使用 Dotprompt 管理提示

---
model: googleai/gemini-1.5-flash
config:
  temperature: 0.9
input:
  schema:
    location: string
    style?: string
    name?: string
  default:
    location: a restaurant
---

You are the world's most welcoming AI assistant and are currently working at {{location}}.

Greet a guest{{#if name}} named {{name}}{{/if}}{{#if style}} in the style of {{style}}{{/if}}.

your-project/
├── lib/
├── node_modules/
├── prompts/
│   └── hello.prompt
├── src/
├── package-lock.json
├── package.json
└── tsconfig.json

const ai = genkit({
  promptDir: './llm_prompts',
  // (Other settings...)
});

---
model: vertexai/gemini-1.5-flash
---
You are the world's most welcoming AI assistant. Greet the user and offer your assistance.

import { genkit } from 'genkit';

// Import the model plugins you want to use.
import { googleAI } from '@genkit-ai/googleai';

const ai = genkit({
  // Initialize and configure the model plugins.
  plugins: [
    googleAI({
      apiKey: 'your-api-key', // Or (preferred): export GOOGLE_GENAI_API_KEY=...
    }),
  ],
});

genkit start -- tsx --watch src/your-code.ts

import { genkit } from 'genkit';

// Import the model plugins you want to use.
import { googleAI } from '@genkit-ai/googleai';

const ai = genkit({
  // Initialize and configure the model plugins.
  plugins: [
    googleAI({
      apiKey: 'your-api-key', // Or (preferred): export GOOGLE_GENAI_API_KEY=...
    }),
  ],
});

const helloPrompt = ai.prompt('hello');

const response = await helloPrompt();

// Alternatively, use destructuring assignments to get only the properties
// you're interested in:
const { text } = await helloPrompt();

const response2 = await helloPrompt(
  // Prompt input:
  { name: 'Ted' },

  // Generation options:
  {
    config: {
      temperature: 0.4,
    },
  }
);

genkit start -- tsx --watch src/your-code.ts

---
model: googleai/gemini-1.5-flash
config:
  temperature: 1.4
  topK: 50
  topP: 0.4
  maxOutputTokens: 400
  stopSequences:
    -   "<end>"
    -   "<fin>"
---

const response3 = await helloPrompt(
  {},
  {
    config: {
      temperature: 1.4,
      topK: 50,
      topP: 0.4,
      maxOutputTokens: 400,
      stopSequences: ['<end>', '<fin>'],
    },
  }
);

---
model: googleai/gemini-1.5-flash
input:
  schema:
    theme?: string
  default:
    theme: "pirate"
output:
  schema:
    dishname: string
    description: string
    calories: integer
    allergens(array): string
---
Invent a menu item for a {{theme}} themed restaurant.

const menuPrompt = ai.prompt('menu');
const { data } = await menuPrompt({ theme: 'medieval' });

const dishName = data['dishname'];
const description = data['description'];

schema:
  title: string # string, number, and boolean types are defined like this
  subtitle?: string # optional fields are marked with a `?`
  draft?: boolean, true when in draft state
  status?(enum, approval status): [PENDING, APPROVED]
  date: string, the date of publication e.g. '2024-04-09' # descriptions follow a comma
  tags(array, relevant tags for article): string # arrays are denoted via parentheses
  authors(array):
    name: string
    email?: string
  metadata?(object): # objects are also denoted via parentheses
    updatedAt?: string, ISO timestamp of last update
    approvedBy?: integer, id of approver
  extra?: any, arbitrary extra data
  (*): string, wildcard field

interface Article {
  title: string;
  subtitle?: string | null;
  /** true when in draft state */
  draft?: boolean | null;
  /** approval status */
  status?: 'PENDING' | 'APPROVED' | null;
  /** the date of publication e.g. '2024-04-09' */
  date: string;
  /** relevant tags for article */
  tags: string[];
  authors: {
    name: string;
    email?: string | null;
  }[];
  metadata?: {
    /** ISO timestamp of last update */
    updatedAt?: string | null;
    /** id of approver */
    approvedBy?: number | null;
  } | null;
  /** arbitrary extra data */
  extra?: any;
  /** wildcard field */

}

output:
  schema:
    type: object
    properties:
      field1:
        type: number
        minimum: 20

import { z } from 'genkit';

const MenuItemSchema = ai.defineSchema(
  'MenuItemSchema',
  z.object({
    dishname: z.string(),
    description: z.string(),
    calories: z.coerce.number(),
    allergens: z.array(z.string()),
  })
);

---
model: googleai/gemini-1.5-flash-latest
output:
  schema: MenuItemSchema
---

const menuPrompt = ai.prompt<
  z.ZodTypeAny, // Input schema
  typeof MenuItemSchema, // Output schema
  z.ZodTypeAny // Custom options schema
>('menu');
const { data } = await menuPrompt({ theme: 'medieval' });

// Now data is strongly typed as MenuItemSchema:
const dishName = data?.dishname;
const description = data?.description;

---
model: googleai/gemini-1.5-flash
config:
  temperature: 1.4
  topK: 50
  topP: 0.4
  maxOutputTokens: 400
  stopSequences:
    -   "<end>"
    -   "<fin>"
---

const menuPrompt = ai.prompt('menu');
const { data } = await menuPrompt({ theme: 'medieval' });

---
model: googleai/gemini-1.5-flash
input:
  schema:
    theme?: string
---
Invent a menu item for a {{#if theme}}{{theme}} themed{{/if}} restaurant.

---
model: vertexai/gemini-1.5-flash
input:
  schema:
    userQuestion: string
---
{{role "system"}}
You are a helpful AI assistant that really loves to talk about food. Try to work
food items into all of your conversations.
{{role "user"}}
{{userQuestion}}

---
model: vertexai/gemini-1.5-flash
input:
  schema:
    photoUrl: string
---
Describe this image in a detailed paragraph:

{{media url=photoUrl}}

const multimodalPrompt = ai.prompt('multimodal');
const { text } = await multimodalPrompt({
  photoUrl: 'https://example.com/photo.jpg',
});

You should speak like a {{#if style}}{{style}}{{else}}helpful assistant.{{/else}}.

---
model: googleai/gemini-1.5-flash
input:
  schema:
    name: string
    style?: string
---
{{ role "system" }}
{{>personality style=style}}

{{ role "user" }}
Give the user a friendly greeting.

User's Name: {{name}}

- {{name}} ({{country}})

---
model: googleai/gemini-1.5-flash-latest
input:
  schema:
    destinations(array):
      name: string
      country: string
---
Help the user decide between these vacation destinations:

{{#each destinations}}
{{>destination this}}
{{/each}}

ai.definePartial(
  'personality',
  'Talk like a {{#if style}}{{style}}{{else}}helpful assistant{{/if}}.'
);

ai.defineHelper('shout', (text: string) => text.toUpperCase());

---
model: googleai/gemini-1.5-flash
input:
  schema:
    name: string
---

HELLO, {{shout name}}!!!

const myPrompt = ai.prompt('my_prompt', { variant: 'gemini15pro' });

const myPrompt = ai.definePrompt(
  {
    name: 'myPrompt',
    model: 'googleai/gemini-1.5-flash',
    input: {
      schema: z.object({
        name: z.string(),
      }),
    },
  },
  'Hello, {{name}}. How are you today?'
);

const myPrompt = ai.definePrompt(
  {
    name: 'myPrompt',
    model: 'googleai/gemini-1.5-flash',
    input: {
      schema: z.object({
        name: z.string(),
      }),
    },
  },
  async (input): Promise<GenerateRequest> => {
    return {
      messages: [
        {
          role: 'user',
          content: [{ text: `Hello, ${input.name}. How are you today?` }],
        },
      ],
    };
  }
);