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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¶ classmethod update_forward_refs(**localns: Any) → None¶ Try to update ForwardRefs on...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.javelin_ai_gateway.ChatParams.html
5ec3149e3d6c-0
langchain.chat_models.anthropic.convert_messages_to_prompt_anthropic¶ langchain.chat_models.anthropic.convert_messages_to_prompt_anthropic(messages: List[BaseMessage], *, human_prompt: str = '\n\nHuman:', ai_prompt: str = '\n\nAssistant:') → str[source]¶ Format a list of messages into a full prompt for the Anthropic mo...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.anthropic.convert_messages_to_prompt_anthropic.html
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langchain.chat_models.bedrock.BedrockChat¶ class langchain.chat_models.bedrock.BedrockChat[source]¶ Bases: BaseChatModel, BedrockBase 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[boo...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.bedrock.BedrockChat.html
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param region_name: Optional[str] = None¶ The aws region e.g., us-west-2. Fallsback to AWS_DEFAULT_REGION env variable or region specified in ~/.aws/config in case it is not provided here. param streaming: bool = False¶ Whether to stream the results. param tags: Optional[List[str]] = None¶ Tags to add to the run trace. ...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.bedrock.BedrockChat.html
db2495b5c576-2
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 agnostic to the underlying language modeltype (e.g., pure text completion ...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.bedrock.BedrockChat.html
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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. async apredict_messages(messages: List[BaseMessage], *, stop: Optional[Sequence[str]] = None, **kwargs: Any) → BaseMessage¶ A...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.bedrock.BedrockChat.html
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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 can be applied in order to construct state. async atransform(input: As...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.bedrock.BedrockChat.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/chat_models/langchain.chat_models.bedrock.BedrockChat.html
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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 agnostic to the underlying language modeltype (e.g., pure text completion models vs chat models). Parameters prompts – List of PromptValues. A PromptVal...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.bedrock.BedrockChat.html
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Returns The sum of the number of tokens across the messages. get_token_ids(text: str) → List[int]¶ 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[PromptValu...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.bedrock.BedrockChat.html
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by calling invoke() with each input. classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶ classmethod parse_obj(obj: Any) → Model¶ classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = No...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.bedrock.BedrockChat.html
db2495b5c576-9
to the model provider API call. Returns Top model prediction as a message. 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(in...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.bedrock.BedrockChat.html
db2495b5c576-10
Bind config to a Runnable, returning a new Runnable. with_fallbacks(fallbacks: ~typing.Sequence[~langchain.schema.runnable.base.Runnable[~langchain.schema.runnable.utils.Input, ~langchain.schema.runnable.utils.Output]], *, exceptions_to_handle: ~typing.Tuple[~typing.Type[BaseException], ...] = (<class 'Exception'>,)) →...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.bedrock.BedrockChat.html
753da5d658b1-0
langchain.chat_models.jinachat.acompletion_with_retry¶ async langchain.chat_models.jinachat.acompletion_with_retry(llm: JinaChat, **kwargs: Any) → Any[source]¶ Use tenacity to retry the async completion call.
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.jinachat.acompletion_with_retry.html
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langchain.chat_models.base.BaseChatModel¶ class langchain.chat_models.base.BaseChatModel[source]¶ Bases: BaseLanguageModel[BaseMessageChunk], ABC Base class for Chat models. Create a new model by parsing and validating input data from keyword arguments. Raises ValidationError if the input data cannot be parsed to form ...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.base.BaseChatModel.html
ae5d97389c53-1
Subclasses should override this method if they can batch more efficiently. async agenerate(messages: List[List[BaseMessage]], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = Non...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.base.BaseChatModel.html
ae5d97389c53-2
async ainvoke(input: Union[PromptValue, str, List[BaseMessage]], config: Optional[RunnableConfig] = None, *, stop: Optional[List[str]] = None, **kwargs: Any) → BaseMessageChunk[source]¶ Default implementation of ainvoke, which calls invoke in a thread pool. Subclasses should override this method if they can run asynchr...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.base.BaseChatModel.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[BaseMessageChunk][source]¶ Default implementation of astream, which cal...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.base.BaseChatModel.html
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input is still being generated. batch(inputs: List[Input], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, return_exceptions: bool = False, **kwargs: Optional[Any]) → List[Output]¶ Default implementation of batch, which calls invoke N times. Subclasses should override this method if they can ba...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.base.BaseChatModel.html
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Return a dictionary of the LLM. classmethod from_orm(obj: Any) → Model¶ generate(messages: List[List[BaseMessage]], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, run_nam...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.base.BaseChatModel.html
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classmethod get_lc_namespace() → List[str]¶ Get the namespace of the langchain object. For example, if the class is langchain.llms.openai.OpenAI, then the namespace is [“langchain”, “llms”, “openai”] get_num_tokens(text: str) → int¶ Get the number of tokens present in the text. Useful for checking if an input will fit ...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.base.BaseChatModel.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/chat_models/langchain.chat_models.base.BaseChatModel.html
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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/chat_models/langchain.chat_models.base.BaseChatModel.html
ae5d97389c53-9
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/chat_models/langchain.chat_models.base.BaseChatModel.html
ae5d97389c53-10
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 output_schema: Type[pydantic.main.BaseModel]¶
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.base.BaseChatModel.html
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langchain.chat_models.azureml_endpoint.LlamaContentFormatter¶ class langchain.chat_models.azureml_endpoint.LlamaContentFormatter[source]¶ Content formatter for LLaMA. Attributes SUPPORTED_ROLES accepts The MIME type of the response data returned from the endpoint content_type The MIME type of the input data passed to t...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.azureml_endpoint.LlamaContentFormatter.html
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langchain.chat_models.google_palm.chat_with_retry¶ langchain.chat_models.google_palm.chat_with_retry(llm: ChatGooglePalm, **kwargs: Any) → Any[source]¶ Use tenacity to retry the completion call.
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.google_palm.chat_with_retry.html
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langchain.chat_models.base.SimpleChatModel¶ class langchain.chat_models.base.SimpleChatModel[source]¶ Bases: BaseChatModel Simple Chat 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: Opti...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.base.SimpleChatModel.html
cb7be2a1738e-1
Subclasses should override this method if they can batch more efficiently. async agenerate(messages: List[List[BaseMessage]], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = Non...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.base.SimpleChatModel.html
cb7be2a1738e-2
async ainvoke(input: Union[PromptValue, str, List[BaseMessage]], config: Optional[RunnableConfig] = None, *, stop: Optional[List[str]] = None, **kwargs: Any) → BaseMessageChunk¶ Default implementation of ainvoke, which calls invoke in a thread pool. Subclasses should override this method if they can run asynchronously....
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.base.SimpleChatModel.html
cb7be2a1738e-3
Default implementation of astream, which calls ainvoke. 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[...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.base.SimpleChatModel.html
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Bind arguments to a Runnable, returning a new Runnable. call_as_llm(message: str, stop: Optional[List[str]] = None, **kwargs: Any) → str¶ 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. Defaul...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.base.SimpleChatModel.html
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Top Level call generate_prompt(prompts: List[PromptValue], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, **kwargs: Any) → LLMResult¶ Pass a sequence of prompts to the model and return model generations. This method should make use of batched calls f...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.base.SimpleChatModel.html
cb7be2a1738e-6
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. Useful for checking if an input will fit in a model’s context window. Parameters messages – The message inputs to t...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.base.SimpleChatModel.html
cb7be2a1738e-7
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 each input. classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encod...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.base.SimpleChatModel.html
cb7be2a1738e-8
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 message. classmethod schema(by_alias: bool = True, ref_templ...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.base.SimpleChatModel.html
cb7be2a1738e-9
Bind config to a Runnable, returning a new Runnable. with_fallbacks(fallbacks: ~typing.Sequence[~langchain.schema.runnable.base.Runnable[~langchain.schema.runnable.utils.Input, ~langchain.schema.runnable.utils.Output]], *, exceptions_to_handle: ~typing.Tuple[~typing.Type[BaseException], ...] = (<class 'Exception'>,)) →...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.base.SimpleChatModel.html
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langchain.chat_models.javelin_ai_gateway.ChatJavelinAIGateway¶ class langchain.chat_models.javelin_ai_gateway.ChatJavelinAIGateway[source]¶ Bases: BaseChatModel Javelin AI Gateway chat models API. To use, you should have the javelin_sdk python package installed. For more information, see https://docs.getjavelin.io Exam...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.javelin_ai_gateway.ChatJavelinAIGateway.html
2bc0f490dae5-1
param tags: Optional[List[str]] = None¶ Tags to add to the run trace. param verbose: bool [Optional]¶ Whether to print out response text. __call__(messages: List[BaseMessage], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, **kwargs: Any) → BaseMessag...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.javelin_ai_gateway.ChatJavelinAIGateway.html
2bc0f490dae5-2
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/chat_models/langchain.chat_models.javelin_ai_gateway.ChatJavelinAIGateway.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/chat_models/langchain.chat_models.javelin_ai_gateway.ChatJavelinAIGateway.html
2bc0f490dae5-4
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/chat_models/langchain.chat_models.javelin_ai_gateway.ChatJavelinAIGateway.html
2bc0f490dae5-5
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 copy of the model Returns new model instance dict(**kw...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.javelin_ai_gateway.ChatJavelinAIGateway.html
2bc0f490dae5-6
first occurrence of any of these substrings. callbacks – Callbacks to pass through. Used for executing additional 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 co...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.javelin_ai_gateway.ChatJavelinAIGateway.html
2bc0f490dae5-7
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/chat_models/langchain.chat_models.javelin_ai_gateway.ChatJavelinAIGateway.html
2bc0f490dae5-8
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/chat_models/langchain.chat_models.javelin_ai_gateway.ChatJavelinAIGateway.html
2bc0f490dae5-9
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/chat_models/langchain.chat_models.javelin_ai_gateway.ChatJavelinAIGateway.html
2bc0f490dae5-10
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 output_schema: Type[pydantic.main.BaseModel]¶
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.javelin_ai_gateway.ChatJavelinAIGateway.html
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langchain.chat_models.fake.FakeMessagesListChatModel¶ class langchain.chat_models.fake.FakeMessagesListChatModel[source]¶ Bases: BaseChatModel 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: Opt...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.fake.FakeMessagesListChatModel.html
5b316afa11ad-1
Subclasses should override this method if they can batch more efficiently. async agenerate(messages: List[List[BaseMessage]], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = Non...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.fake.FakeMessagesListChatModel.html
5b316afa11ad-2
async ainvoke(input: Union[PromptValue, str, List[BaseMessage]], config: Optional[RunnableConfig] = None, *, stop: Optional[List[str]] = None, **kwargs: Any) → BaseMessageChunk¶ Default implementation of ainvoke, which calls invoke in a thread pool. Subclasses should override this method if they can run asynchronously....
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.fake.FakeMessagesListChatModel.html
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Default implementation of astream, which calls ainvoke. 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[...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.fake.FakeMessagesListChatModel.html
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Bind arguments to a Runnable, returning a new Runnable. call_as_llm(message: str, stop: Optional[List[str]] = None, **kwargs: Any) → str¶ 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. Defaul...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.fake.FakeMessagesListChatModel.html
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Top Level call generate_prompt(prompts: List[PromptValue], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, **kwargs: Any) → LLMResult¶ Pass a sequence of prompts to the model and return model generations. This method should make use of batched calls f...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.fake.FakeMessagesListChatModel.html
5b316afa11ad-6
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. Useful for checking if an input will fit in a model’s context window. Parameters messages – The message inputs to t...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.fake.FakeMessagesListChatModel.html
5b316afa11ad-7
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 each input. classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encod...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.fake.FakeMessagesListChatModel.html
5b316afa11ad-8
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 message. classmethod schema(by_alias: bool = True, ref_templ...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.fake.FakeMessagesListChatModel.html
5b316afa11ad-9
Bind config to a Runnable, returning a new Runnable. with_fallbacks(fallbacks: ~typing.Sequence[~langchain.schema.runnable.base.Runnable[~langchain.schema.runnable.utils.Input, ~langchain.schema.runnable.utils.Output]], *, exceptions_to_handle: ~typing.Tuple[~typing.Type[BaseException], ...] = (<class 'Exception'>,)) →...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.fake.FakeMessagesListChatModel.html
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langchain.chat_models.ollama.ChatOllama¶ class langchain.chat_models.ollama.ChatOllama[source]¶ Bases: BaseChatModel, _OllamaCommon Ollama locally runs large language models. To use, follow the instructions at https://ollama.ai/. Example from langchain.chat_models import ChatOllama ollama = ChatOllama(model="llama2") C...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.ollama.ChatOllama.html
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coherent text. (Default: 5.0) param model: str = 'llama2'¶ Model name to use. param num_ctx: Optional[int] = None¶ Sets the size of the context window used to generate the next token. (Default: 2048) param num_gpu: Optional[int] = None¶ The number of GPUs to use. On macOS it defaults to 1 to enable metal support, 0 to ...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.ollama.ChatOllama.html
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Tail free sampling is used to reduce the impact of less probable tokens from the output. A higher value (e.g., 2.0) will reduce the impact more, while a value of 1.0 disables this setting. (default: 1) param top_k: Optional[int] = None¶ Reduces the probability of generating nonsense. A higher value (e.g. 100) will give...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.ollama.ChatOllama.html
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Subclasses should override this method if they can batch more efficiently. async agenerate(messages: List[List[BaseMessage]], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = Non...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.ollama.ChatOllama.html
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async ainvoke(input: Union[PromptValue, str, List[BaseMessage]], config: Optional[RunnableConfig] = None, *, stop: Optional[List[str]] = None, **kwargs: Any) → BaseMessageChunk¶ Default implementation of ainvoke, which calls invoke in a thread pool. Subclasses should override this method if they can run asynchronously....
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.ollama.ChatOllama.html
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Default implementation of astream, which calls ainvoke. 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[...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.ollama.ChatOllama.html
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Bind arguments to a Runnable, returning a new Runnable. call_as_llm(message: str, stop: Optional[List[str]] = None, **kwargs: Any) → str¶ 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. Defaul...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.ollama.ChatOllama.html
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Top Level call generate_prompt(prompts: List[PromptValue], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, **kwargs: Any) → LLMResult¶ Pass a sequence of prompts to the model and return model generations. This method should make use of batched calls f...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.ollama.ChatOllama.html
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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. Useful for checking if an input will fit in a model’s context window. Parameters messages – The message inputs to t...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.ollama.ChatOllama.html
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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 each input. classmethod parse_file...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.ollama.ChatOllama.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/chat_models/langchain.chat_models.ollama.ChatOllama.html
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Bind config to a Runnable, returning a new Runnable. with_fallbacks(fallbacks: ~typing.Sequence[~langchain.schema.runnable.base.Runnable[~langchain.schema.runnable.utils.Input, ~langchain.schema.runnable.utils.Output]], *, exceptions_to_handle: ~typing.Tuple[~typing.Type[BaseException], ...] = (<class 'Exception'>,)) →...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.ollama.ChatOllama.html
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langchain.chat_models.azureml_endpoint.AzureMLChatOnlineEndpoint¶ class langchain.chat_models.azureml_endpoint.AzureMLChatOnlineEndpoint[source]¶ Bases: SimpleChatModel AzureML Chat models API. Example azure_chat = AzureMLChatOnlineEndpoint( endpoint_url="https://<your-endpoint>.<your_region>.inference.ml.azure.com...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.azureml_endpoint.AzureMLChatOnlineEndpoint.html
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param verbose: bool [Optional]¶ Whether to print out response text. __call__(messages: List[BaseMessage], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, **kwargs: Any) → BaseMessage¶ Call self as a function. async abatch(inputs: List[Input], config: ...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.azureml_endpoint.AzureMLChatOnlineEndpoint.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/chat_models/langchain.chat_models.azureml_endpoint.AzureMLChatOnlineEndpoint.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/chat_models/langchain.chat_models.azureml_endpoint.AzureMLChatOnlineEndpoint.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/chat_models/langchain.chat_models.azureml_endpoint.AzureMLChatOnlineEndpoint.html
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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 copy of the model Returns new model instance dict(**kw...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.azureml_endpoint.AzureMLChatOnlineEndpoint.html
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first occurrence of any of these substrings. callbacks – Callbacks to pass through. Used for executing additional 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 co...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.azureml_endpoint.AzureMLChatOnlineEndpoint.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/chat_models/langchain.chat_models.azureml_endpoint.AzureMLChatOnlineEndpoint.html
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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/chat_models/langchain.chat_models.azureml_endpoint.AzureMLChatOnlineEndpoint.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/chat_models/langchain.chat_models.azureml_endpoint.AzureMLChatOnlineEndpoint.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 output_schema: Type[pydantic.main.BaseModel]¶ ...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.azureml_endpoint.AzureMLChatOnlineEndpoint.html
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langchain.chat_models.promptlayer_openai.PromptLayerChatOpenAI¶ class langchain.chat_models.promptlayer_openai.PromptLayerChatOpenAI[source]¶ Bases: ChatOpenAI PromptLayer and OpenAI Chat large language models API. To use, you should have the openai and promptlayer python package installed, and the environment variable...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.promptlayer_openai.PromptLayerChatOpenAI.html
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Holds any model parameters valid for create call not explicitly specified. param model_name: str = 'gpt-3.5-turbo' (alias 'model')¶ Model name to use. param n: int = 1¶ Number of chat completions to generate for each prompt. param openai_api_base: Optional[str] = None¶ param openai_api_key: Optional[str] = None¶ Base U...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.promptlayer_openai.PromptLayerChatOpenAI.html
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API but with different models. In those cases, in order to avoid erroring when tiktoken is called, you can specify a model name to use here. param verbose: bool [Optional]¶ Whether to print out response text. __call__(messages: List[BaseMessage], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[BaseCall...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.promptlayer_openai.PromptLayerChatOpenAI.html
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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/chat_models/langchain.chat_models.promptlayer_openai.PromptLayerChatOpenAI.html
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to the model provider API call. Returns Top model prediction as a string. async apredict_messages(messages: List[BaseMessage], *, stop: Optional[Sequence[str]] = None, **kwargs: Any) → BaseMessage¶ Asynchronously pass messages to the model and return a message prediction. Use this method when calling chat models and on...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.promptlayer_openai.PromptLayerChatOpenAI.html
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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 can be applied in order to construct state. async atransform(input: AsyncIterator[Input], config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → AsyncIterator[Output]¶ Default im...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.promptlayer_openai.PromptLayerChatOpenAI.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/chat_models/langchain.chat_models.promptlayer_openai.PromptLayerChatOpenAI.html
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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 agnostic to the underlying language modeltype (e.g., pure text completion models vs chat models). Parameters prompts – List of PromptValues. A PromptVal...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.promptlayer_openai.PromptLayerChatOpenAI.html
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main/examples/How_to_format_inputs_to_ChatGPT_models.ipynb get_token_ids(text: str) → List[int]¶ Get the tokens present in the text with tiktoken package. invoke(input: Union[PromptValue, str, List[BaseMessage]], config: Optional[RunnableConfig] = None, *, stop: Optional[List[str]] = None, **kwargs: Any) → BaseMessageC...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.promptlayer_openai.PromptLayerChatOpenAI.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/chat_models/langchain.chat_models.promptlayer_openai.PromptLayerChatOpenAI.html
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stream(input: Union[PromptValue, str, List[BaseMessage]], config: Optional[RunnableConfig] = None, *, stop: Optional[List[str]] = None, **kwargs: Any) → Iterator[BaseMessageChunk]¶ Default implementation of stream, which calls invoke. Subclasses should override this method if they support streaming output. to_json() → ...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.promptlayer_openai.PromptLayerChatOpenAI.html
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property InputType: TypeAlias¶ Get the input type for this runnable. property OutputType: Any¶ 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 be acce...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.promptlayer_openai.PromptLayerChatOpenAI.html
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langchain.chat_models.baidu_qianfan_endpoint.convert_message_to_dict¶ langchain.chat_models.baidu_qianfan_endpoint.convert_message_to_dict(message: BaseMessage) → dict[source]¶ Examples using convert_message_to_dict¶ Twitter (via Apify)
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.baidu_qianfan_endpoint.convert_message_to_dict.html
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langchain.chat_models.fireworks.acompletion_with_retry_streaming¶ async langchain.chat_models.fireworks.acompletion_with_retry_streaming(llm: ChatFireworks, *, run_manager: Optional[AsyncCallbackManagerForLLMRun] = None, **kwargs: Any) → Any[source]¶ Use tenacity to retry the completion call for streaming.
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.fireworks.acompletion_with_retry_streaming.html
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langchain.chat_models.minimax.MiniMaxChat¶ class langchain.chat_models.minimax.MiniMaxChat[source]¶ Bases: MinimaxCommon, BaseChatModel Wrapper around Minimax large language models. To use, you should have the environment variable MINIMAX_GROUP_ID and MINIMAX_API_KEY set with your API token, or pass it as a named param...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.minimax.MiniMaxChat.html
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param top_p: float = 0.95¶ Total probability mass of tokens to consider at each step. param verbose: bool [Optional]¶ Whether to print out response text. __call__(messages: List[BaseMessage], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, **kwargs: A...
https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.minimax.MiniMaxChat.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/chat_models/langchain.chat_models.minimax.MiniMaxChat.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/chat_models/langchain.chat_models.minimax.MiniMaxChat.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/chat_models/langchain.chat_models.minimax.MiniMaxChat.html