serialized kwargs. These attributes must be accepted by the
constructor.
property lc_namespace: List[str]#
Return the namespace of the langchain object.
eg. [“langchain”, “llms”, “openai”]
property lc_secrets: Dict[str, str]#
Return a map of constructor argument names to secret ids.
eg. {“openai_api_key”: “OPENAI_API_KEY”}
property lc_serializable: bool#
Return whether or not the class is serializable.
pydantic model langchain.llms.Anthropic[source]#
Wrapper around Anthropic’s large language models.
To use, you should have the anthropic python package installed, and the
environment variable ANTHROPIC_API_KEY set with your API key, or pass
it as a named parameter to the constructor.
Example
import anthropic
from langchain.llms import Anthropic
model = Anthropic(model="<model_name>", anthropic_api_key="my-api-key")
# Simplest invocation, automatically wrapped with HUMAN_PROMPT
# and AI_PROMPT.
response = model("What are the biggest risks facing humanity?")
# Or if you want to use the chat mode, build a few-shot-prompt, or
# put words in the Assistant's mouth, use HUMAN_PROMPT and AI_PROMPT:
raw_prompt = "What are the biggest risks facing humanity?"
prompt = f"{anthropic.HUMAN_PROMPT} {prompt}{anthropic.AI_PROMPT}"
response = model(prompt)
Validators
raise_deprecation » all fields
raise_warning » all fields
set_verbose » verbose
validate_environment » all fields
field default_request_timeout: Optional[Union[float, Tuple[float, float]]] = None#
Timeout for requests to Anthropic Completion API. Default is 600 seconds.
field max_tokens_to_sample: int = 256#
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html