datasette-llm-sql-writer 0.2.0

Generate Datasette SQL queries using plain language and an LLM

datasette-llm-sql-writer

Generate Datasette SQL queries using plain language and an LLM.

This plugin adds an "LLM SQL Writer" panel to Datasette pages that helps you write read‑only SQL (SELECT/CTE) from a natural‑language prompt. It keeps a per‑database chat history, lets you copy or re‑run previously generated queries, and respects Datasette’s built‑in SQL editor when present.

Installation

Install this plugin in the same environment as Datasette.

datasette install datasette-llm-sql-writer

Usage

1. Start Datasette with a database

Provide any SQLite database file when starting Datasette. Navigate to a table page to see the LLM panel above the table. On non‑table pages the panel is inserted below the first page header so you can still generate and run queries.

datasette path/to/your.db -p 8001
# Then visit http://127.0.0.1:8001/your/tablename

2. Configure the LLM model (optional but recommended)

By default, the plugin targets OpenAI and uses gpt-5-mini unless you override it. You can configure a model via Datasette metadata or an environment variable (see below):

metadata.json:

{
  "plugins": {
    "datasette-llm-sql-writer": {
      "model": "gpt-5-mini"
    }
  }
}

Then start Datasette with --metadata:

datasette path/to/your.db --metadata metadata.json -p 8001

3. Use the panel

• Enter a natural‑language prompt in the panel.
• Click "Generate Only" to request SQL from the LLM and preview it in the panel. If the SQL editor is visible, the latest SQL is also inserted there.
• Click "Generate & Run" to generate (if needed) and immediately execute the SQL.
• Each assistant SQL card includes icon buttons:
  • Copy (clipboard icon): copies the SQL to your clipboard.
  • Run (triangle icon): runs that specific SQL—either by inserting it into the editor and submitting, or by redirecting to the query page if the editor is hidden.

Notes:

• The backend enforces that generated SQL is read‑only. See datasette_llm_sql_writer/generator.py:is_select_only().
• The panel tracks whether the current prompt/SQL has already been run—if you change the prompt or the SQL in the editor, "Generate & Run" will regenerate before running.

CAUTION CAUTION CAUTION - THIS GRANTS OTHERS USE OF YOUR LLM ACCOUNT

This plugin uses your API key to generate SQL queries. If you're using this plugin locally, that's exactly what you want. If you're using this plugin to share a dataset with others, be aware that you're letting them run up LLM bills on your behalf.

(In practice, these prompts will be effectively free, but it's still a good idea to be aware of this. And somebody is likely to be able to find some extra use for free API calls if they work hard enough. )

Authentication and API Keys

This plugin relies on the llm package for model execution and authentication. To minimize friction and keep secrets management simple, you have two supported options:

1. Use llm's built-in key store (best for local development)

llm keys set openai

This stores your key securely for your user account. The plugin will just work if llm can access the model you specify.

2. Provide an environment variable (best for containers/CI)

• Default env var: OPENAI_API_KEY
• You can change which env var to read via metadata.json under this plugin's config:

{
  "plugins": {
    "datasette-llm-sql-writer": {
      "model": "anthropic/claude-sonnet-4-0",
      "env_api_key_var": "ANTHROPIC_API_KEY"
    }
  }
}

• No configuration file is needed to use the default model, gpt-5-mini.

Quick check:

export OPENAI_API_KEY="sk-..."
datasette path/to/your.db -p 8001

If you see authentication errors, visit the diagnostics section of this page.

Model selection

The model id is resolved with this precedence:

1. metadata.json plugin config: plugins.datasette-llm-sql-writer.model
2. Environment variable: LLM_SQL_WRITER_MODEL
3. Default: gpt-5-mini (OpenAI)

Examples:

{
  "plugins": {
    "datasette-llm-sql-writer": {
      "model": "gpt-5-mini"
    }
  }
}

or

export LLM_SQL_WRITER_MODEL=gpt-5-mini

Configuration

• You need the llm package configured with an API key for your chosen provider. Install the model/provider you want to use (e.g., OpenAI) per the llm docs.
• The default model id can be set in metadata.json as shown above; otherwise the plugin uses a placeholder and will error if the model does not exist in your llm setup.

Front‑end state and persistence

The panel persists small UI state and chat history in localStorage, scoped per database:

• State key: llm_sql_writer:state:v1:db:{db}
  • panelCollapsed (bool): whether the panel is collapsed.
  • lastPrompt (str): last prompt used to generate SQL.
  • lastSql (str): last SQL returned by the LLM.
  • lastRanSql (str): last SQL that was executed.
• History key: llm_sql_writer:history:v1:db:{db}
  • The chat history associated with that database (trimmed to a bounded length).
• Changes propagate across tabs via the storage event.

No secrets are stored in localStorage—API keys should be configured with the llm package on the server side.

Development

To set up this plugin locally, clone the repo and use uv to manage the environment and dependencies:

git clone https://github.com/etjones/datasette-llm-sql-writer
cd datasette-llm-sql-writer
uv venv
source .venv/bin/activate
uv sync --all-extras # installs runtime and test dependencies from pyproject.toml

Run the tests:

pytest -q

Launch Datasette against an example DB to try the panel:

datasette path/to/your.db -p 8001
# Visit http://127.0.0.1:8001/{db}/{table}

How it works

• Backend route: /-/llm-sql-writer/generate accepts {db, table, prompt, history} and returns {sql}.
• The LLM prompt includes the schema context (table/column names) and optional chat history.
• Returned SQL is validated to be read‑only before being emitted to the UI.
• On table pages the panel uses the Datasette 1.x JavaScript plugin panel API; on non‑table pages it is inserted under the main header.

Diagnostics

Visit http://localhost:8001/-/llm-sql-writer/diagnostics to quickly check whether:

• llm is installed
• The resolved model_id is available
• Your environment variable for the API key is present

The endpoint returns JSON with helpful hints and links to docs.

FAQ

• Can I put my API key in metadata.json?

  Nope. Keep secrets in llm's key store or environment variables.

• I get an error about unknown or unavailable model

  Install the appropriate llm provider plugin and confirm the model/alias exists. For Claude:

  uv add llm-anthropic
  llm keys set anthropic
  

  See llm docs for more info on provider plugins.

• I set a key but it still fails

  Ensure Datasette is running as the same user and virtual environment where you configured llm. If you use an env var, make sure it is set in the same process environment as the Datasette server.

• Local usage notes and privacy

  This plugin is commonly used locally. Be mindful that prompts and schema context are sent to the model provider. Use provider-side controls and review your data handling policies if you work with sensitive data.