id stringlengths 14 16 | text stringlengths 36 2.73k | source stringlengths 49 117 |
|---|---|---|
f8a76bd808b1-66 | Run the LLM on the given prompt and input.
async agenerate_prompt(prompts: List[langchain.schema.PromptValue], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None) β langchain.schema.LLMResult#
Take in a li... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-67 | Returns
new model instance
dict(**kwargs: Any) β Dict#
Return a dictionary of the LLM.
generate(prompts: List[str], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None) β langchain.schema.LLMResult#
Run the... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-68 | encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
predict(text: str, *, stop: Optional[Sequence[str]] = None) β str#
Predict text from text.
predict_messages(messages: List[langchain.schema.BaseMessage], *, stop: Optional[Sequence[str]] = None) β langchain.schema... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-69 | Task to call the model with.
Should be a task that returns generated_text or summary_text.
field verbose: bool [Optional]#
Whether to print out response text.
__call__(prompt: str, stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.Ba... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-70 | Behaves as if Config.extra = βallowβ 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) β Model#
Duplicate a model, optionally... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-71 | get_token_ids(text: str) β List[int]#
Get the token present in the text.
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_... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-72 | Example using from_model_id:from langchain.llms import HuggingFacePipeline
hf = HuggingFacePipeline.from_model_id(
model_id="gpt2",
task="text-generation",
pipeline_kwargs={"max_new_tokens": 10},
)
Example passing pipeline in directly:from langchain.llms import HuggingFacePipeline
from transformers import A... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-73 | Run the LLM on the given prompt and input.
async agenerate_prompt(prompts: List[langchain.schema.PromptValue], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None) β langchain.schema.LLMResult#
Take in a li... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-74 | Returns
new model instance
dict(**kwargs: Any) β Dict#
Return a dictionary of the LLM.
classmethod from_model_id(model_id: str, task: str, device: int = - 1, model_kwargs: Optional[dict] = None, pipeline_kwargs: Optional[dict] = None, **kwargs: Any) β langchain.llms.base.LLM[source]#
Construct the pipeline object from ... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-75 | Get the token present in the text.
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: ... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-76 | Attributes:
- max_new_tokens: The maximum number of tokens to generate.
- top_k: The number of top-k tokens to consider when generating text.
- top_p: The cumulative probability threshold for generating text.
- typical_p: The typical probability threshold for generating text.
- temperature: The temperature to use when ... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-77 | Run the LLM on the given prompt and input.
async agenerate_prompt(prompts: List[langchain.schema.PromptValue], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None) β langchain.schema.LLMResult#
Take in a li... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-78 | Returns
new model instance
dict(**kwargs: Any) β Dict#
Return a dictionary of the LLM.
generate(prompts: List[str], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None) β langchain.schema.LLMResult#
Run the... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-79 | encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
predict(text: str, *, stop: Optional[Sequence[str]] = None) β str#
Predict text from text.
predict_messages(messages: List[langchain.schema.BaseMessage], *, stop: Optional[Sequence[str]] = None) β langchain.schema... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-80 | Run the LLM on the given prompt and input.
async agenerate_prompt(prompts: List[langchain.schema.PromptValue], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None) β langchain.schema.LLMResult#
Take in a li... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-81 | Returns
new model instance
dict(**kwargs: Any) β Dict#
Return a dictionary of the LLM.
generate(prompts: List[str], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None) β langchain.schema.LLMResult#
Run the... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-82 | encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
predict(text: str, *, stop: Optional[Sequence[str]] = None) β str#
Predict text from text.
predict_messages(messages: List[langchain.schema.BaseMessage], *, stop: Optional[Sequence[str]] = None) β langchain.schema... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-83 | field logprobs: Optional[int] = None#
The number of logprobs to return. If None, no logprobs are returned.
field lora_base: Optional[str] = None#
The path to the Llama LoRA base model.
field lora_path: Optional[str] = None#
The path to the Llama LoRA. If None, no LoRa is loaded.
field max_tokens: Optional[int] = 256#
T... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-84 | field temperature: Optional[float] = 0.8#
The temperature to use for sampling.
field top_k: Optional[int] = 40#
The top-k value to use for sampling.
field top_p: Optional[float] = 0.95#
The top-p value to use for sampling.
field use_mlock: bool = False#
Force system to keep model in RAM.
field use_mmap: Optional[bool] ... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-85 | Predict text from text.
async apredict_messages(messages: List[langchain.schema.BaseMessage], *, stop: Optional[Sequence[str]] = None) β langchain.schema.BaseMessage#
Predict message from messages.
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) β Model#
Creates a new model setting __dict__ a... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-86 | Run the LLM on the given prompt and input.
generate_prompt(prompts: List[langchain.schema.PromptValue], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None) β langchain.schema.LLMResult#
Take in a list of p... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-87 | Save the LLM.
Parameters
file_path β Path to file to save the LLM to.
Example:
.. code-block:: python
llm.save(file_path=βpath/llm.yamlβ)
stream(prompt: str, stop: Optional[List[str]] = None, run_manager: Optional[langchain.callbacks.manager.CallbackManagerForLLMRun] = None) β Generator[Dict, None, None][source]#
Yield... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-88 | 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
Validators
build_extra Β» all fields
raise_deprecation Β» all fields
set_verbose Β» verbose
field endpoint_url: str = ''#
model end... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-89 | Predict message from messages.
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) β 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 = βallowβ was set ... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-90 | Take in a list of prompt values and return an LLMResult.
get_num_tokens(text: str) β int#
Get the number of tokens present in the text.
get_num_tokens_from_messages(messages: List[langchain.schema.BaseMessage]) β int#
Get the number of tokens in the message.
get_token_ids(text: str) β List[int]#
Get the token present i... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-91 | Try to update ForwardRefs on fields based on this Model, globalns and localns.
pydantic model langchain.llms.MosaicML[source]#
Wrapper around MosaicMLβs LLM inference service.
To use, you should have the
environment variable MOSAICML_API_TOKEN set with your API token, or pass
it as a named parameter to the constructor.... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-92 | Check Cache and run the LLM on the given prompt and input.
async agenerate(prompts: List[str], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None) β langchain.schema.LLMResult#
Run the LLM on the given pro... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-93 | Parameters
include β fields to include in new model
exclude β fields to exclude from new model, as with values this takes precedence over include
update β 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 β set to True to make a deep co... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-94 | Get the token present in the text.
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: ... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-95 | nlpcloud = NLPCloud(model="gpt-neox-20b")
Validators
raise_deprecation Β» all fields
set_verbose Β» verbose
validate_environment Β» all fields
field bad_words: List[str] = []#
List of tokens not allowed to be generated.
field do_sample: bool = True#
Whether to use sampling (True) or greedy decoding.
field early_stopping: ... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-96 | Total probability mass of tokens to consider at each step.
field verbose: bool [Optional]#
Whether to print out response text.
__call__(prompt: str, stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None) β st... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-97 | Behaves as if Config.extra = βallowβ 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) β Model#
Duplicate a model, optionally... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-98 | get_token_ids(text: str) β List[int]#
Get the token present in the text.
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_... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-99 | Any parameters that are valid to be passed to the openai.create call can be passed
in, even if not explicitly saved on this class.
Example
from langchain.llms import OpenAI
openai = OpenAI(model_name="text-davinci-003")
Validators
build_extra Β» all fields
raise_deprecation Β» all fields
set_verbose Β» verbose
validate_en... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-100 | field presence_penalty: float = 0#
Penalizes repeated tokens.
field request_timeout: Optional[Union[float, Tuple[float, float]]] = None#
Timeout for requests to OpenAI completion API. Default is 600 seconds.
field streaming: bool = False#
Whether to stream the results or not.
field temperature: float = 0.7#
What sampli... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-101 | Predict message from messages.
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) β 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 = βallowβ was set ... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-102 | Run the LLM on the given prompt and input.
generate_prompt(prompts: List[langchain.schema.PromptValue], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None) β langchain.schema.LLMResult#
Take in a list of p... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-103 | Parameters
prompt β The prompt to pass into the model.
Returns
The maximum number of tokens to generate for a prompt.
Example
max_tokens = openai.max_token_for_prompt("Tell me a joke.")
modelname_to_contextsize(modelname: str) β int#
Calculate the maximum number of tokens possible to generate for a model.
Parameters
mo... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-104 | for token in generator:
yield token
classmethod update_forward_refs(**localns: Any) β None#
Try to update ForwardRefs on fields based on this Model, globalns and localns.
pydantic model langchain.llms.OpenAIChat[source]#
Wrapper around OpenAI Chat large language models.
To use, you should have the openai python pac... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-105 | field verbose: bool [Optional]#
Whether to print out response text.
__call__(prompt: str, stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None) β str#
Check Cache and run the LLM on the given prompt and inpu... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-106 | Behaves as if Config.extra = βallowβ 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) β Model#
Duplicate a model, optionally... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-107 | get_token_ids(text: str) β List[int][source]#
Get the token IDs using the tiktoken package.
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: boo... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-108 | Set of special tokens that are allowedγ
field batch_size: int = 20#
Batch size to use when passing multiple documents to generate.
field best_of: int = 1#
Generates best_of completions server-side and returns the βbestβ.
field disallowed_special: Union[Literal['all'], Collection[str]] = 'all'#
Set of special tokens tha... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-109 | field verbose: bool [Optional]#
Whether to print out response text.
__call__(prompt: str, stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None) β str#
Check Cache and run the LLM on the given prompt and inpu... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-110 | Behaves as if Config.extra = βallowβ 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) β Model#
Duplicate a model, optionally... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-111 | Get the number of tokens present in the text.
get_num_tokens_from_messages(messages: List[langchain.schema.BaseMessage]) β int#
Get the number of tokens in the message.
get_sub_prompts(params: Dict[str, Any], prompts: List[str], stop: Optional[List[str]] = None) β List[List[str]]#
Get the sub prompts for llm call.
get_... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-112 | Example
max_tokens = openai.modelname_to_contextsize("text-davinci-003")
predict(text: str, *, stop: Optional[Sequence[str]] = None) β str#
Predict text from text.
predict_messages(messages: List[langchain.schema.BaseMessage], *, stop: Optional[Sequence[str]] = None) β langchain.schema.BaseMessage#
Predict message from... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-113 | Any parameters that are valid to be passed to the call can be passed
in, even if not explicitly saved on this class.
Example
Validators
build_extra Β» all fields
raise_deprecation Β» all fields
set_verbose Β» verbose
validate_environment Β» all fields
field client: Any = None#
The client to use for the API calls.
field do_... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-114 | Check Cache and run the LLM on the given prompt and input.
async agenerate(prompts: List[str], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None) β langchain.schema.LLMResult#
Run the LLM on the given pro... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-115 | Parameters
include β fields to include in new model
exclude β fields to exclude from new model, as with values this takes precedence over include
update β 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 β set to True to make a deep co... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-116 | Get the token present in the text.
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: ... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-117 | in, even if not explicitly saved on this class.
Example
Validators
build_extra Β» all fields
raise_deprecation Β» all fields
set_verbose Β» verbose
validate_environment Β» all fields
field pipeline_key: str = ''#
The id or tag of the target pipeline
field pipeline_kwargs: Dict[str, Any] [Optional]#
Holds any pipeline param... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-118 | 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 = βallowβ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclu... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-119 | Get the number of tokens present in the text.
get_num_tokens_from_messages(messages: List[langchain.schema.BaseMessage]) β int#
Get the number of tokens in the message.
get_token_ids(text: str) β List[int]#
Get the token present in the text.
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, ... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-120 | Wrapper around Prediction Guard large language models.
To use, you should have the predictionguard python package installed, and the
environment variable PREDICTIONGUARD_TOKEN set with your access token, or pass
it as a named parameter to the constructor.
.. rubric:: Example
Validators
raise_deprecation Β» all fields
se... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-121 | Predict text from text.
async apredict_messages(messages: List[langchain.schema.BaseMessage], *, stop: Optional[Sequence[str]] = None) β langchain.schema.BaseMessage#
Predict message from messages.
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) β Model#
Creates a new model setting __dict__ a... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-122 | Run the LLM on the given prompt and input.
generate_prompt(prompts: List[langchain.schema.PromptValue], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None) β langchain.schema.LLMResult#
Take in a list of p... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-123 | Save the LLM.
Parameters
file_path β Path to file to save the LLM to.
Example:
.. code-block:: python
llm.save(file_path=βpath/llm.yamlβ)
classmethod update_forward_refs(**localns: Any) β None#
Try to update ForwardRefs on fields based on this Model, globalns and localns.
pydantic model langchain.llms.PromptLayerOpenAI... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-124 | Run the LLM on the given prompt and input.
async agenerate_prompt(prompts: List[langchain.schema.PromptValue], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None) β langchain.schema.LLMResult#
Take in a li... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-125 | deep β set to True to make a deep copy of the model
Returns
new model instance
create_llm_result(choices: Any, prompts: List[str], token_usage: Dict[str, int]) β langchain.schema.LLMResult#
Create the LLMResult from the choices and prompts.
dict(**kwargs: Any) β Dict#
Return a dictionary of the LLM.
generate(prompts: L... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-126 | Get the token IDs using the tiktoken package.
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exc... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-127 | Prepare the params for streaming.
save(file_path: Union[pathlib.Path, str]) β None#
Save the LLM.
Parameters
file_path β Path to file to save the LLM to.
Example:
.. code-block:: python
llm.save(file_path=βpath/llm.yamlβ)
stream(prompt: str, stop: Optional[List[str]] = None) β Generator#
Call OpenAI with streaming flag... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-128 | Generation object.
Example
from langchain.llms import PromptLayerOpenAIChat
openaichat = PromptLayerOpenAIChat(model_name="gpt-3.5-turbo")
Validators
build_extra Β» all fields
raise_deprecation Β» all fields
set_verbose Β» verbose
validate_environment Β» all fields
field allowed_special: Union[Literal['all'], AbstractSet[s... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-129 | Run the LLM on the given prompt and input.
async agenerate_prompt(prompts: List[langchain.schema.PromptValue], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None) β langchain.schema.LLMResult#
Take in a li... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-130 | Returns
new model instance
dict(**kwargs: Any) β Dict#
Return a dictionary of the LLM.
generate(prompts: List[str], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None) β langchain.schema.LLMResult#
Run the... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-131 | encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
predict(text: str, *, stop: Optional[Sequence[str]] = None) β str#
Predict text from text.
predict_messages(messages: List[langchain.schema.BaseMessage], *, stop: Optional[Sequence[str]] = None) β langchain.schema... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-132 | in the text so far, decreasing the modelβs likelihood to repeat the same
line verbatim..
field penalty_alpha_presence: float = 0.4#
Positive values penalize new tokens based on whether they appear
in the text so far, increasing the modelβs likelihood to talk about
new topics..
field rwkv_verbose: bool = True#
Print deb... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-133 | Predict text from text.
async apredict_messages(messages: List[langchain.schema.BaseMessage], *, stop: Optional[Sequence[str]] = None) β langchain.schema.BaseMessage#
Predict message from messages.
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) β Model#
Creates a new model setting __dict__ a... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-134 | Run the LLM on the given prompt and input.
generate_prompt(prompts: List[langchain.schema.PromptValue], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None) β langchain.schema.LLMResult#
Take in a list of p... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-135 | Save the LLM.
Parameters
file_path β Path to file to save the LLM to.
Example:
.. code-block:: python
llm.save(file_path=βpath/llm.yamlβ)
classmethod update_forward_refs(**localns: Any) β None#
Try to update ForwardRefs on fields based on this Model, globalns and localns.
pydantic model langchain.llms.Replicate[source]... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-136 | Run the LLM on the given prompt and input.
async agenerate_prompt(prompts: List[langchain.schema.PromptValue], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None) β langchain.schema.LLMResult#
Take in a li... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-137 | Returns
new model instance
dict(**kwargs: Any) β Dict#
Return a dictionary of the LLM.
generate(prompts: List[str], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None) β langchain.schema.LLMResult#
Run the... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-138 | encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
predict(text: str, *, stop: Optional[Sequence[str]] = None) β str#
Predict text from text.
predict_messages(messages: List[langchain.schema.BaseMessage], *, stop: Optional[Sequence[str]] = None) β langchain.schema... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-139 | The content handler class that provides an input and
output transform functions to handle formats between LLM
and the endpoint.
field credentials_profile_name: Optional[str] = None#
The name of the profile in the ~/.aws/credentials or ~/.aws/config files, which
has either access keys or role information specified.
If n... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-140 | Run the LLM on the given prompt and input.
async agenerate_prompt(prompts: List[langchain.schema.PromptValue], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None) β langchain.schema.LLMResult#
Take in a li... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-141 | Returns
new model instance
dict(**kwargs: Any) β Dict#
Return a dictionary of the LLM.
generate(prompts: List[str], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None) β langchain.schema.LLMResult#
Run the... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-142 | encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
predict(text: str, *, stop: Optional[Sequence[str]] = None) β str#
Predict text from text.
predict_messages(messages: List[langchain.schema.BaseMessage], *, stop: Optional[Sequence[str]] = None) β langchain.schema... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-143 | hardware=gpu
)
Example passing fn that generates a pipeline (bc the pipeline is not serializable):from langchain.llms import SelfHostedHuggingFaceLLM
from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
import runhouse as rh
def get_pipeline():
model_id = "gpt2"
tokenizer = AutoTokenizer.from_... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-144 | Hugging Face task (βtext-generationβ, βtext2text-generationβ or
βsummarizationβ).
field verbose: bool [Optional]#
Whether to print out response text.
__call__(prompt: str, stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbac... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-145 | Behaves as if Config.extra = βallowβ 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) β Model#
Duplicate a model, optionally... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-146 | Take in a list of prompt values and return an LLMResult.
get_num_tokens(text: str) β int#
Get the number of tokens present in the text.
get_num_tokens_from_messages(messages: List[langchain.schema.BaseMessage]) β int#
Get the number of tokens in the message.
get_token_ids(text: str) β List[int]#
Get the token present i... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-147 | Try to update ForwardRefs on fields based on this Model, globalns and localns.
pydantic model langchain.llms.SelfHostedPipeline[source]#
Run model inference on self-hosted remote hardware.
Supported hardware includes auto-launched instances on AWS, GCP, Azure,
and Lambda, as well as servers specified
by IP address and ... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-148 | hardware=gpu,
model_reqs=["./", "torch", "transformers"],
)
Example passing model path for larger models:from langchain.llms import SelfHostedPipeline
import runhouse as rh
import pickle
from transformers import pipeline
generator = pipeline(model="gpt2")
rh.blob(pickle.dumps(generator), path="models/pipeline.pkl"
... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-149 | Run the LLM on the given prompt and input.
async agenerate_prompt(prompts: List[langchain.schema.PromptValue], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None) β langchain.schema.LLMResult#
Take in a li... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-150 | Returns
new model instance
dict(**kwargs: Any) β Dict#
Return a dictionary of the LLM.
classmethod from_pipeline(pipeline: Any, hardware: Any, model_reqs: Optional[List[str]] = None, device: int = 0, **kwargs: Any) β langchain.llms.base.LLM[source]#
Init the SelfHostedPipeline from a pipeline object or string.
generate... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-151 | Get the token present in the text.
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: ... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-152 | stochasticai = StochasticAI(api_url="")
Validators
build_extra Β» all fields
raise_deprecation Β» all fields
set_verbose Β» verbose
validate_environment Β» all fields
field api_url: str = ''#
Model name to use.
field model_kwargs: Dict[str, Any] [Optional]#
Holds any model parameters valid for create call not
explicitly sp... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-153 | 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 = βallowβ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclu... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-154 | Get the number of tokens present in the text.
get_num_tokens_from_messages(messages: List[langchain.schema.BaseMessage]) β int#
Get the number of tokens in the message.
get_token_ids(text: str) β List[int]#
Get the token present in the text.
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, ... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-155 | Wrapper around Google Vertex AI large language models.
Validators
raise_deprecation Β» all fields
set_verbose Β» verbose
validate_environment Β» all fields
field credentials: Any = None#
The default custom credentials (google.auth.credentials.Credentials) to use
field location: str = 'us-central1'#
The default location to... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-156 | Run the LLM on the given prompt and input.
async agenerate_prompt(prompts: List[langchain.schema.PromptValue], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None) β langchain.schema.LLMResult#
Take in a li... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-157 | Returns
new model instance
dict(**kwargs: Any) β Dict#
Return a dictionary of the LLM.
generate(prompts: List[str], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None) β langchain.schema.LLMResult#
Run the... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-158 | encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
predict(text: str, *, stop: Optional[Sequence[str]] = None) β str#
Predict text from text.
predict_messages(messages: List[langchain.schema.BaseMessage], *, stop: Optional[Sequence[str]] = None) β langchain.schema... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-159 | field model_id: str = 'palmyra-instruct'#
Model name to use.
field n: Optional[int] = None#
How many completions to generate.
field presence_penalty: Optional[float] = None#
Penalizes repeated tokens regardless of frequency.
field repetition_penalty: Optional[float] = None#
Penalizes repeated tokens according to freque... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-160 | Take in a list of prompt values and return an LLMResult.
async apredict(text: str, *, stop: Optional[Sequence[str]] = None) β str#
Predict text from text.
async apredict_messages(messages: List[langchain.schema.BaseMessage], *, stop: Optional[Sequence[str]] = None) β langchain.schema.BaseMessage#
Predict message from m... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-161 | Run the LLM on the given prompt and input.
generate_prompt(prompts: List[langchain.schema.PromptValue], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None) β langchain.schema.LLMResult#
Take in a list of p... | https://python.langchain.com/en/latest/reference/modules/llms.html |
f8a76bd808b1-162 | Save the LLM.
Parameters
file_path β Path to file to save the LLM to.
Example:
.. code-block:: python
llm.save(file_path=βpath/llm.yamlβ)
classmethod update_forward_refs(**localns: Any) β None#
Try to update ForwardRefs on fields based on this Model, globalns and localns.
previous
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Chat Models
By Harrison Ch... | https://python.langchain.com/en/latest/reference/modules/llms.html |
10ba8875dd49-0 | .rst
.pdf
Embeddings
Embeddings#
Wrappers around embedding modules.
pydantic model langchain.embeddings.AlephAlphaAsymmetricSemanticEmbedding[source]#
Wrapper for Aleph Alphaβs Asymmetric Embeddings
AA provides you with an endpoint to embed a document and a query.
The models were optimized to make the embeddings of doc... | https://python.langchain.com/en/latest/reference/modules/embeddings.html |
10ba8875dd49-1 | embed_documents(texts: List[str]) β List[List[float]][source]#
Call out to Aleph Alphaβs asymmetric Document endpoint.
Parameters
texts β The list of texts to embed.
Returns
List of embeddings, one for each text.
embed_query(text: str) β List[float][source]#
Call out to Aleph Alphaβs asymmetric, query embedding endpoin... | https://python.langchain.com/en/latest/reference/modules/embeddings.html |
10ba8875dd49-2 | Model name to use.
field truncate: Optional[str] = None#
Truncate embeddings that are too long from start or end (βNONEβ|βSTARTβ|βENDβ)
embed_documents(texts: List[str]) β List[List[float]][source]#
Call out to Cohereβs embedding endpoint.
Parameters
texts β The list of texts to embed.
Returns
List of embeddings, one f... | https://python.langchain.com/en/latest/reference/modules/embeddings.html |
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