refactor: 移除 Python 后端源码，全面迁移至 Rust gateway 架构

- 删除全部 Python 源码 (src/) 及 Alembic 迁移脚本，归档至 _deprecated_py_src/
- 重构 Rust gateway ai_pipeline: 拆分 planner/finalize 模块，新增 contracts/adaptation 层
- 重组 handlers 模块为 admin/public/proxy/internal/shared 子模块结构
- 新增 executor 模块，引入 Rust 原生数据库迁移 (aether-data/migrations)
- 简化 CI/Docker 构建流程，移除 base image 二级构建，统一为单一 app image
- 移除 Python 相关基础设施文件 (entrypoint.sh, gunicorn_conf.py, Dockerfile.base)

_deprecated_py_src/services/billing/usage_mapper.py

@@ -0,0 +1,251 @@
+"""
+Usage 字段映射器
+
+将不同 API 格式的原始 usage 数据映射为标准化格式。
+
+支持的格式：
+- openai:*: OpenAI compatible (Chat/CLI)
+- claude:*: Anthropic Messages (Chat/CLI)
+- gemini:*: Google Gemini (Chat/CLI)
+"""
+
+from typing import Any
+
+from src.services.billing.models import StandardizedUsage
+
+
+class UsageMapper:
+    """
+    Usage 字段映射器
+
+    将不同 API 格式的 usage 统一映射为 StandardizedUsage。
+
+    示例:
+        # OpenAI 格式
+        raw_usage = {
+            "prompt_tokens": 100,
+            "completion_tokens": 50,
+            "prompt_tokens_details": {"cached_tokens": 20},
+            "completion_tokens_details": {"reasoning_tokens": 10}
+        }
+        usage = UsageMapper.map(raw_usage, "OPENAI")
+
+        # Claude 格式
+        raw_usage = {
+            "input_tokens": 100,
+            "output_tokens": 50,
+            "cache_creation_input_tokens": 30,
+            "cache_read_input_tokens": 20
+        }
+        usage = UsageMapper.map(raw_usage, "CLAUDE")
+    """
+
+    # =========================================================================
+    # 字段映射配置
+    # 格式: "source_path" -> "target_field"
+    # source_path 支持点号分隔的嵌套路径
+    # =========================================================================
+
+    # OpenAI 格式字段映射
+    OPENAI_MAPPING: dict[str, str] = {
+        "prompt_tokens": "input_tokens",
+        "completion_tokens": "output_tokens",
+        "prompt_tokens_details.cached_tokens": "cache_read_tokens",
+        "completion_tokens_details.reasoning_tokens": "reasoning_tokens",
+    }
+
+    # Claude 格式字段映射
+    CLAUDE_MAPPING: dict[str, str] = {
+        "input_tokens": "input_tokens",
+        "output_tokens": "output_tokens",
+        "cache_creation_input_tokens": "cache_creation_tokens",
+        "cache_read_input_tokens": "cache_read_tokens",
+    }
+
+    # Gemini 格式字段映射
+    GEMINI_MAPPING: dict[str, str] = {
+        "promptTokenCount": "input_tokens",
+        "candidatesTokenCount": "output_tokens",
+        "cachedContentTokenCount": "cache_read_tokens",
+        # Gemini 的 usageMetadata 格式
+        "usageMetadata.promptTokenCount": "input_tokens",
+        "usageMetadata.candidatesTokenCount": "output_tokens",
+        "usageMetadata.cachedContentTokenCount": "cache_read_tokens",
+    }
+
+    @classmethod
+    def map(
+        cls,
+        raw_usage: dict[str, Any],
+        api_format: str,
+        extra_mapping: dict[str, str] | None = None,
+    ) -> StandardizedUsage:
+        """
+        将原始 usage 映射为标准化格式
+
+        Args:
+            raw_usage: 原始 usage 字典
+            api_format: API 格式 ("OPENAI", "CLAUDE", "GEMINI" 等)
+            extra_mapping: 额外的字段映射（用于自定义扩展）
+
+        Returns:
+            标准化的 usage 对象
+        """
+        if not raw_usage:
+            return StandardizedUsage()
+
+        # 获取对应格式的字段映射
+        mapping = cls._get_mapping(api_format)
+
+        # 合并额外映射
+        if extra_mapping:
+            mapping = {**mapping, **extra_mapping}
+
+        result = StandardizedUsage()
+
+        # 执行映射
+        for source_path, target_field in mapping.items():
+            value = cls._get_nested_value(raw_usage, source_path)
+            if value is not None:
+                result.set(target_field, value)
+
+        return result
+
+    @classmethod
+    def map_from_response(
+        cls,
+        response: dict[str, Any],
+        api_format: str,
+    ) -> StandardizedUsage:
+        """
+        从完整响应中提取并映射 usage
+
+        不同 API 格式的 usage 位置可能不同：
+        - OpenAI: response["usage"]
+        - Claude: response["usage"] 或 message_delta 中
+        - Gemini: response["usageMetadata"]
+
+        Args:
+            response: 完整的 API 响应
+            api_format: API 格式
+
+        Returns:
+            标准化的 usage 对象
+        """
+        format_norm = (api_format or "").strip().lower()
+        api_family = format_norm.split(":", 1)[0] if ":" in format_norm else format_norm
+
+        # 提取 usage 部分
+        usage_data: dict[str, Any] = {}
+
+        if api_family == "gemini":
+            # Gemini: usageMetadata
+            usage_data = response.get("usageMetadata", {})
+            if not usage_data:
+                # 尝试从 candidates 中获取
+                candidates = response.get("candidates", [])
+                if candidates:
+                    usage_data = candidates[0].get("usageMetadata", {})
+        else:
+            # OpenAI/Claude: usage
+            usage_data = response.get("usage", {})
+
+        return cls.map(usage_data, api_format)
+
+    @classmethod
+    def _get_mapping(cls, api_format: str) -> dict[str, str]:
+        """获取对应格式的字段映射"""
+        format_norm = (api_format or "").strip().lower()
+        api_family = format_norm.split(":", 1)[0] if ":" in format_norm else format_norm
+
+        if api_family == "openai":
+            return cls.OPENAI_MAPPING
+        if api_family == "gemini":
+            return cls.GEMINI_MAPPING
+        # 默认 Claude（也覆盖未知/空值）
+        return cls.CLAUDE_MAPPING
+
+    @classmethod
+    def _get_nested_value(cls, data: dict[str, Any], path: str) -> Any:
+        """
+        获取嵌套字段值
+
+        支持点号分隔的路径，如 "prompt_tokens_details.cached_tokens"
+
+        Args:
+            data: 数据字典
+            path: 字段路径
+
+        Returns:
+            字段值，不存在则返回 None
+        """
+        if not data or not path:
+            return None
+
+        keys = path.split(".")
+        value: Any = data
+
+        for key in keys:
+            if isinstance(value, dict):
+                value = value.get(key)
+                if value is None:
+                    return None
+            else:
+                return None
+
+        return value
+
+    @classmethod
+    def register_format(cls, format_name: str, mapping: dict[str, str]) -> None:
+        """
+        注册新的格式映射
+
+        Args:
+            format_name: 格式名称（会自动转为大写）
+            mapping: 字段映射
+        """
+        cls.FORMAT_MAPPINGS[format_name.upper()] = mapping
+
+    @classmethod
+    def get_supported_formats(cls) -> list:
+        """获取所有支持的格式"""
+        return list(cls.FORMAT_MAPPINGS.keys())
+
+
+# =========================================================================
+# 便捷函数
+# =========================================================================
+
+
+def map_usage(
+    raw_usage: dict[str, Any],
+    api_format: str,
+) -> StandardizedUsage:
+    """
+    便捷函数：将原始 usage 映射为标准化格式
+
+    Args:
+        raw_usage: 原始 usage 字典
+        api_format: API 格式
+
+    Returns:
+        StandardizedUsage 对象
+    """
+    return UsageMapper.map(raw_usage, api_format)
+
+
+def map_usage_from_response(
+    response: dict[str, Any],
+    api_format: str,
+) -> StandardizedUsage:
+    """
+    便捷函数：从响应中提取并映射 usage
+
+    Args:
+        response: API 响应
+        api_format: API 格式
+
+    Returns:
+        StandardizedUsage 对象
+    """
+    return UsageMapper.map_from_response(response, api_format)