2.1 KiB
Usage
The default command for this is llm prompt - you can use llm instead if you prefer.
Executing a prompt
To run a prompt, streaming tokens as they come in:
llm 'Ten names for cheesecakes'
To disable streaming and only return the response once it has completed:
llm 'Ten names for cheesecakes' --no-stream
To switch from ChatGPT 3.5 (the default) to GPT-4 if you have access:
llm 'Ten names for cheesecakes' -m gpt4
You can use -m 4 as an even shorter shortcut.
Pass --model <model name> to use a different model.
You can also send a prompt to standard input, for example:
echo 'Ten names for cheesecakes' | llm
Continuing a conversation
By default, the tool will start a new conversation each time you run it.
You can opt to continue the previous conversation by passing the -c/--continue option:
llm 'More names' --continue
This will re-send the prompts and responses for the previous conversation. Note that this can add up quickly in terms of tokens, especially if you are using more expensive models.
To continue a conversation that is not the most recent one, use the --chat <id> option:
llm 'More names' --chat 2
You can find these chat IDs using the llm logs command.
Note that this feature only works if you have been logging your previous conversations to a database, having run the llm init-db command described below.
Using with a shell
To generate a description of changes made to a Git repository since the last commit:
llm "Describe these changes: $(git diff)"
This pattern of using $(command) inside a double quoted string is a useful way to quickly assemble prompts.
System prompts
You can use -s/--system '...' to set a system prompt.
llm 'SQL to calculate total sales by month' \
--system 'You are an exaggerated sentient cheesecake that knows SQL and talks about cheesecake a lot'
This is useful for piping content to standard input, for example:
curl -s 'https://simonwillison.net/2023/May/15/per-interpreter-gils/' | \
llm -s 'Suggest topics for this post as a JSON array'