Tabby自托管AI代码补全部署

import subprocessimport timeimport threadingfrom typing import List, Dict, Optionalfrom dataclasses import dataclass, fieldfrom collections import deque  @dataclassclass CompletionRequest:    """代码补全请求"""    prefix: str    suffix: str    language: str    max_tokens: int = 256    temperature: float = 0.1  @dataclassclass CompletionResult:    """补全结果"""    completion: str    latency_ms: float    model_name: str    tokens_generated: int  class TabbyServer:    """模拟Tabby自托管AI代码补全服务器"""     def __init__(self, model_name: str = "starcoder-3b",                 gpu_id: int = 0, quantization: str = "int8"):        self.model_name = model_name        self.gpu_id = gpu_id        self.quantization = quantization        self.running = False        self.request_queue = deque()        self.completion_cache = {}        self.total_requests = 0        self.total_latency = 0.0        self.supported_languages = [            "python", "javascript", "typescript", "java",            "go", "rust", "cpp", "ruby"        ]     def start(self):        """启动Tabby服务器（模拟Docker容器启动）"""        print(f"[Tabby] 启动服务器...")        print(f"  模型: {self.model_name}")        print(f"  GPU: cuda:{self.gpu_id}")        print(f"  量化: {self.quantization}")        print(f"  监听: http://0.0.0.0:8080")        self.running = True        print(f"[Tabby] 服务器就绪 ✓")     def stop(self):        """停止服务器"""        self.running = False        print("[Tabby] 服务器已停止")     def complete(self, request: CompletionRequest) -> CompletionResult:        """处理代码补全请求"""        if not self.running:            raise RuntimeError("服务器未启动")         cache_key = f"{request.language}:{request.prefix[-50:]}"        if cache_key in self.completion_cache:            cached = self.completion_cache[cache_key]            return CompletionResult(                completion=cached,                latency_ms=5.0,                model_name=self.model_name,                tokens_generated=len(cached.split())            )         start = time.time()        completion = self._generate_completion(request)        elapsed = (time.time() - start) * 1000         self.total_requests += 1        self.total_latency += elapsed         self.completion_cache[cache_key] = completion        if len(self.completion_cache) > 1000:            oldest = next(iter(self.completion_cache))            del self.completion_cache[oldest]         return CompletionResult(            completion=completion,            latency_ms=round(elapsed, 2),            model_name=self.model_name,            tokens_generated=len(completion.split())        )     def _generate_completion(self, req: CompletionRequest) -> str:        """模拟模型推理生成补全代码"""        templates = {            "python": [                "def process_data(input_path, output_path):\n    import pandas as pd\n    df = pd.read_csv(input_path)\n    result = df.dropna().reset_index(drop=True)\n    result.to_csv(output_path, index=False)\n    return result",                "class DataPipeline:\n    def __init__(self, config):\n        self.config = config\n        self.stages = []\n    \n    def add_stage(self, name, func):\n        self.stages.append((name, func))\n    \n    def run(self, data):\n        for name, func in self.stages:\n            data = func(data)\n        return data",            "import numpy as np\n\ndef normalize_features(X):\n    mean = np.mean(X, axis=0)\n    std = np.std(X, axis=0) + 1e-8\n    return (X - mean) / std"            ],            "javascript": [                "async function fetchData(url) {\n  const response = await fetch(url);\n  if (!response.ok) throw new Error(`HTTP ${response.status}`);\n  return response.json();\n}",                "const debounce = (fn, delay) => {\n  let timer;\n  return (...args) => {\n    clearTimeout(timer);\n    timer = setTimeout(() => fn(...args), delay);\n  };\n};"            ],            "java": [                "public class UserService {\n    private final UserRepository repo;\n    \n    public User findById(Long id) {\n        return repo.findById(id)\n            .orElseThrow(() -> new UserNotFoundException(id));\n    }\n}"            ]        }        lang_templates = templates.get(req.language, templates["python"])        return random.choice(lang_templates)     def get_stats(self) -> Dict:        """获取服务器统计信息"""        avg_latency = (            self.total_latency / self.total_requests            if self.total_requests > 0 else 0        )        return {            "model": self.model_name,            "total_requests": self.total_requests,            "avg_latency_ms": round(avg_latency, 2),            "cache_size": len(self.completion_cache),            "running": self.running        }  class IDEIntegration:    """模拟IDE插件集成"""     def __init__(self, server: TabbyServer, ide_name: str = "VSCode"):        self.server = server        self.ide_name = ide_name        self.accepted = 0        self.rejected = 0     def on_keystroke(self, prefix: str, suffix: str,                     language: str) -> Optional[str]:        """模拟按键触发补全"""        req = CompletionRequest(            prefix=prefix, suffix=suffix, language=language        )        result = self.server.complete(req)        return result.completion     def accept_completion(self):        """用户接受补全"""        self.accepted += 1     def reject_completion(self):        """用户拒绝补全"""        self.rejected += 1     def adoption_rate(self) -> float:        """计算补全采纳率"""        total = self.accepted + self.rejected        return self.accepted / max(total, 1)  def demo_tabby_deployment():    """演示Tabby自托管AI代码补全全流程"""    random.seed(42)     print("=" * 60)    print("Tabby 自托管AI代码补全 - 部署演示")    print("=" * 60)     server = TabbyServer(        model_name="starcoder-3b",        gpu_id=0,        quantization="int8"    )    server.start()     ide = IDEIntegration(server, "VSCode")     test_cases = [        ("def process_", "", "python"),        ("async function fetch", "", "javascript"),        ("class Data", "", "python"),        ("import numpy", "", "python"),        ("public class User", "", "java"),        ("const debounce", "", "javascript"),    ]     print("\n--- 补全测试 ---")    for prefix, suffix, lang in test_cases:        result = server.complete(            CompletionRequest(prefix=prefix, suffix=suffix, language=lang)        )        print(f"\n[{lang}] 前缀: '{prefix}'")        print(f"  延迟: {result.latency_ms}ms")        print(f"  补全: {result.completion[:80]}...")        if random.random() > 0.3:            ide.accept_completion()        else:            ide.reject_completion()     print(f"\n--- 服务器统计 ---")    stats = server.get_stats()    for k, v in stats.items():        print(f"  {k}: {v}")     print(f"\n--- IDE集成统计 ---")    print(f"  IDE: {ide.ide_name}")    print(f"  采纳率: {ide.adoption_rate():.1%}")    print(f"  接受: {ide.accepted}, 拒绝: {ide.rejected}")     server.stop()    print("\n演示完成!")  if __name__ == "__main__":    demo_tabby_deployment()