100 lines
2.9 KiB
TypeScript
100 lines
2.9 KiB
TypeScript
import * as core from '@actions/core'
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import ModelClient, { isUnexpected } from '@azure-rest/ai-inference'
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import { AzureKeyCredential } from '@azure/core-auth'
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import * as fs from 'fs'
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import * as os from 'os'
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import * as path from 'path'
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const RESPONSE_FILE = 'modelResponse.txt'
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/**
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* The main function for the action.
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*
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* @returns Resolves when the action is complete.
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*/
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export async function run(): Promise<void> {
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try {
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const promptFile: string = core.getInput('prompt-file')
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const promptString: string = core.getInput('prompt')
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let prompt: string
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if (promptFile !== undefined && promptFile !== '') {
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if (!fs.existsSync(promptFile)) {
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throw new Error(`Prompt file not found: ${promptFile}`)
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}
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prompt = fs.readFileSync(promptFile, 'utf-8')
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} else if (promptString !== undefined && promptString !== '') {
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prompt = promptString
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} else {
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throw new Error('prompt is not set')
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}
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const systemPrompt: string = core.getInput('system-prompt')
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const modelName: string = core.getInput('model')
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const maxTokens: number = parseInt(core.getInput('max-tokens'), 10)
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const token = core.getInput('token') || process.env['GITHUB_TOKEN']
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if (token === undefined) {
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throw new Error('GITHUB_TOKEN is not set')
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}
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const endpoint = core.getInput('endpoint')
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const client = ModelClient(endpoint, new AzureKeyCredential(token), {
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userAgentOptions: { userAgentPrefix: 'github-actions-ai-inference' }
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})
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const response = await client.path('/chat/completions').post({
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body: {
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messages: [
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{
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role: 'system',
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content: systemPrompt
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},
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{ role: 'user', content: prompt }
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],
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max_tokens: maxTokens,
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model: modelName
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}
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})
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if (isUnexpected(response)) {
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if (response.body.error) {
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throw response.body.error
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}
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throw new Error(
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'An error occurred while fetching the response (' +
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response.status +
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'): ' +
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response.body
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)
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}
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const modelResponse: string | null =
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response.body.choices[0].message.content
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// Set outputs for other workflow steps to use
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core.setOutput('response', modelResponse || '')
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// Save the response to a file in case the response overflow the output limit
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const responseFilePath = path.join(tempDir(), RESPONSE_FILE)
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core.setOutput('response-file', responseFilePath)
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if (modelResponse && modelResponse !== '') {
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fs.writeFileSync(responseFilePath, modelResponse, 'utf-8')
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}
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} catch (error) {
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// Fail the workflow run if an error occurs
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if (error instanceof Error) {
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core.setFailed(error.message)
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} else {
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core.setFailed('An unexpected error occurred')
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}
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}
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}
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function tempDir(): string {
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const tempDirectory = process.env['RUNNER_TEMP'] || os.tmpdir()
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return tempDirectory
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}
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