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community[patch]: fix errors introduced by pydantic 2.10 (#28297)

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ccurme 2024-11-22 17:50:13 -05:00 committed by GitHub
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23 changed files with 164 additions and 162 deletions
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5
libs/community/langchain_community/agent_toolkits/sql/toolkit.py
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@ -2,6 +2,8 @@
from typing import List
from langchain_core.caches import BaseCache as BaseCache
from langchain_core.callbacks import Callbacks as Callbacks
from langchain_core.language_models import BaseLanguageModel
from langchain_core.tools import BaseTool
from langchain_core.tools.base import BaseToolkit
@ -129,3 +131,6 @@ class SQLDatabaseToolkit(BaseToolkit):
def get_context(self) -> dict:
"""Return db context that you may want in agent prompt."""
return self.db.get_context()
SQLDatabaseToolkit.model_rebuild()

2
libs/community/langchain_community/chat_models/anyscale.py
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@ -72,7 +72,7 @@ class ChatAnyscale(ChatOpenAI):
def is_lc_serializable(cls) -> bool:
return False
anyscale_api_key: SecretStr = Field(default=None)
anyscale_api_key: SecretStr = Field(default=SecretStr(""))
"""AnyScale Endpoints API keys."""
model_name: str = Field(default=DEFAULT_MODEL, alias="model")
"""Model name to use."""

2
libs/community/langchain_community/chat_models/gpt_router.py
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@ -152,7 +152,7 @@ class GPTRouter(BaseChatModel):
client: Any = Field(default=None, exclude=True) #: :meta private:
models_priority_list: List[GPTRouterModel] = Field(min_length=1)
gpt_router_api_base: str = Field(default=None)
gpt_router_api_base: str = Field(default="")
"""WriteSonic GPTRouter custom endpoint"""
gpt_router_api_key: Optional[SecretStr] = None
"""WriteSonic GPTRouter API Key"""

15
libs/community/langchain_community/chat_models/kinetica.py
View File

@ -38,7 +38,7 @@ class _KdtSuggestContext(BaseModel):
table: Optional[str] = Field(default=None, title="Name of table")
description: Optional[str] = Field(default=None, title="Table description")
columns: List[str] = Field(default=None, title="Table columns list")
columns: List[str] = Field(default=[], title="Table columns list")
rules: Optional[List[str]] = Field(
default=None, title="Rules that apply to the table."
)
@ -121,7 +121,7 @@ class _KdtoSuggestRequest(BaseModel):
class _KdtMessage(BaseModel):
"""pydantic API response type"""
role: str = Field(default=None, title="One of [user|assistant|system]")
role: str = Field(default="", title="One of [user|assistant|system]")
content: str
@ -129,7 +129,7 @@ class _KdtChoice(BaseModel):
"""pydantic API response type"""
index: int
message: _KdtMessage = Field(default=None, title="The generated SQL")
message: Optional[_KdtMessage] = Field(default=None, title="The generated SQL")
finish_reason: str
@ -150,7 +150,7 @@ class _KdtSqlResponse(BaseModel):
model: str
choices: List[_KdtChoice]
usage: _KdtUsage
prompt: str = Field(default=None, title="The input question")
prompt: str = Field(default="", title="The input question")
class _KdtCompletionResponse(BaseModel):
@ -376,9 +376,8 @@ class ChatKinetica(BaseChatModel):
dict_messages = [self._convert_message_to_dict(m) for m in messages]
sql_response = self._submit_completion(dict_messages)
response_message = sql_response.choices[0].message
# generated_dict = response_message.model_dump() # pydantic v2
generated_dict = response_message.dict()
response_message = cast(_KdtMessage, sql_response.choices[0].message)
generated_dict = response_message.model_dump()
generated_message = self._convert_message_from_dict(generated_dict)
@ -539,7 +538,7 @@ class KineticaSqlResponse(BaseModel):
the generated SQL and related Pandas Dataframe fetched from the database.
"""
sql: str = Field(default=None)
sql: str = Field(default="")
"""The generated SQL."""
# dataframe: "pd.DataFrame" = Field(default=None)

16
libs/community/langchain_community/chat_models/naver.py
View File

@ -175,8 +175,8 @@ class ChatClovaX(BaseChatModel):
model.invoke([HumanMessage(content="Come up with 10 names for a song about parrots.")])
""" # noqa: E501
client: httpx.Client = Field(default=None) #: :meta private:
async_client: httpx.AsyncClient = Field(default=None) #: :meta private:
client: Optional[httpx.Client] = Field(default=None) #: :meta private:
async_client: Optional[httpx.AsyncClient] = Field(default=None) #: :meta private:
model_name: str = Field(
default="HCX-003",
@ -197,7 +197,7 @@ class ChatClovaX(BaseChatModel):
ncp_apigw_api_key: Optional[SecretStr] = Field(default=None, alias="apigw_api_key")
"""Automatically inferred from env are `NCP_APIGW_API_KEY` if not provided."""
base_url: str = Field(default=None, alias="base_url")
base_url: str = Field(default="", alias="base_url")
"""
Automatically inferred from env are `NCP_CLOVASTUDIO_API_BASE_URL` if not provided.
"""
@ -356,11 +356,12 @@ class ChatClovaX(BaseChatModel):
kwargs["stream"] = False
stream = kwargs["stream"]
client = cast(httpx.Client, self.client)
if stream:
def iter_sse() -> Iterator[ServerSentEvent]:
with connect_sse(
self.client, "POST", self._api_url, json=kwargs
client, "POST", self._api_url, json=kwargs
) as event_source:
_raise_on_error(event_source.response)
for sse in event_source.iter_sse():
@ -376,7 +377,7 @@ class ChatClovaX(BaseChatModel):
return iter_sse()
else:
response = self.client.post(url=self._api_url, json=kwargs)
response = client.post(url=self._api_url, json=kwargs)
_raise_on_error(response)
return response.json()
@ -395,13 +396,14 @@ class ChatClovaX(BaseChatModel):
if "stream" not in kwargs:
kwargs["stream"] = False
stream = kwargs["stream"]
async_client = cast(httpx.AsyncClient, self.async_client)
if stream:
event_source = aconnect_sse(
self.async_client, "POST", self._api_url, json=kwargs
async_client, "POST", self._api_url, json=kwargs
)
return _aiter_sse(event_source)
else:
response = await self.async_client.post(url=self._api_url, json=kwargs)
response = await async_client.post(url=self._api_url, json=kwargs)
await _araise_on_error(response)
return response.json()

2
libs/community/langchain_community/chat_models/octoai.py
View File

@ -46,7 +46,7 @@ class ChatOctoAI(ChatOpenAI):
"""
octoai_api_base: str = Field(default=DEFAULT_API_BASE)
octoai_api_token: SecretStr = Field(default=None, alias="api_key")
octoai_api_token: SecretStr = Field(default=SecretStr(""), alias="api_key")
model_name: str = Field(default=DEFAULT_MODEL, alias="model")
@property

4
libs/community/langchain_community/chat_models/sambanova.py
View File

@ -256,7 +256,7 @@ class ChatSambaNovaCloud(BaseChatModel):
sambanova_url: str = Field(default="")
"""SambaNova Cloud Url"""
sambanova_api_key: SecretStr = Field(default="")
sambanova_api_key: SecretStr = Field(default=SecretStr(""))
"""SambaNova Cloud api key"""
model: str = Field(default="Meta-Llama-3.1-8B-Instruct")
@ -1072,7 +1072,7 @@ class ChatSambaStudio(BaseChatModel):
sambastudio_url: str = Field(default="")
"""SambaStudio Url"""
sambastudio_api_key: SecretStr = Field(default="")
sambastudio_api_key: SecretStr = Field(default=SecretStr(""))
"""SambaStudio api key"""
base_url: str = Field(default="", exclude=True)

4
libs/community/langchain_community/embeddings/anyscale.py
View File

@ -2,7 +2,7 @@
from __future__ import annotations
from typing import Dict
from typing import Dict, Optional
from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env, pre_init
from pydantic import Field, SecretStr
@ -17,7 +17,7 @@ DEFAULT_MODEL = "thenlper/gte-large"
class AnyscaleEmbeddings(OpenAIEmbeddings):
"""`Anyscale` Embeddings API."""
anyscale_api_key: SecretStr = Field(default=None)
anyscale_api_key: Optional[SecretStr] = Field(default=None)
"""AnyScale Endpoints API keys."""
model: str = Field(default=DEFAULT_MODEL)
"""Model name to use."""

14
libs/community/langchain_community/embeddings/naver.py
View File

@ -1,5 +1,5 @@
import logging
from typing import Any, Dict, List, Optional
from typing import Any, Dict, List, Optional, cast
import httpx
from langchain_core.embeddings import Embeddings
@ -60,8 +60,8 @@ class ClovaXEmbeddings(BaseModel, Embeddings):
output = embedding.embed_documents(documents)
""" # noqa: E501
client: httpx.Client = Field(default=None) #: :meta private:
async_client: httpx.AsyncClient = Field(default=None) #: :meta private:
client: Optional[httpx.Client] = Field(default=None) #: :meta private:
async_client: Optional[httpx.AsyncClient] = Field(default=None) #: :meta private:
ncp_clovastudio_api_key: Optional[SecretStr] = Field(default=None, alias="api_key")
"""Automatically inferred from env are `NCP_CLOVASTUDIO_API_KEY` if not provided."""
@ -69,7 +69,7 @@ class ClovaXEmbeddings(BaseModel, Embeddings):
ncp_apigw_api_key: Optional[SecretStr] = Field(default=None, alias="apigw_api_key")
"""Automatically inferred from env are `NCP_APIGW_API_KEY` if not provided."""
base_url: str = Field(default=None, alias="base_url")
base_url: Optional[str] = Field(default=None, alias="base_url")
"""
Automatically inferred from env are `NCP_CLOVASTUDIO_API_BASE_URL` if not provided.
"""
@ -168,13 +168,15 @@ class ClovaXEmbeddings(BaseModel, Embeddings):
def _embed_text(self, text: str) -> List[float]:
payload = {"text": text}
response = self.client.post(url=self._api_url, json=payload)
client = cast(httpx.Client, self.client)
response = client.post(url=self._api_url, json=payload)
_raise_on_error(response)
return response.json()["result"]["embedding"]
async def _aembed_text(self, text: str) -> List[float]:
payload = {"text": text}
response = await self.async_client.post(url=self._api_url, json=payload)
async_client = cast(httpx.AsyncClient, self.client)
response = await async_client.post(url=self._api_url, json=payload)
await _araise_on_error(response)
return response.json()["result"]["embedding"]

4
libs/community/langchain_community/embeddings/octoai_embeddings.py
View File

@ -1,4 +1,4 @@
from typing import Dict
from typing import Dict, Optional
from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env, pre_init
from pydantic import Field, SecretStr
@ -20,7 +20,7 @@ class OctoAIEmbeddings(OpenAIEmbeddings):
Alternatively, you can use the octoai_api_token keyword argument.
"""
octoai_api_token: SecretStr = Field(default=None)
octoai_api_token: Optional[SecretStr] = Field(default=None)
"""OctoAI Endpoints API keys."""
endpoint_url: str = Field(default=DEFAULT_API_BASE)
"""Base URL path for API requests."""

2
libs/community/langchain_community/llms/anyscale.py
View File

@ -84,7 +84,7 @@ class Anyscale(BaseOpenAI): # type: ignore[override]
"""Key word arguments to pass to the model."""
anyscale_api_base: str = Field(default=DEFAULT_BASE_URL)
anyscale_api_key: SecretStr = Field(default=None)
anyscale_api_key: SecretStr = Field(default=SecretStr(""))
model_name: str = Field(default=DEFAULT_MODEL)
prefix_messages: List = Field(default_factory=list)

4
libs/community/langchain_community/llms/exllamav2.py
View File

@ -43,7 +43,7 @@ class ExLlamaV2(LLM):
# Langchain parameters
logfunc: Callable = print
stop_sequences: List[str] = Field("")
stop_sequences: List[str] = Field([])
"""Sequences that immediately will stop the generator."""
max_new_tokens: int = Field(150)
@ -56,7 +56,7 @@ class ExLlamaV2(LLM):
"""Whether to print debug information."""
# Generator parameters
disallowed_tokens: List[int] = Field(None)
disallowed_tokens: Optional[List[int]] = Field(None)
"""List of tokens to disallow during generation."""
@pre_init

2
libs/community/langchain_community/llms/gooseai.py
View File

@ -61,7 +61,7 @@ class GooseAI(LLM):
model_kwargs: Dict[str, Any] = Field(default_factory=dict)
"""Holds any model parameters valid for `create` call not explicitly specified."""
logit_bias: Optional[Dict[str, float]] = Field(default_factory=dict)
logit_bias: Optional[Dict[str, float]] = Field(default_factory=dict) # type: ignore[arg-type]
"""Adjust the probability of specific tokens being generated."""
gooseai_api_key: Optional[SecretStr] = None

2
libs/community/langchain_community/llms/octoai_endpoint.py
View File

@ -36,7 +36,7 @@ class OctoAIEndpoint(BaseOpenAI): # type: ignore[override]
"""Key word arguments to pass to the model."""
octoai_api_base: str = Field(default=DEFAULT_BASE_URL)
octoai_api_token: SecretStr = Field(default=None)
octoai_api_token: SecretStr = Field(default=SecretStr(""))
model_name: str = Field(default=DEFAULT_MODEL)
@classmethod

2
libs/community/langchain_community/llms/openai.py
View File

@ -219,7 +219,7 @@ class BaseOpenAI(BaseLLM):
)
"""Timeout for requests to OpenAI completion API. Can be float, httpx.Timeout or
None."""
logit_bias: Optional[Dict[str, float]] = Field(default_factory=dict)
logit_bias: Optional[Dict[str, float]] = Field(default_factory=dict) # type: ignore[arg-type]
"""Adjust the probability of specific tokens being generated."""
max_retries: int = 2
"""Maximum number of retries to make when generating."""

4
libs/community/langchain_community/llms/sambanova.py
View File

@ -105,7 +105,7 @@ class SambaStudio(LLM):
sambastudio_url: str = Field(default="")
"""SambaStudio Url"""
sambastudio_api_key: SecretStr = Field(default="")
sambastudio_api_key: SecretStr = Field(default=SecretStr(""))
"""SambaStudio api key"""
base_url: str = Field(default="", exclude=True)
@ -607,7 +607,7 @@ class SambaNovaCloud(LLM):
sambanova_url: str = Field(default="")
"""SambaNova Cloud Url"""
sambanova_api_key: SecretStr = Field(default="")
sambanova_api_key: SecretStr = Field(default=SecretStr(""))
"""SambaNova Cloud api key"""
model: str = Field(default="Meta-Llama-3.1-8B-Instruct")

5
libs/community/langchain_community/tools/edenai/edenai_base_tool.py
View File

@ -23,7 +23,7 @@ class EdenaiTool(BaseTool): # type: ignore[override]
feature: str
subfeature: str
edenai_api_key: SecretStr = Field(
edenai_api_key: Optional[SecretStr] = Field(
default_factory=secret_from_env("EDENAI_API_KEY", default=None)
)
is_async: bool = False
@ -48,8 +48,9 @@ class EdenaiTool(BaseTool): # type: ignore[override]
requests.Response: The response from the EdenAI API call.
"""
api_key = self.edenai_api_key.get_secret_value() if self.edenai_api_key else ""
headers = {
"Authorization": f"Bearer {self.edenai_api_key.get_secret_value()}",
"Authorization": f"Bearer {api_key}",
"User-Agent": self.get_user_agent(),
}

2
libs/community/langchain_community/tools/office365/messages_search.py
View File

@ -19,7 +19,7 @@ class SearchEmailsInput(BaseModel):
"""From https://learn.microsoft.com/en-us/graph/search-query-parameter"""
folder: str = Field(
default=None,
default="",
description=(
" If the user wants to search in only one folder, the name of the folder. "
'Default folders are "inbox", "drafts", "sent items", "deleted ttems", but '

2
libs/community/langchain_community/utilities/dalle_image_generator.py
View File

@ -31,7 +31,7 @@ class DallEAPIWrapper(BaseModel):
async_client: Any = Field(default=None, exclude=True) #: :meta private:
model_name: str = Field(default="dall-e-2", alias="model")
model_kwargs: Dict[str, Any] = Field(default_factory=dict)
openai_api_key: SecretStr = Field(
openai_api_key: Optional[SecretStr] = Field(
alias="api_key",
default_factory=secret_from_env(
"OPENAI_API_KEY",

2
libs/community/langchain_community/utilities/scenexplain.py
View File

@ -23,7 +23,7 @@ class SceneXplainAPIWrapper(BaseModel):
and create a new API key.
"""
scenex_api_key: str = Field(..., default_factory=from_env("SCENEX_API_KEY"))
scenex_api_key: str = Field(..., default_factory=from_env("SCENEX_API_KEY")) # type: ignore[call-overload]
scenex_api_url: str = "https://api.scenex.jina.ai/v1/describe"
def _describe_image(self, image: str) -> str:

2
libs/community/langchain_community/vectorstores/redis/schema.py
View File

@ -97,7 +97,7 @@ class RedisVectorField(RedisField):
dims: int = Field(...)
algorithm: object = Field(...)
datatype: str = Field(default="FLOAT32")
distance_metric: RedisDistanceMetric = Field(default="COSINE")
distance_metric: RedisDistanceMetric = Field(default="COSINE") # type: ignore[assignment]
initial_cap: Optional[int] = None
@field_validator("algorithm", "datatype", "distance_metric", mode="before")

224
libs/community/poetry.lock generated
View File

@ -2532,41 +2532,30 @@ files = [
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5
libs/langchain/langchain/chains/natbot/base.py
View File

@ -6,7 +6,9 @@ import warnings
from typing import Any, Dict, List, Optional
from langchain_core._api import deprecated
from langchain_core.caches import BaseCache as BaseCache
from langchain_core.callbacks import CallbackManagerForChainRun
from langchain_core.callbacks import Callbacks as Callbacks
from langchain_core.language_models import BaseLanguageModel
from langchain_core.output_parsers import StrOutputParser
from langchain_core.runnables import Runnable
@ -156,3 +158,6 @@ class NatBotChain(Chain):
@property
def _chain_type(self) -> str:
return "nat_bot_chain"
NatBotChain.model_rebuild()