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自定义代码 RAG ​

代码检索增强生成（Code RAG）是 ByteBuddy 的核心功能之一，它允许 AI 智能地检索和理解您的代码库，从而提供更准确、更有针对性的代码建议。

什么是代码 RAG？ ​

基本概念 ​

代码 RAG 结合了：

  • 检索（Retrieval）: 从代码库中查找相关的代码片段
  • 增强（Augmented）: 使用检索到的代码上下文增强 AI 的理解
  • 生成（Generation）: 基于增强的上下文生成代码或回答

工作原理 ​

  1. 代码索引: 将代码库分割成可检索的块
  2. 向量化: 将代码块转换为向量表示
  3. 相似度搜索: 根据查询找到最相关的代码片段
  4. 上下文注入: 将相关代码注入到 AI 的提示中
  5. 智能生成: 基于检索到的上下文生成响应

配置代码 RAG ​

基础配置 ​

json
{
  "rag": {
    "enabled": true,
    "indexing": {
      "auto_index": true,
      "index_interval": "daily",
      "include_patterns": ["src/**/*", "lib/**/*"],
      "exclude_patterns": ["node_modules/**", "dist/**", "*.test.*"]
    },
    "retrieval": {
      "max_results": 10,
      "similarity_threshold": 0.7,
      "context_window": 4000
    }
  }
}

高级配置 ​

json
{
  "rag": {
    "vector_store": {
      "type": "chroma",
      "path": "./.bytebuddy/vector_store",
      "embedding_model": "text-embedding-ada-002"
    },
    "chunking": {
      "strategy": "semantic",
      "chunk_size": 1000,
      "chunk_overlap": 200,
      "respect_code_boundaries": true
    },
    "filtering": {
      "language_filters": true,
      "dependency_aware": true,
      "test_code_exclusion": false
    }
  }
}

索引策略 ​

代码分割策略 ​

按文件分割 ​

json
{
  "chunking": {
    "strategy": "file",
    "max_file_size": "10KB",
    "merge_small_files": true
  }
}

按函数分割 ​

json
{
  "chunking": {
    "strategy": "function",
    "include_comments": true,
    "include_docstrings": true,
    "max_function_size": 50
  }
}

语义分割 ​

json
{
  "chunking": {
    "strategy": "semantic",
    "embedding_model": "code-bert",
    "similarity_threshold": 0.8,
    "max_chunk_size": 1000
  }
}

索引优化 ​

增量索引 ​

json
{
  "indexing": {
    "mode": "incremental",
    "watch_changes": true,
    "batch_size": 100,
    "index_delay": "5s"
  }
}

定期重建 ​

json
{
  "indexing": {
    "mode": "scheduled",
    "rebuild_interval": "weekly",
    "full_rebuild_day": "sunday",
    "rebuild_time": "02:00"
  }
}

检索优化 ​

混合检索 ​

json
{
  "retrieval": {
    "hybrid_search": true,
    "keyword_weight": 0.3,
    "semantic_weight": 0.7,
    "rerank": true,
    "rerank_model": "cross-encoder/ms-marco-MiniLM-L-6-v2"
  }
}

上下文过滤 ​

json
{
  "retrieval": {
    "filters": {
      "file_types": [".js", ".ts", ".py", ".java"],
      "exclude_test_files": false,
      "include_dependencies": true,
      "date_range": {
        "start": "2024-01-01",
        "end": null
      }
    }
  }
}

多模态检索 ​

json
{
  "retrieval": {
    "multimodal": {
      "code_embeddings": true,
      "text_embeddings": true,
      "documentation_embeddings": true,
      "comment_embeddings": true
    }
  }
}

向量存储 ​

ChromaDB 配置 ​

json
{
  "vector_store": {
    "type": "chroma",
    "host": "localhost",
    "port": 8000,
    "collection": "bytebuddy-code",
    "persist_directory": "./chroma_db",
    "embedding_function": "openai"
  }
}

Pinecone 配置 ​

json
{
  "vector_store": {
    "type": "pinecone",
    "api_key": "${PINECONE_API_KEY}",
    "environment": "us-west1-gcp",
    "index_name": "bytebuddy-code",
    "dimension": 1536,
    "metric": "cosine"
  }
}

本地存储 ​

json
{
  "vector_store": {
    "type": "local",
    "path": "./.bytebuddy/vectors",
    "compression": true,
    "encryption": false
  }
}

语言特定优化 ​

Python 代码 RAG ​

json
{
  "languages": {
    "python": {
      "parsing": {
        "extract_classes": true,
        "extract_functions": true,
        "extract_docstrings": true,
        "include_type_hints": true
      },
      "filters": {
        "include_imports": false,
        "include_decorators": true,
        "filter_private_methods": true
      }
    }
  }
}

JavaScript/TypeScript 代码 RAG ​

json
{
  "languages": {
    "javascript": {
      "parsing": {
        "extract_components": true,
        "extract_hooks": true,
        "extract_types": true,
        "include_javadoc": true
      },
      "filters": {
        "include_node_modules": false,
        "include_tests": false,
        "filter_minified": true
      }
    }
  }
}

Java 代码 RAG ​

json
{
  "languages": {
    "java": {
      "parsing": {
        "extract_classes": true,
        "extract_interfaces": true,
        "extract_methods": true,
        "include_annotations": true,
        "include_javadoc": true
      },
      "filters": {
        "include_package_private": false,
        "include_synthetic": false,
        "filter_getters_setters": true
      }
    }
  }
}

实时更新 ​

文件监控 ​

json
{
  "watching": {
    "enabled": true,
    "debounce": 1000,
    "patterns": ["src/**/*"],
    "ignore_patterns": ["*.tmp", "*.log"],
    "events": ["create", "modify", "delete"],
    "auto_reindex": true
  }
}

Git 集成 ​

json
{
  "git_integration": {
    "enabled": true,
    "index_branches": ["main", "develop"],
    "track_commits": true,
    "pr_context": true,
    "diff_analysis": true
  }
}

性能优化 ​

缓存策略 ​

json
{
  "cache": {
    "enabled": true,
    "query_cache_size": 1000,
    "result_cache_ttl": 3600,
    "vector_cache_ttl": 86400,
    "compression": true
  }
}

并发控制 ​

json
{
  "concurrency": {
    "max_concurrent_queries": 10,
    "queue_size": 100,
    "timeout": 30000,
    "batch_size": 50
  }
}

质量控制 ​

相关性评估 ​

json
{
  "quality": {
    "relevance_threshold": 0.7,
    "diversity_boost": 0.1,
    "freshness_weight": 0.2,
    "quality_threshold": 0.8
  }
}

人工反馈 ​

json
{
  "feedback": {
    "enabled": true,
    "collect_user_ratings": true,
    "auto_retrain": true,
    "feedback_threshold": 0.6
  }
}

监控和分析 ​

性能监控 ​

json
{
  "monitoring": {
    "track_query_times": true,
    "track_hit_rates": true,
    "track_error_rates": true,
    "dashboard_enabled": true
  }
}

分析报告 ​

json
{
  "analytics": {
    "query_analysis": true,
    "usage_patterns": true,
    "performance_metrics": true,
    "report_interval": "daily"
  }
}

安全考虑 ​

数据隐私 ​

json
{
  "privacy": {
    "encryption_at_rest": true,
    "encryption_in_transit": true,
    "anonymize_data": false,
    "data_retention": "90d"
  }
}

访问控制 ​

json
{
  "access_control": {
    "role_based_access": true,
    "api_key_required": true,
    "rate_limiting": true,
    "audit_logging": true
  }
}

故障排除 ​

常见问题 ​

索引构建缓慢

json
{
  "optimization": {
    "parallel_processing": true,
    "batch_size": 200,
    "memory_limit": "2GB",
    "temp_directory": "./temp"
  }
}

检索结果不准确

json
{
  "tuning": {
    "similarity_threshold": 0.6,
    "rerank_enabled": true,
    "context_expansion": true,
    "query_expansion": true
  }
}

调试工具 ​

bash
# 检查索引状态
bytebuddy rag status

# 测试检索
bytebuddy rag test --query="用户登录功能"

# 分析索引质量
bytebuddy rag analyze --quality

# 重建索引
bytebuddy rag rebuild --force

最佳实践 ​

索引策略 ​

  1. 增量索引: 只索引变更的文件
  2. 智能分割: 尊重代码边界
  3. 定期清理: 删除过期的索引
  4. 监控质量: 跟踪检索准确性

性能优化 ​

  1. 缓存结果: 缓存常用查询
  2. 并行处理: 多线程索引和检索
  3. 压缩存储: 减少存储空间
  4. 批量操作: 批量处理文件变更

质量保证 ​

  1. 相关度调优: 调整相似度阈值
  2. 重排序: 使用重排序模型
  3. 人工反馈: 收集用户反馈
  4. 持续改进: 基于反馈优化

通过合理配置代码 RAG，您可以让 ByteBuddy 更好地理解您的代码库，提供更准确、更有针对性的 AI 辅助。

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