id stringlengths 14 16 | text stringlengths 13 2.7k | source stringlengths 57 178 |
|---|---|---|
0ae9a393e23b-9 | property lc_attributes: Dict¶
List of attribute names that should be included in the serialized kwargs.
These attributes must be accepted by the constructor.
property lc_secrets: Dict[str, str]¶
A map of constructor argument names to secret ids.
For example,{“openai_api_key”: “OPENAI_API_KEY”}
property output_schema: T... | lang/api.python.langchain.com/en/latest/output_parsers/langchain.output_parsers.retry.RetryOutputParser.html |
eae8bb3e09b9-0 | langchain.output_parsers.combining.CombiningOutputParser¶
class langchain.output_parsers.combining.CombiningOutputParser[source]¶
Bases: BaseOutputParser
Combine multiple output parsers into one.
param parsers: List[langchain.schema.output_parser.BaseOutputParser] [Required]¶
async abatch(inputs: List[Input], config: O... | lang/api.python.langchain.com/en/latest/output_parsers/langchain.output_parsers.combining.CombiningOutputParser.html |
eae8bb3e09b9-1 | to be different candidate outputs for a single model input.
Returns
Structured output.
async astream(input: Input, config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → AsyncIterator[Output]¶
Default implementation of astream, which calls ainvoke.
Subclasses should override this method if they support str... | lang/api.python.langchain.com/en/latest/output_parsers/langchain.output_parsers.combining.CombiningOutputParser.html |
eae8bb3e09b9-2 | Default implementation runs invoke in parallel using a thread pool executor.
The default implementation of batch works well for IO bound runnables.
Subclasses should override this method if they can batch more efficiently;
e.g., if the underlying runnable uses an API which supports a batch mode.
bind(**kwargs: Any) → R... | lang/api.python.langchain.com/en/latest/output_parsers/langchain.output_parsers.combining.CombiningOutputParser.html |
eae8bb3e09b9-3 | 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... | lang/api.python.langchain.com/en/latest/output_parsers/langchain.output_parsers.combining.CombiningOutputParser.html |
eae8bb3e09b9-4 | methods will have a dynamic output schema that depends on which
configuration the runnable is invoked with.
This method allows to get an output schema for a specific configuration.
Parameters
config – A config to use when generating the schema.
Returns
A pydantic model that can be used to validate output.
invoke(input:... | lang/api.python.langchain.com/en/latest/output_parsers/langchain.output_parsers.combining.CombiningOutputParser.html |
eae8bb3e09b9-5 | The unique identifier is a list of strings that describes the path
to the object.
map() → Runnable[List[Input], List[Output]]¶
Return a new Runnable that maps a list of inputs to a list of outputs,
by calling invoke() with each input.
parse(text: str) → Dict[str, Any][source]¶
Parse the output of an LLM call.
classmeth... | lang/api.python.langchain.com/en/latest/output_parsers/langchain.output_parsers.combining.CombiningOutputParser.html |
eae8bb3e09b9-6 | classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
stream(input: Input, config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → Iterator[Output]¶
Default implementation of stream, which calls invoke.
Subclasses should override t... | lang/api.python.langchain.com/en/latest/output_parsers/langchain.output_parsers.combining.CombiningOutputParser.html |
eae8bb3e09b9-7 | fallback in order, upon failures.
with_listeners(*, on_start: Optional[Listener] = None, on_end: Optional[Listener] = None, on_error: Optional[Listener] = None) → Runnable[Input, Output]¶
Bind lifecycle listeners to a Runnable, returning a new Runnable.
on_start: Called before the runnable starts running, with the Run ... | lang/api.python.langchain.com/en/latest/output_parsers/langchain.output_parsers.combining.CombiningOutputParser.html |
eae8bb3e09b9-8 | The type of output this runnable produces specified as a type annotation.
property config_specs: List[langchain.schema.runnable.utils.ConfigurableFieldSpec]¶
List configurable fields for this runnable.
property input_schema: Type[pydantic.main.BaseModel]¶
The type of input this runnable accepts specified as a pydantic ... | lang/api.python.langchain.com/en/latest/output_parsers/langchain.output_parsers.combining.CombiningOutputParser.html |
ef490339c175-0 | langchain.output_parsers.list.MarkdownListOutputParser¶
class langchain.output_parsers.list.MarkdownListOutputParser[source]¶
Bases: ListOutputParser
Parse a markdown list.
async abatch(inputs: List[Input], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, return_exceptions: bool = False, **kwarg... | lang/api.python.langchain.com/en/latest/output_parsers/langchain.output_parsers.list.MarkdownListOutputParser.html |
ef490339c175-1 | to be different candidate outputs for a single model input.
Returns
Structured output.
async astream(input: Input, config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → AsyncIterator[Output]¶
Default implementation of astream, which calls ainvoke.
Subclasses should override this method if they support str... | lang/api.python.langchain.com/en/latest/output_parsers/langchain.output_parsers.list.MarkdownListOutputParser.html |
ef490339c175-2 | Default implementation runs invoke in parallel using a thread pool executor.
The default implementation of batch works well for IO bound runnables.
Subclasses should override this method if they can batch more efficiently;
e.g., if the underlying runnable uses an API which supports a batch mode.
bind(**kwargs: Any) → R... | lang/api.python.langchain.com/en/latest/output_parsers/langchain.output_parsers.list.MarkdownListOutputParser.html |
ef490339c175-3 | 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... | lang/api.python.langchain.com/en/latest/output_parsers/langchain.output_parsers.list.MarkdownListOutputParser.html |
ef490339c175-4 | methods will have a dynamic output schema that depends on which
configuration the runnable is invoked with.
This method allows to get an output schema for a specific configuration.
Parameters
config – A config to use when generating the schema.
Returns
A pydantic model that can be used to validate output.
invoke(input:... | lang/api.python.langchain.com/en/latest/output_parsers/langchain.output_parsers.list.MarkdownListOutputParser.html |
ef490339c175-5 | The unique identifier is a list of strings that describes the path
to the object.
map() → Runnable[List[Input], List[Output]]¶
Return a new Runnable that maps a list of inputs to a list of outputs,
by calling invoke() with each input.
parse(text: str) → List[str][source]¶
Parse the output of an LLM call.
classmethod pa... | lang/api.python.langchain.com/en/latest/output_parsers/langchain.output_parsers.list.MarkdownListOutputParser.html |
ef490339c175-6 | classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
stream(input: Input, config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → Iterator[Output]¶
Default implementation of stream, which calls invoke.
Subclasses should override t... | lang/api.python.langchain.com/en/latest/output_parsers/langchain.output_parsers.list.MarkdownListOutputParser.html |
ef490339c175-7 | fallback in order, upon failures.
with_listeners(*, on_start: Optional[Listener] = None, on_end: Optional[Listener] = None, on_error: Optional[Listener] = None) → Runnable[Input, Output]¶
Bind lifecycle listeners to a Runnable, returning a new Runnable.
on_start: Called before the runnable starts running, with the Run ... | lang/api.python.langchain.com/en/latest/output_parsers/langchain.output_parsers.list.MarkdownListOutputParser.html |
ef490339c175-8 | The type of output this runnable produces specified as a type annotation.
property config_specs: List[langchain.schema.runnable.utils.ConfigurableFieldSpec]¶
List configurable fields for this runnable.
property input_schema: Type[pydantic.main.BaseModel]¶
The type of input this runnable accepts specified as a pydantic ... | lang/api.python.langchain.com/en/latest/output_parsers/langchain.output_parsers.list.MarkdownListOutputParser.html |
bf2d19254abf-0 | langchain.tools.render.render_text_description_and_args¶
langchain.tools.render.render_text_description_and_args(tools: List[BaseTool]) → str[source]¶
Render the tool name, description, and args in plain text.
Output will be in the format of:
search: This tool is used for search, args: {"query": {"type": "string"}}
cal... | lang/api.python.langchain.com/en/latest/tools.render/langchain.tools.render.render_text_description_and_args.html |
e37f4b7e52dc-0 | langchain.tools.render.format_tool_to_openai_function¶
langchain.tools.render.format_tool_to_openai_function(tool: BaseTool) → FunctionDescription[source]¶
Format tool into the OpenAI function API.
Examples using format_tool_to_openai_function¶
Tools as OpenAI Functions | lang/api.python.langchain.com/en/latest/tools.render/langchain.tools.render.format_tool_to_openai_function.html |
af9c6206f148-0 | langchain.tools.render.render_text_description¶
langchain.tools.render.render_text_description(tools: List[BaseTool]) → str[source]¶
Render the tool name and description in plain text.
Output will be in the format of:
search: This tool is used for search
calculator: This tool is used for math | lang/api.python.langchain.com/en/latest/tools.render/langchain.tools.render.render_text_description.html |
2b953d2106fd-0 | langchain.tools.render.format_tool_to_openai_tool¶
langchain.tools.render.format_tool_to_openai_tool(tool: BaseTool) → ToolDescription[source]¶
Format tool into the OpenAI function API. | lang/api.python.langchain.com/en/latest/tools.render/langchain.tools.render.format_tool_to_openai_tool.html |
bcdde03a7d91-0 | 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... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.huggingface.HuggingFaceEmbeddings.html |
bcdde03a7d91-1 | 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... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.huggingface.HuggingFaceEmbeddings.html |
bcdde03a7d91-2 | 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... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.huggingface.HuggingFaceEmbeddings.html |
bcdde03a7d91-3 | Sentence Transformers
LOTR (Merger Retriever)
ScaNN
Annoy
your local model path
Pairwise Embedding Distance
Embedding Distance
Lost in the middle: The problem with long contexts | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.huggingface.HuggingFaceEmbeddings.html |
fdbcffb2087c-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 ... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.embaas.EmbaasEmbeddingsPayload.html |
fdbcffb2087c-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... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.embaas.EmbaasEmbeddingsPayload.html |
a23c12ca08bb-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. | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.localai.async_embed_with_retry.html |
7220ad1098bb-0 | langchain.embeddings.aleph_alpha.AlephAlphaSymmetricSemanticEmbedding¶
class langchain.embeddings.aleph_alpha.AlephAlphaSymmetricSemanticEmbedding[source]¶
Bases: AlephAlphaAsymmetricSemanticEmbedding
The symmetric version of the Aleph Alpha’s semantic embeddings.
The main difference is that here, both the documents an... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.aleph_alpha.AlephAlphaSymmetricSemanticEmbedding.html |
7220ad1098bb-1 | Determines in which datacenters the request may be processed.
You can either set the parameter to “aleph-alpha” or omit it (defaulting to None).
Not setting this value, or setting it to None, gives us maximal flexibility
in processing your request in our
own datacenters and on servers hosted with other providers.
Choos... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.aleph_alpha.AlephAlphaSymmetricSemanticEmbedding.html |
7220ad1098bb-2 | 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 other validation is performed.
Behaves as if Config.extra = ‘allow’ was set ... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.aleph_alpha.AlephAlphaSymmetricSemanticEmbedding.html |
7220ad1098bb-3 | Returns
List of embeddings, one for each text.
embed_query(text: str) → List[float][source]¶
Call out to Aleph Alpha’s asymmetric, query embedding endpoint
:param text: The text to embed.
Returns
Embeddings for the text.
classmethod from_orm(obj: Any) → Model¶
json(*, include: Optional[Union[AbstractSetIntStr, MappingI... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.aleph_alpha.AlephAlphaSymmetricSemanticEmbedding.html |
7220ad1098bb-4 | 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 AlephAlphaSymmetricSemanticEmbedding¶
Aleph Alpha | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.aleph_alpha.AlephAlphaSymmetricSemanticEmbedding.html |
a76afdcb88d0-0 | langchain.embeddings.baidu_qianfan_endpoint.QianfanEmbeddingsEndpoint¶
class langchain.embeddings.baidu_qianfan_endpoint.QianfanEmbeddingsEndpoint[source]¶
Bases: BaseModel, Embeddings
Baidu Qianfan Embeddings embedding models.
Create a new model by parsing and validating input data from keyword arguments.
Raises Valid... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.baidu_qianfan_endpoint.QianfanEmbeddingsEndpoint.html |
a76afdcb88d0-1 | 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... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.baidu_qianfan_endpoint.QianfanEmbeddingsEndpoint.html |
a76afdcb88d0-2 | embed_query(text: str) → List[float][source]¶
Embed query 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, exclud... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.baidu_qianfan_endpoint.QianfanEmbeddingsEndpoint.html |
9d396e409990-0 | 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... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.deepinfra.DeepInfraEmbeddings.html |
9d396e409990-1 | 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... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.deepinfra.DeepInfraEmbeddings.html |
9d396e409990-2 | 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 ... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.deepinfra.DeepInfraEmbeddings.html |
9d396e409990-3 | 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 | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.deepinfra.DeepInfraEmbeddings.html |
8013c4d16a4c-0 | langchain.embeddings.gradient_ai.GradientEmbeddings¶
class langchain.embeddings.gradient_ai.GradientEmbeddings[source]¶
Bases: BaseModel, Embeddings
Gradient.ai Embedding models.
GradientLLM is a class to interact with Embedding Models on gradient.ai
To use, set the environment variable GRADIENT_ACCESS_TOKEN with your
... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.gradient_ai.GradientEmbeddings.html |
8013c4d16a4c-1 | Parameters
text – The text to embed.
Returns
Embeddings for the 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 other validation is performed.
Behave... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.gradient_ai.GradientEmbeddings.html |
8013c4d16a4c-2 | Parameters
texts – The list of texts to embed.
Returns
List of embeddings, one for each text.
embed_query(text: str) → List[float][source]¶
Call out to Gradient’s embedding endpoint.
Parameters
text – The text to embed.
Returns
Embeddings for the text.
classmethod from_orm(obj: Any) → Model¶
json(*, include: Optional[U... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.gradient_ai.GradientEmbeddings.html |
8013c4d16a4c-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¶ | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.gradient_ai.GradientEmbeddings.html |
134ecb966fd4-0 | 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 ... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.elasticsearch.ElasticsearchEmbeddings.html |
134ecb966fd4-1 | 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... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.elasticsearch.ElasticsearchEmbeddings.html |
134ecb966fd4-2 | 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... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.elasticsearch.ElasticsearchEmbeddings.html |
134ecb966fd4-3 | 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... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.elasticsearch.ElasticsearchEmbeddings.html |
88c2af2b18f8-0 | 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... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.mlflow_gateway.MlflowAIGatewayEmbeddings.html |
88c2af2b18f8-1 | 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... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.mlflow_gateway.MlflowAIGatewayEmbeddings.html |
88c2af2b18f8-2 | 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... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.mlflow_gateway.MlflowAIGatewayEmbeddings.html |
3efd7b8f1b42-0 | langchain.embeddings.javelin_ai_gateway.JavelinAIGatewayEmbeddings¶
class langchain.embeddings.javelin_ai_gateway.JavelinAIGatewayEmbeddings[source]¶
Bases: Embeddings, BaseModel
Wrapper around embeddings LLMs in the Javelin AI Gateway.
To use, you should have the javelin_sdk python package installed.
For more informat... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.javelin_ai_gateway.JavelinAIGatewayEmbeddings.html |
3efd7b8f1b42-1 | 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... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.javelin_ai_gateway.JavelinAIGatewayEmbeddings.html |
3efd7b8f1b42-2 | Embed query 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: bool ... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.javelin_ai_gateway.JavelinAIGatewayEmbeddings.html |
7066459d9973-0 | langchain.embeddings.localai.LocalAIEmbeddings¶
class langchain.embeddings.localai.LocalAIEmbeddings[source]¶
Bases: BaseModel, Embeddings
LocalAI embedding models.
Since LocalAI and OpenAI have 1:1 compatibility between APIs, this class
uses the openai Python package’s openai.Embedding as its client.
Thus, you should ... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.localai.LocalAIEmbeddings.html |
7066459d9973-1 | param openai_api_base: Optional[str] = None¶
param openai_api_key: Optional[str] = None¶
param openai_api_version: Optional[str] = None¶
param openai_organization: Optional[str] = None¶
param openai_proxy: Optional[str] = None¶
param request_timeout: Optional[Union[float, Tuple[float, float]]] = None¶
Timeout in second... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.localai.LocalAIEmbeddings.html |
7066459d9973-2 | 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... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.localai.LocalAIEmbeddings.html |
7066459d9973-3 | 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:... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.localai.LocalAIEmbeddings.html |
9f51eae3c9f8-0 | 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... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.cohere.CohereEmbeddings.html |
9f51eae3c9f8-1 | async aembed_query(text: str) → List[float][source]¶
Async call out to Cohere’s embedding endpoint.
Parameters
text – The text to embed.
Returns
Embeddings for the text.
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶
Creates a new model setting __dict__ and __fields_set__ from trust... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.cohere.CohereEmbeddings.html |
9f51eae3c9f8-2 | Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
embed_documents(texts: List[str]) → List[List[float]][source]¶
Call out to Cohere’s embedding endpoint.
Parameters
texts – The list of texts to embed.
Returns
List of embeddings, one for each text.
embed_query(t... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.cohere.CohereEmbeddings.html |
9f51eae3c9f8-3 | 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... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.cohere.CohereEmbeddings.html |
f7d84ad969b8-0 | langchain.embeddings.voyageai.embed_with_retry¶
langchain.embeddings.voyageai.embed_with_retry(embeddings: VoyageEmbeddings, **kwargs: Any) → Any[source]¶
Use tenacity to retry the embedding call. | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.voyageai.embed_with_retry.html |
abf094fc7e71-0 | langchain.embeddings.awa.AwaEmbeddings¶
class langchain.embeddings.awa.AwaEmbeddings[source]¶
Bases: BaseModel, Embeddings
Embedding documents and queries with Awa DB.
client¶
The AwaEmbedding client.
model¶
The name of the model used for embedding.
Default is “all-mpnet-base-v2”.
Create a new model by parsing and vali... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.awa.AwaEmbeddings.html |
abf094fc7e71-1 | 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... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.awa.AwaEmbeddings.html |
abf094fc7e71-2 | 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... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.awa.AwaEmbeddings.html |
84e87e8b1703-0 | 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... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.clarifai.ClarifaiEmbeddings.html |
84e87e8b1703-1 | 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... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.clarifai.ClarifaiEmbeddings.html |
84e87e8b1703-2 | 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... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.clarifai.ClarifaiEmbeddings.html |
84e87e8b1703-3 | classmethod validate(value: Any) → Model¶
Examples using ClarifaiEmbeddings¶
Clarifai | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.clarifai.ClarifaiEmbeddings.html |
56ddad8e92bd-0 | langchain.embeddings.jina.JinaEmbeddings¶
class langchain.embeddings.jina.JinaEmbeddings[source]¶
Bases: BaseModel, Embeddings
Jina embedding models.
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 jin... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.jina.JinaEmbeddings.html |
56ddad8e92bd-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... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.jina.JinaEmbeddings.html |
56ddad8e92bd-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... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.jina.JinaEmbeddings.html |
f89b83fc1d56-0 | 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. | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.localai.embed_with_retry.html |
ec2a2345e25b-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... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.huggingface.HuggingFaceInstructEmbeddings.html |
ec2a2345e25b-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... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.huggingface.HuggingFaceInstructEmbeddings.html |
ec2a2345e25b-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... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.huggingface.HuggingFaceInstructEmbeddings.html |
ec2a2345e25b-3 | classmethod validate(value: Any) → Model¶
Examples using HuggingFaceInstructEmbeddings¶
InstructEmbeddings
Vector SQL Retriever with MyScale | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.huggingface.HuggingFaceInstructEmbeddings.html |
f8cdbb95d51c-0 | langchain.embeddings.voyageai.VoyageEmbeddings¶
class langchain.embeddings.voyageai.VoyageEmbeddings[source]¶
Bases: BaseModel, Embeddings
Voyage embedding models.
To use, you should have the environment variable VOYAGE_API_KEY set with
your API key or pass it as a named parameter to the constructor.
Example
from langc... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.voyageai.VoyageEmbeddings.html |
f8cdbb95d51c-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... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.voyageai.VoyageEmbeddings.html |
f8cdbb95d51c-2 | Call out to Voyage 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]] = None,... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.voyageai.VoyageEmbeddings.html |
c880b77cd637-0 | 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... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.openai.OpenAIEmbeddings.html |
c880b77cd637-1 | 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 default_headers... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.openai.OpenAIEmbeddings.html |
c880b77cd637-2 | param openai_organization: Optional[str] = None (alias 'organization')¶
Automatically inferred from env var OPENAI_ORG_ID if not provided.
param openai_proxy: Optional[str] = None¶
param request_timeout: Optional[Union[float, Tuple[float, float], Any]] = None (alias 'timeout')¶
Timeout for requests to OpenAI completion... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.openai.OpenAIEmbeddings.html |
c880b77cd637-3 | specified by the class.
Returns
List of embeddings, one for each text.
async aembed_query(text: str) → List[float][source]¶
Call out to OpenAI’s embedding endpoint async for embedding query text.
Parameters
text – The text to embed.
Returns
Embedding for the text.
classmethod construct(_fields_set: Optional[SetStr] = N... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.openai.OpenAIEmbeddings.html |
c880b77cd637-4 | Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
embed_documents(texts: List[str], chunk_size: Optional[int] = 0) → List[List[float]][source]¶
Call out to OpenAI’s embedding endpoint for embedding search docs.
Parameters
texts – The list of texts to embed.
chu... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.openai.OpenAIEmbeddings.html |
c880b77cd637-5 | 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¶
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶
classmet... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.openai.OpenAIEmbeddings.html |
c880b77cd637-6 | Hologres
MongoDB Atlas
Meilisearch
Loading documents from a YouTube url
Psychic
Docugami
LLM Caching integrations
Set env var OPENAI_API_KEY or load from a .env file:
Set env var OPENAI_API_KEY or load from a .env file
Question Answering
Perform context-aware text splitting
Conversational Retrieval Agent
Retrieve from ... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.openai.OpenAIEmbeddings.html |
351cc964302b-0 | langchain.embeddings.edenai.EdenAiEmbeddings¶
class langchain.embeddings.edenai.EdenAiEmbeddings[source]¶
Bases: BaseModel, Embeddings
EdenAI embedding.
environment variable EDENAI_API_KEY set with your API key, or pass
it as a named parameter.
Create a new model by parsing and validating input data from keyword argume... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.edenai.EdenAiEmbeddings.html |
351cc964302b-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... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.edenai.EdenAiEmbeddings.html |
351cc964302b-2 | static get_user_agent() → str[source]¶
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_no... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.edenai.EdenAiEmbeddings.html |
fc9d3bd8bdf8-0 | 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. | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.dashscope.embed_with_retry.html |
f5913242cbee-0 | langchain.embeddings.fastembed.FastEmbedEmbeddings¶
class langchain.embeddings.fastembed.FastEmbedEmbeddings[source]¶
Bases: BaseModel, Embeddings
Qdrant FastEmbedding models.
FastEmbed is a lightweight, fast, Python library built for embedding generation.
See more documentation at:
* https://github.com/qdrant/fastembe... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.fastembed.FastEmbedEmbeddings.html |
f5913242cbee-1 | 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[SetStr] = None, **values: Any) → Model¶
Creates a new model setting __dict__ and __fields_set__ from trust... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.fastembed.FastEmbedEmbeddings.html |
f5913242cbee-2 | embed_documents(texts: List[str]) → List[List[float]][source]¶
Generate embeddings for documents using FastEmbed.
Parameters
texts – The list of texts to embed.
Returns
List of embeddings, one for each text.
embed_query(text: str) → List[float][source]¶
Generate query embeddings using FastEmbed.
Parameters
text – The t... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.fastembed.FastEmbedEmbeddings.html |
f5913242cbee-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¶ | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.fastembed.FastEmbedEmbeddings.html |
625b1403ed05-0 | langchain.embeddings.google_palm.embed_with_retry¶
langchain.embeddings.google_palm.embed_with_retry(embeddings: GooglePalmEmbeddings, *args: Any, **kwargs: Any) → Any[source]¶
Use tenacity to retry the completion call. | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.google_palm.embed_with_retry.html |
1c9484528b0a-0 | langchain.embeddings.self_hosted_hugging_face.SelfHostedHuggingFaceEmbeddings¶
class langchain.embeddings.self_hosted_hugging_face.SelfHostedHuggingFaceEmbeddings[source]¶
Bases: SelfHostedEmbeddings
HuggingFace embedding models on self-hosted remote hardware.
Supported hardware includes auto-launched instances on AWS,... | lang/api.python.langchain.com/en/latest/embeddings/langchain.embeddings.self_hosted_hugging_face.SelfHostedHuggingFaceEmbeddings.html |
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