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Sync auto-advance-ball.yml from .github repo
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‎.github/workflows/auto-advance-ball.yml‎

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name: "Automation: Advance the Ball (6h)"
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on:
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schedule:
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- cron: "0 */6 * * *"
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workflow_dispatch:
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inputs:
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llm_provider:
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description: "LLM provider"
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required: false
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default: ""
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type: choice
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options:
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- ""
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- openai
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- gemini
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- anthropic
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llm_model:
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description: "Model name (provider-specific)"
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required: false
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default: ""
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type: string
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permissions:
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contents: read
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issues: write
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concurrency:
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group: advance-ball-${{ github.repository }}
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cancel-in-progress: true
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jobs:
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advance:
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runs-on: ubuntu-latest
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timeout-minutes: 30
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steps:
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- name: Checkout
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uses: actions/checkout@v4
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with:
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fetch-depth: 0
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- name: Gather repo context
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shell: bash
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run: |
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set -euo pipefail
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{
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echo "Repository: ${GITHUB_REPOSITORY}"
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echo "Run URL: ${GITHUB_SERVER_URL}/${GITHUB_REPOSITORY}/actions/runs/${GITHUB_RUN_ID}"
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echo "Ref: ${GITHUB_REF_NAME}"
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echo "SHA: ${GITHUB_SHA}"
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echo ""
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echo "Top-level files/directories:"
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ls -la
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echo ""
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echo "Recent commits (last 20):"
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git log --oneline -20 2>/dev/null || true
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echo ""
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echo "Recent changed files (best-effort):"
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git diff --name-only HEAD~20..HEAD 2>/dev/null | head -n 200 || true
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echo ""
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echo "Recent open PRs/issues pointers:"
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echo "- See: ${GITHUB_SERVER_URL}/${GITHUB_REPOSITORY}/pulls"
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echo "- See: ${GITHUB_SERVER_URL}/${GITHUB_REPOSITORY}/issues"
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} > /tmp/automation_context.txt
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if [ -f "AUTOMATION.txt" ]; then
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cat "AUTOMATION.txt" > /tmp/automation_guidance.txt
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else
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: > /tmp/automation_guidance.txt
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fi
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- name: Generate direction and write/update issue
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uses: actions/github-script@v7
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env:
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LLM_PROVIDER: ${{ (github.event_name == 'workflow_dispatch' && github.event.inputs.llm_provider) || vars.AUTOMATION_LLM_PROVIDER || vars.LLM_PROVIDER || 'openai' }}
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LLM_MODEL: ${{ (github.event_name == 'workflow_dispatch' && github.event.inputs.llm_model) || vars.AUTOMATION_LLM_MODEL || vars.LLM_MODEL || 'gpt-5.2' }}
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OPENAI_BASE_URL: ${{ vars.OPENAI_BASE_URL || 'https://api.openai.com/v1' }}
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OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
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GEMINI_API_KEY: ${{ secrets.GEMINI_API_KEY }}
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ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
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with:
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github-token: ${{ secrets.GITHUB_TOKEN }}
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script: |
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const fs = require("fs");
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const owner = context.repo.owner;
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const repo = context.repo.repo;
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const provider = (process.env.LLM_PROVIDER || "openai").trim().toLowerCase();
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const model = (process.env.LLM_MODEL || "").trim();
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if (!model) {
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core.setFailed("LLM model is required (set vars.AUTOMATION_LLM_MODEL or workflow_dispatch input llm_model).");
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return;
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}
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const contextText = fs.readFileSync("/tmp/automation_context.txt", "utf8");
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const guidanceText = fs.readFileSync("/tmp/automation_guidance.txt", "utf8").trim();
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const marker = "<!-- advance-ball -->";
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const now = new Date().toISOString();
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const defaultInstruction = [
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"Analyze this repository and propose a concrete direction.",
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"If there is no AUTOMATION.txt guidance, decide a direction and proceed by producing an actionable plan.",
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"Document your direction, assumptions, risks, and next steps.",
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"Prefer small, safe changes that increase reliability and reduce toil.",
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"Include suggested tests and a short checklist for verifying progress.",
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].join(" ");
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const systemPrompt = [
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"You are an expert software engineer and technical lead.",
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"You are producing an automation direction update for a repository.",
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"Be specific, actionable, and concise.",
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"Avoid hand-wavy advice; prefer concrete steps and file paths.",
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].join(" ");
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const userPromptParts = [];
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userPromptParts.push(`Repository: ${owner}/${repo}`);
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userPromptParts.push(`Timestamp: ${now}`);
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userPromptParts.push("");
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userPromptParts.push("Repository context:");
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userPromptParts.push(contextText);
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if (guidanceText) {
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userPromptParts.push("");
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userPromptParts.push("AUTOMATION.txt guidance (highest priority):");
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userPromptParts.push(guidanceText.length > 6000 ? guidanceText.slice(0, 6000) + "\n...(truncated)..." : guidanceText);
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} else {
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userPromptParts.push("");
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userPromptParts.push("No AUTOMATION.txt was found. Use this default instruction:");
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userPromptParts.push(defaultInstruction);
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}
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userPromptParts.push("");
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userPromptParts.push("Output format:");
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userPromptParts.push("- Summary");
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userPromptParts.push("- Direction (what and why)");
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userPromptParts.push("- Plan (next 1-3 steps)");
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userPromptParts.push("- Risks/unknowns");
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userPromptParts.push("- Suggested tests");
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const userPrompt = userPromptParts.join("\n");
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async function callOpenAI({ apiKey, baseUrl, model, messages }) {
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if (!apiKey) throw new Error("OPENAI_API_KEY is not set.");
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const url = `${baseUrl.replace(/\\/$/, "")}/chat/completions`;
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const payload = { model, messages };
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const isGpt5ish = /gpt-?5/i.test(model) || /^o\\d/i.test(model) || /^o1/i.test(model);
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if (isGpt5ish) {
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payload.max_completion_tokens = 2048;
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} else {
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payload.max_tokens = 2048;
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payload.temperature = 0.2;
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}
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const resp = await fetch(url, {
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method: "POST",
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headers: {
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"Authorization": `Bearer ${apiKey}`,
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"Content-Type": "application/json",
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},
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body: JSON.stringify(payload),
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});
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if (!resp.ok) {
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const text = await resp.text();
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throw new Error(`OpenAI API error (${resp.status}): ${text}`);
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}
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const data = await resp.json();
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const content = data?.choices?.[0]?.message?.content;
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if (!content) throw new Error("OpenAI API returned no content.");
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return content;
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}
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async function callGemini({ apiKey, model, prompt }) {
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if (!apiKey) throw new Error("GEMINI_API_KEY is not set.");
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const geminiModel = model || "gemini-1.5-pro";
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const url = `https://generativelanguage.googleapis.com/v1beta/models/${encodeURIComponent(geminiModel)}:generateContent?key=${encodeURIComponent(apiKey)}`;
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const payload = {
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contents: [{ role: "user", parts: [{ text: prompt }] }],
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generationConfig: { temperature: 0.2, maxOutputTokens: 2048 },
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};
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const resp = await fetch(url, {
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method: "POST",
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headers: { "Content-Type": "application/json" },
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body: JSON.stringify(payload),
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});
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if (!resp.ok) {
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const text = await resp.text();
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throw new Error(`Gemini API error (${resp.status}): ${text}`);
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}
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const data = await resp.json();
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const parts = data?.candidates?.[0]?.content?.parts || [];
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const text = parts.map(p => p.text || "").join("").trim();
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if (!text) throw new Error("Gemini API returned no content.");
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return text;
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}
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async function callAnthropic({ apiKey, model, system, prompt }) {
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if (!apiKey) throw new Error("ANTHROPIC_API_KEY is not set.");
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const anthropicModel = model || "claude-3-5-sonnet-latest";
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const url = "https://api.anthropic.com/v1/messages";
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const payload = {
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model: anthropicModel,
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max_tokens: 2048,
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temperature: 0.2,
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system,
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messages: [{ role: "user", content: prompt }],
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};
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const resp = await fetch(url, {
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method: "POST",
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headers: {
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"x-api-key": apiKey,
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"anthropic-version": "2023-06-01",
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"content-type": "application/json",
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},
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body: JSON.stringify(payload),
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});
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if (!resp.ok) {
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const text = await resp.text();
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throw new Error(`Anthropic API error (${resp.status}): ${text}`);
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}
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const data = await resp.json();
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const text = (data?.content || []).map(p => p.text || "").join("").trim();
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if (!text) throw new Error("Anthropic API returned no content.");
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return text;
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}
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let direction = "";
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try {
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if (provider === "openai") {
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direction = await callOpenAI({
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apiKey: process.env.OPENAI_API_KEY,
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baseUrl: process.env.OPENAI_BASE_URL,
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model,
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messages: [
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{ role: "system", content: systemPrompt },
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{ role: "user", content: userPrompt },
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],
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});
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} else if (provider === "gemini") {
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direction = await callGemini({
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apiKey: process.env.GEMINI_API_KEY,
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model,
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prompt: `${systemPrompt}\n\n${userPrompt}`,
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});
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} else if (provider === "anthropic") {
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direction = await callAnthropic({
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apiKey: process.env.ANTHROPIC_API_KEY,
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model,
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system: systemPrompt,
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prompt: userPrompt,
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});
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} else {
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throw new Error(`Unsupported provider: ${provider}`);
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}
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} catch (e) {
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core.setFailed(e.message || String(e));
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return;
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}
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async function ensureLabel(name, color, description) {
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try {
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await github.rest.issues.getLabel({ owner, repo, name });
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return;
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} catch (e) {
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// Not found -> create
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}
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await github.rest.issues.createLabel({
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owner,
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repo,
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name,
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color,
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description,
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});
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}
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const labelName = "automation";
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try {
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await ensureLabel(labelName, "5319E7", "Automation-generated direction and planning");
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} catch (e) {
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core.info(`Could not ensure label '${labelName}': ${e.message || e}`);
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}
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const issueTitle = "Automation: Direction";
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const newBody = [
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marker,
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`Last generated: ${now}`,
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`Provider: ${provider}`,
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`Model: ${model}`,
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"",
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direction,
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].join("\n");
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// Find existing open issue with our marker
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let existingIssueNumber = null;
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try {
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const search = await github.rest.search.issuesAndPullRequests({
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q: `repo:${owner}/${repo} is:issue is:open in:body \"${marker}\"`,
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per_page: 10,
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});
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const first = (search.data.items || [])[0];
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if (first && typeof first.number === "number") existingIssueNumber = first.number;
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} catch (e) {
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// Search can be delayed; fall back to listing recent issues
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}
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if (!existingIssueNumber) {
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const recent = await github.rest.issues.listForRepo({
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owner,
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repo,
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state: "open",
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per_page: 50,
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});
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const found = (recent.data || []).find(i => typeof i.body === "string" && i.body.includes(marker));
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if (found) existingIssueNumber = found.number;
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}
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if (existingIssueNumber) {
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await github.rest.issues.update({
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owner,
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repo,
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issue_number: existingIssueNumber,
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title: issueTitle,
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body: newBody,
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});
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core.info(`Updated issue #${existingIssueNumber}`);
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} else {
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const created = await github.rest.issues.create({
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owner,
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repo,
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title: issueTitle,
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body: newBody,
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labels: [labelName],
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});
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core.info(`Created issue #${created.data.number}`);
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}

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