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multiple[patch]: fix deprecation versions (#18349)
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commit
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@ -1,4 +1,5 @@
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"""Azure OpenAI embeddings wrapper."""
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from __future__ import annotations
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import os
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@ -14,7 +15,7 @@ from langchain_community.utils.openai import is_openai_v1
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@deprecated(
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since="0.1.0",
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since="0.0.9",
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removal="0.2.0",
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alternative_import="langchain_openai.AzureOpenAIEmbeddings",
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)
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@ -139,7 +139,7 @@ async def async_embed_with_retry(embeddings: OpenAIEmbeddings, **kwargs: Any) ->
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@deprecated(
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since="0.1.0",
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since="0.0.9",
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removal="0.2.0",
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alternative_import="langchain_openai.OpenAIEmbeddings",
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)
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@ -59,7 +59,7 @@ def _strip_erroneous_leading_spaces(text: str) -> str:
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return text
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@deprecated("0.0.351", alternative_import="langchain_google_genai.GoogleGenerativeAI")
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@deprecated("0.0.12", alternative_import="langchain_google_genai.GoogleGenerativeAI")
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class GooglePalm(BaseLLM, BaseModel):
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"""
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DEPRECATED: Use `langchain_google_genai.GoogleGenerativeAI` instead.
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@ -120,7 +120,7 @@ class _UpstashRedisStore(BaseStore[str, str]):
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yield key
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@deprecated("0.0.335", alternative="UpstashRedisByteStore")
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@deprecated("0.0.1", alternative="UpstashRedisByteStore")
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class UpstashRedisStore(_UpstashRedisStore):
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"""
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BaseStore implementation using Upstash Redis
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@ -358,7 +358,7 @@ class ElasticVectorSearch(VectorStore):
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self.client.delete(index=self.index_name, id=id)
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@deprecated("0.0.265", alternative="ElasticsearchStore class.", pending=True)
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@deprecated("0.0.1", alternative="ElasticsearchStore class.", pending=True)
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class ElasticKnnSearch(VectorStore):
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"""[DEPRECATED] `Elasticsearch` with k-nearest neighbor search
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(`k-NN`) vector store.
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@ -564,9 +564,11 @@ class ElasticKnnSearch(VectorStore):
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docs_and_scores = [
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(
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Document(
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page_content=hit["_source"][page_content]
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if source
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else hit["fields"][page_content][0],
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page_content=(
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hit["_source"][page_content]
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if source
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else hit["fields"][page_content][0]
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),
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metadata=hit["fields"] if fields else {},
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),
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hit["_score"],
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@ -647,9 +649,11 @@ class ElasticKnnSearch(VectorStore):
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docs_and_scores = [
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(
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Document(
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page_content=hit["_source"][page_content]
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if source
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else hit["fields"][page_content][0],
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page_content=(
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hit["_source"][page_content]
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if source
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else hit["fields"][page_content][0]
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),
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metadata=hit["fields"] if fields else {},
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),
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hit["_score"],
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@ -742,7 +742,7 @@ class Redis(VectorStore):
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tags.extend(self._get_retriever_tags())
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return RedisVectorStoreRetriever(vectorstore=self, **kwargs, tags=tags)
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@deprecated("0.0.272", alternative="similarity_search(distance_threshold=0.1)")
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@deprecated("0.0.1", alternative="similarity_search(distance_threshold=0.1)")
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def similarity_search_limit_score(
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self, query: str, k: int = 4, score_threshold: float = 0.2, **kwargs: Any
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) -> List[Document]:
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@ -672,7 +672,7 @@ class ChatPromptTemplate(BaseChatPromptTemplate):
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return cls.from_messages([message])
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@classmethod
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@deprecated("0.0.260", alternative="from_messages classmethod", pending=True)
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@deprecated("0.0.1", alternative="from_messages classmethod", pending=True)
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def from_role_strings(
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cls, string_messages: List[Tuple[str, str]]
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) -> ChatPromptTemplate:
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@ -692,7 +692,7 @@ class ChatPromptTemplate(BaseChatPromptTemplate):
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)
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@classmethod
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@deprecated("0.0.260", alternative="from_messages classmethod", pending=True)
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@deprecated("0.0.1", alternative="from_messages classmethod", pending=True)
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def from_strings(
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cls, string_messages: List[Tuple[Type[BaseMessagePromptTemplate], str]]
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) -> ChatPromptTemplate:
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