LLMInputOutputAdapter#
- class langchain_aws.llms.bedrock.LLMInputOutputAdapter[source]#
Adapter class to prepare the inputs from Langchain to a format that LLM model expects.
It also provides helper function to extract the generated text from the model response.
Attributes
provider_to_output_key_map
Methods
__init__
()aprepare_output_stream
(provider, response[, ...])prepare_input
(provider, model_kwargs[, ...])prepare_output
(provider, response)prepare_output_stream
(provider, response[, ...])- __init__()#
- classmethod aprepare_output_stream(provider: str, response: Any, stop: List[str] | None = None, messages_api: bool = False, coerce_content_to_string: bool = False) AsyncIterator[GenerationChunk | AIMessageChunk] [source]#
- Parameters:
provider (str)
response (Any)
stop (List[str] | None)
messages_api (bool)
coerce_content_to_string (bool)
- Return type:
AsyncIterator[GenerationChunk | AIMessageChunk]
- classmethod prepare_input(provider: str, model_kwargs: Dict[str, Any], prompt: str | None = None, system: str | None = None, messages: List[Dict] | None = None, tools: List[AnthropicTool] | None = None, *, max_tokens: int | None = None, temperature: float | None = None) Dict[str, Any] [source]#
- Parameters:
provider (str)
model_kwargs (Dict[str, Any])
prompt (str | None)
system (str | None)
messages (List[Dict] | None)
tools (List[AnthropicTool] | None)
max_tokens (int | None)
temperature (float | None)
- Return type:
Dict[str, Any]
- classmethod prepare_output(provider: str, response: Any) dict [source]#
- Parameters:
provider (str)
response (Any)
- Return type:
dict
- classmethod prepare_output_stream(provider: str, response: Any, stop: List[str] | None = None, messages_api: bool = False, coerce_content_to_string: bool = False) Iterator[GenerationChunk | AIMessageChunk] [source]#
- Parameters:
provider (str)
response (Any)
stop (List[str] | None)
messages_api (bool)
coerce_content_to_string (bool)
- Return type:
Iterator[GenerationChunk | AIMessageChunk]