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a8109838f8aa-0 | langchain.llms.promptlayer_openai.PromptLayerOpenAI¶
class langchain.llms.promptlayer_openai.PromptLayerOpenAI[source]¶
Bases: OpenAI
PromptLayer OpenAI large language models.
To use, you should have the openai and promptlayer python
package installed, and the environment variable OPENAI_API_KEY
and PROMPTLAYER_API_KEY... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.promptlayer_openai.PromptLayerOpenAI.html |
a8109838f8aa-1 | param default_query: Union[Mapping[str, object], None] = None¶
param disallowed_special: Union[Literal['all'], Collection[str]] = 'all'¶
Set of special tokens that are not allowed。
param frequency_penalty: float = 0¶
Penalizes repeated tokens according to frequency.
param http_client: Union[Any, None] = None¶
Optional ... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.promptlayer_openai.PromptLayerOpenAI.html |
a8109838f8aa-2 | param openai_proxy: Optional[str] = None¶
param pl_tags: Optional[List[str]] = None¶
param presence_penalty: float = 0¶
Penalizes repeated tokens.
param request_timeout: Union[float, Tuple[float, float], Any, None] = None (alias 'timeout')¶
Timeout for requests to OpenAI completion API. Can be float, httpx.Timeout or
N... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.promptlayer_openai.PromptLayerOpenAI.html |
a8109838f8aa-3 | 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.promptlayer_openai.PromptLayerOpenAI.html |
a8109838f8aa-4 | 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.promptlayer_openai.PromptLayerOpenAI.html |
a8109838f8aa-5 | 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.promptlayer_openai.PromptLayerOpenAI.html |
a8109838f8aa-6 | 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.promptlayer_openai.PromptLayerOpenAI.html |
a8109838f8aa-7 | 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.promptlayer_openai.PromptLayerOpenAI.html |
a8109838f8aa-8 | 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
create_ll... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.promptlayer_openai.PromptLayerOpenAI.html |
a8109838f8aa-9 | 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 agnostic to the underlying language modeltype (e.g., pure text completion models vs chat models).
Parameters
prompts – List of PromptValues. A PromptVal... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.promptlayer_openai.PromptLayerOpenAI.html |
a8109838f8aa-10 | 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
The integer number of tokens in the text.
get_num_tokens_from_messages(messages: List[BaseMessage]) → int¶
Get the ... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.promptlayer_openai.PromptLayerOpenAI.html |
a8109838f8aa-11 | 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 keys. Please refer to the RunnableConfig
for more details.
Returns
The output of the runnable.
classmethod is_... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.promptlayer_openai.PromptLayerOpenAI.html |
a8109838f8aa-12 | Example
max_tokens = openai.max_token_for_prompt("Tell me a joke.")
static modelname_to_contextsize(modelname: str) → int¶
Calculate the maximum number of tokens possible to generate for a model.
Parameters
modelname – The modelname we want to know the context size for.
Returns
The maximum context size
Example
max_toke... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.promptlayer_openai.PromptLayerOpenAI.html |
a8109838f8aa-13 | 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... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.promptlayer_openai.PromptLayerOpenAI.html |
a8109838f8aa-14 | 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: Sequence[Runnable[Input, Output]], *, exceptions_to_handle: Tuple[Type[BaseException], ...] = (<class 'E... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.promptlayer_openai.PromptLayerOpenAI.html |
a8109838f8aa-15 | Create a new Runnable that retries the original runnable on exceptions.
Parameters
retry_if_exception_type – A tuple of exception types to retry on
wait_exponential_jitter – Whether to add jitter to the wait time
between retries
stop_after_attempt – The maximum number of attempts to make before giving up
Returns
A new ... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.promptlayer_openai.PromptLayerOpenAI.html |
35eecd157f80-0 | langchain.llms.replicate.Replicate¶
class langchain.llms.replicate.Replicate[source]¶
Bases: LLM
Replicate models.
To use, you should have the replicate python package installed,
and the environment variable REPLICATE_API_TOKEN set with your API token.
You can find your token here: https://replicate.com/account
The mod... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.replicate.Replicate.html |
35eecd157f80-1 | param tags: Optional[List[str]] = None¶
Tags to add to the run trace.
param verbose: bool [Optional]¶
Whether to print out response text.
param version_obj: Any = None¶
Optionally pass in the model version object during initialization to avoid
having to make an extra API call to retrieve it during streaming. NOTE: not
... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.replicate.Replicate.html |
35eecd157f80-2 | 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.replicate.Replicate.html |
35eecd157f80-3 | 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.replicate.Replicate.html |
35eecd157f80-4 | 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.replicate.Replicate.html |
35eecd157f80-5 | 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.replicate.Replicate.html |
35eecd157f80-6 | 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.replicate.Replicate.html |
35eecd157f80-7 | 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.replicate.Replicate.html |
35eecd157f80-8 | 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.replicate.Replicate.html |
35eecd157f80-9 | The output of the runnable.
classmethod is_lc_serializable() → bool[source]¶
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, exclu... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.replicate.Replicate.html |
35eecd157f80-10 | 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.replicate.Replicate.html |
35eecd157f80-11 | 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.replicate.Replicate.html |
35eecd157f80-12 | 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.replicate.Replicate.html |
35eecd157f80-13 | 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.replicate.Replicate.html |
95eb0036ea29-0 | langchain.llms.yandex.YandexGPT¶
class langchain.llms.yandex.YandexGPT[source]¶
Bases: _BaseYandexGPT, LLM
Yandex large language models.
To use, you should have the yandexcloud python package installed.
There are two authentication options for the service account
with the ai.languageModels.user role:
You can specify th... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.yandex.YandexGPT.html |
95eb0036ea29-1 | Sequences when completion generation will stop.
param tags: Optional[List[str]] = None¶
Tags to add to the run trace.
param temperature: float = 0.6¶
What sampling temperature to use.
Should be a double number between 0 (inclusive) and 1 (inclusive).
param url: str = 'llm.api.cloud.yandex.net:443'¶
The url of the API.
... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.yandex.YandexGPT.html |
95eb0036ea29-2 | 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.yandex.YandexGPT.html |
95eb0036ea29-3 | 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.yandex.YandexGPT.html |
95eb0036ea29-4 | 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.yandex.YandexGPT.html |
95eb0036ea29-5 | 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.yandex.YandexGPT.html |
95eb0036ea29-6 | 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.yandex.YandexGPT.html |
95eb0036ea29-7 | 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.yandex.YandexGPT.html |
95eb0036ea29-8 | 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.yandex.YandexGPT.html |
95eb0036ea29-9 | 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.yandex.YandexGPT.html |
95eb0036ea29-10 | 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.yandex.YandexGPT.html |
95eb0036ea29-11 | .. 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.yandex.YandexGPT.html |
95eb0036ea29-12 | 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.yandex.YandexGPT.html |
95eb0036ea29-13 | 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.yandex.YandexGPT.html |
2cafb08a6ad9-0 | langchain.llms.huggingface_text_gen_inference.HuggingFaceTextGenInference¶
class langchain.llms.huggingface_text_gen_inference.HuggingFaceTextGenInference[source]¶
Bases: LLM
HuggingFace text generation API.
To use, you should have the text-generation python package installed and
a text-generation server running.
Examp... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.huggingface_text_gen_inference.HuggingFaceTextGenInference.html |
2cafb08a6ad9-1 | param do_sample: bool = False¶
Activate logits sampling
param inference_server_url: str = ''¶
text-generation-inference instance base url
param max_new_tokens: int = 512¶
Maximum number of generated tokens
param metadata: Optional[Dict[str, Any]] = None¶
Metadata to add to the run trace.
param model_kwargs: Dict[str, A... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.huggingface_text_gen_inference.HuggingFaceTextGenInference.html |
2cafb08a6ad9-2 | param truncate: Optional[int] = None¶
Truncate inputs tokens to the given size
param typical_p: Optional[float] = 0.95¶
Typical Decoding mass. See [Typical Decoding for Natural Language
Generation](https://arxiv.org/abs/2202.00666) for more information.
param verbose: bool [Optional]¶
Whether to print out response text... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.huggingface_text_gen_inference.HuggingFaceTextGenInference.html |
2cafb08a6ad9-3 | 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.huggingface_text_gen_inference.HuggingFaceTextGenInference.html |
2cafb08a6ad9-4 | 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.huggingface_text_gen_inference.HuggingFaceTextGenInference.html |
2cafb08a6ad9-5 | 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.huggingface_text_gen_inference.HuggingFaceTextGenInference.html |
2cafb08a6ad9-6 | 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.huggingface_text_gen_inference.HuggingFaceTextGenInference.html |
2cafb08a6ad9-7 | 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.huggingface_text_gen_inference.HuggingFaceTextGenInference.html |
2cafb08a6ad9-8 | 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.huggingface_text_gen_inference.HuggingFaceTextGenInference.html |
2cafb08a6ad9-9 | 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.huggingface_text_gen_inference.HuggingFaceTextGenInference.html |
2cafb08a6ad9-10 | 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.huggingface_text_gen_inference.HuggingFaceTextGenInference.html |
2cafb08a6ad9-11 | 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.huggingface_text_gen_inference.HuggingFaceTextGenInference.html |
2cafb08a6ad9-12 | .. 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.huggingface_text_gen_inference.HuggingFaceTextGenInference.html |
2cafb08a6ad9-13 | 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.huggingface_text_gen_inference.HuggingFaceTextGenInference.html |
2cafb08a6ad9-14 | 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.huggingface_text_gen_inference.HuggingFaceTextGenInference.html |
cce49921704a-0 | langchain.llms.azureml_endpoint.LlamaContentFormatter¶
class langchain.llms.azureml_endpoint.LlamaContentFormatter[source]¶
Content formatter for LLaMa
Attributes
accepts
The MIME type of the response data returned from the endpoint
content_type
The MIME type of the input data passed to the endpoint
Methods
__init__()
... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.azureml_endpoint.LlamaContentFormatter.html |
525b43da5bba-0 | langchain.llms.sagemaker_endpoint.LineIterator¶
class langchain.llms.sagemaker_endpoint.LineIterator(stream: Any)[source]¶
A helper class for parsing the byte stream input.
The output of the model will be in the following format:
b’{“outputs”: [” a”]}
‘b’{“outputs”: [” challenging”]}
‘b’{“outputs”: [” problem”]}
‘…
Whi... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.sagemaker_endpoint.LineIterator.html |
180798377838-0 | langchain.llms.pipelineai.PipelineAI¶
class langchain.llms.pipelineai.PipelineAI[source]¶
Bases: LLM, BaseModel
PipelineAI large language models.
To use, you should have the pipeline-ai python package installed,
and the environment variable PIPELINE_API_KEY set with your API key.
Any parameters that are valid to be pas... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.pipelineai.PipelineAI.html |
180798377838-1 | 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.llms.pipelineai.PipelineAI.html |
180798377838-2 | 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.llms.pipelineai.PipelineAI.html |
180798377838-3 | **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.llms.pipelineai.PipelineAI.html |
180798377838-4 | 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.llms.pipelineai.PipelineAI.html |
180798377838-5 | 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.llms.pipelineai.PipelineAI.html |
180798377838-6 | 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... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.pipelineai.PipelineAI.html |
180798377838-7 | 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.
get_inp... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.pipelineai.PipelineAI.html |
180798377838-8 | 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.pipelineai.PipelineAI.html |
180798377838-9 | 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.pipelineai.PipelineAI.html |
180798377838-10 | 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.pipelineai.PipelineAI.html |
180798377838-11 | 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.pipelineai.PipelineAI.html |
180798377838-12 | 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.pipelineai.PipelineAI.html |
180798377838-13 | 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.pipelineai.PipelineAI.html |
147d1ac83cfa-0 | langchain.llms.databricks.get_default_api_token¶
langchain.llms.databricks.get_default_api_token() → str[source]¶
Gets the default Databricks personal access token.
Raises an error if the token cannot be automatically determined. | lang/api.python.langchain.com/en/latest/llms/langchain.llms.databricks.get_default_api_token.html |
ec234dbaa88e-0 | langchain.llms.tongyi.generate_with_retry¶
langchain.llms.tongyi.generate_with_retry(llm: Tongyi, **kwargs: Any) → Any[source]¶
Use tenacity to retry the completion call. | lang/api.python.langchain.com/en/latest/llms/langchain.llms.tongyi.generate_with_retry.html |
09674692c137-0 | langchain.llms.xinference.Xinference¶
class langchain.llms.xinference.Xinference[source]¶
Bases: LLM
Wrapper for accessing Xinference’s large-scale model inference service.
To use, you should have the xinference library installed:
pip install "xinference[all]"
Check out: https://github.com/xorbitsai/inference
To run, y... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.xinference.Xinference.html |
09674692c137-1 | param callback_manager: Optional[BaseCallbackManager] = None¶
param callbacks: Callbacks = None¶
param client: Any = None¶
param metadata: Optional[Dict[str, Any]] = None¶
Metadata to add to the run trace.
param model_kwargs: Dict[str, Any] [Required]¶
Keyword arguments to be passed to xinference.LLM
param model_uid: O... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.xinference.Xinference.html |
09674692c137-2 | 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.xinference.Xinference.html |
09674692c137-3 | 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.xinference.Xinference.html |
09674692c137-4 | 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.xinference.Xinference.html |
09674692c137-5 | 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.xinference.Xinference.html |
09674692c137-6 | 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.xinference.Xinference.html |
09674692c137-7 | 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.xinference.Xinference.html |
09674692c137-8 | 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.xinference.Xinference.html |
09674692c137-9 | 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.xinference.Xinference.html |
09674692c137-10 | 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.xinference.Xinference.html |
09674692c137-11 | .. 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.xinference.Xinference.html |
09674692c137-12 | 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.xinference.Xinference.html |
09674692c137-13 | 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.xinference.Xinference.html |
d26a797910e6-0 | langchain.llms.ctranslate2.CTranslate2¶
class langchain.llms.ctranslate2.CTranslate2[source]¶
Bases: BaseLLM
CTranslate2 language model.
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 cache: Optional[... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.ctranslate2.CTranslate2.html |
d26a797910e6-1 | Keep the most probable tokens whose cumulative probability exceeds this value.
param tags: Optional[List[str]] = None¶
Tags to add to the run trace.
param tokenizer_name: str = ''¶
Name of the original Hugging Face model needed to load the proper tokenizer.
param verbose: bool [Optional]¶
Whether to print out response ... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.ctranslate2.CTranslate2.html |
d26a797910e6-2 | 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.ctranslate2.CTranslate2.html |
d26a797910e6-3 | 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.ctranslate2.CTranslate2.html |
d26a797910e6-4 | 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.ctranslate2.CTranslate2.html |
d26a797910e6-5 | 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.ctranslate2.CTranslate2.html |
d26a797910e6-6 | 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.ctranslate2.CTranslate2.html |
d26a797910e6-7 | 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.ctranslate2.CTranslate2.html |
d26a797910e6-8 | 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.ctranslate2.CTranslate2.html |
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