index.ts•2.66 kB
/**
* Copyright 2024 Google LLC
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
import { googleAI } from '@genkit-ai/googleai';
import { genkit, z } from 'genkit';
const ai = genkit({
plugins: [googleAI()],
});
/*
title: string, recipe title
ingredients(array):
name: string
quantity: string
steps(array, the steps required to complete the recipe): string
*/
const RecipeSchema = ai.defineSchema(
'Recipe',
z.object({
title: z.string().describe('recipe title'),
ingredients: z.array(z.object({ name: z.string(), quantity: z.string() })),
steps: z
.array(z.string())
.describe('the steps required to complete the recipe'),
})
);
// This example demonstrates using prompt files in a flow
// Load the prompt file during initialization.
// If it fails, due to the prompt file being invalid, the process will crash,
// instead of us getting a more mysterious failure later when the flow runs.
ai.defineHelper('list', (data: any) => {
if (!Array.isArray(data)) {
return '';
}
return data.map((item) => `- ${item}`).join('\n');
});
ai.defineFlow(
{
name: 'chefFlow',
inputSchema: z.object({
food: z.string(),
}),
outputSchema: RecipeSchema,
},
async (input) =>
(await ai.prompt<any, typeof RecipeSchema>('recipe')(input)).output!
);
ai.defineFlow(
{
name: 'robotChefFlow',
inputSchema: z.object({
food: z.string(),
}),
outputSchema: z.any(),
},
async (input) =>
(await ai.prompt('recipe', { variant: 'robot' })(input)).output
);
// A variation that supports streaming, optionally
ai.defineFlow(
{
name: 'tellStory',
inputSchema: z.object({
subject: z.string(),
personality: z.string().optional(),
}),
outputSchema: z.string(),
streamSchema: z.string(),
},
async ({ subject, personality }, { sendChunk }) => {
const storyPrompt = ai.prompt('story');
const { response, stream } = storyPrompt.stream({
subject,
personality,
});
for await (const chunk of stream) {
sendChunk(chunk.content[0]?.text!);
}
return (await response).text;
}
);