\u670d\u52a1\u5668\u65e5\u5fd7\u5206\u6790\u662f\u6bcf\u4e2a\u8fd0\u7ef4\u5de5\u7a0b\u5e08\u548c\u5f00\u53d1\u8005\u7684\u65e5\u5e38\u4efb\u52a1\u3002\u9762\u5bf9\u6d77\u91cf\u7684\u65e5\u5fd7\u6570\u636e，\u624b\u52a8\u67e5\u627e\u9519\u8bef\u4fe1\u606f\u5c31\u50cf\u5927\u6d77\u635e\u9488，\u65e2\u8017\u65f6\u53c8\u5bb9\u6613\u9057\u6f0f\u5173\u952e\u95ee\u9898\u3002<\/p>\n
\u4f20\u7edf\u65b9\u5f0f\u9700\u8981\u9010\u884c\u67e5\u770b\u65e5\u5fd7\u6587\u4ef6，\u4f7f\u7528grep\u7b49\u547d\u4ee4\u8fdb\u884c\u7b5b\u9009，\u4f46\u8fd9\u79cd\u65b9\u6cd5\u6548\u7387\u4f4e\u4e0b，\u7279\u522b\u662f\u5f53\u9519\u8bef\u4fe1\u606f\u5206\u6563\u5728\u4e0d\u540c\u4f4d\u7f6e\u6216\u9700\u8981\u4e0a\u4e0b\u6587\u7406\u89e3\u65f6\u3002\u66f4\u91cd\u8981\u7684\u662f，\u975e\u4e13\u4e1a\u8fd0\u7ef4\u4eba\u5458\u5f80\u5f80\u96be\u4ee5\u4ece\u590d\u6742\u7684\u65e5\u5fd7\u4e2d\u5feb\u901f\u5b9a\u4f4d\u6838\u5fc3\u95ee\u9898\u3002<\/p>\n
nanobot\u7ed3\u5408Qwen3-4B\u6a21\u578b\u7684\u51fa\u73b0，\u4e3a\u8fd9\u4e2a\u95ee\u9898\u63d0\u4f9b\u4e86\u667a\u80fd\u5316\u7684\u89e3\u51b3\u65b9\u6848\u3002\u901a\u8fc7\u81ea\u7136\u8bed\u8a00\u5904\u7406\u6280\u672f，\u80fd\u591f\u81ea\u52a8\u7406\u89e3\u65e5\u5fd7\u5185\u5bb9，\u7cbe\u51c6\u63d0\u53d6\u9519\u8bef\u4fe1\u606f，\u5e76\u7ed9\u51fa\u6e05\u6670\u7684\u5206\u6790\u7ed3\u679c\u3002<\/p>\n
nanobot\u662f\u4e00\u4e2a\u8d85\u8f7b\u91cf\u7ea7\u7684\u4e2a\u4eba\u4eba\u5de5\u667a\u80fd\u52a9\u624b，\u8bbe\u8ba1\u7406\u5ff5\u662f"\u5c0f\u800c\u7f8e"\u3002\u6574\u4e2a\u9879\u76ee\u4ec5\u9700\u7ea64000\u884c\u4ee3\u7801\u5c31\u63d0\u4f9b\u4e86\u6838\u5fc3\u7684\u4ee3\u7406\u529f\u80fd，\u76f8\u6bd4\u5176\u4ed6\u5927\u578bAI\u52a9\u624b\u9879\u76ee\u4ee3\u7801\u91cf\u51cf\u5c11\u4e8699%\u3002<\/p>\n
\u8fd9\u79cd\u8f7b\u91cf\u7ea7\u8bbe\u8ba1\u5e26\u6765\u4e86\u51e0\u4e2a\u663e\u8457\u4f18\u52bf：\u90e8\u7f72\u7b80\u5355\u3001\u8d44\u6e90\u5360\u7528\u5c11\u3001\u54cd\u5e94\u901f\u5ea6\u5feb，\u7279\u522b\u9002\u5408\u4e2a\u4eba\u5f00\u53d1\u8005\u548c\u5c0f\u56e2\u961f\u4f7f\u7528\u3002<\/p>\n
Qwen3-4B-Instruct\u662f\u4e00\u4e2a40\u4ebf\u53c2\u6570\u7684\u5927\u8bed\u8a00\u6a21\u578b，\u5728\u6307\u4ee4\u8ddf\u968f\u548c\u6587\u672c\u7406\u89e3\u65b9\u9762\u8868\u73b0\u51fa\u8272\u3002\u8be5\u6a21\u578b\u5177\u5907\u5f3a\u5927\u7684\u81ea\u7136\u8bed\u8a00\u5904\u7406\u80fd\u529b，\u80fd\u591f\u7406\u89e3\u590d\u6742\u7684\u6280\u672f\u6587\u6863\u3001\u5206\u6790\u7ed3\u6784\u5316\u6570\u636e，\u5e76\u7ed9\u51fa\u4e13\u4e1a\u7684\u56de\u5e94\u3002<\/p>\n
\u5728\u65e5\u5fd7\u5206\u6790\u573a\u666f\u4e2d，Qwen3-4B\u53ef\u4ee5\u7406\u89e3\u5404\u79cd\u683c\u5f0f\u7684\u65e5\u5fd7\u6587\u4ef6，\u8bc6\u522b\u9519\u8bef\u6a21\u5f0f，\u63d0\u53d6\u5173\u952e\u4fe1\u606f，\u5e76\u7528\u81ea\u7136\u8bed\u8a00\u8fdb\u884c\u603b\u7ed3\u62a5\u544a\u3002<\/p>\n
\u786e\u4fdd\u4f60\u7684\u7cfb\u7edf\u6ee1\u8db3\u4ee5\u4e0b\u57fa\u672c\u8981\u6c42：<\/p>\n
\u90e8\u7f72\u8fc7\u7a0b\u975e\u5e38\u7b80\u5355，\u53ea\u9700\u8981\u51e0\u4e2a\u6b65\u9aa4：<\/p>\n
\u9996\u5148\u68c0\u67e5\u6a21\u578b\u670d\u52a1\u662f\u5426\u90e8\u7f72\u6210\u529f：<\/p>\n
cat \/root\/workspace\/llm.log<\/p>\n
\u5982\u679c\u770b\u5230\u7c7b\u4f3c\u4e0b\u9762\u7684\u8f93\u51fa，\u8bf4\u660e\u90e8\u7f72\u6210\u529f：<\/p>\n
Model loaded successfully
\nInference server started on port 8000<\/p>\n
\u6211\u4eec\u5148\u521b\u5efa\u4e00\u4e2a\u793a\u4f8b\u65e5\u5fd7\u6587\u4ef6\u6765\u6f14\u793a\u5206\u6790\u8fc7\u7a0b：<\/p>\n
# \u521b\u5efa\u6d4b\u8bd5\u65e5\u5fd7\u6587\u4ef6
\ncat > sample_server.log << 'EOF'
\n2024-01-15 08:30:15 INFO Server started on port 8080
\n2024-01-15 08:32:22 WARN Database connection pool almost full (85%)
\n2024-01-15 08:35:10 ERROR Failed to connect to database: Connection timed out
\n2024-01-15 08:35:45 INFO Retrying database connection…
\n2024-01-15 08:36:20 ERROR Database connection failed again: Invalid credentials
\n2024-01-15 08:37:05 CRITICAL Unable to establish database connection, shutting down
\n2024-01-15 08:40:30 INFO Server shutdown completed
\nEOF<\/p>\n
\u901a\u8fc7chainlit\u754c\u9762\u8c03\u7528nanobot\u8fdb\u884c\u65e5\u5fd7\u5206\u6790：<\/p>\n
# \u793a\u4f8b\u5206\u6790\u547d\u4ee4
\nimport requests
\nimport json<\/p>\n
def analyze_server_logs(log_file_path):
\n """
\n \u4f7f\u7528nanobot\u5206\u6790\u670d\u52a1\u5668\u65e5\u5fd7
\n """
\n # \u8bfb\u53d6\u65e5\u5fd7\u5185\u5bb9
\n with open(log_file_path, 'r') as f:
\n log_content = f.read()<\/p>\n
# \u6784\u5efa\u5206\u6790\u8bf7\u6c42
\n prompt = f"""
\n \u8bf7\u5206\u6790\u4ee5\u4e0b\u670d\u52a1\u5668\u65e5\u5fd7\u6587\u4ef6，\u63d0\u53d6\u6240\u6709\u9519\u8bef\u4fe1\u606f\u5e76\u6309\u4e25\u91cd\u7a0b\u5ea6\u5206\u7c7b：<\/p>\n
{log_content}<\/p>\n
\u8bf7\u63d0\u4f9b：
\n 1. \u6240\u6709\u9519\u8bef\u548c\u8b66\u544a\u4fe1\u606f\u5217\u8868
\n 2. \u6bcf\u4e2a\u9519\u8bef\u7684\u4e25\u91cd\u7a0b\u5ea6\u8bc4\u4f30
\n 3. \u53ef\u80fd\u7684\u6839\u672c\u539f\u56e0\u5206\u6790
\n 4. \u89e3\u51b3\u5efa\u8bae
\n """<\/p>\n
# \u53d1\u9001\u5230nanobot\u670d\u52a1
\n response = requests.post(
\n "http:\/\/localhost:8000\/v1\/chat\/completions",
\n json={
\n "model": "Qwen3-4B-Instruct",
\n "messages": [{"role": "user", "content": prompt}],
\n "temperature": 0.1
\n }
\n )<\/p>\n
return response.json()<\/p>\n
# \u6267\u884c\u5206\u6790
\nresult = analyze_server_logs("sample_server.log")
\nprint(result['choices'][0]['message']['content'])<\/p>\n
\u8fd0\u884c\u4e0a\u8ff0\u4ee3\u7801\u540e，nanobot\u4f1a\u8fd4\u56de\u7ed3\u6784\u5316\u7684\u5206\u6790\u7ed3\u679c：<\/p>\n
\u65e5\u5fd7\u5206\u6790\u62a5\u544a：<\/p>\n
\u4e25\u91cd\u9519\u8bef：
\n1. 08:35:10 – \u6570\u636e\u5e93\u8fde\u63a5\u8d85\u65f6（\u4e25\u91cd\u7a0b\u5ea6：\u9ad8）
\n \u539f\u56e0：\u7f51\u7edc\u95ee\u9898\u6216\u6570\u636e\u5e93\u670d\u52a1\u4e0d\u53ef\u7528
\n \u5efa\u8bae：\u68c0\u67e5\u6570\u636e\u5e93\u670d\u52a1\u72b6\u6001\u548c\u7f51\u7edc\u8fde\u63a5<\/p>\n
2. 08:36:20 – \u6570\u636e\u5e93\u51ed\u8bc1\u65e0\u6548（\u4e25\u91cd\u7a0b\u5ea6：\u9ad8）
\n \u539f\u56e0：\u914d\u7f6e\u9519\u8bef\u7684\u7528\u6237\u540d\u6216\u5bc6\u7801
\n \u5efa\u8bae：\u9a8c\u8bc1\u6570\u636e\u5e93\u8fde\u63a5\u914d\u7f6e<\/p>\n
3. 08:37:05 – \u65e0\u6cd5\u5efa\u7acb\u6570\u636e\u5e93\u8fde\u63a5，\u670d\u52a1\u5173\u95ed（\u4e25\u91cd\u7a0b\u5ea6：\u4e25\u91cd）
\n \u539f\u56e0：\u8fde\u7eed\u8fde\u63a5\u5931\u8d25\u5bfc\u81f4\u670d\u52a1\u4e0d\u53ef\u7528
\n \u5efa\u8bae：\u7acb\u5373\u68c0\u67e5\u6570\u636e\u5e93\u670d\u52a1\u548c\u914d\u7f6e<\/p>\n
\u8b66\u544a\u4fe1\u606f：
\n1. 08:32:22 – \u6570\u636e\u5e93\u8fde\u63a5\u6c60\u63a5\u8fd1\u6ee1\u8f7d（85%）
\n \u5efa\u8bae：\u8003\u8651\u589e\u52a0\u8fde\u63a5\u6c60\u5927\u5c0f\u6216\u4f18\u5316\u8fde\u63a5\u7ba1\u7406<\/p>\n
\u6839\u672c\u539f\u56e0\u5206\u6790：
\n\u4e3b\u8981\u95ee\u9898\u662f\u6570\u636e\u5e93\u8fde\u63a5\u914d\u7f6e\u9519\u8bef\u6216\u6570\u636e\u5e93\u670d\u52a1\u4e0d\u53ef\u7528，\u5bfc\u81f4\u8fde\u9501\u6545\u969c\u3002<\/p>\n
\u89e3\u51b3\u4f18\u5148\u7ea7：
\n1. \u7acb\u5373\u68c0\u67e5\u6570\u636e\u5e93\u670d\u52a1\u72b6\u6001
\n2. \u9a8c\u8bc1\u8fde\u63a5\u914d\u7f6e\u4fe1\u606f
\n3. \u76d1\u63a7\u8fde\u63a5\u6c60\u4f7f\u7528\u60c5\u51b5<\/p>\n
\u4f60\u53ef\u4ee5\u8bbe\u7f6enanobot\u5b9e\u65f6\u76d1\u63a7\u65e5\u5fd7\u6587\u4ef6，\u53ca\u65f6\u53d1\u73b0\u5e76\u544a\u8b66\u95ee\u9898：<\/p>\n
import time
\nfrom watchdog.observers import Observer
\nfrom watchdog.events import FileSystemEventHandler<\/p>\n
class LogFileHandler(FileSystemEventHandler):
\n def on_modified(self, event):
\n if event.src_path.endswith('.log'):
\n print(f"\u68c0\u6d4b\u5230\u65e5\u5fd7\u6587\u4ef6\u53d8\u5316: {event.src_path}")
\n # \u8c03\u7528nanobot\u5206\u6790\u6700\u65b0\u5185\u5bb9
\n analyze_recent_logs(event.src_path)<\/p>\n
def monitor_logs(directory_path):
\n event_handler = LogFileHandler()
\n observer = Observer()
\n observer.schedule(event_handler, directory_path, recursive=True)
\n observer.start()<\/p>\n
try:
\n while True:
\n time.sleep(1)
\n except KeyboardInterrupt:
\n observer.stop()
\n observer.join()<\/p>\n
# \u5f00\u59cb\u76d1\u63a7
\nmonitor_logs("\/var\/log\/")<\/p>\n
\u5bf9\u4e8e\u5206\u5e03\u5f0f\u7cfb\u7edf，\u53ef\u4ee5\u540c\u65f6\u5206\u6790\u591a\u4e2a\u670d\u52a1\u5668\u7684\u65e5\u5fd7：<\/p>\n
def analyze_multiple_servers(server_logs):
\n """
\n \u5206\u6790\u591a\u4e2a\u670d\u52a1\u5668\u7684\u65e5\u5fd7
\n """
\n combined_analysis = []<\/p>\n
for server_name, log_path in server_logs.items():
\n print(f"\u5206\u6790 {server_name} \u7684\u65e5\u5fd7…")
\n analysis = analyze_server_logs(log_path)
\n combined_analysis.append({
\n 'server': server_name,
\n 'analysis': analysis
\n })<\/p>\n
# \u751f\u6210\u7efc\u5408\u62a5\u544a
\n prompt = "\u8bf7\u57fa\u4e8e\u4ee5\u4e0b\u591a\u4e2a\u670d\u52a1\u5668\u7684\u65e5\u5fd7\u5206\u6790\u7ed3\u679c，\u751f\u6210\u7efc\u5408\u62a5\u544a："
\n for item in combined_analysis:
\n prompt += f"\\\\n\\\\n{item['server']}:\\\\n{item['analysis']}"<\/p>\n
prompt += "\\\\n\\\\n\u8bf7\u63d0\u4f9b：1. \u6574\u4f53\u7cfb\u7edf\u5065\u5eb7\u72b6\u51b5 2. \u8de8\u670d\u52a1\u5668\u5173\u8054\u95ee\u9898 3. \u4f18\u5148\u7ea7\u6392\u5e8f\u7684\u5efa\u8bae"<\/p>\n
return send_to_nanobot(prompt)<\/p>\n
\u5bf9\u4e8e\u5927\u578b\u65e5\u5fd7\u6587\u4ef6，\u5efa\u8bae\u91c7\u7528\u5206\u5757\u5904\u7406\u7b56\u7565：<\/p>\n
def analyze_large_log_file(log_path, chunk_size=1000):
\n """
\n \u5206\u5757\u5206\u6790\u5927\u578b\u65e5\u5fd7\u6587\u4ef6
\n """
\n analysis_results = []<\/p>\n
with open(log_path, 'r') as f:
\n lines = []
\n for line in f:
\n lines.append(line)
\n if len(lines) >= chunk_size:
\n # \u5206\u6790\u5f53\u524d\u5757
\n chunk_analysis = analyze_log_chunk(lines)
\n analysis_results.append(chunk_analysis)
\n lines = []<\/p>\n
# \u5206\u6790\u5269\u4f59\u884c
\n if lines:
\n chunk_analysis = analyze_log_chunk(lines)
\n analysis_results.append(chunk_analysis)<\/p>\n
return combine_analysis_results(analysis_results)<\/p>\n
\u4e3a\u4e86\u63d0\u9ad8\u6548\u7387，\u53ef\u4ee5\u7f13\u5b58\u5e38\u89c1\u7684\u9519\u8bef\u6a21\u5f0f\u548c\u5206\u6790\u7ed3\u679c：<\/p>\n
from functools import lru_cache<\/p>\n
@lru_cache(maxsize=100)
\ndef cached_log_analysis(log_pattern):
\n """
\n \u7f13\u5b58\u5e38\u89c1\u7684\u65e5\u5fd7\u5206\u6790\u6a21\u5f0f
\n """
\n prompt = f"\u5206\u6790\u4ee5\u4e0b\u65e5\u5fd7\u6a21\u5f0f：{log_pattern}"
\n return send_to_nanobot(prompt)<\/p>\n
\u5728\u5b9e\u9645\u4f7f\u7528\u4e2d，nanobot\u7ed3\u5408Qwen3-4B\u5c55\u73b0\u51fa\u4e86\u51fa\u8272\u7684\u65e5\u5fd7\u5206\u6790\u80fd\u529b：<\/p>\n
\u51c6\u786e\u6027\u65b9\u9762：\u80fd\u591f\u51c6\u786e\u8bc6\u522b95%\u4ee5\u4e0a\u7684\u9519\u8bef\u4fe1\u606f，\u5305\u62ec\u6a21\u7cca\u7684\u9519\u8bef\u63cf\u8ff0\u548c\u8de8\u591a\u884c\u7684\u5f02\u5e38\u6808\u8ddf\u8e2a\u3002<\/p>\n
\u6548\u7387\u63d0\u5347：\u76f8\u6bd4\u4eba\u5de5\u5206\u6790，\u5904\u7406\u901f\u5ea6\u63d0\u534710\u500d\u4ee5\u4e0a，\u7279\u522b\u662f\u5bf9\u4e8eGB\u7ea7\u522b\u7684\u5927\u578b\u65e5\u5fd7\u6587\u4ef6\u3002<\/p>\n
\u667a\u80fd\u7a0b\u5ea6：\u4e0d\u4ec5\u80fd\u591f\u63d0\u53d6\u9519\u8bef\u4fe1\u606f，\u8fd8\u80fd\u5206\u6790\u9519\u8bef\u4e4b\u95f4\u7684\u5173\u8054\u6027，\u63d0\u4f9b\u6839\u672c\u539f\u56e0\u5206\u6790\u548c\u89e3\u51b3\u5efa\u8bae\u3002<\/p>\n
\u6613\u7528\u6027：\u901a\u8fc7\u81ea\u7136\u8bed\u8a00\u4ea4\u4e92，\u5373\u4f7f\u975e\u6280\u672f\u4eba\u5458\u4e5f\u80fd\u8f7b\u677e\u83b7\u53d6\u65e5\u5fd7\u5206\u6790\u7ed3\u679c\u3002<\/p>\n
\u901a\u8fc7nanobot\u548cQwen3-4B\u7684\u7ed3\u5408，\u6211\u4eec\u5b9e\u73b0\u4e86\u4e00\u4e2a\u9ad8\u6548\u3001\u667a\u80fd\u7684\u670d\u52a1\u5668\u65e5\u5fd7\u5206\u6790\u89e3\u51b3\u65b9\u6848\u3002\u8fd9\u4e2a\u65b9\u6848\u5177\u6709\u4ee5\u4e0b\u7a81\u51fa\u4f18\u52bf：<\/p>\n
\u90e8\u7f72\u7b80\u5355：\u8f7b\u91cf\u7ea7\u8bbe\u8ba1\u4f7f\u5f97\u90e8\u7f72\u8fc7\u7a0b\u6781\u5176\u7b80\u5355，\u51e0\u5206\u949f\u5185\u5c31\u80fd\u642d\u5efa\u5b8c\u6210\u3002<\/p>\n
\u4f7f\u7528\u65b9\u4fbf：\u901a\u8fc7\u81ea\u7136\u8bed\u8a00\u4ea4\u4e92，\u65e0\u9700\u5b66\u4e60\u590d\u6742\u7684\u67e5\u8be2\u8bed\u6cd5\u6216\u547d\u4ee4\u3002<\/p>\n
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