你的问题 / Your question:“我们就把 OpenClaw DeepSeek通过 Ollamareview Spring Boot 代码给我一个完整方案。”下面给你一个可以真正落地的完整架构从环境 → 模型 → OpenClaw → 代码扫描 → Review 输出。我会用中文 English说明。一、整体架构 (Overall Architecture)目标用OpenClaw DeepSeek Ollama自动 ReviewSpring Boot 项目代码架构┌───────────────┐ │ Spring Boot │ │ Project Repo │ │ (Git / Local) │ └───────┬───────┘ │ │ scan ▼ ┌───────────────┐ │ OpenClaw │ │ Code Analyzer │ └───────┬───────┘ │ │ prompt ▼ ┌───────────────┐ │ Ollama │ │ DeepSeek LLM │ └───────┬───────┘ │ ▼ ┌───────────────┐ │ Review Report │ │ Markdown/HTML │ └───────────────┘功能自动扫描 Java 文件提取 Spring Boot 关键代码调用 DeepSeek生成 Review 报告二、安装环境 (Environment Setup)建议 Linux / Mac / WSL1 安装 Ollamacurl -fsSL https://ollama.com/install.sh | sh检查ollama --version2 安装 DeepSeek 模型推荐ollama pull deepseek-coder:33b如果机器普通ollama pull deepseek-coder:6.7b测试ollama run deepseek-coder输入review java spring boot code3 安装 OpenClawgit clone https://github.com/openclaw/openclaw cd openclaw pip install -r requirements.txt三、配置 Ollama APIOllama 默认 APIhttp://localhost:11434测试curl http://localhost:11434/api/generate -d { model: deepseek-coder, prompt: review java code, stream: false }四、Spring Boot Review Prompt关键是Prompt 设计示例You are a senior Java architect. Please review the following Spring Boot code. Check: 1 code security 2 performance issues 3 bad practice 4 concurrency issues 5 SQL injection 6 memory leak 7 transaction problem 8 API design 9 microservice architecture Return result in markdown: ## Issues ## Suggestions ## Refactor code五、OpenClaw 扫描代码扫描 Spring Bootproject ├─ controller ├─ service ├─ repository ├─ entity └─ configPython 扫描器import os def scan_java(path): files [] for root, dirs, fs in os.walk(path): for f in fs: if f.endswith(.java): files.append(os.path.join(root,f)) return files六、调用 Ollama ReviewPython 示例import requests def review_code(code): prompt f Review this Spring Boot code: {code} r requests.post( http://localhost:11434/api/generate, json{ model:deepseek-coder, prompt:prompt, stream:False } ) return r.json()[response]七、自动 Review 整个项目完整脚本files scan_java(./springboot-project) for f in files: code open(f).read() result review_code(code) print(FILE:,f) print(result)八、生成 Review 报告输出 Markdownreview.md示例# Spring Boot Code Review ## UserController.java ### Issues - missing validation - possible NPE ### Suggestion Use Valid annotation --- ## UserService.java ### Issues transaction missing ### Suggestion add Transactional九、CI自动Review (推荐)接入 CIGitHub Actions流程git push ↓ CI pipeline ↓ run openclaw scan ↓ call deepseek ↓ generate review report ↓ comment PR十、最终完整架构生产级方案┌──────────────┐ │ Git Repo │ └──────┬───────┘ │ ▼ ┌──────────────────┐ │ OpenClaw Scanner │ └──────┬───────────┘ │ ▼ ┌──────────────────┐ │ Prompt Builder │ └──────┬───────────┘ │ ▼ ┌──────────────────┐ │ Ollama API │ │ DeepSeek Coder │ └──────┬───────────┘ │ ▼ ┌──────────────────┐ │ Review Generator │ └──────┬───────────┘ │ ▼ ┌──────────────────┐ │ Markdown / PR │ └──────────────────┘十一、增强方案 (Advanced)建议再加 3 个组件1 AST分析用tree-sitter只给 LLM关键代码否则 token 爆炸。2 RAG把spring best practice java security rule放进向量库推荐milvus chroma3 multi-agent review多个角色agent1 security agent2 performance agent3 architecture agent4 bug detection效果比单次 prompt 强很多。十二、最终效果自动生成类似Spring Boot Code Review Score: 7/10 Security Issues: - SQL injection risk Architecture Issues: - Service layer mixing logic Performance: - N1 query Suggestion: Refactor repository layer十三、如果你愿意我可以直接给你一个完整开源级项目模板包含OpenClawOllamaDeepSeekSpring Boot reviewer自动 PR 评论向量数据库 RAGWeb UI大概5000 行代码的完整系统。我也可以再给你一套公司级 AI Code Review 架构很多大厂正在用的那种。