Logging to SQLite#
llm
defaults to logging all prompts and responses to a SQLite database.
You can find the location of that database using the llm logs path
command:
llm logs path
On my Mac that outputs:
/Users/simon/Library/Application Support/io.datasette.llm/logs.db
This will differ for other operating systems.
To avoid logging an individual prompt, pass --no-log
or -n
to the command:
llm 'Ten names for cheesecakes' -n
To turn logging by default off:
llm logs off
If you’ve turned off logging you can still log an individual prompt and response by adding --log
:
llm 'Five ambitious names for a pet pterodactyl' --log
To turn logging by default back on again:
llm logs on
To see the status of the logs database, run this:
llm logs status
Example output:
Logging is ON for all prompts
Found log database at /Users/simon/Library/Application Support/io.datasette.llm/logs.db
Number of conversations logged: 33
Number of responses logged: 48
Database file size: 19.96MB
Viewing the logs#
You can view the logs using the llm logs
command:
llm logs
This will output the three most recent logged items in Markdown format, showing both the prompt and the response formatted using Markdown.
To get back just the most recent prompt response as plain text, add -r/--response
:
llm logs -r
Add --json
to get the log messages in JSON instead:
llm logs --json
Add -n 10
to see the ten most recent items:
llm logs -n 10
Or -n 0
to see everything that has ever been logged:
llm logs -n 0
You can truncate the display of the prompts and responses using the -t/--truncate
option. This can help make the JSON output more readable:
llm logs -n 5 -t --json
Logs for a conversation#
To view the logs for the most recent conversation you have had with a model, use -c
:
llm logs -c
To see logs for a specific conversation based on its ID, use --cid ID
or --conversation ID
:
llm logs --cid 01h82n0q9crqtnzmf13gkyxawg
Searching the logs#
You can search the logs for a search term in the prompt
or the response
columns.
llm logs -q 'cheesecake'
The most relevant terms will be shown at the bottom of the output.
Filtering by model#
You can filter to logs just for a specific model (or model alias) using -m/--model
:
llm logs -m chatgpt
Browsing logs using Datasette#
You can also use Datasette to browse your logs like this:
datasette "$(llm logs path)"
SQL schema#
Here’s the SQL schema used by the logs.db
database:
CREATE TABLE [conversations] (
[id] TEXT PRIMARY KEY,
[name] TEXT,
[model] TEXT
);
CREATE TABLE [responses] (
[id] TEXT PRIMARY KEY,
[model] TEXT,
[prompt] TEXT,
[system] TEXT,
[prompt_json] TEXT,
[options_json] TEXT,
[response] TEXT,
[response_json] TEXT,
[conversation_id] TEXT REFERENCES [conversations]([id]),
[duration_ms] INTEGER,
[datetime_utc] TEXT
);
CREATE VIRTUAL TABLE [responses_fts] USING FTS5 (
[prompt],
[response],
content=[responses]
);
responses_fts
configures SQLite full-text search against the prompt
and response
columns in the responses
table.