id stringlengths 14 15 | text stringlengths 35 2.51k | source stringlengths 61 154 |
|---|---|---|
9dfec98ab6bd-1 | You can use these to eg identify a specific instance of a chain with its use case.
param verbose: bool [Optional]¶
Whether or not run in verbose mode. In verbose mode, some intermediate logs
will be printed to the console. Defaults to langchain.verbose value.
__call__(inputs: Union[Dict[str, Any], Any], return_only_out... | https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.base.BaseCombineDocumentsChain.html |
9dfec98ab6bd-2 | response. If True, only new keys generated by this chain will be
returned. If False, both input keys and new keys generated by this
chain will be returned. Defaults to False.
callbacks – Callbacks to use for this chain run. If not provided, will
use the callbacks provided to the chain.
include_run_info – Whether to inc... | https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.base.BaseCombineDocumentsChain.html |
9dfec98ab6bd-3 | Returns None if the method does not depend on the prompt length.
validator raise_deprecation » all fields¶
Raise deprecation warning if callback_manager is used.
run(*args: Any, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, tags: Optional[List[str]] = None, **kwargs: Any) → str¶
R... | https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.base.BaseCombineDocumentsChain.html |
330c4aa064dd-0 | langchain.chains.loading.load_chain¶
langchain.chains.loading.load_chain(path: Union[str, Path], **kwargs: Any) → Chain[source]¶
Unified method for loading a chain from LangChainHub or local fs. | https://api.python.langchain.com/en/latest/chains/langchain.chains.loading.load_chain.html |
744a8cca7bca-0 | langchain.chains.openai_functions.openapi.get_openapi_chain¶
langchain.chains.openai_functions.openapi.get_openapi_chain(spec: Union[OpenAPISpec, str], llm: Optional[BaseLanguageModel] = None, prompt: Optional[BasePromptTemplate] = None, request_chain: Optional[Chain] = None, llm_kwargs: Optional[Dict] = None, verbose:... | https://api.python.langchain.com/en/latest/chains/langchain.chains.openai_functions.openapi.get_openapi_chain.html |
49a3084b9de7-0 | langchain.chains.router.base.MultiRouteChain¶
class langchain.chains.router.base.MultiRouteChain(*, memory: Optional[BaseMemory] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, callback_manager: Optional[BaseCallbackManager] = None, verbose: bool = None, tags: Optional[List[st... | https://api.python.langchain.com/en/latest/chains/langchain.chains.router.base.MultiRouteChain.html |
49a3084b9de7-1 | There are many different types of memory - please see memory docs
for the full catalog.
param router_chain: RouterChain [Required]¶
Chain that routes inputs to destination chains.
param silent_errors: bool = False¶
If True, use default_chain when an invalid destination name is provided.
Defaults to False.
param tags: O... | https://api.python.langchain.com/en/latest/chains/langchain.chains.router.base.MultiRouteChain.html |
49a3084b9de7-2 | include_run_info – Whether to include run info in the response. Defaults
to False.
async acall(inputs: Union[Dict[str, Any], Any], return_only_outputs: bool = False, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, include_run_info: bool = False) → ... | https://api.python.langchain.com/en/latest/chains/langchain.chains.router.base.MultiRouteChain.html |
49a3084b9de7-3 | Validate and prep inputs.
prep_outputs(inputs: Dict[str, str], outputs: Dict[str, str], return_only_outputs: bool = False) → Dict[str, str]¶
Validate and prep outputs.
validator raise_deprecation » all fields¶
Raise deprecation warning if callback_manager is used.
run(*args: Any, callbacks: Optional[Union[List[BaseCa... | https://api.python.langchain.com/en/latest/chains/langchain.chains.router.base.MultiRouteChain.html |
49a3084b9de7-4 | Configuration for this pydantic object.
arbitrary_types_allowed = True¶
extra = 'forbid'¶ | https://api.python.langchain.com/en/latest/chains/langchain.chains.router.base.MultiRouteChain.html |
b1205f9e7433-0 | langchain.chains.query_constructor.ir.Visitor¶
class langchain.chains.query_constructor.ir.Visitor[source]¶
Bases: ABC
Defines interface for IR translation using visitor pattern.
Methods
__init__()
visit_comparison(comparison)
Translate a Comparison.
visit_operation(operation)
Translate an Operation.
visit_structured_q... | https://api.python.langchain.com/en/latest/chains/langchain.chains.query_constructor.ir.Visitor.html |
788571586a10-0 | langchain.chains.openai_functions.extraction.create_extraction_chain_pydantic¶
langchain.chains.openai_functions.extraction.create_extraction_chain_pydantic(pydantic_schema: Any, llm: BaseLanguageModel) → Chain[source]¶
Creates a chain that extracts information from a passage using pydantic schema.
Parameters
pydantic_... | https://api.python.langchain.com/en/latest/chains/langchain.chains.openai_functions.extraction.create_extraction_chain_pydantic.html |
aa996752a74a-0 | langchain.chains.prompt_selector.BasePromptSelector¶
class langchain.chains.prompt_selector.BasePromptSelector[source]¶
Bases: BaseModel, ABC
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.
abstract get_prom... | https://api.python.langchain.com/en/latest/chains/langchain.chains.prompt_selector.BasePromptSelector.html |
6d9f00bfa4b2-0 | langchain.chains.natbot.base.NatBotChain¶
class langchain.chains.natbot.base.NatBotChain(*, memory: Optional[BaseMemory] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, callback_manager: Optional[BaseCallbackManager] = None, verbose: bool = None, tags: Optional[List[str]] = No... | https://api.python.langchain.com/en/latest/chains/langchain.chains.natbot.base.NatBotChain.html |
6d9f00bfa4b2-1 | and at the end of every chain. At the start, memory loads variables and passes
them along in the chain. At the end, it saves any returned variables.
There are many different types of memory - please see memory docs
for the full catalog.
param objective: str [Required]¶
Objective that NatBot is tasked with completing.
p... | https://api.python.langchain.com/en/latest/chains/langchain.chains.natbot.base.NatBotChain.html |
6d9f00bfa4b2-2 | include_run_info – Whether to include run info in the response. Defaults
to False.
async acall(inputs: Union[Dict[str, Any], Any], return_only_outputs: bool = False, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, include_run_info: bool = False) → ... | https://api.python.langchain.com/en/latest/chains/langchain.chains.natbot.base.NatBotChain.html |
6d9f00bfa4b2-3 | browser_content – Content of the page as currently displayed by the browser.
Returns
Next browser command to run.
Example
browser_content = "...."
llm_command = natbot.run("www.google.com", browser_content)
classmethod from_default(objective: str, **kwargs: Any) → NatBotChain[source]¶
Load with default LLMChain.
classm... | https://api.python.langchain.com/en/latest/chains/langchain.chains.natbot.base.NatBotChain.html |
6d9f00bfa4b2-4 | property lc_attributes: Dict¶
Return a list of attribute names that should be included in the
serialized kwargs. These attributes must be accepted by the
constructor.
property lc_namespace: List[str]¶
Return the namespace of the langchain object.
eg. [“langchain”, “llms”, “openai”]
property lc_secrets: Dict[str, str]¶
... | https://api.python.langchain.com/en/latest/chains/langchain.chains.natbot.base.NatBotChain.html |
2545430045a6-0 | langchain.chains.llm_requests.LLMRequestsChain¶
class langchain.chains.llm_requests.LLMRequestsChain(*, memory: Optional[BaseMemory] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, callback_manager: Optional[BaseCallbackManager] = None, verbose: bool = None, tags: Optional[Lis... | https://api.python.langchain.com/en/latest/chains/langchain.chains.llm_requests.LLMRequestsChain.html |
2545430045a6-1 | for the full catalog.
param requests_wrapper: TextRequestsWrapper [Optional]¶
param tags: Optional[List[str]] = None¶
Optional list of tags associated with the chain. Defaults to None
These tags will be associated with each call to this chain,
and passed as arguments to the handlers defined in callbacks.
You can use th... | https://api.python.langchain.com/en/latest/chains/langchain.chains.llm_requests.LLMRequestsChain.html |
2545430045a6-2 | include_run_info – Whether to include run info in the response. Defaults
to False.
async acall(inputs: Union[Dict[str, Any], Any], return_only_outputs: bool = False, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, include_run_info: bool = False) → ... | https://api.python.langchain.com/en/latest/chains/langchain.chains.llm_requests.LLMRequestsChain.html |
2545430045a6-3 | Validate and prep inputs.
prep_outputs(inputs: Dict[str, str], outputs: Dict[str, str], return_only_outputs: bool = False) → Dict[str, str]¶
Validate and prep outputs.
validator raise_deprecation » all fields¶
Raise deprecation warning if callback_manager is used.
run(*args: Any, callbacks: Optional[Union[List[BaseCa... | https://api.python.langchain.com/en/latest/chains/langchain.chains.llm_requests.LLMRequestsChain.html |
2545430045a6-4 | Return whether or not the class is serializable.
model Config[source]¶
Bases: object
Configuration for this pydantic object.
arbitrary_types_allowed = True¶
extra = 'forbid'¶ | https://api.python.langchain.com/en/latest/chains/langchain.chains.llm_requests.LLMRequestsChain.html |
1166e10fb3e9-0 | langchain.schema.HumanMessage¶
class langchain.schema.HumanMessage(*, content: str, additional_kwargs: dict = None, example: bool = False)[source]¶
Bases: BaseMessage
Type of message that is spoken by the human.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if th... | https://api.python.langchain.com/en/latest/schema/langchain.schema.HumanMessage.html |
8ba0406ef205-0 | langchain.schema.Generation¶
class langchain.schema.Generation(*, text: str, generation_info: Optional[Dict[str, Any]] = None)[source]¶
Bases: Serializable
Output of a single generation.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be pa... | https://api.python.langchain.com/en/latest/schema/langchain.schema.Generation.html |
a3dbc0300c65-0 | langchain.schema.SystemMessage¶
class langchain.schema.SystemMessage(*, content: str, additional_kwargs: dict = None)[source]¶
Bases: BaseMessage
Type of message that is a system message.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be p... | https://api.python.langchain.com/en/latest/schema/langchain.schema.SystemMessage.html |
13120ad4a837-0 | langchain.schema.messages_to_dict¶
langchain.schema.messages_to_dict(messages: List[BaseMessage]) → List[dict][source]¶
Convert messages to dict.
Parameters
messages – List of messages to convert.
Returns
List of dicts. | https://api.python.langchain.com/en/latest/schema/langchain.schema.messages_to_dict.html |
38ac7df427c4-0 | langchain.schema.LLMResult¶
class langchain.schema.LLMResult(*, generations: List[List[Generation]], llm_output: Optional[dict] = None, run: Optional[List[RunInfo]] = None)[source]¶
Bases: BaseModel
Class that contains all relevant information for an LLM Result.
Create a new model by parsing and validating input data f... | https://api.python.langchain.com/en/latest/schema/langchain.schema.LLMResult.html |
393d8af327a8-0 | langchain.schema.BaseMemory¶
class langchain.schema.BaseMemory[source]¶
Bases: Serializable, ABC
Base interface for memory in chains.
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.
abstract clear() → None[s... | https://api.python.langchain.com/en/latest/schema/langchain.schema.BaseMemory.html |
0a43c3c15c20-0 | langchain.schema.FunctionMessage¶
class langchain.schema.FunctionMessage(*, content: str, additional_kwargs: dict = None, name: str)[source]¶
Bases: BaseMessage
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... | https://api.python.langchain.com/en/latest/schema/langchain.schema.FunctionMessage.html |
5122c475bcd3-0 | langchain.schema.AgentFinish¶
class langchain.schema.AgentFinish(return_values: dict, log: str)[source]¶
Bases: NamedTuple
Agent’s return value.
Create new instance of AgentFinish(return_values, log)
Methods
__init__()
count(value, /)
Return number of occurrences of value.
index(value[, start, stop])
Return first index... | https://api.python.langchain.com/en/latest/schema/langchain.schema.AgentFinish.html |
f03acbbc3d80-0 | langchain.schema.messages_from_dict¶
langchain.schema.messages_from_dict(messages: List[dict]) → List[BaseMessage][source]¶
Convert messages from dict.
Parameters
messages – List of messages (dicts) to convert.
Returns
List of messages (BaseMessages). | https://api.python.langchain.com/en/latest/schema/langchain.schema.messages_from_dict.html |
757058b1876d-0 | langchain.schema.BaseRetriever¶
class langchain.schema.BaseRetriever[source]¶
Bases: ABC
Base interface for a retriever.
Methods
__init__()
aget_relevant_documents(query, *[, callbacks])
Asynchronously get documents relevant to a query.
get_relevant_documents(query, *[, callbacks])
Retrieve documents relevant to a quer... | https://api.python.langchain.com/en/latest/schema/langchain.schema.BaseRetriever.html |
cdac1c3ee732-0 | langchain.schema.BaseChatMessageHistory¶
class langchain.schema.BaseChatMessageHistory[source]¶
Bases: ABC
Base interface for chat message history
See ChatMessageHistory for default implementation.
Methods
__init__()
add_ai_message(message)
Add an AI message to the store
add_message(message)
Add a self-created message ... | https://api.python.langchain.com/en/latest/schema/langchain.schema.BaseChatMessageHistory.html |
85573316be85-0 | langchain.schema.ChatGeneration¶
class langchain.schema.ChatGeneration(*, text: str = '', generation_info: Optional[Dict[str, Any]] = None, message: BaseMessage)[source]¶
Bases: Generation
Output of a single generation.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationErr... | https://api.python.langchain.com/en/latest/schema/langchain.schema.ChatGeneration.html |
ab454a775eb6-0 | langchain.schema.get_buffer_string¶
langchain.schema.get_buffer_string(messages: List[BaseMessage], human_prefix: str = 'Human', ai_prefix: str = 'AI') → str[source]¶
Get buffer string of messages. | https://api.python.langchain.com/en/latest/schema/langchain.schema.get_buffer_string.html |
5a201d617aa9-0 | langchain.schema.PromptValue¶
class langchain.schema.PromptValue[source]¶
Bases: Serializable, ABC
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.
to_json() → Union[SerializedConstructor, SerializedNotImplem... | https://api.python.langchain.com/en/latest/schema/langchain.schema.PromptValue.html |
a1e800c33bc0-0 | langchain.schema.BaseLLMOutputParser¶
class langchain.schema.BaseLLMOutputParser[source]¶
Bases: Serializable, ABC, Generic[T]
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.
abstract parse_result(result: Li... | https://api.python.langchain.com/en/latest/schema/langchain.schema.BaseLLMOutputParser.html |
6658a70b58cd-0 | langchain.schema.NoOpOutputParser¶
class langchain.schema.NoOpOutputParser[source]¶
Bases: BaseOutputParser[str]
Output parser that just returns the text as is.
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... | https://api.python.langchain.com/en/latest/schema/langchain.schema.NoOpOutputParser.html |
6658a70b58cd-1 | Return a map of constructor argument names to secret ids.
eg. {“openai_api_key”: “OPENAI_API_KEY”}
property lc_serializable: bool¶
Return whether or not the class is serializable.
model Config¶
Bases: object
extra = 'ignore'¶ | https://api.python.langchain.com/en/latest/schema/langchain.schema.NoOpOutputParser.html |
ccef5acbc4a2-0 | langchain.schema.BaseDocumentTransformer¶
class langchain.schema.BaseDocumentTransformer[source]¶
Bases: ABC
Base interface for transforming documents.
Methods
__init__()
atransform_documents(documents, **kwargs)
Asynchronously transform a list of documents.
transform_documents(documents, **kwargs)
Transform a list of ... | https://api.python.langchain.com/en/latest/schema/langchain.schema.BaseDocumentTransformer.html |
6ed9460796b4-0 | langchain.schema.AIMessage¶
class langchain.schema.AIMessage(*, content: str, additional_kwargs: dict = None, example: bool = False)[source]¶
Bases: BaseMessage
Type of message that is spoken by the AI.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input d... | https://api.python.langchain.com/en/latest/schema/langchain.schema.AIMessage.html |
04301f78bab9-0 | langchain.schema.ChatResult¶
class langchain.schema.ChatResult(*, generations: List[ChatGeneration], llm_output: Optional[dict] = None)[source]¶
Bases: BaseModel
Class that contains all relevant information for a Chat Result.
Create a new model by parsing and validating input data from keyword arguments.
Raises Validat... | https://api.python.langchain.com/en/latest/schema/langchain.schema.ChatResult.html |
4e3f1cd06dde-0 | langchain.schema.OutputParserException¶
class langchain.schema.OutputParserException(error: Any, observation: str | None = None, llm_output: str | None = None, send_to_llm: bool = False)[source]¶
Bases: ValueError
Exception that output parsers should raise to signify a parsing error.
This exists to differentiate parsin... | https://api.python.langchain.com/en/latest/schema/langchain.schema.OutputParserException.html |
d1bf044f070a-0 | langchain.schema.BaseMessage¶
class langchain.schema.BaseMessage(*, content: str, additional_kwargs: dict = None)[source]¶
Bases: Serializable
Message object.
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.
... | https://api.python.langchain.com/en/latest/schema/langchain.schema.BaseMessage.html |
acb91b85156f-0 | langchain.schema.ChatMessage¶
class langchain.schema.ChatMessage(*, content: str, additional_kwargs: dict = None, role: str)[source]¶
Bases: BaseMessage
Type of message with arbitrary speaker.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot... | https://api.python.langchain.com/en/latest/schema/langchain.schema.ChatMessage.html |
c8f7a3c92b10-0 | langchain.schema.Document¶
class langchain.schema.Document(*, page_content: str, metadata: dict = None)[source]¶
Bases: Serializable
Interface for interacting with a document.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to for... | https://api.python.langchain.com/en/latest/schema/langchain.schema.Document.html |
f4e99429add9-0 | langchain.schema.RunInfo¶
class langchain.schema.RunInfo(*, run_id: UUID)[source]¶
Bases: BaseModel
Class that contains all relevant metadata for a Run.
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 ... | https://api.python.langchain.com/en/latest/schema/langchain.schema.RunInfo.html |
a9d26939cd4b-0 | langchain.schema.BaseOutputParser¶
class langchain.schema.BaseOutputParser[source]¶
Bases: BaseLLMOutputParser, ABC, Generic[T]
Class to parse the output of an LLM call.
Output parsers help structure language model responses.
Create a new model by parsing and validating input data from keyword arguments.
Raises Validat... | https://api.python.langchain.com/en/latest/schema/langchain.schema.BaseOutputParser.html |
a9d26939cd4b-1 | eg. [“langchain”, “llms”, “openai”]
property lc_secrets: Dict[str, str]¶
Return a map of constructor argument names to secret ids.
eg. {“openai_api_key”: “OPENAI_API_KEY”}
property lc_serializable: bool¶
Return whether or not the class is serializable.
model Config¶
Bases: object
extra = 'ignore'¶ | https://api.python.langchain.com/en/latest/schema/langchain.schema.BaseOutputParser.html |
0c0efdd0ae97-0 | langchain.embeddings.embaas.EmbaasEmbeddings¶
class langchain.embeddings.embaas.EmbaasEmbeddings(*, model: str = 'e5-large-v2', instruction: Optional[str] = None, api_url: str = 'https://api.embaas.io/v1/embeddings/', embaas_api_key: Optional[str] = None)[source]¶
Bases: BaseModel, Embeddings
Wrapper around embaas’s em... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.embaas.EmbaasEmbeddings.html |
0c0efdd0ae97-1 | Returns
List of embeddings, one for each text.
embed_query(text: str) → List[float][source]¶
Get embeddings for a single text.
Parameters
text – The text to get embeddings for.
Returns
List of embeddings.
validator validate_environment » all fields[source]¶
Validate that api key and python package exists in environme... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.embaas.EmbaasEmbeddings.html |
d86a28b1e73d-0 | langchain.embeddings.embaas.EmbaasEmbeddingsPayload¶
class langchain.embeddings.embaas.EmbaasEmbeddingsPayload[source]¶
Bases: TypedDict
Payload for the embaas embeddings API.
Methods
__init__(*args, **kwargs)
clear()
copy()
fromkeys([value])
Create a new dictionary with keys from iterable and values set to value.
get(... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.embaas.EmbaasEmbeddingsPayload.html |
d86a28b1e73d-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 |
2d15bcc0e2e9-0 | langchain.embeddings.jina.JinaEmbeddings¶
class langchain.embeddings.jina.JinaEmbeddings(*, client: Any = None, model_name: str = 'ViT-B-32::openai', jina_auth_token: Optional[str] = None, jina_api_url: str = 'https://api.clip.jina.ai/api/v1/models/', request_headers: Optional[dict] = None)[source]¶
Bases: BaseModel, E... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.jina.JinaEmbeddings.html |
986cae0e47d6-0 | langchain.embeddings.google_palm.GooglePalmEmbeddings¶
class langchain.embeddings.google_palm.GooglePalmEmbeddings(*, client: Any = None, google_api_key: Optional[str] = None, model_name: str = 'models/embedding-gecko-001')[source]¶
Bases: BaseModel, Embeddings
Create a new model by parsing and validating input data fr... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.google_palm.GooglePalmEmbeddings.html |
870cb2f3a591-0 | langchain.embeddings.octoai_embeddings.OctoAIEmbeddings¶
class langchain.embeddings.octoai_embeddings.OctoAIEmbeddings(*, endpoint_url: Optional[str] = None, model_kwargs: Optional[dict] = None, octoai_api_token: Optional[str] = None, embed_instruction: str = 'Represent this input: ', query_instruction: str = 'Represen... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.octoai_embeddings.OctoAIEmbeddings.html |
c3d6b9d35af6-0 | langchain.embeddings.huggingface.HuggingFaceInstructEmbeddings¶
class langchain.embeddings.huggingface.HuggingFaceInstructEmbeddings(*, client: Any = None, model_name: str = 'hkunlp/instructor-large', cache_folder: Optional[str] = None, model_kwargs: Dict[str, Any] = None, encode_kwargs: Dict[str, Any] = None, embed_in... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.huggingface.HuggingFaceInstructEmbeddings.html |
c3d6b9d35af6-1 | Instruction to use for embedding query.
embed_documents(texts: List[str]) → List[List[float]][source]¶
Compute doc embeddings using a HuggingFace instruct model.
Parameters
texts – The list of texts to embed.
Returns
List of embeddings, one for each text.
embed_query(text: str) → List[float][source]¶
Compute query embe... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.huggingface.HuggingFaceInstructEmbeddings.html |
70cc1777f1b2-0 | langchain.embeddings.deepinfra.DeepInfraEmbeddings¶
class langchain.embeddings.deepinfra.DeepInfraEmbeddings(*, model_id: str = 'sentence-transformers/clip-ViT-B-32', normalize: bool = False, embed_instruction: str = 'passage: ', query_instruction: str = 'query: ', model_kwargs: Optional[dict] = None, deepinfra_api_tok... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.deepinfra.DeepInfraEmbeddings.html |
70cc1777f1b2-1 | param model_kwargs: Optional[dict] = None¶
Other model keyword args
param normalize: bool = False¶
whether to normalize the computed embeddings
param query_instruction: str = 'query: '¶
Instruction used to embed the query.
embed_documents(texts: List[str]) → List[List[float]][source]¶
Embed documents using a Deep Infra... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.deepinfra.DeepInfraEmbeddings.html |
3c2ed997bce1-0 | 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 |
e89c25a860b3-0 | langchain.embeddings.sagemaker_endpoint.EmbeddingsContentHandler¶
class langchain.embeddings.sagemaker_endpoint.EmbeddingsContentHandler[source]¶
Bases: ContentHandlerBase[List[str], List[List[float]]]
Content handler for LLM class.
Methods
__init__()
transform_input(prompt, model_kwargs)
Transforms the input to a form... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.sagemaker_endpoint.EmbeddingsContentHandler.html |
4625e4b73805-0 | langchain.embeddings.cohere.CohereEmbeddings¶
class langchain.embeddings.cohere.CohereEmbeddings(*, client: Any = None, model: str = 'embed-english-v2.0', truncate: Optional[str] = None, cohere_api_key: Optional[str] = None)[source]¶
Bases: BaseModel, Embeddings
Wrapper around Cohere embedding models.
To use, you shoul... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.cohere.CohereEmbeddings.html |
4625e4b73805-1 | model Config[source]¶
Bases: object
Configuration for this pydantic object.
extra = 'forbid'¶ | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.cohere.CohereEmbeddings.html |
d06cbc061dd4-0 | langchain.embeddings.huggingface_hub.HuggingFaceHubEmbeddings¶
class langchain.embeddings.huggingface_hub.HuggingFaceHubEmbeddings(*, client: Any = None, repo_id: str = 'sentence-transformers/all-mpnet-base-v2', task: Optional[str] = 'feature-extraction', model_kwargs: Optional[dict] = None, huggingfacehub_api_token: O... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.huggingface_hub.HuggingFaceHubEmbeddings.html |
d06cbc061dd4-1 | 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 HuggingFaceHub’s embedding endpoint for embedding query text.
Parameters
text – The text to embed.
Returns
Embeddings for the text.
validator validate_environment » a... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.huggingface_hub.HuggingFaceHubEmbeddings.html |
af563e21d1ab-0 | langchain.embeddings.self_hosted_hugging_face.SelfHostedHuggingFaceEmbeddings¶
class langchain.embeddings.self_hosted_hugging_face.SelfHostedHuggingFaceEmbeddings(*, cache: ~typing.Optional[bool] = None, verbose: bool = None, callbacks: ~typing.Optional[~typing.Union[~typing.List[~langchain.callbacks.base.BaseCallbackH... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.self_hosted_hugging_face.SelfHostedHuggingFaceEmbeddings.html |
af563e21d1ab-1 | gpu = rh.cluster(name="rh-a10x", instance_type="A100:1")
hf = SelfHostedHuggingFaceEmbeddings(model_name=model_name, hardware=gpu)
Initialize the remote inference function.
param cache: Optional[bool] = None¶
param callback_manager: Optional[BaseCallbackManager] = None¶
param callbacks: Callbacks = None¶
param hardware... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.self_hosted_hugging_face.SelfHostedHuggingFaceEmbeddings.html |
af563e21d1ab-2 | Check Cache and run the LLM on the given prompt and input.
async agenerate(prompts: List[str], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, **kwargs: Any) → LLMResult¶
Run the LLM on the given prompt and input.
... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.self_hosted_hugging_face.SelfHostedHuggingFaceEmbeddings.html |
af563e21d1ab-3 | Init the SelfHostedPipeline from a pipeline object or string.
generate(prompts: List[str], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, **kwargs: Any) → LLMResult¶
Run the LLM on the given prompt and input.
gene... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.self_hosted_hugging_face.SelfHostedHuggingFaceEmbeddings.html |
af563e21d1ab-4 | This allows users to pass in None as verbose to access the global setting.
to_json() → Union[SerializedConstructor, SerializedNotImplemented]¶
to_json_not_implemented() → SerializedNotImplemented¶
property lc_attributes: Dict¶
Return a list of attribute names that should be included in the
serialized kwargs. These attr... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.self_hosted_hugging_face.SelfHostedHuggingFaceEmbeddings.html |
53a1683709b8-0 | 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 |
2bc26f3a56e2-0 | langchain.embeddings.dashscope.DashScopeEmbeddings¶
class langchain.embeddings.dashscope.DashScopeEmbeddings(*, client: Any = None, model: str = 'text-embedding-v1', dashscope_api_key: Optional[str] = None, max_retries: int = 5)[source]¶
Bases: BaseModel, Embeddings
Wrapper around DashScope embedding models.
To use, yo... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.dashscope.DashScopeEmbeddings.html |
2bc26f3a56e2-1 | specified by the class.
Returns
List of embeddings, one for each text.
embed_query(text: str) → List[float][source]¶
Call out to DashScope’s embedding endpoint for embedding query text.
Parameters
text – The text to embed.
Returns
Embedding for the text.
validator validate_environment » all fields[source]¶
model Conf... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.dashscope.DashScopeEmbeddings.html |
4ef490adb67b-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. | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.google_palm.embed_with_retry.html |
40f14cf60e4a-0 | langchain.embeddings.self_hosted.SelfHostedEmbeddings¶
class langchain.embeddings.self_hosted.SelfHostedEmbeddings(*, cache: ~typing.Optional[bool] = None, verbose: bool = None, callbacks: ~typing.Optional[~typing.Union[~typing.List[~langchain.callbacks.base.BaseCallbackHandler], ~langchain.callbacks.base.BaseCallbackM... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.self_hosted.SelfHostedEmbeddings.html |
40f14cf60e4a-1 | model = AutoModelForCausalLM.from_pretrained(model_id)
return pipeline("feature-extraction", model=model, tokenizer=tokenizer)
embeddings = SelfHostedEmbeddings(
model_load_fn=get_pipeline,
hardware=gpu
model_reqs=["./", "torch", "transformers"],
)
Example passing in a pipeline path:from langchain.embed... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.self_hosted.SelfHostedEmbeddings.html |
40f14cf60e4a-2 | param model_load_fn: Callable [Required]¶
Function to load the model remotely on the server.
param model_reqs: List[str] = ['./', 'torch']¶
Requirements to install on hardware to inference the model.
param tags: Optional[List[str]] = None¶
Tags to add to the run trace.
param verbose: bool [Optional]¶
Whether to print o... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.self_hosted.SelfHostedEmbeddings.html |
40f14cf60e4a-3 | embed_documents(texts: List[str]) → List[List[float]][source]¶
Compute doc embeddings using a HuggingFace transformer model.
Parameters
texts – The list of texts to embed.s
Returns
List of embeddings, one for each text.
embed_query(text: str) → List[float][source]¶
Compute query embeddings using a HuggingFace transform... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.self_hosted.SelfHostedEmbeddings.html |
40f14cf60e4a-4 | Predict text from text.
predict_messages(messages: List[BaseMessage], *, stop: Optional[Sequence[str]] = None, **kwargs: Any) → BaseMessage¶
Predict message from messages.
validator raise_deprecation » all fields¶
Raise deprecation warning if callback_manager is used.
save(file_path: Union[Path, str]) → None¶
Save th... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.self_hosted.SelfHostedEmbeddings.html |
5e01a1a4184b-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 |
783055376292-0 | langchain.embeddings.vertexai.VertexAIEmbeddings¶
class langchain.embeddings.vertexai.VertexAIEmbeddings(*, client: _LanguageModel = None, model_name: str = 'textembedding-gecko', temperature: float = 0.0, max_output_tokens: int = 128, top_p: float = 0.95, top_k: int = 40, stop: Optional[List[str]] = None, project: Opt... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.vertexai.VertexAIEmbeddings.html |
783055376292-1 | param top_p: float = 0.95¶
Tokens are selected from most probable to least until the sum of their
embed_documents(texts: List[str], batch_size: int = 5) → List[List[float]][source]¶
Embed a list of strings. Vertex AI currently
sets a max batch size of 5 strings.
Parameters
texts – List[str] The list of strings to embed... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.vertexai.VertexAIEmbeddings.html |
4f26aa187ddd-0 | langchain.embeddings.minimax.MiniMaxEmbeddings¶
class langchain.embeddings.minimax.MiniMaxEmbeddings(*, endpoint_url: str = 'https://api.minimax.chat/v1/embeddings', model: str = 'embo-01', embed_type_db: str = 'db', embed_type_query: str = 'query', minimax_group_id: Optional[str] = None, minimax_api_key: Optional[str]... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.minimax.MiniMaxEmbeddings.html |
4f26aa187ddd-1 | embed_documents(texts: List[str]) → List[List[float]][source]¶
Embed documents using a MiniMax embedding endpoint.
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 MiniMax embedding endpoint.
Parameters
text... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.minimax.MiniMaxEmbeddings.html |
24d20d3fc89a-0 | langchain.embeddings.openai.OpenAIEmbeddings¶
class langchain.embeddings.openai.OpenAIEmbeddings(*, client: Any = None, model: str = 'text-embedding-ada-002', deployment: str = 'text-embedding-ada-002', openai_api_version: Optional[str] = None, openai_api_base: Optional[str] = None, openai_api_type: Optional[str] = Non... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.openai.OpenAIEmbeddings.html |
24d20d3fc89a-1 | In addition, the deployment name must be passed as the model parameter.
Example
import os
os.environ["OPENAI_API_TYPE"] = "azure"
os.environ["OPENAI_API_BASE"] = "https://<your-endpoint.openai.azure.com/"
os.environ["OPENAI_API_KEY"] = "your AzureOpenAI key"
os.environ["OPENAI_API_VERSION"] = "2023-03-15-preview"
os.en... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.openai.OpenAIEmbeddings.html |
24d20d3fc89a-2 | param openai_api_key: Optional[str] = None¶
param openai_api_type: 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... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.openai.OpenAIEmbeddings.html |
24d20d3fc89a-3 | Parameters
text – The text to embed.
Returns
Embedding for the text.
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.
chunk_size – The chunk size of embeddings. ... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.openai.OpenAIEmbeddings.html |
6ebbe8888dd4-0 | langchain.embeddings.fake.FakeEmbeddings¶
class langchain.embeddings.fake.FakeEmbeddings(*, size: int)[source]¶
Bases: Embeddings, BaseModel
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 size: int [R... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.fake.FakeEmbeddings.html |
fd7c71da2e5f-0 | langchain.embeddings.aleph_alpha.AlephAlphaAsymmetricSemanticEmbedding¶
class langchain.embeddings.aleph_alpha.AlephAlphaAsymmetricSemanticEmbedding(*, client: Any = None, model: Optional[str] = 'luminous-base', hosting: Optional[str] = 'https://api.aleph-alpha.com', normalize: Optional[bool] = True, compress_to_size: ... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.aleph_alpha.AlephAlphaAsymmetricSemanticEmbedding.html |
fd7c71da2e5f-1 | Attention control parameters only apply to those tokens that have
explicitly been set in the request.
param control_log_additive: Optional[bool] = True¶
Apply controls on prompt items by adding the log(control_factor)
to attention scores.
param hosting: Optional[str] = 'https://api.aleph-alpha.com'¶
Optional parameter ... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.aleph_alpha.AlephAlphaAsymmetricSemanticEmbedding.html |
6783bdb18cba-0 | langchain.embeddings.base.Embeddings¶
class langchain.embeddings.base.Embeddings[source]¶
Bases: ABC
Interface for embedding models.
Methods
__init__()
aembed_documents(texts)
Embed search docs.
aembed_query(text)
Embed query text.
embed_documents(texts)
Embed search docs.
embed_query(text)
Embed query text.
async aemb... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.base.Embeddings.html |
2fe1ab792df1-0 | langchain.embeddings.huggingface.HuggingFaceEmbeddings¶
class langchain.embeddings.huggingface.HuggingFaceEmbeddings(*, client: Any = None, model_name: str = 'sentence-transformers/all-mpnet-base-v2', cache_folder: Optional[str] = None, model_kwargs: Dict[str, Any] = None, encode_kwargs: Dict[str, Any] = None)[source]¶... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.huggingface.HuggingFaceEmbeddings.html |
2fe1ab792df1-1 | Compute query embeddings using a HuggingFace transformer model.
Parameters
text – The text to embed.
Returns
Embeddings for the text.
model Config[source]¶
Bases: object
Configuration for this pydantic object.
extra = 'forbid'¶ | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.huggingface.HuggingFaceEmbeddings.html |
2f3d88f9e008-0 | langchain.embeddings.aleph_alpha.AlephAlphaSymmetricSemanticEmbedding¶
class langchain.embeddings.aleph_alpha.AlephAlphaSymmetricSemanticEmbedding(*, client: Any = None, model: Optional[str] = 'luminous-base', hosting: Optional[str] = 'https://api.aleph-alpha.com', normalize: Optional[bool] = True, compress_to_size: Op... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.aleph_alpha.AlephAlphaSymmetricSemanticEmbedding.html |
2f3d88f9e008-1 | param control_log_additive: Optional[bool] = True¶
Apply controls on prompt items by adding the log(control_factor)
to attention scores.
param hosting: Optional[str] = 'https://api.aleph-alpha.com'¶
Optional parameter that specifies which datacenters may process the request.
param model: Optional[str] = 'luminous-base'... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.aleph_alpha.AlephAlphaSymmetricSemanticEmbedding.html |
c57809e677d0-0 | langchain.embeddings.modelscope_hub.ModelScopeEmbeddings¶
class langchain.embeddings.modelscope_hub.ModelScopeEmbeddings(*, embed: Any = None, model_id: str = 'damo/nlp_corom_sentence-embedding_english-base')[source]¶
Bases: BaseModel, Embeddings
Wrapper around modelscope_hub embedding models.
To use, you should have t... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.modelscope_hub.ModelScopeEmbeddings.html |
c6c7bda1ab37-0 | langchain.embeddings.bedrock.BedrockEmbeddings¶
class langchain.embeddings.bedrock.BedrockEmbeddings(*, client: Any = None, region_name: Optional[str] = None, credentials_profile_name: Optional[str] = None, model_id: str = 'amazon.titan-e1t-medium', model_kwargs: Optional[Dict] = None)[source]¶
Bases: BaseModel, Embedd... | https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.bedrock.BedrockEmbeddings.html |
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