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

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.