From 203d20caa504955157e55dd9bef241b306ed7330 Mon Sep 17 00:00:00 2001 From: ccurme Date: Fri, 22 Nov 2024 17:50:13 -0500 Subject: [PATCH] community[patch]: fix errors introduced by pydantic 2.10 (#28297) --- .../agent_toolkits/sql/toolkit.py | 5 + .../chat_models/anyscale.py | 2 +- .../chat_models/gpt_router.py | 2 +- .../chat_models/kinetica.py | 15 +- .../langchain_community/chat_models/naver.py | 16 +- .../langchain_community/chat_models/octoai.py | 2 +- .../chat_models/sambanova.py | 4 +- .../embeddings/anyscale.py | 4 +- .../langchain_community/embeddings/naver.py | 14 +- .../embeddings/octoai_embeddings.py | 4 +- .../langchain_community/llms/anyscale.py | 2 +- .../langchain_community/llms/exllamav2.py | 4 +- .../langchain_community/llms/gooseai.py | 2 +- .../llms/octoai_endpoint.py | 2 +- .../langchain_community/llms/openai.py | 2 +- .../langchain_community/llms/sambanova.py | 4 +- .../tools/edenai/edenai_base_tool.py | 5 +- .../tools/office365/messages_search.py | 2 +- .../utilities/dalle_image_generator.py | 2 +- .../utilities/scenexplain.py | 2 +- .../vectorstores/redis/schema.py | 2 +- libs/community/poetry.lock | 224 +++++++++--------- .../langchain/langchain/chains/natbot/base.py | 5 + 23 files changed, 164 insertions(+), 162 deletions(-) diff --git a/libs/community/langchain_community/agent_toolkits/sql/toolkit.py b/libs/community/langchain_community/agent_toolkits/sql/toolkit.py index 6920349cd3f29..75566c96b9307 100644 --- a/libs/community/langchain_community/agent_toolkits/sql/toolkit.py +++ b/libs/community/langchain_community/agent_toolkits/sql/toolkit.py @@ -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 @@ def get_tools(self) -> List[BaseTool]: def get_context(self) -> dict: """Return db context that you may want in agent prompt.""" return self.db.get_context() + + +SQLDatabaseToolkit.model_rebuild() diff --git a/libs/community/langchain_community/chat_models/anyscale.py b/libs/community/langchain_community/chat_models/anyscale.py index e6f70b359f1eb..b5db8bbeb0caa 100644 --- a/libs/community/langchain_community/chat_models/anyscale.py +++ b/libs/community/langchain_community/chat_models/anyscale.py @@ -72,7 +72,7 @@ def lc_secrets(self) -> Dict[str, str]: 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.""" diff --git a/libs/community/langchain_community/chat_models/gpt_router.py b/libs/community/langchain_community/chat_models/gpt_router.py index c833b8e42404f..395fb80c01e30 100644 --- a/libs/community/langchain_community/chat_models/gpt_router.py +++ b/libs/community/langchain_community/chat_models/gpt_router.py @@ -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""" diff --git a/libs/community/langchain_community/chat_models/kinetica.py b/libs/community/langchain_community/chat_models/kinetica.py index e4a44f8d6a0fd..2af8b33715d41 100644 --- a/libs/community/langchain_community/chat_models/kinetica.py +++ b/libs/community/langchain_community/chat_models/kinetica.py @@ -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 @@ def _generate( 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) diff --git a/libs/community/langchain_community/chat_models/naver.py b/libs/community/langchain_community/chat_models/naver.py index c54b4a0d68678..2df6ad1a4f25f 100644 --- a/libs/community/langchain_community/chat_models/naver.py +++ b/libs/community/langchain_community/chat_models/naver.py @@ -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 @@ def _completion_with_retry(self, **kwargs: Any) -> Any: 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 @@ def iter_sse() -> Iterator[ServerSentEvent]: 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 @@ async def _completion_with_retry(**kwargs: Any) -> Any: 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() diff --git a/libs/community/langchain_community/chat_models/octoai.py b/libs/community/langchain_community/chat_models/octoai.py index 4f7120c2c8398..7087748729762 100644 --- a/libs/community/langchain_community/chat_models/octoai.py +++ b/libs/community/langchain_community/chat_models/octoai.py @@ -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 diff --git a/libs/community/langchain_community/chat_models/sambanova.py b/libs/community/langchain_community/chat_models/sambanova.py index 358650a892e9b..fb43c7c86a9e8 100644 --- a/libs/community/langchain_community/chat_models/sambanova.py +++ b/libs/community/langchain_community/chat_models/sambanova.py @@ -256,7 +256,7 @@ class Joke(BaseModel): 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) diff --git a/libs/community/langchain_community/embeddings/anyscale.py b/libs/community/langchain_community/embeddings/anyscale.py index 82a87c46debbc..7f35a729b484b 100644 --- a/libs/community/langchain_community/embeddings/anyscale.py +++ b/libs/community/langchain_community/embeddings/anyscale.py @@ -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 @@ 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.""" diff --git a/libs/community/langchain_community/embeddings/naver.py b/libs/community/langchain_community/embeddings/naver.py index 9b111a841bbf8..1de8921017769 100644 --- a/libs/community/langchain_community/embeddings/naver.py +++ b/libs/community/langchain_community/embeddings/naver.py @@ -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 @@ def default_headers(self) -> Dict[str, Any]: 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"] diff --git a/libs/community/langchain_community/embeddings/octoai_embeddings.py b/libs/community/langchain_community/embeddings/octoai_embeddings.py index 3cbfe01449ae4..dc16288da94ed 100644 --- a/libs/community/langchain_community/embeddings/octoai_embeddings.py +++ b/libs/community/langchain_community/embeddings/octoai_embeddings.py @@ -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.""" diff --git a/libs/community/langchain_community/llms/anyscale.py b/libs/community/langchain_community/llms/anyscale.py index 60e3e2526d0cc..e91607543e17e 100644 --- a/libs/community/langchain_community/llms/anyscale.py +++ b/libs/community/langchain_community/llms/anyscale.py @@ -84,7 +84,7 @@ def send_query(llm, text): """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) diff --git a/libs/community/langchain_community/llms/exllamav2.py b/libs/community/langchain_community/llms/exllamav2.py index 27f5c1ac1d53c..6ac9dc5832af9 100644 --- a/libs/community/langchain_community/llms/exllamav2.py +++ b/libs/community/langchain_community/llms/exllamav2.py @@ -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 diff --git a/libs/community/langchain_community/llms/gooseai.py b/libs/community/langchain_community/llms/gooseai.py index e8dc5ec77efeb..61383e9b7db8b 100644 --- a/libs/community/langchain_community/llms/gooseai.py +++ b/libs/community/langchain_community/llms/gooseai.py @@ -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 diff --git a/libs/community/langchain_community/llms/octoai_endpoint.py b/libs/community/langchain_community/llms/octoai_endpoint.py index 38abe0813f73b..de56c11eb5817 100644 --- a/libs/community/langchain_community/llms/octoai_endpoint.py +++ b/libs/community/langchain_community/llms/octoai_endpoint.py @@ -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 diff --git a/libs/community/langchain_community/llms/openai.py b/libs/community/langchain_community/llms/openai.py index fe74a55105a2f..9a3937179c96f 100644 --- a/libs/community/langchain_community/llms/openai.py +++ b/libs/community/langchain_community/llms/openai.py @@ -219,7 +219,7 @@ def is_lc_serializable(cls) -> bool: ) """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.""" diff --git a/libs/community/langchain_community/llms/sambanova.py b/libs/community/langchain_community/llms/sambanova.py index 7b4badce9b269..a485b87cd404c 100644 --- a/libs/community/langchain_community/llms/sambanova.py +++ b/libs/community/langchain_community/llms/sambanova.py @@ -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") diff --git a/libs/community/langchain_community/tools/edenai/edenai_base_tool.py b/libs/community/langchain_community/tools/edenai/edenai_base_tool.py index 6c802bbf72a3c..5ce3b89dce3a2 100644 --- a/libs/community/langchain_community/tools/edenai/edenai_base_tool.py +++ b/libs/community/langchain_community/tools/edenai/edenai_base_tool.py @@ -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 @@ def _call_eden_ai(self, query_params: Dict[str, Any]) -> str: 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(), } diff --git a/libs/community/langchain_community/tools/office365/messages_search.py b/libs/community/langchain_community/tools/office365/messages_search.py index a320844356941..07178c5f1e2db 100644 --- a/libs/community/langchain_community/tools/office365/messages_search.py +++ b/libs/community/langchain_community/tools/office365/messages_search.py @@ -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 ' diff --git a/libs/community/langchain_community/utilities/dalle_image_generator.py b/libs/community/langchain_community/utilities/dalle_image_generator.py index ed34231b2bfe3..d95483bb4f67b 100644 --- a/libs/community/langchain_community/utilities/dalle_image_generator.py +++ b/libs/community/langchain_community/utilities/dalle_image_generator.py @@ -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", diff --git a/libs/community/langchain_community/utilities/scenexplain.py b/libs/community/langchain_community/utilities/scenexplain.py index 30eff00fdfb14..2c7b5304adec6 100644 --- a/libs/community/langchain_community/utilities/scenexplain.py +++ b/libs/community/langchain_community/utilities/scenexplain.py @@ -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: diff --git a/libs/community/langchain_community/vectorstores/redis/schema.py b/libs/community/langchain_community/vectorstores/redis/schema.py index 413951e1fffb4..cd1920799e6da 100644 --- a/libs/community/langchain_community/vectorstores/redis/schema.py +++ b/libs/community/langchain_community/vectorstores/redis/schema.py @@ -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", 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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 @@ def execute(self, url: str, browser_content: str) -> str: @property def _chain_type(self) -> str: return "nat_bot_chain" + + +NatBotChain.model_rebuild()