id stringlengths 14 16 | text stringlengths 31 2.41k | source stringlengths 53 121 |
|---|---|---|
a44a60c1f5be-161 | Predict message from messages.
Parameters
messages (List[langchain.schema.BaseMessage]) β
stop (Optional[Sequence[str]]) β
kwargs (Any) β
Return type
langchain.schema.BaseMessage
save(file_path)ο
Save the LLM.
Parameters
file_path (Union[pathlib.Path, str]) β Path to file to save the LLM to.
Return type
None
Example... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-162 | property lc_serializable: boolο
Return whether or not the class is serializable.
class langchain.llms.LlamaCpp(*, cache=None, verbose=None, callbacks=None, callback_manager=None, tags=None, client=None, model_path, lora_base=None, lora_path=None, n_ctx=512, n_parts=- 1, seed=- 1, f16_kv=True, logits_all=False, vocab_on... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-163 | n_ctx (int) β
n_parts (int) β
seed (int) β
f16_kv (bool) β
logits_all (bool) β
vocab_only (bool) β
use_mlock (bool) β
n_threads (Optional[int]) β
n_batch (Optional[int]) β
n_gpu_layers (Optional[int]) β
suffix (Optional[str]) β
max_tokens (Optional[int]) β
temperature (Optional[float]) β
top_p (Optional[fl... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-164 | attribute max_tokens: Optional[int] = 256ο
The maximum number of tokens to generate.
attribute model_path: str [Required]ο
The path to the Llama model file.
attribute n_batch: Optional[int] = 8ο
Number of tokens to process in parallel.
Should be a number between 1 and n_ctx.
attribute n_ctx: int = 512ο
Token context wi... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-165 | The top-p value to use for sampling.
attribute use_mlock: bool = Falseο
Force system to keep model in RAM.
attribute use_mmap: Optional[bool] = Trueο
Whether to keep the model loaded in RAM
attribute verbose: bool [Optional]ο
Whether to print out response text.
attribute vocab_only: bool = Falseο
Only load the vocabula... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-166 | kwargs (Any) β
Return type
langchain.schema.LLMResult
async apredict(text, *, stop=None, **kwargs)ο
Predict text from text.
Parameters
text (str) β
stop (Optional[Sequence[str]]) β
kwargs (Any) β
Return type
str
async apredict_messages(messages, *, stop=None, **kwargs)ο
Predict message from messages.
Parameters
mes... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-167 | Returns
new model instance
Return type
Model
dict(**kwargs)ο
Return a dictionary of the LLM.
Parameters
kwargs (Any) β
Return type
Dict
generate(prompts, stop=None, callbacks=None, *, tags=None, **kwargs)ο
Run the LLM on the given prompt and input.
Parameters
prompts (List[str]) β
stop (Optional[List[str]]) β
callba... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-168 | Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
Parameters
include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) β
exclude (Optional[Union[AbstractSetIntStr, Map... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-169 | Once that happens, this interface could change.
It also calls the callback managerβs on_llm_new_token event with
similar parameters to the OpenAI LLM class method of the same name.
Args:prompt: The prompts to pass into the model.
stop: Optional list of stop words to use when generating.
Returns:A generator representing... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-170 | Return a map of constructor argument names to secret ids.
eg. {βopenai_api_keyβ: βOPENAI_API_KEYβ}
property lc_serializable: boolο
Return whether or not the class is serializable.
class langchain.llms.TextGen(*, cache=None, verbose=None, callbacks=None, callback_manager=None, tags=None, model_url, max_new_tokens=250, d... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-171 | callback_manager (Optional[langchain.callbacks.base.BaseCallbackManager]) β
tags (Optional[List[str]]) β
model_url (str) β
max_new_tokens (Optional[int]) β
do_sample (bool) β
temperature (Optional[float]) β
top_p (Optional[float]) β
typical_p (Optional[float]) β
epsilon_cutoff (Optional[float]) β
eta_cutoff (O... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-172 | Length Penalty
attribute max_new_tokens: Optional[int] = 250ο
The maximum number of tokens to generate.
attribute min_length: Optional[int] = 0ο
Minimum generation length in tokens.
attribute model_url: str [Required]ο
The full URL to the textgen webui including http[s]://host:port
attribute no_repeat_ngram_size: Optio... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-173 | attribute top_k: Optional[float] = 40ο
Similar to top_p, but select instead only the top_k most likely tokens.
Higher value = higher range of possible random results.
attribute top_p: Optional[float] = 0.1ο
If not set to 1, select tokens with probabilities adding up to less than this
number. Higher value = higher range... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-174 | kwargs (Any) β
Return type
langchain.schema.LLMResult
async agenerate_prompt(prompts, stop=None, callbacks=None, **kwargs)ο
Take in a list of prompt values and return an LLMResult.
Parameters
prompts (List[langchain.schema.PromptValue]) β
stop (Optional[List[str]]) β
callbacks (Optional[Union[List[langchain.callback... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-175 | exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) β fields to exclude from new model, as with values this takes precedence over include
update (Optional[DictStrAny]) 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 (bool... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-176 | Get the number of tokens in the message.
Parameters
messages (List[langchain.schema.BaseMessage]) β
Return type
int
get_token_ids(text)ο
Get the token present in the text.
Parameters
text (str) β
Return type
List[int]
json(*, include=None, exclude=None, by_alias=False, skip_defaults=None, exclude_unset=False, exclude... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-177 | save(file_path)ο
Save the LLM.
Parameters
file_path (Union[pathlib.Path, str]) β Path to file to save the LLM to.
Return type
None
Example:
.. code-block:: python
llm.save(file_path=βpath/llm.yamlβ)
classmethod update_forward_refs(**localns)ο
Try to update ForwardRefs on fields based on this Model, globalns and localns... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-178 | llm_kwargs (Optional[Dict]) β
Return type
None
attribute tags: Optional[List[str]] = Noneο
Tags to add to the run trace.
attribute verbose: bool [Optional]ο
Whether to print out response text.
__call__(prompt, stop=None, callbacks=None, **kwargs)ο
Check Cache and run the LLM on the given prompt and input.
Parameters
p... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-179 | stop (Optional[Sequence[str]]) β
kwargs (Any) β
Return type
str
async apredict_messages(messages, *, stop=None, **kwargs)ο
Predict message from messages.
Parameters
messages (List[langchain.schema.BaseMessage]) β
stop (Optional[Sequence[str]]) β
kwargs (Any) β
Return type
langchain.schema.BaseMessage
classmethod c... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-180 | generate(prompts, stop=None, callbacks=None, *, tags=None, **kwargs)ο
Run the LLM on the given prompt and input.
Parameters
prompts (List[str]) β
stop (Optional[List[str]]) β
callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) β
tags (Optional... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-181 | Parameters
include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) β
exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) β
by_alias (bool) β
skip_defaults (Optional[bool]) β
exclude_unset (bool) β
exclude_defaults (bool) β
exclude_none (bool) β
encoder (Optional[Callable[[Any], Any]]) β
models... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-182 | property lc_namespace: List[str]ο
Return the namespace of the langchain object.
eg. [βlangchainβ, βllmsβ, βopenaiβ]
property lc_secrets: Dict[str, str]ο
Return a map of constructor argument names to secret ids.
eg. {βopenai_api_keyβ: βOPENAI_API_KEYβ}
property lc_serializable: boolο
Return whether or not the class is s... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-183 | attribute verbose: bool [Optional]ο
Whether to print out response text.
__call__(prompt, stop=None, callbacks=None, **kwargs)ο
Check Cache and run the LLM on the given prompt and input.
Parameters
prompt (str) β
stop (Optional[List[str]]) β
callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler],... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-184 | Predict message from messages.
Parameters
messages (List[langchain.schema.BaseMessage]) β
stop (Optional[Sequence[str]]) β
kwargs (Any) β
Return type
langchain.schema.BaseMessage
classmethod construct(_fields_set=None, **values)ο
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated d... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-185 | Parameters
prompts (List[str]) β
stop (Optional[List[str]]) β
callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) β
tags (Optional[List[str]]) β
kwargs (Any) β
Return type
langchain.schema.LLMResult
generate_prompt(prompts, stop=None, callba... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-186 | include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) β
exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) β
by_alias (bool) β
skip_defaults (Optional[bool]) β
exclude_unset (bool) β
exclude_defaults (bool) β
exclude_none (bool) β
encoder (Optional[Callable[[Any], Any]]) β
models_as_dict (b... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-187 | property lc_namespace: List[str]ο
Return the namespace of the langchain object.
eg. [βlangchainβ, βllmsβ, βopenaiβ]
property lc_secrets: Dict[str, str]ο
Return a map of constructor argument names to secret ids.
eg. {βopenai_api_keyβ: βOPENAI_API_KEYβ}
property lc_serializable: boolο
Return whether or not the class is s... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-188 | endpoint_url (str) β
inject_instruction_format (bool) β
model_kwargs (Optional[dict]) β
retry_sleep (float) β
mosaicml_api_token (Optional[str]) β
Return type
None
attribute endpoint_url: str = 'https://models.hosted-on.mosaicml.hosting/mpt-7b-instruct/v1/predict'ο
Endpoint URL to use.
attribute inject_instruction... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-189 | kwargs (Any) β
Return type
langchain.schema.LLMResult
async agenerate_prompt(prompts, stop=None, callbacks=None, **kwargs)ο
Take in a list of prompt values and return an LLMResult.
Parameters
prompts (List[langchain.schema.PromptValue]) β
stop (Optional[List[str]]) β
callbacks (Optional[Union[List[langchain.callback... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-190 | exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) β fields to exclude from new model, as with values this takes precedence over include
update (Optional[DictStrAny]) 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 (bool... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-191 | Get the number of tokens in the message.
Parameters
messages (List[langchain.schema.BaseMessage]) β
Return type
int
get_token_ids(text)ο
Get the token present in the text.
Parameters
text (str) β
Return type
List[int]
json(*, include=None, exclude=None, by_alias=False, skip_defaults=None, exclude_unset=False, exclude... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-192 | save(file_path)ο
Save the LLM.
Parameters
file_path (Union[pathlib.Path, str]) β Path to file to save the LLM to.
Return type
None
Example:
.. code-block:: python
llm.save(file_path=βpath/llm.yamlβ)
classmethod update_forward_refs(**localns)ο
Try to update ForwardRefs on fields based on this Model, globalns and localns... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-193 | Wrapper around 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(model="gpt-neox-20b")
Parameters
cache (Optional[bool]) β
verbose (bool) β
... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-194 | Whether min_length and max_length should include the length of the input.
attribute length_penalty: float = 1.0ο
Exponential penalty to the length.
attribute max_length: int = 256ο
The maximum number of tokens to generate in the completion.
attribute min_length: int = 1ο
The minimum number of tokens to generate in the ... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-195 | Parameters
prompt (str) β
stop (Optional[List[str]]) β
callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) β
kwargs (Any) β
Return type
str
async agenerate(prompts, stop=None, callbacks=None, *, tags=None, **kwargs)ο
Run the LLM on the given ... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-196 | langchain.schema.BaseMessage
classmethod construct(_fields_set=None, **values)ο
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
Par... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-197 | kwargs (Any) β
Return type
langchain.schema.LLMResult
generate_prompt(prompts, stop=None, callbacks=None, **kwargs)ο
Take in a list of prompt values and return an LLMResult.
Parameters
prompts (List[langchain.schema.PromptValue]) β
stop (Optional[List[str]]) β
callbacks (Optional[Union[List[langchain.callbacks.base.... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-198 | exclude_defaults (bool) β
exclude_none (bool) β
encoder (Optional[Callable[[Any], Any]]) β
models_as_dict (bool) β
dumps_kwargs (Any) β
Return type
unicode
predict(text, *, stop=None, **kwargs)ο
Predict text from text.
Parameters
text (str) β
stop (Optional[Sequence[str]]) β
kwargs (Any) β
Return type
str
predi... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-199 | property lc_serializable: boolο
Return whether or not the class is serializable.
class langchain.llms.OpenAI(*, cache=None, verbose=None, callbacks=None, callback_manager=None, tags=None, client=None, model='text-davinci-003', temperature=0.7, max_tokens=256, top_p=1, frequency_penalty=0, presence_penalty=0, n=1, best_... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-200 | presence_penalty (float) β
n (int) β
best_of (int) β
model_kwargs (Dict[str, Any]) β
openai_api_key (Optional[str]) β
openai_api_base (Optional[str]) β
openai_organization (Optional[str]) β
openai_proxy (Optional[str]) β
batch_size (int) β
request_timeout (Optional[Union[float, Tuple[float, float]]]) β
logit_... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-201 | -1 returns as many tokens as possible given the prompt and
the models maximal context size.
attribute model_kwargs: Dict[str, Any] [Optional]ο
Holds any model parameters valid for create call not explicitly specified.
attribute model_name: str = 'text-davinci-003' (alias 'model')ο
Model name to use.
attribute n: int = ... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-202 | Total probability mass of tokens to consider at each step.
attribute verbose: bool [Optional]ο
Whether to print out response text.
__call__(prompt, stop=None, callbacks=None, **kwargs)ο
Check Cache and run the LLM on the given prompt and input.
Parameters
prompt (str) β
stop (Optional[List[str]]) β
callbacks (Optiona... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-203 | str
async apredict_messages(messages, *, stop=None, **kwargs)ο
Predict message from messages.
Parameters
messages (List[langchain.schema.BaseMessage]) β
stop (Optional[Sequence[str]]) β
kwargs (Any) β
Return type
langchain.schema.BaseMessage
classmethod construct(_fields_set=None, **values)ο
Creates a new model sett... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-204 | Return type
langchain.schema.LLMResult
dict(**kwargs)ο
Return a dictionary of the LLM.
Parameters
kwargs (Any) β
Return type
Dict
generate(prompts, stop=None, callbacks=None, *, tags=None, **kwargs)ο
Run the LLM on the given prompt and input.
Parameters
prompts (List[str]) β
stop (Optional[List[str]]) β
callbacks (O... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-205 | get_token_ids(text)ο
Get the token IDs using the tiktoken package.
Parameters
text (str) β
Return type
List[int]
json(*, include=None, exclude=None, by_alias=False, skip_defaults=None, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=None, models_as_dict=True, **dumps_kwargs)ο
Generate a JSON r... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-206 | max_tokens = openai.modelname_to_contextsize("text-davinci-003")
predict(text, *, stop=None, **kwargs)ο
Predict text from text.
Parameters
text (str) β
stop (Optional[Sequence[str]]) β
kwargs (Any) β
Return type
str
predict_messages(messages, *, stop=None, **kwargs)ο
Predict message from messages.
Parameters
message... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-207 | Parameters
localns (Any) β
Return type
None
property lc_attributes: Dictο
Return a list of attribute names that should be included in the
serialized kwargs. These attributes must be accepted by the
constructor.
property lc_namespace: List[str]ο
Return the namespace of the langchain object.
eg. [βlangchainβ, βllmsβ, βo... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-208 | Parameters
cache (Optional[bool]) β
verbose (bool) β
callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) β
callback_manager (Optional[langchain.callbacks.base.BaseCallbackManager]) β
tags (Optional[List[str]]) β
client (Any) β
model_name (s... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-209 | Tags to add to the run trace.
attribute verbose: bool [Optional]ο
Whether to print out response text.
__call__(prompt, stop=None, callbacks=None, **kwargs)ο
Check Cache and run the LLM on the given prompt and input.
Parameters
prompt (str) β
stop (Optional[List[str]]) β
callbacks (Optional[Union[List[langchain.callba... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-210 | Predict message from messages.
Parameters
messages (List[langchain.schema.BaseMessage]) β
stop (Optional[Sequence[str]]) β
kwargs (Any) β
Return type
langchain.schema.BaseMessage
classmethod construct(_fields_set=None, **values)ο
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated d... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-211 | Parameters
prompts (List[str]) β
stop (Optional[List[str]]) β
callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) β
tags (Optional[List[str]]) β
kwargs (Any) β
Return type
langchain.schema.LLMResult
generate_prompt(prompts, stop=None, callba... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-212 | include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) β
exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) β
by_alias (bool) β
skip_defaults (Optional[bool]) β
exclude_unset (bool) β
exclude_defaults (bool) β
exclude_none (bool) β
encoder (Optional[Callable[[Any], Any]]) β
models_as_dict (b... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-213 | property lc_namespace: List[str]ο
Return the namespace of the langchain object.
eg. [βlangchainβ, βllmsβ, βopenaiβ]
property lc_secrets: Dict[str, str]ο
Return a map of constructor argument names to secret ids.
eg. {βopenai_api_keyβ: βOPENAI_API_KEYβ}
property lc_serializable: boolο
Return whether or not the class is s... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-214 | model_id (Optional[str]) β
server_url (Optional[str]) β
server_type (Literal['grpc', 'http']) β
embedded (bool) β
cache (Optional[bool]) β
verbose (bool) β
callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) β
callback_manager (Optional[la... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-215 | Parameters
prompt (str) β
stop (Optional[List[str]]) β
callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) β
kwargs (Any) β
Return type
str
async agenerate(prompts, stop=None, callbacks=None, *, tags=None, **kwargs)ο
Run the LLM on the given ... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-216 | langchain.schema.BaseMessage
classmethod construct(_fields_set=None, **values)ο
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
Par... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-217 | kwargs (Any) β
Return type
langchain.schema.LLMResult
generate_prompt(prompts, stop=None, callbacks=None, **kwargs)ο
Take in a list of prompt values and return an LLMResult.
Parameters
prompts (List[langchain.schema.PromptValue]) β
stop (Optional[List[str]]) β
callbacks (Optional[Union[List[langchain.callbacks.base.... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-218 | exclude_defaults (bool) β
exclude_none (bool) β
encoder (Optional[Callable[[Any], Any]]) β
models_as_dict (bool) β
dumps_kwargs (Any) β
Return type
unicode
predict(text, *, stop=None, **kwargs)ο
Predict text from text.
Parameters
text (str) β
stop (Optional[Sequence[str]]) β
kwargs (Any) β
Return type
str
predi... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-219 | property lc_serializable: boolο
Return whether or not the class is serializable.
property runner: openllm.LLMRunnerο
Get the underlying openllm.LLMRunner instance for integration with BentoML.
Example:
.. code-block:: python
llm = OpenLLM(model_name=βflan-t5β,
model_id=βgoogle/flan-t5-largeβ,
embedded=False,
)
tools = ... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-220 | callback_manager (Optional[langchain.callbacks.base.BaseCallbackManager]) β
tags (Optional[List[str]]) β
client (Any) β
model (str) β
temperature (float) β
max_tokens (int) β
top_p (float) β
frequency_penalty (float) β
presence_penalty (float) β
n (int) β
best_of (int) β
model_kwargs (Dict[str, Any]) β
open... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-221 | attribute logit_bias: Optional[Dict[str, float]] [Optional]ο
Adjust the probability of specific tokens being generated.
attribute max_retries: int = 6ο
Maximum number of retries to make when generating.
attribute max_tokens: int = 256ο
The maximum number of tokens to generate in the completion.
-1 returns as many token... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-222 | supported by tiktoken. This can include when using Azure embeddings or
when using one of the many model providers that expose an OpenAI-like
API but with different models. In those cases, in order to avoid erroring
when tiktoken is called, you can specify a model name to use here.
attribute top_p: float = 1ο
Total prob... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-223 | kwargs (Any) β
Return type
langchain.schema.LLMResult
async apredict(text, *, stop=None, **kwargs)ο
Predict text from text.
Parameters
text (str) β
stop (Optional[Sequence[str]]) β
kwargs (Any) β
Return type
str
async apredict_messages(messages, *, stop=None, **kwargs)ο
Predict message from messages.
Parameters
mes... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-224 | self (Model) β
Returns
new model instance
Return type
Model
create_llm_result(choices, prompts, token_usage)ο
Create the LLMResult from the choices and prompts.
Parameters
choices (Any) β
prompts (List[str]) β
token_usage (Dict[str, int]) β
Return type
langchain.schema.LLMResult
dict(**kwargs)ο
Return a dictionary ... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-225 | Parameters
messages (List[langchain.schema.BaseMessage]) β
Return type
int
get_sub_prompts(params, prompts, stop=None)ο
Get the sub prompts for llm call.
Parameters
params (Dict[str, Any]) β
prompts (List[str]) β
stop (Optional[List[str]]) β
Return type
List[List[str]]
get_token_ids(text)ο
Get the token IDs using t... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-226 | int
Example
max_tokens = openai.max_token_for_prompt("Tell me a joke.")
static modelname_to_contextsize(modelname)ο
Calculate the maximum number of tokens possible to generate for a model.
Parameters
modelname (str) β The modelname we want to know the context size for.
Returns
The maximum context size
Return type
int
E... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-227 | stop (Optional[List[str]]) β Optional list of stop words to use when generating.
Returns
A generator representing the stream of tokens from OpenAI.
Return type
Generator
Example
generator = openai.stream("Tell me a joke.")
for token in generator:
yield token
classmethod update_forward_refs(**localns)ο
Try to update... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-228 | environment variable HUGGINGFACE_API_KEY set with your API key.
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.llms import petals
petals = Petals()
Parameters
cache (Optional[bool]) β
verbose (bool) β
callbacks (Optional[Unio... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-229 | Tags to add to the run trace.
attribute temperature: float = 0.7ο
What sampling temperature to use
attribute tokenizer: Any = Noneο
The tokenizer to use for the API calls.
attribute top_k: Optional[int] = Noneο
The number of highest probability vocabulary tokens
to keep for top-k-filtering.
attribute top_p: float = 0.9... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-230 | kwargs (Any) β
Return type
langchain.schema.LLMResult
async apredict(text, *, stop=None, **kwargs)ο
Predict text from text.
Parameters
text (str) β
stop (Optional[Sequence[str]]) β
kwargs (Any) β
Return type
str
async apredict_messages(messages, *, stop=None, **kwargs)ο
Predict message from messages.
Parameters
mes... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-231 | Returns
new model instance
Return type
Model
dict(**kwargs)ο
Return a dictionary of the LLM.
Parameters
kwargs (Any) β
Return type
Dict
generate(prompts, stop=None, callbacks=None, *, tags=None, **kwargs)ο
Run the LLM on the given prompt and input.
Parameters
prompts (List[str]) β
stop (Optional[List[str]]) β
callba... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-232 | Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
Parameters
include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) β
exclude (Optional[Union[AbstractSetIntStr, Map... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-233 | Return a list of attribute names that should be included in the
serialized kwargs. These attributes must be accepted by the
constructor.
property lc_namespace: List[str]ο
Return the namespace of the langchain object.
eg. [βlangchainβ, βllmsβ, βopenaiβ]
property lc_secrets: Dict[str, str]ο
Return a map of constructor ar... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-234 | attribute pipeline_key: str = ''ο
The id or tag of the target pipeline
attribute pipeline_kwargs: Dict[str, Any] [Optional]ο
Holds any pipeline parameters valid for create call not
explicitly specified.
attribute tags: Optional[List[str]] = Noneο
Tags to add to the run trace.
attribute verbose: bool [Optional]ο
Whether... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-235 | kwargs (Any) β
Return type
langchain.schema.LLMResult
async apredict(text, *, stop=None, **kwargs)ο
Predict text from text.
Parameters
text (str) β
stop (Optional[Sequence[str]]) β
kwargs (Any) β
Return type
str
async apredict_messages(messages, *, stop=None, **kwargs)ο
Predict message from messages.
Parameters
mes... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-236 | Returns
new model instance
Return type
Model
dict(**kwargs)ο
Return a dictionary of the LLM.
Parameters
kwargs (Any) β
Return type
Dict
generate(prompts, stop=None, callbacks=None, *, tags=None, **kwargs)ο
Run the LLM on the given prompt and input.
Parameters
prompts (List[str]) β
stop (Optional[List[str]]) β
callba... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-237 | Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
Parameters
include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) β
exclude (Optional[Union[AbstractSetIntStr, Map... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-238 | Return a list of attribute names that should be included in the
serialized kwargs. These attributes must be accepted by the
constructor.
property lc_namespace: List[str]ο
Return the namespace of the langchain object.
eg. [βlangchainβ, βllmsβ, βopenaiβ]
property lc_secrets: Dict[str, str]ο
Return a map of constructor ar... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-239 | tags (Optional[List[str]]) β
client (Any) β
model (Optional[str]) β
output (Optional[Dict[str, Any]]) β
max_tokens (int) β
temperature (float) β
token (Optional[str]) β
stop (Optional[List[str]]) β
Return type
None
attribute max_tokens: int = 256ο
Denotes the number of tokens to predict per generation.
attribut... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-240 | tags (Optional[List[str]]) β
kwargs (Any) β
Return type
langchain.schema.LLMResult
async agenerate_prompt(prompts, stop=None, callbacks=None, **kwargs)ο
Take in a list of prompt values and return an LLMResult.
Parameters
prompts (List[langchain.schema.PromptValue]) β
stop (Optional[List[str]]) β
callbacks (Optional... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-241 | exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) β fields to exclude from new model, as with values this takes precedence over include
update (Optional[DictStrAny]) 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 (bool... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-242 | Get the number of tokens in the message.
Parameters
messages (List[langchain.schema.BaseMessage]) β
Return type
int
get_token_ids(text)ο
Get the token present in the text.
Parameters
text (str) β
Return type
List[int]
json(*, include=None, exclude=None, by_alias=False, skip_defaults=None, exclude_unset=False, exclude... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-243 | save(file_path)ο
Save the LLM.
Parameters
file_path (Union[pathlib.Path, str]) β Path to file to save the LLM to.
Return type
None
Example:
.. code-block:: python
llm.save(file_path=βpath/llm.yamlβ)
classmethod update_forward_refs(**localns)ο
Try to update ForwardRefs on fields based on this Model, globalns and localns... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-244 | Bases: langchain.llms.openai.OpenAI
Wrapper around OpenAI large language models.
To use, you should have the openai and promptlayer python
package installed, and the environment variable OPENAI_API_KEY
and PROMPTLAYER_API_KEY set with your openAI API key and
promptlayer key respectively.
All parameters that can be pass... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-245 | max_retries (int) β
streaming (bool) β
allowed_special (Union[Literal['all'], typing.AbstractSet[str]]) β
disallowed_special (Union[Literal['all'], typing.Collection[str]]) β
tiktoken_model_name (Optional[str]) β
Return type
None
Example
from langchain.llms import PromptLayerOpenAI
openai = PromptLayerOpenAI(model... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-246 | kwargs (Any) β
Return type
langchain.schema.LLMResult
async apredict(text, *, stop=None, **kwargs)ο
Predict text from text.
Parameters
text (str) β
stop (Optional[Sequence[str]]) β
kwargs (Any) β
Return type
str
async apredict_messages(messages, *, stop=None, **kwargs)ο
Predict message from messages.
Parameters
mes... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-247 | self (Model) β
Returns
new model instance
Return type
Model
create_llm_result(choices, prompts, token_usage)ο
Create the LLMResult from the choices and prompts.
Parameters
choices (Any) β
prompts (List[str]) β
token_usage (Dict[str, int]) β
Return type
langchain.schema.LLMResult
dict(**kwargs)ο
Return a dictionary ... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-248 | Parameters
messages (List[langchain.schema.BaseMessage]) β
Return type
int
get_sub_prompts(params, prompts, stop=None)ο
Get the sub prompts for llm call.
Parameters
params (Dict[str, Any]) β
prompts (List[str]) β
stop (Optional[List[str]]) β
Return type
List[List[str]]
get_token_ids(text)ο
Get the token IDs using t... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-249 | int
Example
max_tokens = openai.max_token_for_prompt("Tell me a joke.")
static modelname_to_contextsize(modelname)ο
Calculate the maximum number of tokens possible to generate for a model.
Parameters
modelname (str) β The modelname we want to know the context size for.
Returns
The maximum context size
Return type
int
E... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-250 | stop (Optional[List[str]]) β Optional list of stop words to use when generating.
Returns
A generator representing the stream of tokens from OpenAI.
Return type
Generator
Example
generator = openai.stream("Tell me a joke.")
for token in generator:
yield token
classmethod update_forward_refs(**localns)ο
Try to update... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-251 | To use, you should have the openai and promptlayer python
package installed, and the environment variable OPENAI_API_KEY
and PROMPTLAYER_API_KEY set with your openAI API key and
promptlayer key respectively.
All parameters that can be passed to the OpenAIChat LLM can also
be passed here. The PromptLayerOpenAIChat adds ... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-252 | Set of special tokens that are allowedγ
attribute disallowed_special: Union[Literal['all'], Collection[str]] = 'all'ο
Set of special tokens that are not allowedγ
attribute max_retries: int = 6ο
Maximum number of retries to make when generating.
attribute model_kwargs: Dict[str, Any] [Optional]ο
Holds any model paramete... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-253 | Parameters
prompts (List[langchain.schema.PromptValue]) β
stop (Optional[List[str]]) β
callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) β
kwargs (Any) β
Return type
langchain.schema.LLMResult
async apredict(text, *, stop=None, **kwargs)ο
P... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-254 | the new model: you should trust this data
deep (bool) β set to True to make a deep copy of the model
self (Model) β
Returns
new model instance
Return type
Model
dict(**kwargs)ο
Return a dictionary of the LLM.
Parameters
kwargs (Any) β
Return type
Dict
generate(prompts, stop=None, callbacks=None, *, tags=None, **kwarg... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-255 | Parameters
text (str) β
Return type
List[int]
json(*, include=None, exclude=None, by_alias=False, skip_defaults=None, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=None, models_as_dict=True, **dumps_kwargs)ο
Generate a JSON representation of the model, include and exclude arguments as per di... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-256 | .. code-block:: python
llm.save(file_path=βpath/llm.yamlβ)
classmethod update_forward_refs(**localns)ο
Try to update ForwardRefs on fields based on this Model, globalns and localns.
Parameters
localns (Any) β
Return type
None
property lc_attributes: Dictο
Return a list of attribute names that should be included in the... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-257 | # Simplest invocation
response = model("Once upon a time, ")
Parameters
cache (Optional[bool]) β
verbose (bool) β
callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) β
callback_manager (Optional[langchain.callbacks.base.BaseCallbackManager]) β... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-258 | attribute strategy: str = 'cpu fp32'ο
Token context window.
attribute tags: Optional[List[str]] = Noneο
Tags to add to the run trace.
attribute temperature: float = 1.0ο
The temperature to use for sampling.
attribute tokens_path: str [Required]ο
Path to the RWKV tokens file.
attribute top_p: float = 0.5ο
The top-p valu... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-259 | kwargs (Any) β
Return type
langchain.schema.LLMResult
async apredict(text, *, stop=None, **kwargs)ο
Predict text from text.
Parameters
text (str) β
stop (Optional[Sequence[str]]) β
kwargs (Any) β
Return type
str
async apredict_messages(messages, *, stop=None, **kwargs)ο
Predict message from messages.
Parameters
mes... | https://api.python.langchain.com/en/stable/modules/llms.html |
a44a60c1f5be-260 | Returns
new model instance
Return type
Model
dict(**kwargs)ο
Return a dictionary of the LLM.
Parameters
kwargs (Any) β
Return type
Dict
generate(prompts, stop=None, callbacks=None, *, tags=None, **kwargs)ο
Run the LLM on the given prompt and input.
Parameters
prompts (List[str]) β
stop (Optional[List[str]]) β
callba... | https://api.python.langchain.com/en/stable/modules/llms.html |
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