id stringlengths 14 16 | text stringlengths 13 2.7k | source stringlengths 57 178 |
|---|---|---|
d946a896f476-1 | }
],
"stream": False,
"max_tokens": 256
}
)
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[bool] = None¶
param callback_manager: Optional[BaseCallbackManage... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.octoai_endpoint.OctoAIEndpoint.html |
d946a896f476-2 | 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.octoai_endpoint.OctoAIEndpoint.html |
d946a896f476-3 | 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.octoai_endpoint.OctoAIEndpoint.html |
d946a896f476-4 | 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.octoai_endpoint.OctoAIEndpoint.html |
d946a896f476-5 | 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.octoai_endpoint.OctoAIEndpoint.html |
d946a896f476-6 | 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.octoai_endpoint.OctoAIEndpoint.html |
d946a896f476-7 | 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.octoai_endpoint.OctoAIEndpoint.html |
d946a896f476-8 | 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.octoai_endpoint.OctoAIEndpoint.html |
d946a896f476-9 | Parameters
text – The string input to tokenize.
Returns
A list of ids corresponding to the tokens in the text, in order they occurin the text.
invoke(input: Union[PromptValue, str, List[BaseMessage]], config: Optional[RunnableConfig] = None, *, stop: Optional[List[str]] = None, **kwargs: Any) → str¶
Transform a single ... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.octoai_endpoint.OctoAIEndpoint.html |
d946a896f476-10 | 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.
classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool =... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.octoai_endpoint.OctoAIEndpoint.html |
d946a896f476-11 | 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.
save(file_path: Union[Path, str]) → None¶
Save the LLM.
Parameters
file_path – Path to file to save the LLM to.
Example:
.. ... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.octoai_endpoint.OctoAIEndpoint.html |
d946a896f476-12 | 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.octoai_endpoint.OctoAIEndpoint.html |
d946a896f476-13 | 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.octoai_endpoint.OctoAIEndpoint.html |
0a778628f004-0 | langchain.llms.tongyi.Tongyi¶
class langchain.llms.tongyi.Tongyi[source]¶
Bases: LLM
Tongyi Qwen large language models.
To use, you should have the dashscope python package installed, and the
environment variable DASHSCOPE_API_KEY set with your API key, or pass
it as a named parameter to the constructor.
Example
from l... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.tongyi.Tongyi.html |
0a778628f004-1 | 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.tongyi.Tongyi.html |
0a778628f004-2 | 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.tongyi.Tongyi.html |
0a778628f004-3 | 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.tongyi.Tongyi.html |
0a778628f004-4 | 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.tongyi.Tongyi.html |
0a778628f004-5 | 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.tongyi.Tongyi.html |
0a778628f004-6 | 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.tongyi.Tongyi.html |
0a778628f004-7 | 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.tongyi.Tongyi.html |
0a778628f004-8 | 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.tongyi.Tongyi.html |
0a778628f004-9 | 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.tongyi.Tongyi.html |
0a778628f004-10 | 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.tongyi.Tongyi.html |
0a778628f004-11 | 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.tongyi.Tongyi.html |
0a778628f004-12 | 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.tongyi.Tongyi.html |
0a778628f004-13 | 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.tongyi.Tongyi.html |
3af2edcd8333-0 | langchain.llms.symblai_nebula.make_request¶
langchain.llms.symblai_nebula.make_request(self: Nebula, instruction: str, conversation: str, url: str = 'https://api-nebula.symbl.ai/v1/model/generate', params: Optional[Dict] = None) → Any[source]¶
Generate text from the model. | lang/api.python.langchain.com/en/latest/llms/langchain.llms.symblai_nebula.make_request.html |
a91361fafc09-0 | langchain.llms.databricks.get_repl_context¶
langchain.llms.databricks.get_repl_context() → Any[source]¶
Gets the notebook REPL context if running inside a Databricks notebook.
Returns None otherwise. | lang/api.python.langchain.com/en/latest/llms/langchain.llms.databricks.get_repl_context.html |
cfda562cb94c-0 | langchain.llms.stochasticai.StochasticAI¶
class langchain.llms.stochasticai.StochasticAI[source]¶
Bases: LLM
StochasticAI large language models.
To use, you should have the environment variable STOCHASTICAI_API_KEY
set with your API key.
Example
from langchain.llms import StochasticAI
stochasticai = StochasticAI(api_ur... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.stochasticai.StochasticAI.html |
cfda562cb94c-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.stochasticai.StochasticAI.html |
cfda562cb94c-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.stochasticai.StochasticAI.html |
cfda562cb94c-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.stochasticai.StochasticAI.html |
cfda562cb94c-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.stochasticai.StochasticAI.html |
cfda562cb94c-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.stochasticai.StochasticAI.html |
cfda562cb94c-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.stochasticai.StochasticAI.html |
cfda562cb94c-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.stochasticai.StochasticAI.html |
cfda562cb94c-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.stochasticai.StochasticAI.html |
cfda562cb94c-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.stochasticai.StochasticAI.html |
cfda562cb94c-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.stochasticai.StochasticAI.html |
cfda562cb94c-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.stochasticai.StochasticAI.html |
cfda562cb94c-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.stochasticai.StochasticAI.html |
cfda562cb94c-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.stochasticai.StochasticAI.html |
dcf882eef8df-0 | langchain.llms.ollama.Ollama¶
class langchain.llms.ollama.Ollama[source]¶
Bases: BaseLLM, _OllamaCommon
Ollama locally runs large language models.
To use, follow the instructions at https://ollama.ai/.
Example
from langchain.llms import Ollama
ollama = Ollama(model="llama2")
Create a new model by parsing and validating... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.ollama.Ollama.html |
dcf882eef8df-1 | Model name to use.
param num_ctx: Optional[int] = None¶
Sets the size of the context window used to generate the
next token. (Default: 2048)
param num_gpu: Optional[int] = None¶
The number of GPUs to use. On macOS it defaults to 1 to
enable metal support, 0 to disable.
param num_thread: Optional[int] = None¶
Sets the n... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.ollama.Ollama.html |
dcf882eef8df-2 | param tfs_z: Optional[float] = None¶
Tail free sampling is used to reduce the impact of less probable
tokens from the output. A higher value (e.g., 2.0) will reduce the
impact more, while a value of 1.0 disables this setting. (default: 1)
param top_k: Optional[int] = None¶
Reduces the probability of generating nonsense... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.ollama.Ollama.html |
dcf882eef8df-3 | 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[BaseCallbackHandler], BaseCallbackManager, None, List[Optional[Union[List[BaseC... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.ollama.Ollama.html |
dcf882eef8df-4 | 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 usually passed
to the model provider API call.
Returns
An LLMResult, which co... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.ollama.Ollama.html |
dcf882eef8df-5 | 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.ollama.Ollama.html |
dcf882eef8df-6 | Default implementation of atransform, which buffers input and calls astream.
Subclasses should override this method if they can start producing output while
input is still being generated.
batch(inputs: List[Union[PromptValue, str, List[BaseMessage]]], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = Non... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.ollama.Ollama.html |
dcf882eef8df-7 | 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... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.ollama.Ollama.html |
dcf882eef8df-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.ollama.Ollama.html |
dcf882eef8df-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.ollama.Ollama.html |
dcf882eef8df-10 | Parameters
text – The string input to tokenize.
Returns
A list of ids corresponding to the tokens in the text, in order they occurin the text.
invoke(input: Union[PromptValue, str, List[BaseMessage]], config: Optional[RunnableConfig] = None, *, stop: Optional[List[str]] = None, **kwargs: Any) → str¶
Transform a single ... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.ollama.Ollama.html |
dcf882eef8df-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.
classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool =... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.ollama.Ollama.html |
dcf882eef8df-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 message.
save(file_path: Union[Path, str]) → None¶
Save the LLM.
Parameters
file_path – Path to file to save the LLM to.
Example:
.. ... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.ollama.Ollama.html |
dcf882eef8df-13 | 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.ollama.Ollama.html |
dcf882eef8df-14 | 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.ollama.Ollama.html |
6d786bc3e525-0 | 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. | lang/api.python.langchain.com/en/latest/llms/langchain.llms.databricks.get_default_host.html |
1bac6a303fa7-0 | langchain.llms.ai21.AI21¶
class langchain.llms.ai21.AI21[source]¶
Bases: LLM
AI21 large language models.
To use, you should have the environment variable AI21_API_KEY
set with your API key or pass it as a named parameter to the constructor.
Example
from langchain.llms import AI21
ai21 = AI21(ai21_api_key="my-api-key", ... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.ai21.AI21.html |
1bac6a303fa7-1 | Adjust the probability of specific tokens being generated.
param maxTokens: int = 256¶
The maximum number of tokens to generate in the completion.
param metadata: Optional[Dict[str, Any]] = None¶
Metadata to add to the run trace.
param minTokens: int = 0¶
The minimum number of tokens to generate in the completion.
para... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.ai21.AI21.html |
1bac6a303fa7-2 | 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.ai21.AI21.html |
1bac6a303fa7-3 | 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.ai21.AI21.html |
1bac6a303fa7-4 | **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.ai21.AI21.html |
1bac6a303fa7-5 | 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.ai21.AI21.html |
1bac6a303fa7-6 | 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.ai21.AI21.html |
1bac6a303fa7-7 | 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... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.ai21.AI21.html |
1bac6a303fa7-8 | 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.
get_inp... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.ai21.AI21.html |
1bac6a303fa7-9 | 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.ai21.AI21.html |
1bac6a303fa7-10 | 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.ai21.AI21.html |
1bac6a303fa7-11 | 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.ai21.AI21.html |
1bac6a303fa7-12 | 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.ai21.AI21.html |
1bac6a303fa7-13 | 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.ai21.AI21.html |
1bac6a303fa7-14 | 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.ai21.AI21.html |
3144618d6fe2-0 | langchain.llms.sagemaker_endpoint.ContentHandlerBase¶
class langchain.llms.sagemaker_endpoint.ContentHandlerBase[source]¶
A handler class to transform input from LLM to a
format that SageMaker endpoint expects.
Similarly, the class handles transforming output from the
SageMaker endpoint to a format that LLM class expec... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.sagemaker_endpoint.ContentHandlerBase.html |
2a28b7afacdf-0 | langchain.llms.sagemaker_endpoint.LLMContentHandler¶
class langchain.llms.sagemaker_endpoint.LLMContentHandler[source]¶
Content handler for LLM class.
Attributes
accepts
The MIME type of the response data returned from endpoint
content_type
The MIME type of the input data passed to endpoint
Methods
__init__()
transform... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.sagemaker_endpoint.LLMContentHandler.html |
8b712a73cdba-0 | langchain.llms.fireworks.acompletion_with_retry_streaming¶
async langchain.llms.fireworks.acompletion_with_retry_streaming(llm: Fireworks, use_retry: bool, *, run_manager: Optional[AsyncCallbackManagerForLLMRun] = None, **kwargs: Any) → Any[source]¶
Use tenacity to retry the completion call for streaming. | lang/api.python.langchain.com/en/latest/llms/langchain.llms.fireworks.acompletion_with_retry_streaming.html |
cf7082912544-0 | langchain.llms.base.update_cache¶
langchain.llms.base.update_cache(existing_prompts: Dict[int, List], llm_string: str, missing_prompt_idxs: List[int], new_results: LLMResult, prompts: List[str]) → Optional[dict][source]¶
Update the cache and get the LLM output. | lang/api.python.langchain.com/en/latest/llms/langchain.llms.base.update_cache.html |
27f5ed23cfab-0 | langchain.llms.nlpcloud.NLPCloud¶
class langchain.llms.nlpcloud.NLPCloud[source]¶
Bases: LLM
NLPCloud large language models.
To use, you should have the nlpcloud python package installed, and the
environment variable NLPCLOUD_API_KEY set with your API key.
Example
from langchain.llms import NLPCloud
nlpcloud = NLPCloud... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.nlpcloud.NLPCloud.html |
27f5ed23cfab-1 | Whether or not to remove the end sequence token.
param remove_input: bool = True¶
Remove input text from API response
param repetition_penalty: float = 1.0¶
Penalizes repeated tokens. 1.0 means no penalty.
param tags: Optional[List[str]] = None¶
Tags to add to the run trace.
param temperature: float = 0.7¶
What samplin... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.nlpcloud.NLPCloud.html |
27f5ed23cfab-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.nlpcloud.NLPCloud.html |
27f5ed23cfab-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.nlpcloud.NLPCloud.html |
27f5ed23cfab-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.nlpcloud.NLPCloud.html |
27f5ed23cfab-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.nlpcloud.NLPCloud.html |
27f5ed23cfab-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.nlpcloud.NLPCloud.html |
27f5ed23cfab-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.nlpcloud.NLPCloud.html |
27f5ed23cfab-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.nlpcloud.NLPCloud.html |
27f5ed23cfab-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.nlpcloud.NLPCloud.html |
27f5ed23cfab-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.nlpcloud.NLPCloud.html |
27f5ed23cfab-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.nlpcloud.NLPCloud.html |
27f5ed23cfab-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.nlpcloud.NLPCloud.html |
27f5ed23cfab-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.nlpcloud.NLPCloud.html |
f28f26dc9a26-0 | langchain.llms.fake.FakeListLLM¶
class langchain.llms.fake.FakeListLLM[source]¶
Bases: LLM
Fake LLM for testing purposes.
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[bool] = None¶
p... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.fake.FakeListLLM.html |
f28f26dc9a26-1 | 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.fake.FakeListLLM.html |
f28f26dc9a26-2 | 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... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.fake.FakeListLLM.html |
f28f26dc9a26-3 | 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.fake.FakeListLLM.html |
f28f26dc9a26-4 | 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 runs invoke in parallel using a thread pool executor.
The default i... | lang/api.python.langchain.com/en/latest/llms/langchain.llms.fake.FakeListLLM.html |
f28f26dc9a26-5 | 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.fake.FakeListLLM.html |
f28f26dc9a26-6 | 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.fake.FakeListLLM.html |
f28f26dc9a26-7 | 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.fake.FakeListLLM.html |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.