr(default=None)
-
+    _async_client: anthropic.AsyncClient = PrivateAttr(default=None)
-    _client: anthropic.Client = Field(default=None)
-    _async_client: anthropic.AsyncClient = Field(default=None)
 
     model: str = Field(alias="model_name")
     """Model name to use."""
@@ -626,8 +627,9 @@ class ChatAnthropic(BaseChatModel):
             ls_params["ls_stop"] = ls_stop
         return ls_params
 
-    @root_validator(pre=True)
+    @model_validator(mode="before")
-    def build_extra(cls, values: Dict) -> Dict:
+    @classmethod
+    def build_extra(cls, values: Dict) -> Any:
         extra = values.get("model_kwargs", {})
         all_required_field_names = get_pydantic_field_names(cls)
         values["model_kwargs"] = build_extra_kwargs(
@@ -635,28 +637,25 @@ class ChatAnthropic(BaseChatModel):
         )
         return values
 
-    @root_validator(pre=False, skip_on_failure=True)
+    @model_validator(mode="after")
-    def post_init(cls, values: Dict) -> Dict:
+    def post_init(self) -> Self:
-        api_key = values["anthropic_api_key"].get_secret_value()
+        api_key = self.anthropic_api_key.get_secret_value()
-        api_url = values["anthropic_api_url"]
+        api_url = self.anthropic_api_url
-        client_params = {
+        client_params: Dict[str, Any] = {
             "api_key": api_key,
             "base_url": api_url,
-            "max_retries": values["max_retries"],
+            "max_retries": self.max_retries,
-            "default_headers": values.get("default_headers"),
+            "default_headers": (self.default_headers or None),
         }
         # value <= 0 indicates the param should be ignored. None is a meaningful value
         # for Anthropic client and treated differently than not specifying the param at
         # all.
-        if (
+        if self.default_request_timeout is None or self.default_request_timeout > 0:
-            values["default_request_timeout"] is None
+            client_params["timeout"] = self.default_request_timeout
-            or values["default_request_timeout"] > 0
-        ):
-            client_params["timeout"] = values["default_request_timeout"]
 
-        values["_client"] = anthropic.Client(**client_params)
+        self._client = anthropic.Client(**client_params)
-        values["_async_client"] = anthropic.AsyncClient(**client_params)
+        self._async_client = anthropic.AsyncClient(**client_params)
-        return values
+        return self
 
     def _get_request_payload(
         self,
@@ -825,7 +824,7 @@ class ChatAnthropic(BaseChatModel):
             .. code-block:: python
 
                 from langchain_anthropic import ChatAnthropic
-                from langchain_core.pydantic_v1 import BaseModel, Field
+                from pydantic import BaseModel, Field
 
                 class GetWeather(BaseModel):
                     '''Get the current weather in a given location'''
@@ -854,7 +853,7 @@ class ChatAnthropic(BaseChatModel):
             .. code-block:: python
 
                 from langchain_anthropic import ChatAnthropic
-                from langchain_core.pydantic_v1 import BaseModel, Field
+                from pydantic import BaseModel, Field
 
                 class GetWeather(BaseModel):
                     '''Get the current weather in a given location'''
@@ -876,7 +875,7 @@ class ChatAnthropic(BaseChatModel):
             .. code-block:: python
 
                 from langchain_anthropic import ChatAnthropic
-                from langchain_core.pydantic_v1 import BaseModel, Field
+                from pydantic import BaseModel, Field
 
                 class GetWeather(BaseModel):
                     '''Get the current weather in a given location'''
@@ -897,7 +896,7 @@ class ChatAnthropic(BaseChatModel):
             .. code-block:: python
 
                 from langchain_anthropic import ChatAnthropic, convert_to_anthropic_tool
-                from langchain_core.pydantic_v1 import BaseModel, Field
+                from pydantic import BaseModel, Field
 
                 class GetWeather(BaseModel):
                     '''Get the current weather in a given location'''
@@ -1007,7 +1006,7 @@ class ChatAnthropic(BaseChatModel):
             .. code-block:: python
 
                 from langchain_anthropic import ChatAnthropic
-                from langchain_core.pydantic_v1 import BaseModel
+                from pydantic import BaseModel
 
                 class AnswerWithJustification(BaseModel):
                     '''An answer to the user question along with justification for the answer.'''
@@ -1028,7 +1027,7 @@ class ChatAnthropic(BaseChatModel):
             .. code-block:: python
 
                 from langchain_anthropic import ChatAnthropic
-                from langchain_core.pydantic_v1 import BaseModel
+                from pydantic import BaseModel
 
                 class AnswerWithJustification(BaseModel):
                     '''An answer to the user question along with justification for the answer.'''

libs/partners/anthropic/langchain_anthropic/experimental.py

@@ -7,7 +7,7 @@ from typing import (
 )
 
 from langchain_core._api import deprecated
-from langchain_core.pydantic_v1 import Field
+from pydantic import PrivateAttr
 
 from langchain_anthropic.chat_models import ChatAnthropic
 
@@ -156,4 +156,4 @@ def _xml_to_tool_calls(elem: Any, tools: List[Dict]) -> List[Dict[str, Any]]:
 class ChatAnthropicTools(ChatAnthropic):
     """Chat model for interacting with Anthropic functions."""
 
-    _xmllib: Any = Field(default=None)
+    _xmllib: Any = PrivateAttr(default=None)

libs/partners/anthropic/langchain_anthropic/llms.py

@@ -21,7 +21,6 @@ from langchain_core.language_models import BaseLanguageModel, LangSmithParams
 from langchain_core.language_models.llms import LLM
 from langchain_core.outputs import GenerationChunk
 from langchain_core.prompt_values import PromptValue
-from langchain_core.pydantic_v1 import Field, SecretStr, root_validator
 from langchain_core.utils import (
     get_pydantic_field_names,
 )
@@ -30,6 +29,8 @@ from langchain_core.utils.utils import (
     from_env,
     secret_from_env,
 )
+from pydantic import ConfigDict, Field, SecretStr, model_validator
+from typing_extensions import Self
 
 
 class _AnthropicCommon(BaseLanguageModel):
@@ -84,8 +85,9 @@ class _AnthropicCommon(BaseLanguageModel):
     count_tokens: Optional[Callable[[str], int]] = None
     model_kwargs: Dict[str, Any] = Field(default_factory=dict)
 
-    @root_validator(pre=True)
+    @model_validator(mode="before")
-    def build_extra(cls, values: Dict) -> Dict:
+    @classmethod
+    def build_extra(cls, values: Dict) -> Any:
         extra = values.get("model_kwargs", {})
         all_required_field_names = get_pydantic_field_names(cls)
         values["model_kwargs"] = build_extra_kwargs(
@@ -93,25 +95,25 @@ class _AnthropicCommon(BaseLanguageModel):
         )
         return values
 
-    @root_validator(pre=False, skip_on_failure=True)
+    @model_validator(mode="after")
-    def validate_environment(cls, values: Dict) -> Dict:
+    def validate_environment(self) -> Self:
         """Validate that api key and python package exists in environment."""
-        values["client"] = anthropic.Anthropic(
+        self.client = anthropic.Anthropic(
-            base_url=values["anthropic_api_url"],
+            base_url=self.anthropic_api_url,
-            api_key=values["anthropic_api_key"].get_secret_value(),
+            api_key=self.anthropic_api_key.get_secret_value(),
-            timeout=values["default_request_timeout"],
+            timeout=self.default_request_timeout,
-            max_retries=values["max_retries"],
+            max_retries=self.max_retries,
         )
-        values["async_client"] = anthropic.AsyncAnthropic(
+        self.async_client = anthropic.AsyncAnthropic(
-            base_url=values["anthropic_api_url"],
+            base_url=self.anthropic_api_url,
-            api_key=values["anthropic_api_key"].get_secret_value(),
+            api_key=self.anthropic_api_key.get_secret_value(),
-            timeout=values["default_request_timeout"],
+            timeout=self.default_request_timeout,
-            max_retries=values["max_retries"],
+            max_retries=self.max_retries,
         )
-        values["HUMAN_PROMPT"] = anthropic.HUMAN_PROMPT
+        self.HUMAN_PROMPT = anthropic.HUMAN_PROMPT
-        values["AI_PROMPT"] = anthropic.AI_PROMPT
+        self.AI_PROMPT = anthropic.AI_PROMPT
-        values["count_tokens"] = values["client"].count_tokens
+        self.count_tokens = self.client.count_tokens
-        return values
+        return self
 
     @property
     def _default_params(self) -> Mapping[str, Any]:
@@ -160,14 +162,14 @@ class AnthropicLLM(LLM, _AnthropicCommon):
             model = AnthropicLLM()
     """
 
-    class Config:
+    model_config = ConfigDict(
-        """Configuration for this pydantic object."""
+        populate_by_name=True,
+        arbitrary_types_allowed=True,
+    )
 
-        allow_population_by_field_name = True
+    @model_validator(mode="before")
-        arbitrary_types_allowed = True
+    @classmethod
-
+    def raise_warning(cls, values: Dict) -> Any:
-    @root_validator(pre=True)
-    def raise_warning(cls, values: Dict) -> Dict:
         """Raise warning that this class is deprecated."""
         warnings.warn(
             "This Anthropic LLM is deprecated. "

libs/partners/anthropic/langchain_anthropic/output_parsers.py

@@ -4,7 +4,7 @@ from langchain_core.messages import AIMessage, ToolCall
 from langchain_core.messages.tool import tool_call
 from langchain_core.output_parsers import BaseGenerationOutputParser
 from langchain_core.outputs import ChatGeneration, Generation
-from langchain_core.pydantic_v1 import BaseModel
+from pydantic import BaseModel, ConfigDict
 
 
 class ToolsOutputParser(BaseGenerationOutputParser):
@@ -17,8 +17,9 @@ class ToolsOutputParser(BaseGenerationOutputParser):
     pydantic_schemas: Optional[List[Type[BaseModel]]] = None
     """Pydantic schemas to parse tool calls into."""
 
-    class Config:
+    model_config = ConfigDict(
-        extra = "forbid"
+        extra="forbid",
+    )
 
     def parse_result(self, result: List[Generation], *, partial: bool = False) -> Any:
         """Parse a list of candidate model Generations into a specific format.

libs/partners/anthropic/poetry.lock

@@ -11,9 +11,6 @@ files = [
     {file = "annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89"},
 ]
 
-[package.dependencies]
-typing-extensions = {version = ">=4.0.0", markers = "python_version < \"3.9\""}
-
 [[package]]
 name = "anthropic"
 version = "0.33.1"
@@ -513,7 +510,7 @@ files = [
 
 [[package]]
 name = "langchain-core"
-version = "0.2.30"
+version = "0.2.38"
 description = "Building applications with LLMs through composability"
 optional = false
 python-versions = ">=3.8.1,<4.0"
@@ -1318,5 +1315,5 @@ watchmedo = ["PyYAML (>=3.10)"]
 
 [metadata]
 lock-version = "2.0"
-python-versions = ">=3.8.1,<4.0"
+python-versions = ">=3.9,<4.0"
-content-hash = "8e57ed7d6701a7ae5881fb1e5be89fc53ba81b98f04a9b54ffb0032d33589960"
+content-hash = "5263e046aef60dc42d7b0af41ec35ce48282f88d3ae8ce71003a54382fe4a1e6"

libs/partners/anthropic/pyproject.toml

@@ -19,9 +19,10 @@ disallow_untyped_defs = "True"
 "Release Notes" = "https://github.com/langchain-ai/langchain/releases?q=tag%3A%22langchain-anthropic%3D%3D0%22&expanded=true"
 
 [tool.poetry.dependencies]
-python = ">=3.8.1,<4.0"
+python = ">=3.9,<4.0"
 anthropic = ">=0.30.0,<1"
 langchain-core = "^0.2.26"
+pydantic = ">=2,<3"
 
 [tool.ruff.lint]
 select = [ "E", "F", "I", "T201",]

libs/partners/anthropic/scripts/check_pydantic.sh

@@ -1,27 +0,0 @@
-#!/bin/bash
-#
-# This script searches for lines starting with "import pydantic" or "from pydantic"
-# in tracked files within a Git repository.
-#
-# Usage: ./scripts/check_pydantic.sh /path/to/repository
-
-# Check if a path argument is provided
-if [ $# -ne 1 ]; then
-  echo "Usage: $0 /path/to/repository"
-  exit 1
-fi
-
-repository_path="$1"
-
-# Search for lines matching the pattern within the specified repository
-result=$(git -C "$repository_path" grep -E '^import pydantic|^from pydantic')
-
-# Check if any matching lines were found
-if [ -n "$result" ]; then
-  echo "ERROR: The following lines need to be updated:"
-  echo "$result"
-  echo "Please replace the code with an import from langchain_core.pydantic_v1."
-  echo "For example, replace 'from pydantic import BaseModel'"
-  echo "with 'from langchain_core.pydantic_v1 import BaseModel'"
-  exit 1
-fi

libs/partners/anthropic/tests/integration_tests/test_chat_models.py

@@ -16,8 +16,8 @@ from langchain_core.messages import (
 )
 from langchain_core.outputs import ChatGeneration, LLMResult
 from langchain_core.prompts import ChatPromptTemplate
-from langchain_core.pydantic_v1 import BaseModel, Field
 from langchain_core.tools import tool
+from pydantic import BaseModel, Field
 
 from langchain_anthropic import ChatAnthropic, ChatAnthropicMessages
 from tests.unit_tests._utils import FakeCallbackHandler

libs/partners/anthropic/tests/integration_tests/test_experimental.py

@@ -4,7 +4,7 @@ from enum import Enum
 from typing import List, Optional
 
 from langchain_core.prompts import ChatPromptTemplate
-from langchain_core.pydantic_v1 import BaseModel, Field
+from pydantic import BaseModel, Field
 
 from langchain_anthropic.experimental import ChatAnthropicTools
 

libs/partners/anthropic/tests/unit_tests/_utils.py

@@ -3,7 +3,7 @@
 from typing import Any, Union
 
 from langchain_core.callbacks import BaseCallbackHandler
-from langchain_core.pydantic_v1 import BaseModel
+from pydantic import BaseModel
 
 
 class BaseFakeCallbackHandler(BaseModel):
@@ -251,5 +251,6 @@ class FakeCallbackHandler(BaseCallbackHandler, BaseFakeCallbackHandlerMixin):
     ) -> Any:
         self.on_retriever_error_common()
 
-    def __deepcopy__(self, memo: dict) -> "FakeCallbackHandler":
+    # Overriding since BaseModel has __deepcopy__ method as well
+    def __deepcopy__(self, memo: dict) -> "FakeCallbackHandler":  # type: ignore
         return self

libs/partners/anthropic/tests/unit_tests/test_chat_models.py

@@ -7,9 +7,9 @@ import pytest
 from anthropic.types import Message, TextBlock, Usage
 from langchain_core.messages import AIMessage, HumanMessage, SystemMessage, ToolMessage
 from langchain_core.outputs import ChatGeneration, ChatResult
-from langchain_core.pydantic_v1 import BaseModel, Field, SecretStr
 from langchain_core.runnables import RunnableBinding
 from langchain_core.tools import BaseTool
+from pydantic import BaseModel, Field, SecretStr
 from pytest import CaptureFixture, MonkeyPatch
 
 from langchain_anthropic import ChatAnthropic

libs/partners/anthropic/tests/unit_tests/test_output_parsers.py

@@ -2,7 +2,7 @@ from typing import Any, List, Literal
 
 from langchain_core.messages import AIMessage
 from langchain_core.outputs import ChatGeneration
-from langchain_core.pydantic_v1 import BaseModel
+from pydantic import BaseModel
 
 from langchain_anthropic.output_parsers import ToolsOutputParser