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feat: Adds in prompt.yml support
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‎examples/ai/generate-text.ts‎

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@@ -2,18 +2,14 @@ import {githubModels} from '@github/models'
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import {generateText} from 'ai'
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import 'dotenv/config'
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async function main() {
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const result = await generateText({
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model: githubModels('openai/gpt-4o'),
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prompt: 'I want 100 words on how to inflate a balloon.',
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})
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const result = await generateText({
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model: githubModels('openai/gpt-4o'),
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prompt: 'I want 100 words on how to inflate a balloon.',
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})
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console.log('Text:')
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console.log(result.text)
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console.log()
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console.log('Text:')
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console.log(result.text)
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console.log()
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console.log('Token usage:', result.usage)
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console.log('Finish reason:', result.finishReason)
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}
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main().catch(console.error)
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console.log('Token usage:', result.usage)
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console.log('Finish reason:', result.finishReason)

‎examples/ai/package.json‎

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@@ -7,8 +7,9 @@
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"node": ">=24"
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},
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"dependencies": {
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"@github/models": "file:../../",
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"ai": "beta",
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"dotenv": "^17",
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"@github/models": "file:../../"
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"confbox": "^0.2",
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"dotenv": "^17"
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}
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}

‎examples/ai/prompt.ts‎

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import {readFile} from 'node:fs/promises'
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import {parseYAML} from 'confbox/yaml'
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import {createObjectPrompt} from '@github/models/prompt'
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import {generateObject} from 'ai'
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import 'dotenv/config'
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const promptFile = parseYAML(await readFile('./teacher.prompt.yml', 'utf8'))
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const prompt = createObjectPrompt(promptFile)
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const result = await generateObject(
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prompt({
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subject: 'balloon popping',
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}),
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)
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console.log('Object:')
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console.log(result.object)
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console.log()
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console.log('Token usage:', result.usage)
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console.log('Finish reason:', result.finishReason)

‎examples/ai/teacher.prompt.yml‎

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name: teacher
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model: openai/gpt-4.1
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responseFormat: json_schema
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jsonSchema: |-
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{
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"name": "explanation",
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"strict": true,
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"schema": {
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"type": "object",
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"properties": {
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"lesson": {
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"type": "string",
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"description": "The lesson about the subject"
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}
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},
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"additionalProperties": false,
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"required": [
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"lesson"
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]
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}
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}
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messages:
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- role: system
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content: You're an elementary school teacher who loves to make learning fun.
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- role: user
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content: Please explain {{subject}} in as little as 5 sentences and give it to be as json.

‎package-lock.json‎

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‎package.json‎

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"types": "./dist/index.d.ts",
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"default": "./dist/index.js"
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},
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"./prompt": {
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"types": "./dist/prompt.d.ts",
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"default": "./dist/prompt.js"
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},
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"./package.json": "./package.json"
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},
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"scripts": {
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"dependencies": {
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"@ai-sdk/openai-compatible": "beta",
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"@ai-sdk/provider": "beta",
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"@ai-sdk/provider-utils": "beta"
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"@ai-sdk/provider-utils": "beta",
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"templite": "^1.2.0",
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"tiny-invariant": "^1.3.3",
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"zod": "^3 || ^4"
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},
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"devDependencies": {
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"@github/prettier-config": "0.0.6",
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"@types/node": "^24",
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"dotenv": "^17.2.0",
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"eslint": "^9",
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"eslint-plugin-github": "^6",
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"eslint-plugin-simple-import-sort": "12.1.1",
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"prettier": "^3",
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"tsup": "^8.3.0",
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"typescript": "^5.7.2",
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"vitest": "^3",
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"dotenv": "^17.2.0"
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"vitest": "^3"
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},
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"engines": {
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"node": ">=20"

‎readme.md‎

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@@ -11,72 +11,167 @@ The GitHub Models provider is available in the `@github/models` NPM package. You
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npm i @github/models
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```
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## Provider Instance
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## Quick Start
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To get started, you'll need a [GitHub PAT (personal access token)](https://github.com/settings/tokens).
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> [!TIP]
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> If you want to use GitHub Models beyond the [free usage](https://gh.io/models-rate-limits) included in your account, you can choose to opt in to paid usage. For more information, visit the [pricing page](https://gh.io/github-models-pricing).
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The GitHub Models provider instance is used to create model instances that call the [GitHub Models Inference API](https://docs.github.com/en/rest/models/inference?apiVersion=2022-11-28#run-an-inference-request).
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Please find all the available models on the [models catalog](https://github.com/marketplace?type=models).
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```ts
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import {githubModels} from '@github/models'
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```
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#### Example
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```ts
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import {githubModels} from '@github/models'
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import {generateText} from 'ai'
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const {text} = await generateText({
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const result = await generateText({
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model: githubModels('meta/meta-llama-3.1-8b-instruct'),
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prompt: 'I want 100 words on how to inflate a balloon.',
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prompt: 'Write a haiku about programming.',
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})
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console.log(result.text)
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```
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> [!TIP]
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> GitHub Models includes [free usage](https://gh.io/models-rate-limits) for all accounts. For higher usage limits, you can opt into [paid usage](https://gh.io/github-models-pricing).
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If you need a customized setup, you can import `createGithubModels` from `@github/models` and create a provider instance with your settings:
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```ts
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import {createGithubModels} from '@github/models'
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const githubModels = createGithubModels({
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org: 'my-org',
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org: 'my-organization',
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apiKey: process.env.GITHUB_TOKEN,
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baseURL: 'https://models.github.ai/inference',
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})
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```
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You can use the following optional settings to customize the GitHub Models provider instance:
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### Configuration Options
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- **org** _string_
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- **apiKey** _string_
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Your GitHub [Personal Access Token](https://github.com/settings/tokens) or [Fine-Grained Token](https://github.com/settings/personal-access-tokens) with `read:models` scope.
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Defaults to the `GITHUB_TOKEN` environment variable.
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Set the organization that should be used to attribute inference.
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- **org** _string_
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Organization to attribute API usage to (optional).
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- **baseURL** _string_
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Custom API endpoint URL.
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Defaults to `https://models.github.ai/inference`.
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Use a different URL prefix for API calls. The default prefix is `https://models.github.ai/inference`.
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- **headers** _Record<string, string>_
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Additional headers to include with requests.
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- **apiKey** _string_
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- **fetch** _(input: RequestInfo, init?: RequestInit) => Promise<Response>_
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Custom [fetch](https://developer.mozilla.org/en-US/docs/Web/API/fetch) implementation.
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Defaults to the global `fetch` function.
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You can use it as a middleware to intercept requests,
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or to provide a custom fetch implementation for e.g. testing.
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API key that is being sent using the `Authorization` header. Either a
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GitHub PAT [_(Personal Access Token)_](https://github.com/settings/tokens), or FGT [_(Fine-Grained Token)_](https://github.com/settings/personal-access-tokens) with the `read:models` scope.
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It defaults to the `GITHUB_TOKEN` environment variable.
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## Prompt Management
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- **headers** _Record&lt;string,string&gt;_
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The `@github/models/prompt` sub-module provides a powerful way to integrate with AI SDK methods like `generateText` and `generateObject` using your `prompt.yml` files.
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Prompt YAML files are designed to create reusable artifacts that integrate with GitHub's suite of AI tools. Check out the [Models tab](https://github.com/github/models-ai-sdk/models).
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Custom headers to include in the requests.
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### Example
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- **fetch** _(input: RequestInfo, init?: RequestInit) => Promise&lt;Response&gt;_
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Create a `.prompt.yml` file:
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Custom [fetch](https://developer.mozilla.org/en-US/docs/Web/API/fetch) implementation.
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Defaults to the global `fetch` function.
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You can use it as a middleware to intercept requests,
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or to provide a custom fetch implementation for e.g. testing.
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```yaml
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name: teacher
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description: An elementary school teacher who explains concepts simply
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model: openai/gpt-4o
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modelParameters:
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temperature: 0.7
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maxTokens: 500
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messages:
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- role: system
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content: You're an elementary school teacher who loves making learning fun.
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- role: user
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content: Explain {{subject}} in exactly {{sentences}} sentences for a 10-year-old.
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```
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Use `createTextPrompt` for text-based responses:
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```ts
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import {readFile} from 'node:fs/promises'
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import {parseYAML} from 'confbox/yaml'
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import {createTextPrompt} from '@github/models/prompt'
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import {generateText} from 'ai'
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const config = parseYAML(await readFile('./teacher.prompt.yml', 'utf8'))
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const prompt = createTextPrompt(config)
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const result = await generateText(
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prompt({
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subject: 'photosynthesis',
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sentences: '5',
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}),
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)
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console.log(result.text)
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```
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<details><summary>Structured Generation</summary>
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Use `createObjectPrompt` for JSON responses with schema validation:
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```yaml
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name: recipe-generator
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model: openai/gpt-4o
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responseFormat: json_schema
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jsonSchema: |-
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{
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"name": "recipe",
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"strict": true,
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"schema": {
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"type": "object",
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"properties": {
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"title": {"type": "string"},
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"ingredients": {
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"type": "array",
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"items": {"type": "string"}
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},
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"instructions": {
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"type": "array",
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"items": {"type": "string"}
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}
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},
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"required": ["title", "ingredients", "instructions"],
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"additionalProperties": false
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}
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}
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messages:
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- role: user
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content: Create a recipe for {{dish}} that serves {{servings}} people.
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```
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```ts
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import {createObjectPrompt} from '@github/models/prompt'
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import {generateObject} from 'ai'
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const config = parseYAML(await readFile('./recipe.prompt.yml', 'utf8'))
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const prompt = createObjectPrompt(config)
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const result = await generateObject(
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prompt({
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dish: 'chocolate chip cookies',
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servings: '4',
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}),
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)
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console.log(result.object.title)
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console.log(result.object.ingredients)
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```
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</details>
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## API Reference
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The GitHub Models provider uses the [GitHub Models Inference API](https://docs.github.com/en/rest/models/inference?apiVersion=2022-11-28#run-an-inference-request).
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## License
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Distributed under the MIT license. See [LICENSE](./license.txt) for details.
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Distributed under the MIT License. See [LICENSE](./license.txt) for more information.
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<!-- LINKS -->
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