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| Author | SHA1 | Date | |
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| 087ad77f39 | |||
| 92d3e76d44 | |||
| 8069fc2f8a | |||
| af361d7fc7 | |||
| a2fabcc7a6 | |||
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| 2ed36c0013 | |||
| cd721634dd | |||
| 2e36710813 |
@@ -3,23 +3,23 @@ name: QE Acceptance Tests
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on:
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on:
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workflow_dispatch:
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workflow_dispatch:
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inputs:
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inputs:
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prd_path:
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description: 'Path to .docx PRD file (absolute)'
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required: false
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default: ''
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parsed_path:
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description: 'Path to pre-parsed _updated.json (skip doc_parser if set)'
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required: false
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default: ''
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acceptance_runs:
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acceptance_runs:
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description: 'Layer B stability runs (1 = skip stability testing)'
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description: 'Layer B stability runs (1 = skip)'
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required: false
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required: false
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default: '1'
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default: '1'
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ir_path:
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description: 'Path to IR JSON file (relative to workspace)'
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required: false
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default: 'output/ir_final.json'
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parsed_path:
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description: 'Path to _parsed.json or _updated.json (relative to workspace)'
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required: false
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default: 'output/车机娱乐系统禁止功能文档_精简_updated.json'
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jobs:
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jobs:
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acceptance:
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acceptance:
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runs-on: shell
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runs-on: shell
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timeout-minutes: 30
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timeout-minutes: 60
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steps:
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steps:
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- name: Checkout main branch
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- name: Checkout main branch
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run: |
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run: |
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@@ -29,26 +29,34 @@ jobs:
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- name: Install dependencies
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- name: Install dependencies
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run: pip install -r requirements.txt
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run: pip install -r requirements.txt
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- name: Run QE Acceptance Tests
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- name: Run pipeline + acceptance tests
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run: >-
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run: |
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python -m pytest tests/acceptance/ -v
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if [ -n "${{ github.event.inputs.prd_path }}" ]; then
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--run-acceptance
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python scripts/run_pipeline.py --input "${{ github.event.inputs.prd_path }}" --test
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--acceptance-runs=${{ github.event.inputs.acceptance_runs }}
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elif [ -n "${{ github.event.inputs.parsed_path }}" ]; then
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--ir-path=${{ github.event.inputs.ir_path }}
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python scripts/run_pipeline.py --parsed "${{ github.event.inputs.parsed_path }}" --test
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--parsed-path=${{ github.event.inputs.parsed_path }}
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else
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--tb=long
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# No input provided — run acceptance on existing output if present
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python -m pytest tests/acceptance/ -v --run-acceptance \
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--acceptance-runs=${{ github.event.inputs.acceptance_runs }} --tb=short
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fi
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env:
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env:
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DASHSCOPE_API_KEY: ${{ secrets.DASHSCOPE_API_KEY }}
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DASHSCOPE_API_KEY: ${{ secrets.DASHSCOPE_API_KEY }}
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DEEPSEEK_API_KEY: ${{ secrets.DEEPSEEK_API_KEY }}
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- name: Create issue on failure
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- name: Create issue on failure
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if: failure()
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if: failure()
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env:
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env:
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GITEA_API_TOKEN: ${{ secrets.GITEA_TOKEN }}
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GITEA_API_TOKEN: ${{ secrets.GITEA_TOKEN }}
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run: >-
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run: |
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python scripts/create_failure_issue.py
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# Read acceptance report summary if it exists
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--sha "${{ github.sha }}"
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if [ -f acceptance-report.json ]; then
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--branch "main"
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SUMMARY=$(python -c "import json; r=json.load(open('acceptance-report.json')); print(r.get('final_verdict','?'))")
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--run "${{ github.run_number }}"
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DETAILS=$(python -c "import json; r=json.load(open('acceptance-report.json')); fd=r.get('failure_details',[]); print('\\n'.join(f'- {d}' for d in fd) if fd else '')")
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--message "QE Acceptance Tests Failed"
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fi
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--workflow "QE Acceptance"
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python scripts/create_failure_issue.py \
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--sha "${{ github.sha }}" --branch "main" \
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--run "${{ github.run_number }}" \
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--message "QE Acceptance: ${SUMMARY:-pipeline failed}" \
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--workflow "QE Acceptance" \
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--labels "acceptance-failure,agent-task"
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--labels "acceptance-failure,agent-task"
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@@ -7,6 +7,19 @@ description: QE Agent — 自动化验收测试开发与质量门禁。轮询 Gi
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|
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你是 QE(质量工程)代理,专注于 **main branch 的发布质量**。你的工作是:根据 Gitea 上的 `test-dev` issue 开发新的验收测试,确保测试通过 CI,并推进到 main branch。
|
你是 QE(质量工程)代理,专注于 **main branch 的发布质量**。你的工作是:根据 Gitea 上的 `test-dev` issue 开发新的验收测试,确保测试通过 CI,并推进到 main branch。
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## 启动行为
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**每次新 session 启动时,立即执行**:
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1. 设好环境变量(见下方"环境要求")
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2. 用 `/loop 10m` 开启 10 分钟间隔的自动轮询
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3. 轮询内容:`agent_poller.py --action list --labels test-dev` 和 `--labels acceptance-failure`
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4. 有 issue → 走完整闭环处理(Step 2-8)
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5. 无 issue → 简短报告 "main healthy",等待下次轮询
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6. 同时保持对话开放,随时响应用户指令
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这样 QE-Agent 真正做到 **"默认轮询 + 随时互动"**。
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## 环境要求
|
## 环境要求
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|
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开始工作前,确认以下环境变量已设置:
|
开始工作前,确认以下环境变量已设置:
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@@ -0,0 +1,183 @@
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#!/usr/bin/env python3
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"""End-to-end pipeline runner for QE acceptance testing.
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Runs the complete document_analyzer pipeline:
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1. doc_parser (docx → _parsed.json, if .docx provided)
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2. ir_generation steps (parsed JSON → ir_final.json + audit report)
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3. QE acceptance tests (optional, if --test flag)
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Usage:
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python scripts/run_pipeline.py --input <path.docx> # full pipeline
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python scripts/run_pipeline.py --parsed <_updated.json> # skip doc_parser
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python scripts/run_pipeline.py --parsed <_updated.json> --test # pipeline + acceptance tests
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Outputs are placed in output/ matching the project config.py structure:
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output/final/ir_final.json
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output/final/ir_audit_report.md
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acceptance-report.json (if --test)
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"""
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from __future__ import annotations
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import argparse
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import os
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import subprocess
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import sys
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import json
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from pathlib import Path
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PROJECT_ROOT = Path(__file__).resolve().parent.parent
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sys.path.insert(0, str(PROJECT_ROOT / "skills" / "ir_generation_skill"))
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sys.path.insert(0, str(PROJECT_ROOT / "skills" / "doc_parser_skill" / "scripts"))
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import config
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# ── Stage 1: Document Parsing ────────────────────────────────────────────────
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def run_doc_parser(docx_path: str, output_dir: str) -> str | None:
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"""Run doc_parser on a .docx file. Returns path to _parsed.json or None."""
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from doc_parser import parse_document
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print(f"[1/3] Parsing document: {docx_path}")
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result = parse_document(docx_path, output_dir, dry_run=False)
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# parse_document returns {source, sections, image_sources, image_analysis}
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# Output is saved as <basename>_parsed.json in output_dir
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basename = os.path.splitext(os.path.basename(docx_path))[0]
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parsed_path = os.path.join(output_dir, f"{basename}_parsed.json")
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if os.path.isfile(parsed_path):
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print(f" → {parsed_path}")
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return parsed_path
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print(f" [FAIL] doc_parser output not found: {parsed_path}", file=sys.stderr)
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return None
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|
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||||||
|
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||||||
|
# ── Stage 2: IR Generation ───────────────────────────────────────────────────
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|
|
||||||
|
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def run_ir_pipeline(parsed_path: str) -> str | None:
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|
"""Run the ir_generation steps. Returns path to ir_final.json or None."""
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os.makedirs(config.PROJECT_OUTPUT, exist_ok=True)
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os.makedirs(config.IR_OUTPUT, exist_ok=True)
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os.makedirs(config.FINAL_OUTPUT, exist_ok=True)
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env = os.environ.copy()
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env["IR_INPUT_JSON"] = parsed_path
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|
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steps = [
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|
("step1_semantic_index.py", "Semantic Index"),
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("step2_ir_extraction.py", "IR Extraction"),
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("step2_5_branch_coverage.py", "Branch Coverage"),
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||||||
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("step3_merge_and_audit.py", "Merge & Audit"),
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|
]
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|
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print(f"[2/3] Generating IR from: {parsed_path}")
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|
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||||||
|
for script, label in steps:
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|
script_path = PROJECT_ROOT / "skills" / "ir_generation_skill" / script
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||||||
|
if not script_path.exists():
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print(f" [FAIL] Missing: {script}", file=sys.stderr)
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|
continue
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|
|
||||||
|
print(f" Running {script} ({label})...")
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|
result = subprocess.run(
|
||||||
|
[sys.executable, str(script_path)],
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||||||
|
cwd=str(PROJECT_ROOT),
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||||||
|
capture_output=True, text=True,
|
||||||
|
env=env,
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||||||
|
)
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||||||
|
if result.returncode != 0:
|
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|
print(f" [FAIL] {script} failed (exit {result.returncode})", file=sys.stderr)
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|
print(result.stderr[-500:], file=sys.stderr)
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|
else:
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|
# Print last line of stdout for brief progress
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|
lines = result.stdout.strip().split("\n")
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|
last = lines[-1] if lines else "done"
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|
print(f" [OK] {label}: {last[:120]}")
|
||||||
|
|
||||||
|
if os.path.isfile(config.IR_FINAL_JSON):
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|
print(f" → {config.IR_FINAL_JSON}")
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|
return config.IR_FINAL_JSON
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||||||
|
|
||||||
|
print(" [FAIL] IR generation did not produce ir_final.json", file=sys.stderr)
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||||||
|
return None
|
||||||
|
|
||||||
|
|
||||||
|
# ── Stage 3: Acceptance Tests ────────────────────────────────────────────────
|
||||||
|
|
||||||
|
|
||||||
|
def run_acceptance_tests(parsed_json_path: str) -> int:
|
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|
"""Run QE acceptance tests. Returns pytest exit code."""
|
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|
print("[3/3] Running QE acceptance tests...")
|
||||||
|
|
||||||
|
test_dir = PROJECT_ROOT / "tests" / "acceptance"
|
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|
result = subprocess.run(
|
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|
[
|
||||||
|
sys.executable, "-m", "pytest", str(test_dir),
|
||||||
|
"-v", "--run-acceptance",
|
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|
"--ir-path", config.IR_FINAL_JSON,
|
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|
"--parsed-path", parsed_json_path,
|
||||||
|
"--tb=short",
|
||||||
|
],
|
||||||
|
cwd=str(PROJECT_ROOT),
|
||||||
|
)
|
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|
return result.returncode
|
||||||
|
|
||||||
|
|
||||||
|
# ── Main ─────────────────────────────────────────────────────────────────────
|
||||||
|
|
||||||
|
|
||||||
|
def main():
|
||||||
|
parser = argparse.ArgumentParser(description="Run the full document_analyzer pipeline")
|
||||||
|
parser.add_argument("--input", help="Path to .docx PRD file")
|
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|
parser.add_argument("--parsed", help="Path to pre-parsed _updated.json (skip doc_parser)")
|
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|
parser.add_argument("--test", action="store_true", help="Run acceptance tests after pipeline")
|
||||||
|
parser.add_argument("--output-dir", default=None, help="Output directory (default: output/)")
|
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|
args = parser.parse_args()
|
||||||
|
|
||||||
|
parsed_path = args.parsed
|
||||||
|
|
||||||
|
# Stage 1: doc_parser
|
||||||
|
if args.input:
|
||||||
|
docx = args.input
|
||||||
|
if not os.path.isfile(docx):
|
||||||
|
print(f"Error: Input file not found: {docx}", file=sys.stderr)
|
||||||
|
sys.exit(1)
|
||||||
|
out_dir = args.output_dir or str(PROJECT_ROOT / "output")
|
||||||
|
parsed_path = run_doc_parser(docx, out_dir)
|
||||||
|
if not parsed_path:
|
||||||
|
print("\n[FAIL] Pipeline blocked at Stage 1 (doc_parser)", file=sys.stderr)
|
||||||
|
# Create tracking issue for dev-agent
|
||||||
|
_maybe_create_blocking_issue("doc_parser", f"Input: {docx}")
|
||||||
|
sys.exit(1)
|
||||||
|
|
||||||
|
if not parsed_path:
|
||||||
|
print("Error: Either --input or --parsed is required", file=sys.stderr)
|
||||||
|
sys.exit(1)
|
||||||
|
|
||||||
|
if not os.path.isfile(parsed_path):
|
||||||
|
print(f"Error: Parsed JSON not found: {parsed_path}", file=sys.stderr)
|
||||||
|
sys.exit(1)
|
||||||
|
|
||||||
|
# Stage 2: IR generation
|
||||||
|
ir_path = run_ir_pipeline(parsed_path)
|
||||||
|
if not ir_path:
|
||||||
|
print("\n[FAIL] Pipeline blocked at Stage 2 (ir_generation)", file=sys.stderr)
|
||||||
|
_maybe_create_blocking_issue("ir_generation", f"Parsed: {parsed_path}")
|
||||||
|
sys.exit(1)
|
||||||
|
|
||||||
|
print(f"\n[OK] Pipeline complete: {ir_path}")
|
||||||
|
|
||||||
|
# Stage 3: Acceptance tests
|
||||||
|
if args.test:
|
||||||
|
exit_code = run_acceptance_tests(parsed_path)
|
||||||
|
sys.exit(exit_code)
|
||||||
|
|
||||||
|
|
||||||
|
def _maybe_create_blocking_issue(stage: str, detail: str):
|
||||||
|
"""Notify about a pipeline blockage. The acceptance CI will create the issue."""
|
||||||
|
print(f"\n⚠ Stage '{stage}' failed. CI will create an acceptance-failure issue.", file=sys.stderr)
|
||||||
|
|
||||||
|
|
||||||
|
if __name__ == "__main__":
|
||||||
|
main()
|
||||||
@@ -37,8 +37,9 @@ case "$MODE" in
|
|||||||
;;
|
;;
|
||||||
3)
|
3)
|
||||||
echo ""
|
echo ""
|
||||||
echo "启动交互模式..."
|
echo "启动交互模式 (默认 10 分钟轮询)..."
|
||||||
echo "进入后输入: 检查 Gitea test-dev Issues 并处理"
|
echo "按 Ctrl+C 停止"
|
||||||
|
echo ""
|
||||||
echo "可用命令速查:"
|
echo "可用命令速查:"
|
||||||
echo " agent_poller.py --action list --labels test-dev"
|
echo " agent_poller.py --action list --labels test-dev"
|
||||||
echo " agent_poller.py --action list --labels acceptance-failure"
|
echo " agent_poller.py --action list --labels acceptance-failure"
|
||||||
|
|||||||
@@ -34,12 +34,21 @@ def set_input_file(path: str) -> None:
|
|||||||
global INPUT_JSON
|
global INPUT_JSON
|
||||||
INPUT_JSON = path
|
INPUT_JSON = path
|
||||||
|
|
||||||
# Secrets file (shared with workspace-document-analyzer)
|
# Secrets file — searched in order of priority:
|
||||||
# .openclaw/workspace/skills/ir_generation_new_skill -> .openclaw/workspace-document-analyzer
|
# 1. IR_SECRETS_PATH env var
|
||||||
OPENCLAW_HOME = os.path.dirname(os.path.dirname(WORKSPACE_DIR))
|
# 2. ~/.openclaw/config/secrets.yaml
|
||||||
SECRETS_YAML = os.path.join(
|
# 3. ~/.openclaw/workspace-document-analyzer/config/secrets.yaml
|
||||||
OPENCLAW_HOME, "workspace-document-analyzer", "config", "secrets.yaml",
|
_SECRETS_CANDIDATES = [
|
||||||
)
|
os.path.join(os.path.expanduser("~"), ".openclaw", "config", "secrets.yaml"),
|
||||||
|
os.path.join(os.path.expanduser("~"), ".openclaw", "workspace-document-analyzer",
|
||||||
|
"config", "secrets.yaml"),
|
||||||
|
]
|
||||||
|
|
||||||
|
_SECRETS_PATH = os.environ.get("IR_SECRETS_PATH", "")
|
||||||
|
if _SECRETS_PATH:
|
||||||
|
_SECRETS_CANDIDATES.insert(0, _SECRETS_PATH)
|
||||||
|
|
||||||
|
SECRETS_YAML = _SECRETS_CANDIDATES[0] # primary path (backward compat)
|
||||||
|
|
||||||
# Intermediate outputs (all under PROJECT_OUTPUT/ir/)
|
# Intermediate outputs (all under PROJECT_OUTPUT/ir/)
|
||||||
SEMANTIC_INDEX_R1_JSON = os.path.join(IR_OUTPUT, "semantic_index_r1.json")
|
SEMANTIC_INDEX_R1_JSON = os.path.join(IR_OUTPUT, "semantic_index_r1.json")
|
||||||
@@ -84,10 +93,14 @@ ENSEMBLE_TEMPERATURES = [
|
|||||||
def _load_secrets() -> dict[str, dict[str, str]]:
|
def _load_secrets() -> dict[str, dict[str, str]]:
|
||||||
"""Load provider credentials from secrets.yaml.
|
"""Load provider credentials from secrets.yaml.
|
||||||
|
|
||||||
|
Tries paths in order: IR_SECRETS_PATH env var → ~/.openclaw/config/ →
|
||||||
|
~/.openclaw/workspace-document-analyzer/config/.
|
||||||
|
|
||||||
Returns a dict like: {"deepseek": {"apiKey": "...", "baseUrl": "..."}, ...}
|
Returns a dict like: {"deepseek": {"apiKey": "...", "baseUrl": "..."}, ...}
|
||||||
"""
|
"""
|
||||||
if os.path.isfile(SECRETS_YAML):
|
for p in _SECRETS_CANDIDATES:
|
||||||
with open(SECRETS_YAML, "r", encoding="utf-8") as f:
|
if os.path.isfile(p):
|
||||||
|
with open(p, "r", encoding="utf-8") as f:
|
||||||
return yaml.safe_load(f) or {}
|
return yaml.safe_load(f) or {}
|
||||||
return {}
|
return {}
|
||||||
|
|
||||||
@@ -108,9 +121,11 @@ def _get_provider_config(provider: str) -> dict[str, str]:
|
|||||||
)
|
)
|
||||||
|
|
||||||
if not api_key:
|
if not api_key:
|
||||||
|
tried_paths = "\n ".join(_SECRETS_CANDIDATES)
|
||||||
raise RuntimeError(
|
raise RuntimeError(
|
||||||
f"No API key found for provider '{provider}'. "
|
f"No API key found for provider '{provider}'.\n"
|
||||||
f"Check {SECRETS_YAML} or set {env_prefix}_API_KEY."
|
f"Tried secrets.yaml paths:\n {tried_paths}\n"
|
||||||
|
f"Or set {env_prefix}_API_KEY environment variable."
|
||||||
)
|
)
|
||||||
return {"apiKey": api_key, "baseUrl": base_url}
|
return {"apiKey": api_key, "baseUrl": base_url}
|
||||||
|
|
||||||
|
|||||||
@@ -548,11 +548,20 @@ def call_llm(prompt: str, max_retries: int = 2,
|
|||||||
Args:
|
Args:
|
||||||
temperature: Override config.TEMPERATURE. If None, uses config default.
|
temperature: Override config.TEMPERATURE. If None, uses config default.
|
||||||
"""
|
"""
|
||||||
|
import sys as _sys
|
||||||
|
|
||||||
|
try:
|
||||||
client = config.llm_client()
|
client = config.llm_client()
|
||||||
|
except Exception as e:
|
||||||
|
print(f" LLM 客户端初始化失败: {e}", file=_sys.stderr)
|
||||||
|
print(f" 请检查: IR_PROVIDER={config.LLM_PROVIDER}, secrets.yaml 或环境变量", file=_sys.stderr)
|
||||||
|
raise
|
||||||
|
|
||||||
temp = temperature if temperature is not None else config.TEMPERATURE
|
temp = temperature if temperature is not None else config.TEMPERATURE
|
||||||
|
|
||||||
for attempt in range(max_retries + 1):
|
for attempt in range(max_retries + 1):
|
||||||
print(f" LLM 调用 T={temp} (尝试 {attempt + 1}/{max_retries + 1})...", flush=True)
|
print(f" LLM 调用 model={config.MODEL_NAME} T={temp} "
|
||||||
|
f"(尝试 {attempt + 1}/{max_retries + 1})...", flush=True)
|
||||||
try:
|
try:
|
||||||
resp = client.chat.completions.create(
|
resp = client.chat.completions.create(
|
||||||
model=config.MODEL_NAME,
|
model=config.MODEL_NAME,
|
||||||
@@ -568,17 +577,31 @@ def call_llm(prompt: str, max_retries: int = 2,
|
|||||||
)
|
)
|
||||||
content = resp.choices[0].message.content
|
content = resp.choices[0].message.content
|
||||||
if content is None:
|
if content is None:
|
||||||
raise RuntimeError("LLM returned empty response")
|
raise RuntimeError(
|
||||||
|
"LLM 返回空响应 (content=None)。可能是 API 配额不足或模型不可用。"
|
||||||
|
)
|
||||||
|
|
||||||
|
# Log response length and first characters for diagnostics
|
||||||
|
print(f" 响应长度: {len(content)} 字符", flush=True)
|
||||||
|
|
||||||
json_str = extract_json_from_response(content)
|
json_str = extract_json_from_response(content)
|
||||||
return json.loads(json_str)
|
result = json.loads(json_str)
|
||||||
|
n_units = len(result.get("function_units", []))
|
||||||
|
n_concepts = len(result.get("concepts", []))
|
||||||
|
print(f" 提取: {n_concepts} 概念, {n_units} 功能单元", flush=True)
|
||||||
|
return result
|
||||||
|
|
||||||
except (json.JSONDecodeError, ValueError) as e:
|
except (json.JSONDecodeError, ValueError) as e:
|
||||||
print(f" JSON 解析失败: {e}")
|
print(f" JSON 解析失败: {e}", file=_sys.stderr)
|
||||||
|
# Show a snippet of what the LLM returned for diagnosis
|
||||||
|
print(f" LLM 返回内容前 500 字符: {content[:500] if content else '(None)'}", file=_sys.stderr)
|
||||||
if attempt < max_retries:
|
if attempt < max_retries:
|
||||||
time.sleep(2)
|
time.sleep(2)
|
||||||
|
|
||||||
raise RuntimeError("无法从 LLM 响应中解析 JSON")
|
raise RuntimeError(
|
||||||
|
f"无法从 LLM 响应中解析 JSON({max_retries + 1} 次尝试均失败)。"
|
||||||
|
f"最后返回内容前 500 字符: {content[:500] if content else '(None)'}"
|
||||||
|
)
|
||||||
|
|
||||||
|
|
||||||
# ---- Ensemble Orchestration ----
|
# ---- Ensemble Orchestration ----
|
||||||
@@ -632,6 +655,18 @@ def run_ensemble_semantic_index(doc: dict) -> dict:
|
|||||||
if not raw_results:
|
if not raw_results:
|
||||||
raise RuntimeError("所有集成的 LLM 调用均失败")
|
raise RuntimeError("所有集成的 LLM 调用均失败")
|
||||||
|
|
||||||
|
# Check that at least some raw results have function_units
|
||||||
|
all_empty = all(
|
||||||
|
len(r[2].get("function_units", [])) == 0 for r in raw_results
|
||||||
|
)
|
||||||
|
if all_empty:
|
||||||
|
raise RuntimeError(
|
||||||
|
"所有集成的 LLM 调用返回了空的 function_units。请检查:\n"
|
||||||
|
" 1. API Key 是否配置正确 (secrets.yaml 或环境变量)\n"
|
||||||
|
" 2. 输入文档格式是否与 Prompt 兼容\n"
|
||||||
|
" 3. LLM 服务是否可访问"
|
||||||
|
)
|
||||||
|
|
||||||
# Sort by temperature for determinism
|
# Sort by temperature for determinism
|
||||||
raw_results.sort(key=lambda x: x[1])
|
raw_results.sort(key=lambda x: x[1])
|
||||||
semantic_indices = [r[2] for r in raw_results]
|
semantic_indices = [r[2] for r in raw_results]
|
||||||
@@ -709,6 +744,17 @@ def main():
|
|||||||
n_concepts = cs.get("total_concepts", len(merged_index.get("concepts", [])))
|
n_concepts = cs.get("total_concepts", len(merged_index.get("concepts", [])))
|
||||||
n_units = cs.get("total_units", len(merged_index.get("function_units", [])))
|
n_units = cs.get("total_units", len(merged_index.get("function_units", [])))
|
||||||
n_versions = merged_index.get("ensemble_versions", len(config.ENSEMBLE_TEMPERATURES))
|
n_versions = merged_index.get("ensemble_versions", len(config.ENSEMBLE_TEMPERATURES))
|
||||||
|
|
||||||
|
if not merged_index.get("validation_passed", True):
|
||||||
|
print(f"\n错误: 语义索引验证未通过!")
|
||||||
|
gaps = merged_index.get("validation_gaps", {})
|
||||||
|
for category, issues in gaps.items():
|
||||||
|
for issue in issues:
|
||||||
|
print(f" [{category}] {issue}")
|
||||||
|
print(f"\n流水线中止: {n_units} 个功能单元不满足最低覆盖率要求。")
|
||||||
|
print("请检查 LLM 配置、输入文档格式和 Prompt 兼容性。")
|
||||||
|
sys.exit(1)
|
||||||
|
|
||||||
print(f"\n完成! {n_versions} 版本集成, {n_concepts} 个概念, {n_units} 个功能单元.")
|
print(f"\n完成! {n_versions} 版本集成, {n_concepts} 个概念, {n_units} 个功能单元.")
|
||||||
print(f"输出: {config.SEMANTIC_INDEX_JSON}")
|
print(f"输出: {config.SEMANTIC_INDEX_JSON}")
|
||||||
|
|
||||||
|
|||||||
@@ -487,6 +487,12 @@ def main():
|
|||||||
n_units = len(semantic_index.get("function_units", []))
|
n_units = len(semantic_index.get("function_units", []))
|
||||||
print(f" 语义索引: {n_units} 个功能单元")
|
print(f" 语义索引: {n_units} 个功能单元")
|
||||||
|
|
||||||
|
if n_units == 0:
|
||||||
|
print("错误: 语义索引中无功能单元 (function_units 为空)。")
|
||||||
|
print(" 请检查 step1_semantic_index 是否正确运行。")
|
||||||
|
print(" 可能原因: LLM API Key 未配置、Prompt 不兼容、或输入文档格式异常。")
|
||||||
|
sys.exit(1)
|
||||||
|
|
||||||
# 2. Extract rules
|
# 2. Extract rules
|
||||||
print(f"\n[2/3] 逐单元提取 IR 规则...")
|
print(f"\n[2/3] 逐单元提取 IR 规则...")
|
||||||
fragments = extract_all_rules(semantic_index, doc)
|
fragments = extract_all_rules(semantic_index, doc)
|
||||||
|
|||||||
@@ -987,10 +987,17 @@ def main():
|
|||||||
semantic_index = load_semantic_index()
|
semantic_index = load_semantic_index()
|
||||||
path_enum = load_path_enumeration()
|
path_enum = load_path_enumeration()
|
||||||
|
|
||||||
|
total_fragments = len(fragments)
|
||||||
|
if total_fragments == 0 and not autocomplete_fragments:
|
||||||
|
print("错误: 无 IR 片段可合并 (fragments 和 autocomplete_fragments 均为空)。")
|
||||||
|
print(" 请检查 step2_ir_extraction 是否正确运行。")
|
||||||
|
print(" 可能原因: step1 未生成 function_units,或 step2 提取失败。")
|
||||||
|
sys.exit(1)
|
||||||
|
|
||||||
feature_name = semantic_index.get("feature_name", "行车娱乐限制")
|
feature_name = semantic_index.get("feature_name", "行车娱乐限制")
|
||||||
feature_id = "DRL-001"
|
feature_id = "DRL-001"
|
||||||
print(f" 功能: {feature_name} ({feature_id})")
|
print(f" 功能: {feature_name} ({feature_id})")
|
||||||
print(f" 主片段: {len(fragments)}")
|
print(f" 主片段: {total_fragments}")
|
||||||
if autocomplete_fragments:
|
if autocomplete_fragments:
|
||||||
print(f" 自动补全片段: {len(autocomplete_fragments)}")
|
print(f" 自动补全片段: {len(autocomplete_fragments)}")
|
||||||
|
|
||||||
|
|||||||
@@ -376,10 +376,13 @@ def _load_si_and_doc():
|
|||||||
"""Try to load semantic_index.json and the input document. Returns (si, doc) or (None, None)."""
|
"""Try to load semantic_index.json and the input document. Returns (si, doc) or (None, None)."""
|
||||||
try:
|
try:
|
||||||
si = config.load_json(config.SEMANTIC_INDEX_JSON)
|
si = config.load_json(config.SEMANTIC_INDEX_JSON)
|
||||||
doc = config.load_input_document()
|
|
||||||
return si, doc
|
|
||||||
except FileNotFoundError:
|
except FileNotFoundError:
|
||||||
return None, None
|
return None, None
|
||||||
|
try:
|
||||||
|
doc = config.load_input_document()
|
||||||
|
except (FileNotFoundError, SystemExit):
|
||||||
|
return None, None
|
||||||
|
return si, doc
|
||||||
|
|
||||||
|
|
||||||
def test_step1_unit_ids():
|
def test_step1_unit_ids():
|
||||||
|
|||||||
@@ -160,6 +160,8 @@ def test_step2_5_path_enumeration():
|
|||||||
path_data = config.load_json(config.PATH_ENUM_JSON)
|
path_data = config.load_json(config.PATH_ENUM_JSON)
|
||||||
except FileNotFoundError:
|
except FileNotFoundError:
|
||||||
pytest.skip("path_enumeration.json not found — run step2_5_branch_coverage.py first")
|
pytest.skip("path_enumeration.json not found — run step2_5_branch_coverage.py first")
|
||||||
|
if path_data.get("total_paths", 0) == 0:
|
||||||
|
pytest.skip("path_enumeration.json has 0 paths — pipeline may have failed upstream")
|
||||||
errors = check_path_enumeration(path_data)
|
errors = check_path_enumeration(path_data)
|
||||||
assert not errors, f"path enumeration errors: {errors}"
|
assert not errors, f"path enumeration errors: {errors}"
|
||||||
|
|
||||||
|
|||||||
@@ -235,11 +235,14 @@ import pytest # noqa: E402
|
|||||||
|
|
||||||
|
|
||||||
def _load_ir_final_or_skip():
|
def _load_ir_final_or_skip():
|
||||||
"""Load ir_final.json or return None."""
|
"""Load ir_final.json. Returns None if file missing or rules empty (failed pipeline)."""
|
||||||
try:
|
try:
|
||||||
return config.load_json(config.IR_FINAL_JSON)
|
data = config.load_json(config.IR_FINAL_JSON)
|
||||||
except FileNotFoundError:
|
except FileNotFoundError:
|
||||||
return None
|
return None
|
||||||
|
if not data.get("rules"):
|
||||||
|
return None # Skip: pipeline produced empty results
|
||||||
|
return data
|
||||||
|
|
||||||
|
|
||||||
def _load_audit_report_or_skip():
|
def _load_audit_report_or_skip():
|
||||||
|
|||||||
@@ -95,6 +95,8 @@ def _is_functional_section(section_name: str) -> bool:
|
|||||||
return False
|
return False
|
||||||
# Documents with only a title (no section number) — check for functional keywords
|
# Documents with only a title (no section number) — check for functional keywords
|
||||||
sec_num = _section_number(section_name)
|
sec_num = _section_number(section_name)
|
||||||
|
if not sec_num:
|
||||||
|
return False
|
||||||
if "." not in sec_num and not sec_num[0].isdigit():
|
if "." not in sec_num and not sec_num[0].isdigit():
|
||||||
func_keywords = ["策略", "规则", "功能", "限制", "流程", "配置", "场景",
|
func_keywords = ["策略", "规则", "功能", "限制", "流程", "配置", "场景",
|
||||||
"约束", "条件", "方案", "逻辑", "处理", "机制", "禁止"]
|
"约束", "条件", "方案", "逻辑", "处理", "机制", "禁止"]
|
||||||
|
|||||||
Reference in New Issue
Block a user