llm/docs/usage.md
2023-06-15 18:42:17 +01:00

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# Usage
The default command for this is `llm prompt` - you can use `llm` instead if you prefer.
## Executing a prompt
To run a prompt:
llm 'Ten names for cheesecakes'
To stream the results a token at a time:
llm 'Ten names for cheesecakes' -s
To switch from ChatGPT 3.5 (the default) to GPT-4 if you have access:
llm 'Ten names for cheesecakes' -4
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 `--system '...'` to set a system prompt.
llm 'SQL to calculate total sales by month' -s \
--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 --system 'Suggest topics for this post as a JSON array' --stream