Dotprompt comes to Genkit Dart: Richer prompt templating and management
Genkit | Blog ·
Genkit Dart 0.14.0 adds Dotprompt support, letting you manage prompts, models, and parameters as version-controlled config in .prompt files, decoupled from your app code and tunable in the Developer UI.
Prompt engineering is an iterative process. The model, its parameters, and the prompt text all shape the output together, and getting them right takes many rounds of tuning. As a prompt grows in complexity, it helps to treat that whole bundle as an artifact you can edit, version, and test on its own. That is where Dotrpompt can help!
Genkit Dart 0.14.0 brings Dotprompt to Dart and Flutter developers. Simple prompts are often fine inline, and Genkit still supports that. When a prompt does more work, Dotprompt lets you move it into a .prompt file that lives alongside your app. You define the prompt there, iterate on it in the Developer UI, and run it from Dart by name.
A .prompt file is YAML front matter, holding the model and its config, followed by a Handlebars template. Drop this into your prompts/ directory as greeting.prompt :
--- model : googleai/gemini-flash-latest config : temperature : 0.7 input : schema : name : string, the person to greet style : string, the greeting style (e.g. cheerful, casual, pirate) --- {{ role " system " }} You are a friendly greeter. Greet the user warmly. {{ role " user " }} Say hello to {{ name }} in a {{ style }} way. Then load and run it from your app. By default Genkit looks for prompts in ./prompts :
import 'package:genkit/genkit.dart' ; import 'package:genkit_google_genai/genkit_google_genai.dart' ; void main () async { final ai = Genkit (plugins : [ googleAI ()]); final greeting = await ai. prompt ( 'greeting' ); final response = await greeting ({ 'name' : 'Ada' , 'style' : 'cheerful' }); print (response.text); } For a prompt like this, none of the prose lives in your code. The model and temperature sit right next to the text they shape, and your application asks for the prompt by name and stays out of the tuning loop.
Not every prompt needs one. A single-line system prompt can stay in your Dart. Reach for a .prompt file once a prompt does enough work to earn the benefits below, which usually means complex or highly dynamic templating, or text that a separate subject-matter expert needs to review and edit.
This release brings the full Dotprompt feature set to Dart:
Prefer to keep prompts in code but still want the templating benefits? Define a strongly-typed input schema with schemantic :
@Schema () abstract class $JokeInput { @Field (description : 'The joke topic (e.g. programming, cats, cooking)' ) String get topic; @Field (description : 'The joke style (e.g. punny, dry, dad)' ) String get style; } Then definePrompt() takes the same metadata as a .prompt file with a Handlebars template and the generated schema:
final jokePrompt = ai. definePrompt ( name : 'joke' , model : modelRef ( 'googleai/gemini-flash-latest' ), config : { 'temperature' : 0.9 }, inputSchema : JokeInput .$schema, system : 'You are a witty comedian. Keep jokes family-friendly.' , prompt : 'Tell me a {{style}} joke about {{topic}}.' , ); final response = await jokePrompt ( JokeInput (topic : 'cats' , style : 'punny' )); print (response.text); And when you need to build messages programmatically, defineCustomPrompt() lets you return a GenerateActionOptions describing the request yourself.
Every .prompt file loads straight into the Genkit Developer UI . There you can edit parameters, run them against live input, and compare variants side by side in traces.
Start the UI alongside your app:
genkit start -- dart run Get started Update to Genkit Dart 0.14.0 and start moving your prompts into .prompt files today.
We can’t wait to see what you build. Happy prompting! 🚀