selfreleaseandDevin
5c21e8fcd0
包含功能: - 法务参谋/经营决策/生活助理/情绪中心四大AI对话模块 - 专家咨询系统(用户选定→专家确认→咨询→回复→评价) - 角色登录(用户/专家/管理员)+ ProtectedRoute 权限控制 - 管理后台(用户管理/专家管理/AI使用统计/专家活跃度) - 专家工作台(待确认服务/待回复咨询/已回复咨询/服务中用户) - 服务关系取消(用户和专家均可取消,需自己确认) - 全页面移动端响应式适配 - 知识库RAG检索 - 对话历史(普通/保密模式) Generated with [Devin](https://devin.ai) Co-Authored-By: Devin <158243242+devin-ai-integration[bot]@users.noreply.github.com>
240 lines
7.9 KiB
Python
240 lines
7.9 KiB
Python
"""性能测试:并发会话、长文档解析、OCR 耗时、API 响应时间基线。
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用法: python3 test_performance.py
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输出: perf_report.json + 控制台统计
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"""
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import json
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import time
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import os
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import sys
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import threading
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from concurrent.futures import ThreadPoolExecutor, as_completed
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sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
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from fastapi.testclient import TestClient
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import api as api_module
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from api import app
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client = TestClient(app)
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def perf_single_session_ask():
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"""单会话 ask 响应时间(不含 Kimi,只测分诊+RAG)。"""
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# 清理限流桶
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api_module._rate_buckets.clear()
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sid = client.post('/sessions', json={'mode': 'normal'}).json()['session_id']
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times = []
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questions = [
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'员工工伤后能否开除',
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'合同违约金怎么约定',
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'客户欠款三个月不还',
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'收到税务通知要求补缴',
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'最近压力大想聊聊',
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]
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for q in questions:
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start = time.time()
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r = client.post(f'/sessions/{sid}/ask', json={'question': q, 'scene': 'legal'})
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elapsed = time.time() - start
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times.append(elapsed)
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assert r.status_code == 200, f"ask 失败: {r.status_code}"
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return {
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"test": "single_session_ask",
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"iterations": len(times),
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"avg_ms": round(sum(times) / len(times) * 1000, 1),
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"min_ms": round(min(times) * 1000, 1),
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"max_ms": round(max(times) * 1000, 1),
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}
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def perf_concurrent_sessions():
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"""并发会话创建 + 提问(10 并发)。"""
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api_module._rate_buckets.clear()
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def worker(i):
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start = time.time()
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sid = client.post('/sessions', json={'mode': 'normal'}).json()['session_id']
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r = client.post(f'/sessions/{sid}/ask', json={
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'question': f'测试问题 {i}', 'scene': 'legal'})
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elapsed = time.time() - start
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return elapsed, r.status_code
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with ThreadPoolExecutor(max_workers=10) as executor:
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futures = [executor.submit(worker, i) for i in range(10)]
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results = [f.result() for f in as_completed(futures)]
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times = [r[0] for r in results]
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status_codes = [r[1] for r in results]
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return {
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"test": "concurrent_sessions_10",
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"concurrency": 10,
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"avg_ms": round(sum(times) / len(times) * 1000, 1),
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"min_ms": round(min(times) * 1000, 1),
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"max_ms": round(max(times) * 1000, 1),
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"all_200": all(c == 200 for c in status_codes),
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"status_codes": status_codes,
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}
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def perf_long_document_parse():
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"""长文档解析:100KB / 1MB TXT 提取时间。"""
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api_module._rate_buckets.clear()
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sid = client.post('/sessions', json={'mode': 'normal'}).json()['session_id']
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results = []
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for size_kb in [10, 100, 500]:
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content = '合同条款测试内容。' * (size_kb * 1024 // 10)
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data = content.encode('utf-8')
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start = time.time()
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r = client.post(f'/sessions/{sid}/file',
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files={'file': (f'test_{size_kb}kb.txt', data)})
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elapsed = time.time() - start
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assert r.status_code == 200, f"文件上传失败: {r.status_code}"
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results.append({
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"size_kb": size_kb,
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"parse_ms": round(elapsed * 1000, 1),
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"text_length": r.json().get('text_length', 0),
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})
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return {"test": "long_document_parse", "results": results}
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def perf_ocr_image():
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"""OCR 图片识别耗时。"""
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api_module._rate_buckets.clear()
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try:
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from PIL import Image, ImageDraw, ImageFont
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import io
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import pytesseract
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except ImportError:
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return {"test": "ocr_image", "skipped": "PIL/pytesseract not installed"}
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sid = client.post('/sessions', json={'mode': 'normal'}).json()['session_id']
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# 生成不同复杂度的图片
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results = []
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for num_lines in [1, 5, 20]:
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img = Image.new('RGB', (800, 60 * num_lines + 40), 'white')
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d = ImageDraw.Draw(img)
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try:
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font = ImageFont.truetype('/System/Library/Fonts/STHeiti Medium.ttc', 36)
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except Exception:
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font = ImageFont.load_default()
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for i in range(num_lines):
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d.text((20, 20 + i * 60), f'合同第{i+1}条违约金条款', fill='black', font=font)
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buf = io.BytesIO()
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img.save(buf, format='PNG')
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data = buf.getvalue()
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start = time.time()
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r = client.post(f'/sessions/{sid}/file',
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files={'file': (f'test_{num_lines}lines.png', data)})
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elapsed = time.time() - start
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if r.status_code == 200:
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results.append({
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"lines": num_lines,
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"ocr_ms": round(elapsed * 1000, 1),
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"text_length": r.json().get('text_length', 0),
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})
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else:
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results.append({"lines": num_lines, "error": r.status_code})
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return {"test": "ocr_image", "results": results}
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def perf_rag_search():
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"""RAG 检索耗时:关键词 + 向量。"""
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api_module._rate_buckets.clear()
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queries = ['工伤解除', '合同违约金', '税务稽查', '欠款催收', '劳动仲裁']
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keyword_times = []
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vector_times = []
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for q in queries:
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start = time.time()
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r = client.get(f'/knowledge/search?q={q}')
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keyword_times.append(time.time() - start)
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assert r.status_code == 200
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start = time.time()
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r = client.get(f'/knowledge/vector-search?q={q}')
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vector_times.append(time.time() - start)
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assert r.status_code == 200
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return {
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"test": "rag_search",
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"keyword_avg_ms": round(sum(keyword_times) / len(keyword_times) * 1000, 1),
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"vector_avg_ms": round(sum(vector_times) / len(vector_times) * 1000, 1),
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"queries": len(queries),
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}
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def perf_session_destroy():
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"""会话销毁耗时。"""
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times = []
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for _ in range(20):
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api_module._rate_buckets.clear()
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sid = client.post('/sessions', json={'mode': 'ephemeral'}).json()['session_id']
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start = time.time()
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client.post(f'/sessions/{sid}/destroy')
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times.append(time.time() - start)
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return {
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"test": "session_destroy",
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"iterations": len(times),
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"avg_ms": round(sum(times) / len(times) * 1000, 1),
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"min_ms": round(min(times) * 1000, 1),
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"max_ms": round(max(times) * 1000, 1),
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}
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def run_all():
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"""运行全部性能测试。"""
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print("=" * 60)
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print("BossAi 性能测试")
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print("=" * 60)
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tests = [
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("单会话 ask 响应时间", perf_single_session_ask),
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("并发 10 会话", perf_concurrent_sessions),
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("长文档解析", perf_long_document_parse),
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("OCR 图片识别", perf_ocr_image),
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("RAG 检索", perf_rag_search),
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("会话销毁", perf_session_destroy),
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]
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all_results = []
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for name, test_func in tests:
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print(f"\n--- {name} ---")
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try:
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result = test_func()
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all_results.append(result)
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# 简洁输出
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for k, v in result.items():
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if k != "test" and not isinstance(v, list):
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print(f" {k}: {v}")
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elif isinstance(v, list) and k == "results":
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for item in v:
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print(f" {item}")
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except Exception as e:
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print(f" ERROR: {e}")
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all_results.append({"test": name, "error": str(e)})
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# 写入报告
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with open("perf_report.json", "w", encoding="utf-8") as f:
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json.dump(all_results, f, ensure_ascii=False, indent=2)
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print(f"\n{'=' * 60}")
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print(f"性能报告已写入 perf_report.json")
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print(f"{'=' * 60}")
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# 性能基线总结
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print("\n性能基线总结:")
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for r in all_results:
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if "error" in r:
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print(f" {r['test']}: ERROR")
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elif "avg_ms" in r:
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print(f" {r['test']}: avg {r['avg_ms']}ms")
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elif "keyword_avg_ms" in r:
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print(f" {r['test']}: keyword {r['keyword_avg_ms']}ms, vector {r['vector_avg_ms']}ms")
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if __name__ == "__main__":
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run_all()
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