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Copy src from ai-inference
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‎src/helpers.ts‎

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import * as core from '@actions/core'
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import { GetChatCompletionsDefaultResponse } from '@azure-rest/ai-inference'
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import * as fs from 'fs'
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import { PromptConfig } from './prompt.js'
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import { InferenceRequest } from './inference.js'
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/**
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* Helper function to load content from a file or use fallback input
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* @param filePathInput - Input name for the file path
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* @param contentInput - Input name for the direct content
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* @param defaultValue - Default value to use if neither file nor content is provided
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* @returns The loaded content
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*/
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export function loadContentFromFileOrInput(
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filePathInput: string,
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contentInput: string,
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defaultValue?: string
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): string {
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const filePath = core.getInput(filePathInput)
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const contentString = core.getInput(contentInput)
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if (filePath !== undefined && filePath !== '') {
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if (!fs.existsSync(filePath)) {
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throw new Error(`File for ${filePathInput} was not found: ${filePath}`)
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}
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return fs.readFileSync(filePath, 'utf-8')
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} else if (contentString !== undefined && contentString !== '') {
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return contentString
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} else if (defaultValue !== undefined) {
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return defaultValue
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} else {
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throw new Error(`Neither ${filePathInput} nor ${contentInput} was set`)
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}
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}
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/**
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* Helper function to handle unexpected responses from AI service
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* @param response - The response object from the AI service
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* @throws Error with appropriate error message based on response content
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*/
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export function handleUnexpectedResponse(
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response: GetChatCompletionsDefaultResponse
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): never {
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// Extract x-ms-error-code from headers if available
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const errorCode = response.headers['x-ms-error-code']
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const errorCodeMsg = errorCode ? ` (error code: ${errorCode})` : ''
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// Check if response body exists and contains error details
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if (response.body && response.body.error) {
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throw response.body.error
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}
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// Handle case where response body is missing
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if (!response.body) {
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throw new Error(
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`Failed to get response from AI service (status: ${response.status})${errorCodeMsg}. ` +
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'Please check network connection and endpoint configuration.'
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)
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}
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// Handle other error cases
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throw new Error(
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`AI service returned error response (status: ${response.status})${errorCodeMsg}: ` +
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(typeof response.body === 'string'
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? response.body
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: JSON.stringify(response.body))
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)
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}
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/**
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* Build messages array from either prompt config or legacy format
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*/
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export function buildMessages(
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promptConfig?: PromptConfig,
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systemPrompt?: string,
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prompt?: string
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): Array<{ role: string; content: string }> {
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if (promptConfig?.messages && promptConfig.messages.length > 0) {
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// Use new message format
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return promptConfig.messages.map((msg) => ({
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role: msg.role,
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content: msg.content
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}))
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} else {
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// Use legacy format
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return [
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{
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role: 'system',
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content: systemPrompt || 'You are a helpful assistant'
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},
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{ role: 'user', content: prompt || '' }
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]
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}
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}
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/**
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* Build response format object for API from prompt config
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*/
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export function buildResponseFormat(
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promptConfig?: PromptConfig
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): { type: 'json_schema'; json_schema: unknown } | undefined {
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if (
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promptConfig?.responseFormat === 'json_schema' &&
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promptConfig.jsonSchema
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) {
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try {
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const schema = JSON.parse(promptConfig.jsonSchema)
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return {
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type: 'json_schema',
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json_schema: schema
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}
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} catch (error) {
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throw new Error(
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`Invalid JSON schema: ${error instanceof Error ? error.message : 'Unknown error'}`
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)
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}
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}
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return undefined
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}
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/**
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* Build complete InferenceRequest from prompt config and inputs
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*/
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export function buildInferenceRequest(
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promptConfig: PromptConfig | undefined,
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systemPrompt: string | undefined,
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prompt: string | undefined,
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modelName: string,
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maxTokens: number,
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endpoint: string,
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token: string
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): InferenceRequest {
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const messages = buildMessages(promptConfig, systemPrompt, prompt)
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const responseFormat = buildResponseFormat(promptConfig)
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return {
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messages,
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modelName,
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maxTokens,
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endpoint,
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token,
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responseFormat
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}
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}

‎src/index.ts‎

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/**
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* The entrypoint for the action. This file simply imports and runs the action's
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* main logic.
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*/
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import { run } from './main.js'
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/* istanbul ignore next */
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run()

‎src/inference.ts‎

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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 { GitHubMCPClient, executeToolCalls, MCPTool, ToolCall } from './mcp.js'
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import { handleUnexpectedResponse } from './helpers.js'
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interface ChatMessage {
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role: string
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content: string | null
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tool_calls?: ToolCall[]
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}
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interface ChatCompletionsRequestBody {
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messages: ChatMessage[]
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max_tokens: number
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model: string
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response_format?: { type: 'json_schema'; json_schema: unknown }
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tools?: MCPTool[]
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}
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export interface InferenceRequest {
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messages: Array<{ role: string; content: string }>
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modelName: string
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maxTokens: number
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endpoint: string
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token: string
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responseFormat?: { type: 'json_schema'; json_schema: unknown } // Processed response format for the API
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}
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export interface InferenceResponse {
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content: string | null
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toolCalls?: Array<{
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id: string
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type: string
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function: {
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name: string
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arguments: string
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}
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}>
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}
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/**
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* Simple one-shot inference without tools
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*/
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export async function simpleInference(
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request: InferenceRequest
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): Promise<string | null> {
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core.info('Running simple inference without tools')
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const client = ModelClient(
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request.endpoint,
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new AzureKeyCredential(request.token),
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{
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userAgentOptions: { userAgentPrefix: 'github-actions-ai-inference' }
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}
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)
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const requestBody: ChatCompletionsRequestBody = {
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messages: request.messages,
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max_tokens: request.maxTokens,
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model: request.modelName
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}
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// Add response format if specified
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if (request.responseFormat) {
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requestBody.response_format = request.responseFormat
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}
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const response = await client.path('/chat/completions').post({
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body: requestBody
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})
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if (isUnexpected(response)) {
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handleUnexpectedResponse(response)
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}
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const modelResponse = response.body.choices[0].message.content
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core.info(`Model response: ${modelResponse || 'No response content'}`)
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return modelResponse
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}
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/**
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* GitHub MCP-enabled inference with tool execution loop
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*/
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export async function mcpInference(
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request: InferenceRequest,
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githubMcpClient: GitHubMCPClient
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): Promise<string | null> {
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core.info('Running GitHub MCP inference with tools')
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const client = ModelClient(
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request.endpoint,
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new AzureKeyCredential(request.token),
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{
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userAgentOptions: { userAgentPrefix: 'github-actions-ai-inference' }
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}
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)
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// Start with the pre-processed messages
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const messages: ChatMessage[] = [...request.messages]
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let iterationCount = 0
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const maxIterations = 5 // Prevent infinite loops
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while (iterationCount < maxIterations) {
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iterationCount++
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core.info(`MCP inference iteration ${iterationCount}`)
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const requestBody: ChatCompletionsRequestBody = {
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messages: messages,
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max_tokens: request.maxTokens,
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model: request.modelName,
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tools: githubMcpClient.tools
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}
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// Add response format if specified (only on first iteration to avoid conflicts)
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if (iterationCount === 1 && request.responseFormat) {
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requestBody.response_format = request.responseFormat
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}
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const response = await client.path('/chat/completions').post({
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body: requestBody
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})
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if (isUnexpected(response)) {
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handleUnexpectedResponse(response)
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}
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const assistantMessage = response.body.choices[0].message
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const modelResponse = assistantMessage.content
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const toolCalls = assistantMessage.tool_calls
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core.info(`Model response: ${modelResponse || 'No response content'}`)
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messages.push({
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role: 'assistant',
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content: modelResponse || '',
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...(toolCalls && { tool_calls: toolCalls })
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})
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if (!toolCalls || toolCalls.length === 0) {
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core.info('No tool calls requested, ending GitHub MCP inference loop')
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return modelResponse
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}
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core.info(`Model requested ${toolCalls.length} tool calls`)
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// Execute all tool calls via GitHub MCP
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const toolResults = await executeToolCalls(
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githubMcpClient.client,
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toolCalls
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)
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// Add tool results to the conversation
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messages.push(...toolResults)
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core.info('Tool results added, continuing conversation...')
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}
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core.warning(
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`GitHub MCP inference loop exceeded maximum iterations (${maxIterations})`
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)
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// Return the last assistant message content
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const lastAssistantMessage = messages
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.slice()
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.reverse()
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.find((msg) => msg.role === 'assistant')
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return lastAssistantMessage?.content || null
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}

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