id stringlengths 14 15 | text stringlengths 49 2.47k | source stringlengths 61 166 |
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c74bea976122-0 | langchain.embeddings.xinference.XinferenceEmbeddings¶
class langchain.embeddings.xinference.XinferenceEmbeddings(server_url: Optional[str] = None, model_uid: Optional[str] = None)[source]¶
Wrapper around xinference embedding models.
To use, you should have the xinference library installed:
.. code-block:: bash
pip inst... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.xinference.XinferenceEmbeddings.html |
c74bea976122-1 | aembed_query(text)
Asynchronous Embed query text.
embed_documents(texts)
Embed a list of documents using Xinference.
embed_query(text)
Embed a query of documents using Xinference.
__init__(server_url: Optional[str] = None, model_uid: Optional[str] = None)[source]¶
async aembed_documents(texts: List[str]) → List[List[fl... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.xinference.XinferenceEmbeddings.html |
cdd39b76a5d9-0 | langchain.embeddings.cohere.CohereEmbeddings¶
class langchain.embeddings.cohere.CohereEmbeddings[source]¶
Bases: BaseModel, Embeddings
Cohere embedding models.
To use, you should have the cohere python package installed, and the
environment variable COHERE_API_KEY set with your API key or pass it
as a named parameter t... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.cohere.CohereEmbeddings.html |
cdd39b76a5d9-1 | Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclu... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.cohere.CohereEmbeddings.html |
cdd39b76a5d9-2 | Call out to Cohere’s embedding endpoint.
Parameters
text – The text to embed.
Returns
Embeddings for the text.
classmethod from_orm(obj: Any) → Model¶
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = Fals... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.cohere.CohereEmbeddings.html |
cdd39b76a5d9-3 | classmethod validate(value: Any) → Model¶
Examples using CohereEmbeddings¶
Cohere
How to add memory to a Multi-Input Chain
Router | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.cohere.CohereEmbeddings.html |
f41af7f77537-0 | langchain.embeddings.localai.embed_with_retry¶
langchain.embeddings.localai.embed_with_retry(embeddings: LocalAIEmbeddings, **kwargs: Any) → Any[source]¶
Use tenacity to retry the embedding call. | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.localai.embed_with_retry.html |
d81dad93f5da-0 | langchain.embeddings.localai.async_embed_with_retry¶
async langchain.embeddings.localai.async_embed_with_retry(embeddings: LocalAIEmbeddings, **kwargs: Any) → Any[source]¶
Use tenacity to retry the embedding call. | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.localai.async_embed_with_retry.html |
495d326f4d81-0 | langchain.embeddings.localai.LocalAIEmbeddings¶
class langchain.embeddings.localai.LocalAIEmbeddings[source]¶
Bases: BaseModel, Embeddings
LocalAI embedding models.
To use, you should have the openai python package installed, and the
environment variable OPENAI_API_KEY set to a random string. You need to
specify OPENAI... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.localai.LocalAIEmbeddings.html |
495d326f4d81-1 | param openai_organization: Optional[str] = None¶
param openai_proxy: Optional[str] = None¶
param request_timeout: Optional[Union[float, Tuple[float, float]]] = None¶
Timeout in seconds for the LocalAI request.
param show_progress_bar: bool = False¶
Whether to show a progress bar when embedding.
async aembed_documents(t... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.localai.LocalAIEmbeddings.html |
495d326f4d81-2 | exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data
deep – set to True to make a deep copy of the model
Returns
new model instance
dict(*, i... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.localai.LocalAIEmbeddings.html |
495d326f4d81-3 | Embedding for the text.
classmethod from_orm(obj: Any) → Model¶
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults:... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.localai.LocalAIEmbeddings.html |
16ae5cf72200-0 | langchain.embeddings.llamacpp.LlamaCppEmbeddings¶
class langchain.embeddings.llamacpp.LlamaCppEmbeddings[source]¶
Bases: BaseModel, Embeddings
llama.cpp embedding models.
To use, you should have the llama-cpp-python library installed, and provide the
path to the Llama model as a named parameter to the constructor.
Chec... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.llamacpp.LlamaCppEmbeddings.html |
16ae5cf72200-1 | Force system to keep model in RAM.
param vocab_only: bool = False¶
Only load the vocabulary, no weights.
async aembed_documents(texts: List[str]) → List[List[float]]¶
Asynchronous Embed search docs.
async aembed_query(text: str) → List[float]¶
Asynchronous Embed query text.
classmethod construct(_fields_set: Optional[S... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.llamacpp.LlamaCppEmbeddings.html |
16ae5cf72200-2 | Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
embed_documents(texts: List[str]) → List[List[float]][source]¶
Embed a list of documents using the Llama model.
Parameters
texts – The list of texts to embed.
Returns
List of embeddings, one for each text.
embed... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.llamacpp.LlamaCppEmbeddings.html |
16ae5cf72200-3 | classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
classmethod update_forward_refs(**localns: Any) → None¶
Try to update ForwardRefs on fields based on this Model, globalns and localns.
classmethod validate(value: Any) → Model¶
Examples usi... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.llamacpp.LlamaCppEmbeddings.html |
5fe4be4d0fd8-0 | langchain.embeddings.self_hosted_hugging_face.load_embedding_model¶
langchain.embeddings.self_hosted_hugging_face.load_embedding_model(model_id: str, instruct: bool = False, device: int = 0) → Any[source]¶
Load the embedding model. | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.self_hosted_hugging_face.load_embedding_model.html |
98afce2be8cb-0 | langchain.embeddings.deepinfra.DeepInfraEmbeddings¶
class langchain.embeddings.deepinfra.DeepInfraEmbeddings[source]¶
Bases: BaseModel, Embeddings
Deep Infra’s embedding inference service.
To use, you should have the
environment variable DEEPINFRA_API_TOKEN set with your API token, or pass
it as a named parameter to th... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.deepinfra.DeepInfraEmbeddings.html |
98afce2be8cb-1 | Asynchronous Embed search docs.
async aembed_query(text: str) → List[float]¶
Asynchronous Embed query text.
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
Default values are respected, but no... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.deepinfra.DeepInfraEmbeddings.html |
98afce2be8cb-2 | Embed documents using a Deep Infra deployed embedding model.
Parameters
texts – The list of texts to embed.
Returns
List of embeddings, one for each text.
embed_query(text: str) → List[float][source]¶
Embed a query using a Deep Infra deployed embedding model.
Parameters
text – The text to embed.
Returns
Embeddings for ... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.deepinfra.DeepInfraEmbeddings.html |
98afce2be8cb-3 | classmethod update_forward_refs(**localns: Any) → None¶
Try to update ForwardRefs on fields based on this Model, globalns and localns.
classmethod validate(value: Any) → Model¶
Examples using DeepInfraEmbeddings¶
DeepInfra | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.deepinfra.DeepInfraEmbeddings.html |
f0d1a4f2b3b0-0 | langchain.embeddings.mlflow_gateway.MlflowAIGatewayEmbeddings¶
class langchain.embeddings.mlflow_gateway.MlflowAIGatewayEmbeddings[source]¶
Bases: Embeddings, BaseModel
Wrapper around embeddings LLMs in the MLflow AI Gateway.
To use, you should have the mlflow[gateway] python package installed.
For more information, se... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.mlflow_gateway.MlflowAIGatewayEmbeddings.html |
f0d1a4f2b3b0-1 | Duplicate a model, optionally choose which fields to include, exclude and change.
Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creat... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.mlflow_gateway.MlflowAIGatewayEmbeddings.html |
f0d1a4f2b3b0-2 | Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.mlflow_gateway.MlflowAIGatewayEmbeddings.html |
daf6c1a87a56-0 | langchain.embeddings.modelscope_hub.ModelScopeEmbeddings¶
class langchain.embeddings.modelscope_hub.ModelScopeEmbeddings[source]¶
Bases: BaseModel, Embeddings
ModelScopeHub embedding models.
To use, you should have the modelscope python package installed.
Example
from langchain.embeddings import ModelScopeEmbeddings
mo... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.modelscope_hub.ModelScopeEmbeddings.html |
daf6c1a87a56-1 | exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data
deep – set to True to make a deep copy of the model
Returns
new model instance
dict(*, i... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.modelscope_hub.ModelScopeEmbeddings.html |
daf6c1a87a56-2 | Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.modelscope_hub.ModelScopeEmbeddings.html |
39a8289292ac-0 | langchain.embeddings.minimax.embed_with_retry¶
langchain.embeddings.minimax.embed_with_retry(embeddings: MiniMaxEmbeddings, *args: Any, **kwargs: Any) → Any[source]¶
Use tenacity to retry the completion call. | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.minimax.embed_with_retry.html |
8782e4e8d3de-0 | langchain.embeddings.huggingface.HuggingFaceBgeEmbeddings¶
class langchain.embeddings.huggingface.HuggingFaceBgeEmbeddings[source]¶
Bases: BaseModel, Embeddings
HuggingFace BGE sentence_transformers embedding models.
To use, you should have the sentence_transformers python package installed.
Example
from langchain.embe... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.huggingface.HuggingFaceBgeEmbeddings.html |
8782e4e8d3de-1 | Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.huggingface.HuggingFaceBgeEmbeddings.html |
8782e4e8d3de-2 | Parameters
text – The text to embed.
Returns
Embeddings for the text.
classmethod from_orm(obj: Any) → Model¶
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, ... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.huggingface.HuggingFaceBgeEmbeddings.html |
0e1f362e74b9-0 | langchain.embeddings.dashscope.embed_with_retry¶
langchain.embeddings.dashscope.embed_with_retry(embeddings: DashScopeEmbeddings, **kwargs: Any) → Any[source]¶
Use tenacity to retry the embedding call. | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.dashscope.embed_with_retry.html |
3dc53190f4d6-0 | langchain.embeddings.tensorflow_hub.TensorflowHubEmbeddings¶
class langchain.embeddings.tensorflow_hub.TensorflowHubEmbeddings[source]¶
Bases: BaseModel, Embeddings
TensorflowHub embedding models.
To use, you should have the tensorflow_text python package installed.
Example
from langchain.embeddings import TensorflowHu... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.tensorflow_hub.TensorflowHubEmbeddings.html |
3dc53190f4d6-1 | the new model: you should trust this data
deep – set to True to make a deep copy of the model
Returns
new model instance
dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[boo... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.tensorflow_hub.TensorflowHubEmbeddings.html |
3dc53190f4d6-2 | classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
classmethod parse_obj(obj: Any) → Model¶
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.tensorflow_hub.TensorflowHubEmbeddings.html |
e4fc0897c8d3-0 | langchain.embeddings.embaas.EmbaasEmbeddingsPayload¶
class langchain.embeddings.embaas.EmbaasEmbeddingsPayload[source]¶
Payload for the embaas embeddings API.
Attributes
model
texts
instruction
Methods
__init__(*args, **kwargs)
clear()
copy()
fromkeys([value])
Create a new dictionary with keys from iterable and values ... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.embaas.EmbaasEmbeddingsPayload.html |
e4fc0897c8d3-1 | keys() → a set-like object providing a view on D's keys¶
pop(k[, d]) → v, remove specified key and return the corresponding value.¶
If the key is not found, return the default if given; otherwise,
raise a KeyError.
popitem()¶
Remove and return a (key, value) pair as a 2-tuple.
Pairs are returned in LIFO (last-in, first... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.embaas.EmbaasEmbeddingsPayload.html |
81baff6368ff-0 | langchain.embeddings.base.Embeddings¶
class langchain.embeddings.base.Embeddings[source]¶
Interface for embedding models.
Methods
__init__()
aembed_documents(texts)
Asynchronous Embed search docs.
aembed_query(text)
Asynchronous Embed query text.
embed_documents(texts)
Embed search docs.
embed_query(text)
Embed query t... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.base.Embeddings.html |
69a2bc192e0a-0 | langchain.embeddings.openai.embed_with_retry¶
langchain.embeddings.openai.embed_with_retry(embeddings: OpenAIEmbeddings, **kwargs: Any) → Any[source]¶
Use tenacity to retry the embedding call. | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.openai.embed_with_retry.html |
2651f81b451a-0 | langchain.embeddings.openai.OpenAIEmbeddings¶
class langchain.embeddings.openai.OpenAIEmbeddings[source]¶
Bases: BaseModel, Embeddings
OpenAI embedding models.
To use, you should have the openai python package installed, and the
environment variable OPENAI_API_KEY set with your API key or pass it
as a named parameter t... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.openai.OpenAIEmbeddings.html |
2651f81b451a-1 | Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
param allowed_special: Union[Literal['all'], Set[str]] = {}¶
param chunk_size: int = 1000¶
Maximum number of texts to embed in each batch
param deployment: str... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.openai.OpenAIEmbeddings.html |
2651f81b451a-2 | them to be under a certain limit. By default, when set to None, this will
be the same as the embedding model name. However, there are some cases
where you may want to use this Embedding class with a model name not
supported by tiktoken. This can include when using Azure embeddings or
when using one of the many model pr... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.openai.OpenAIEmbeddings.html |
2651f81b451a-3 | Duplicate a model, optionally choose which fields to include, exclude and change.
Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creat... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.openai.OpenAIEmbeddings.html |
2651f81b451a-4 | Embedding for the text.
classmethod from_orm(obj: Any) → Model¶
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults:... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.openai.OpenAIEmbeddings.html |
2651f81b451a-5 | AzureOpenAI
Cohere Reranker
kNN
DocArray Retriever
SVM
Pinecone Hybrid Search
LOTR (Merger Retriever)
Azure OpenAI
Document Comparison
Vectorstore Agent
LanceDB
Weaviate
Activeloop’s Deep Lake
Redis
PGVector
Rockset
Zilliz
SingleStoreDB
Typesense
Atlas
Chroma
Alibaba Cloud OpenSearch
StarRocks
scikit-learn
DocArrayHnsw... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.openai.OpenAIEmbeddings.html |
2651f81b451a-6 | Generative Agents in LangChain
MultiQueryRetriever
WebResearchRetriever
Weaviate self-querying
Chroma self-querying
DeepLake self-querying
Self-querying with Pinecone
Self-querying with MyScale
Qdrant self-querying
How to add memory to a Multi-Input Chain
Combine agents and vector stores
Custom agent with tool retr... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.openai.OpenAIEmbeddings.html |
50e20baa9ea1-0 | langchain.embeddings.minimax.MiniMaxEmbeddings¶
class langchain.embeddings.minimax.MiniMaxEmbeddings[source]¶
Bases: BaseModel, Embeddings
MiniMax’s embedding service.
To use, you should have the environment variable MINIMAX_GROUP_ID and
MINIMAX_API_KEY set with your API token, or pass it as a named parameter to
the co... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.minimax.MiniMaxEmbeddings.html |
50e20baa9ea1-1 | Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.minimax.MiniMaxEmbeddings.html |
50e20baa9ea1-2 | Parameters
text – The text to embed.
Returns
Embeddings for the text.
classmethod from_orm(obj: Any) → Model¶
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, ... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.minimax.MiniMaxEmbeddings.html |
4b8dfff0da35-0 | langchain.embeddings.sagemaker_endpoint.EmbeddingsContentHandler¶
class langchain.embeddings.sagemaker_endpoint.EmbeddingsContentHandler[source]¶
Content handler for LLM class.
Attributes
accepts
The MIME type of the response data returned from endpoint
content_type
The MIME type of the input data passed to endpoint
Me... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.sagemaker_endpoint.EmbeddingsContentHandler.html |
f14add1d2898-0 | langchain.embeddings.nlpcloud.NLPCloudEmbeddings¶
class langchain.embeddings.nlpcloud.NLPCloudEmbeddings[source]¶
Bases: BaseModel, Embeddings
NLP Cloud embedding models.
To use, you should have the nlpcloud python package installed
Example
from langchain.embeddings import NLPCloudEmbeddings
embeddings = NLPCloudEmbedd... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.nlpcloud.NLPCloudEmbeddings.html |
f14add1d2898-1 | the new model: you should trust this data
deep – set to True to make a deep copy of the model
Returns
new model instance
dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[boo... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.nlpcloud.NLPCloudEmbeddings.html |
f14add1d2898-2 | classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
classmethod parse_obj(obj: Any) → Model¶
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.nlpcloud.NLPCloudEmbeddings.html |
543ee169c123-0 | langchain.embeddings.elasticsearch.ElasticsearchEmbeddings¶
class langchain.embeddings.elasticsearch.ElasticsearchEmbeddings(client: MlClient, model_id: str, *, input_field: str = 'text_field')[source]¶
Elasticsearch embedding models.
This class provides an interface to generate embeddings using a model deployed
in an ... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.elasticsearch.ElasticsearchEmbeddings.html |
543ee169c123-1 | Initialize the ElasticsearchEmbeddings instance.
Parameters
client (MlClient) – An Elasticsearch ML client object.
model_id (str) – The model_id of the model deployed in the Elasticsearch
cluster.
input_field (str) – The name of the key for the input text field in the
document. Defaults to ‘text_field’.
async aembed_do... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.elasticsearch.ElasticsearchEmbeddings.html |
543ee169c123-2 | es_user – (str, optional): Elasticsearch username.
es_password – (str, optional): Elasticsearch password.
Example
from langchain.embeddings import ElasticsearchEmbeddings
# Define the model ID and input field name (if different from default)
model_id = "your_model_id"
# Optional, only if different from 'text_field'
inp... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.elasticsearch.ElasticsearchEmbeddings.html |
543ee169c123-3 | Example
from elasticsearch import Elasticsearch
from langchain.embeddings import ElasticsearchEmbeddings
# Define the model ID and input field name (if different from default)
model_id = "your_model_id"
# Optional, only if different from 'text_field'
input_field = "your_input_field"
# Create Elasticsearch connection
es... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.elasticsearch.ElasticsearchEmbeddings.html |
a4086486b313-0 | langchain.embeddings.huggingface.HuggingFaceEmbeddings¶
class langchain.embeddings.huggingface.HuggingFaceEmbeddings[source]¶
Bases: BaseModel, Embeddings
HuggingFace sentence_transformers embedding models.
To use, you should have the sentence_transformers python package installed.
Example
from langchain.embeddings imp... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.huggingface.HuggingFaceEmbeddings.html |
a4086486b313-1 | Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model¶
Duplicate a model, optionally... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.huggingface.HuggingFaceEmbeddings.html |
a4086486b313-2 | Embeddings for the text.
classmethod from_orm(obj: Any) → Model¶
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.huggingface.HuggingFaceEmbeddings.html |
a4086486b313-3 | Hugging Face Hub
Sentence Transformers Embeddings
LOTR (Merger Retriever)
Hugging Face
Annoy
Pairwise Embedding Distance
Embedding Distance
Lost in the middle: The problem with long contexts | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.huggingface.HuggingFaceEmbeddings.html |
eaabb7823fd7-0 | langchain.embeddings.dashscope.DashScopeEmbeddings¶
class langchain.embeddings.dashscope.DashScopeEmbeddings[source]¶
Bases: BaseModel, Embeddings
DashScope embedding models.
To use, you should have the dashscope python package installed, and the
environment variable DASHSCOPE_API_KEY set with your API key or pass it
a... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.dashscope.DashScopeEmbeddings.html |
eaabb7823fd7-1 | Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.dashscope.DashScopeEmbeddings.html |
eaabb7823fd7-2 | Call out to DashScope’s embedding endpoint for embedding query text.
Parameters
text – The text to embed.
Returns
Embedding for the text.
classmethod from_orm(obj: Any) → Model¶
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = ... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.dashscope.DashScopeEmbeddings.html |
eaabb7823fd7-3 | classmethod validate(value: Any) → Model¶
Examples using DashScopeEmbeddings¶
DashScope | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.dashscope.DashScopeEmbeddings.html |
aa2c03941b47-0 | langchain.embeddings.clarifai.ClarifaiEmbeddings¶
class langchain.embeddings.clarifai.ClarifaiEmbeddings[source]¶
Bases: BaseModel, Embeddings
Clarifai embedding models.
To use, you should have the clarifai python package installed, and the
environment variable CLARIFAI_PAT set with your personal access token or pass i... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.clarifai.ClarifaiEmbeddings.html |
aa2c03941b47-1 | Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclu... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.clarifai.ClarifaiEmbeddings.html |
aa2c03941b47-2 | Call out to Clarifai’s embedding models.
Parameters
text – The text to embed.
Returns
Embeddings for the text.
classmethod from_orm(obj: Any) → Model¶
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = Fals... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.clarifai.ClarifaiEmbeddings.html |
aa2c03941b47-3 | classmethod validate(value: Any) → Model¶
Examples using ClarifaiEmbeddings¶
Clarifai | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.clarifai.ClarifaiEmbeddings.html |
fb0a3392ec56-0 | langchain.embeddings.bedrock.BedrockEmbeddings¶
class langchain.embeddings.bedrock.BedrockEmbeddings[source]¶
Bases: BaseModel, Embeddings
Bedrock embedding models.
To authenticate, the AWS client uses the following methods to
automatically load credentials:
https://boto3.amazonaws.com/v1/documentation/api/latest/guide... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.bedrock.BedrockEmbeddings.html |
fb0a3392ec56-1 | The aws region e.g., us-west-2. Fallsback to AWS_DEFAULT_REGION env variable
or region specified in ~/.aws/config in case it is not provided here.
async aembed_documents(texts: List[str]) → List[List[float]]¶
Asynchronous Embed search docs.
async aembed_query(text: str) → List[float]¶
Asynchronous Embed query text.
cla... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.bedrock.BedrockEmbeddings.html |
fb0a3392ec56-2 | deep – set to True to make a deep copy of the model
Returns
new model instance
dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, ex... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.bedrock.BedrockEmbeddings.html |
fb0a3392ec56-3 | Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.bedrock.BedrockEmbeddings.html |
4c26c08cbd96-0 | langchain.embeddings.self_hosted.SelfHostedEmbeddings¶
class langchain.embeddings.self_hosted.SelfHostedEmbeddings[source]¶
Bases: SelfHostedPipeline, Embeddings
Custom embedding models on self-hosted remote hardware.
Supported hardware includes auto-launched instances on AWS, GCP, Azure,
and Lambda, as well as servers... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.self_hosted.SelfHostedEmbeddings.html |
4c26c08cbd96-1 | pipeline="models/pipeline.pkl",
hardware=gpu,
model_reqs=["./", "torch", "transformers"],
)
Init the pipeline with an auxiliary function.
The load function must be in global scope to be imported
and run on the server, i.e. in a module and not a REPL or closure.
Then, initialize the remote inference function.
pa... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.self_hosted.SelfHostedEmbeddings.html |
4c26c08cbd96-2 | Check Cache and run the LLM on the given prompt and input.
async abatch(inputs: List[Union[PromptValue, str, List[BaseMessage]]], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, max_concurrency: Optional[int] = None, **kwargs: Any) → List[str]¶
async aembed_documents(texts: List[str]) → List[List[... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.self_hosted.SelfHostedEmbeddings.html |
4c26c08cbd96-3 | Parameters
prompts – List of PromptValues. A PromptValue is an object that can be
converted to match the format of any language model (string for pure
text generation models and BaseMessages for chat models).
stop – Stop words to use when generating. Model output is cut off at the
first occurrence of any of these subst... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.self_hosted.SelfHostedEmbeddings.html |
4c26c08cbd96-4 | Use this method when calling chat models and only the topcandidate generation is needed.
Parameters
messages – A sequence of chat messages corresponding to a single model input.
stop – Stop words to use when generating. Model output is cut off at the
first occurrence of any of these substrings.
**kwargs – Arbitrary add... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.self_hosted.SelfHostedEmbeddings.html |
4c26c08cbd96-5 | Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data
deep – set to True to make a deep co... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.self_hosted.SelfHostedEmbeddings.html |
4c26c08cbd96-6 | Run the LLM on the given prompt and input.
generate_prompt(prompts: List[PromptValue], stop: Optional[List[str]] = None, callbacks: Union[List[BaseCallbackHandler], BaseCallbackManager, None, List[Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]]]] = None, **kwargs: Any) → LLMResult¶
Pass a sequence of pr... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.self_hosted.SelfHostedEmbeddings.html |
4c26c08cbd96-7 | get_num_tokens_from_messages(messages: List[BaseMessage]) → int¶
Get the number of tokens in the messages.
Useful for checking if an input will fit in a model’s context window.
Parameters
messages – The message inputs to tokenize.
Returns
The sum of the number of tokens across the messages.
get_token_ids(text: str) → L... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.self_hosted.SelfHostedEmbeddings.html |
4c26c08cbd96-8 | classmethod parse_obj(obj: Any) → Model¶
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
predict(text: str, *, stop: Optional[Sequence[str]] = None, **kwargs: Any) → str¶
Pass a single string input to t... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.self_hosted.SelfHostedEmbeddings.html |
4c26c08cbd96-9 | .. code-block:: python
llm.save(file_path=”path/llm.yaml”)
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶
classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
stream(input: Union[Promp... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.self_hosted.SelfHostedEmbeddings.html |
4c26c08cbd96-10 | property lc_serializable: bool¶
Return whether or not the class is serializable.
Examples using SelfHostedEmbeddings¶
Self Hosted Embeddings | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.self_hosted.SelfHostedEmbeddings.html |
a7d7ec85840e-0 | langchain.embeddings.huggingface.HuggingFaceInstructEmbeddings¶
class langchain.embeddings.huggingface.HuggingFaceInstructEmbeddings[source]¶
Bases: BaseModel, Embeddings
Wrapper around sentence_transformers embedding models.
To use, you should have the sentence_transformers
and InstructorEmbedding python packages inst... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.huggingface.HuggingFaceInstructEmbeddings.html |
a7d7ec85840e-1 | Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclu... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.huggingface.HuggingFaceInstructEmbeddings.html |
a7d7ec85840e-2 | Compute query embeddings using a HuggingFace instruct model.
Parameters
text – The text to embed.
Returns
Embeddings for the text.
classmethod from_orm(obj: Any) → Model¶
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, b... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.huggingface.HuggingFaceInstructEmbeddings.html |
a7d7ec85840e-3 | classmethod validate(value: Any) → Model¶
Examples using HuggingFaceInstructEmbeddings¶
InstructEmbeddings | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.huggingface.HuggingFaceInstructEmbeddings.html |
ddea048075f7-0 | langchain.embeddings.mosaicml.MosaicMLInstructorEmbeddings¶
class langchain.embeddings.mosaicml.MosaicMLInstructorEmbeddings[source]¶
Bases: BaseModel, Embeddings
MosaicML embedding service.
To use, you should have the
environment variable MOSAICML_API_TOKEN set with your API token, or pass
it as a named parameter to t... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.mosaicml.MosaicMLInstructorEmbeddings.html |
ddea048075f7-1 | Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclu... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.mosaicml.MosaicMLInstructorEmbeddings.html |
ddea048075f7-2 | Embed a query using a MosaicML deployed instructor embedding model.
Parameters
text – The text to embed.
Returns
Embeddings for the text.
classmethod from_orm(obj: Any) → Model¶
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = ... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.mosaicml.MosaicMLInstructorEmbeddings.html |
ddea048075f7-3 | classmethod validate(value: Any) → Model¶
Examples using MosaicMLInstructorEmbeddings¶
MosaicML embeddings | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.mosaicml.MosaicMLInstructorEmbeddings.html |
d1c0b8c72256-0 | langchain.embeddings.self_hosted_hugging_face.SelfHostedHuggingFaceInstructEmbeddings¶
class langchain.embeddings.self_hosted_hugging_face.SelfHostedHuggingFaceInstructEmbeddings[source]¶
Bases: SelfHostedHuggingFaceEmbeddings
HuggingFace InstructEmbedding models on self-hosted remote hardware.
Supported hardware inclu... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.self_hosted_hugging_face.SelfHostedHuggingFaceInstructEmbeddings.html |
d1c0b8c72256-1 | Metadata to add to the run trace.
param model_id: str = 'hkunlp/instructor-large'¶
Model name to use.
param model_load_fn: Callable = <function load_embedding_model>¶
Function to load the model remotely on the server.
param model_reqs: List[str] = ['./', 'InstructorEmbedding', 'torch']¶
Requirements to install on hardw... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.self_hosted_hugging_face.SelfHostedHuggingFaceInstructEmbeddings.html |
d1c0b8c72256-2 | Asynchronous Embed query text.
async agenerate(prompts: List[str], stop: Optional[List[str]] = None, callbacks: Union[List[BaseCallbackHandler], BaseCallbackManager, None, List[Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]]]] = None, *, tags: Optional[Union[List[str], List[List[str]]]] = None, metadata... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.self_hosted_hugging_face.SelfHostedHuggingFaceInstructEmbeddings.html |
d1c0b8c72256-3 | to the model provider API call.
Returns
An LLMResult, which contains a list of candidate Generations for each inputprompt and additional model provider-specific output.
async ainvoke(input: Union[PromptValue, str, List[BaseMessage]], config: Optional[RunnableConfig] = None, *, stop: Optional[List[str]] = None, **kwargs... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.self_hosted_hugging_face.SelfHostedHuggingFaceInstructEmbeddings.html |
d1c0b8c72256-4 | batch(inputs: List[Union[PromptValue, str, List[BaseMessage]]], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, max_concurrency: Optional[int] = None, **kwargs: Any) → List[str]¶
bind(**kwargs: Any) → Runnable[Input, Output]¶
Bind arguments to a Runnable, returning a new Runnable.
classmethod cons... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.self_hosted_hugging_face.SelfHostedHuggingFaceInstructEmbeddings.html |
d1c0b8c72256-5 | Returns
List of embeddings, one for each text.
embed_query(text: str) → List[float][source]¶
Compute query embeddings using a HuggingFace instruct model.
Parameters
text – The text to embed.
Returns
Embeddings for the text.
classmethod from_orm(obj: Any) → Model¶
classmethod from_pipeline(pipeline: Any, hardware: Any, ... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.self_hosted_hugging_face.SelfHostedHuggingFaceInstructEmbeddings.html |
d1c0b8c72256-6 | Parameters
prompts – List of PromptValues. A PromptValue is an object that can be
converted to match the format of any language model (string for pure
text generation models and BaseMessages for chat models).
stop – Stop words to use when generating. Model output is cut off at the
first occurrence of any of these subst... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.self_hosted_hugging_face.SelfHostedHuggingFaceInstructEmbeddings.html |
d1c0b8c72256-7 | json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Cal... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.self_hosted_hugging_face.SelfHostedHuggingFaceInstructEmbeddings.html |
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