# 拉取Qwen2.5 7B模型，中文場景吊打同體量
ollama pull qwen2.5:7b
# 后臺運行，只監(jiān)聽本地（關(guān)鍵?。?
OLLAMA_HOST=127.0.0.1:11434 ollama serve

curl http://localhost:11434/api/generate -d '{
"model": "qwen2.5:7b",
"prompt": "你好，請用一句話證明你是本地部署的AI"
}'

npm install -g @openclaw/cli

openclaw init --local-only

llm:
  provider: ollama
  model: qwen2.5:7b
  base_url: http://127.0.0.1:11434
security:
  sandbox_mode: strict  # 嚴(yán)格沙箱，禁止危險操作
  allowed_paths:
    - /opt/data/    # 只允許AI碰這個目錄

org.springframework.boot
spring-boot-starter-web
org.springframework.ai
spring-ai-ollama-spring-boot-starter
1.0.0-M3

@Service
public class LocalLLMService {
    private final OllamaChatClient chatClient;
    public LocalLLMService(OllamaChatClient chatClient) {
        this.chatClient = chatClient;
    }
    public String chat(String message) {
        return chatClient.call(message);
    }
}

@RestController
@RequestMapping("/api/ai")
public class AIController {
    @Autowired
    private LocalLLMService llmService;

    @PostMapping("/chat")
    public ResponseEntity chat(@RequestBody ChatRequest request) {
        // 這里可以加企業(yè)級邏輯：權(quán)限校驗、敏感詞過濾、日志記錄
        String response = llmService.chat(request.getMessage());
        return ResponseEntity.ok(response);
    }
}

@Service
public class OpenClawService {
    private final RestTemplate restTemplate = new RestTemplate();
    private static final String OPENCLAW_URL = "http://127.0.0.1:3000/api/execute";

    public String executeTask(String taskDescription) {
        Map request = new HashMap<>();
        request.put("task", taskDescription);
        request.put("context", "內(nèi)網(wǎng)環(huán)境，只能訪問/opt/data目錄");
        
        ResponseEntity response = restTemplate.postForEntity(
            OPENCLAW_URL, request, String.class
        );
        
        return response.getBody();
    }
}

@PostMapping("/process-excel")
public String processExcel(@RequestParam String filePath) {
    String task = "讀取" + filePath + "，統(tǒng)計第三列銷售額總和，生成匯總報告保存到/opt/data/report.txt";
    return openClawService.executeTask(task);
}

@Service
public class PrivateRAGService {
    @Autowired
    private VectorStore vectorStore;

    public String queryWithContext(String question) {
        // 1. 向量化檢索本地知識庫
        List docs = vectorStore.similaritySearch(question);
        // 2. 組裝Prompt
        String context = docs.stream().map(Document::getContent).collect(Collectors.joining("\n"));
        String prompt = "基于以下內(nèi)部資料回答問題：\n" + context + "\n\n問題：" + question;

        // 3. 調(diào)用本地模型
        return llmService.chat(prompt);
    }
}

private String desensitize(String content) {
    return content.replaceAll("\\d{11}", "【手機號】")
           .replaceAll("\\d{18}", "【身份證】");
}

# 只允許特定IP段訪問11434端口
iptables -A INPUT -p tcp --dport 11434 -s 192.168.1.0/24 -j ACCEPT
iptables -A INPUT -p tcp --dport 11434 -j DROP

@Aspect
@Component
public class AIAuditAspect {
    @AfterReturning(value = "@annotation(Auditable)", returning = "result")
    public void logAIInteraction(JoinPoint jp, Object result) {
        // 記錄到數(shù)據(jù)庫，留著查賬
        auditLogService.save(new AIInteractionLog(jp.getArgs(), result));
    }
}

sandbox:
  type: chroot    # 類似Docker的隔離，但更輕量
  readonly_paths:
    - /etc/passwd # 想看用戶列表？沒門
    - /var/log    # 日志也不給看

ollama pull qwen2.5:7b-q4_K_M

@GetMapping("/stream-chat")
public Flux streamChat(String message) {
    return chatClient.stream(message)
           .flatMap(content -> Flux.just(content))
           .subscribeOn(Schedulers.boundedElastic());
}

@Cacheable(value = "aiResponse", key = "#message.hashCode()")
public String chat(String message) {
    return chatClient.call(message);
}

System.setProperty("file.encoding", "UTF-8");