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Take in a list of prompt values and return an LLMResult. Parameters prompts (List[langchain.schema.PromptValue]) – stop (Optional[List[str]]) – callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) – kwargs (Any) – Return type langchain.schema....
https://api.python.langchain.com/en/latest/modules/llms.html
0e0436a883fe-212
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) Generate a JSON representation of the model, include and exclude arguments as per dict(). encoder is an optio...
https://api.python.langchain.com/en/latest/modules/llms.html
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models_as_dict (bool) – dumps_kwargs (Any) – Return type unicode predict(text, *, stop=None, **kwargs) Predict text from text. Parameters text (str) – stop (Optional[Sequence[str]]) – kwargs (Any) – Return type str predict_messages(messages, *, stop=None, **kwargs) Predict message from messages. Parameters messa...
https://api.python.langchain.com/en/latest/modules/llms.html
0e0436a883fe-214
classmethod update_forward_refs(**localns) Try to update ForwardRefs on fields based on this Model, globalns and localns. Parameters localns (Any) – Return type None property lc_attributes: Dict Return a list of attribute names that should be included in the serialized kwargs. These attributes must be accepted by th...
https://api.python.langchain.com/en/latest/modules/llms.html
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class langchain.llms.FakeListLLM(*, cache=None, verbose=None, callbacks=None, callback_manager=None, tags=None, responses, i=0)[source] Bases: langchain.llms.base.LLM Fake LLM wrapper for testing purposes. Parameters cache (Optional[bool]) – verbose (bool) – callbacks (Optional[Union[List[langchain.callbacks.base.Ba...
https://api.python.langchain.com/en/latest/modules/llms.html
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Whether to print out response text. __call__(prompt, stop=None, callbacks=None, **kwargs) Check Cache and run the LLM on the given prompt and input. Parameters prompt (str) – stop (Optional[List[str]]) – callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallba...
https://api.python.langchain.com/en/latest/modules/llms.html
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kwargs (Any) – Return type langchain.schema.LLMResult async agenerate_prompt(prompts, stop=None, callbacks=None, **kwargs) Take in a list of prompt values and return an LLMResult. Parameters prompts (List[langchain.schema.PromptValue]) – stop (Optional[List[str]]) – callbacks (Optional[Union[List[langchain.callback...
https://api.python.langchain.com/en/latest/modules/llms.html
0e0436a883fe-218
Predict message from messages. Parameters messages (List[langchain.schema.BaseMessage]) – stop (Optional[Sequence[str]]) – kwargs (Any) – Return type langchain.schema.BaseMessage classmethod construct(_fields_set=None, **values) Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated d...
https://api.python.langchain.com/en/latest/modules/llms.html
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exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to exclude from new model, as with values this takes precedence over include update (Optional[DictStrAny]) – 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/latest/modules/llms.html
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stop (Optional[List[str]]) – callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) – tags (Optional[List[str]]) – kwargs (Any) – Return type langchain.schema.LLMResult generate_prompt(prompts, stop=None, callbacks=None, **kwargs) Take in a lis...
https://api.python.langchain.com/en/latest/modules/llms.html
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Return type int get_num_tokens_from_messages(messages) Get the number of tokens in the message. Parameters messages (List[langchain.schema.BaseMessage]) – Return type int get_token_ids(text) Get the token present in the text. Parameters text (str) – Return type List[int] json(*, include=None, exclude=None, by_alias...
https://api.python.langchain.com/en/latest/modules/llms.html
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exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – by_alias (bool) – skip_defaults (Optional[bool]) – exclude_unset (bool) – exclude_defaults (bool) – exclude_none (bool) – encoder (Optional[Callable[[Any], Any]]) – models_as_dict (bool) – dumps_kwargs (Any) – Return type unicode predict(text, *,...
https://api.python.langchain.com/en/latest/modules/llms.html
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kwargs (Any) – Return type langchain.schema.BaseMessage save(file_path) Save the LLM. Parameters file_path (Union[pathlib.Path, str]) – Path to file to save the LLM to. Return type None Example: .. code-block:: python llm.save(file_path=”path/llm.yaml”) classmethod update_forward_refs(**localns) Try to update Forwar...
https://api.python.langchain.com/en/latest/modules/llms.html
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property lc_secrets: Dict[str, str] Return a map of constructor argument names to secret ids. eg. {β€œopenai_api_key”: β€œOPENAI_API_KEY”} property lc_serializable: bool Return whether or not the class is serializable. class langchain.llms.ForefrontAI(*, cache=None, verbose=None, callbacks=None, callback_manager=None, ta...
https://api.python.langchain.com/en/latest/modules/llms.html
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from langchain.llms import ForefrontAI forefrontai = ForefrontAI(endpoint_url="") Parameters cache (Optional[bool]) – verbose (bool) – callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) – callback_manager (Optional[langchain.callbacks.base.Ba...
https://api.python.langchain.com/en/latest/modules/llms.html
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attribute endpoint_url: str = '' Model name to use. attribute length: int = 256 The maximum number of tokens to generate in the completion. attribute repetition_penalty: int = 1 Penalizes repeated tokens according to frequency. attribute tags: Optional[List[str]] = None Tags to add to the run trace. attribute tempe...
https://api.python.langchain.com/en/latest/modules/llms.html
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Check Cache and run the LLM on the given prompt and input. Parameters prompt (str) – stop (Optional[List[str]]) – callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) – kwargs (Any) – Return type str async agenerate(prompts, stop=None, callbac...
https://api.python.langchain.com/en/latest/modules/llms.html
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Take in a list of prompt values and return an LLMResult. Parameters prompts (List[langchain.schema.PromptValue]) – stop (Optional[List[str]]) – callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) – kwargs (Any) – Return type langchain.schema....
https://api.python.langchain.com/en/latest/modules/llms.html
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Return type langchain.schema.BaseMessage classmethod construct(_fields_set=None, **values) 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 = β€˜allow’ was set since it adds all passe...
https://api.python.langchain.com/en/latest/modules/llms.html
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update (Optional[DictStrAny]) – 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) – set to True to make a deep copy of the model self (Model) – Returns new model instance Return type Model dict(**kwargs) Return a dictionary of ...
https://api.python.langchain.com/en/latest/modules/llms.html
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kwargs (Any) – Return type langchain.schema.LLMResult generate_prompt(prompts, stop=None, callbacks=None, **kwargs) Take in a list of prompt values and return an LLMResult. Parameters prompts (List[langchain.schema.PromptValue]) – stop (Optional[List[str]]) – callbacks (Optional[Union[List[langchain.callbacks.base....
https://api.python.langchain.com/en/latest/modules/llms.html
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int get_token_ids(text) Get the token present in the text. Parameters text (str) – 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) Generate a JSON represen...
https://api.python.langchain.com/en/latest/modules/llms.html
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exclude_none (bool) – encoder (Optional[Callable[[Any], Any]]) – models_as_dict (bool) – dumps_kwargs (Any) – Return type unicode predict(text, *, stop=None, **kwargs) Predict text from text. Parameters text (str) – stop (Optional[Sequence[str]]) – kwargs (Any) – Return type str predict_messages(messages, *, st...
https://api.python.langchain.com/en/latest/modules/llms.html
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Return type None Example: .. code-block:: python llm.save(file_path=”path/llm.yaml”) classmethod update_forward_refs(**localns) Try to update ForwardRefs on fields based on this Model, globalns and localns. Parameters localns (Any) – Return type None property lc_attributes: Dict Return a list of attribute names that...
https://api.python.langchain.com/en/latest/modules/llms.html
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property lc_serializable: bool Return whether or not the class is serializable. class langchain.llms.GPT4All(*, cache=None, verbose=None, callbacks=None, callback_manager=None, tags=None, model, backend=None, n_ctx=512, n_parts=- 1, seed=0, f16_kv=False, logits_all=False, vocab_only=False, use_mlock=False, embedding=F...
https://api.python.langchain.com/en/latest/modules/llms.html
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pre-trained model file, and the model’s config information. Example from langchain.llms import GPT4All model = GPT4All(model="./models/gpt4all-model.bin", n_ctx=512, n_threads=8) # Simplest invocation response = model("Once upon a time, ") Parameters cache (Optional[bool]) – verbose (bool) – callbacks (Optional[Union...
https://api.python.langchain.com/en/latest/modules/llms.html
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logits_all (bool) – vocab_only (bool) – use_mlock (bool) – embedding (bool) – n_threads (Optional[int]) – n_predict (Optional[int]) – temp (Optional[float]) – top_p (Optional[float]) – top_k (Optional[int]) – echo (Optional[bool]) – stop (Optional[List[str]]) – repeat_last_n (Optional[int]) – repeat_penalty...
https://api.python.langchain.com/en/latest/modules/llms.html
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Leave (n_ctx * context_erase) tokens starting from beginning if the context has run out. attribute echo: Optional[bool] = False Whether to echo the prompt. attribute embedding: bool = False Use embedding mode only. attribute f16_kv: bool = False Use half-precision for key/value cache. attribute logits_all: bool = Fa...
https://api.python.langchain.com/en/latest/modules/llms.html
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attribute n_predict: Optional[int] = 256 The maximum number of tokens to generate. attribute n_threads: Optional[int] = 4 Number of threads to use. attribute repeat_last_n: Optional[int] = 64 Last n tokens to penalize attribute repeat_penalty: Optional[float] = 1.3 The penalty to apply to repeated tokens. attribute...
https://api.python.langchain.com/en/latest/modules/llms.html
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The temperature to use for sampling. attribute top_k: Optional[int] = 40 The top-k value to use for sampling. attribute top_p: Optional[float] = 0.95 The top-p value to use for sampling. attribute use_mlock: bool = False Force system to keep model in RAM. attribute verbose: bool [Optional] Whether to print out resp...
https://api.python.langchain.com/en/latest/modules/llms.html
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kwargs (Any) – Return type str async agenerate(prompts, stop=None, callbacks=None, *, tags=None, **kwargs) Run the LLM on the given prompt and input. Parameters prompts (List[str]) – stop (Optional[List[str]]) – callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.B...
https://api.python.langchain.com/en/latest/modules/llms.html
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stop (Optional[List[str]]) – callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) – kwargs (Any) – Return type langchain.schema.LLMResult async apredict(text, *, stop=None, **kwargs) Predict text from text. Parameters text (str) – stop (Optio...
https://api.python.langchain.com/en/latest/modules/llms.html
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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 = β€˜allow’ was set since it adds all passed values Parameters _fields_set (Optional[SetStr]) – values (Any) – Return type Model copy...
https://api.python.langchain.com/en/latest/modules/llms.html
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the new model: you should trust this data deep (bool) – set to True to make a deep copy of the model self (Model) – Returns new model instance Return type Model dict(**kwargs) Return a dictionary of the LLM. Parameters kwargs (Any) – Return type Dict generate(prompts, stop=None, callbacks=None, *, tags=None, **kwarg...
https://api.python.langchain.com/en/latest/modules/llms.html
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Take in a list of prompt values and return an LLMResult. Parameters prompts (List[langchain.schema.PromptValue]) – stop (Optional[List[str]]) – callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) – kwargs (Any) – Return type langchain.schema....
https://api.python.langchain.com/en/latest/modules/llms.html
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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) Generate a JSON representation of the model, include and exclude arguments as per dict(). encoder is an optio...
https://api.python.langchain.com/en/latest/modules/llms.html
0e0436a883fe-247
models_as_dict (bool) – dumps_kwargs (Any) – Return type unicode predict(text, *, stop=None, **kwargs) Predict text from text. Parameters text (str) – stop (Optional[Sequence[str]]) – kwargs (Any) – Return type str predict_messages(messages, *, stop=None, **kwargs) Predict message from messages. Parameters messa...
https://api.python.langchain.com/en/latest/modules/llms.html
0e0436a883fe-248
classmethod update_forward_refs(**localns) Try to update ForwardRefs on fields based on this Model, globalns and localns. Parameters localns (Any) – Return type None property lc_attributes: Dict Return a list of attribute names that should be included in the serialized kwargs. These attributes must be accepted by th...
https://api.python.langchain.com/en/latest/modules/llms.html
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class langchain.llms.GooglePalm(*, cache=None, verbose=None, callbacks=None, callback_manager=None, tags=None, client=None, google_api_key=None, model_name='models/text-bison-001', temperature=0.7, top_p=None, top_k=None, max_output_tokens=None, n=1)[source] Bases: langchain.llms.base.BaseLLM, pydantic.main.BaseModel ...
https://api.python.langchain.com/en/latest/modules/llms.html
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temperature (float) – top_p (Optional[float]) – top_k (Optional[int]) – max_output_tokens (Optional[int]) – n (int) – Return type None attribute max_output_tokens: Optional[int] = None Maximum number of tokens to include in a candidate. Must be greater than zero. If unset, will default to 64. attribute model_name...
https://api.python.langchain.com/en/latest/modules/llms.html
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[0.0, 1.0]. attribute top_k: Optional[int] = None Decode using top-k sampling: consider the set of top_k most probable tokens. Must be positive. attribute top_p: Optional[float] = None Decode using nucleus sampling: consider the smallest set of tokens whose probability sum is at least top_p. Must be in the closed int...
https://api.python.langchain.com/en/latest/modules/llms.html
0e0436a883fe-252
kwargs (Any) – Return type str async agenerate(prompts, stop=None, callbacks=None, *, tags=None, **kwargs) Run the LLM on the given prompt and input. Parameters prompts (List[str]) – stop (Optional[List[str]]) – callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.B...
https://api.python.langchain.com/en/latest/modules/llms.html
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stop (Optional[List[str]]) – callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) – kwargs (Any) – Return type langchain.schema.LLMResult async apredict(text, *, stop=None, **kwargs) Predict text from text. Parameters text (str) – stop (Optio...
https://api.python.langchain.com/en/latest/modules/llms.html
0e0436a883fe-254
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 = β€˜allow’ was set since it adds all passed values Parameters _fields_set (Optional[SetStr]) – values (Any) – Return type Model copy...
https://api.python.langchain.com/en/latest/modules/llms.html
0e0436a883fe-255
the new model: you should trust this data deep (bool) – set to True to make a deep copy of the model self (Model) – Returns new model instance Return type Model dict(**kwargs) Return a dictionary of the LLM. Parameters kwargs (Any) – Return type Dict generate(prompts, stop=None, callbacks=None, *, tags=None, **kwarg...
https://api.python.langchain.com/en/latest/modules/llms.html
0e0436a883fe-256
Take in a list of prompt values and return an LLMResult. Parameters prompts (List[langchain.schema.PromptValue]) – stop (Optional[List[str]]) – callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) – kwargs (Any) – Return type langchain.schema....
https://api.python.langchain.com/en/latest/modules/llms.html
0e0436a883fe-257
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) Generate a JSON representation of the model, include and exclude arguments as per dict(). encoder is an optio...
https://api.python.langchain.com/en/latest/modules/llms.html
0e0436a883fe-258
models_as_dict (bool) – dumps_kwargs (Any) – Return type unicode predict(text, *, stop=None, **kwargs) Predict text from text. Parameters text (str) – stop (Optional[Sequence[str]]) – kwargs (Any) – Return type str predict_messages(messages, *, stop=None, **kwargs) Predict message from messages. Parameters messa...
https://api.python.langchain.com/en/latest/modules/llms.html
0e0436a883fe-259
classmethod update_forward_refs(**localns) Try to update ForwardRefs on fields based on this Model, globalns and localns. Parameters localns (Any) – Return type None property lc_attributes: Dict Return a list of attribute names that should be included in the serialized kwargs. These attributes must be accepted by th...
https://api.python.langchain.com/en/latest/modules/llms.html
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class langchain.llms.GooseAI(*, cache=None, verbose=None, callbacks=None, callback_manager=None, tags=None, client=None, model_name='gpt-neo-20b', temperature=0.7, max_tokens=256, top_p=1, min_tokens=1, frequency_penalty=0, presence_penalty=0, n=1, model_kwargs=None, logit_bias=None, gooseai_api_key=None)[source] Base...
https://api.python.langchain.com/en/latest/modules/llms.html
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from langchain.llms import GooseAI gooseai = GooseAI(model_name="gpt-neo-20b") Parameters cache (Optional[bool]) – verbose (bool) – callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) – callback_manager (Optional[langchain.callbacks.base.BaseC...
https://api.python.langchain.com/en/latest/modules/llms.html
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gooseai_api_key (Optional[str]) – Return type None attribute frequency_penalty: float = 0 Penalizes repeated tokens according to frequency. attribute logit_bias: Optional[Dict[str, float]] [Optional] Adjust the probability of specific tokens being generated. attribute max_tokens: int = 256 The maximum number of tok...
https://api.python.langchain.com/en/latest/modules/llms.html
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attribute n: int = 1 How many completions to generate for each prompt. attribute presence_penalty: float = 0 Penalizes repeated tokens. attribute tags: Optional[List[str]] = None Tags to add to the run trace. attribute temperature: float = 0.7 What sampling temperature to use attribute top_p: float = 1 Total proba...
https://api.python.langchain.com/en/latest/modules/llms.html
0e0436a883fe-264
kwargs (Any) – Return type str async agenerate(prompts, stop=None, callbacks=None, *, tags=None, **kwargs) Run the LLM on the given prompt and input. Parameters prompts (List[str]) – stop (Optional[List[str]]) – callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.B...
https://api.python.langchain.com/en/latest/modules/llms.html
0e0436a883fe-265
stop (Optional[List[str]]) – callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) – kwargs (Any) – Return type langchain.schema.LLMResult async apredict(text, *, stop=None, **kwargs) Predict text from text. Parameters text (str) – stop (Optio...
https://api.python.langchain.com/en/latest/modules/llms.html
0e0436a883fe-266
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 = β€˜allow’ was set since it adds all passed values Parameters _fields_set (Optional[SetStr]) – values (Any) – Return type Model copy...
https://api.python.langchain.com/en/latest/modules/llms.html
0e0436a883fe-267
the new model: you should trust this data deep (bool) – set to True to make a deep copy of the model self (Model) – Returns new model instance Return type Model dict(**kwargs) Return a dictionary of the LLM. Parameters kwargs (Any) – Return type Dict generate(prompts, stop=None, callbacks=None, *, tags=None, **kwarg...
https://api.python.langchain.com/en/latest/modules/llms.html
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Take in a list of prompt values and return an LLMResult. Parameters prompts (List[langchain.schema.PromptValue]) – stop (Optional[List[str]]) – callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) – kwargs (Any) – Return type langchain.schema....
https://api.python.langchain.com/en/latest/modules/llms.html
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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) Generate a JSON representation of the model, include and exclude arguments as per dict(). encoder is an optio...
https://api.python.langchain.com/en/latest/modules/llms.html
0e0436a883fe-270
models_as_dict (bool) – dumps_kwargs (Any) – Return type unicode predict(text, *, stop=None, **kwargs) Predict text from text. Parameters text (str) – stop (Optional[Sequence[str]]) – kwargs (Any) – Return type str predict_messages(messages, *, stop=None, **kwargs) Predict message from messages. Parameters messa...
https://api.python.langchain.com/en/latest/modules/llms.html
0e0436a883fe-271
classmethod update_forward_refs(**localns) Try to update ForwardRefs on fields based on this Model, globalns and localns. Parameters localns (Any) – Return type None property lc_attributes: Dict Return a list of attribute names that should be included in the serialized kwargs. These attributes must be accepted by th...
https://api.python.langchain.com/en/latest/modules/llms.html
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class langchain.llms.HuggingFaceEndpoint(*, cache=None, verbose=None, callbacks=None, callback_manager=None, tags=None, endpoint_url='', task=None, model_kwargs=None, huggingfacehub_api_token=None)[source] Bases: langchain.llms.base.LLM Wrapper around HuggingFaceHub Inference Endpoints. To use, you should have the hug...
https://api.python.langchain.com/en/latest/modules/llms.html
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) Parameters cache (Optional[bool]) – verbose (bool) – callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) – callback_manager (Optional[langchain.callbacks.base.BaseCallbackManager]) – tags (Optional[List[str]]) – endpoint_url (str) – task ...
https://api.python.langchain.com/en/latest/modules/llms.html
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Task to call the model with. Should be a task that returns generated_text or summary_text. attribute verbose: bool [Optional] Whether to print out response text. __call__(prompt, stop=None, callbacks=None, **kwargs) Check Cache and run the LLM on the given prompt and input. Parameters prompt (str) – stop (Optional[L...
https://api.python.langchain.com/en/latest/modules/llms.html
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stop (Optional[List[str]]) – callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) – tags (Optional[List[str]]) – kwargs (Any) – Return type langchain.schema.LLMResult async agenerate_prompt(prompts, stop=None, callbacks=None, **kwargs) Take i...
https://api.python.langchain.com/en/latest/modules/llms.html
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Parameters text (str) – stop (Optional[Sequence[str]]) – kwargs (Any) – Return type str async apredict_messages(messages, *, stop=None, **kwargs) Predict message from messages. Parameters messages (List[langchain.schema.BaseMessage]) – stop (Optional[Sequence[str]]) – kwargs (Any) – Return type langchain.schema....
https://api.python.langchain.com/en/latest/modules/llms.html
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Return type Model copy(*, include=None, exclude=None, update=None, deep=False) Duplicate a model, optionally choose which fields to include, exclude and change. Parameters include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to include in new model exclude (Optional[Union[AbstractSetIntStr, MappingI...
https://api.python.langchain.com/en/latest/modules/llms.html
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kwargs (Any) – Return type Dict generate(prompts, stop=None, callbacks=None, *, tags=None, **kwargs) Run the LLM on the given prompt and input. Parameters prompts (List[str]) – stop (Optional[List[str]]) – callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCal...
https://api.python.langchain.com/en/latest/modules/llms.html
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kwargs (Any) – Return type langchain.schema.LLMResult get_num_tokens(text) Get the number of tokens present in the text. Parameters text (str) – Return type int get_num_tokens_from_messages(messages) Get the number of tokens in the message. Parameters messages (List[langchain.schema.BaseMessage]) – Return type int...
https://api.python.langchain.com/en/latest/modules/llms.html
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encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps(). Parameters include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – by_alias (bool) – skip_defaults (Optional[bool]) – exclude_unset (bo...
https://api.python.langchain.com/en/latest/modules/llms.html
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Return type str predict_messages(messages, *, stop=None, **kwargs) Predict message from messages. Parameters messages (List[langchain.schema.BaseMessage]) – stop (Optional[Sequence[str]]) – kwargs (Any) – Return type langchain.schema.BaseMessage save(file_path) Save the LLM. Parameters file_path (Union[pathlib.Pat...
https://api.python.langchain.com/en/latest/modules/llms.html
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serialized kwargs. These attributes must be accepted by the constructor. property lc_namespace: List[str] Return the namespace of the langchain object. eg. [β€œlangchain”, β€œllms”, β€œopenai”] property lc_secrets: Dict[str, str] Return a map of constructor argument names to secret ids. eg. {β€œopenai_api_key”: β€œOPENAI_API_K...
https://api.python.langchain.com/en/latest/modules/llms.html
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Wrapper around HuggingFaceHub 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 pass it as a named parameter to the constructor. Only supports text-generation, text2text-generation and summarization for now. E...
https://api.python.langchain.com/en/latest/modules/llms.html
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repo_id (str) – task (Optional[str]) – model_kwargs (Optional[dict]) – huggingfacehub_api_token (Optional[str]) – Return type None attribute model_kwargs: Optional[dict] = None Key word arguments to pass to the model. attribute repo_id: str = 'gpt2' Model name to use. attribute tags: Optional[List[str]] = None T...
https://api.python.langchain.com/en/latest/modules/llms.html
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Parameters prompt (str) – stop (Optional[List[str]]) – callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) – kwargs (Any) – Return type str async agenerate(prompts, stop=None, callbacks=None, *, tags=None, **kwargs) Run the LLM on the given ...
https://api.python.langchain.com/en/latest/modules/llms.html
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Parameters prompts (List[langchain.schema.PromptValue]) – stop (Optional[List[str]]) – callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) – kwargs (Any) – Return type langchain.schema.LLMResult async apredict(text, *, stop=None, **kwargs) P...
https://api.python.langchain.com/en/latest/modules/llms.html
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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 = β€˜allow’ was set since it adds all passed values Parameters _fields_set (Optional[SetStr]) – values (Any) – Return type Model copy...
https://api.python.langchain.com/en/latest/modules/llms.html
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the new model: you should trust this data deep (bool) – set to True to make a deep copy of the model self (Model) – Returns new model instance Return type Model dict(**kwargs) Return a dictionary of the LLM. Parameters kwargs (Any) – Return type Dict generate(prompts, stop=None, callbacks=None, *, tags=None, **kwarg...
https://api.python.langchain.com/en/latest/modules/llms.html
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Take in a list of prompt values and return an LLMResult. Parameters prompts (List[langchain.schema.PromptValue]) – stop (Optional[List[str]]) – callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) – kwargs (Any) – Return type langchain.schema....
https://api.python.langchain.com/en/latest/modules/llms.html
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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) Generate a JSON representation of the model, include and exclude arguments as per dict(). encoder is an optio...
https://api.python.langchain.com/en/latest/modules/llms.html
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models_as_dict (bool) – dumps_kwargs (Any) – Return type unicode predict(text, *, stop=None, **kwargs) Predict text from text. Parameters text (str) – stop (Optional[Sequence[str]]) – kwargs (Any) – Return type str predict_messages(messages, *, stop=None, **kwargs) Predict message from messages. Parameters messa...
https://api.python.langchain.com/en/latest/modules/llms.html
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classmethod update_forward_refs(**localns) Try to update ForwardRefs on fields based on this Model, globalns and localns. Parameters localns (Any) – Return type None property lc_attributes: Dict Return a list of attribute names that should be included in the serialized kwargs. These attributes must be accepted by th...
https://api.python.langchain.com/en/latest/modules/llms.html
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class langchain.llms.HuggingFacePipeline(*, cache=None, verbose=None, callbacks=None, callback_manager=None, tags=None, pipeline=None, model_id='gpt2', model_kwargs=None, pipeline_kwargs=None)[source] Bases: langchain.llms.base.LLM Wrapper around HuggingFace Pipeline API. To use, you should have the transformers pytho...
https://api.python.langchain.com/en/latest/modules/llms.html
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model_id = "gpt2" tokenizer = AutoTokenizer.from_pretrained(model_id) model = AutoModelForCausalLM.from_pretrained(model_id) pipe = pipeline( "text-generation", model=model, tokenizer=tokenizer, max_new_tokens=10 ) hf = HuggingFacePipeline(pipeline=pipe) Parameters cache (Optional[bool]) – verbose (bool) – callba...
https://api.python.langchain.com/en/latest/modules/llms.html
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Model name to use. attribute model_kwargs: Optional[dict] = None Key word arguments passed to the model. attribute pipeline_kwargs: Optional[dict] = None Key word arguments passed to the pipeline. attribute tags: Optional[List[str]] = None Tags to add to the run trace. attribute verbose: bool [Optional] Whether to ...
https://api.python.langchain.com/en/latest/modules/llms.html
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Run the LLM on the given prompt and input. Parameters prompts (List[str]) – stop (Optional[List[str]]) – callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) – tags (Optional[List[str]]) – kwargs (Any) – Return type langchain.schema.LLMResult...
https://api.python.langchain.com/en/latest/modules/llms.html
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Return type langchain.schema.LLMResult async apredict(text, *, stop=None, **kwargs) Predict text from text. Parameters text (str) – stop (Optional[Sequence[str]]) – kwargs (Any) – Return type str async apredict_messages(messages, *, stop=None, **kwargs) Predict message from messages. Parameters messages (List[lang...
https://api.python.langchain.com/en/latest/modules/llms.html
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Parameters _fields_set (Optional[SetStr]) – values (Any) – Return type Model copy(*, include=None, exclude=None, update=None, deep=False) Duplicate a model, optionally choose which fields to include, exclude and change. Parameters include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to include in ...
https://api.python.langchain.com/en/latest/modules/llms.html
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Model dict(**kwargs) Return a dictionary of the LLM. Parameters kwargs (Any) – Return type Dict classmethod from_model_id(model_id, task, device=- 1, model_kwargs=None, pipeline_kwargs=None, **kwargs)[source] Construct the pipeline object from model_id and task. Parameters model_id (str) – task (str) – device (int...
https://api.python.langchain.com/en/latest/modules/llms.html
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stop (Optional[List[str]]) – callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) – tags (Optional[List[str]]) – kwargs (Any) – Return type langchain.schema.LLMResult generate_prompt(prompts, stop=None, callbacks=None, **kwargs) Take in a lis...
https://api.python.langchain.com/en/latest/modules/llms.html
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Return type int get_num_tokens_from_messages(messages) Get the number of tokens in the message. Parameters messages (List[langchain.schema.BaseMessage]) – Return type int get_token_ids(text) Get the token present in the text. Parameters text (str) – Return type List[int] json(*, include=None, exclude=None, by_alias...
https://api.python.langchain.com/en/latest/modules/llms.html
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exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – by_alias (bool) – skip_defaults (Optional[bool]) – exclude_unset (bool) – exclude_defaults (bool) – exclude_none (bool) – encoder (Optional[Callable[[Any], Any]]) – models_as_dict (bool) – dumps_kwargs (Any) – Return type unicode predict(text, *,...
https://api.python.langchain.com/en/latest/modules/llms.html
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kwargs (Any) – Return type langchain.schema.BaseMessage save(file_path) Save the LLM. Parameters file_path (Union[pathlib.Path, str]) – Path to file to save the LLM to. Return type None Example: .. code-block:: python llm.save(file_path=”path/llm.yaml”) classmethod update_forward_refs(**localns) Try to update Forwar...
https://api.python.langchain.com/en/latest/modules/llms.html
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property lc_secrets: Dict[str, str] Return a map of constructor argument names to secret ids. eg. {β€œopenai_api_key”: β€œOPENAI_API_KEY”} property lc_serializable: bool Return whether or not the class is serializable. class langchain.llms.HuggingFaceTextGenInference(*, cache=None, verbose=None, callbacks=None, callback_...
https://api.python.langchain.com/en/latest/modules/llms.html
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It is used to generate text from a given prompt. 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 ...
https://api.python.langchain.com/en/latest/modules/llms.html
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- async_client: The async client object used to communicate with the server. Methods: - _call: Generates text based on a given prompt and stop sequences. - _acall: Async generates text based on a given prompt and stop sequences. - _llm_type: Returns the type of LLM. Parameters cache (Optional[bool]) – verbose (bool) –...
https://api.python.langchain.com/en/latest/modules/llms.html
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stop_sequences (List[str]) – seed (Optional[int]) – inference_server_url (str) – timeout (int) – server_kwargs (Dict[str, Any]) – stream (bool) – client (Any) – async_client (Any) – Return type None attribute tags: Optional[List[str]] = None Tags to add to the run trace. attribute verbose: bool [Optional] Whe...
https://api.python.langchain.com/en/latest/modules/llms.html
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Return type str async agenerate(prompts, stop=None, callbacks=None, *, tags=None, **kwargs) Run the LLM on the given prompt and input. Parameters prompts (List[str]) – stop (Optional[List[str]]) – callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManag...
https://api.python.langchain.com/en/latest/modules/llms.html
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kwargs (Any) – Return type langchain.schema.LLMResult async apredict(text, *, stop=None, **kwargs) Predict text from text. Parameters text (str) – stop (Optional[Sequence[str]]) – kwargs (Any) – Return type str async apredict_messages(messages, *, stop=None, **kwargs) Predict message from messages. Parameters mes...
https://api.python.langchain.com/en/latest/modules/llms.html
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Parameters _fields_set (Optional[SetStr]) – values (Any) – Return type Model copy(*, include=None, exclude=None, update=None, deep=False) Duplicate a model, optionally choose which fields to include, exclude and change. Parameters include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to include in ...
https://api.python.langchain.com/en/latest/modules/llms.html