AWS Bedrock provides a number of language models, including those from Anthropic's Claude, using the Bedrock Converse API.
Authentication is handled through {paws.common}, so if authentication
does not work for you automatically, you'll need to follow the advice
at https://www.paws-r-sdk.com/#credentials. In particular, if your
org uses AWS SSO, you'll need to run aws sso login at the terminal.
A system prompt to set the behavior of the assistant.
The base URL to the endpoint; the default uses OpenAI.
The model to use for the chat (defaults to "anthropic.claude-3-5-sonnet-20240620-v1:0").
We regularly update the default, so we strongly recommend explicitly specifying a model for anything other than casual use.
Use models_models_aws_bedrock() to see all options.
.
While ellmer provides a default model, there's no guarantee that you'll
have access to it, so you'll need to specify a model that you can.
If you're using cross-region inference,
you'll need to use the inference profile ID, e.g.
model="us.anthropic.claude-3-5-sonnet-20240620-v1:0".
AWS profile to use.
Common model parameters, usually created by params().
Named list of arbitrary extra arguments appended to the body of every chat API call. Some useful arguments include:
Named character vector of arbitrary extra headers appended to every chat API call.
One of the following options:
none: don't emit any output (default when running in a function).
output: echo text and tool-calling output as it streams in (default
when running at the console).
all: echo all input and output.
Note this only affects the chat() method.
A Chat object.
Other chatbots:
chat_anthropic(),
chat_azure_openai(),
chat_cloudflare(),
chat_databricks(),
chat_deepseek(),
chat_github(),
chat_google_gemini(),
chat_groq(),
chat_huggingface(),
chat_mistral(),
chat_ollama(),
chat_openai(),
chat_openrouter(),
chat_perplexity(),
chat_portkey()
if (FALSE) { # \dontrun{
# Basic usage
chat <- chat_aws_bedrock()
chat$chat("Tell me three jokes about statisticians")
} # }