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To wrap it as an LLM you must have β€œCan Query” permission to the endpoint. Set endpoint_name accordingly and do not set cluster_id and cluster_driver_port. The expected model signature is: inputs: [{"name": "prompt", "type": "string"}, {"name": "stop", "type": "list[string]"}] outputs: [{"type": "string"}] Cluster dri...
https://python.langchain.com/en/latest/reference/modules/llms.html
98a4fcd9b56e-40
Databricks personal access token. If not provided, the default value is determined by the DATABRICKS_API_TOKEN environment variable if present, or an automatically generated temporary token if running inside a Databricks notebook attached to an interactive cluster in β€œsingle user” or β€œno isolation shared” mode. field c...
https://python.langchain.com/en/latest/reference/modules/llms.html
98a4fcd9b56e-41
field transform_input_fn: Optional[Callable] = None# A function that transforms {prompt, stop, **kwargs} into a JSON-compatible request object that the endpoint accepts. For example, you can apply a prompt template to the input prompt. field transform_output_fn: Optional[Callable[[...], str]] = None# A function that tr...
https://python.langchain.com/en/latest/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 = β€˜allow’ was set since it adds all passed values copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclu...
https://python.langchain.com/en/latest/reference/modules/llms.html
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Get the number of tokens present in the text. get_num_tokens_from_messages(messages: List[langchain.schema.BaseMessage]) β†’ int# Get the number of tokens in the message. get_token_ids(text: str) β†’ List[int]# Get the token present in the text. json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, ...
https://python.langchain.com/en/latest/reference/modules/llms.html
98a4fcd9b56e-44
Wrapper around DeepInfra deployed models. To use, you should have the requests python package installed, and the environment variable DEEPINFRA_API_TOKEN set with your API token, or pass it as a named parameter to the constructor. Only supports text-generation and text2text-generation for now. Example from langchain.ll...
https://python.langchain.com/en/latest/reference/modules/llms.html
98a4fcd9b56e-45
Predict text from text. async apredict_messages(messages: List[langchain.schema.BaseMessage], *, stop: Optional[Sequence[str]] = None) β†’ langchain.schema.BaseMessage# Predict message from messages. classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) β†’ Model# Creates a new model setting __dict__ a...
https://python.langchain.com/en/latest/reference/modules/llms.html
98a4fcd9b56e-46
Run the LLM on the given prompt and input. generate_prompt(prompts: List[langchain.schema.PromptValue], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None) β†’ langchain.schema.LLMResult# Take in a list of p...
https://python.langchain.com/en/latest/reference/modules/llms.html
98a4fcd9b56e-47
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) β†’ None# Try to update ForwardRefs on fields based on this Model, globalns and localns. pydantic model langchain.llms.FakeListLLM[sourc...
https://python.langchain.com/en/latest/reference/modules/llms.html
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Predict message from messages. classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) β†’ Model# Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = β€˜allow’ was set ...
https://python.langchain.com/en/latest/reference/modules/llms.html
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Take in a list of prompt values and return an LLMResult. get_num_tokens(text: str) β†’ int# Get the number of tokens present in the text. get_num_tokens_from_messages(messages: List[langchain.schema.BaseMessage]) β†’ int# Get the number of tokens in the message. get_token_ids(text: str) β†’ List[int]# Get the token present i...
https://python.langchain.com/en/latest/reference/modules/llms.html
98a4fcd9b56e-50
Try to update ForwardRefs on fields based on this Model, globalns and localns. pydantic model langchain.llms.ForefrontAI[source]# Wrapper around ForefrontAI large language models. To use, you should have the environment variable FOREFRONTAI_API_KEY set with your API key. Example from langchain.llms import ForefrontAI f...
https://python.langchain.com/en/latest/reference/modules/llms.html
98a4fcd9b56e-51
Run the LLM on the given prompt and input. async agenerate_prompt(prompts: List[langchain.schema.PromptValue], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None) β†’ langchain.schema.LLMResult# Take in a li...
https://python.langchain.com/en/latest/reference/modules/llms.html
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Returns new model instance dict(**kwargs: Any) β†’ Dict# Return a dictionary of the LLM. generate(prompts: List[str], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None) β†’ langchain.schema.LLMResult# Run the...
https://python.langchain.com/en/latest/reference/modules/llms.html
98a4fcd9b56e-53
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps(). predict(text: str, *, stop: Optional[Sequence[str]] = None) β†’ str# Predict text from text. predict_messages(messages: List[langchain.schema.BaseMessage], *, stop: Optional[Sequence[str]] = None) β†’ langchain.schema...
https://python.langchain.com/en/latest/reference/modules/llms.html
98a4fcd9b56e-54
field f16_kv: bool = False# Use half-precision for key/value cache. field logits_all: bool = False# Return logits for all tokens, not just the last token. field model: str [Required]# Path to the pre-trained GPT4All model file. field n_batch: int = 1# Batch size for prompt processing. field n_ctx: int = 512# Token cont...
https://python.langchain.com/en/latest/reference/modules/llms.html
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field vocab_only: bool = False# Only load the vocabulary, no weights. __call__(prompt: str, stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None) β†’ str# Check Cache and run the LLM on the given prompt and in...
https://python.langchain.com/en/latest/reference/modules/llms.html
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Behaves as if Config.extra = β€˜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) β†’ Model# Duplicate a model, optionally...
https://python.langchain.com/en/latest/reference/modules/llms.html
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get_token_ids(text: str) β†’ List[int]# Get the token present in the text. json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_...
https://python.langchain.com/en/latest/reference/modules/llms.html
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If unset, will default to 64. field model_name: str = 'models/text-bison-001'# Model name to use. field n: int = 1# Number of chat completions to generate for each prompt. Note that the API may not return the full n completions if duplicates are generated. field temperature: float = 0.7# Run inference with this tempera...
https://python.langchain.com/en/latest/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) β†’ str# Predict text from text. async apredict_messages(messages: List[langchain.schema.BaseMessage], *, stop: Optional[Sequence[str]] = None) β†’ langchain.schema.BaseMessage# Predict message from m...
https://python.langchain.com/en/latest/reference/modules/llms.html
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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) β†’ langchain.schema.LLMResult# Take in a list of p...
https://python.langchain.com/en/latest/reference/modules/llms.html
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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) β†’ None# Try to update ForwardRefs on fields based on this Model, globalns and localns. pydantic model langchain.llms.GooseAI[source]# ...
https://python.langchain.com/en/latest/reference/modules/llms.html
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Penalizes repeated tokens. field temperature: float = 0.7# What sampling temperature to use field top_p: float = 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[str]] = None, callbacks: Optional[U...
https://python.langchain.com/en/latest/reference/modules/llms.html
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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 copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny...
https://python.langchain.com/en/latest/reference/modules/llms.html
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Get the number of tokens in the message. get_token_ids(text: str) β†’ List[int]# Get the token present in the text. json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = No...
https://python.langchain.com/en/latest/reference/modules/llms.html
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environment variable HUGGINGFACEHUB_API_TOKEN set with your API token, or pass it as a named parameter to the constructor. Only supports text-generation and text2text-generation for now. Example from langchain.llms import HuggingFaceEndpoint endpoint_url = ( "https://abcdefghijklmnop.us-east-1.aws.endpoints.hugging...
https://python.langchain.com/en/latest/reference/modules/llms.html
98a4fcd9b56e-66
Run the LLM on the given prompt and input. async agenerate_prompt(prompts: List[langchain.schema.PromptValue], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None) β†’ langchain.schema.LLMResult# Take in a li...
https://python.langchain.com/en/latest/reference/modules/llms.html
98a4fcd9b56e-67
Returns new model instance dict(**kwargs: Any) β†’ Dict# Return a dictionary of the LLM. generate(prompts: List[str], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None) β†’ langchain.schema.LLMResult# Run the...
https://python.langchain.com/en/latest/reference/modules/llms.html
98a4fcd9b56e-68
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps(). predict(text: str, *, stop: Optional[Sequence[str]] = None) β†’ str# Predict text from text. predict_messages(messages: List[langchain.schema.BaseMessage], *, stop: Optional[Sequence[str]] = None) β†’ langchain.schema...
https://python.langchain.com/en/latest/reference/modules/llms.html
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Task to call the model with. Should be a task that returns generated_text or summary_text. field verbose: bool [Optional]# Whether to print out response text. __call__(prompt: str, stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.Ba...
https://python.langchain.com/en/latest/reference/modules/llms.html
98a4fcd9b56e-70
Behaves as if Config.extra = β€˜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) β†’ Model# Duplicate a model, optionally...
https://python.langchain.com/en/latest/reference/modules/llms.html
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get_token_ids(text: str) β†’ List[int]# Get the token present in the text. json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_...
https://python.langchain.com/en/latest/reference/modules/llms.html
98a4fcd9b56e-72
Example using from_model_id:from langchain.llms import HuggingFacePipeline hf = HuggingFacePipeline.from_model_id( model_id="gpt2", task="text-generation", pipeline_kwargs={"max_new_tokens": 10}, ) Example passing pipeline in directly:from langchain.llms import HuggingFacePipeline from transformers import A...
https://python.langchain.com/en/latest/reference/modules/llms.html
98a4fcd9b56e-73
Run the LLM on the given prompt and input. async agenerate_prompt(prompts: List[langchain.schema.PromptValue], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None) β†’ langchain.schema.LLMResult# Take in a li...
https://python.langchain.com/en/latest/reference/modules/llms.html
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Returns new model instance dict(**kwargs: Any) β†’ Dict# Return a dictionary of the LLM. classmethod from_model_id(model_id: str, task: str, device: int = - 1, model_kwargs: Optional[dict] = None, pipeline_kwargs: Optional[dict] = None, **kwargs: Any) β†’ langchain.llms.base.LLM[source]# Construct the pipeline object from ...
https://python.langchain.com/en/latest/reference/modules/llms.html
98a4fcd9b56e-75
Get the token present in the text. json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: ...
https://python.langchain.com/en/latest/reference/modules/llms.html
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Attributes: - max_new_tokens: The maximum number of tokens to generate. - top_k: The number of top-k tokens to consider when generating text. - top_p: The cumulative probability threshold for generating text. - typical_p: The typical probability threshold for generating text. - temperature: The temperature to use when ...
https://python.langchain.com/en/latest/reference/modules/llms.html
98a4fcd9b56e-77
Run the LLM on the given prompt and input. async agenerate_prompt(prompts: List[langchain.schema.PromptValue], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None) β†’ langchain.schema.LLMResult# Take in a li...
https://python.langchain.com/en/latest/reference/modules/llms.html
98a4fcd9b56e-78
Returns new model instance dict(**kwargs: Any) β†’ Dict# Return a dictionary of the LLM. generate(prompts: List[str], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None) β†’ langchain.schema.LLMResult# Run the...
https://python.langchain.com/en/latest/reference/modules/llms.html
98a4fcd9b56e-79
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps(). predict(text: str, *, stop: Optional[Sequence[str]] = None) β†’ str# Predict text from text. predict_messages(messages: List[langchain.schema.BaseMessage], *, stop: Optional[Sequence[str]] = None) β†’ langchain.schema...
https://python.langchain.com/en/latest/reference/modules/llms.html
98a4fcd9b56e-80
Run the LLM on the given prompt and input. async agenerate_prompt(prompts: List[langchain.schema.PromptValue], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None) β†’ langchain.schema.LLMResult# Take in a li...
https://python.langchain.com/en/latest/reference/modules/llms.html
98a4fcd9b56e-81
Returns new model instance dict(**kwargs: Any) β†’ Dict# Return a dictionary of the LLM. generate(prompts: List[str], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None) β†’ langchain.schema.LLMResult# Run the...
https://python.langchain.com/en/latest/reference/modules/llms.html
98a4fcd9b56e-82
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps(). predict(text: str, *, stop: Optional[Sequence[str]] = None) β†’ str# Predict text from text. predict_messages(messages: List[langchain.schema.BaseMessage], *, stop: Optional[Sequence[str]] = None) β†’ langchain.schema...
https://python.langchain.com/en/latest/reference/modules/llms.html
98a4fcd9b56e-83
field logprobs: Optional[int] = None# The number of logprobs to return. If None, no logprobs are returned. field lora_base: Optional[str] = None# The path to the Llama LoRA base model. field lora_path: Optional[str] = None# The path to the Llama LoRA. If None, no LoRa is loaded. field max_tokens: Optional[int] = 256# T...
https://python.langchain.com/en/latest/reference/modules/llms.html
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field temperature: Optional[float] = 0.8# The temperature to use for sampling. field top_k: Optional[int] = 40# The top-k value to use for sampling. field top_p: Optional[float] = 0.95# The top-p value to use for sampling. field use_mlock: bool = False# Force system to keep model in RAM. field use_mmap: Optional[bool] ...
https://python.langchain.com/en/latest/reference/modules/llms.html
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Predict text from text. async apredict_messages(messages: List[langchain.schema.BaseMessage], *, stop: Optional[Sequence[str]] = None) β†’ langchain.schema.BaseMessage# Predict message from messages. classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) β†’ Model# Creates a new model setting __dict__ a...
https://python.langchain.com/en/latest/reference/modules/llms.html
98a4fcd9b56e-86
Run the LLM on the given prompt and input. generate_prompt(prompts: List[langchain.schema.PromptValue], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None) β†’ langchain.schema.LLMResult# Take in a list of p...
https://python.langchain.com/en/latest/reference/modules/llms.html
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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, run_manager: Optional[langchain.callbacks.manager.CallbackManagerForLLMRun] = None) β†’ Generator[Dict, None, None][source]# Yield...
https://python.langchain.com/en/latest/reference/modules/llms.html
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To use, you should have the modal-client python package installed. Any parameters that are valid to be passed to the call can be passed in, even if not explicitly saved on this class. Example Validators build_extra Β» all fields raise_deprecation Β» all fields set_verbose Β» verbose field endpoint_url: str = ''# model end...
https://python.langchain.com/en/latest/reference/modules/llms.html
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Predict message from messages. classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) β†’ Model# Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = β€˜allow’ was set ...
https://python.langchain.com/en/latest/reference/modules/llms.html
98a4fcd9b56e-90
Take in a list of prompt values and return an LLMResult. get_num_tokens(text: str) β†’ int# Get the number of tokens present in the text. get_num_tokens_from_messages(messages: List[langchain.schema.BaseMessage]) β†’ int# Get the number of tokens in the message. get_token_ids(text: str) β†’ List[int]# Get the token present i...
https://python.langchain.com/en/latest/reference/modules/llms.html
98a4fcd9b56e-91
Try to update ForwardRefs on fields based on this Model, globalns and localns. pydantic model langchain.llms.MosaicML[source]# Wrapper around MosaicML’s LLM inference service. To use, you should have the environment variable MOSAICML_API_TOKEN set with your API token, or pass it as a named parameter to the constructor....
https://python.langchain.com/en/latest/reference/modules/llms.html
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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) β†’ langchain.schema.LLMResult# Run the LLM on the given pro...
https://python.langchain.com/en/latest/reference/modules/llms.html
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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 creating the new model: you should trust this data deep – set to True to make a deep co...
https://python.langchain.com/en/latest/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: ...
https://python.langchain.com/en/latest/reference/modules/llms.html
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nlpcloud = NLPCloud(model="gpt-neox-20b") Validators raise_deprecation Β» all fields set_verbose Β» verbose validate_environment Β» all fields field bad_words: List[str] = []# List of tokens not allowed to be generated. field do_sample: bool = True# Whether to use sampling (True) or greedy decoding. field early_stopping: ...
https://python.langchain.com/en/latest/reference/modules/llms.html
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Total probability mass of tokens to consider at each step. field verbose: bool [Optional]# Whether to print out response text. __call__(prompt: str, stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None) β†’ st...
https://python.langchain.com/en/latest/reference/modules/llms.html
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Behaves as if Config.extra = β€˜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) β†’ Model# Duplicate a model, optionally...
https://python.langchain.com/en/latest/reference/modules/llms.html
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get_token_ids(text: str) β†’ List[int]# Get the token present in the text. json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_...
https://python.langchain.com/en/latest/reference/modules/llms.html
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Any parameters that are valid to be passed to the openai.create call can be passed in, even if not explicitly saved on this class. Example from langchain.llms import OpenAI openai = OpenAI(model_name="text-davinci-003") Validators build_extra Β» all fields raise_deprecation Β» all fields set_verbose Β» verbose validate_en...
https://python.langchain.com/en/latest/reference/modules/llms.html
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field presence_penalty: float = 0# Penalizes repeated tokens. field request_timeout: Optional[Union[float, Tuple[float, float]]] = None# Timeout for requests to OpenAI completion API. Default is 600 seconds. field streaming: bool = False# Whether to stream the results or not. field temperature: float = 0.7# What sampli...
https://python.langchain.com/en/latest/reference/modules/llms.html
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Predict message from messages. classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) β†’ Model# Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = β€˜allow’ was set ...
https://python.langchain.com/en/latest/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) β†’ langchain.schema.LLMResult# Take in a list of p...
https://python.langchain.com/en/latest/reference/modules/llms.html
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Parameters prompt – The prompt to pass into the model. Returns The maximum number of tokens to generate for a prompt. Example max_tokens = openai.max_token_for_prompt("Tell me a joke.") modelname_to_contextsize(modelname: str) β†’ int# Calculate the maximum number of tokens possible to generate for a model. Parameters mo...
https://python.langchain.com/en/latest/reference/modules/llms.html
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for token in generator: yield token classmethod update_forward_refs(**localns: Any) β†’ None# Try to update ForwardRefs on fields based on this Model, globalns and localns. pydantic model langchain.llms.OpenAIChat[source]# Wrapper around OpenAI Chat large language models. To use, you should have the openai python pac...
https://python.langchain.com/en/latest/reference/modules/llms.html
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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) β†’ str# Check Cache and run the LLM on the given prompt and inpu...
https://python.langchain.com/en/latest/reference/modules/llms.html
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Behaves as if Config.extra = β€˜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) β†’ Model# Duplicate a model, optionally...
https://python.langchain.com/en/latest/reference/modules/llms.html
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get_token_ids(text: str) β†’ List[int][source]# Get the token IDs using the tiktoken package. json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: boo...
https://python.langchain.com/en/latest/reference/modules/llms.html
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Set of special tokens that are allowed。 field batch_size: int = 20# Batch size to use when passing multiple documents to generate. field best_of: int = 1# Generates best_of completions server-side and returns the β€œbest”. field disallowed_special: Union[Literal['all'], Collection[str]] = 'all'# Set of special tokens tha...
https://python.langchain.com/en/latest/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) β†’ str# Check Cache and run the LLM on the given prompt and inpu...
https://python.langchain.com/en/latest/reference/modules/llms.html
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Behaves as if Config.extra = β€˜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) β†’ Model# Duplicate a model, optionally...
https://python.langchain.com/en/latest/reference/modules/llms.html
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Get the number of tokens present in the text. get_num_tokens_from_messages(messages: List[langchain.schema.BaseMessage]) β†’ int# Get the number of tokens in the message. get_sub_prompts(params: Dict[str, Any], prompts: List[str], stop: Optional[List[str]] = None) β†’ List[List[str]]# Get the sub prompts for llm call. get_...
https://python.langchain.com/en/latest/reference/modules/llms.html
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Example max_tokens = openai.modelname_to_contextsize("text-davinci-003") predict(text: str, *, stop: Optional[Sequence[str]] = None) β†’ str# Predict text from text. predict_messages(messages: List[langchain.schema.BaseMessage], *, stop: Optional[Sequence[str]] = None) β†’ langchain.schema.BaseMessage# Predict message from...
https://python.langchain.com/en/latest/reference/modules/llms.html
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Any parameters that are valid to be passed to the call can be passed in, even if not explicitly saved on this class. Example Validators build_extra Β» all fields raise_deprecation Β» all fields set_verbose Β» verbose validate_environment Β» all fields field client: Any = None# The client to use for the API calls. field do_...
https://python.langchain.com/en/latest/reference/modules/llms.html
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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) β†’ langchain.schema.LLMResult# Run the LLM on the given pro...
https://python.langchain.com/en/latest/reference/modules/llms.html
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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 creating the new model: you should trust this data deep – set to True to make a deep co...
https://python.langchain.com/en/latest/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: ...
https://python.langchain.com/en/latest/reference/modules/llms.html
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in, even if not explicitly saved on this class. Example Validators build_extra Β» all fields raise_deprecation Β» all fields set_verbose Β» verbose validate_environment Β» all fields field pipeline_key: str = ''# The id or tag of the target pipeline field pipeline_kwargs: Dict[str, Any] [Optional]# Holds any pipeline param...
https://python.langchain.com/en/latest/reference/modules/llms.html
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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 copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclu...
https://python.langchain.com/en/latest/reference/modules/llms.html
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Get the number of tokens present in the text. get_num_tokens_from_messages(messages: List[langchain.schema.BaseMessage]) β†’ int# Get the number of tokens in the message. get_token_ids(text: str) β†’ List[int]# Get the token present in the text. json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, ...
https://python.langchain.com/en/latest/reference/modules/llms.html
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Wrapper around Prediction Guard large language models. To use, you should have the predictionguard python package installed, and the environment variable PREDICTIONGUARD_TOKEN set with your access token, or pass it as a named parameter to the constructor. To use Prediction Guard’s API along with OpenAI models, set the ...
https://python.langchain.com/en/latest/reference/modules/llms.html
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Run the LLM on the given prompt and input. async agenerate_prompt(prompts: List[langchain.schema.PromptValue], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None) β†’ langchain.schema.LLMResult# Take in a li...
https://python.langchain.com/en/latest/reference/modules/llms.html
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Returns new model instance dict(**kwargs: Any) β†’ Dict# Return a dictionary of the LLM. generate(prompts: List[str], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None) β†’ langchain.schema.LLMResult# Run the...
https://python.langchain.com/en/latest/reference/modules/llms.html
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encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps(). predict(text: str, *, stop: Optional[Sequence[str]] = None) β†’ str# Predict text from text. predict_messages(messages: List[langchain.schema.BaseMessage], *, stop: Optional[Sequence[str]] = None) β†’ langchain.schema...
https://python.langchain.com/en/latest/reference/modules/llms.html
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raise_deprecation Β» all fields set_verbose Β» verbose validate_environment Β» all fields __call__(prompt: str, stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None) β†’ str# Check Cache and run the LLM on the gi...
https://python.langchain.com/en/latest/reference/modules/llms.html
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Behaves as if Config.extra = β€˜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) β†’ Model# Duplicate a model, optionally...
https://python.langchain.com/en/latest/reference/modules/llms.html
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Get the number of tokens present in the text. get_num_tokens_from_messages(messages: List[langchain.schema.BaseMessage]) β†’ int# Get the number of tokens in the message. get_sub_prompts(params: Dict[str, Any], prompts: List[str], stop: Optional[List[str]] = None) β†’ List[List[str]]# Get the sub prompts for llm call. get_...
https://python.langchain.com/en/latest/reference/modules/llms.html
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Example max_tokens = openai.modelname_to_contextsize("text-davinci-003") predict(text: str, *, stop: Optional[Sequence[str]] = None) β†’ str# Predict text from text. predict_messages(messages: List[langchain.schema.BaseMessage], *, stop: Optional[Sequence[str]] = None) β†’ langchain.schema.BaseMessage# Predict message from...
https://python.langchain.com/en/latest/reference/modules/llms.html
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promptlayer key respectively. All parameters that can be passed to the OpenAIChat LLM can also be passed here. The PromptLayerOpenAIChat adds two optional :param pl_tags: List of strings to tag the request with. :param return_pl_id: If True, the PromptLayer request ID will be returned in the generation_info field of th...
https://python.langchain.com/en/latest/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) β†’ langchain.schema.LLMResult# Run the LLM on the given pro...
https://python.langchain.com/en/latest/reference/modules/llms.html
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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 creating the new model: you should trust this data deep – set to True to make a deep co...
https://python.langchain.com/en/latest/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...
https://python.langchain.com/en/latest/reference/modules/llms.html
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Example from langchain.llms import RWKV model = RWKV(model="./models/rwkv-3b-fp16.bin", strategy="cpu fp32") # Simplest invocation response = model("Once upon a time, ") Validators raise_deprecation Β» all fields set_verbose Β» verbose validate_environment Β» all fields field CHUNK_LEN: int = 256# Batch size for prompt pr...
https://python.langchain.com/en/latest/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) β†’ langchain.schema.LLMResult# Run the LLM on the given pro...
https://python.langchain.com/en/latest/reference/modules/llms.html
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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 creating the new model: you should trust this data deep – set to True to make a deep co...
https://python.langchain.com/en/latest/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: ...
https://python.langchain.com/en/latest/reference/modules/llms.html
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The model param is required, but any other model parameters can also be passed in with the format input={model_param: value, …} Example Validators build_extra Β» all fields raise_deprecation Β» all fields set_verbose Β» verbose validate_environment Β» all fields field verbose: bool [Optional]# Whether to print out response...
https://python.langchain.com/en/latest/reference/modules/llms.html
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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 copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny...
https://python.langchain.com/en/latest/reference/modules/llms.html
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Get the number of tokens in the message. get_token_ids(text: str) β†’ List[int]# Get the token present in the text. json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = No...
https://python.langchain.com/en/latest/reference/modules/llms.html