move embeddings to schema

libs/experimental/langchain_experimental/sql/vector_sql.py

@@ -6,9 +6,9 @@
 from langchain.callbacks.manager import CallbackManagerForChainRun
 from langchain.chains.llm import LLMChain
 from langchain.chains.sql_database.prompt import PROMPT, SQL_PROMPTS
-from langchain.embeddings.base import Embeddings
 from langchain.prompts.prompt import PromptTemplate
 from langchain.schema import BaseOutputParser, BasePromptTemplate
+from langchain.schema.base import Embeddings
 from langchain.schema.language_model import BaseLanguageModel
 from langchain.tools.sql_database.prompt import QUERY_CHECKER
 from langchain.utilities.sql_database import SQLDatabase

libs/langchain/langchain/cache.py

@@ -51,12 +51,12 @@
     from sqlalchemy.ext.declarative import declarative_base
 
 
-from langchain.embeddings.base import Embeddings
 from langchain.llms.base import LLM, get_prompts
 from langchain.load.dump import dumps
 from langchain.load.load import loads
 from langchain.schema import ChatGeneration, Generation
 from langchain.schema.cache import RETURN_VAL_TYPE, BaseCache
+from langchain.schema.embeddings import Embeddings
 from langchain.utils import get_from_env
 from langchain.vectorstores.redis import Redis as RedisVectorstore
 

libs/langchain/langchain/chains/hyde/base.py

@@ -12,8 +12,8 @@
 from langchain.chains.base import Chain
 from langchain.chains.hyde.prompts import PROMPT_MAP
 from langchain.chains.llm import LLMChain
-from langchain.embeddings.base import Embeddings
 from langchain.pydantic_v1 import Extra
+from langchain.schema.embeddings import Embeddings
 from langchain.schema.language_model import BaseLanguageModel
 
 

libs/langchain/langchain/chains/router/embedding_router.py

@@ -5,8 +5,8 @@
 from langchain.callbacks.manager import CallbackManagerForChainRun
 from langchain.chains.router.base import RouterChain
 from langchain.docstore.document import Document
-from langchain.embeddings.base import Embeddings
 from langchain.pydantic_v1 import Extra
+from langchain.schema.embeddings import Embeddings
 from langchain.vectorstores.base import VectorStore
 
 

libs/langchain/langchain/document_transformers/embeddings_redundant_filter.py

@@ -3,9 +3,9 @@
 
 import numpy as np
 
-from langchain.embeddings.base import Embeddings
 from langchain.pydantic_v1 import BaseModel, Field
 from langchain.schema import BaseDocumentTransformer, Document
+from langchain.schema.embeddings import Embeddings
 from langchain.utils.math import cosine_similarity
 
 

libs/langchain/langchain/embeddings/aleph_alpha.py

@@ -1,7 +1,7 @@
 from typing import Any, Dict, List, Optional
 
-from langchain.embeddings.base import Embeddings
 from langchain.pydantic_v1 import BaseModel, root_validator
+from langchain.schema.embeddings import Embeddings
 from langchain.utils import get_from_dict_or_env
 
 

libs/langchain/langchain/embeddings/awa.py

@@ -1,7 +1,7 @@
 from typing import Any, Dict, List
 
-from langchain.embeddings.base import Embeddings
 from langchain.pydantic_v1 import BaseModel, root_validator
+from langchain.schema.embeddings import Embeddings
 
 
 class AwaEmbeddings(BaseModel, Embeddings):

libs/langchain/langchain/embeddings/baidu_qianfan_endpoint.py

@@ -3,8 +3,8 @@
 import logging
 from typing import Any, Dict, List, Optional
 
-from langchain.embeddings.base import Embeddings
 from langchain.pydantic_v1 import BaseModel, root_validator
+from langchain.schema.embeddings import Embeddings
 from langchain.utils import get_from_dict_or_env
 
 logger = logging.getLogger(__name__)

libs/langchain/langchain/embeddings/bedrock.py

@@ -4,8 +4,8 @@
 from functools import partial
 from typing import Any, Dict, List, Optional
 
-from langchain.embeddings.base import Embeddings
 from langchain.pydantic_v1 import BaseModel, Extra, root_validator
+from langchain.schema.embeddings import Embeddings
 
 
 class BedrockEmbeddings(BaseModel, Embeddings):

libs/langchain/langchain/embeddings/cache.py

@@ -14,8 +14,8 @@
 from functools import partial
 from typing import Callable, List, Sequence, Union, cast
 
-from langchain.embeddings.base import Embeddings
 from langchain.schema import BaseStore
+from langchain.schema.embeddings import Embeddings
 from langchain.storage.encoder_backed import EncoderBackedStore
 
 NAMESPACE_UUID = uuid.UUID(int=1985)

libs/langchain/langchain/embeddings/clarifai.py

@@ -1,8 +1,8 @@
 import logging
 from typing import Any, Dict, List, Optional
 
-from langchain.embeddings.base import Embeddings
 from langchain.pydantic_v1 import BaseModel, Extra, root_validator
+from langchain.schema.embeddings import Embeddings
 from langchain.utils import get_from_dict_or_env
 
 logger = logging.getLogger(__name__)

libs/langchain/langchain/embeddings/cohere.py

@@ -1,7 +1,7 @@
 from typing import Any, Dict, List, Optional
 
-from langchain.embeddings.base import Embeddings
 from langchain.pydantic_v1 import BaseModel, Extra, root_validator
+from langchain.schema.embeddings import Embeddings
 from langchain.utils import get_from_dict_or_env
 
 

libs/langchain/langchain/embeddings/dashscope.py

@@ -18,8 +18,8 @@
     wait_exponential,
 )
 
-from langchain.embeddings.base import Embeddings
 from langchain.pydantic_v1 import BaseModel, Extra, root_validator
+from langchain.schema.embeddings import Embeddings
 from langchain.utils import get_from_dict_or_env
 
 logger = logging.getLogger(__name__)

libs/langchain/langchain/embeddings/deepinfra.py

@@ -2,8 +2,8 @@
 
 import requests
 
-from langchain.embeddings.base import Embeddings
 from langchain.pydantic_v1 import BaseModel, Extra, root_validator
+from langchain.schema.embeddings import Embeddings
 from langchain.utils import get_from_dict_or_env
 
 DEFAULT_MODEL_ID = "sentence-transformers/clip-ViT-B-32"

libs/langchain/langchain/embeddings/edenai.py

@@ -1,8 +1,8 @@
 from typing import Any, Dict, List, Optional
 
-from langchain.embeddings.base import Embeddings
 from langchain.pydantic_v1 import BaseModel, Extra, Field, root_validator
 from langchain.requests import Requests
+from langchain.schema.embeddings import Embeddings
 from langchain.utils import get_from_dict_or_env
 
 

libs/langchain/langchain/embeddings/elasticsearch.py

@@ -8,7 +8,7 @@
     from elasticsearch import Elasticsearch
     from elasticsearch.client import MlClient
 
-from langchain.embeddings.base import Embeddings
+from langchain.schema.embeddings import Embeddings
 
 
 class ElasticsearchEmbeddings(Embeddings):

libs/langchain/langchain/embeddings/embaas.py

@@ -3,8 +3,8 @@
 import requests
 from typing_extensions import NotRequired, TypedDict
 
-from langchain.embeddings.base import Embeddings
 from langchain.pydantic_v1 import BaseModel, Extra, root_validator
+from langchain.schema.embeddings import Embeddings
 from langchain.utils import get_from_dict_or_env
 
 # Currently supported maximum batch size for embedding requests

libs/langchain/langchain/embeddings/ernie.py

@@ -6,8 +6,8 @@
 
 import requests
 
-from langchain.embeddings.base import Embeddings
 from langchain.pydantic_v1 import BaseModel, root_validator
+from langchain.schema.embeddings import Embeddings
 from langchain.utils import get_from_dict_or_env
 
 logger = logging.getLogger(__name__)

libs/langchain/langchain/embeddings/fake.py

@@ -3,8 +3,8 @@
 
 import numpy as np
 
-from langchain.embeddings.base import Embeddings
 from langchain.pydantic_v1 import BaseModel
+from langchain.schema.embeddings import Embeddings
 
 
 class FakeEmbeddings(Embeddings, BaseModel):

libs/langchain/langchain/embeddings/google_palm.py

@@ -11,8 +11,8 @@
     wait_exponential,
 )
 
-from langchain.embeddings.base import Embeddings
 from langchain.pydantic_v1 import BaseModel, root_validator
+from langchain.schema.embeddings import Embeddings
 from langchain.utils import get_from_dict_or_env
 
 logger = logging.getLogger(__name__)

libs/langchain/langchain/embeddings/gpt4all.py

@@ -1,7 +1,7 @@
 from typing import Any, Dict, List
 
-from langchain.embeddings.base import Embeddings
 from langchain.pydantic_v1 import BaseModel, root_validator
+from langchain.schema.embeddings import Embeddings
 
 
 class GPT4AllEmbeddings(BaseModel, Embeddings):

libs/langchain/langchain/embeddings/huggingface.py

@@ -2,8 +2,8 @@
 
 import requests
 
-from langchain.embeddings.base import Embeddings
 from langchain.pydantic_v1 import BaseModel, Extra, Field
+from langchain.schema.embeddings import Embeddings
 
 DEFAULT_MODEL_NAME = "sentence-transformers/all-mpnet-base-v2"
 DEFAULT_INSTRUCT_MODEL = "hkunlp/instructor-large"

libs/langchain/langchain/embeddings/huggingface_hub.py

@@ -1,7 +1,7 @@
 from typing import Any, Dict, List, Optional
 
-from langchain.embeddings.base import Embeddings
 from langchain.pydantic_v1 import BaseModel, Extra, root_validator
+from langchain.schema.embeddings import Embeddings
 from langchain.utils import get_from_dict_or_env
 
 DEFAULT_REPO_ID = "sentence-transformers/all-mpnet-base-v2"

libs/langchain/langchain/embeddings/jina.py

@@ -3,8 +3,8 @@
 
 import requests
 
-from langchain.embeddings.base import Embeddings
 from langchain.pydantic_v1 import BaseModel, root_validator
+from langchain.schema.embeddings import Embeddings
 from langchain.utils import get_from_dict_or_env
 
 

libs/langchain/langchain/embeddings/llamacpp.py

@@ -1,7 +1,7 @@
 from typing import Any, Dict, List, Optional
 
-from langchain.embeddings.base import Embeddings
 from langchain.pydantic_v1 import BaseModel, Extra, Field, root_validator
+from langchain.schema.embeddings import Embeddings
 
 
 class LlamaCppEmbeddings(BaseModel, Embeddings):

libs/langchain/langchain/embeddings/localai.py

@@ -24,8 +24,8 @@
     wait_exponential,
 )
 
-from langchain.embeddings.base import Embeddings
 from langchain.pydantic_v1 import BaseModel, Extra, Field, root_validator
+from langchain.schema.embeddings import Embeddings
 from langchain.utils import get_from_dict_or_env, get_pydantic_field_names
 
 logger = logging.getLogger(__name__)

libs/langchain/langchain/embeddings/minimax.py

@@ -11,8 +11,8 @@
     wait_exponential,
 )
 
-from langchain.embeddings.base import Embeddings
 from langchain.pydantic_v1 import BaseModel, Extra, root_validator
+from langchain.schema.embeddings import Embeddings
 from langchain.utils import get_from_dict_or_env
 
 logger = logging.getLogger(__name__)

libs/langchain/langchain/embeddings/mlflow_gateway.py

@@ -2,8 +2,8 @@
 
 from typing import Any, Iterator, List, Optional
 
-from langchain.embeddings.base import Embeddings
 from langchain.pydantic_v1 import BaseModel
+from langchain.schema.embeddings import Embeddings
 
 
 def _chunk(texts: List[str], size: int) -> Iterator[List[str]]:

libs/langchain/langchain/embeddings/modelscope_hub.py

@@ -1,7 +1,7 @@
 from typing import Any, List, Optional
 
-from langchain.embeddings.base import Embeddings
 from langchain.pydantic_v1 import BaseModel, Extra
+from langchain.schema.embeddings import Embeddings
 
 
 class ModelScopeEmbeddings(BaseModel, Embeddings):

libs/langchain/langchain/embeddings/mosaicml.py

@@ -2,8 +2,8 @@
 
 import requests
 
-from langchain.embeddings.base import Embeddings
 from langchain.pydantic_v1 import BaseModel, Extra, root_validator
+from langchain.schema.embeddings import Embeddings
 from langchain.utils import get_from_dict_or_env
 
 

libs/langchain/langchain/embeddings/nlpcloud.py

@@ -1,7 +1,7 @@
 from typing import Any, Dict, List
 
-from langchain.embeddings.base import Embeddings
 from langchain.pydantic_v1 import BaseModel, root_validator
+from langchain.schema.embeddings import Embeddings
 from langchain.utils import get_from_dict_or_env
 
 

libs/langchain/langchain/embeddings/octoai_embeddings.py

@@ -1,7 +1,7 @@
 from typing import Any, Dict, List, Mapping, Optional
 
-from langchain.embeddings.base import Embeddings
 from langchain.pydantic_v1 import BaseModel, Extra, Field, root_validator
+from langchain.schema.embeddings import Embeddings
 from langchain.utils import get_from_dict_or_env
 
 DEFAULT_EMBED_INSTRUCTION = "Represent this input: "

libs/langchain/langchain/embeddings/ollama.py

@@ -2,8 +2,8 @@
 
 import requests
 
-from langchain.embeddings.base import Embeddings
 from langchain.pydantic_v1 import BaseModel, Extra
+from langchain.schema.embeddings import Embeddings
 
 
 class OllamaEmbeddings(BaseModel, Embeddings):

libs/langchain/langchain/embeddings/openai.py

@@ -25,8 +25,8 @@
     wait_exponential,
 )
 
-from langchain.embeddings.base import Embeddings
 from langchain.pydantic_v1 import BaseModel, Extra, Field, root_validator
+from langchain.schema.embeddings import Embeddings
 from langchain.utils import get_from_dict_or_env, get_pydantic_field_names
 
 logger = logging.getLogger(__name__)

libs/langchain/langchain/embeddings/sagemaker_endpoint.py

@@ -1,8 +1,8 @@
 from typing import Any, Dict, List, Optional
 
-from langchain.embeddings.base import Embeddings
 from langchain.llms.sagemaker_endpoint import ContentHandlerBase
 from langchain.pydantic_v1 import BaseModel, Extra, root_validator
+from langchain.schema.embeddings import Embeddings
 
 
 class EmbeddingsContentHandler(ContentHandlerBase[List[str], List[List[float]]]):

libs/langchain/langchain/embeddings/self_hosted.py

@@ -1,8 +1,8 @@
 from typing import Any, Callable, List
 
-from langchain.embeddings.base import Embeddings
 from langchain.llms import SelfHostedPipeline
 from langchain.pydantic_v1 import Extra
+from langchain.schema.embeddings import Embeddings
 
 
 def _embed_documents(pipeline: Any, *args: Any, **kwargs: Any) -> List[List[float]]:

libs/langchain/langchain/embeddings/spacy_embeddings.py

@@ -1,8 +1,8 @@
 import importlib.util
 from typing import Any, Dict, List
 
-from langchain.embeddings.base import Embeddings
 from langchain.pydantic_v1 import BaseModel, Extra, root_validator
+from langchain.schema.embeddings import Embeddings
 
 
 class SpacyEmbeddings(BaseModel, Embeddings):

libs/langchain/langchain/embeddings/tensorflow_hub.py

@@ -1,7 +1,7 @@
 from typing import Any, List
 
-from langchain.embeddings.base import Embeddings
 from langchain.pydantic_v1 import BaseModel, Extra
+from langchain.schema.embeddings import Embeddings
 
 DEFAULT_MODEL_URL = "https://tfhub.dev/google/universal-sentence-encoder-multilingual/3"
 

libs/langchain/langchain/embeddings/vertexai.py

@@ -1,8 +1,8 @@
 from typing import Dict, List
 
-from langchain.embeddings.base import Embeddings
 from langchain.llms.vertexai import _VertexAICommon
 from langchain.pydantic_v1 import root_validator
+from langchain.schema.embeddings import Embeddings
 from langchain.utilities.vertexai import raise_vertex_import_error
 
 

libs/langchain/langchain/embeddings/xinference.py

@@ -1,7 +1,7 @@
 """Wrapper around Xinference embedding models."""
 from typing import Any, List, Optional
 
-from langchain.embeddings.base import Embeddings
+from langchain.schema.embeddings import Embeddings
 
 
 class XinferenceEmbeddings(Embeddings):