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the new model: you should trust this data deep – set to True to make a deep copy of the model Returns new model instance dict(**kwargs: Any) → Dict¶ Return a dictionary of the LLM. classmethod from_orm(obj: Any) → Model¶ generate(prompts: List[str], stop: Optional[List[str]] = None, callbacks: Union[List[BaseCallbackHa...
https://api.python.langchain.com/en/latest/llms/langchain.llms.koboldai.KoboldApiLLM.html
4a7db6c7f632-7
text generation models and BaseMessages for chat models). stop – Stop words to use when generating. Model output is cut off at the first occurrence of any of these substrings. callbacks – Callbacks to pass through. Used for executing additional functionality, such as logging or streaming, throughout generation. **kwarg...
https://api.python.langchain.com/en/latest/llms/langchain.llms.koboldai.KoboldApiLLM.html
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invoke(input: Union[PromptValue, str, List[BaseMessage]], config: Optional[RunnableConfig] = None, *, stop: Optional[List[str]] = None, **kwargs: Any) → str¶ classmethod is_lc_serializable() → bool¶ Is this class serializable? json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Option...
https://api.python.langchain.com/en/latest/llms/langchain.llms.koboldai.KoboldApiLLM.html
4a7db6c7f632-9
predict(text: str, *, stop: Optional[Sequence[str]] = None, **kwargs: Any) → str¶ Pass a single string input to the model and return a string prediction. Use this method when passing in raw text. If you want to pass in specifictypes of chat messages, use predict_messages. Parameters text – String input to pass to the m...
https://api.python.langchain.com/en/latest/llms/langchain.llms.koboldai.KoboldApiLLM.html
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stream(input: Union[PromptValue, str, List[BaseMessage]], config: Optional[RunnableConfig] = None, *, stop: Optional[List[str]] = None, **kwargs: Any) → Iterator[str]¶ Default implementation of stream, which calls invoke. Subclasses should override this method if they support streaming output. to_json() → Union[Seriali...
https://api.python.langchain.com/en/latest/llms/langchain.llms.koboldai.KoboldApiLLM.html
4a7db6c7f632-11
property InputType: TypeAlias¶ Get the input type for this runnable. property OutputType: Type[str]¶ Get the input type for this runnable. property input_schema: Type[pydantic.main.BaseModel]¶ property lc_attributes: Dict¶ List of attribute names that should be included in the serialized kwargs. These attributes must b...
https://api.python.langchain.com/en/latest/llms/langchain.llms.koboldai.KoboldApiLLM.html
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langchain.llms.vllm.VLLMOpenAI¶ class langchain.llms.vllm.VLLMOpenAI[source]¶ Bases: BaseOpenAI vLLM OpenAI-compatible API client Create a new model by parsing and validating input data from keyword arguments. Raises ValidationError if the input data cannot be parsed to form a valid model. param allowed_special: Union[...
https://api.python.langchain.com/en/latest/llms/langchain.llms.vllm.VLLMOpenAI.html
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Model name to use. param n: int = 1¶ How many completions to generate for each prompt. param openai_api_base: Optional[str] = None¶ param openai_api_key: Optional[str] = None¶ param openai_organization: Optional[str] = None¶ param openai_proxy: Optional[str] = None¶ param presence_penalty: float = 0¶ Penalizes repeated...
https://api.python.langchain.com/en/latest/llms/langchain.llms.vllm.VLLMOpenAI.html
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param verbose: bool [Optional]¶ Whether to print out response text. __call__(prompt: str, stop: Optional[List[str]] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, **kwargs: Any) → str¶ Check Cache...
https://api.python.langchain.com/en/latest/llms/langchain.llms.vllm.VLLMOpenAI.html
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Asynchronously pass a sequence of prompts and return model generations. This method should make use of batched calls for models that expose a batched API. Use this method when you want to: take advantage of batched calls, need more output from the model than just the top generated value, are building chains that are ag...
https://api.python.langchain.com/en/latest/llms/langchain.llms.vllm.VLLMOpenAI.html
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Parameters text – String input to pass to the model. stop – Stop words to use when generating. Model output is cut off at the first occurrence of any of these substrings. **kwargs – Arbitrary additional keyword arguments. These are usually passed to the model provider API call. Returns Top model prediction as a string....
https://api.python.langchain.com/en/latest/llms/langchain.llms.vllm.VLLMOpenAI.html
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Stream all output from a runnable, as reported to the callback system. This includes all inner runs of LLMs, Retrievers, Tools, etc. Output is streamed as Log objects, which include a list of jsonpatch ops that describe how the state of the run has changed in each step, and the final state of the run. The jsonpatch ops...
https://api.python.langchain.com/en/latest/llms/langchain.llms.vllm.VLLMOpenAI.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...
https://api.python.langchain.com/en/latest/llms/langchain.llms.vllm.VLLMOpenAI.html
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Run the LLM on the given prompt and input. generate_prompt(prompts: List[PromptValue], stop: Optional[List[str]] = None, callbacks: Union[List[BaseCallbackHandler], BaseCallbackManager, None, List[Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]]]] = None, **kwargs: Any) → LLMResult¶ Pass a sequence of pr...
https://api.python.langchain.com/en/latest/llms/langchain.llms.vllm.VLLMOpenAI.html
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Get the number of tokens present in the text. Useful for checking if an input will fit in a model’s context window. Parameters text – The string input to tokenize. Returns The integer number of tokens in the text. get_num_tokens_from_messages(messages: List[BaseMessage]) → int¶ Get the number of tokens in the messages....
https://api.python.langchain.com/en/latest/llms/langchain.llms.vllm.VLLMOpenAI.html
fff7cb7208ba-9
classmethod lc_id() → List[str]¶ A unique identifier for this class for serialization purposes. The unique identifier is a list of strings that describes the path to the object. map() → Runnable[List[Input], List[Output]]¶ Return a new Runnable that maps a list of inputs to a list of outputs, by calling invoke() with e...
https://api.python.langchain.com/en/latest/llms/langchain.llms.vllm.VLLMOpenAI.html
fff7cb7208ba-10
Parameters text – String input to pass to the model. stop – Stop words to use when generating. Model output is cut off at the first occurrence of any of these substrings. **kwargs – Arbitrary additional keyword arguments. These are usually passed to the model provider API call. Returns Top model prediction as a string....
https://api.python.langchain.com/en/latest/llms/langchain.llms.vllm.VLLMOpenAI.html
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Subclasses should override this method if they support streaming output. to_json() → Union[SerializedConstructor, SerializedNotImplemented]¶ to_json_not_implemented() → SerializedNotImplemented¶ transform(input: Iterator[Input], config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → Iterator[Output]¶ Defau...
https://api.python.langchain.com/en/latest/llms/langchain.llms.vllm.VLLMOpenAI.html
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List of attribute names that should be included in the serialized kwargs. These attributes must be accepted by the constructor. property lc_secrets: Dict[str, str]¶ A map of constructor argument names to secret ids. For example,{“openai_api_key”: “OPENAI_API_KEY”} property max_context_size: int¶ Get max context size fo...
https://api.python.langchain.com/en/latest/llms/langchain.llms.vllm.VLLMOpenAI.html
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langchain.llms.ctranslate2.CTranslate2¶ class langchain.llms.ctranslate2.CTranslate2[source]¶ Bases: BaseLLM CTranslate2 language model. Create a new model by parsing and validating input data from keyword arguments. Raises ValidationError if the input data cannot be parsed to form a valid model. param cache: Optional[...
https://api.python.langchain.com/en/latest/llms/langchain.llms.ctranslate2.CTranslate2.html
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Keep the most probable tokens whose cumulative probability exceeds this value. param tags: Optional[List[str]] = None¶ Tags to add to the run trace. param tokenizer_name: str = ''¶ Name of the original Hugging Face model needed to load the proper tokenizer. param verbose: bool [Optional]¶ Whether to print out response ...
https://api.python.langchain.com/en/latest/llms/langchain.llms.ctranslate2.CTranslate2.html
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Run the LLM on the given prompt and input. async agenerate_prompt(prompts: List[PromptValue], stop: Optional[List[str]] = None, callbacks: Union[List[BaseCallbackHandler], BaseCallbackManager, None, List[Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]]]] = None, **kwargs: Any) → LLMResult¶ Asynchronously...
https://api.python.langchain.com/en/latest/llms/langchain.llms.ctranslate2.CTranslate2.html
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Subclasses should override this method if they can run asynchronously. async apredict(text: str, *, stop: Optional[Sequence[str]] = None, **kwargs: Any) → str¶ Asynchronously pass a string to the model and return a string prediction. Use this method when calling pure text generation models and only the topcandidate gen...
https://api.python.langchain.com/en/latest/llms/langchain.llms.ctranslate2.CTranslate2.html
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Subclasses should override this method if they support streaming output. async astream_log(input: Any, config: Optional[RunnableConfig] = None, *, include_names: Optional[Sequence[str]] = None, include_types: Optional[Sequence[str]] = None, include_tags: Optional[Sequence[str]] = None, exclude_names: Optional[Sequence[...
https://api.python.langchain.com/en/latest/llms/langchain.llms.ctranslate2.CTranslate2.html
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Bind arguments to a Runnable, returning a new Runnable. 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...
https://api.python.langchain.com/en/latest/llms/langchain.llms.ctranslate2.CTranslate2.html
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Run the LLM on the given prompt and input. generate_prompt(prompts: List[PromptValue], stop: Optional[List[str]] = None, callbacks: Union[List[BaseCallbackHandler], BaseCallbackManager, None, List[Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]]]] = None, **kwargs: Any) → LLMResult¶ Pass a sequence of pr...
https://api.python.langchain.com/en/latest/llms/langchain.llms.ctranslate2.CTranslate2.html
628cea11598e-7
Get the number of tokens present in the text. Useful for checking if an input will fit in a model’s context window. Parameters text – The string input to tokenize. Returns The integer number of tokens in the text. get_num_tokens_from_messages(messages: List[BaseMessage]) → int¶ Get the number of tokens in the messages....
https://api.python.langchain.com/en/latest/llms/langchain.llms.ctranslate2.CTranslate2.html
628cea11598e-8
classmethod lc_id() → List[str]¶ A unique identifier for this class for serialization purposes. The unique identifier is a list of strings that describes the path to the object. map() → Runnable[List[Input], List[Output]]¶ Return a new Runnable that maps a list of inputs to a list of outputs, by calling invoke() with e...
https://api.python.langchain.com/en/latest/llms/langchain.llms.ctranslate2.CTranslate2.html
628cea11598e-9
Parameters messages – A sequence of chat messages corresponding to a single model input. stop – Stop words to use when generating. Model output is cut off at the first occurrence of any of these substrings. **kwargs – Arbitrary additional keyword arguments. These are usually passed to the model provider API call. Retur...
https://api.python.langchain.com/en/latest/llms/langchain.llms.ctranslate2.CTranslate2.html
628cea11598e-10
classmethod validate(value: Any) → Model¶ with_config(config: Optional[RunnableConfig] = None, **kwargs: Any) → Runnable[Input, Output]¶ Bind config to a Runnable, returning a new Runnable. with_fallbacks(fallbacks: ~typing.Sequence[~langchain.schema.runnable.base.Runnable[~langchain.schema.runnable.utils.Input, ~langc...
https://api.python.langchain.com/en/latest/llms/langchain.llms.ctranslate2.CTranslate2.html
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langchain.llms.openllm.IdentifyingParams¶ class langchain.llms.openllm.IdentifyingParams[source]¶ Parameters for identifying a model as a typed dict. model_name: str¶ model_id: Optional[str]¶ server_url: Optional[str]¶ server_type: Optional[Literal['http', 'grpc']]¶ embedded: bool¶ llm_kwargs: Dict[str, Any]¶
https://api.python.langchain.com/en/latest/llms/langchain.llms.openllm.IdentifyingParams.html
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langchain.llms.edenai.EdenAI¶ class langchain.llms.edenai.EdenAI[source]¶ Bases: LLM Wrapper around edenai models. To use, you should have the environment variable EDENAI_API_KEY set with your API token. You can find your token here: https://app.edenai.run/admin/account/settings feature and subfeature are required, but...
https://api.python.langchain.com/en/latest/llms/langchain.llms.edenai.EdenAI.html
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DEPRECATED: use temperature, max_tokens, resolution directly optional parameters to pass to api param provider: str [Required]¶ Generative provider to use (eg: openai,stabilityai,cohere,google etc.) param resolution: Optional[Literal['256x256', '512x512', '1024x1024']] = None¶ param stop_sequences: Optional[List[str]] ...
https://api.python.langchain.com/en/latest/llms/langchain.llms.edenai.EdenAI.html
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Subclasses should override this method if they can batch more efficiently. async agenerate(prompts: List[str], stop: Optional[List[str]] = None, callbacks: Union[List[BaseCallbackHandler], BaseCallbackManager, None, List[Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]]]] = None, *, tags: Optional[Union[L...
https://api.python.langchain.com/en/latest/llms/langchain.llms.edenai.EdenAI.html
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functionality, such as logging or streaming, throughout generation. **kwargs – Arbitrary additional keyword arguments. These are usually passed to the model provider API call. Returns An LLMResult, which contains a list of candidate Generations for each inputprompt and additional model provider-specific output. async a...
https://api.python.langchain.com/en/latest/llms/langchain.llms.edenai.EdenAI.html
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to the model provider API call. Returns Top model prediction as a message. async astream(input: Union[PromptValue, str, List[BaseMessage]], config: Optional[RunnableConfig] = None, *, stop: Optional[List[str]] = None, **kwargs: Any) → AsyncIterator[str]¶ Default implementation of astream, which calls ainvoke. Subclasse...
https://api.python.langchain.com/en/latest/llms/langchain.llms.edenai.EdenAI.html
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input is still being generated. batch(inputs: List[Union[PromptValue, str, List[BaseMessage]]], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, return_exceptions: bool = False, **kwargs: Any) → List[str]¶ Default implementation of batch, which calls invoke N times. Subclasses should override th...
https://api.python.langchain.com/en/latest/llms/langchain.llms.edenai.EdenAI.html
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classmethod from_orm(obj: Any) → Model¶ generate(prompts: List[str], stop: Optional[List[str]] = None, callbacks: Union[List[BaseCallbackHandler], BaseCallbackManager, None, List[Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]]]] = None, *, tags: Optional[Union[List[str], List[List[str]]]] = None, metada...
https://api.python.langchain.com/en/latest/llms/langchain.llms.edenai.EdenAI.html
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functionality, such as logging or streaming, throughout generation. **kwargs – Arbitrary additional keyword arguments. These are usually passed to the model provider API call. Returns An LLMResult, which contains a list of candidate Generations for each inputprompt and additional model provider-specific output. classme...
https://api.python.langchain.com/en/latest/llms/langchain.llms.edenai.EdenAI.html
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classmethod is_lc_serializable() → bool¶ Is this class serializable? 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_defa...
https://api.python.langchain.com/en/latest/llms/langchain.llms.edenai.EdenAI.html
91991932115e-9
Pass a single string input to the model and return a string prediction. Use this method when passing in raw text. If you want to pass in specifictypes of chat messages, use predict_messages. Parameters text – String input to pass to the model. stop – Stop words to use when generating. Model output is cut off at the fir...
https://api.python.langchain.com/en/latest/llms/langchain.llms.edenai.EdenAI.html
91991932115e-10
stream(input: Union[PromptValue, str, List[BaseMessage]], config: Optional[RunnableConfig] = None, *, stop: Optional[List[str]] = None, **kwargs: Any) → Iterator[str]¶ Default implementation of stream, which calls invoke. Subclasses should override this method if they support streaming output. to_json() → Union[Seriali...
https://api.python.langchain.com/en/latest/llms/langchain.llms.edenai.EdenAI.html
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property InputType: TypeAlias¶ Get the input type for this runnable. property OutputType: Type[str]¶ Get the input type for this runnable. property input_schema: Type[pydantic.main.BaseModel]¶ property lc_attributes: Dict¶ List of attribute names that should be included in the serialized kwargs. These attributes must b...
https://api.python.langchain.com/en/latest/llms/langchain.llms.edenai.EdenAI.html
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langchain.llms.replicate.Replicate¶ class langchain.llms.replicate.Replicate[source]¶ Bases: LLM Replicate models. To use, you should have the replicate python package installed, and the environment variable REPLICATE_API_TOKEN set with your API token. You can find your token here: https://replicate.com/account The mod...
https://api.python.langchain.com/en/latest/llms/langchain.llms.replicate.Replicate.html
8ec4b33d5ad7-1
param tags: Optional[List[str]] = None¶ Tags to add to the run trace. param verbose: bool [Optional]¶ Whether to print out response text. param version_obj: Any = None¶ Optionally pass in the model version object during initialization to avoid having to make an extra API call to retrieve it during streaming. NOTE: not ...
https://api.python.langchain.com/en/latest/llms/langchain.llms.replicate.Replicate.html
8ec4b33d5ad7-2
Run the LLM on the given prompt and input. async agenerate_prompt(prompts: List[PromptValue], stop: Optional[List[str]] = None, callbacks: Union[List[BaseCallbackHandler], BaseCallbackManager, None, List[Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]]]] = None, **kwargs: Any) → LLMResult¶ Asynchronously...
https://api.python.langchain.com/en/latest/llms/langchain.llms.replicate.Replicate.html
8ec4b33d5ad7-3
Subclasses should override this method if they can run asynchronously. async apredict(text: str, *, stop: Optional[Sequence[str]] = None, **kwargs: Any) → str¶ Asynchronously pass a string to the model and return a string prediction. Use this method when calling pure text generation models and only the topcandidate gen...
https://api.python.langchain.com/en/latest/llms/langchain.llms.replicate.Replicate.html
8ec4b33d5ad7-4
Subclasses should override this method if they support streaming output. async astream_log(input: Any, config: Optional[RunnableConfig] = None, *, include_names: Optional[Sequence[str]] = None, include_types: Optional[Sequence[str]] = None, include_tags: Optional[Sequence[str]] = None, exclude_names: Optional[Sequence[...
https://api.python.langchain.com/en/latest/llms/langchain.llms.replicate.Replicate.html
8ec4b33d5ad7-5
Bind arguments to a Runnable, returning a new Runnable. 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...
https://api.python.langchain.com/en/latest/llms/langchain.llms.replicate.Replicate.html
8ec4b33d5ad7-6
Run the LLM on the given prompt and input. generate_prompt(prompts: List[PromptValue], stop: Optional[List[str]] = None, callbacks: Union[List[BaseCallbackHandler], BaseCallbackManager, None, List[Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]]]] = None, **kwargs: Any) → LLMResult¶ Pass a sequence of pr...
https://api.python.langchain.com/en/latest/llms/langchain.llms.replicate.Replicate.html
8ec4b33d5ad7-7
Get the number of tokens present in the text. Useful for checking if an input will fit in a model’s context window. Parameters text – The string input to tokenize. Returns The integer number of tokens in the text. get_num_tokens_from_messages(messages: List[BaseMessage]) → int¶ Get the number of tokens in the messages....
https://api.python.langchain.com/en/latest/llms/langchain.llms.replicate.Replicate.html
8ec4b33d5ad7-8
classmethod lc_id() → List[str]¶ A unique identifier for this class for serialization purposes. The unique identifier is a list of strings that describes the path to the object. map() → Runnable[List[Input], List[Output]]¶ Return a new Runnable that maps a list of inputs to a list of outputs, by calling invoke() with e...
https://api.python.langchain.com/en/latest/llms/langchain.llms.replicate.Replicate.html
8ec4b33d5ad7-9
Parameters messages – A sequence of chat messages corresponding to a single model input. stop – Stop words to use when generating. Model output is cut off at the first occurrence of any of these substrings. **kwargs – Arbitrary additional keyword arguments. These are usually passed to the model provider API call. Retur...
https://api.python.langchain.com/en/latest/llms/langchain.llms.replicate.Replicate.html
8ec4b33d5ad7-10
classmethod validate(value: Any) → Model¶ with_config(config: Optional[RunnableConfig] = None, **kwargs: Any) → Runnable[Input, Output]¶ Bind config to a Runnable, returning a new Runnable. with_fallbacks(fallbacks: ~typing.Sequence[~langchain.schema.runnable.base.Runnable[~langchain.schema.runnable.utils.Input, ~langc...
https://api.python.langchain.com/en/latest/llms/langchain.llms.replicate.Replicate.html
ef5ae5e64fc5-0
langchain_experimental.llms.jsonformer_decoder.JsonFormer¶ class langchain_experimental.llms.jsonformer_decoder.JsonFormer[source]¶ Bases: HuggingFacePipeline Jsonformer wrapped LLM using HuggingFace Pipeline API. This pipeline is experimental and not yet stable. Create a new model by parsing and validating input data ...
https://api.python.langchain.com/en/latest/llms/langchain_experimental.llms.jsonformer_decoder.JsonFormer.html
ef5ae5e64fc5-1
Check Cache and run the LLM on the given prompt and input. async abatch(inputs: List[Union[PromptValue, str, List[BaseMessage]]], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, return_exceptions: bool = False, **kwargs: Any) → List[str]¶ Default implementation of abatch, which calls ainvoke N ...
https://api.python.langchain.com/en/latest/llms/langchain_experimental.llms.jsonformer_decoder.JsonFormer.html
ef5ae5e64fc5-2
Parameters prompts – List of PromptValues. A PromptValue is an object that can be converted to match the format of any language model (string for pure text generation models and BaseMessages for chat models). stop – Stop words to use when generating. Model output is cut off at the first occurrence of any of these subst...
https://api.python.langchain.com/en/latest/llms/langchain_experimental.llms.jsonformer_decoder.JsonFormer.html
ef5ae5e64fc5-3
Asynchronously pass messages to the model and return a message prediction. Use this method when calling chat models and only the topcandidate generation is needed. Parameters messages – A sequence of chat messages corresponding to a single model input. stop – Stop words to use when generating. Model output is cut off a...
https://api.python.langchain.com/en/latest/llms/langchain_experimental.llms.jsonformer_decoder.JsonFormer.html
ef5ae5e64fc5-4
The jsonpatch ops can be applied in order to construct state. async atransform(input: AsyncIterator[Input], config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → AsyncIterator[Output]¶ Default implementation of atransform, which buffers input and calls astream. Subclasses should override this method if th...
https://api.python.langchain.com/en/latest/llms/langchain_experimental.llms.jsonformer_decoder.JsonFormer.html
ef5ae5e64fc5-5
the new model: you should trust this data deep – set to True to make a deep copy of the model Returns new model instance dict(**kwargs: Any) → 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]...
https://api.python.langchain.com/en/latest/llms/langchain_experimental.llms.jsonformer_decoder.JsonFormer.html
ef5ae5e64fc5-6
need more output from the model than just the top generated value, are building chains that are agnostic to the underlying language modeltype (e.g., pure text completion models vs chat models). Parameters prompts – List of PromptValues. A PromptValue is an object that can be converted to match the format of any languag...
https://api.python.langchain.com/en/latest/llms/langchain_experimental.llms.jsonformer_decoder.JsonFormer.html
ef5ae5e64fc5-7
Return the ordered ids of the tokens in a text. Parameters text – The string input to tokenize. Returns A list of ids corresponding to the tokens in the text, in order they occurin the text. invoke(input: Union[PromptValue, str, List[BaseMessage]], config: Optional[RunnableConfig] = None, *, stop: Optional[List[str]] =...
https://api.python.langchain.com/en/latest/llms/langchain_experimental.llms.jsonformer_decoder.JsonFormer.html
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classmethod parse_obj(obj: Any) → Model¶ classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶ predict(text: str, *, stop: Optional[Sequence[str]] = None, **kwargs: Any) → str¶ Pass a single string input to t...
https://api.python.langchain.com/en/latest/llms/langchain_experimental.llms.jsonformer_decoder.JsonFormer.html
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.. code-block:: python llm.save(file_path=”path/llm.yaml”) classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶ classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶ stream(input: Union[Promp...
https://api.python.langchain.com/en/latest/llms/langchain_experimental.llms.jsonformer_decoder.JsonFormer.html
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with_retry(*, retry_if_exception_type: ~typing.Tuple[~typing.Type[BaseException], ...] = (<class 'Exception'>,), wait_exponential_jitter: bool = True, stop_after_attempt: int = 3) → Runnable[Input, Output]¶ property InputType: TypeAlias¶ Get the input type for this runnable. property OutputType: Type[str]¶ Get the inpu...
https://api.python.langchain.com/en/latest/llms/langchain_experimental.llms.jsonformer_decoder.JsonFormer.html
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langchain.llms.google_palm.generate_with_retry¶ langchain.llms.google_palm.generate_with_retry(llm: GooglePalm, **kwargs: Any) → Any[source]¶ Use tenacity to retry the completion call.
https://api.python.langchain.com/en/latest/llms/langchain.llms.google_palm.generate_with_retry.html
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langchain.llms.gooseai.GooseAI¶ class langchain.llms.gooseai.GooseAI[source]¶ Bases: LLM GooseAI large language models. To use, you should have the openai python package installed, and the environment variable GOOSEAI_API_KEY set with your API key. Any parameters that are valid to be passed to the openai.create call ca...
https://api.python.langchain.com/en/latest/llms/langchain.llms.gooseai.GooseAI.html
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Model name to use param n: int = 1¶ How many completions to generate for each prompt. param presence_penalty: float = 0¶ Penalizes repeated tokens. param tags: Optional[List[str]] = None¶ Tags to add to the run trace. param temperature: float = 0.7¶ What sampling temperature to use param top_p: float = 1¶ Total probabi...
https://api.python.langchain.com/en/latest/llms/langchain.llms.gooseai.GooseAI.html
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Run the LLM on the given prompt and input. async agenerate_prompt(prompts: List[PromptValue], stop: Optional[List[str]] = None, callbacks: Union[List[BaseCallbackHandler], BaseCallbackManager, None, List[Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]]]] = None, **kwargs: Any) → LLMResult¶ Asynchronously...
https://api.python.langchain.com/en/latest/llms/langchain.llms.gooseai.GooseAI.html
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Subclasses should override this method if they can run asynchronously. async apredict(text: str, *, stop: Optional[Sequence[str]] = None, **kwargs: Any) → str¶ Asynchronously pass a string to the model and return a string prediction. Use this method when calling pure text generation models and only the topcandidate gen...
https://api.python.langchain.com/en/latest/llms/langchain.llms.gooseai.GooseAI.html
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Subclasses should override this method if they support streaming output. async astream_log(input: Any, config: Optional[RunnableConfig] = None, *, include_names: Optional[Sequence[str]] = None, include_types: Optional[Sequence[str]] = None, include_tags: Optional[Sequence[str]] = None, exclude_names: Optional[Sequence[...
https://api.python.langchain.com/en/latest/llms/langchain.llms.gooseai.GooseAI.html
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Bind arguments to a Runnable, returning a new Runnable. 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...
https://api.python.langchain.com/en/latest/llms/langchain.llms.gooseai.GooseAI.html
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Run the LLM on the given prompt and input. generate_prompt(prompts: List[PromptValue], stop: Optional[List[str]] = None, callbacks: Union[List[BaseCallbackHandler], BaseCallbackManager, None, List[Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]]]] = None, **kwargs: Any) → LLMResult¶ Pass a sequence of pr...
https://api.python.langchain.com/en/latest/llms/langchain.llms.gooseai.GooseAI.html
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Get the number of tokens present in the text. Useful for checking if an input will fit in a model’s context window. Parameters text – The string input to tokenize. Returns The integer number of tokens in the text. get_num_tokens_from_messages(messages: List[BaseMessage]) → int¶ Get the number of tokens in the messages....
https://api.python.langchain.com/en/latest/llms/langchain.llms.gooseai.GooseAI.html
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classmethod lc_id() → List[str]¶ A unique identifier for this class for serialization purposes. The unique identifier is a list of strings that describes the path to the object. map() → Runnable[List[Input], List[Output]]¶ Return a new Runnable that maps a list of inputs to a list of outputs, by calling invoke() with e...
https://api.python.langchain.com/en/latest/llms/langchain.llms.gooseai.GooseAI.html
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Parameters messages – A sequence of chat messages corresponding to a single model input. stop – Stop words to use when generating. Model output is cut off at the first occurrence of any of these substrings. **kwargs – Arbitrary additional keyword arguments. These are usually passed to the model provider API call. Retur...
https://api.python.langchain.com/en/latest/llms/langchain.llms.gooseai.GooseAI.html
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classmethod validate(value: Any) → Model¶ with_config(config: Optional[RunnableConfig] = None, **kwargs: Any) → Runnable[Input, Output]¶ Bind config to a Runnable, returning a new Runnable. with_fallbacks(fallbacks: ~typing.Sequence[~langchain.schema.runnable.base.Runnable[~langchain.schema.runnable.utils.Input, ~langc...
https://api.python.langchain.com/en/latest/llms/langchain.llms.gooseai.GooseAI.html
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langchain.llms.writer.Writer¶ class langchain.llms.writer.Writer[source]¶ Bases: LLM Writer large language models. To use, you should have the environment variable WRITER_API_KEY and WRITER_ORG_ID set with your API key and organization ID respectively. Example from langchain.llms import Writer writer = Writer(model_id=...
https://api.python.langchain.com/en/latest/llms/langchain.llms.writer.Writer.html
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param tags: Optional[List[str]] = None¶ Tags to add to the run trace. param temperature: Optional[float] = None¶ What sampling temperature to use. param top_p: Optional[float] = None¶ Total probability mass of tokens to consider at each step. param verbose: bool [Optional]¶ Whether to print out response text. param wri...
https://api.python.langchain.com/en/latest/llms/langchain.llms.writer.Writer.html
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Run the LLM on the given prompt and input. async agenerate_prompt(prompts: List[PromptValue], stop: Optional[List[str]] = None, callbacks: Union[List[BaseCallbackHandler], BaseCallbackManager, None, List[Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]]]] = None, **kwargs: Any) → LLMResult¶ Asynchronously...
https://api.python.langchain.com/en/latest/llms/langchain.llms.writer.Writer.html
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Subclasses should override this method if they can run asynchronously. async apredict(text: str, *, stop: Optional[Sequence[str]] = None, **kwargs: Any) → str¶ Asynchronously pass a string to the model and return a string prediction. Use this method when calling pure text generation models and only the topcandidate gen...
https://api.python.langchain.com/en/latest/llms/langchain.llms.writer.Writer.html
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Subclasses should override this method if they support streaming output. async astream_log(input: Any, config: Optional[RunnableConfig] = None, *, include_names: Optional[Sequence[str]] = None, include_types: Optional[Sequence[str]] = None, include_tags: Optional[Sequence[str]] = None, exclude_names: Optional[Sequence[...
https://api.python.langchain.com/en/latest/llms/langchain.llms.writer.Writer.html
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Bind arguments to a Runnable, returning a new Runnable. 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...
https://api.python.langchain.com/en/latest/llms/langchain.llms.writer.Writer.html
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Run the LLM on the given prompt and input. generate_prompt(prompts: List[PromptValue], stop: Optional[List[str]] = None, callbacks: Union[List[BaseCallbackHandler], BaseCallbackManager, None, List[Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]]]] = None, **kwargs: Any) → LLMResult¶ Pass a sequence of pr...
https://api.python.langchain.com/en/latest/llms/langchain.llms.writer.Writer.html
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Get the number of tokens present in the text. Useful for checking if an input will fit in a model’s context window. Parameters text – The string input to tokenize. Returns The integer number of tokens in the text. get_num_tokens_from_messages(messages: List[BaseMessage]) → int¶ Get the number of tokens in the messages....
https://api.python.langchain.com/en/latest/llms/langchain.llms.writer.Writer.html
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classmethod lc_id() → List[str]¶ A unique identifier for this class for serialization purposes. The unique identifier is a list of strings that describes the path to the object. map() → Runnable[List[Input], List[Output]]¶ Return a new Runnable that maps a list of inputs to a list of outputs, by calling invoke() with e...
https://api.python.langchain.com/en/latest/llms/langchain.llms.writer.Writer.html
8a82b60f708a-9
Parameters messages – A sequence of chat messages corresponding to a single model input. stop – Stop words to use when generating. Model output is cut off at the first occurrence of any of these substrings. **kwargs – Arbitrary additional keyword arguments. These are usually passed to the model provider API call. Retur...
https://api.python.langchain.com/en/latest/llms/langchain.llms.writer.Writer.html
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classmethod validate(value: Any) → Model¶ with_config(config: Optional[RunnableConfig] = None, **kwargs: Any) → Runnable[Input, Output]¶ Bind config to a Runnable, returning a new Runnable. with_fallbacks(fallbacks: ~typing.Sequence[~langchain.schema.runnable.base.Runnable[~langchain.schema.runnable.utils.Input, ~langc...
https://api.python.langchain.com/en/latest/llms/langchain.llms.writer.Writer.html
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langchain.llms.stochasticai.StochasticAI¶ class langchain.llms.stochasticai.StochasticAI[source]¶ Bases: LLM StochasticAI large language models. To use, you should have the environment variable STOCHASTICAI_API_KEY set with your API key. Example from langchain.llms import StochasticAI stochasticai = StochasticAI(api_ur...
https://api.python.langchain.com/en/latest/llms/langchain.llms.stochasticai.StochasticAI.html
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Check Cache and run the LLM on the given prompt and input. async abatch(inputs: List[Union[PromptValue, str, List[BaseMessage]]], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, return_exceptions: bool = False, **kwargs: Any) → List[str]¶ Default implementation of abatch, which calls ainvoke N ...
https://api.python.langchain.com/en/latest/llms/langchain.llms.stochasticai.StochasticAI.html
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Parameters prompts – List of PromptValues. A PromptValue is an object that can be converted to match the format of any language model (string for pure text generation models and BaseMessages for chat models). stop – Stop words to use when generating. Model output is cut off at the first occurrence of any of these subst...
https://api.python.langchain.com/en/latest/llms/langchain.llms.stochasticai.StochasticAI.html
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Asynchronously pass messages to the model and return a message prediction. Use this method when calling chat models and only the topcandidate generation is needed. Parameters messages – A sequence of chat messages corresponding to a single model input. stop – Stop words to use when generating. Model output is cut off a...
https://api.python.langchain.com/en/latest/llms/langchain.llms.stochasticai.StochasticAI.html
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The jsonpatch ops can be applied in order to construct state. async atransform(input: AsyncIterator[Input], config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → AsyncIterator[Output]¶ Default implementation of atransform, which buffers input and calls astream. Subclasses should override this method if th...
https://api.python.langchain.com/en/latest/llms/langchain.llms.stochasticai.StochasticAI.html
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the new model: you should trust this data deep – set to True to make a deep copy of the model Returns new model instance dict(**kwargs: Any) → Dict¶ Return a dictionary of the LLM. classmethod from_orm(obj: Any) → Model¶ generate(prompts: List[str], stop: Optional[List[str]] = None, callbacks: Union[List[BaseCallbackHa...
https://api.python.langchain.com/en/latest/llms/langchain.llms.stochasticai.StochasticAI.html
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text generation models and BaseMessages for chat models). stop – Stop words to use when generating. Model output is cut off at the first occurrence of any of these substrings. callbacks – Callbacks to pass through. Used for executing additional functionality, such as logging or streaming, throughout generation. **kwarg...
https://api.python.langchain.com/en/latest/llms/langchain.llms.stochasticai.StochasticAI.html
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invoke(input: Union[PromptValue, str, List[BaseMessage]], config: Optional[RunnableConfig] = None, *, stop: Optional[List[str]] = None, **kwargs: Any) → str¶ classmethod is_lc_serializable() → bool¶ Is this class serializable? json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Option...
https://api.python.langchain.com/en/latest/llms/langchain.llms.stochasticai.StochasticAI.html
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predict(text: str, *, stop: Optional[Sequence[str]] = None, **kwargs: Any) → str¶ Pass a single string input to the model and return a string prediction. Use this method when passing in raw text. If you want to pass in specifictypes of chat messages, use predict_messages. Parameters text – String input to pass to the m...
https://api.python.langchain.com/en/latest/llms/langchain.llms.stochasticai.StochasticAI.html
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stream(input: Union[PromptValue, str, List[BaseMessage]], config: Optional[RunnableConfig] = None, *, stop: Optional[List[str]] = None, **kwargs: Any) → Iterator[str]¶ Default implementation of stream, which calls invoke. Subclasses should override this method if they support streaming output. to_json() → Union[Seriali...
https://api.python.langchain.com/en/latest/llms/langchain.llms.stochasticai.StochasticAI.html
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property InputType: TypeAlias¶ Get the input type for this runnable. property OutputType: Type[str]¶ Get the input type for this runnable. property input_schema: Type[pydantic.main.BaseModel]¶ property lc_attributes: Dict¶ List of attribute names that should be included in the serialized kwargs. These attributes must b...
https://api.python.langchain.com/en/latest/llms/langchain.llms.stochasticai.StochasticAI.html
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langchain.llms.azureml_endpoint.LlamaContentFormatter¶ class langchain.llms.azureml_endpoint.LlamaContentFormatter[source]¶ Content formatter for LLaMa Attributes accepts The MIME type of the response data returned from the endpoint content_type The MIME type of the input data passed to the endpoint Methods __init__() ...
https://api.python.langchain.com/en/latest/llms/langchain.llms.azureml_endpoint.LlamaContentFormatter.html