id stringlengths 14 15 | text stringlengths 44 2.47k | source stringlengths 61 181 |
|---|---|---|
64fec41a2e50-10 | Bind config to a Runnable, returning a new Runnable.
with_fallbacks(fallbacks: ~typing.Sequence[~langchain.schema.runnable.base.Runnable[~langchain.schema.runnable.utils.Input, ~langchain.schema.runnable.utils.Output]], *, exceptions_to_handle: ~typing.Tuple[~typing.Type[BaseException], ...] = (<class 'Exception'>,)) →... | https://api.python.langchain.com/en/latest/llms/langchain.llms.anyscale.Anyscale.html |
bb7a9c41f91b-0 | langchain.llms.base.LLM¶
class langchain.llms.base.LLM[source]¶
Bases: BaseLLM
Base LLM abstract class.
The purpose of this class is to expose a simpler interface for working
with LLMs, rather than expect the user to implement the full _generate method.
Create a new model by parsing and validating input data from keywo... | https://api.python.langchain.com/en/latest/llms/langchain.llms.base.LLM.html |
bb7a9c41f91b-1 | Subclasses should override this method if they can batch more efficiently.
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[L... | https://api.python.langchain.com/en/latest/llms/langchain.llms.base.LLM.html |
bb7a9c41f91b-2 | functionality, such as logging or streaming, throughout generation.
**kwargs – Arbitrary additional keyword arguments. These are usually passed
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 a... | https://api.python.langchain.com/en/latest/llms/langchain.llms.base.LLM.html |
bb7a9c41f91b-3 | to the model provider API call.
Returns
Top model prediction as a message.
async astream(input: Union[PromptValue, str, List[BaseMessage]], config: Optional[RunnableConfig] = None, *, stop: Optional[List[str]] = None, **kwargs: Any) → AsyncIterator[str]¶
Default implementation of astream, which calls ainvoke.
Subclasse... | https://api.python.langchain.com/en/latest/llms/langchain.llms.base.LLM.html |
bb7a9c41f91b-4 | input is still being generated.
batch(inputs: List[Union[PromptValue, str, List[BaseMessage]]], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, return_exceptions: bool = False, **kwargs: Any) → List[str]¶
Default implementation of batch, which calls invoke N times.
Subclasses should override th... | https://api.python.langchain.com/en/latest/llms/langchain.llms.base.LLM.html |
bb7a9c41f91b-5 | classmethod from_orm(obj: Any) → Model¶
generate(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, metada... | https://api.python.langchain.com/en/latest/llms/langchain.llms.base.LLM.html |
bb7a9c41f91b-6 | functionality, such as logging or streaming, throughout generation.
**kwargs – Arbitrary additional keyword arguments. These are usually passed
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.
classme... | https://api.python.langchain.com/en/latest/llms/langchain.llms.base.LLM.html |
bb7a9c41f91b-7 | classmethod is_lc_serializable() → bool¶
Is this class serializable?
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_defa... | https://api.python.langchain.com/en/latest/llms/langchain.llms.base.LLM.html |
bb7a9c41f91b-8 | Pass a single string input to the model and return a string prediction.
Use this method when passing in raw text. If you want to pass in specifictypes of chat messages, use predict_messages.
Parameters
text – String input to pass to the model.
stop – Stop words to use when generating. Model output is cut off at the
fir... | https://api.python.langchain.com/en/latest/llms/langchain.llms.base.LLM.html |
bb7a9c41f91b-9 | stream(input: Union[PromptValue, str, List[BaseMessage]], config: Optional[RunnableConfig] = None, *, stop: Optional[List[str]] = None, **kwargs: Any) → Iterator[str]¶
Default implementation of stream, which calls invoke.
Subclasses should override this method if they support streaming output.
to_json() → Union[Seriali... | https://api.python.langchain.com/en/latest/llms/langchain.llms.base.LLM.html |
bb7a9c41f91b-10 | property InputType: TypeAlias¶
Get the input type for this runnable.
property OutputType: Type[str]¶
Get the input type for this runnable.
property input_schema: Type[pydantic.main.BaseModel]¶
property lc_attributes: Dict¶
List of attribute names that should be included in the serialized kwargs.
These attributes must b... | https://api.python.langchain.com/en/latest/llms/langchain.llms.base.LLM.html |
698c2898fb8d-0 | langchain.llms.opaqueprompts.OpaquePrompts¶
class langchain.llms.opaqueprompts.OpaquePrompts[source]¶
Bases: LLM
An LLM wrapper that uses OpaquePrompts to sanitize prompts.
Wraps another LLM and sanitizes prompts before passing it to the LLM, thende-sanitizes the response.
To use, you should have the opaqueprompts pyth... | https://api.python.langchain.com/en/latest/llms/langchain.llms.opaqueprompts.OpaquePrompts.html |
698c2898fb8d-1 | 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, *, return_exceptions: bool = False, **kwargs: Any) → List[str]¶
Default implementation of abatch, which calls ainvoke N ... | https://api.python.langchain.com/en/latest/llms/langchain.llms.opaqueprompts.OpaquePrompts.html |
698c2898fb8d-2 | 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/llms/langchain.llms.opaqueprompts.OpaquePrompts.html |
698c2898fb8d-3 | Asynchronously pass messages to the model and return a message prediction.
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 a... | https://api.python.langchain.com/en/latest/llms/langchain.llms.opaqueprompts.OpaquePrompts.html |
698c2898fb8d-4 | The jsonpatch ops can be applied in order to construct state.
async atransform(input: AsyncIterator[Input], config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → AsyncIterator[Output]¶
Default implementation of atransform, which buffers input and calls astream.
Subclasses should override this method if th... | https://api.python.langchain.com/en/latest/llms/langchain.llms.opaqueprompts.OpaquePrompts.html |
698c2898fb8d-5 | 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(**kwargs: Any) → Dict¶
Return a dictionary of the LLM.
classmethod from_orm(obj: Any) → Model¶
generate(prompts: List[str], stop: Optional[List[str]] = None, callbacks: Union[List[BaseCallbackHa... | https://api.python.langchain.com/en/latest/llms/langchain.llms.opaqueprompts.OpaquePrompts.html |
698c2898fb8d-6 | 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 substrings.
callbacks – Callbacks to pass through. Used for executing additional
functionality, such as logging or streaming, throughout generation.
**kwarg... | https://api.python.langchain.com/en/latest/llms/langchain.llms.opaqueprompts.OpaquePrompts.html |
698c2898fb8d-7 | invoke(input: Union[PromptValue, str, List[BaseMessage]], config: Optional[RunnableConfig] = None, *, stop: Optional[List[str]] = None, **kwargs: Any) → str¶
classmethod is_lc_serializable() → bool¶
Is this class serializable?
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Option... | https://api.python.langchain.com/en/latest/llms/langchain.llms.opaqueprompts.OpaquePrompts.html |
698c2898fb8d-8 | predict(text: str, *, stop: Optional[Sequence[str]] = None, **kwargs: Any) → str¶
Pass a single string input to the model and return a string prediction.
Use this method when passing in raw text. If you want to pass in specifictypes of chat messages, use predict_messages.
Parameters
text – String input to pass to the m... | https://api.python.langchain.com/en/latest/llms/langchain.llms.opaqueprompts.OpaquePrompts.html |
698c2898fb8d-9 | stream(input: Union[PromptValue, str, List[BaseMessage]], config: Optional[RunnableConfig] = None, *, stop: Optional[List[str]] = None, **kwargs: Any) → Iterator[str]¶
Default implementation of stream, which calls invoke.
Subclasses should override this method if they support streaming output.
to_json() → Union[Seriali... | https://api.python.langchain.com/en/latest/llms/langchain.llms.opaqueprompts.OpaquePrompts.html |
698c2898fb8d-10 | property InputType: TypeAlias¶
Get the input type for this runnable.
property OutputType: Type[str]¶
Get the input type for this runnable.
property input_schema: Type[pydantic.main.BaseModel]¶
property lc_attributes: Dict¶
List of attribute names that should be included in the serialized kwargs.
These attributes must b... | https://api.python.langchain.com/en/latest/llms/langchain.llms.opaqueprompts.OpaquePrompts.html |
9d0fa44e15e4-0 | langchain.llms.databricks.get_default_host¶
langchain.llms.databricks.get_default_host() → str[source]¶
Gets the default Databricks workspace hostname.
Raises an error if the hostname cannot be automatically determined. | https://api.python.langchain.com/en/latest/llms/langchain.llms.databricks.get_default_host.html |
455815e4ee08-0 | langchain.llms.vertexai.VertexAI¶
class langchain.llms.vertexai.VertexAI[source]¶
Bases: _VertexAICommon, BaseLLM
Google Vertex AI large language 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... | https://api.python.langchain.com/en/latest/llms/langchain.llms.vertexai.VertexAI.html |
455815e4ee08-1 | How the model selects tokens for output, the next token is selected from
param top_p: float = 0.95¶
Tokens are selected from most probable to least until the sum of their
param tuned_model_name: Optional[str] = None¶
The name of a tuned model. If provided, model_name is ignored.
param verbose: bool [Optional]¶
Whether ... | https://api.python.langchain.com/en/latest/llms/langchain.llms.vertexai.VertexAI.html |
455815e4ee08-2 | Run the LLM on the given prompt and input.
async agenerate_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¶
Asynchronously... | https://api.python.langchain.com/en/latest/llms/langchain.llms.vertexai.VertexAI.html |
455815e4ee08-3 | Subclasses should override this method if they can run asynchronously.
async apredict(text: str, *, stop: Optional[Sequence[str]] = None, **kwargs: Any) → str¶
Asynchronously pass a string to the model and return a string prediction.
Use this method when calling pure text generation models and only the topcandidate gen... | https://api.python.langchain.com/en/latest/llms/langchain.llms.vertexai.VertexAI.html |
455815e4ee08-4 | Subclasses should override this method if they support streaming output.
async astream_log(input: Any, config: Optional[RunnableConfig] = None, *, include_names: Optional[Sequence[str]] = None, include_types: Optional[Sequence[str]] = None, include_tags: Optional[Sequence[str]] = None, exclude_names: Optional[Sequence[... | https://api.python.langchain.com/en/latest/llms/langchain.llms.vertexai.VertexAI.html |
455815e4ee08-5 | Bind arguments to a Runnable, returning a new Runnable.
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... | https://api.python.langchain.com/en/latest/llms/langchain.llms.vertexai.VertexAI.html |
455815e4ee08-6 | 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/llms/langchain.llms.vertexai.VertexAI.html |
455815e4ee08-7 | Get the number of tokens present in the text.
Useful for checking if an input will fit in a model’s context window.
Parameters
text – The string input to tokenize.
Returns
The integer number of tokens in the text.
get_num_tokens_from_messages(messages: List[BaseMessage]) → int¶
Get the number of tokens in the messages.... | https://api.python.langchain.com/en/latest/llms/langchain.llms.vertexai.VertexAI.html |
455815e4ee08-8 | classmethod lc_id() → List[str]¶
A unique identifier for this class for serialization purposes.
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 e... | https://api.python.langchain.com/en/latest/llms/langchain.llms.vertexai.VertexAI.html |
455815e4ee08-9 | 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 additional keyword arguments. These are usually passed
to the model provider API call.
Retur... | https://api.python.langchain.com/en/latest/llms/langchain.llms.vertexai.VertexAI.html |
455815e4ee08-10 | classmethod validate(value: Any) → Model¶
with_config(config: Optional[RunnableConfig] = None, **kwargs: Any) → Runnable[Input, Output]¶
Bind config to a Runnable, returning a new Runnable.
with_fallbacks(fallbacks: ~typing.Sequence[~langchain.schema.runnable.base.Runnable[~langchain.schema.runnable.utils.Input, ~langc... | https://api.python.langchain.com/en/latest/llms/langchain.llms.vertexai.VertexAI.html |
0348732cb5d6-0 | langchain.llms.databricks.Databricks¶
class langchain.llms.databricks.Databricks[source]¶
Bases: LLM
Databricks serving endpoint or a cluster driver proxy app for LLM.
It supports two endpoint types:
Serving endpoint (recommended for both production and development).
We assume that an LLM was registered and deployed to... | https://api.python.langchain.com/en/latest/llms/langchain.llms.databricks.Databricks.html |
0348732cb5d6-1 | If the endpoint model signature is different or you want to set extra params,
you can use transform_input_fn and transform_output_fn to apply necessary
transformations before and after the query.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data can... | https://api.python.langchain.com/en/latest/llms/langchain.llms.databricks.Databricks.html |
0348732cb5d6-2 | param host: str [Optional]¶
Databricks workspace hostname.
If not provided, the default value is determined by
the DATABRICKS_HOST environment variable if present, or
the hostname of the current Databricks workspace if running inside
a Databricks notebook attached to an interactive cluster in “single user”
or “no isola... | https://api.python.langchain.com/en/latest/llms/langchain.llms.databricks.Databricks.html |
0348732cb5d6-3 | Default implementation of abatch, which calls ainvoke N times.
Subclasses should override this method if they can batch more efficiently.
async agenerate(prompts: List[str], stop: Optional[List[str]] = None, callbacks: Union[List[BaseCallbackHandler], BaseCallbackManager, None, List[Optional[Union[List[BaseCallbackHand... | https://api.python.langchain.com/en/latest/llms/langchain.llms.databricks.Databricks.html |
0348732cb5d6-4 | callbacks – Callbacks to pass through. Used for executing additional
functionality, such as logging or streaming, throughout generation.
**kwargs – Arbitrary additional keyword arguments. These are usually passed
to the model provider API call.
Returns
An LLMResult, which contains a list of candidate Generations for ea... | https://api.python.langchain.com/en/latest/llms/langchain.llms.databricks.Databricks.html |
0348732cb5d6-5 | **kwargs – Arbitrary additional keyword arguments. These are usually passed
to the model provider API call.
Returns
Top model prediction as a message.
async astream(input: Union[PromptValue, str, List[BaseMessage]], config: Optional[RunnableConfig] = None, *, stop: Optional[List[str]] = None, **kwargs: Any) → AsyncIter... | https://api.python.langchain.com/en/latest/llms/langchain.llms.databricks.Databricks.html |
0348732cb5d6-6 | input is still being generated.
batch(inputs: List[Union[PromptValue, str, List[BaseMessage]]], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, return_exceptions: bool = False, **kwargs: Any) → List[str]¶
Default implementation of batch, which calls invoke N times.
Subclasses should override th... | https://api.python.langchain.com/en/latest/llms/langchain.llms.databricks.Databricks.html |
0348732cb5d6-7 | classmethod from_orm(obj: Any) → Model¶
generate(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, metada... | https://api.python.langchain.com/en/latest/llms/langchain.llms.databricks.Databricks.html |
0348732cb5d6-8 | functionality, such as logging or streaming, throughout generation.
**kwargs – Arbitrary additional keyword arguments. These are usually passed
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.
classme... | https://api.python.langchain.com/en/latest/llms/langchain.llms.databricks.Databricks.html |
0348732cb5d6-9 | classmethod is_lc_serializable() → bool¶
Is this class serializable?
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_defa... | https://api.python.langchain.com/en/latest/llms/langchain.llms.databricks.Databricks.html |
0348732cb5d6-10 | Pass a single string input to the model and return a string prediction.
Use this method when passing in raw text. If you want to pass in specifictypes of chat messages, use predict_messages.
Parameters
text – String input to pass to the model.
stop – Stop words to use when generating. Model output is cut off at the
fir... | https://api.python.langchain.com/en/latest/llms/langchain.llms.databricks.Databricks.html |
0348732cb5d6-11 | stream(input: Union[PromptValue, str, List[BaseMessage]], config: Optional[RunnableConfig] = None, *, stop: Optional[List[str]] = None, **kwargs: Any) → Iterator[str]¶
Default implementation of stream, which calls invoke.
Subclasses should override this method if they support streaming output.
to_json() → Union[Seriali... | https://api.python.langchain.com/en/latest/llms/langchain.llms.databricks.Databricks.html |
0348732cb5d6-12 | property InputType: TypeAlias¶
Get the input type for this runnable.
property OutputType: Type[str]¶
Get the input type for this runnable.
property input_schema: Type[pydantic.main.BaseModel]¶
property lc_attributes: Dict¶
List of attribute names that should be included in the serialized kwargs.
These attributes must b... | https://api.python.langchain.com/en/latest/llms/langchain.llms.databricks.Databricks.html |
b145f1bc9e91-0 | langchain.llms.openllm.OpenLLM¶
class langchain.llms.openllm.OpenLLM[source]¶
Bases: LLM
OpenLLM, supporting both in-process model
instance and remote OpenLLM servers.
To use, you should have the openllm library installed:
pip install openllm
Learn more at: https://github.com/bentoml/openllm
Example running an LLM mode... | https://api.python.langchain.com/en/latest/llms/langchain.llms.openllm.OpenLLM.html |
b145f1bc9e91-1 | Metadata to add to the run trace.
param model_id: Optional[str] = None¶
Model Id to use. If not provided, will use the default model for the model name.
See ‘openllm models’ for all available model variants.
param model_name: Optional[str] = None¶
Model name to use. See ‘openllm models’ for all available models.
param ... | https://api.python.langchain.com/en/latest/llms/langchain.llms.openllm.OpenLLM.html |
b145f1bc9e91-2 | Subclasses should override this method if they can batch more efficiently.
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[L... | https://api.python.langchain.com/en/latest/llms/langchain.llms.openllm.OpenLLM.html |
b145f1bc9e91-3 | functionality, such as logging or streaming, throughout generation.
**kwargs – Arbitrary additional keyword arguments. These are usually passed
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 a... | https://api.python.langchain.com/en/latest/llms/langchain.llms.openllm.OpenLLM.html |
b145f1bc9e91-4 | to the model provider API call.
Returns
Top model prediction as a message.
async astream(input: Union[PromptValue, str, List[BaseMessage]], config: Optional[RunnableConfig] = None, *, stop: Optional[List[str]] = None, **kwargs: Any) → AsyncIterator[str]¶
Default implementation of astream, which calls ainvoke.
Subclasse... | https://api.python.langchain.com/en/latest/llms/langchain.llms.openllm.OpenLLM.html |
b145f1bc9e91-5 | input is still being generated.
batch(inputs: List[Union[PromptValue, str, List[BaseMessage]]], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, return_exceptions: bool = False, **kwargs: Any) → List[str]¶
Default implementation of batch, which calls invoke N times.
Subclasses should override th... | https://api.python.langchain.com/en/latest/llms/langchain.llms.openllm.OpenLLM.html |
b145f1bc9e91-6 | classmethod from_orm(obj: Any) → Model¶
generate(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, metada... | https://api.python.langchain.com/en/latest/llms/langchain.llms.openllm.OpenLLM.html |
b145f1bc9e91-7 | functionality, such as logging or streaming, throughout generation.
**kwargs – Arbitrary additional keyword arguments. These are usually passed
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.
classme... | https://api.python.langchain.com/en/latest/llms/langchain.llms.openllm.OpenLLM.html |
b145f1bc9e91-8 | classmethod is_lc_serializable() → bool¶
Is this class serializable?
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_defa... | https://api.python.langchain.com/en/latest/llms/langchain.llms.openllm.OpenLLM.html |
b145f1bc9e91-9 | Pass a single string input to the model and return a string prediction.
Use this method when passing in raw text. If you want to pass in specifictypes of chat messages, use predict_messages.
Parameters
text – String input to pass to the model.
stop – Stop words to use when generating. Model output is cut off at the
fir... | https://api.python.langchain.com/en/latest/llms/langchain.llms.openllm.OpenLLM.html |
b145f1bc9e91-10 | stream(input: Union[PromptValue, str, List[BaseMessage]], config: Optional[RunnableConfig] = None, *, stop: Optional[List[str]] = None, **kwargs: Any) → Iterator[str]¶
Default implementation of stream, which calls invoke.
Subclasses should override this method if they support streaming output.
to_json() → Union[Seriali... | https://api.python.langchain.com/en/latest/llms/langchain.llms.openllm.OpenLLM.html |
b145f1bc9e91-11 | property InputType: TypeAlias¶
Get the input type for this runnable.
property OutputType: Type[str]¶
Get the input type for this runnable.
property input_schema: Type[pydantic.main.BaseModel]¶
property lc_attributes: Dict¶
List of attribute names that should be included in the serialized kwargs.
These attributes must b... | https://api.python.langchain.com/en/latest/llms/langchain.llms.openllm.OpenLLM.html |
98ca42a47b59-0 | langchain.llms.octoai_endpoint.OctoAIEndpoint¶
class langchain.llms.octoai_endpoint.OctoAIEndpoint[source]¶
Bases: LLM
OctoAI LLM Endpoints.
OctoAIEndpoint is a class to interact with OctoAICompute Service large language model endpoints.
To use, you should have the octoai python package installed, and the
environment v... | https://api.python.langchain.com/en/latest/llms/langchain.llms.octoai_endpoint.OctoAIEndpoint.html |
98ca42a47b59-1 | OCTOAI API Token
param tags: Optional[List[str]] = None¶
Tags to add to the run trace.
param verbose: bool [Optional]¶
Whether to print out response text.
__call__(prompt: str, stop: Optional[List[str]] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, *, tags: Optional[List[str... | https://api.python.langchain.com/en/latest/llms/langchain.llms.octoai_endpoint.OctoAIEndpoint.html |
98ca42a47b59-2 | Run the LLM on the given prompt and input.
async agenerate_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¶
Asynchronously... | https://api.python.langchain.com/en/latest/llms/langchain.llms.octoai_endpoint.OctoAIEndpoint.html |
98ca42a47b59-3 | Subclasses should override this method if they can run asynchronously.
async apredict(text: str, *, stop: Optional[Sequence[str]] = None, **kwargs: Any) → str¶
Asynchronously pass a string to the model and return a string prediction.
Use this method when calling pure text generation models and only the topcandidate gen... | https://api.python.langchain.com/en/latest/llms/langchain.llms.octoai_endpoint.OctoAIEndpoint.html |
98ca42a47b59-4 | Subclasses should override this method if they support streaming output.
async astream_log(input: Any, config: Optional[RunnableConfig] = None, *, include_names: Optional[Sequence[str]] = None, include_types: Optional[Sequence[str]] = None, include_tags: Optional[Sequence[str]] = None, exclude_names: Optional[Sequence[... | https://api.python.langchain.com/en/latest/llms/langchain.llms.octoai_endpoint.OctoAIEndpoint.html |
98ca42a47b59-5 | Bind arguments to a Runnable, returning a new Runnable.
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... | https://api.python.langchain.com/en/latest/llms/langchain.llms.octoai_endpoint.OctoAIEndpoint.html |
98ca42a47b59-6 | 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/llms/langchain.llms.octoai_endpoint.OctoAIEndpoint.html |
98ca42a47b59-7 | Get the number of tokens present in the text.
Useful for checking if an input will fit in a model’s context window.
Parameters
text – The string input to tokenize.
Returns
The integer number of tokens in the text.
get_num_tokens_from_messages(messages: List[BaseMessage]) → int¶
Get the number of tokens in the messages.... | https://api.python.langchain.com/en/latest/llms/langchain.llms.octoai_endpoint.OctoAIEndpoint.html |
98ca42a47b59-8 | classmethod lc_id() → List[str]¶
A unique identifier for this class for serialization purposes.
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 e... | https://api.python.langchain.com/en/latest/llms/langchain.llms.octoai_endpoint.OctoAIEndpoint.html |
98ca42a47b59-9 | 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 additional keyword arguments. These are usually passed
to the model provider API call.
Retur... | https://api.python.langchain.com/en/latest/llms/langchain.llms.octoai_endpoint.OctoAIEndpoint.html |
98ca42a47b59-10 | classmethod validate(value: Any) → Model¶
with_config(config: Optional[RunnableConfig] = None, **kwargs: Any) → Runnable[Input, Output]¶
Bind config to a Runnable, returning a new Runnable.
with_fallbacks(fallbacks: ~typing.Sequence[~langchain.schema.runnable.base.Runnable[~langchain.schema.runnable.utils.Input, ~langc... | https://api.python.langchain.com/en/latest/llms/langchain.llms.octoai_endpoint.OctoAIEndpoint.html |
6733d7e19987-0 | langchain.llms.huggingface_pipeline.HuggingFacePipeline¶
class langchain.llms.huggingface_pipeline.HuggingFacePipeline[source]¶
Bases: BaseLLM
HuggingFace Pipeline API.
To use, you should have the transformers python package installed.
Only supports text-generation, text2text-generation and summarization for now.
Examp... | https://api.python.langchain.com/en/latest/llms/langchain.llms.huggingface_pipeline.HuggingFacePipeline.html |
6733d7e19987-1 | param pipeline_kwargs: Optional[dict] = None¶
Key word arguments passed to the pipeline.
param tags: Optional[List[str]] = None¶
Tags to add to the run trace.
param verbose: bool [Optional]¶
Whether to print out response text.
__call__(prompt: str, stop: Optional[List[str]] = None, callbacks: Optional[Union[List[BaseCa... | https://api.python.langchain.com/en/latest/llms/langchain.llms.huggingface_pipeline.HuggingFacePipeline.html |
6733d7e19987-2 | Run the LLM on the given prompt and input.
async agenerate_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¶
Asynchronously... | https://api.python.langchain.com/en/latest/llms/langchain.llms.huggingface_pipeline.HuggingFacePipeline.html |
6733d7e19987-3 | Subclasses should override this method if they can run asynchronously.
async apredict(text: str, *, stop: Optional[Sequence[str]] = None, **kwargs: Any) → str¶
Asynchronously pass a string to the model and return a string prediction.
Use this method when calling pure text generation models and only the topcandidate gen... | https://api.python.langchain.com/en/latest/llms/langchain.llms.huggingface_pipeline.HuggingFacePipeline.html |
6733d7e19987-4 | Subclasses should override this method if they support streaming output.
async astream_log(input: Any, config: Optional[RunnableConfig] = None, *, include_names: Optional[Sequence[str]] = None, include_types: Optional[Sequence[str]] = None, include_tags: Optional[Sequence[str]] = None, exclude_names: Optional[Sequence[... | https://api.python.langchain.com/en/latest/llms/langchain.llms.huggingface_pipeline.HuggingFacePipeline.html |
6733d7e19987-5 | Bind arguments to a Runnable, returning a new Runnable.
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... | https://api.python.langchain.com/en/latest/llms/langchain.llms.huggingface_pipeline.HuggingFacePipeline.html |
6733d7e19987-6 | classmethod from_orm(obj: Any) → Model¶
generate(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, metada... | https://api.python.langchain.com/en/latest/llms/langchain.llms.huggingface_pipeline.HuggingFacePipeline.html |
6733d7e19987-7 | functionality, such as logging or streaming, throughout generation.
**kwargs – Arbitrary additional keyword arguments. These are usually passed
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.
classme... | https://api.python.langchain.com/en/latest/llms/langchain.llms.huggingface_pipeline.HuggingFacePipeline.html |
6733d7e19987-8 | classmethod is_lc_serializable() → bool¶
Is this class serializable?
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_defa... | https://api.python.langchain.com/en/latest/llms/langchain.llms.huggingface_pipeline.HuggingFacePipeline.html |
6733d7e19987-9 | Pass a single string input to the model and return a string prediction.
Use this method when passing in raw text. If you want to pass in specifictypes of chat messages, use predict_messages.
Parameters
text – String input to pass to the model.
stop – Stop words to use when generating. Model output is cut off at the
fir... | https://api.python.langchain.com/en/latest/llms/langchain.llms.huggingface_pipeline.HuggingFacePipeline.html |
6733d7e19987-10 | stream(input: Union[PromptValue, str, List[BaseMessage]], config: Optional[RunnableConfig] = None, *, stop: Optional[List[str]] = None, **kwargs: Any) → Iterator[str]¶
Default implementation of stream, which calls invoke.
Subclasses should override this method if they support streaming output.
to_json() → Union[Seriali... | https://api.python.langchain.com/en/latest/llms/langchain.llms.huggingface_pipeline.HuggingFacePipeline.html |
6733d7e19987-11 | property InputType: TypeAlias¶
Get the input type for this runnable.
property OutputType: Type[str]¶
Get the input type for this runnable.
property input_schema: Type[pydantic.main.BaseModel]¶
property lc_attributes: Dict¶
List of attribute names that should be included in the serialized kwargs.
These attributes must b... | https://api.python.langchain.com/en/latest/llms/langchain.llms.huggingface_pipeline.HuggingFacePipeline.html |
8415d0be6382-0 | langchain.llms.bedrock.BedrockBase¶
class langchain.llms.bedrock.BedrockBase[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.
param credentials_profile_name: Optional[str] = Non... | https://api.python.langchain.com/en/latest/llms/langchain.llms.bedrock.BedrockBase.html |
8415d0be6382-1 | 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/llms/langchain.llms.bedrock.BedrockBase.html |
8415d0be6382-2 | 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 = False, exclude_n... | https://api.python.langchain.com/en/latest/llms/langchain.llms.bedrock.BedrockBase.html |
c36dd7652e7a-0 | langchain.llms.gradient_ai.GradientLLM¶
class langchain.llms.gradient_ai.GradientLLM[source]¶
Bases: LLM
Gradient.ai LLM Endpoints.
GradientLLM is a class to interact with LLMs on gradient.ai
To use, set the environment variable GRADIENT_ACCESS_TOKEN with your
API token and GRADIENT_WORKSPACE_ID for your gradient works... | https://api.python.langchain.com/en/latest/llms/langchain.llms.gradient_ai.GradientLLM.html |
c36dd7652e7a-1 | param gradient_workspace_id: Optional[str] = None¶
Underlying gradient.ai workspace_id.
param metadata: Optional[Dict[str, Any]] = None¶
Metadata to add to the run trace.
param model_id: str [Required]¶
Underlying gradient.ai model id (base or fine-tuned).
param model_kwargs: Optional[dict] = None¶
Key word arguments t... | https://api.python.langchain.com/en/latest/llms/langchain.llms.gradient_ai.GradientLLM.html |
c36dd7652e7a-2 | Subclasses should override this method if they can batch more efficiently.
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[L... | https://api.python.langchain.com/en/latest/llms/langchain.llms.gradient_ai.GradientLLM.html |
c36dd7652e7a-3 | functionality, such as logging or streaming, throughout generation.
**kwargs – Arbitrary additional keyword arguments. These are usually passed
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 a... | https://api.python.langchain.com/en/latest/llms/langchain.llms.gradient_ai.GradientLLM.html |
c36dd7652e7a-4 | to the model provider API call.
Returns
Top model prediction as a message.
async astream(input: Union[PromptValue, str, List[BaseMessage]], config: Optional[RunnableConfig] = None, *, stop: Optional[List[str]] = None, **kwargs: Any) → AsyncIterator[str]¶
Default implementation of astream, which calls ainvoke.
Subclasse... | https://api.python.langchain.com/en/latest/llms/langchain.llms.gradient_ai.GradientLLM.html |
c36dd7652e7a-5 | input is still being generated.
batch(inputs: List[Union[PromptValue, str, List[BaseMessage]]], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, return_exceptions: bool = False, **kwargs: Any) → List[str]¶
Default implementation of batch, which calls invoke N times.
Subclasses should override th... | https://api.python.langchain.com/en/latest/llms/langchain.llms.gradient_ai.GradientLLM.html |
c36dd7652e7a-6 | classmethod from_orm(obj: Any) → Model¶
generate(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, metada... | https://api.python.langchain.com/en/latest/llms/langchain.llms.gradient_ai.GradientLLM.html |
c36dd7652e7a-7 | functionality, such as logging or streaming, throughout generation.
**kwargs – Arbitrary additional keyword arguments. These are usually passed
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.
classme... | https://api.python.langchain.com/en/latest/llms/langchain.llms.gradient_ai.GradientLLM.html |
c36dd7652e7a-8 | classmethod is_lc_serializable() → bool¶
Is this class serializable?
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_defa... | https://api.python.langchain.com/en/latest/llms/langchain.llms.gradient_ai.GradientLLM.html |
c36dd7652e7a-9 | Pass a single string input to the model and return a string prediction.
Use this method when passing in raw text. If you want to pass in specifictypes of chat messages, use predict_messages.
Parameters
text – String input to pass to the model.
stop – Stop words to use when generating. Model output is cut off at the
fir... | https://api.python.langchain.com/en/latest/llms/langchain.llms.gradient_ai.GradientLLM.html |
c36dd7652e7a-10 | stream(input: Union[PromptValue, str, List[BaseMessage]], config: Optional[RunnableConfig] = None, *, stop: Optional[List[str]] = None, **kwargs: Any) → Iterator[str]¶
Default implementation of stream, which calls invoke.
Subclasses should override this method if they support streaming output.
to_json() → Union[Seriali... | https://api.python.langchain.com/en/latest/llms/langchain.llms.gradient_ai.GradientLLM.html |
c36dd7652e7a-11 | property InputType: TypeAlias¶
Get the input type for this runnable.
property OutputType: Type[str]¶
Get the input type for this runnable.
property input_schema: Type[pydantic.main.BaseModel]¶
property lc_attributes: Dict¶
List of attribute names that should be included in the serialized kwargs.
These attributes must b... | https://api.python.langchain.com/en/latest/llms/langchain.llms.gradient_ai.GradientLLM.html |
43fcb9cc9f9c-0 | langchain.llms.vertexai.VertexAIModelGarden¶
class langchain.llms.vertexai.VertexAIModelGarden[source]¶
Bases: _VertexAIBase, BaseLLM
Large language models served from Vertex AI Model Garden.
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/llms/langchain.llms.vertexai.VertexAIModelGarden.html |
43fcb9cc9f9c-1 | param verbose: bool [Optional]¶
Whether to print out response text.
__call__(prompt: str, stop: Optional[List[str]] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, **kwargs: Any) → str¶
Check Cache... | https://api.python.langchain.com/en/latest/llms/langchain.llms.vertexai.VertexAIModelGarden.html |
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