feat: 添加多维度计费系统和视频任务管理功能

计费系统:
- 新增 BillingRule 和 DimensionCollector 数据模型
- 实现 FormulaEngine 安全表达式求值引擎 (AST 白名单)
- 支持 dimension/matrix/tiered/constant 多种维度映射
- BillingRuleService 支持 Provider Model -> GlobalModel 规则回退
- CLI task_type 在计费域自动映射为 chat

视频任务增强:
- 添加 request_metadata 字段记录候选 key 和计费规则快照
- 后台轮询支持并发控制 (Semaphore + 独立 session)
- 任务终态自动写入 Usage 记录并计算成本
- 新增视频任务管理 API 和前端界面

其他改进:
- UsageService 新增 record_usage_with_custom_cost 方法
- StandardizedUsage 支持 dimensions 字段 (兼容 extra)
- 配置新增 BILLING_REQUIRE_RULE 和 BILLING_STRICT_MODE

tests/services/billing/test_formula_engine.py

@@ -0,0 +1,169 @@
+import pytest
+
+from src.services.billing.formula_engine import (
+    BillingIncompleteError,
+    FormulaEngine,
+    UnsafeExpressionError,
+)
+
+
+class TestSafeExpression:
+    def test_reject_attribute_access(self) -> None:
+        engine = FormulaEngine()
+        with pytest.raises(UnsafeExpressionError):
+            engine.evaluate(
+                expression="(1).__class__",
+                variables={},
+                dimensions={},
+                dimension_mappings={},
+                strict_mode=True,  # 确保抛出异常，便于断言类型
+            )
+
+    def test_reject_import(self) -> None:
+        engine = FormulaEngine()
+        with pytest.raises(UnsafeExpressionError):
+            engine.evaluate(
+                expression="__import__('os').system('echo hacked')",
+                variables={},
+                dimensions={},
+                dimension_mappings={},
+                strict_mode=True,
+            )
+
+
+class TestFormulaEngine:
+    def test_basic_video_formula(self) -> None:
+        engine = FormulaEngine()
+        result = engine.evaluate(
+            expression="(base_price + duration_seconds * price_per_second) * resolution_multiplier",
+            variables={"base_price": 0.05, "price_per_second": 0.02},
+            dimensions={"duration_seconds": 10, "resolution": "720p"},
+            dimension_mappings={
+                "duration_seconds": {
+                    "source": "dimension",
+                    "key": "duration_seconds",
+                    "required": True,
+                },
+                "resolution_multiplier": {
+                    "source": "matrix",
+                    "key": "resolution",
+                    "map": {"720p": 1.0, "1080p": 1.5},
+                    "default": 1.0,
+                },
+            },
+        )
+        assert result.status == "complete"
+        assert result.missing_required == []
+        assert abs(result.cost - 0.25) < 1e-9
+
+    def test_required_dimension_missing_non_strict(self) -> None:
+        engine = FormulaEngine()
+        result = engine.evaluate(
+            expression="base_price + duration_seconds * price_per_second",
+            variables={"base_price": 0.05, "price_per_second": 0.02},
+            dimensions={"duration_seconds": None},
+            dimension_mappings={
+                "duration_seconds": {
+                    "source": "dimension",
+                    "key": "duration_seconds",
+                    "required": True,
+                },
+            },
+            strict_mode=False,
+        )
+        assert result.status == "incomplete"
+        assert result.cost == 0.0
+        assert result.missing_required == ["duration_seconds"]
+
+    def test_required_dimension_missing_strict_raises(self) -> None:
+        engine = FormulaEngine()
+        with pytest.raises(BillingIncompleteError) as exc:
+            engine.evaluate(
+                expression="base_price + duration_seconds * price_per_second",
+                variables={"base_price": 0.05, "price_per_second": 0.02},
+                dimensions={"duration_seconds": None},
+                dimension_mappings={
+                    "duration_seconds": {
+                        "source": "dimension",
+                        "key": "duration_seconds",
+                        "required": True,
+                    },
+                },
+                strict_mode=True,
+            )
+        assert exc.value.missing_required == ["duration_seconds"]
+
+    def test_allow_zero(self) -> None:
+        engine = FormulaEngine()
+
+        # allow_zero=false（默认）：0 视为缺失
+        result = engine.evaluate(
+            expression="duration_seconds * 1",
+            variables={},
+            dimensions={"duration_seconds": 0},
+            dimension_mappings={
+                "duration_seconds": {
+                    "source": "dimension",
+                    "key": "duration_seconds",
+                    "required": True,
+                },
+            },
+        )
+        assert result.status == "incomplete"
+        assert result.missing_required == ["duration_seconds"]
+
+        # allow_zero=true：0 合法
+        result = engine.evaluate(
+            expression="duration_seconds * 1",
+            variables={},
+            dimensions={"duration_seconds": 0},
+            dimension_mappings={
+                "duration_seconds": {
+                    "source": "dimension",
+                    "key": "duration_seconds",
+                    "required": True,
+                    "allow_zero": True,
+                },
+            },
+        )
+        assert result.status == "complete"
+        assert result.cost == 0.0
+
+    def test_tiered_mapping(self) -> None:
+        engine = FormulaEngine()
+
+        result = engine.evaluate(
+            expression="input_price",
+            variables={},
+            dimensions={"total_input_tokens": 100_000},
+            dimension_mappings={
+                "input_price": {
+                    "source": "tiered",
+                    "tier_key": "total_input_tokens",
+                    "tiers": [
+                        {"up_to": 128_000, "value": 3.0},
+                        {"up_to": None, "value": 1.5},
+                    ],
+                }
+            },
+        )
+        assert result.status == "complete"
+        assert result.cost == 3.0
+
+        result = engine.evaluate(
+            expression="input_price",
+            variables={},
+            dimensions={"total_input_tokens": 200_000},
+            dimension_mappings={
+                "input_price": {
+                    "source": "tiered",
+                    "tier_key": "total_input_tokens",
+                    "tiers": [
+                        {"up_to": 128_000, "value": 3.0},
+                        {"up_to": None, "value": 1.5},
+                    ],
+                }
+            },
+        )
+        assert result.status == "complete"
+        assert result.cost == 1.5