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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
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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
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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