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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
ff6d0b7b0742-156
exclude_defaults (bool) – 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 predi...
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.HumanInputLLM(*, cache=None, verbose=None, callbacks=None, callback_manager=None, tags=None, input_func=None, prompt_func=None, separator='\n', input_kwargs={}, prompt_kwargs={})[source] Bases: langchain.llms.base.LLM...
https://api.python.langchain.com/en/latest/modules/llms.html
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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 async agenerate_prompt(prompts, stop=None,...
https://api.python.langchain.com/en/latest/modules/llms.html
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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, MappingIntStrAny]]) ...
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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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.Path, str]) – Path to file to save the LLM to. Return type None Example...
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.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/latest/modules/llms.html
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n_ctx (int) – n_parts (int) – seed (int) – f16_kv (bool) – logits_all (bool) – vocab_only (bool) – use_mlock (bool) – n_threads (Optional[int]) – n_batch (Optional[int]) – n_gpu_layers (Optional[int]) – suffix (Optional[str]) – max_tokens (Optional[int]) – temperature (Optional[float]) – top_p (Optional[fl...
https://api.python.langchain.com/en/latest/modules/llms.html
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attribute max_tokens: Optional[int] = 256 The maximum number of tokens to generate. attribute model_path: str [Required] The path to the Llama model file. attribute n_batch: Optional[int] = 8 Number of tokens to process in parallel. Should be a number between 1 and n_ctx. attribute n_ctx: int = 512 Token context wi...
https://api.python.langchain.com/en/latest/modules/llms.html
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The top-p value to use for sampling. attribute use_mlock: bool = False Force system to keep model in RAM. attribute use_mmap: Optional[bool] = True Whether to keep the model loaded in RAM attribute verbose: bool [Optional] Whether to print out response text. attribute vocab_only: bool = False Only load the vocabula...
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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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, **kwargs) Run the LLM on the given prompt and input. Parameters prompts (List[str]) – stop (Optional[List[str]]) – callba...
https://api.python.langchain.com/en/latest/modules/llms.html
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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]]) – exclude (Optional[Union[AbstractSetIntStr, Map...
https://api.python.langchain.com/en/latest/modules/llms.html
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Once that happens, this interface could change. It also calls the callback manager’s 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/latest/modules/llms.html
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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.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/latest/modules/llms.html
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callback_manager (Optional[langchain.callbacks.base.BaseCallbackManager]) – tags (Optional[List[str]]) – model_url (str) – max_new_tokens (Optional[int]) – do_sample (bool) – temperature (Optional[float]) – top_p (Optional[float]) – typical_p (Optional[float]) – epsilon_cutoff (Optional[float]) – eta_cutoff (O...
https://api.python.langchain.com/en/latest/modules/llms.html
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Length Penalty attribute max_new_tokens: Optional[int] = 250 The maximum number of tokens to generate. attribute min_length: Optional[int] = 0 Minimum generation length in tokens. attribute model_url: str [Required] The full URL to the textgen webui including http[s]://host:port attribute no_repeat_ngram_size: Optio...
https://api.python.langchain.com/en/latest/modules/llms.html
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attribute top_k: Optional[float] = 40 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] = 0.1 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/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
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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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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=False, skip_defaults=None, exclude_unset=False, exclude...
https://api.python.langchain.com/en/latest/modules/llms.html
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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 ForwardRefs on fields based on this Model, globalns and localns...
https://api.python.langchain.com/en/latest/modules/llms.html
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llm_kwargs (Optional[Dict]) – Return type None attribute tags: Optional[List[str]] = None Tags to add to the run trace. 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 p...
https://api.python.langchain.com/en/latest/modules/llms.html
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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.BaseMessage classmethod c...
https://api.python.langchain.com/en/latest/modules/llms.html
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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.BaseCallbackManager]]) – tags (Optional...
https://api.python.langchain.com/en/latest/modules/llms.html
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Parameters include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – 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...
https://api.python.langchain.com/en/latest/modules/llms.html
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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_KEY”} property lc_serializable: bool Return whether or not the class is s...
https://api.python.langchain.com/en/latest/modules/llms.html
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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[List[str]]) – callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler],...
https://api.python.langchain.com/en/latest/modules/llms.html
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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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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 generate_prompt(prompts, stop=None, callba...
https://api.python.langchain.com/en/latest/modules/llms.html
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include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – 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 (b...
https://api.python.langchain.com/en/latest/modules/llms.html
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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_KEY”} property lc_serializable: bool Return whether or not the class is s...
https://api.python.langchain.com/en/latest/modules/llms.html
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endpoint_url (str) – inject_instruction_format (bool) – model_kwargs (Optional[dict]) – retry_sleep (float) – mosaicml_api_token (Optional[str]) – Return type None attribute endpoint_url: str = 'https://models.hosted-on.mosaicml.hosting/mpt-7b-instruct/v1/predict' Endpoint URL to use. attribute inject_instruction...
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
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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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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=False, skip_defaults=None, exclude_unset=False, exclude...
https://api.python.langchain.com/en/latest/modules/llms.html
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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 ForwardRefs on fields based on this Model, globalns and localns...
https://api.python.langchain.com/en/latest/modules/llms.html
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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]) – verbose (bool) – ...
https://api.python.langchain.com/en/latest/modules/llms.html
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Whether min_length and max_length should include the length of the input. attribute length_penalty: float = 1.0 Exponential penalty to the length. attribute max_length: int = 256 The maximum number of tokens to generate in the completion. attribute min_length: int = 1 The minimum number of tokens to generate in the ...
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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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 passed values Par...
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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exclude_defaults (bool) – 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 predi...
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.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/latest/modules/llms.html
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presence_penalty (float) – n (int) – best_of (int) – model_kwargs (Dict[str, Any]) – openai_api_key (Optional[str]) – openai_api_base (Optional[str]) – openai_organization (Optional[str]) – openai_proxy (Optional[str]) – batch_size (int) – request_timeout (Optional[Union[float, Tuple[float, float]]]) – logit_...
https://api.python.langchain.com/en/latest/modules/llms.html
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-1 returns as many tokens as possible given the prompt and the models maximal context size. attribute model_kwargs: Dict[str, Any] [Optional] Holds any model parameters valid for create call not explicitly specified. attribute model_name: str = 'text-davinci-003' (alias 'model') Model name to use. attribute n: int = ...
https://api.python.langchain.com/en/latest/modules/llms.html
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Total probability mass of tokens to consider at each step. 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[List[str]]) – callbacks (Optiona...
https://api.python.langchain.com/en/latest/modules/llms.html
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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.BaseMessage classmethod construct(_fields_set=None, **values) Creates a new model sett...
https://api.python.langchain.com/en/latest/modules/llms.html
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Return type langchain.schema.LLMResult dict(**kwargs) Return a dictionary of the LLM. Parameters 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 (O...
https://api.python.langchain.com/en/latest/modules/llms.html
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get_token_ids(text) Get the token IDs using the tiktoken package. 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 r...
https://api.python.langchain.com/en/latest/modules/llms.html
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max_tokens = openai.modelname_to_contextsize("text-davinci-003") 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 message...
https://api.python.langchain.com/en/latest/modules/llms.html
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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 the constructor. property lc_namespace: List[str] Return the namespace of the langchain object. eg. [β€œlangchain”, β€œllms”, β€œo...
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]]) – client (Any) – model_name (s...
https://api.python.langchain.com/en/latest/modules/llms.html
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Tags to add to the run trace. 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[List[str]]) – callbacks (Optional[Union[List[langchain.callba...
https://api.python.langchain.com/en/latest/modules/llms.html
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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
ff6d0b7b0742-211
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 generate_prompt(prompts, stop=None, callba...
https://api.python.langchain.com/en/latest/modules/llms.html
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include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – 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 (b...
https://api.python.langchain.com/en/latest/modules/llms.html
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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_KEY”} property lc_serializable: bool Return whether or not the class is s...
https://api.python.langchain.com/en/latest/modules/llms.html
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model_id (Optional[str]) – server_url (Optional[str]) – server_type (Literal['grpc', 'http']) – embedded (bool) – cache (Optional[bool]) – verbose (bool) – callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) – callback_manager (Optional[la...
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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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 passed values Par...
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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exclude_defaults (bool) – 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 predi...
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. property runner: openllm.LLMRunner Get the underlying openllm.LLMRunner instance for integration with BentoML. Example: .. code-block:: python llm = OpenLLM(model_name=’flan-t5’, model_id=’google/flan-t5-large’, embedded=False, ) tools = ...
https://api.python.langchain.com/en/latest/modules/llms.html
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callback_manager (Optional[langchain.callbacks.base.BaseCallbackManager]) – tags (Optional[List[str]]) – client (Any) – model (str) – temperature (float) – max_tokens (int) – top_p (float) – frequency_penalty (float) – presence_penalty (float) – n (int) – best_of (int) – model_kwargs (Dict[str, Any]) – open...
https://api.python.langchain.com/en/latest/modules/llms.html
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attribute logit_bias: Optional[Dict[str, float]] [Optional] Adjust the probability of specific tokens being generated. attribute max_retries: int = 6 Maximum number of retries to make when generating. attribute max_tokens: int = 256 The maximum number of tokens to generate in the completion. -1 returns as many token...
https://api.python.langchain.com/en/latest/modules/llms.html
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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 = 1 Total prob...
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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self (Model) – Returns new model instance Return type Model create_llm_result(choices, prompts, token_usage) Create the LLMResult from the choices and prompts. Parameters choices (Any) – prompts (List[str]) – token_usage (Dict[str, int]) – Return type langchain.schema.LLMResult dict(**kwargs) Return a dictionary ...
https://api.python.langchain.com/en/latest/modules/llms.html
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Parameters messages (List[langchain.schema.BaseMessage]) – Return type int get_sub_prompts(params, prompts, stop=None) Get the sub prompts for llm call. Parameters params (Dict[str, Any]) – prompts (List[str]) – stop (Optional[List[str]]) – Return type List[List[str]] get_token_ids(text) Get the token IDs using t...
https://api.python.langchain.com/en/latest/modules/llms.html
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int Example max_tokens = openai.max_token_for_prompt("Tell me a joke.") static modelname_to_contextsize(modelname) Calculate the maximum number of tokens possible to generate for a model. Parameters modelname (str) – 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/latest/modules/llms.html
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stop (Optional[List[str]]) – 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) Try to update...
https://api.python.langchain.com/en/latest/modules/llms.html
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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]) – verbose (bool) – callbacks (Optional[Unio...
https://api.python.langchain.com/en/latest/modules/llms.html
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Tags to add to the run trace. attribute temperature: float = 0.7 What sampling temperature to use attribute tokenizer: Any = None The tokenizer to use for the API calls. attribute top_k: Optional[int] = None 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/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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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, **kwargs) Run the LLM on the given prompt and input. Parameters prompts (List[str]) – stop (Optional[List[str]]) – callba...
https://api.python.langchain.com/en/latest/modules/llms.html
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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]]) – exclude (Optional[Union[AbstractSetIntStr, Map...
https://api.python.langchain.com/en/latest/modules/llms.html
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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] 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 ar...
https://api.python.langchain.com/en/latest/modules/llms.html
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attribute pipeline_key: str = '' The id or tag of the target pipeline attribute pipeline_kwargs: Dict[str, Any] [Optional] Holds any pipeline parameters valid for create call not explicitly specified. attribute tags: Optional[List[str]] = None Tags to add to the run trace. attribute verbose: bool [Optional] Whether...
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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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, **kwargs) Run the LLM on the given prompt and input. Parameters prompts (List[str]) – stop (Optional[List[str]]) – callba...
https://api.python.langchain.com/en/latest/modules/llms.html
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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]]) – exclude (Optional[Union[AbstractSetIntStr, Map...
https://api.python.langchain.com/en/latest/modules/llms.html
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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] 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 ar...
https://api.python.langchain.com/en/latest/modules/llms.html
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tags (Optional[List[str]]) – client (Any) – model (Optional[str]) – output (Optional[Dict[str, Any]]) – max_tokens (int) – temperature (float) – token (Optional[str]) – stop (Optional[List[str]]) – Return type None attribute max_tokens: int = 256 Denotes the number of tokens to predict per generation. attribut...
https://api.python.langchain.com/en/latest/modules/llms.html
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tags (Optional[List[str]]) – 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...
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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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=False, skip_defaults=None, exclude_unset=False, exclude...
https://api.python.langchain.com/en/latest/modules/llms.html
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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 ForwardRefs on fields based on this Model, globalns and localns...
https://api.python.langchain.com/en/latest/modules/llms.html
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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/latest/modules/llms.html
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max_retries (int) – streaming (bool) – allowed_special (Union[Literal['all'], typing.AbstractSet[str]]) – disallowed_special (Union[Literal['all'], typing.Collection[str]]) – tiktoken_model_name (Optional[str]) – Return type None Example from langchain.llms import PromptLayerOpenAI openai = PromptLayerOpenAI(model...
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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self (Model) – Returns new model instance Return type Model create_llm_result(choices, prompts, token_usage) Create the LLMResult from the choices and prompts. Parameters choices (Any) – prompts (List[str]) – token_usage (Dict[str, int]) – Return type langchain.schema.LLMResult dict(**kwargs) Return a dictionary ...
https://api.python.langchain.com/en/latest/modules/llms.html
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Parameters messages (List[langchain.schema.BaseMessage]) – Return type int get_sub_prompts(params, prompts, stop=None) Get the sub prompts for llm call. Parameters params (Dict[str, Any]) – prompts (List[str]) – stop (Optional[List[str]]) – Return type List[List[str]] get_token_ids(text) Get the token IDs using t...
https://api.python.langchain.com/en/latest/modules/llms.html
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int Example max_tokens = openai.max_token_for_prompt("Tell me a joke.") static modelname_to_contextsize(modelname) Calculate the maximum number of tokens possible to generate for a model. Parameters modelname (str) – 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/latest/modules/llms.html
ff6d0b7b0742-250
stop (Optional[List[str]]) – 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) Try to update...
https://api.python.langchain.com/en/latest/modules/llms.html
ff6d0b7b0742-251
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/latest/modules/llms.html
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Set of special tokens that are allowed。 attribute disallowed_special: Union[Literal['all'], Collection[str]] = 'all' Set of special tokens that are not allowed。 attribute max_retries: int = 6 Maximum number of retries to make when generating. attribute model_kwargs: Dict[str, Any] [Optional] Holds any model paramete...
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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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