id stringlengths 14 15 | text stringlengths 44 2.47k | source stringlengths 61 181 |
|---|---|---|
43fcb9cc9f9c-2 | Asynchronously pass a sequence of prompts 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 ag... | https://api.python.langchain.com/en/latest/llms/langchain.llms.vertexai.VertexAIModelGarden.html |
43fcb9cc9f9c-3 | Parameters
text – String input to pass to the model.
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.
Returns
Top model prediction as a string.... | https://api.python.langchain.com/en/latest/llms/langchain.llms.vertexai.VertexAIModelGarden.html |
43fcb9cc9f9c-4 | Stream all output from a runnable, as reported to the callback system.
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... | https://api.python.langchain.com/en/latest/llms/langchain.llms.vertexai.VertexAIModelGarden.html |
43fcb9cc9f9c-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... | https://api.python.langchain.com/en/latest/llms/langchain.llms.vertexai.VertexAIModelGarden.html |
43fcb9cc9f9c-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... | https://api.python.langchain.com/en/latest/llms/langchain.llms.vertexai.VertexAIModelGarden.html |
43fcb9cc9f9c-7 | 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_token_ids(text: str) → List[int]¶
Return the ordered ids of the tokens in a text.
Parameters
text – The string input to tokenize.
R... | https://api.python.langchain.com/en/latest/llms/langchain.llms.vertexai.VertexAIModelGarden.html |
43fcb9cc9f9c-8 | 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 = False) → Model¶
classmethod parse_obj(obj: Any) → Model¶
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = No... | https://api.python.langchain.com/en/latest/llms/langchain.llms.vertexai.VertexAIModelGarden.html |
43fcb9cc9f9c-9 | 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 = '#/definitions/{model}') → DictStrAny¶
classmethod schema_json(*, by_alias... | https://api.python.langchain.com/en/latest/llms/langchain.llms.vertexai.VertexAIModelGarden.html |
43fcb9cc9f9c-10 | Bind config to a Runnable, returning a new Runnable.
with_fallbacks(fallbacks: ~typing.Sequence[~langchain.schema.runnable.base.Runnable[~langchain.schema.runnable.utils.Input, ~langchain.schema.runnable.utils.Output]], *, exceptions_to_handle: ~typing.Tuple[~typing.Type[BaseException], ...] = (<class 'Exception'>,)) →... | https://api.python.langchain.com/en/latest/llms/langchain.llms.vertexai.VertexAIModelGarden.html |
198c27400757-0 | langchain.llms.huggingface_endpoint.HuggingFaceEndpoint¶
class langchain.llms.huggingface_endpoint.HuggingFaceEndpoint[source]¶
Bases: LLM
HuggingFace Endpoint 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 ... | https://api.python.langchain.com/en/latest/llms/langchain.llms.huggingface_endpoint.HuggingFaceEndpoint.html |
198c27400757-1 | param verbose: bool [Optional]¶
Whether to print out response text.
__call__(prompt: str, stop: Optional[List[str]] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, **kwargs: Any) → str¶
Check Cache... | https://api.python.langchain.com/en/latest/llms/langchain.llms.huggingface_endpoint.HuggingFaceEndpoint.html |
198c27400757-2 | Asynchronously pass a sequence of prompts 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 ag... | https://api.python.langchain.com/en/latest/llms/langchain.llms.huggingface_endpoint.HuggingFaceEndpoint.html |
198c27400757-3 | Parameters
text – String input to pass to the model.
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.
Returns
Top model prediction as a string.... | https://api.python.langchain.com/en/latest/llms/langchain.llms.huggingface_endpoint.HuggingFaceEndpoint.html |
198c27400757-4 | Stream all output from a runnable, as reported to the callback system.
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... | https://api.python.langchain.com/en/latest/llms/langchain.llms.huggingface_endpoint.HuggingFaceEndpoint.html |
198c27400757-5 | 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... | https://api.python.langchain.com/en/latest/llms/langchain.llms.huggingface_endpoint.HuggingFaceEndpoint.html |
198c27400757-6 | 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... | https://api.python.langchain.com/en/latest/llms/langchain.llms.huggingface_endpoint.HuggingFaceEndpoint.html |
198c27400757-7 | 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_token_ids(text: str) → List[int]¶
Return the ordered ids of the tokens in a text.
Parameters
text – The string input to tokenize.
R... | https://api.python.langchain.com/en/latest/llms/langchain.llms.huggingface_endpoint.HuggingFaceEndpoint.html |
198c27400757-8 | 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 = False) → Model¶
classmethod parse_obj(obj: Any) → Model¶
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = No... | https://api.python.langchain.com/en/latest/llms/langchain.llms.huggingface_endpoint.HuggingFaceEndpoint.html |
198c27400757-9 | 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 = '#/definitions/{model}') → DictStrAny¶
classmethod schema_json(*, by_alias... | https://api.python.langchain.com/en/latest/llms/langchain.llms.huggingface_endpoint.HuggingFaceEndpoint.html |
198c27400757-10 | Bind config to a Runnable, returning a new Runnable.
with_fallbacks(fallbacks: ~typing.Sequence[~langchain.schema.runnable.base.Runnable[~langchain.schema.runnable.utils.Input, ~langchain.schema.runnable.utils.Output]], *, exceptions_to_handle: ~typing.Tuple[~typing.Type[BaseException], ...] = (<class 'Exception'>,)) →... | https://api.python.langchain.com/en/latest/llms/langchain.llms.huggingface_endpoint.HuggingFaceEndpoint.html |
e4373e6e017b-0 | langchain.llms.openai.completion_with_retry¶
langchain.llms.openai.completion_with_retry(llm: Union[BaseOpenAI, OpenAIChat], run_manager: Optional[CallbackManagerForLLMRun] = None, **kwargs: Any) → Any[source]¶
Use tenacity to retry the completion call. | https://api.python.langchain.com/en/latest/llms/langchain.llms.openai.completion_with_retry.html |
935d4be8ad4b-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. | https://api.python.langchain.com/en/latest/llms/langchain.llms.tongyi.generate_with_retry.html |
e201d2bcfc2f-0 | langchain.llms.bedrock.Bedrock¶
class langchain.llms.bedrock.Bedrock[source]¶
Bases: LLM, BedrockBase
Bedrock models.
To authenticate, the AWS client uses the following methods to
automatically load credentials:
https://boto3.amazonaws.com/v1/documentation/api/latest/guide/credentials.html
If a specific credential prof... | https://api.python.langchain.com/en/latest/llms/langchain.llms.bedrock.Bedrock.html |
e201d2bcfc2f-1 | Key word arguments to pass to the model.
param provider_stop_sequence_key_name_map: Mapping[str, str] = {'ai21': 'stop_sequences', 'amazon': 'stopSequences', 'anthropic': 'stop_sequences'}¶
param region_name: Optional[str] = None¶
The aws region e.g., us-west-2. Fallsback to AWS_DEFAULT_REGION env variable
or region sp... | https://api.python.langchain.com/en/latest/llms/langchain.llms.bedrock.Bedrock.html |
e201d2bcfc2f-2 | Subclasses should override this method if they can batch more efficiently.
async agenerate(prompts: List[str], stop: Optional[List[str]] = None, callbacks: Union[List[BaseCallbackHandler], BaseCallbackManager, None, List[Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]]]] = None, *, tags: Optional[Union[L... | https://api.python.langchain.com/en/latest/llms/langchain.llms.bedrock.Bedrock.html |
e201d2bcfc2f-3 | functionality, such as logging or streaming, throughout generation.
**kwargs – Arbitrary additional keyword arguments. These are usually passed
to the model provider API call.
Returns
An LLMResult, which contains a list of candidate Generations for each inputprompt and additional model provider-specific output.
async a... | https://api.python.langchain.com/en/latest/llms/langchain.llms.bedrock.Bedrock.html |
e201d2bcfc2f-4 | to the model provider API call.
Returns
Top model prediction as a message.
async astream(input: Union[PromptValue, str, List[BaseMessage]], config: Optional[RunnableConfig] = None, *, stop: Optional[List[str]] = None, **kwargs: Any) → AsyncIterator[str]¶
Default implementation of astream, which calls ainvoke.
Subclasse... | https://api.python.langchain.com/en/latest/llms/langchain.llms.bedrock.Bedrock.html |
e201d2bcfc2f-5 | input is still being generated.
batch(inputs: List[Union[PromptValue, str, List[BaseMessage]]], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, return_exceptions: bool = False, **kwargs: Any) → List[str]¶
Default implementation of batch, which calls invoke N times.
Subclasses should override th... | https://api.python.langchain.com/en/latest/llms/langchain.llms.bedrock.Bedrock.html |
e201d2bcfc2f-6 | classmethod from_orm(obj: Any) → Model¶
generate(prompts: List[str], stop: Optional[List[str]] = None, callbacks: Union[List[BaseCallbackHandler], BaseCallbackManager, None, List[Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]]]] = None, *, tags: Optional[Union[List[str], List[List[str]]]] = None, metada... | https://api.python.langchain.com/en/latest/llms/langchain.llms.bedrock.Bedrock.html |
e201d2bcfc2f-7 | functionality, such as logging or streaming, throughout generation.
**kwargs – Arbitrary additional keyword arguments. These are usually passed
to the model provider API call.
Returns
An LLMResult, which contains a list of candidate Generations for each inputprompt and additional model provider-specific output.
classme... | https://api.python.langchain.com/en/latest/llms/langchain.llms.bedrock.Bedrock.html |
e201d2bcfc2f-8 | classmethod is_lc_serializable() → bool¶
Is this class serializable?
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defa... | https://api.python.langchain.com/en/latest/llms/langchain.llms.bedrock.Bedrock.html |
e201d2bcfc2f-9 | Pass a single string input to the model and return a string prediction.
Use this method when passing in raw text. If you want to pass in specifictypes of chat messages, use predict_messages.
Parameters
text – String input to pass to the model.
stop – Stop words to use when generating. Model output is cut off at the
fir... | https://api.python.langchain.com/en/latest/llms/langchain.llms.bedrock.Bedrock.html |
e201d2bcfc2f-10 | stream(input: Union[PromptValue, str, List[BaseMessage]], config: Optional[RunnableConfig] = None, *, stop: Optional[List[str]] = None, **kwargs: Any) → Iterator[str]¶
Default implementation of stream, which calls invoke.
Subclasses should override this method if they support streaming output.
to_json() → Union[Seriali... | https://api.python.langchain.com/en/latest/llms/langchain.llms.bedrock.Bedrock.html |
e201d2bcfc2f-11 | property InputType: TypeAlias¶
Get the input type for this runnable.
property OutputType: Type[str]¶
Get the input type for this runnable.
property input_schema: Type[pydantic.main.BaseModel]¶
property lc_attributes: Dict¶
List of attribute names that should be included in the serialized kwargs.
These attributes must b... | https://api.python.langchain.com/en/latest/llms/langchain.llms.bedrock.Bedrock.html |
80ab2c305674-0 | langchain.llms.fireworks.Fireworks¶
class langchain.llms.fireworks.Fireworks[source]¶
Bases: LLM
Fireworks 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 cache: Optional[bool] = None¶
param ca... | https://api.python.langchain.com/en/latest/llms/langchain.llms.fireworks.Fireworks.html |
80ab2c305674-1 | Subclasses should override this method if they can batch more efficiently.
async agenerate(prompts: List[str], stop: Optional[List[str]] = None, callbacks: Union[List[BaseCallbackHandler], BaseCallbackManager, None, List[Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]]]] = None, *, tags: Optional[Union[L... | https://api.python.langchain.com/en/latest/llms/langchain.llms.fireworks.Fireworks.html |
80ab2c305674-2 | functionality, such as logging or streaming, throughout generation.
**kwargs – Arbitrary additional keyword arguments. These are usually passed
to the model provider API call.
Returns
An LLMResult, which contains a list of candidate Generations for each inputprompt and additional model provider-specific output.
async a... | https://api.python.langchain.com/en/latest/llms/langchain.llms.fireworks.Fireworks.html |
80ab2c305674-3 | to the model provider API call.
Returns
Top model prediction as a message.
async astream(input: Union[PromptValue, str, List[BaseMessage]], config: Optional[RunnableConfig] = None, *, stop: Optional[List[str]] = None, **kwargs: Any) → AsyncIterator[str][source]¶
Default implementation of astream, which calls ainvoke.
S... | https://api.python.langchain.com/en/latest/llms/langchain.llms.fireworks.Fireworks.html |
80ab2c305674-4 | input is still being generated.
batch(inputs: List[Union[PromptValue, str, List[BaseMessage]]], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, return_exceptions: bool = False, **kwargs: Any) → List[str]¶
Default implementation of batch, which calls invoke N times.
Subclasses should override th... | https://api.python.langchain.com/en/latest/llms/langchain.llms.fireworks.Fireworks.html |
80ab2c305674-5 | classmethod from_orm(obj: Any) → Model¶
generate(prompts: List[str], stop: Optional[List[str]] = None, callbacks: Union[List[BaseCallbackHandler], BaseCallbackManager, None, List[Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]]]] = None, *, tags: Optional[Union[List[str], List[List[str]]]] = None, metada... | https://api.python.langchain.com/en/latest/llms/langchain.llms.fireworks.Fireworks.html |
80ab2c305674-6 | functionality, such as logging or streaming, throughout generation.
**kwargs – Arbitrary additional keyword arguments. These are usually passed
to the model provider API call.
Returns
An LLMResult, which contains a list of candidate Generations for each inputprompt and additional model provider-specific output.
classme... | https://api.python.langchain.com/en/latest/llms/langchain.llms.fireworks.Fireworks.html |
80ab2c305674-7 | classmethod is_lc_serializable() → bool¶
Is this class serializable?
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defa... | https://api.python.langchain.com/en/latest/llms/langchain.llms.fireworks.Fireworks.html |
80ab2c305674-8 | Pass a single string input to the model and return a string prediction.
Use this method when passing in raw text. If you want to pass in specifictypes of chat messages, use predict_messages.
Parameters
text – String input to pass to the model.
stop – Stop words to use when generating. Model output is cut off at the
fir... | https://api.python.langchain.com/en/latest/llms/langchain.llms.fireworks.Fireworks.html |
80ab2c305674-9 | stream(input: Union[PromptValue, str, List[BaseMessage]], config: Optional[RunnableConfig] = None, *, stop: Optional[List[str]] = None, **kwargs: Any) → Iterator[str][source]¶
Default implementation of stream, which calls invoke.
Subclasses should override this method if they support streaming output.
to_json() → Union... | https://api.python.langchain.com/en/latest/llms/langchain.llms.fireworks.Fireworks.html |
80ab2c305674-10 | property InputType: TypeAlias¶
Get the input type for this runnable.
property OutputType: Type[str]¶
Get the input type for this runnable.
property input_schema: Type[pydantic.main.BaseModel]¶
property lc_attributes: Dict¶
List of attribute names that should be included in the serialized kwargs.
These attributes must b... | https://api.python.langchain.com/en/latest/llms/langchain.llms.fireworks.Fireworks.html |
1b54b0ee7449-0 | langchain.llms.deepsparse.DeepSparse¶
class langchain.llms.deepsparse.DeepSparse[source]¶
Bases: LLM
Neural Magic DeepSparse LLM interface.
To use, you should have the deepsparse or deepsparse-nightly
python package installed. See https://github.com/neuralmagic/deepsparse
This interface let’s you deploy optimized LLMs ... | https://api.python.langchain.com/en/latest/llms/langchain.llms.deepsparse.DeepSparse.html |
1b54b0ee7449-1 | param verbose: bool [Optional]¶
Whether to print out response text.
__call__(prompt: str, stop: Optional[List[str]] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, **kwargs: Any) → str¶
Check Cache... | https://api.python.langchain.com/en/latest/llms/langchain.llms.deepsparse.DeepSparse.html |
1b54b0ee7449-2 | Asynchronously pass a sequence of prompts 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 ag... | https://api.python.langchain.com/en/latest/llms/langchain.llms.deepsparse.DeepSparse.html |
1b54b0ee7449-3 | Parameters
text – String input to pass to the model.
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.
Returns
Top model prediction as a string.... | https://api.python.langchain.com/en/latest/llms/langchain.llms.deepsparse.DeepSparse.html |
1b54b0ee7449-4 | Stream all output from a runnable, as reported to the callback system.
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... | https://api.python.langchain.com/en/latest/llms/langchain.llms.deepsparse.DeepSparse.html |
1b54b0ee7449-5 | 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... | https://api.python.langchain.com/en/latest/llms/langchain.llms.deepsparse.DeepSparse.html |
1b54b0ee7449-6 | 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... | https://api.python.langchain.com/en/latest/llms/langchain.llms.deepsparse.DeepSparse.html |
1b54b0ee7449-7 | 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_token_ids(text: str) → List[int]¶
Return the ordered ids of the tokens in a text.
Parameters
text – The string input to tokenize.
R... | https://api.python.langchain.com/en/latest/llms/langchain.llms.deepsparse.DeepSparse.html |
1b54b0ee7449-8 | 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 = False) → Model¶
classmethod parse_obj(obj: Any) → Model¶
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = No... | https://api.python.langchain.com/en/latest/llms/langchain.llms.deepsparse.DeepSparse.html |
1b54b0ee7449-9 | 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 = '#/definitions/{model}') → DictStrAny¶
classmethod schema_json(*, by_alias... | https://api.python.langchain.com/en/latest/llms/langchain.llms.deepsparse.DeepSparse.html |
1b54b0ee7449-10 | Bind config to a Runnable, returning a new Runnable.
with_fallbacks(fallbacks: ~typing.Sequence[~langchain.schema.runnable.base.Runnable[~langchain.schema.runnable.utils.Input, ~langchain.schema.runnable.utils.Output]], *, exceptions_to_handle: ~typing.Tuple[~typing.Type[BaseException], ...] = (<class 'Exception'>,)) →... | https://api.python.langchain.com/en/latest/llms/langchain.llms.deepsparse.DeepSparse.html |
9aeb3cf42b42-0 | langchain.llms.azureml_endpoint.AzureMLOnlineEndpoint¶
class langchain.llms.azureml_endpoint.AzureMLOnlineEndpoint[source]¶
Bases: LLM, BaseModel
Azure ML Online Endpoint models.
Example
azure_llm = AzureMLOnlineEndpoint(
endpoint_url="https://<your-endpoint>.<your_region>.inference.ml.azure.com/score",
endpoin... | https://api.python.langchain.com/en/latest/llms/langchain.llms.azureml_endpoint.AzureMLOnlineEndpoint.html |
9aeb3cf42b42-1 | param verbose: bool [Optional]¶
Whether to print out response text.
__call__(prompt: str, stop: Optional[List[str]] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, **kwargs: Any) → str¶
Check Cache... | https://api.python.langchain.com/en/latest/llms/langchain.llms.azureml_endpoint.AzureMLOnlineEndpoint.html |
9aeb3cf42b42-2 | Asynchronously pass a sequence of prompts 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 ag... | https://api.python.langchain.com/en/latest/llms/langchain.llms.azureml_endpoint.AzureMLOnlineEndpoint.html |
9aeb3cf42b42-3 | Parameters
text – String input to pass to the model.
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.
Returns
Top model prediction as a string.... | https://api.python.langchain.com/en/latest/llms/langchain.llms.azureml_endpoint.AzureMLOnlineEndpoint.html |
9aeb3cf42b42-4 | Stream all output from a runnable, as reported to the callback system.
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... | https://api.python.langchain.com/en/latest/llms/langchain.llms.azureml_endpoint.AzureMLOnlineEndpoint.html |
9aeb3cf42b42-5 | 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... | https://api.python.langchain.com/en/latest/llms/langchain.llms.azureml_endpoint.AzureMLOnlineEndpoint.html |
9aeb3cf42b42-6 | 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... | https://api.python.langchain.com/en/latest/llms/langchain.llms.azureml_endpoint.AzureMLOnlineEndpoint.html |
9aeb3cf42b42-7 | 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_token_ids(text: str) → List[int]¶
Return the ordered ids of the tokens in a text.
Parameters
text – The string input to tokenize.
R... | https://api.python.langchain.com/en/latest/llms/langchain.llms.azureml_endpoint.AzureMLOnlineEndpoint.html |
9aeb3cf42b42-8 | 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 = False) → Model¶
classmethod parse_obj(obj: Any) → Model¶
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = No... | https://api.python.langchain.com/en/latest/llms/langchain.llms.azureml_endpoint.AzureMLOnlineEndpoint.html |
9aeb3cf42b42-9 | 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 = '#/definitions/{model}') → DictStrAny¶
classmethod schema_json(*, by_alias... | https://api.python.langchain.com/en/latest/llms/langchain.llms.azureml_endpoint.AzureMLOnlineEndpoint.html |
9aeb3cf42b42-10 | Bind config to a Runnable, returning a new Runnable.
with_fallbacks(fallbacks: ~typing.Sequence[~langchain.schema.runnable.base.Runnable[~langchain.schema.runnable.utils.Input, ~langchain.schema.runnable.utils.Output]], *, exceptions_to_handle: ~typing.Tuple[~typing.Type[BaseException], ...] = (<class 'Exception'>,)) →... | https://api.python.langchain.com/en/latest/llms/langchain.llms.azureml_endpoint.AzureMLOnlineEndpoint.html |
66a93dbda112-0 | langchain.llms.modal.Modal¶
class langchain.llms.modal.Modal[source]¶
Bases: LLM
Modal large language models.
To use, you should have the modal-client python package installed.
Any parameters that are valid to be passed to the call can be passed
in, even if not explicitly saved on this class.
Example
from langchain.llm... | https://api.python.langchain.com/en/latest/llms/langchain.llms.modal.Modal.html |
66a93dbda112-1 | Default implementation of abatch, which calls ainvoke N times.
Subclasses should override this method if they can batch more efficiently.
async agenerate(prompts: List[str], stop: Optional[List[str]] = None, callbacks: Union[List[BaseCallbackHandler], BaseCallbackManager, None, List[Optional[Union[List[BaseCallbackHand... | https://api.python.langchain.com/en/latest/llms/langchain.llms.modal.Modal.html |
66a93dbda112-2 | callbacks – Callbacks to pass through. Used for executing additional
functionality, such as logging or streaming, throughout generation.
**kwargs – Arbitrary additional keyword arguments. These are usually passed
to the model provider API call.
Returns
An LLMResult, which contains a list of candidate Generations for ea... | https://api.python.langchain.com/en/latest/llms/langchain.llms.modal.Modal.html |
66a93dbda112-3 | **kwargs – Arbitrary additional keyword arguments. These are usually passed
to the model provider API call.
Returns
Top model prediction as a message.
async astream(input: Union[PromptValue, str, List[BaseMessage]], config: Optional[RunnableConfig] = None, *, stop: Optional[List[str]] = None, **kwargs: Any) → AsyncIter... | https://api.python.langchain.com/en/latest/llms/langchain.llms.modal.Modal.html |
66a93dbda112-4 | input is still being generated.
batch(inputs: List[Union[PromptValue, str, List[BaseMessage]]], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, return_exceptions: bool = False, **kwargs: Any) → List[str]¶
Default implementation of batch, which calls invoke N times.
Subclasses should override th... | https://api.python.langchain.com/en/latest/llms/langchain.llms.modal.Modal.html |
66a93dbda112-5 | classmethod from_orm(obj: Any) → Model¶
generate(prompts: List[str], stop: Optional[List[str]] = None, callbacks: Union[List[BaseCallbackHandler], BaseCallbackManager, None, List[Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]]]] = None, *, tags: Optional[Union[List[str], List[List[str]]]] = None, metada... | https://api.python.langchain.com/en/latest/llms/langchain.llms.modal.Modal.html |
66a93dbda112-6 | functionality, such as logging or streaming, throughout generation.
**kwargs – Arbitrary additional keyword arguments. These are usually passed
to the model provider API call.
Returns
An LLMResult, which contains a list of candidate Generations for each inputprompt and additional model provider-specific output.
classme... | https://api.python.langchain.com/en/latest/llms/langchain.llms.modal.Modal.html |
66a93dbda112-7 | classmethod is_lc_serializable() → bool¶
Is this class serializable?
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defa... | https://api.python.langchain.com/en/latest/llms/langchain.llms.modal.Modal.html |
66a93dbda112-8 | Pass a single string input to the model and return a string prediction.
Use this method when passing in raw text. If you want to pass in specifictypes of chat messages, use predict_messages.
Parameters
text – String input to pass to the model.
stop – Stop words to use when generating. Model output is cut off at the
fir... | https://api.python.langchain.com/en/latest/llms/langchain.llms.modal.Modal.html |
66a93dbda112-9 | stream(input: Union[PromptValue, str, List[BaseMessage]], config: Optional[RunnableConfig] = None, *, stop: Optional[List[str]] = None, **kwargs: Any) → Iterator[str]¶
Default implementation of stream, which calls invoke.
Subclasses should override this method if they support streaming output.
to_json() → Union[Seriali... | https://api.python.langchain.com/en/latest/llms/langchain.llms.modal.Modal.html |
66a93dbda112-10 | property InputType: TypeAlias¶
Get the input type for this runnable.
property OutputType: Type[str]¶
Get the input type for this runnable.
property input_schema: Type[pydantic.main.BaseModel]¶
property lc_attributes: Dict¶
List of attribute names that should be included in the serialized kwargs.
These attributes must b... | https://api.python.langchain.com/en/latest/llms/langchain.llms.modal.Modal.html |
776ae6301f87-0 | langchain_experimental.llms.anthropic_functions.TagParser¶
class langchain_experimental.llms.anthropic_functions.TagParser[source]¶
A heavy-handed solution, but it’s fast for prototyping.
Might be re-implemented later to restrict scope to the limited grammar, and
more efficiency.
Uses an HTML parser to parse a limited ... | https://api.python.langchain.com/en/latest/llms/langchain_experimental.llms.anthropic_functions.TagParser.html |
776ae6301f87-1 | parse_declaration(i)
parse_endtag(i)
parse_html_declaration(i)
parse_marked_section(i[, report])
parse_pi(i)
parse_starttag(i)
reset()
Reset this instance.
set_cdata_mode(elem)
unknown_decl(data)
updatepos(i, j)
__init__() → None[source]¶
A heavy-handed solution, but it’s fast for prototyping.
Might be re-implemented l... | https://api.python.langchain.com/en/latest/llms/langchain_experimental.llms.anthropic_functions.TagParser.html |
776ae6301f87-2 | Hook when a tag is closed.
handle_entityref(name)¶
handle_pi(data)¶
handle_startendtag(tag, attrs)¶
handle_starttag(tag: str, attrs: Any) → None[source]¶
Hook when a new tag is encountered.
parse_bogus_comment(i, report=1)¶
parse_comment(i, report=1)¶
parse_declaration(i)¶
parse_endtag(i)¶
parse_html_declaration(i)¶
pa... | https://api.python.langchain.com/en/latest/llms/langchain_experimental.llms.anthropic_functions.TagParser.html |
baef2ee3d166-0 | langchain.llms.aviary.AviaryBackend¶
class langchain.llms.aviary.AviaryBackend(backend_url: str, bearer: str)[source]¶
Aviary backend.
backend_url¶
The URL for the Aviary backend.
Type
str
bearer¶
The bearer token for the Aviary backend.
Type
str
Attributes
backend_url
bearer
Methods
__init__(backend_url, bearer)
from_... | https://api.python.langchain.com/en/latest/llms/langchain.llms.aviary.AviaryBackend.html |
cd5c2c04e80d-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... | https://api.python.langchain.com/en/latest/llms/langchain.llms.huggingface_text_gen_inference.HuggingFaceTextGenInference.html |
cd5c2c04e80d-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... | https://api.python.langchain.com/en/latest/llms/langchain.llms.huggingface_text_gen_inference.HuggingFaceTextGenInference.html |
cd5c2c04e80d-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... | https://api.python.langchain.com/en/latest/llms/langchain.llms.huggingface_text_gen_inference.HuggingFaceTextGenInference.html |
cd5c2c04e80d-3 | Subclasses should override this method if they can batch more efficiently.
async agenerate(prompts: List[str], stop: Optional[List[str]] = None, callbacks: Union[List[BaseCallbackHandler], BaseCallbackManager, None, List[Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]]]] = None, *, tags: Optional[Union[L... | https://api.python.langchain.com/en/latest/llms/langchain.llms.huggingface_text_gen_inference.HuggingFaceTextGenInference.html |
cd5c2c04e80d-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... | https://api.python.langchain.com/en/latest/llms/langchain.llms.huggingface_text_gen_inference.HuggingFaceTextGenInference.html |
cd5c2c04e80d-5 | to the model provider API call.
Returns
Top model prediction as a message.
async astream(input: Union[PromptValue, str, List[BaseMessage]], config: Optional[RunnableConfig] = None, *, stop: Optional[List[str]] = None, **kwargs: Any) → AsyncIterator[str]¶
Default implementation of astream, which calls ainvoke.
Subclasse... | https://api.python.langchain.com/en/latest/llms/langchain.llms.huggingface_text_gen_inference.HuggingFaceTextGenInference.html |
cd5c2c04e80d-6 | input is still being generated.
batch(inputs: List[Union[PromptValue, str, List[BaseMessage]]], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, return_exceptions: bool = False, **kwargs: Any) → List[str]¶
Default implementation of batch, which calls invoke N times.
Subclasses should override th... | https://api.python.langchain.com/en/latest/llms/langchain.llms.huggingface_text_gen_inference.HuggingFaceTextGenInference.html |
cd5c2c04e80d-7 | classmethod from_orm(obj: Any) → Model¶
generate(prompts: List[str], stop: Optional[List[str]] = None, callbacks: Union[List[BaseCallbackHandler], BaseCallbackManager, None, List[Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]]]] = None, *, tags: Optional[Union[List[str], List[List[str]]]] = None, metada... | https://api.python.langchain.com/en/latest/llms/langchain.llms.huggingface_text_gen_inference.HuggingFaceTextGenInference.html |
cd5c2c04e80d-8 | functionality, such as logging or streaming, throughout generation.
**kwargs – Arbitrary additional keyword arguments. These are usually passed
to the model provider API call.
Returns
An LLMResult, which contains a list of candidate Generations for each inputprompt and additional model provider-specific output.
classme... | https://api.python.langchain.com/en/latest/llms/langchain.llms.huggingface_text_gen_inference.HuggingFaceTextGenInference.html |
cd5c2c04e80d-9 | classmethod is_lc_serializable() → bool¶
Is this class serializable?
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defa... | https://api.python.langchain.com/en/latest/llms/langchain.llms.huggingface_text_gen_inference.HuggingFaceTextGenInference.html |
cd5c2c04e80d-10 | Pass a single string input to the model and return a string prediction.
Use this method when passing in raw text. If you want to pass in specifictypes of chat messages, use predict_messages.
Parameters
text – String input to pass to the model.
stop – Stop words to use when generating. Model output is cut off at the
fir... | https://api.python.langchain.com/en/latest/llms/langchain.llms.huggingface_text_gen_inference.HuggingFaceTextGenInference.html |
cd5c2c04e80d-11 | stream(input: Union[PromptValue, str, List[BaseMessage]], config: Optional[RunnableConfig] = None, *, stop: Optional[List[str]] = None, **kwargs: Any) → Iterator[str]¶
Default implementation of stream, which calls invoke.
Subclasses should override this method if they support streaming output.
to_json() → Union[Seriali... | https://api.python.langchain.com/en/latest/llms/langchain.llms.huggingface_text_gen_inference.HuggingFaceTextGenInference.html |
cd5c2c04e80d-12 | property InputType: TypeAlias¶
Get the input type for this runnable.
property OutputType: Type[str]¶
Get the input type for this runnable.
property input_schema: Type[pydantic.main.BaseModel]¶
property lc_attributes: Dict¶
List of attribute names that should be included in the serialized kwargs.
These attributes must b... | https://api.python.langchain.com/en/latest/llms/langchain.llms.huggingface_text_gen_inference.HuggingFaceTextGenInference.html |
9a8d0892b65a-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:... | https://api.python.langchain.com/en/latest/llms/langchain.llms.openai.BaseOpenAI.html |
9a8d0892b65a-1 | Model name to use.
param n: int = 1¶
How many completions to generate for each prompt.
param openai_api_base: Optional[str] = None¶
param openai_api_key: Optional[str] = None¶
param openai_organization: Optional[str] = None¶
param openai_proxy: Optional[str] = None¶
param presence_penalty: float = 0¶
Penalizes repeated... | https://api.python.langchain.com/en/latest/llms/langchain.llms.openai.BaseOpenAI.html |
9a8d0892b65a-2 | param verbose: bool [Optional]¶
Whether to print out response text.
__call__(prompt: str, stop: Optional[List[str]] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, **kwargs: Any) → str¶
Check Cache... | https://api.python.langchain.com/en/latest/llms/langchain.llms.openai.BaseOpenAI.html |
9a8d0892b65a-3 | Asynchronously pass a sequence of prompts 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 ag... | https://api.python.langchain.com/en/latest/llms/langchain.llms.openai.BaseOpenAI.html |
9a8d0892b65a-4 | Parameters
text – String input to pass to the model.
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.
Returns
Top model prediction as a string.... | https://api.python.langchain.com/en/latest/llms/langchain.llms.openai.BaseOpenAI.html |
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