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There are two ways to use ellmer chat models for batch processing. This flexibility allows you to 1) pass a function that creates a ready-to-go chat model or 2) pass a chat model object for more user control.
The first method is to pass an ellmer chat model function directly.
This is the preferred method because it lets hellmer setup the model,
specifically setting echo = "none"
for cleaner console
output:
library(hellmer)
# Sequential processing
chat <- chat_sequential(
chat_model = chat_claude,
system_prompt = "Reply concisely"
)
# Parallel processing
chat <- chat_future(
chat_model = chat_claude,
system_prompt = "Reply concisely",
workers = 4
)
In this case, hellmer will:
chat_model
is a functionecho = "none"
and any additional
parameters you provideThe second method is to pass a chat model object. This is useful when you need more control over model configuration or want to reuse an existing model:
library(hellmer)
# Create and configure a chat model
claude <- chat_claude(
model = "claude-3-7-sonnet-latest",
system_prompt = "Reply concisely",
echo = "none",
max_tokens = 1000
)
# Sequential processing
chat <- chat_sequential(chat_model = claude)
# Parallel processing
chat <- chat_future(
chat_model = claude,
workers = 4
)
In this case, hellmer will:
chat_model
is an objectThese binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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