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.github/triage-issues-agentic.lock.yml

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+name: Issue Triage Agent (Agentic)
+
+on:
+  issues:
+    types: [opened, edited]
+
+  schedule:
+    - cron: '0 */6 * * *'
+
+  workflow_dispatch:
+    inputs:
+      mode:
+        description: 'Run mode: single or all'
+        required: true
+        default: 'all'
+        type: choice
+        options:
+          - all
+          - single
+      force:
+        description: 'Re-triage issues that already have a triage label (debug only)'
+        required: false
+        default: false
+        type: boolean
+
+permissions:
+  contents: read
+  issues: write
+  pull-requests: write
+  models: read   # required for the GitHub Models inference API
+
+jobs:
+  triage:
+    runs-on: ubuntu-latest
+    timeout-minutes: 15
+
+    steps:
+      - name: Checkout repo
+        uses: actions/checkout@v4
+
+      - name: Set up Python
+        uses: actions/setup-python@v4
+        with:
+          python-version: '3.11'
+
+      - name: Install dependencies
+        run: |
+          pip install -r requirements.txt || true
+          gh --version
+
+      # ─────────────────────────────────────────────────────────────
+      # SINGLE-ISSUE PATH (triggered by issue opened/edited)
+      #
+      # We do NOT inline ${{ github.event.issue.body }} into a heredoc —
+      # backticks, quotes, and $-signs in the body would otherwise mangle
+      # the script. Instead we fetch the issue via `gh api` so it round-trips
+      # cleanly through JSON.
+      # ─────────────────────────────────────────────────────────────
+      - name: Fetch issue payload (single)
+        if: github.event_name == 'issues'
+        run: |
+          echo "📥 Fetching issue #${{ github.event.issue.number }} via gh api"
+          gh api "repos/${GITHUB_REPOSITORY}/issues/${{ github.event.issue.number }}" \
+            --jq '{number: .number, title: .title, body: .body}' \
+            > /tmp/issue.json
+          echo "── Issue payload (sanitized preview) ──"
+          jq '{number, title, body_length: (.body | length)}' /tmp/issue.json
+          # Wrap into a list so triage_batch.py can consume it uniformly
+          jq '[.]' /tmp/issue.json > /tmp/issues.json
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+
+      - name: Log full body (single)
+        if: github.event_name == 'issues'
+        run: |
+          echo "================================================================================"
+          echo "� FULL ISSUE BODY (as the AI will see it)"
+          echo "================================================================================"
+          jq -r '.body' /tmp/issue.json
+          echo "================================================================================"
+
+      - name: Pre-label as triaged (single)
+        if: github.event_name == 'issues'
+        run: |
+          gh label create "triaged" --repo "$GITHUB_REPOSITORY" 2>/dev/null || true
+          gh issue edit ${{ github.event.issue.number }} \
+            --add-label "triaged" --repo "$GITHUB_REPOSITORY"
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+        continue-on-error: true
+
+      # ─────────────────────────────────────────────────────────────
+      # AI-DRIVEN TRIAGE — the LLM reads the body and decides everything:
+      # classification, the comment to post, and (for auto_fix) the literal
+      # current_text / desired_text to substitute in the docs.
+      # triage_batch.py applies the AI's decision (label + comment + PR).
+      # ─────────────────────────────────────────────────────────────
+      - name: AI triage + (optional) auto-PR (single)
+        if: github.event_name == 'issues'
+        run: |
+          echo "🤖 Running AI triage via GitHub Models on issue #${{ github.event.issue.number }}"
+          python3 triage_batch.py /tmp/issues.json
+        env:
+          GITHUB_TOKEN:      ${{ secrets.GITHUB_TOKEN }}
+          LEARN_PR_TOKEN:    ${{ secrets.LEARN_PR_TOKEN }}
+          GITHUB_REPOSITORY: ${{ github.repository }}
+          AI_MODEL:          openai/gpt-4o-mini
+          # Set AI_DEBUG=1 to dump the full prompt + raw model response.
+          AI_DEBUG:          '1'
+          # Single-issue (event-driven) runs always reprocess — a human
+          # just opened/edited the issue and wants fresh triage.
+          TRIAGE_MODE:       single
+
+      # ─────────────────────────────────────────────────────────────
+      # BATCH PATH (scheduled OR workflow_dispatch with mode=all)
+      # ─────────────────────────────────────────────────────────────
+      - name: Batch triage (scheduled / manual)
+        if: github.event_name == 'schedule' || (github.event_name == 'workflow_dispatch' && github.event.inputs.mode == 'all')
+        run: |
+          echo "🔄 BATCH TRIAGE starting..."
+          # We include `labels` in the JSON so triage_batch.py can skip
+          # issues we've already handled (anything carrying one of the
+          # TRIAGE_LABELS — triaged / auto-fix / needs-review / etc.).
+          gh issue list --state open \
+            --json number,title,body,labels --limit 50 \
+            --repo "$GITHUB_REPOSITORY" > /tmp/issues.json
+          echo "📋 Fetched $(jq length /tmp/issues.json) open issues"
+          python3 triage_batch.py /tmp/issues.json
+        env:
+          GITHUB_TOKEN:      ${{ secrets.GITHUB_TOKEN }}
+          LEARN_PR_TOKEN:    ${{ secrets.LEARN_PR_TOKEN }}
+          GITHUB_REPOSITORY: ${{ github.repository }}
+          AI_MODEL:          openai/gpt-4o-mini
+          TRIAGE_MODE:       batch
+          # Only re-triage already-labeled issues when the user explicitly
+          # asks for it via the workflow_dispatch "force" input.
+          FORCE_RETRIAGE:    ${{ github.event.inputs.force == 'true' && '1' || '' }}

_smoke_test.py

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+"""Smoke-test the AI triage pipeline.
+
+Locally there is no GITHUB_TOKEN with models:read scope, so the AI call
+raises and we exercise the heuristic fallback path. The point of this test
+is to prove the fallback returns sensible classifications + comments.
+"""
+import os
+import sys
+
+os.environ.pop("GITHUB_TOKEN", None)  # force the fallback path
+
+from ai_triage import ai_or_fallback
+
+ISSUES = [
+    {
+        "number": 7,
+        "title": "MS Learn Module Update Request: [REPLACE_WITH_MODULE_TITLE]",
+        "body": (
+            "Which of the MS Learn modules from the dropdown are you submitting an update request?\n"
+            "None\n\nAdditional information\n\n"
+            "Fix a broken user experience (broken links, exercise error, etc.)\n\n"
+            "Update incorrect information\n\nAdd new content to the module\n\n"
+            "Some other request\nInformation about the requested update\nNo response"
+        ),
+        "expected": "spam",
+    },
+    {
+        "number": 4,
+        "title": "MS Learn Module Update Request: Manage your work with GitHub Projects",
+        "body": (
+            "Information about the requested update\n"
+            "https://learn.microsoft.com/en-us/training/modules/manage-work-github-projects/7-knowledge-check\n\n"
+            "In Module assessment/Check your knowledge\n\n"
+            "What Project descriptor automatically saves when you change it?\n\n"
+            "Project name (Correct)\n\n\nProject description\n\n\nProject README\n\n"
+            "first answer is marked as correct, should be: None of them."
+        ),
+        "expected": "auto_fix",
+    },
+]
+
+lines = []
+for issue in ISSUES:
+    r = ai_or_fallback(issue)
+    lines.append(
+        f"#{issue['number']:>3}  expected={issue['expected']:<13}  "
+        f"got={r['classification']:<13}  ({r['source']}, conf={r['confidence']})"
+    )
+    lines.append(f"     comment[:140] = {r['comment'][:140]!r}")
+    if r.get("fix_plan"):
+        fp = r["fix_plan"]
+        lines.append(f"     fix_plan = current={fp.get('current_text')!r}  desired={fp.get('desired_text')!r}")
+
+text = "\n".join(lines) + "\n"
+sys.stdout.write(text)
+sys.stdout.flush()
+with open("_smoke_result.txt", "w") as fh:
+    fh.write(text)