From 7b4617f7abb17ae6009352f96d9c33ab54708a02 Mon Sep 17 00:00:00 2001
From: Abner <22141172+Silentely@users.noreply.github.com>
Date: Mon, 10 Aug 2026 21:03:21 +0800
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- 删除 `.github/workflows/ai-issue-smart-reply.yml`，该文件包含约 1469 行的复杂 AI 分诊逻辑
- 新增 `.github/workflows/nomore-spam.yml`，在 issue 打开和 PR 打开时自动检测并关闭垃圾信息
- 新工作流支持通过仓库 secrets 配置自定义 AI 端点、API 密钥和模型名称
- 新工作流启用文件变更分析，可设置分析深度、标签白名单和用户黑名单
---
.github/workflows/ai-issue-smart-reply.yml | 1469 --------------------
.github/workflows/nomore-spam.yml | 30 +
2 files changed, 30 insertions(+), 1469 deletions(-)
delete mode 100644 .github/workflows/ai-issue-smart-reply.yml
create mode 100644 .github/workflows/nomore-spam.yml
diff --git a/.github/workflows/ai-issue-smart-reply.yml b/.github/workflows/ai-issue-smart-reply.yml
deleted file mode 100644
index ee53c9a..0000000
--- a/.github/workflows/ai-issue-smart-reply.yml
+++ /dev/null
@@ -1,1469 +0,0 @@
-name: 🤖 AI Issue Smart Reply
-
-on:
- issues:
- types: [opened]
- issue_comment:
- types: [created]
- workflow_dispatch:
- inputs:
- target_type:
- description: '目标类型'
- required: true
- type: choice
- options:
- - issue
- - pr
- issue_number:
- description: 'Issue 或 PR 编号（如 42）'
- required: true
- type: string
-
-permissions:
- contents: write
- issues: write
- pull-requests: read
-
-concurrency:
- group: ai-issue-${{ github.event.issue.number || github.event.inputs.issue_number }}
- cancel-in-progress: false
-
-jobs:
- ai-smart-reply:
- if: |
- vars.AI_ISSUE_REPLY_ENABLED == 'true' && (
- github.event_name == 'issues' ||
- github.event_name == 'workflow_dispatch' ||
- (github.event_name == 'issue_comment' && startsWith(github.event.comment.body, '/ai-analyze'))
- )
- runs-on: ubuntu-latest
- timeout-minutes: 20
-
- env:
- AI_AUTO_LABEL: ${{ vars.AI_AUTO_LABEL || 'true' }}
- AI_ENABLE_DUPLICATE_CHECK: ${{ vars.AI_ENABLE_DUPLICATE_CHECK || 'true' }}
- AI_ENABLE_PR_SEARCH: ${{ vars.AI_ENABLE_PR_SEARCH || 'true' }}
- AI_ENABLE_COMMIT_SEARCH: ${{ vars.AI_ENABLE_COMMIT_SEARCH || 'true' }}
- AI_ONLY_TEMPLATE_TYPES: ${{ vars.AI_ONLY_TEMPLATE_TYPES || 'false' }}
- AI_MAX_CONTEXT_CHARS: ${{ vars.AI_MAX_CONTEXT_CHARS || '50000' }}
- AI_MAX_DUP_CANDIDATES: ${{ vars.AI_MAX_DUP_CANDIDATES || '80' }}
- AI_MAX_PR_CANDIDATES: ${{ vars.AI_MAX_PR_CANDIDATES || '20' }}
- AI_MAX_COMMIT_CANDIDATES: ${{ vars.AI_MAX_COMMIT_CANDIDATES || '20' }}
- FORCE_JAVASCRIPT_ACTIONS_TO_NODE24: true
-
- steps:
- - name: Checkout repository
- uses: actions/checkout@v4
- with:
- fetch-depth: 100
-
- - name: Install dependencies
- shell: bash
- run: |
- set -euo pipefail
- sudo apt-get update
- sudo apt-get install -y jq python3 ripgrep
-
- - name: Prepare issue payload
- id: issue
- env:
- GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
- INPUT_NUM: ${{ github.event.issue.number || github.event.inputs.issue_number }}
- TARGET_TYPE: ${{ github.event.inputs.target_type || 'issue' }}
- AUTO_TITLE: ${{ github.event.issue.title }}
- AUTO_BODY: ${{ github.event.issue.body || '' }}
- AUTO_AUTHOR: ${{ github.event.issue.user.login }}
- AUTO_URL: ${{ github.event.issue.html_url }}
- EVENT_NAME: ${{ github.event_name }}
- COMMENT_BODY: ${{ github.event.comment.body || '' }}
- shell: bash
- run: |
- set -euo pipefail
- mkdir -p .ai_runtime
-
- python3 - <<'PY'
- import json, os, pathlib, subprocess
-
- input_num = os.environ['INPUT_NUM']
- target_type = os.environ['TARGET_TYPE']
- auto_title = os.environ.get('AUTO_TITLE', '')
- event_name = os.environ.get('EVENT_NAME', '')
- comment_body = os.environ.get('COMMENT_BODY', '')
-
- re_analyze = False
-
- if event_name == 'issue_comment':
- # 评论触发：通过 gh CLI 获取 issue 数据
- cmd = ['gh', 'issue', 'view', input_num,
- '--json', 'number,title,body,author,url']
- result = subprocess.run(cmd, capture_output=True, text=True, check=True)
- d = json.loads(result.stdout)
- author = d.get('author', {})
- payload = {
- "number": d['number'],
- "title": d.get('title', ''),
- "body": d.get('body', '') or '',
- "author": author.get('login', '') if isinstance(author, dict) else str(author),
- "url": d.get('url', ''),
- }
- re_analyze = True
- elif auto_title:
- # 自动触发：使用事件环境变量
- payload = {
- "number": int(input_num),
- "title": auto_title,
- "body": os.environ.get('AUTO_BODY', ''),
- "author": os.environ.get('AUTO_AUTHOR', ''),
- "url": os.environ.get('AUTO_URL', ''),
- }
- else:
- # 手动触发：通过 gh CLI 获取数据
- cmd = ['gh', 'pr' if target_type == 'pr' else 'issue', 'view', input_num,
- '--json', 'number,title,body,author,url']
- result = subprocess.run(cmd, capture_output=True, text=True, check=True)
- d = json.loads(result.stdout)
- author = d.get('author', {})
- payload = {
- "number": d['number'],
- "title": d.get('title', ''),
- "body": d.get('body', '') or '',
- "author": author.get('login', '') if isinstance(author, dict) else str(author),
- "url": d.get('url', ''),
- }
-
- payload["re_analyze"] = re_analyze
-
- pathlib.Path('.ai_runtime/issue.json').write_text(
- json.dumps(payload, ensure_ascii=False, indent=2), encoding='utf-8'
- )
- print(f"成功获取 {target_type} #{input_num}: {payload['title']}")
- PY
-
- echo "payload=$(cat .ai_runtime/issue.json | jq -c .)" >> "$GITHUB_OUTPUT"
- echo "issue_number=$(jq -r '.number' .ai_runtime/issue.json)" >> "$GITHUB_OUTPUT"
- echo "re_analyze=$(jq -r '.re_analyze' .ai_runtime/issue.json)" >> "$GITHUB_OUTPUT"
-
- - name: React to /ai-analyze comment
- if: github.event_name == 'issue_comment' && steps.issue.outputs.re_analyze == 'true'
- uses: actions/github-script@v7
- env:
- ISSUE_NUMBER: ${{ steps.issue.outputs.issue_number }}
- COMMENT_ID: ${{ github.event.comment.id }}
- with:
- script: |
- const issue_number = parseInt(process.env.ISSUE_NUMBER, 10) || context.issue.number;
- const comment_id = parseInt(process.env.COMMENT_ID, 10);
- if (comment_id) {
- await github.rest.reactions.createForIssueComment({
- owner: context.repo.owner,
- repo: context.repo.repo,
- comment_id,
- content: 'rocket'
- });
- }
-
- - name: Stage 1 - classify and rewrite query
- id: rewrite
- shell: bash
- env:
- LLM_API_KEY: ${{ secrets.LLM_API_KEY }}
- LLM_BASE_URL: ${{ secrets.LLM_BASE_URL }}
- LLM_MODEL: ${{ secrets.LLM_MODEL }}
- run: |
- set -euo pipefail
-
- cat > .ai_runtime/rewrite_schema.json <<'JSON'
- {
- "name": "issue_rewrite",
- "parameters": {
- "type": "object",
- "properties": {
- "summary": { "type": "string" },
- "issue_type": {
- "type": "string",
- "enum": ["bug", "enhancement", "question", "documentation", "needs_more_info"]
- },
- "search_queries": {
- "type": "array",
- "items": { "type": "string" }
- },
- "keywords": {
- "type": "array",
- "items": { "type": "string" }
- },
- "components": {
- "type": "array",
- "items": { "type": "string" }
- },
- "likely_paths": {
- "type": "array",
- "items": { "type": "string" }
- }
- },
- "required": ["summary", "issue_type", "search_queries", "keywords", "components", "likely_paths"]
- }
- }
- JSON
-
- cat > .ai_runtime/rewrite_system_prompt.txt <<'EOF'
- 你负责把 Issue 重写成适合仓库检索的查询。
- 输出必须是严格 JSON。
- search_queries 控制在 3-6 条，keywords 控制在 5-12 条。
- EOF
-
- python3 -c "
- import json, pathlib
- issue = json.loads(pathlib.Path('.ai_runtime/issue.json').read_text(encoding='utf-8'))
- pathlib.Path('.ai_runtime/rewrite_input_prompt.txt').write_text(
- '请分析这个 Issue，并输出适合仓库知识库/代码库检索的查询。\n\n标题：\n' + issue.get('title','') + '\n\n正文：\n' + issue.get('body',''),
- encoding='utf-8'
- )
- "
-
- python3 - <<'PY'
- import json, os, pathlib, urllib.request, urllib.error
-
- base_url = os.environ['LLM_BASE_URL'].rstrip('/')
- api_key = os.environ['LLM_API_KEY']
- model = os.environ['LLM_MODEL']
- system_prompt = pathlib.Path('.ai_runtime/rewrite_system_prompt.txt').read_text(encoding='utf-8')
- input_prompt = pathlib.Path('.ai_runtime/rewrite_input_prompt.txt').read_text(encoding='utf-8')
- schema = json.loads(pathlib.Path('.ai_runtime/rewrite_schema.json').read_text(encoding='utf-8'))
-
- candidates = [
- (f"{base_url}/chat/completions", {
- "model": model,
- "temperature": 0.2,
- "response_format": {"type": "json_object"},
- "messages": [
- {"role": "system", "content": system_prompt + "\n你必须直接输出 JSON 对象，不要输出 markdown。"},
- {"role": "user", "content": input_prompt},
- ],
- }, 'chat_json'),
- (f"{base_url}/chat/completions", {
- "model": model,
- "temperature": 0.2,
- "messages": [
- {"role": "system", "content": system_prompt + "\n你必须直接输出 JSON 对象，不要输出 markdown 或代码块。"},
- {"role": "user", "content": input_prompt + "\n\n请直接输出 JSON，不要包含 ```json 代码块标记。"},
- ],
- }, 'chat_plain'),
- ]
-
- headers = {
- 'Authorization': f'Bearer {api_key}',
- 'Content-Type': 'application/json',
- 'Accept': 'application/json',
- 'User-Agent': 'github-actions-ai-triage/1.0',
- }
-
- last_err = None
- content = ''
- mode_used = ''
- required_fields = {"summary", "issue_type", "search_queries", "keywords", "components", "likely_paths"}
-
- def validate_rewrite(s):
- try:
- obj = json.loads(s) if isinstance(s, str) else s
- return required_fields.issubset(set(obj.keys()))
- except Exception:
- return False
-
- for attempt in range(2):
- for url, payload, mode in candidates:
- if attempt > 0:
- extra = "\n\n重要：必须输出包含 summary, issue_type, search_queries, keywords, components, likely_paths 全部字段的 JSON。"
- payload = dict(payload)
- msgs = [dict(m) for m in payload['messages']]
- msgs[-1] = dict(msgs[-1])
- msgs[-1]['content'] = msgs[-1].get('content', '') + extra
- payload['messages'] = msgs
-
- data = json.dumps(payload, ensure_ascii=False).encode('utf-8')
- req = urllib.request.Request(url, data=data, headers=headers, method='POST')
- try:
- with urllib.request.urlopen(req, timeout=180) as resp:
- text = resp.read().decode('utf-8', errors='replace')
- obj = json.loads(text)
- raw = ((obj.get('choices') or [{}])[0].get('message') or {}).get('content') or ''
- # 尝试从 markdown 代码块中提取 JSON
- if raw and not raw.strip().startswith('{'):
- import re
- m = re.search(r'```(?:json)?\s*\n?(.*?)\n?```', raw, re.S)
- if m:
- raw = m.group(1).strip()
- if raw and validate_rewrite(raw):
- content = raw
- mode_used = mode
- pathlib.Path('.ai_runtime/rewrite_raw.txt').write_text(content, encoding='utf-8')
- break
- except urllib.error.HTTPError as e:
- err_body = e.read().decode('utf-8', errors='replace')[:500]
- last_err = f'HTTP {e.code}: {err_body}'
- print(f'[attempt {attempt+1}] {mode} 失败: {last_err}')
- import time; time.sleep(2)
- except Exception as e:
- last_err = e
- print(f'[attempt {attempt+1}] {mode} 异常: {e}')
- if content:
- break
-
- if not content:
- raise RuntimeError(f'LLM rewrite call failed: {last_err}')
-
- pathlib.Path('.ai_runtime/issue_rewrite.txt').write_text(content, encoding='utf-8')
- with open(os.environ['GITHUB_OUTPUT'], 'a', encoding='utf-8') as f:
- f.write(f'mode_used={mode_used}\n')
- PY
-
- python3 .github/scripts/write_output.py issue_rewrite .ai_runtime/issue_rewrite.txt
-
- - name: Normalize rewrite result
- id: rewrite_norm
- shell: bash
- run: |
- set -euo pipefail
-
- cat > .ai_runtime/rewrite_raw.txt <<'EOF'
- ${{ steps.rewrite.outputs.issue_rewrite }}
- EOF
-
- python3 - <<'PY'
- import json, re, pathlib
-
- raw = pathlib.Path(".ai_runtime/rewrite_raw.txt").read_text(encoding="utf-8", errors="ignore").strip()
-
- def parse_json(s):
- try:
- return json.loads(s)
- except Exception:
- m = re.search(r'\{.*\}', s, flags=re.S)
- return json.loads(m.group(0)) if m else {}
-
- d = parse_json(raw) if raw else {}
- issue_type = d.get("issue_type")
- if issue_type not in {"bug","enhancement","question","documentation","needs_more_info"}:
- issue_type = "needs_more_info"
-
- def clean_list(v, n):
- if not isinstance(v, list):
- return []
- out = []
- seen = set()
- for x in v:
- if isinstance(x, str):
- s = x.strip()
- if s and s.lower() not in seen:
- seen.add(s.lower())
- out.append(s)
- if len(out) >= n:
- break
- return out
-
- result = {
- "summary": d.get("summary") if isinstance(d.get("summary"), str) else "",
- "issue_type": issue_type,
- "search_queries": clean_list(d.get("search_queries"), 6),
- "keywords": clean_list(d.get("keywords"), 12),
- "components": clean_list(d.get("components"), 8),
- "likely_paths": clean_list(d.get("likely_paths"), 8)
- }
-
- pathlib.Path(".ai_runtime/rewrite.json").write_text(
- json.dumps(result, ensure_ascii=False, indent=2),
- encoding="utf-8"
- )
- print(json.dumps(result, ensure_ascii=False))
- PY
-
- echo "json=$(cat .ai_runtime/rewrite.json | jq -c .)" >> "$GITHUB_OUTPUT"
-
- - name: Optional filter by issue type
- if: env.AI_ONLY_TEMPLATE_TYPES == 'true'
- shell: bash
- run: |
- set -euo pipefail
- TYPE="$(jq -r '.issue_type' .ai_runtime/rewrite.json)"
- case "$TYPE" in
- bug|enhancement|documentation)
- echo "continue"
- ;;
- *)
- echo "Skipping non-target issue type: $TYPE"
- exit 78
- ;;
- esac
-
- - name: Retrieve context from repository scan
- id: context_scan
- shell: bash
- run: |
- set -euo pipefail
-
- python3 - <<'PY'
- import json, os, pathlib, re
-
- TEXT_EXTS = {
- ".md", ".mdx", ".rst", ".txt", ".js", ".jsx", ".ts", ".tsx", ".py", ".go",
- ".java", ".rs", ".php", ".rb", ".yml", ".yaml", ".json", ".toml", ".sh", ".vue"
- }
- IGNORE_DIRS = {
- ".git", "node_modules", "dist", "build", "coverage", ".next", ".nuxt",
- "__pycache__", ".venv", "venv", "vendor", "target", "out", ".ai_runtime"
- }
-
- rewrite = json.loads(pathlib.Path(".ai_runtime/rewrite.json").read_text(encoding="utf-8"))
- issue = json.loads(pathlib.Path(".ai_runtime/issue.json").read_text(encoding="utf-8"))
-
- # 构建查询词
- query_terms = []
- for key in ("search_queries", "keywords", "components", "likely_paths"):
- query_terms.extend(rewrite.get(key, []))
- query_terms.append(issue.get("title", ""))
- query_terms = [t for t in query_terms if isinstance(t, str) and t.strip()]
-
- def tokenize(text):
- return set(re.findall(r"[A-Za-z0-9_./:#-]{3,}", text.lower()))
-
- q_tokens = tokenize(" ".join(query_terms))
- max_chars = int(os.environ.get("AI_MAX_CONTEXT_CHARS", "50000"))
-
- root = pathlib.Path(".")
- rows = []
-
- for path in root.rglob("*"):
- if not path.is_file():
- continue
- rel = path.relative_to(root).as_posix()
- if any(part in rel for part in IGNORE_DIRS):
- continue
- if path.suffix.lower() not in TEXT_EXTS and not path.name.startswith("README"):
- continue
- try:
- text = path.read_text(encoding="utf-8", errors="ignore")
- except Exception:
- continue
-
- lower = text.lower()
- score = 0
- for t in query_terms:
- tl = t.lower()
- if tl in lower:
- score += 2
- if tl in rel.lower():
- score += 4
- if score <= 0:
- continue
-
- lines = text.splitlines()
- for i, line in enumerate(lines):
- ls = line.lower()
- hit = sum(1 for t in query_terms if t.lower() in ls)
- if hit <= 0:
- continue
- start = max(0, i - 18)
- end = min(len(lines), i + 19)
- block = "\n".join(f"{j+1:>5}: {lines[j]}" for j in range(start, end))
- rows.append({
- "path": rel,
- "start_line": start + 1,
- "end_line": end,
- "text": block,
- "score": score + hit * 5
- })
-
- rows.sort(key=lambda x: (-x["score"], x["path"], x["start_line"]))
-
- # 输出去重后的结果
- parts = []
- cur = 0
- seen = set()
- for row in rows:
- key = (row["path"], row["start_line"], row["end_line"])
- if key in seen:
- continue
- seen.add(key)
- block = f"--- FILE: {row['path']} (lines {row['start_line']}-{row['end_line']}) ---\n{row['text']}\n"
- if cur + len(block) > max_chars:
- break
- parts.append(block)
- cur += len(block)
-
- pathlib.Path(".ai_runtime/final_context.txt").write_text("\n".join(parts), encoding="utf-8")
- print(f"扫描完成: {len(rows)} 个匹配块, {len(parts)} 个输出, {cur} 字符")
- PY
-
- python3 .github/scripts/write_output.py context .ai_runtime/final_context.txt
-
- - name: Fetch duplicate candidates
- if: env.AI_ENABLE_DUPLICATE_CHECK == 'true'
- id: dupes
- env:
- GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
- shell: bash
- run: |
- set -euo pipefail
-
- gh issue list \
- --state all \
- --limit "${AI_MAX_DUP_CANDIDATES}" \
- --json number,title,body,state,updatedAt,url \
- > .ai_runtime/issues_raw.json
-
- python3 - <<'PY'
- import json, pathlib, re
-
- rewrite = json.loads(pathlib.Path(".ai_runtime/rewrite.json").read_text(encoding="utf-8"))
- queries = " ".join(rewrite.get("search_queries", [])) + " " + " ".join(rewrite.get("keywords", []))
- q = set(re.findall(r"[a-z0-9_./:-]{3,}", queries.lower()))
-
- items = json.loads(pathlib.Path(".ai_runtime/issues_raw.json").read_text(encoding="utf-8"))
- scored = []
- for it in items:
- text = ((it.get("title") or "") + "\n" + (it.get("body") or "")).lower()
- toks = set(re.findall(r"[a-z0-9_./:-]{3,}", text))
- inter = len(q & toks)
- if inter == 0:
- continue
- union = max(len(q | toks), 1)
- score = inter * 2 + (inter / union) * 100
- scored.append({
- "number": it["number"],
- "title": it.get("title", ""),
- "state": it.get("state", ""),
- "url": it.get("url", ""),
- "score": round(score, 2),
- })
-
- scored.sort(key=lambda x: (-x["score"], x["number"]))
- top = scored[:12]
- pathlib.Path(".ai_runtime/dupes.txt").write_text(
- "\n".join([f"#{x['number']} [{x['state']}] score={x['score']}: {x['title']}" for x in top]),
- encoding="utf-8"
- )
- PY
-
- python3 .github/scripts/write_output.py candidates .ai_runtime/dupes.txt
-
- - name: Prepare duplicate candidates fallback
- if: env.AI_ENABLE_DUPLICATE_CHECK != 'true'
- id: dupes_disabled
- shell: bash
- run: |
- set -euo pipefail
- echo "No duplicate candidates collected." > .ai_runtime/dupes.txt
- python3 .github/scripts/write_output.py candidates .ai_runtime/dupes.txt
-
- - name: Fetch recent PR candidates
- if: env.AI_ENABLE_PR_SEARCH == 'true'
- id: prs
- env:
- GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
- shell: bash
- run: |
- set -euo pipefail
-
- gh pr list \
- --state all \
- --limit "${AI_MAX_PR_CANDIDATES}" \
- --json number,title,body,mergedAt,state,url \
- > .ai_runtime/prs_raw.json
-
- python3 - <<'PY'
- import json, pathlib, re
-
- rewrite = json.loads(pathlib.Path(".ai_runtime/rewrite.json").read_text(encoding="utf-8"))
- q = set(re.findall(r"[a-z0-9_./:-]{3,}", " ".join(rewrite.get("search_queries", []) + rewrite.get("keywords", [])).lower()))
- items = json.loads(pathlib.Path(".ai_runtime/prs_raw.json").read_text(encoding="utf-8"))
- out = []
- for it in items:
- text = ((it.get("title") or "") + "\n" + (it.get("body") or "")).lower()
- toks = set(re.findall(r"[a-z0-9_./:-]{3,}", text))
- inter = len(q & toks)
- if inter <= 0:
- continue
- out.append((inter, it))
- out.sort(key=lambda x: -x[0])
-
- lines = []
- for _, it in out[:8]:
- lines.append(f"PR #{it['number']} [{it.get('state','')}]: {it.get('title','')} {it.get('url','')}")
- pathlib.Path(".ai_runtime/prs.txt").write_text("\n".join(lines), encoding="utf-8")
- PY
-
- python3 .github/scripts/write_output.py candidates .ai_runtime/prs.txt
-
- - name: Prepare PR candidates fallback
- if: env.AI_ENABLE_PR_SEARCH != 'true'
- id: prs_disabled
- shell: bash
- run: |
- set -euo pipefail
- echo "No PR candidates collected." > .ai_runtime/prs.txt
- python3 .github/scripts/write_output.py candidates .ai_runtime/prs.txt
-
- - name: Fetch recent commit candidates
- if: env.AI_ENABLE_COMMIT_SEARCH == 'true'
- id: commits
- shell: bash
- run: |
- set -euo pipefail
-
- python3 - <<'PY'
- import json, pathlib, subprocess
-
- rewrite = json.loads(pathlib.Path(".ai_runtime/rewrite.json").read_text(encoding="utf-8"))
- keywords = rewrite.get("keywords", [])[:8]
-
- try:
- log = subprocess.check_output(
- ["git", "log", "--pretty=format:%H%x09%s", "-n", "200"],
- text=True
- )
- except Exception:
- log = ""
-
- lines = []
- for row in log.splitlines():
- if "\t" not in row:
- continue
- sha, subject = row.split("\t", 1)
- score = 0
- lower = subject.lower()
- for k in keywords:
- if k.lower() in lower:
- score += 1
- if score > 0:
- lines.append((score, f"{sha[:12]} {subject}"))
-
- lines.sort(key=lambda x: -x[0])
- pathlib.Path(".ai_runtime/commits.txt").write_text(
- "\n".join([x[1] for x in lines[:10]]),
- encoding="utf-8"
- )
- PY
-
- python3 .github/scripts/write_output.py candidates .ai_runtime/commits.txt
-
- - name: Prepare commit candidates fallback
- if: env.AI_ENABLE_COMMIT_SEARCH != 'true'
- id: commits_disabled
- shell: bash
- run: |
- set -euo pipefail
- echo "No commit candidates collected." > .ai_runtime/commits.txt
- python3 .github/scripts/write_output.py candidates .ai_runtime/commits.txt
-
- - name: Prepare final duplicate candidates
- id: final_dupes
- shell: bash
- run: |
- set -euo pipefail
- if [ -s .ai_runtime/dupes.txt ]; then
- cp .ai_runtime/dupes.txt .ai_runtime/final_dupes.txt
- else
- echo "No duplicate candidates collected." > .ai_runtime/final_dupes.txt
- fi
- python3 .github/scripts/write_output.py candidates .ai_runtime/final_dupes.txt
-
- - name: Prepare final PR candidates
- id: final_prs
- shell: bash
- run: |
- set -euo pipefail
- if [ -s .ai_runtime/prs.txt ]; then
- cp .ai_runtime/prs.txt .ai_runtime/final_prs.txt
- else
- echo "No PR candidates collected." > .ai_runtime/final_prs.txt
- fi
- python3 .github/scripts/write_output.py candidates .ai_runtime/final_prs.txt
-
- - name: Prepare final commit candidates
- id: final_commits
- shell: bash
- run: |
- set -euo pipefail
- if [ -s .ai_runtime/commits.txt ]; then
- cp .ai_runtime/commits.txt .ai_runtime/final_commits.txt
- else
- echo "No commit candidates collected." > .ai_runtime/final_commits.txt
- fi
- python3 .github/scripts/write_output.py candidates .ai_runtime/final_commits.txt
-
- - name: Collect enriched context for deeper analysis
- id: enriched
- shell: bash
- run: |
- set -euo pipefail
-
- python3 - <<'PY'
- import json, os, pathlib, re, subprocess
-
- issue = json.loads(pathlib.Path('.ai_runtime/issue.json').read_text(encoding='utf-8'))
- rewrite = json.loads(pathlib.Path('.ai_runtime/rewrite.json').read_text(encoding='utf-8'))
-
- # --- 1. 从 issue body 提取错误模式 ---
- body = issue.get('body', '') or ''
- error_patterns = []
-
- # 提取堆栈跟踪（支持多种语言格式）
- stacktrace_re = re.compile(
- r'(?:(?:Traceback|Exception|Error|at\s+\S+\s*\(|File\s+".*?"|.*?Error:.*|.*?Exception:.*|'
- r'(?:Caused by|Caused):.*|.*?\.java:\d+|.*?\.ts:\d+|.*?\.js:\d+|.*?\.py:\d+|'
- r'(?:errno|EACCES|ENOENT|ECONNREFUSED|ETIMEDOUT)\s.*|'
- r'(?:SIGTERM|SIGKILL|SIGSEGV).*|'
- r'(?:fatal|panic|crash|FATAL|PANIC|CRASH)\s.*))',
- re.MULTILINE | re.IGNORECASE
- )
- for m in stacktrace_re.finditer(body):
- error_patterns.append(m.group(0).strip())
-
- # 提取代码块内容
- code_blocks = re.findall(r'```[\w]*\n(.*?)```', body, re.DOTALL)
- for block in code_blocks[:5]:
- stripped = block.strip()
- if stripped and len(stripped) < 2000:
- error_patterns.append(f"[code block] {stripped}")
-
- # 提取 URL（可能指向日志、截图等）
- urls = re.findall(r'https?://[^\s\)\]>]+', body)
-
- # 去重并限制数量
- seen = set()
- unique_errors = []
- for ep in error_patterns:
- key = ep[:100].lower()
- if key not in seen:
- seen.add(key)
- unique_errors.append(ep)
- error_patterns = unique_errors[:15]
-
- # --- 2. 读取 likely_paths 指向的文件内容（关键词定位 + 上下文窗口） ---
- likely_paths = rewrite.get('likely_paths', [])
- search_terms = []
- for key in ("search_queries", "keywords", "components"):
- search_terms.extend(rewrite.get(key, []))
- search_terms = [t for t in search_terms if isinstance(t, str) and len(t) >= 3]
-
- file_contents = {}
- max_file_chars = 8000 # 每个文件最多 8000 字符
- context_lines = 40 # 关键词命中行前后各取 40 行
-
- for fp in likely_paths[:6]:
- p = pathlib.Path(fp)
- if not p.is_file():
- p = pathlib.Path('.') / fp
- if not (p.is_file() and p.stat().st_size < 500_000):
- continue
- try:
- content = p.read_text(encoding='utf-8', errors='replace')
- except Exception:
- continue
-
- if len(content) <= max_file_chars:
- file_contents[fp] = content
- continue
-
- # 关键词定位：找到匹配行，提取上下文窗口
- lines = content.splitlines()
- matched_ranges = []
- for i, line in enumerate(lines):
- ll = line.lower()
- if any(t.lower() in ll for t in search_terms):
- start = max(0, i - context_lines)
- end = min(len(lines), i + context_lines + 1)
- matched_ranges.append((start, end))
-
- if matched_ranges:
- # 合并重叠区间
- matched_ranges.sort()
- merged = [matched_ranges[0]]
- for s, e in matched_ranges[1:]:
- if s <= merged[-1][1]:
- merged[-1] = (merged[-1][0], max(merged[-1][1], e))
- else:
- merged.append((s, e))
-
- # 提取合并后的区间内容
- parts = []
- cur = 0
- for s, e in merged:
- if s > cur:
- parts.append(f"... [跳过 {s - cur} 行] ...")
- parts.append("\n".join(lines[s:e]))
- cur = e
- if cur < len(lines):
- parts.append(f"... [剩余 {len(lines) - cur} 行] ...")
- result = "\n".join(parts)
- if len(result) > max_file_chars:
- result = result[:max_file_chars] + f'\n... [截断，共 {len(content)} 字符]'
- file_contents[fp] = result
- else:
- # 无关键词命中，回退到读取前半部分
- file_contents[fp] = content[:max_file_chars] + f'\n... [截断，共 {len(content)} 字符]'
-
- # --- 3. 获取相关文件的 git 历史 ---
- git_history = {}
- for fp in list(file_contents.keys())[:4]:
- try:
- log = subprocess.check_output(
- ['git', 'log', '--pretty=format:%h %ad %s', '--date=short', '-n', '5', '--', fp],
- text=True, stderr=subprocess.DEVNULL
- )
- if log.strip():
- git_history[fp] = log.strip().splitlines()
- except Exception:
- pass
-
- # --- 4. 获取仓库结构概览（顶层目录） ---
- repo_structure = []
- try:
- for item in sorted(pathlib.Path('.').iterdir()):
- if item.name.startswith('.'):
- continue
- if item.is_dir():
- repo_structure.append(f"{item.name}/")
- else:
- repo_structure.append(item.name)
- except Exception:
- pass
-
- enriched = {
- "error_patterns": error_patterns,
- "code_blocks_from_issue": [b.strip() for b in code_blocks[:5] if b.strip()],
- "urls_from_issue": urls[:10],
- "file_contents": file_contents,
- "git_history": git_history,
- "repo_structure": repo_structure[:30],
- }
-
- pathlib.Path('.ai_runtime/enriched_context.json').write_text(
- json.dumps(enriched, ensure_ascii=False, indent=2),
- encoding='utf-8'
- )
-
- # 摘要统计
- print(f"错误模式: {len(error_patterns)} 条")
- print(f"读取文件: {len(file_contents)} 个")
- print(f"Git 历史: {len(git_history)} 个文件")
- print(f"Issue URL: {len(urls)} 个")
- PY
-
- - name: Stage 2 - maintainer-grade triage
- id: triage
- shell: bash
- env:
- LLM_API_KEY: ${{ secrets.LLM_API_KEY }}
- LLM_BASE_URL: ${{ secrets.LLM_BASE_URL }}
- LLM_MODEL: ${{ secrets.LLM_MODEL }}
- run: |
- set -euo pipefail
-
- cat > .ai_runtime/triage_schema.json <<'JSON'
- {
- "name": "issue_response",
- "parameters": {
- "type": "object",
- "properties": {
- "summary": { "type": "string" },
- "classification": {
- "type": "string",
- "enum": ["bug", "enhancement", "question", "documentation", "needs_more_info"]
- },
- "support_status": {
- "type": "string",
- "enum": ["supported", "partially_supported", "not_supported", "already_fixed_unreleased", "needs_more_info"]
- },
- "analysis": { "type": "string" },
- "solution": { "type": "string" },
- "workaround": { "type": "string" },
- "error_pattern_summary": { "type": "string" },
- "related_files": {
- "type": "array",
- "items": { "type": "string" }
- },
- "actionable_steps": {
- "type": "array",
- "items": { "type": "string" }
- },
- "roadmap": { "type": "string" },
- "needs_human_followup": { "type": "boolean" },
- "duplicate_confidence": {
- "type": "string",
- "enum": ["low", "medium", "high"]
- },
- "duplicate_issues": {
- "type": "array",
- "items": { "type": "string" }
- },
- "labels": {
- "type": "array",
- "items": {
- "type": "string",
- "enum": ["bug", "enhancement", "question", "documentation", "duplicate", "help wanted", "needs more info"]
- }
- }
- },
- "required": ["summary", "classification", "support_status", "analysis", "solution", "workaround", "error_pattern_summary", "related_files", "actionable_steps", "needs_human_followup", "duplicate_confidence", "duplicate_issues", "labels"]
- }
- }
- JSON
-
- python3 - <<'PY'
- import pathlib
- prompt = (
- "你是一位资深仓库维护者。根据提供的 Issue 信息、代码上下文和历史数据，做出专业判断。\n\n"
- "## 输出要求\n\n"
- "你必须输出严格的 JSON 对象，包含以下字段（缺一不可）：\n\n"
- "- summary: 一句话总结 Issue 核心问题（必填）\n"
- "- classification: 分类，必须是 bug/enhancement/question/documentation/needs_more_info 之一（必填）\n"
- "- support_status: 支持状态，必须是 supported/partially_supported/not_supported/already_fixed_unreleased/needs_more_info 之一（必填）\n"
- "- analysis: 详细分析问题根因，引用具体的代码路径和逻辑（必填，至少 2 句话）\n"
- "- solution: 详细的修复方案，必须包含：受影响的文件路径、具体的函数/方法名、需要修改的代码逻辑描述、修改后的预期行为。格式示例：\"在 `packages/backend/src/auth/service.ts` 的 `validateToken()` 方法中，第 42 行的过期检查逻辑需要改为...\"（必填，至少 2 句话）\n"
- "- workaround: 用户可立即执行的临时解决方案，不依赖代码修改或重新部署。例如：修改配置文件参数、设置环境变量、重启服务、手动执行命令等。如果确实没有临时方案则为空字符串（必填）\n"
- "- error_pattern_summary: 错误模式总结，描述从 Issue 中提取的错误类型、发生位置和调用链路（如果存在错误信息则必填，否则为空字符串）\n"
- "- related_files: 相关文件列表，格式如 [\"packages/backend/src/auth/service.ts\"]，列出与问题直接相关的源代码文件（必填，至少 1 个，最多 8 个）\n"
- "- actionable_steps: 可执行步骤列表，每步必须足够具体以供 AI 编程助手直接执行。格式要求：引用文件路径（如 `src/foo.ts`）、函数名（如 `handleLogin()`）、行号范围、以及需要执行的具体操作（如「将第 15 行的 `==` 改为 `===`」「在 `X` 函数末尾添加空值检查」）。禁止模糊描述如「检查相关代码」「修复问题」。（必填，至少 1 步，最多 6 步）\n"
- "- roadmap: 如果 not_supported，描述实现路线；否则为空字符串\n"
- "- needs_human_followup: 仅当证据明显不足或问题涉及业务决策时设为 true（必填）\n"
- "- duplicate_confidence: 与已有 Issue 的重复程度 low/medium/high（必填）\n"
- '- duplicate_issues: 可能重复的 Issue 编号列表，格式如 ["#123"]（必填）\n'
- "- labels: 1-3 个标签，只能从 bug/enhancement/question/documentation/duplicate/help wanted/needs more info 中选择（必填）\n\n"
- "## 分析增强指引\n\n"
- "当「Enriched Context」部分提供以下信息时，你必须充分利用：\n\n"
- "1. **错误模式 (error_patterns)**：从 Issue 正文中提取的堆栈跟踪、错误消息、异常信息。"
- " 分析错误类型、发生位置、调用链路，定位根因。\n"
- "2. **代码块 (code_blocks_from_issue)**：Issue 中附带的代码片段。"
- " 检查代码逻辑问题、类型错误、API 误用等。\n"
- "3. **相关文件内容 (file_contents)**：仓库中与 Issue 相关的源代码文件。"
- " 逐文件分析代码逻辑，引用具体的函数名、行号和代码路径。\n"
- "4. **Git 历史 (git_history)**：相关文件的最近提交记录。"
- " 检查是否有最近的变更可能导致了问题，或已有修复但未发布。\n"
- "5. **仓库结构 (repo_structure)**：仓库顶层目录结构。"
- " 帮助判断 Issue 涉及的模块和组件。\n\n"
- "## 判断原则\n\n"
- "- 如果代码上下文中有明确的相关文件和逻辑，大胆给出分析和方案\n"
- "- analysis 中必须引用具体的文件路径（如 `packages/backend/src/auth/service.ts`）和函数名\n"
- "- solution 必须写成「AI 编程助手可直接执行」的粒度：文件路径 + 函数名 + 行号 + 具体修改内容 + 预期结果\n"
- "- actionable_steps 必须写成可直接执行的指令，每步包含：目标文件、定位方式（行号/函数名/代码模式）、具体操作、验证方式\n"
- "- workaround 必须提供用户可立即执行的临时规避方法，不依赖代码修改（如配置变更、环境变量、手动操作步骤）\n"
- "- 只有在完全无法判断时才设 needs_human_followup=true\n"
- "- labels 必须从允许的列表中选择，不要自创标签\n"
- "- 输出必须是严格 JSON，不要输出 markdown 或其他文本"
- )
- pathlib.Path('.ai_runtime/triage_system_prompt.txt').write_text(prompt, encoding='utf-8')
- PY
-
- python3 - <<'PY'
- import json, pathlib
- issue = json.loads(pathlib.Path('.ai_runtime/issue.json').read_text(encoding='utf-8'))
- rewrite_json = pathlib.Path('.ai_runtime/rewrite.json').read_text(encoding='utf-8')
- context = pathlib.Path('.ai_runtime/final_context.txt').read_text(encoding='utf-8') if pathlib.Path('.ai_runtime/final_context.txt').exists() else ''
- dupes = pathlib.Path('.ai_runtime/final_dupes.txt').read_text(encoding='utf-8') if pathlib.Path('.ai_runtime/final_dupes.txt').exists() else ''
- prs = pathlib.Path('.ai_runtime/final_prs.txt').read_text(encoding='utf-8') if pathlib.Path('.ai_runtime/final_prs.txt').exists() else ''
- commits = pathlib.Path('.ai_runtime/final_commits.txt').read_text(encoding='utf-8') if pathlib.Path('.ai_runtime/final_commits.txt').exists() else ''
-
- # 读取富化上下文
- enriched_str = ''
- enriched_path = pathlib.Path('.ai_runtime/enriched_context.json')
- if enriched_path.exists():
- enriched = json.loads(enriched_path.read_text(encoding='utf-8'))
- parts = []
- if enriched.get('error_patterns'):
- parts.append("[错误模式 - 从 Issue 提取]\n" + "\n---\n".join(enriched['error_patterns']))
- if enriched.get('code_blocks_from_issue'):
- parts.append("[Issue 中的代码块]\n" + "\n---\n".join(enriched['code_blocks_from_issue']))
- if enriched.get('file_contents'):
- fc_lines = []
- for fpath, content in enriched['file_contents'].items():
- fc_lines.append(f"### {fpath}\n```\n{content}\n```")
- parts.append("[相关文件内容]\n" + "\n\n".join(fc_lines))
- if enriched.get('git_history'):
- gh_lines = []
- for fpath, history in enriched['git_history'].items():
- gh_lines.append(f"### {fpath}\n" + "\n".join(history))
- parts.append("[文件 Git 历史]\n" + "\n\n".join(gh_lines))
- if enriched.get('repo_structure'):
- parts.append("[仓库结构]\n" + "\n".join(enriched['repo_structure']))
- enriched_str = "\n\n".join(parts)
-
- prompt = f"""[Issue]
- 标题：
- {issue.get('title','')}
-
- 正文：
- {issue.get('body','')}
-
- [Stage 1 Rewrite]
- {rewrite_json}
-
- [Retrieved Context]
- {context}
-
- [Enriched Context]
- {enriched_str}
-
- [Duplicate Candidates]
- {dupes}
-
- [PR Candidates]
- {prs}
-
- [Commit Candidates]
- {commits}"""
- pathlib.Path('.ai_runtime/triage_input_prompt.txt').write_text(prompt, encoding='utf-8')
- PY
-
- python3 - <<'PY'
- import json, os, pathlib, urllib.request, urllib.error
-
- base_url = os.environ['LLM_BASE_URL'].rstrip('/')
- api_key = os.environ['LLM_API_KEY']
- model = os.environ['LLM_MODEL']
- system_prompt = pathlib.Path('.ai_runtime/triage_system_prompt.txt').read_text(encoding='utf-8')
- input_prompt = pathlib.Path('.ai_runtime/triage_input_prompt.txt').read_text(encoding='utf-8')
- schema = json.loads(pathlib.Path('.ai_runtime/triage_schema.json').read_text(encoding='utf-8'))
-
- candidates = [
- (f"{base_url}/chat/completions", {
- "model": model,
- "temperature": 0.2,
- "response_format": {"type": "json_object"},
- "messages": [
- {"role": "system", "content": system_prompt + "\n你必须直接输出 JSON 对象，不要输出 markdown。"},
- {"role": "user", "content": input_prompt},
- ],
- }, 'chat_json'),
- (f"{base_url}/chat/completions", {
- "model": model,
- "temperature": 0.2,
- "messages": [
- {"role": "system", "content": system_prompt + "\n你必须直接输出 JSON 对象，不要输出 markdown 或代码块。"},
- {"role": "user", "content": input_prompt + "\n\n请直接输出 JSON，不要包含 ```json 代码块标记。"},
- ],
- }, 'chat_plain'),
- ]
-
- headers = {
- 'Authorization': f'Bearer {api_key}',
- 'Content-Type': 'application/json',
- 'Accept': 'application/json',
- 'User-Agent': 'github-actions-ai-triage/1.0',
- }
-
- last_err = None
- content = ''
- mode_used = ''
- required_fields = {"summary", "classification", "support_status", "analysis", "solution",
- "error_pattern_summary", "related_files", "actionable_steps",
- "needs_human_followup", "duplicate_confidence", "duplicate_issues", "labels"}
-
- def validate_triage(s):
- """检查内容是否包含 triage 必需字段"""
- try:
- obj = json.loads(s) if isinstance(s, str) else s
- return required_fields.issubset(set(obj.keys()))
- except Exception:
- return False
-
- # 最多重试 2 次（首次 + 1 次重试）
- for attempt in range(2):
- for url, payload, mode in candidates:
- # 重试时加入更明确的格式要求
- if attempt > 0:
- extra = "\n\n重要：你必须输出包含以下全部字段的 JSON：summary, classification, support_status, analysis, solution, error_pattern_summary, related_files, actionable_steps, needs_human_followup, duplicate_confidence, duplicate_issues, labels。缺少任何字段都会导致解析失败。"
- payload = dict(payload)
- msgs = [dict(m) for m in payload['messages']]
- msgs[-1] = dict(msgs[-1])
- msgs[-1]['content'] = msgs[-1].get('content', '') + extra
- payload['messages'] = msgs
-
- data = json.dumps(payload, ensure_ascii=False).encode('utf-8')
- req = urllib.request.Request(url, data=data, headers=headers, method='POST')
- try:
- with urllib.request.urlopen(req, timeout=240) as resp:
- text = resp.read().decode('utf-8', errors='replace')
- obj = json.loads(text)
- raw = ((obj.get('choices') or [{}])[0].get('message') or {}).get('content') or ''
- # 尝试从 markdown 代码块中提取 JSON
- if raw and not raw.strip().startswith('{'):
- import re
- m = re.search(r'```(?:json)?\s*\n?(.*?)\n?```', raw, re.S)
- if m:
- raw = m.group(1).strip()
- if raw and validate_triage(raw):
- content = raw
- mode_used = mode
- pathlib.Path('.ai_runtime/triage_raw.txt').write_text(content, encoding='utf-8')
- break
- elif raw:
- last_err = f'LLM 返回内容缺少必需字段: {required_fields - set(json.loads(raw).keys()) if isinstance(raw, str) else "parse error"}'
- except urllib.error.HTTPError as e:
- err_body = e.read().decode('utf-8', errors='replace')[:500]
- last_err = f'HTTP {e.code}: {err_body}'
- print(f'[attempt {attempt+1}] {mode} 失败: {last_err}')
- import time; time.sleep(2)
- except Exception as e:
- last_err = e
- print(f'[attempt {attempt+1}] {mode} 异常: {e}')
- if content:
- break
- print(f'第 {attempt+1} 次尝试未通过验证，准备重试...')
-
- if not content:
- raise RuntimeError(f'LLM triage call failed after retries: {last_err}')
-
- pathlib.Path('.ai_runtime/issue_response.txt').write_text(content, encoding='utf-8')
- with open(os.environ['GITHUB_OUTPUT'], 'a', encoding='utf-8') as f:
- f.write(f'mode_used={mode_used}\n')
- PY
-
- python3 .github/scripts/write_output.py issue_response .ai_runtime/issue_response.txt
-
- - name: Normalize triage result
- id: triage_norm
- shell: bash
- run: |
- set -euo pipefail
-
- cat > .ai_runtime/triage_raw.txt <<'EOF'
- ${{ steps.triage.outputs.issue_response }}
- EOF
-
- python3 - <<'PY'
- import json, pathlib, re
-
- raw = pathlib.Path(".ai_runtime/triage_raw.txt").read_text(encoding="utf-8", errors="ignore").strip()
-
- def parse_json(s):
- try:
- return json.loads(s)
- except Exception:
- m = re.search(r'\{.*\}', s, flags=re.S)
- return json.loads(m.group(0)) if m else {}
-
- d = parse_json(raw) if raw else {}
-
- allowed_labels = {"bug","enhancement","question","documentation","duplicate","help wanted","needs more info"}
- allowed_class = {"bug","enhancement","question","documentation","needs_more_info"}
- allowed_support = {"supported","partially_supported","not_supported","already_fixed_unreleased","needs_more_info"}
- allowed_dup = {"low","medium","high"}
-
- def s(v, default=""):
- return v if isinstance(v, str) else default
-
- def b(v, default=False):
- return v if isinstance(v, bool) else default
-
- def arr(v):
- return v if isinstance(v, list) else []
-
- labels = []
- seen = set()
- for x in arr(d.get("labels")):
- if isinstance(x, str):
- t = x.strip().lower()
- if t in allowed_labels and t not in seen:
- labels.append(t)
- seen.add(t)
-
- classification = s(d.get("classification"), "needs_more_info")
- if classification not in allowed_class:
- classification = "needs_more_info"
-
- if classification != "needs_more_info" and classification not in labels and len(labels) < 3:
- labels.insert(0, classification)
-
- result = {
- "summary": s(d.get("summary"), "AI 未能稳定生成摘要。"),
- "classification": classification,
- "support_status": s(d.get("support_status"), "needs_more_info"),
- "analysis": s(d.get("analysis"), "AI 未能稳定生成分析，请维护者人工复核。"),
- "solution": s(d.get("solution"), "暂无稳定自动建议。"),
- "workaround": s(d.get("workaround"), ""),
- "error_pattern_summary": s(d.get("error_pattern_summary"), ""),
- "related_files": [x.strip() for x in arr(d.get("related_files")) if isinstance(x, str) and x.strip()][:8],
- "actionable_steps": [x.strip() for x in arr(d.get("actionable_steps")) if isinstance(x, str) and x.strip()][:6],
- "roadmap": s(d.get("roadmap"), ""),
- "needs_human_followup": b(d.get("needs_human_followup"), False),
- "duplicate_confidence": s(d.get("duplicate_confidence"), "low"),
- "duplicate_issues": [x.strip() for x in arr(d.get("duplicate_issues")) if isinstance(x, str) and re.fullmatch(r"#\d+", x.strip())],
- "labels": labels[:3]
- }
-
- # 分析或方案为 fallback 默认值时，自动标记需要人工复核
- if result["analysis"] == "AI 未能稳定生成分析，请维护者人工复核。" or \
- result["solution"] == "暂无稳定自动建议。":
- result["needs_human_followup"] = True
-
- if result["support_status"] not in allowed_support:
- result["support_status"] = "needs_more_info"
- if result["duplicate_confidence"] not in allowed_dup:
- result["duplicate_confidence"] = "low"
- if result["duplicate_confidence"] == "high" and result["duplicate_issues"] and "duplicate" not in result["labels"] and len(result["labels"]) < 3:
- result["labels"].append("duplicate")
-
- pathlib.Path(".ai_runtime/triage.json").write_text(
- json.dumps(result, ensure_ascii=False, indent=2),
- encoding="utf-8"
- )
- print(json.dumps(result, ensure_ascii=False))
- PY
-
- echo "json=$(cat .ai_runtime/triage.json | jq -c .)" >> "$GITHUB_OUTPUT"
-
- - name: Create or update AI comment and labels
- uses: actions/github-script@v7
- env:
- AI_AUTO_LABEL: ${{ env.AI_AUTO_LABEL }}
- RESULT_JSON: ${{ steps.triage_norm.outputs.json }}
- ISSUE_NUMBER: ${{ steps.issue.outputs.issue_number }}
- with:
- script: |
- const marker = "";
- const result = JSON.parse(process.env.RESULT_JSON || "{}");
- const owner = context.repo.owner;
- const repo = context.repo.repo;
- const issue_number = parseInt(process.env.ISSUE_NUMBER, 10) || context.issue.number;
-
- function supportText(s) {
- switch (s) {
- case "supported":
- return "✅ 当前仓库上下文显示：该行为已支持。";
- case "partially_supported":
- return "🟡 当前仓库上下文显示：该行为仅部分支持。";
- case "not_supported":
- return "⚠️ 当前仓库上下文显示：当前暂不支持。";
- case "already_fixed_unreleased":
- return "🛠️ 当前仓库上下文显示：可能已修复，但未正式发布。";
- default:
- return "❓ 当前证据不足，需要更多信息。";
- }
- }
-
- function classificationEmoji(c) {
- switch (c) {
- case "bug": return "🐛";
- case "enhancement": return "✨";
- case "question": return "❓";
- case "documentation": return "📝";
- default: return "🔍";
- }
- }
-
- const lines = [
- marker,
- "### 🤖 AI Issue 智能分析",
- "",
- `> **分类**: ${classificationEmoji(result.classification)} ${result.classification || "unknown"} | **状态**: ${supportText(result.support_status)}`,
- "",
- "---",
- "",
- "#### 📋 摘要",
- result.summary || "暂无",
- ""
- ];
-
- // 错误模式分析（仅 bug 类型显示）
- if (result.error_pattern_summary && result.classification === "bug") {
- lines.push("#### 🔍 错误模式");
- lines.push(result.error_pattern_summary);
- lines.push("");
- }
-
- // 相关文件
- if (Array.isArray(result.related_files) && result.related_files.length > 0) {
- lines.push("#### 📁 相关文件");
- for (const f of result.related_files) {
- lines.push(`- \`${f}\``);
- }
- lines.push("");
- }
-
- lines.push("#### 🔬 分析");
- lines.push(result.analysis || "暂无");
- lines.push("");
-
- lines.push("#### 💡 建议方案");
- lines.push(result.solution || "暂无");
- lines.push("");
-
- // 临时解决方案（workaround）
- if (result.workaround) {
- lines.push("#### 🩹 临时解决方案");
- lines.push(result.workaround);
- lines.push("");
- }
-
- // 可执行步骤
- if (Array.isArray(result.actionable_steps) && result.actionable_steps.length > 0) {
- lines.push("#### 🎯 可执行步骤");
- for (let i = 0; i < result.actionable_steps.length; i++) {
- lines.push(`${i + 1}. ${result.actionable_steps[i]}`);
- }
- lines.push("");
- }
-
- if (result.roadmap && result.support_status === "not_supported") {
- lines.push("#### 🗺️ 实现路线");
- lines.push(result.roadmap);
- lines.push("");
- }
-
- if (Array.isArray(result.duplicate_issues) && result.duplicate_issues.length > 0) {
- lines.push("#### 🔗 可能重复的 Issue");
- lines.push(`- **置信度**: ${result.duplicate_confidence || "low"}`);
- lines.push(`- **候选**: ${result.duplicate_issues.join("、")}`);
- lines.push("");
- }
-
- if (result.needs_human_followup) {
- lines.push("#### ⚠️ 维护建议");
- lines.push("建议维护者人工复核后再做最终结论。");
- lines.push("");
- }
-
- lines.push("---");
- lines.push("");
- lines.push("📌 使用说明
");
- lines.push("");
- lines.push("| 操作 | 方法 |");
- lines.push("|------|------|");
- lines.push("| 🔄 重新分析 | 在评论区输入 `/ai-analyze` |");
- lines.push("| 🏷️ 自动标签 | 分析结果会自动添加分类标签 |");
- lines.push("| ⚠️ 需人工复核 | 低置信度分析会自动标记 `needs-review` |");
- lines.push("| 🔗 重复检测 | 自动搜索相似 Issue 并关联 |");
- lines.push("");
- lines.push(" ");
- lines.push("");
- lines.push("_🤖 此评论由 AI 自动化工作流生成 | 结构化输出 + 新评论模式 + 标签白名单 + 代码上下文检索 + 错误模式分析 + AI Agent 可消费方案_");
-
- const body = lines.join("\n");
-
- // 始终创建新评论（不再编辑旧评论，保留历史分析记录）
- const comments = await github.paginate(
- github.rest.issues.listComments,
- { owner, repo, issue_number, per_page: 100 }
- );
-
- const existing = comments.find(
- c => typeof c.body === "string" && c.body.includes(marker)
- );
-
- await github.rest.issues.createComment({
- owner,
- repo,
- issue_number,
- body
- });
-
- if (process.env.AI_AUTO_LABEL === "true") {
- const issue = await github.rest.issues.get({
- owner,
- repo,
- issue_number
- });
-
- const existingLabels = new Set(
- (issue.data.labels || []).map(l => typeof l === "string" ? l : l.name)
- );
-
- const allowed = new Set([
- "bug",
- "enhancement",
- "question",
- "documentation",
- "duplicate",
- "help wanted",
- "needs more info",
- "needs-review"
- ]);
-
- // AI 管理的标签：重新分析时先移除这些旧标签
- const aiManagedLabels = [
- "bug", "enhancement", "question", "documentation",
- "duplicate", "needs more info", "needs-review"
- ];
-
- // 重新分析时移除旧的 AI 管理标签（无论是否有旧评论）
- const toRemove = aiManagedLabels.filter(x => existingLabels.has(x));
- if (toRemove.length > 0) {
- try {
- await github.rest.issues.removeLabel({
- owner,
- repo,
- issue_number,
- name: toRemove
- });
- } catch (e) {
- // 部分标签可能不存在，忽略错误
- }
- }
-
- // 计算新标签
- const desired = Array.isArray(result.labels) ? result.labels : [];
- let toAdd = desired
- .map(x => String(x).trim().toLowerCase())
- .filter(x => allowed.has(x))
- .filter((x, i, arr) => arr.indexOf(x) === i);
-
- // 置信度阈值：低置信度时添加 needs-review
- if (result.needs_human_followup) {
- if (!toAdd.includes("needs more info")) {
- toAdd.push("needs-review");
- }
- }
-
- // 过滤掉已存在的
- toAdd = toAdd.filter(x => !existingLabels.has(x));
-
- if (toAdd.length > 0) {
- await github.rest.issues.addLabels({
- owner,
- repo,
- issue_number,
- labels: toAdd
- });
- }
- }
-
- - name: Step summary
- if: always()
- shell: bash
- run: |
- {
- echo "## AI Issue Smart Reply"
- echo ""
- echo "- Issue: #$(jq -r '.number' .ai_runtime/issue.json 2>/dev/null || echo 'unknown')"
- echo "- Auto label: ${AI_AUTO_LABEL}"
- echo "- Duplicate check: ${AI_ENABLE_DUPLICATE_CHECK}"
- echo "- PR search: ${AI_ENABLE_PR_SEARCH}"
- echo "- Commit search: ${AI_ENABLE_COMMIT_SEARCH}"
- echo ""
- echo "### Rewrite"
- echo '```json'
- cat .ai_runtime/rewrite.json 2>/dev/null || echo '{}'
- echo '```'
- echo ""
- echo "### Enriched Context"
- echo '```json'
- python3 -c "
- import json, pathlib
- p = pathlib.Path('.ai_runtime/enriched_context.json')
- if p.exists():
- d = json.loads(p.read_text())
- print(json.dumps({
- 'error_patterns': len(d.get('error_patterns', [])),
- 'file_contents': list(d.get('file_contents', {}).keys()),
- 'git_history': list(d.get('git_history', {}).keys()),
- }, ensure_ascii=False, indent=2))
- else:
- print('{}')
- " 2>/dev/null || echo '{}'
- echo '```'
- echo ""
- echo "### Triage"
- echo '```json'
- cat .ai_runtime/triage.json 2>/dev/null || echo '{}'
- echo '```'
- } >> "$GITHUB_STEP_SUMMARY"
diff --git a/.github/workflows/nomore-spam.yml b/.github/workflows/nomore-spam.yml
new file mode 100644
index 0000000..fc3f0e0
--- /dev/null
+++ b/.github/workflows/nomore-spam.yml
@@ -0,0 +1,30 @@
+name: NoMore Spam
+
+on:
+ issues:
+ types: [opened]
+ pull_request_target:
+ types: [opened]
+
+permissions:
+ contents: read
+ issues: write
+ pull-requests: write
+ models: read
+
+jobs:
+ spam-detection:
+ runs-on: ubuntu-latest
+
+ steps:
+ - name: Detect and close spam
+ uses: JohnsonRan/nomore-spam@main
+ with:
+ github-token: ${{ github.token }}
+ ai-base-url: ${{ secrets.AI_BASE_URL }} # 可选：自定义API端点（去除 /chat/completions）
+ ai-api-key: ${{ secrets.AI_API_KEY }} # 可选：自定义API密钥
+ ai-model: ${{ secrets.AI_MODEL }} # 可选：自定义模型名称
+ labels: 'bug,enhancement,question'
+ analyze-file-changes: 'true'
+ max-analysis-depth: 'normal'
+ blacklist: ${{ secrets.BLACKLIST }} # 可选：黑名单用户列表
\ No newline at end of file