id stringlengths 14 16 | text stringlengths 13 2.7k | source stringlengths 57 178 |
|---|---|---|
f5a4e85b7022-11 | 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... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.cerebriumai.CerebriumAI.html |
f5a4e85b7022-12 | fallback in order, upon failures.
with_listeners(*, on_start: Optional[Listener] = None, on_end: Optional[Listener] = None, on_error: Optional[Listener] = None) → Runnable[Input, Output]¶
Bind lifecycle listeners to a Runnable, returning a new Runnable.
on_start: Called before the runnable starts running, with the Run ... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.cerebriumai.CerebriumAI.html |
f5a4e85b7022-13 | property config_specs: List[langchain.schema.runnable.utils.ConfigurableFieldSpec]¶
List configurable fields for this runnable.
property input_schema: Type[pydantic.main.BaseModel]¶
The type of input this runnable accepts specified as a pydantic model.
property lc_attributes: Dict¶
List of attribute names that should b... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.cerebriumai.CerebriumAI.html |
b9729ea03a1c-0 | langchain_experimental.llms.rellm_decoder.RELLM¶
class langchain_experimental.llms.rellm_decoder.RELLM[source]¶
Bases: HuggingFacePipeline
RELLM wrapped LLM using HuggingFace Pipeline API.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be ... | lang/api.python.langchain.com/en/latest/llms/langchain_experimental.llms.rellm_decoder.RELLM.html |
b9729ea03a1c-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 runs ainvoke in parallel using as... | lang/api.python.langchain.com/en/latest/llms/langchain_experimental.llms.rellm_decoder.RELLM.html |
b9729ea03a1c-2 | need more output from the model than just the top generated value,
are building chains that are agnostic to the underlying language modeltype (e.g., pure text completion models vs chat models).
Parameters
prompts – List of PromptValues. A PromptValue is an object that can be
converted to match the format of any languag... | lang/api.python.langchain.com/en/latest/llms/langchain_experimental.llms.rellm_decoder.RELLM.html |
b9729ea03a1c-3 | **kwargs – Arbitrary additional keyword arguments. These are usually passed
to the model provider API call.
Returns
Top model prediction as a string.
async apredict_messages(messages: List[BaseMessage], *, stop: Optional[Sequence[str]] = None, **kwargs: Any) → BaseMessage¶
Asynchronously pass messages to the model and ... | lang/api.python.langchain.com/en/latest/llms/langchain_experimental.llms.rellm_decoder.RELLM.html |
b9729ea03a1c-4 | This includes all inner runs of LLMs, Retrievers, Tools, etc.
Output is streamed as Log objects, which include a list of
jsonpatch ops that describe how the state of the run has changed in each
step, and the final state of the run.
The jsonpatch ops can be applied in order to construct state.
async atransform(input: As... | lang/api.python.langchain.com/en/latest/llms/langchain_experimental.llms.rellm_decoder.RELLM.html |
b9729ea03a1c-5 | Returns
A pydantic model that can be used to validate config.
configurable_alternatives(which: ConfigurableField, default_key: str = 'default', **kwargs: Union[Runnable[Input, Output], Callable[[], Runnable[Input, Output]]]) → RunnableSerializable[Input, Output]¶
configurable_fields(**kwargs: Union[ConfigurableField, C... | lang/api.python.langchain.com/en/latest/llms/langchain_experimental.llms.rellm_decoder.RELLM.html |
b9729ea03a1c-6 | dict(**kwargs: Any) → Dict¶
Return a dictionary of the LLM.
classmethod from_model_id(model_id: str, task: str, device: Optional[int] = - 1, device_map: Optional[str] = None, model_kwargs: Optional[dict] = None, pipeline_kwargs: Optional[dict] = None, batch_size: int = 4, **kwargs: Any) → HuggingFacePipeline¶
Construct... | lang/api.python.langchain.com/en/latest/llms/langchain_experimental.llms.rellm_decoder.RELLM.html |
b9729ea03a1c-7 | 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... | lang/api.python.langchain.com/en/latest/llms/langchain_experimental.llms.rellm_decoder.RELLM.html |
b9729ea03a1c-8 | get_num_tokens_from_messages(messages: List[BaseMessage]) → int¶
Get the number of tokens in the messages.
Useful for checking if an input will fit in a model’s context window.
Parameters
messages – The message inputs to tokenize.
Returns
The sum of the number of tokens across the messages.
get_output_schema(config: Op... | lang/api.python.langchain.com/en/latest/llms/langchain_experimental.llms.rellm_decoder.RELLM.html |
b9729ea03a1c-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... | lang/api.python.langchain.com/en/latest/llms/langchain_experimental.llms.rellm_decoder.RELLM.html |
b9729ea03a1c-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... | lang/api.python.langchain.com/en/latest/llms/langchain_experimental.llms.rellm_decoder.RELLM.html |
b9729ea03a1c-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... | lang/api.python.langchain.com/en/latest/llms/langchain_experimental.llms.rellm_decoder.RELLM.html |
b9729ea03a1c-12 | fallback in order, upon failures.
with_listeners(*, on_start: Optional[Listener] = None, on_end: Optional[Listener] = None, on_error: Optional[Listener] = None) → Runnable[Input, Output]¶
Bind lifecycle listeners to a Runnable, returning a new Runnable.
on_start: Called before the runnable starts running, with the Run ... | lang/api.python.langchain.com/en/latest/llms/langchain_experimental.llms.rellm_decoder.RELLM.html |
b9729ea03a1c-13 | property config_specs: List[langchain.schema.runnable.utils.ConfigurableFieldSpec]¶
List configurable fields for this runnable.
property input_schema: Type[pydantic.main.BaseModel]¶
The type of input this runnable accepts specified as a pydantic model.
property lc_attributes: Dict¶
List of attribute names that should b... | lang/api.python.langchain.com/en/latest/llms/langchain_experimental.llms.rellm_decoder.RELLM.html |
aa13693b6f7c-0 | langchain.llms.anyscale.update_token_usage¶
langchain.llms.anyscale.update_token_usage(keys: Set[str], response: Dict[str, Any], token_usage: Dict[str, Any]) → None[source]¶
Update token usage. | lang/api.python.langchain.com/en/latest/llms/langchain.llms.anyscale.update_token_usage.html |
b473f29c745f-0 | langchain.llms.gigachat.GigaChat¶
class langchain.llms.gigachat.GigaChat[source]¶
Bases: _BaseGigaChat, BaseLLM
GigaChat large language models API.
To use, you should pass login and password to access GigaChat API or use token.
Example
from langchain.llms import GigaChat
giga = GigaChat(credentials=..., verify_ssl_cert... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.gigachat.GigaChat.html |
b473f29c745f-1 | Whether to stream the results or not.
param tags: Optional[List[str]] = None¶
Tags to add to the run trace.
param temperature: Optional[float] = None¶
What sampling temperature to use.
param timeout: Optional[float] = None¶
Timeout for request
param user: Optional[str] = None¶
Username for authenticate
param verbose: b... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.gigachat.GigaChat.html |
b473f29c745f-2 | e.g., if the underlying runnable uses an API which supports a batch mode.
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[Li... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.gigachat.GigaChat.html |
b473f29c745f-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... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.gigachat.GigaChat.html |
b473f29c745f-4 | first occurrence of any of these substrings.
**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[... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.gigachat.GigaChat.html |
b473f29c745f-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 runs invoke in parallel using a thread pool executor.
The default i... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.gigachat.GigaChat.html |
b473f29c745f-6 | Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model¶
Duplicate a model, optionally... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.gigachat.GigaChat.html |
b473f29c745f-7 | Pass a sequence of prompts to the model and return model generations.
This method should make use of batched calls for models that expose a batched
API.
Use this method when you want to:
take advantage of batched calls,
need more output from the model than just the top generated value,
are building chains that are agno... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.gigachat.GigaChat.html |
b473f29c745f-8 | For example, if the class is langchain.llms.openai.OpenAI, then the
namespace is [“langchain”, “llms”, “openai”]
get_num_tokens(text: str) → int[source]¶
Count approximate number of tokens
get_num_tokens_from_messages(messages: List[BaseMessage]) → int¶
Get the number of tokens in the messages.
Useful for checking if a... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.gigachat.GigaChat.html |
b473f29c745f-9 | The config supports standard keys like ‘tags’, ‘metadata’ for tracing
purposes, ‘max_concurrency’ for controlling how much work to do
in parallel, and other keys. Please refer to the RunnableConfig
for more details.
Returns
The output of the runnable.
classmethod is_lc_serializable() → bool¶
Is this class serializable?... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.gigachat.GigaChat.html |
b473f29c745f-10 | classmethod parse_obj(obj: Any) → Model¶
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
predict(text: str, *, stop: Optional[Sequence[str]] = None, **kwargs: Any) → str¶
Pass a single string input to t... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.gigachat.GigaChat.html |
b473f29c745f-11 | .. code-block:: python
llm.save(file_path=”path/llm.yaml”)
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶
classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
stream(input: Union[Promp... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.gigachat.GigaChat.html |
b473f29c745f-12 | Add fallbacks to a runnable, returning a new Runnable.
Parameters
fallbacks – A sequence of runnables to try if the original runnable fails.
exceptions_to_handle – A tuple of exception types to handle.
Returns
A new Runnable that will try the original runnable, and then each
fallback in order, upon failures.
with_liste... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.gigachat.GigaChat.html |
b473f29c745f-13 | Bind input and output types to a Runnable, returning a new Runnable.
property InputType: TypeAlias¶
Get the input type for this runnable.
property OutputType: Type[str]¶
Get the input type for this runnable.
property config_specs: List[langchain.schema.runnable.utils.ConfigurableFieldSpec]¶
List configurable fields for... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.gigachat.GigaChat.html |
14957f6f5050-0 | langchain.llms.anyscale.Anyscale¶
class langchain.llms.anyscale.Anyscale[source]¶
Bases: BaseOpenAI
Anyscale large language models.
To use, you should have the environment variable ANYSCALE_API_BASE and
``ANYSCALE_API_KEY``set with your Anyscale Endpoint, or pass it as a named
parameter to the constructor.
Example
Crea... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.anyscale.Anyscale.html |
14957f6f5050-1 | Adjust the probability of specific tokens being generated.
param max_retries: int = 2¶
Maximum number of retries to make when generating.
param max_tokens: int = 256¶
The maximum number of tokens to generate in the completion.
-1 returns as many tokens as possible given the prompt and
the models maximal context size.
p... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.anyscale.Anyscale.html |
14957f6f5050-2 | param tags: Optional[List[str]] = None¶
Tags to add to the run trace.
param temperature: float = 0.7¶
What sampling temperature to use.
param tiktoken_model_name: Optional[str] = None¶
The model name to pass to tiktoken when using this class.
Tiktoken is used to count the number of tokens in documents to constrain
them... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.anyscale.Anyscale.html |
14957f6f5050-3 | The default implementation of batch works well for IO bound runnables.
Subclasses should override this method if they can batch more efficiently;
e.g., if the underlying runnable uses an API which supports a batch mode.
async agenerate(prompts: List[str], stop: Optional[List[str]] = None, callbacks: Union[List[BaseCall... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.anyscale.Anyscale.html |
14957f6f5050-4 | 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.
**kwargs – Arbitrary additional keyword arguments. These are usua... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.anyscale.Anyscale.html |
14957f6f5050-5 | Use this method when calling chat models and only the topcandidate generation is needed.
Parameters
messages – A sequence of chat messages corresponding to a single model input.
stop – Stop words to use when generating. Model output is cut off at the
first occurrence of any of these substrings.
**kwargs – Arbitrary add... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.anyscale.Anyscale.html |
14957f6f5050-6 | 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... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.anyscale.Anyscale.html |
14957f6f5050-7 | classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.anyscale.Anyscale.html |
14957f6f5050-8 | 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... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.anyscale.Anyscale.html |
14957f6f5050-9 | 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.
get_inp... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.anyscale.Anyscale.html |
14957f6f5050-10 | Get a pydantic model that can be used to validate output to the runnable.
Runnables that leverage the configurable_fields and configurable_alternatives
methods will have a dynamic output schema that depends on which
configuration the runnable is invoked with.
This method allows to get an output schema for a specific co... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.anyscale.Anyscale.html |
14957f6f5050-11 | 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... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.anyscale.Anyscale.html |
14957f6f5050-12 | max_tokens = openai.modelname_to_contextsize("text-davinci-003")
classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
classmethod parse_obj(obj: Any) → Model¶
classmethod parse_raw(b: Union[str, bytes], *... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.anyscale.Anyscale.html |
14957f6f5050-13 | to the model provider API call.
Returns
Top model prediction as a message.
save(file_path: Union[Path, str]) → None¶
Save the LLM.
Parameters
file_path – Path to file to save the LLM to.
Example:
.. code-block:: python
llm.save(file_path=”path/llm.yaml”)
classmethod schema(by_alias: bool = True, ref_template: unicode =... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.anyscale.Anyscale.html |
14957f6f5050-14 | Bind config to a Runnable, returning a new Runnable.
with_fallbacks(fallbacks: Sequence[Runnable[Input, Output]], *, exceptions_to_handle: Tuple[Type[BaseException], ...] = (<class 'Exception'>,)) → RunnableWithFallbacksT[Input, Output]¶
Add fallbacks to a runnable, returning a new Runnable.
Parameters
fallbacks – A se... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.anyscale.Anyscale.html |
14957f6f5050-15 | between retries
stop_after_attempt – The maximum number of attempts to make before giving up
Returns
A new Runnable that retries the original runnable on exceptions.
with_types(*, input_type: Optional[Type[Input]] = None, output_type: Optional[Type[Output]] = None) → Runnable[Input, Output]¶
Bind input and output types... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.anyscale.Anyscale.html |
b2dc5e2fd8d6-0 | langchain.llms.baidu_qianfan_endpoint.QianfanLLMEndpoint¶
class langchain.llms.baidu_qianfan_endpoint.QianfanLLMEndpoint[source]¶
Bases: LLM
Baidu Qianfan hosted open source or customized models.
To use, you should have the qianfan python package installed, and
the environment variable qianfan_ak and qianfan_sk set wit... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.baidu_qianfan_endpoint.QianfanLLMEndpoint.html |
b2dc5e2fd8d6-1 | param penalty_score: Optional[float] = 1¶
Model params, only supported in ERNIE-Bot and ERNIE-Bot-turbo.
In the case of other model, passing these params will not affect the result.
param qianfan_ak: Optional[str] = None¶
param qianfan_sk: Optional[str] = None¶
param request_timeout: Optional[int] = 60¶
request timeout... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.baidu_qianfan_endpoint.QianfanLLMEndpoint.html |
b2dc5e2fd8d6-2 | e.g., if the underlying runnable uses an API which supports a batch mode.
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[Li... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.baidu_qianfan_endpoint.QianfanLLMEndpoint.html |
b2dc5e2fd8d6-3 | 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... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.baidu_qianfan_endpoint.QianfanLLMEndpoint.html |
b2dc5e2fd8d6-4 | first occurrence of any of these substrings.
**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[... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.baidu_qianfan_endpoint.QianfanLLMEndpoint.html |
b2dc5e2fd8d6-5 | 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 runs invoke in parallel using a thread pool executor.
The default i... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.baidu_qianfan_endpoint.QianfanLLMEndpoint.html |
b2dc5e2fd8d6-6 | Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model¶
Duplicate a model, optionally... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.baidu_qianfan_endpoint.QianfanLLMEndpoint.html |
b2dc5e2fd8d6-7 | Pass a sequence of prompts to the model and return model generations.
This method should make use of batched calls for models that expose a batched
API.
Use this method when you want to:
take advantage of batched calls,
need more output from the model than just the top generated value,
are building chains that are agno... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.baidu_qianfan_endpoint.QianfanLLMEndpoint.html |
b2dc5e2fd8d6-8 | For example, if the class is langchain.llms.openai.OpenAI, then the
namespace is [“langchain”, “llms”, “openai”]
get_num_tokens(text: str) → int¶
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
Th... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.baidu_qianfan_endpoint.QianfanLLMEndpoint.html |
b2dc5e2fd8d6-9 | Transform a single input into an output. Override to implement.
Parameters
input – The input to the runnable.
config – A config to use when invoking the runnable.
The config supports standard keys like ‘tags’, ‘metadata’ for tracing
purposes, ‘max_concurrency’ for controlling how much work to do
in parallel, and other ... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.baidu_qianfan_endpoint.QianfanLLMEndpoint.html |
b2dc5e2fd8d6-10 | classmethod parse_obj(obj: Any) → Model¶
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
predict(text: str, *, stop: Optional[Sequence[str]] = None, **kwargs: Any) → str¶
Pass a single string input to t... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.baidu_qianfan_endpoint.QianfanLLMEndpoint.html |
b2dc5e2fd8d6-11 | .. code-block:: python
llm.save(file_path=”path/llm.yaml”)
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶
classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
stream(input: Union[Promp... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.baidu_qianfan_endpoint.QianfanLLMEndpoint.html |
b2dc5e2fd8d6-12 | Add fallbacks to a runnable, returning a new Runnable.
Parameters
fallbacks – A sequence of runnables to try if the original runnable fails.
exceptions_to_handle – A tuple of exception types to handle.
Returns
A new Runnable that will try the original runnable, and then each
fallback in order, upon failures.
with_liste... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.baidu_qianfan_endpoint.QianfanLLMEndpoint.html |
b2dc5e2fd8d6-13 | Bind input and output types to a Runnable, returning a new Runnable.
property InputType: TypeAlias¶
Get the input type for this runnable.
property OutputType: Type[str]¶
Get the input type for this runnable.
property config_specs: List[langchain.schema.runnable.utils.ConfigurableFieldSpec]¶
List configurable fields for... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.baidu_qianfan_endpoint.QianfanLLMEndpoint.html |
472e1836a72d-0 | langchain.llms.huggingface_hub.HuggingFaceHub¶
class langchain.llms.huggingface_hub.HuggingFaceHub[source]¶
Bases: LLM
HuggingFaceHub models.
To use, you should have the huggingface_hub python package installed, and the
environment variable HUGGINGFACEHUB_API_TOKEN set with your API token, or pass
it as a named parame... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.huggingface_hub.HuggingFaceHub.html |
472e1836a72d-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... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.huggingface_hub.HuggingFaceHub.html |
472e1836a72d-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... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.huggingface_hub.HuggingFaceHub.html |
472e1836a72d-3 | the runnable did not implement a native async version of invoke.
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 ... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.huggingface_hub.HuggingFaceHub.html |
472e1836a72d-4 | Subclasses should override this method if they support streaming output.
async astream_log(input: Any, config: Optional[RunnableConfig] = None, *, diff: bool = True, include_names: Optional[Sequence[str]] = None, include_types: Optional[Sequence[str]] = None, include_tags: Optional[Sequence[str]] = None, exclude_names:... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.huggingface_hub.HuggingFaceHub.html |
472e1836a72d-5 | e.g., if the underlying runnable uses an API which supports a batch mode.
bind(**kwargs: Any) → Runnable[Input, Output]¶
Bind arguments to a Runnable, returning a new Runnable.
config_schema(*, include: Optional[Sequence[str]] = None) → Type[BaseModel]¶
The type of config this runnable accepts specified as a pydantic m... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.huggingface_hub.HuggingFaceHub.html |
472e1836a72d-6 | exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data
deep – set to True to make a deep copy of the model
Returns
new model instance
dict(**kw... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.huggingface_hub.HuggingFaceHub.html |
472e1836a72d-7 | 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... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.huggingface_hub.HuggingFaceHub.html |
472e1836a72d-8 | get_num_tokens_from_messages(messages: List[BaseMessage]) → int¶
Get the number of tokens in the messages.
Useful for checking if an input will fit in a model’s context window.
Parameters
messages – The message inputs to tokenize.
Returns
The sum of the number of tokens across the messages.
get_output_schema(config: Op... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.huggingface_hub.HuggingFaceHub.html |
472e1836a72d-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... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.huggingface_hub.HuggingFaceHub.html |
472e1836a72d-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... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.huggingface_hub.HuggingFaceHub.html |
472e1836a72d-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... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.huggingface_hub.HuggingFaceHub.html |
472e1836a72d-12 | fallback in order, upon failures.
with_listeners(*, on_start: Optional[Listener] = None, on_end: Optional[Listener] = None, on_error: Optional[Listener] = None) → Runnable[Input, Output]¶
Bind lifecycle listeners to a Runnable, returning a new Runnable.
on_start: Called before the runnable starts running, with the Run ... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.huggingface_hub.HuggingFaceHub.html |
472e1836a72d-13 | property config_specs: List[langchain.schema.runnable.utils.ConfigurableFieldSpec]¶
List configurable fields for this runnable.
property input_schema: Type[pydantic.main.BaseModel]¶
The type of input this runnable accepts specified as a pydantic model.
property lc_attributes: Dict¶
List of attribute names that should b... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.huggingface_hub.HuggingFaceHub.html |
bc4aeac948c5-0 | langchain.llms.openlm.OpenLM¶
class langchain.llms.openlm.OpenLM[source]¶
Bases: BaseOpenAI
OpenLM 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 allowed_special: Union[Literal['all'], Abstrac... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.openlm.OpenLM.html |
bc4aeac948c5-1 | Metadata to add to the run trace.
param model_kwargs: Dict[str, Any] [Optional]¶
Holds any model parameters valid for create call not explicitly specified.
param model_name: str = 'text-davinci-003' (alias 'model')¶
Model name to use.
param n: int = 1¶
How many completions to generate for each prompt.
param openai_api_... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.openlm.OpenLM.html |
bc4aeac948c5-2 | be the same as the embedding model name. However, there are some cases
where you may want to use this Embedding class with a model name not
supported by tiktoken. This can include when using Azure embeddings or
when using one of the many model providers that expose an OpenAI-like
API but with different models. In those... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.openlm.OpenLM.html |
bc4aeac948c5-3 | e.g., if the underlying runnable uses an API which supports a batch mode.
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[Li... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.openlm.OpenLM.html |
bc4aeac948c5-4 | 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... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.openlm.OpenLM.html |
bc4aeac948c5-5 | first occurrence of any of these substrings.
**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[... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.openlm.OpenLM.html |
bc4aeac948c5-6 | 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 runs invoke in parallel using a thread pool executor.
The default i... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.openlm.OpenLM.html |
bc4aeac948c5-7 | Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model¶
Duplicate a model, optionally... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.openlm.OpenLM.html |
bc4aeac948c5-8 | 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... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.openlm.OpenLM.html |
bc4aeac948c5-9 | This method allows to get an input schema for a specific configuration.
Parameters
config – A config to use when generating the schema.
Returns
A pydantic model that can be used to validate input.
classmethod get_lc_namespace() → List[str]¶
Get the namespace of the langchain object.
For example, if the class is langcha... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.openlm.OpenLM.html |
bc4aeac948c5-10 | Get the sub prompts for llm call.
get_token_ids(text: str) → List[int]¶
Get the token IDs using the tiktoken package.
invoke(input: Union[PromptValue, str, List[BaseMessage]], config: Optional[RunnableConfig] = None, *, stop: Optional[List[str]] = None, **kwargs: Any) → str¶
Transform a single input into an output. Ove... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.openlm.OpenLM.html |
bc4aeac948c5-11 | to the object.
map() → Runnable[List[Input], List[Output]]¶
Return a new Runnable that maps a list of inputs to a list of outputs,
by calling invoke() with each input.
max_tokens_for_prompt(prompt: str) → int¶
Calculate the maximum number of tokens possible to generate for a prompt.
Parameters
prompt – The prompt to pa... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.openlm.OpenLM.html |
bc4aeac948c5-12 | first occurrence of any of these substrings.
**kwargs – Arbitrary additional keyword arguments. These are usually passed
to the model provider API call.
Returns
Top model prediction as a string.
predict_messages(messages: List[BaseMessage], *, stop: Optional[Sequence[str]] = None, **kwargs: Any) → BaseMessage¶
Pass a m... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.openlm.OpenLM.html |
bc4aeac948c5-13 | to_json_not_implemented() → SerializedNotImplemented¶
transform(input: Iterator[Input], config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → Iterator[Output]¶
Default implementation of transform, which buffers input and then calls stream.
Subclasses should override this method if they can start producing... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.openlm.OpenLM.html |
bc4aeac948c5-14 | The Run object contains information about the run, including its id,
type, input, output, error, start_time, end_time, and any tags or metadata
added to the run.
with_retry(*, retry_if_exception_type: ~typing.Tuple[~typing.Type[BaseException], ...] = (<class 'Exception'>,), wait_exponential_jitter: bool = True, stop_af... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.openlm.OpenLM.html |
bc4aeac948c5-15 | For example,{“openai_api_key”: “OPENAI_API_KEY”}
property max_context_size: int¶
Get max context size for this model.
property output_schema: Type[pydantic.main.BaseModel]¶
The type of output this runnable produces specified as a pydantic model.
Examples using OpenLM¶
OpenLM | lang/api.python.langchain.com/en/latest/llms/langchain.llms.openlm.OpenLM.html |
343962c61522-0 | langchain.llms.openai.BaseOpenAI¶
class langchain.llms.openai.BaseOpenAI[source]¶
Bases: BaseLLM
Base OpenAI large language model class.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
param allowed_special:... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.openai.BaseOpenAI.html |
343962c61522-1 | Metadata to add to the run trace.
param model_kwargs: Dict[str, Any] [Optional]¶
Holds any model parameters valid for create call not explicitly specified.
param model_name: str = 'text-davinci-003' (alias 'model')¶
Model name to use.
param n: int = 1¶
How many completions to generate for each prompt.
param openai_api_... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.openai.BaseOpenAI.html |
343962c61522-2 | be the same as the embedding model name. However, there are some cases
where you may want to use this Embedding class with a model name not
supported by tiktoken. This can include when using Azure embeddings or
when using one of the many model providers that expose an OpenAI-like
API but with different models. In those... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.openai.BaseOpenAI.html |
343962c61522-3 | e.g., if the underlying runnable uses an API which supports a batch mode.
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[Li... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.openai.BaseOpenAI.html |
343962c61522-4 | 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... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.openai.BaseOpenAI.html |
343962c61522-5 | first occurrence of any of these substrings.
**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[... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.openai.BaseOpenAI.html |
343962c61522-6 | 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 runs invoke in parallel using a thread pool executor.
The default i... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.openai.BaseOpenAI.html |
343962c61522-7 | Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model¶
Duplicate a model, optionally... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.openai.BaseOpenAI.html |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.