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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(). predict(text: str, *, stop: Optional[Sequence[str]] = None, **kwargs: Any) → str# Predict text from text. predict_messages(...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
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environment variable NLPCLOUD_API_KEY set with your API key. Example from langchain.llms import NLPCloud nlpcloud = NLPCloud(model="gpt-neox-20b") Validators raise_deprecation » all fields set_verbose » verbose validate_environment » all fields field bad_words: List[str] = []# List of tokens not allowed to be generated...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
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What sampling temperature to use. field top_k: int = 50# The number of highest probability tokens to keep for top-k filtering. field top_p: int = 1# Total probability mass of tokens to consider at each step. field verbose: bool [Optional]# Whether to print out response text. __call__(prompt: str, stop: Optional[List[st...
rtdocs_stable/api.python.langchain.com/en/stable/reference/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 = ‘allow’ was set since it adds all passed values copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclu...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
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get_num_tokens(text: str) → int# Get the number of tokens present in the text. get_num_tokens_from_messages(messages: List[langchain.schema.BaseMessage]) → int# Get the number of tokens in the message. get_token_ids(text: str) → List[int]# Get the token present in the text. json(*, include: Optional[Union[AbstractSetIn...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
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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. [“langchain”, “llms”, “openai”] property lc_secrets: Dict[str, str]# ...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
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field frequency_penalty: float = 0# Penalizes repeated tokens according to frequency. field logit_bias: Optional[Dict[str, float]] [Optional]# Adjust the probability of specific tokens being generated. field max_retries: int = 6# Maximum number of retries to make when generating. field max_tokens: int = 256# The maximu...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
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Check Cache and run the LLM on the given prompt and input. async agenerate(prompts: List[str], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, **kwargs: Any) → lang...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
14c2a1c4ad3b-129
Duplicate a model, optionally choose which fields to include, exclude and change. Parameters include – fields to include in new model exclude – fields to exclude from new model, as with values this takes precedence over include update – values to change/add in the new model. Note: the data is not validated before creat...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
14c2a1c4ad3b-130
Get the sub prompts for llm call. get_token_ids(text: str) → List[int]# Get the token IDs using the tiktoken package. json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] ...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
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Predict message from messages. prep_streaming_params(stop: Optional[List[str]] = None) → Dict[str, Any]# Prepare the params for streaming. save(file_path: Union[pathlib.Path, str]) → None# Save the LLM. Parameters file_path – Path to file to save the LLM to. Example: .. code-block:: python llm.save(file_path=”path/llm....
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
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pydantic model langchain.llms.OpenAIChat[source]# Wrapper around OpenAI Chat large language models. To use, you should have the openai python package installed, and the environment variable OPENAI_API_KEY set with your API key. Any parameters that are valid to be passed to the openai.create call can be passed in, even ...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
14c2a1c4ad3b-133
Check Cache and run the LLM on the given prompt and input. async agenerate(prompts: List[str], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, **kwargs: Any) → lang...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
14c2a1c4ad3b-134
Duplicate a model, optionally choose which fields to include, exclude and change. Parameters include – fields to include in new model exclude – fields to exclude from new model, as with values this takes precedence over include update – values to change/add in the new model. Note: the data is not validated before creat...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
14c2a1c4ad3b-135
Get the token IDs using the tiktoken package. json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exc...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
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eg. [“langchain”, “llms”, “openai”] property lc_secrets: Dict[str, str]# Return a map of constructor argument names to secret ids. eg. {“openai_api_key”: “OPENAI_API_KEY”} property lc_serializable: bool# Return whether or not the class is serializable. pydantic model langchain.llms.OpenLM[source]# Validators build_extr...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
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Model name to use. field n: int = 1# How many completions to generate for each prompt. field presence_penalty: float = 0# Penalizes repeated tokens. field request_timeout: Optional[Union[float, Tuple[float, float]]] = None# Timeout for requests to OpenAI completion API. Default is 600 seconds. field streaming: bool = F...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
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Take in a list of prompt values and return an LLMResult. async apredict(text: str, *, stop: Optional[Sequence[str]] = None, **kwargs: Any) → str# Predict text from text. async apredict_messages(messages: List[langchain.schema.BaseMessage], *, stop: Optional[Sequence[str]] = None, **kwargs: Any) → langchain.schema.BaseM...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
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dict(**kwargs: Any) → Dict# Return a dictionary of the LLM. generate(prompts: List[str], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, **kwargs: Any) → langchain....
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
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Get the token IDs using the tiktoken package. json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exc...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
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Prepare the params for streaming. save(file_path: Union[pathlib.Path, str]) → None# Save the LLM. Parameters file_path – Path to file to save the LLM to. Example: .. code-block:: python llm.save(file_path=”path/llm.yaml”) stream(prompt: str, stop: Optional[List[str]] = None) → Generator# Call OpenAI with streaming flag...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
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To use, you should have the petals python package installed, and the 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() Validators...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
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field verbose: bool [Optional]# Whether to print out response text. __call__(prompt: str, stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None, **kwargs: Any) → str# Check Cache and run the LLM on the given ...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
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Behaves as if Config.extra = ‘allow’ was set since it adds all passed values copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model# Duplicate a model, optionally...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
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get_num_tokens_from_messages(messages: List[langchain.schema.BaseMessage]) → int# Get the number of tokens in the message. get_token_ids(text: str) → List[int]# Get the token present in the text. json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, Map...
rtdocs_stable/api.python.langchain.com/en/stable/reference/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. [“langchain”, “llms”, “openai”] property lc_secrets: Dict[str, str]# Return a map of constructor argument names to secret ids. eg. {“openai_api_key”: “OPENAI_API_K...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
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Check Cache and run the LLM on the given prompt and input. async agenerate(prompts: List[str], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, **kwargs: Any) → lang...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
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Duplicate a model, optionally choose which fields to include, exclude and change. Parameters include – fields to include in new model exclude – fields to exclude from new model, as with values this takes precedence over include update – values to change/add in the new model. Note: the data is not validated before creat...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
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Get the token present in the text. json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: ...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
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eg. [“langchain”, “llms”, “openai”] property lc_secrets: Dict[str, str]# Return a map of constructor argument names to secret ids. eg. {“openai_api_key”: “OPENAI_API_KEY”} property lc_serializable: bool# Return whether or not the class is serializable. pydantic model langchain.llms.PredictionGuard[source]# Wrapper arou...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
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field verbose: bool [Optional]# Whether to print out response text. __call__(prompt: str, stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None, **kwargs: Any) → str# Check Cache and run the LLM on the given ...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
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Behaves as if Config.extra = ‘allow’ was set since it adds all passed values copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model# Duplicate a model, optionally...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
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get_num_tokens_from_messages(messages: List[langchain.schema.BaseMessage]) → int# Get the number of tokens in the message. get_token_ids(text: str) → List[int]# Get the token present in the text. json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, Map...
rtdocs_stable/api.python.langchain.com/en/stable/reference/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. [“langchain”, “llms”, “openai”] property lc_secrets: Dict[str, str]# Return a map of constructor argument names to secret ids. eg. {“openai_api_key”: “OPENAI_API_K...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
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Check Cache and run the LLM on the given prompt and input. async agenerate(prompts: List[str], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, **kwargs: Any) → lang...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
14c2a1c4ad3b-156
Duplicate a model, optionally choose which fields to include, exclude and change. Parameters include – fields to include in new model exclude – fields to exclude from new model, as with values this takes precedence over include update – values to change/add in the new model. Note: the data is not validated before creat...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
14c2a1c4ad3b-157
Get the sub prompts for llm call. get_token_ids(text: str) → List[int]# Get the token IDs using the tiktoken package. json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] ...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
14c2a1c4ad3b-158
Predict message from messages. prep_streaming_params(stop: Optional[List[str]] = None) → Dict[str, Any]# Prepare the params for streaming. save(file_path: Union[pathlib.Path, str]) → None# Save the LLM. Parameters file_path – Path to file to save the LLM to. Example: .. code-block:: python llm.save(file_path=”path/llm....
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
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pydantic model langchain.llms.PromptLayerOpenAIChat[source]# 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 pa...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
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field streaming: bool = False# Whether to stream the results or not. __call__(prompt: str, stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None, **kwargs: Any) → str# Check Cache and run the LLM on the given...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
14c2a1c4ad3b-161
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model# Duplicate a model, optionally...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
14c2a1c4ad3b-162
get_num_tokens_from_messages(messages: List[langchain.schema.BaseMessage]) → int# Get the number of tokens in the message. get_token_ids(text: str) → List[int]# Get the token IDs using the tiktoken package. json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSet...
rtdocs_stable/api.python.langchain.com/en/stable/reference/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. [“langchain”, “llms”, “openai”] property lc_secrets: Dict[str, str]# Return a map of constructor argument names to secret ids. eg. {“openai_api_key”: “OPENAI_API_K...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
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new topics.. field rwkv_verbose: bool = True# Print debug information. field strategy: str = 'cpu fp32'# Token context window. field tags: Optional[List[str]] = None# Tags to add to the run trace. field temperature: float = 1.0# The temperature to use for sampling. field tokens_path: str [Required]# Path to the RWKV to...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
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Predict text from text. async apredict_messages(messages: List[langchain.schema.BaseMessage], *, stop: Optional[Sequence[str]] = None, **kwargs: Any) → langchain.schema.BaseMessage# Predict message from messages. classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model# Creates a new model set...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
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Run the LLM on the given prompt and input. generate_prompt(prompts: List[langchain.schema.PromptValue], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None, **kwargs: Any) → langchain.schema.LLMResult# Take...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
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save(file_path: Union[pathlib.Path, str]) → None# Save the LLM. Parameters file_path – Path to file to save the LLM to. Example: .. code-block:: python llm.save(file_path=”path/llm.yaml”) classmethod update_forward_refs(**localns: Any) → None# Try to update ForwardRefs on fields based on this Model, globalns and localn...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
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input={"image_dimensions": "512x512"}) Validators build_extra » all fields raise_deprecation » all fields set_verbose » verbose validate_environment » all fields field tags: Optional[List[str]] = None# Tags to add to the run trace. field verbose: bool [Optional]# Whether to print out response text. __call__(prompt: str...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
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Predict message from messages. classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model# Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set ...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
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Run the LLM on the given prompt and input. generate_prompt(prompts: List[langchain.schema.PromptValue], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None, **kwargs: Any) → langchain.schema.LLMResult# Take...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
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save(file_path: Union[pathlib.Path, str]) → None# Save the LLM. Parameters file_path – Path to file to save the LLM to. Example: .. code-block:: python llm.save(file_path=”path/llm.yaml”) classmethod update_forward_refs(**localns: Any) → None# Try to update ForwardRefs on fields based on this Model, globalns and localn...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
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Validators raise_deprecation » all fields set_verbose » verbose validate_environment » all fields field content_handler: langchain.llms.sagemaker_endpoint.LLMContentHandler [Required]# The content handler class that provides an input and output transform functions to handle formats between LLM and the endpoint. field c...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
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Check Cache and run the LLM on the given prompt and input. async agenerate(prompts: List[str], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, **kwargs: Any) → lang...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
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Duplicate a model, optionally choose which fields to include, exclude and change. Parameters include – fields to include in new model exclude – fields to exclude from new model, as with values this takes precedence over include update – values to change/add in the new model. Note: the data is not validated before creat...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
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Get the token present in the text. json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: ...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
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eg. [“langchain”, “llms”, “openai”] property lc_secrets: Dict[str, str]# Return a map of constructor argument names to secret ids. eg. {“openai_api_key”: “OPENAI_API_KEY”} property lc_serializable: bool# Return whether or not the class is serializable. pydantic model langchain.llms.SelfHostedHuggingFaceLLM[source]# Wra...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
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"text-generation", model=model, tokenizer=tokenizer ) return pipe hf = SelfHostedHuggingFaceLLM( model_load_fn=get_pipeline, model_id="gpt2", hardware=gpu) Validators raise_deprecation » all fields set_verbose » verbose field device: int = 0# Device to use for inference. -1 for CPU, 0 for GPU, 1 for second ...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
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Check Cache and run the LLM on the given prompt and input. async agenerate(prompts: List[str], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, **kwargs: Any) → lang...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
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Duplicate a model, optionally choose which fields to include, exclude and change. Parameters include – fields to include in new model exclude – fields to exclude from new model, as with values this takes precedence over include update – values to change/add in the new model. Note: the data is not validated before creat...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
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get_token_ids(text: str) → List[int]# Get the token present in the text. json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
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property lc_namespace: List[str]# Return the namespace of the langchain object. eg. [“langchain”, “llms”, “openai”] property lc_secrets: Dict[str, str]# Return a map of constructor argument names to secret ids. eg. {“openai_api_key”: “OPENAI_API_KEY”} property lc_serializable: bool# Return whether or not the class is s...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
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model_reqs=model_reqs, inference_fn=inference_fn ) Example for <2GB model (can be serialized and sent directly to the server):from langchain.llms import SelfHostedPipeline import runhouse as rh gpu = rh.cluster(name="rh-a10x", instance_type="A100:1") my_model = ... llm = SelfHostedPipeline.from_pipeline( pipeline=m...
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field verbose: bool [Optional]# Whether to print out response text. __call__(prompt: str, stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None, **kwargs: Any) → str# Check Cache and run the LLM on the given ...
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Behaves as if Config.extra = ‘allow’ was set since it adds all passed values copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model# Duplicate a model, optionally...
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Take in a list of prompt values and return an LLMResult. get_num_tokens(text: str) → int# Get the number of tokens present in the text. get_num_tokens_from_messages(messages: List[langchain.schema.BaseMessage]) → int# Get the number of tokens in the message. get_token_ids(text: str) → List[int]# Get the token present i...
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classmethod update_forward_refs(**localns: Any) → None# Try to update ForwardRefs on fields based on this Model, globalns and localns. 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_namesp...
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Check Cache and run the LLM on the given prompt and input. async agenerate(prompts: List[str], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, **kwargs: Any) → lang...
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Duplicate a model, optionally choose which fields to include, exclude and change. Parameters include – fields to include in new model exclude – fields to exclude from new model, as with values this takes precedence over include update – values to change/add in the new model. Note: the data is not validated before creat...
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Get the token present in the text. json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: ...
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eg. [“langchain”, “llms”, “openai”] property lc_secrets: Dict[str, str]# Return a map of constructor argument names to secret ids. eg. {“openai_api_key”: “OPENAI_API_KEY”} property lc_serializable: bool# Return whether or not the class is serializable. pydantic model langchain.llms.VertexAI[source]# Wrapper around Goog...
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field verbose: bool [Optional]# Whether to print out response text. __call__(prompt: str, stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None, **kwargs: Any) → str# Check Cache and run the LLM on the given ...
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Behaves as if Config.extra = ‘allow’ was set since it adds all passed values copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model# Duplicate a model, optionally...
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get_num_tokens_from_messages(messages: List[langchain.schema.BaseMessage]) → int# Get the number of tokens in the message. get_token_ids(text: str) → List[int]# Get the token present in the text. json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, Map...
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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. [“langchain”, “llms”, “openai”] property lc_secrets: Dict[str, str]# Return a map of constructor argument names to secret ids. eg. {“openai_api_key”: “OPENAI_API_K...
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field stop: Optional[List[str]] = None# Sequences when completion generation will stop. field tags: Optional[List[str]] = None# Tags to add to the run trace. field temperature: Optional[float] = None# What sampling temperature to use. field top_p: Optional[float] = None# Total probability mass of tokens to consider at ...
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Predict text from text. async apredict_messages(messages: List[langchain.schema.BaseMessage], *, stop: Optional[Sequence[str]] = None, **kwargs: Any) → langchain.schema.BaseMessage# Predict message from messages. classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model# Creates a new model set...
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Run the LLM on the given prompt and input. generate_prompt(prompts: List[langchain.schema.PromptValue], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None, **kwargs: Any) → langchain.schema.LLMResult# Take...
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save(file_path: Union[pathlib.Path, str]) → None# Save the LLM. Parameters file_path – Path to file to save the LLM to. Example: .. code-block:: python llm.save(file_path=”path/llm.yaml”) classmethod update_forward_refs(**localns: Any) → None# Try to update ForwardRefs on fields based on this Model, globalns and localn...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html
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.rst .pdf Document Loaders Document Loaders# All different types of document loaders. class langchain.document_loaders.AZLyricsLoader(web_path: Union[str, List[str]], header_template: Optional[dict] = None)[source]# Loader that loads AZLyrics webpages. load() → List[langchain.schema.Document][source]# Load webpage. cla...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/document_loaders.html
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field dataset_mapping_function: Callable[[Dict], langchain.schema.Document] [Required]# A custom function that takes a single dictionary (an Apify dataset item) and converts it to an instance of the Document class. load() → List[langchain.schema.Document][source]# Load documents. class langchain.document_loaders.ArxivL...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/document_loaders.html
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Load data into document objects. class langchain.document_loaders.BibtexLoader(file_path: str, *, parser: Optional[langchain.utilities.bibtex.BibtexparserWrapper] = None, max_docs: Optional[int] = None, max_content_chars: Optional[int] = 4000, load_extra_metadata: bool = False, file_pattern: str = '[^:]+\\.pdf')[source...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/document_loaders.html
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are written into the page_content of the document. The metadata_columns are written into the metadata of the document. By default, all columns are written into the page_content and none into the metadata. load() → List[langchain.schema.Document][source]# Load data into document objects. class langchain.document_loaders...
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Download a file from a url. Parameters path – Path to the file. folder_path: str# load() → List[langchain.schema.Document][source]# Load data into document objects. Returns List of documents. load_all_recursively: bool# parse_filename(url: str) → str[source]# Parse the filename from a url. Parameters url – Url to parse...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/document_loaders.html
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Support additional Alchemy APIs (e.g. getTransactions, etc.) Support additional blockain APIs (e.g. Infura, Opensea, etc.) load() → List[langchain.schema.Document][source]# Load data into document objects. class langchain.document_loaders.CSVLoader(file_path: str, source_column: Optional[str] = None, csv_args: Optional...
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load() → List[langchain.schema.Document][source]# Load from file path. class langchain.document_loaders.CollegeConfidentialLoader(web_path: Union[str, List[str]], header_template: Optional[dict] = None)[source]# Loader that loads College Confidential webpages. load() → List[langchain.schema.Document][source]# Load webp...
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a enum content_format argument to load() to specify the content format, this is set to ContentFormat.STORAGE by default. Hint: space_key and page_id can both be found in the URL of a page in Confluence - https://yoursite.atlassian.com/wiki/spaces/<space_key>/pages/<page_id> Example from langchain.document_loaders impor...
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Check if a page is publicly accessible. load(space_key: Optional[str] = None, page_ids: Optional[List[str]] = None, label: Optional[str] = None, cql: Optional[str] = None, include_restricted_content: bool = False, include_archived_content: bool = False, include_attachments: bool = False, include_comments: bool = False,...
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ValueError – _description_ ImportError – _description_ Returns _description_ Return type List[Document] paginate_request(retrieval_method: Callable, **kwargs: Any) → List[source]# Paginate the various methods to retrieve groups of pages. Unfortunately, due to page size, sometimes the Confluence API doesn’t match the li...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/document_loaders.html
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process_pages(pages: List[dict], include_restricted_content: bool, include_attachments: bool, include_comments: bool, content_format: langchain.document_loaders.confluence.ContentFormat, ocr_languages: Optional[str] = None) → List[langchain.schema.Document][source]# Process a list of pages into a list of documents. pro...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/document_loaders.html
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Extract text from Diffbot on all the URLs and return Document instances class langchain.document_loaders.DirectoryLoader(path: str, glob: str = '**/[!.]*', silent_errors: bool = False, load_hidden: bool = False, loader_cls: typing.Union[typing.Type[langchain.document_loaders.unstructured.UnstructuredFileLoader], typing...
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field file_paths: Optional[Sequence[Union[pathlib.Path, str]]] = None# field min_chunk_size: int = 32# load() → List[langchain.schema.Document][source]# Load documents. class langchain.document_loaders.Docx2txtLoader(file_path: str)[source]# Loads a DOCX with docx2txt and chunks at character level. Defaults to check fo...
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loader = EmbaasBlobLoader() blob = Blob.from_path(path="example.mp3") documents = loader.parse(blob=blob) # Custom api parameters (create embeddings automatically) from langchain.document_loaders.embaas import EmbaasBlobLoader loader = EmbaasBlobLoader( params={ "should_embed": True, "model": "e5-la...
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} ) documents = loader.load() Validators validate_blob_loader » blob_loader validate_environment » all fields field blob_loader: Optional[langchain.document_loaders.embaas.EmbaasBlobLoader] = None# The blob loader to use. If not provided, a default one will be created. field file_path: str [Required]# The path to the f...
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notes into a single long Document. True (If this is set to) – the ‘source’ which contains the file name of the export. load() → List[langchain.schema.Document][source]# Load documents from EverNote export file. class langchain.document_loaders.FacebookChatLoader(path: str)[source]# Loader that loads Facebook messages j...
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Loading logic for loading documents from GCS. load() → List[langchain.schema.Document][source]# Load documents. pydantic model langchain.document_loaders.GitHubIssuesLoader[source]# Validators validate_environment » all fields validate_since » since field assignee: Optional[str] = None# Filter on assigned user. Pass ‘n...
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field state: Optional[Literal['open', 'closed', 'all']] = None# Filter on issue state. Can be one of: ‘open’, ‘closed’, ‘all’. lazy_load() → Iterator[langchain.schema.Document][source]# Get issues of a GitHub repository. Returns page_content metadata url title creator created_at last_update_time closed_time number of c...
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Load data into document objects. class langchain.document_loaders.GitbookLoader(web_page: str, load_all_paths: bool = False, base_url: Optional[str] = None, content_selector: str = 'main')[source]# Load GitBook data. load from either a single page, or load all (relative) paths in the navbar. load() → List[langchain.sch...
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Validate that either folder_id or document_ids is set, but not both. class langchain.document_loaders.GoogleApiYoutubeLoader(google_api_client: langchain.document_loaders.youtube.GoogleApiClient, channel_name: Optional[str] = None, video_ids: Optional[List[str]] = None, add_video_info: bool = True, captions_language: s...
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Loader that loads Google Docs from Google Drive. Validators validate_credentials_path » credentials_path validate_inputs » all fields field credentials_path: pathlib.Path = PosixPath('/home/docs/.credentials/credentials.json')# field document_ids: Optional[List[str]] = None# field file_ids: Optional[List[str]] = None# ...
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Load items from an HN page. class langchain.document_loaders.HuggingFaceDatasetLoader(path: str, page_content_column: str = 'text', name: Optional[str] = None, data_dir: Optional[str] = None, data_files: Optional[Union[str, Sequence[str], Mapping[str, Union[str, Sequence[str]]]]] = None, cache_dir: Optional[str] = None...
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/document_loaders.html