feat: add ai cost tracking foundation

ai_knowledge_base_v2/apps/admin-web/src/App.vue

@@ -136,6 +136,14 @@ const modelForm = reactive({
   extraParams: "",
   remark: "",
   timeoutSecond: 30,
+  inputPricePer1k: null as number | null,
+  outputPricePer1k: null as number | null,
+  currency: "CNY",
+  usageScenarios: "",
+  allowSummary: 1,
+  allowReport: 1,
+  allowFixedInfo: 1,
+  allowDeepChat: 1,
 });
 
 const quickModelForm = reactive({
@@ -212,6 +220,9 @@ const nullableModelFields = [
   "responseFormat",
   "extraParams",
   "remark",
+  "inputPricePer1k",
+  "outputPricePer1k",
+  "usageScenarios",
 ] as const;
 
 const systemSettingValues = reactive<Record<string, SystemSettingValue>>({});
@@ -289,6 +300,7 @@ async function loadDashboard() {
 
 async function refreshStorage() { storageLoading.value = true; try { storageStats.value = await api.storageStats(true); ElMessage.success("存储统计已刷新"); } finally { storageLoading.value = false; } }
 function formatBytes(value: unknown) { if (typeof value !== "number") return "无法统计"; const units = ["B", "KB", "MB", "GB", "TB"]; let size = value, i = 0; while (size >= 1024 && i < units.length - 1) { size /= 1024; i += 1; } return `${size.toFixed(i ? 2 : 0)} ${units[i]}`; }
+function formatMoney(value?: number | null, currency = "CNY") { if (typeof value !== "number") return "-"; return `${currency || "CNY"} ${value.toFixed(6)}`; }
 async function cleanupRetrievalLogs() { if (!cleanupBefore.value) return ElMessage.warning("请选择清理日期"); const estimate = await api.estimateRetrievalCleanup(cleanupBefore.value); await ElMessageBox.confirm(`预计清理 ${estimate.estimatedCount} 条检索日志及关联明细，操作日志不会被删除。`, "确认清理", { type: "warning" }); const result = await api.cleanupRetrievalLogs(cleanupBefore.value); ElMessage.success(`已清理 ${result.deleted} 条日志`); await loadCurrentMenu(); }
 async function saveRetention() { await api.saveRetrievalRetention(retentionDays.value); ElMessage.success(retentionDays.value == null ? "已设为永久保留" : `已设为保留 ${retentionDays.value} 天`); await loadCurrentMenu(); }
 
@@ -629,6 +641,14 @@ async function quickAddModel() {
     extraParams: null,
     remark: "快速添加",
     timeoutSecond: 30,
+    inputPricePer1k: null,
+    outputPricePer1k: null,
+    currency: "CNY",
+    usageScenarios: "正式对话",
+    allowSummary: 1,
+    allowReport: 1,
+    allowFixedInfo: 1,
+    allowDeepChat: 1,
   });
   ElMessage.success(`${provider.label} 模型已新增`);
   quickModelForm.apiKey = "";
@@ -715,6 +735,14 @@ function editModel(row: ModelItem) {
     extraParams: row.extraParams ?? "",
     remark: row.remark ?? "",
     timeoutSecond: row.timeoutSecond,
+    inputPricePer1k: row.inputPricePer1k ?? null,
+    outputPricePer1k: row.outputPricePer1k ?? null,
+    currency: row.currency || "CNY",
+    usageScenarios: row.usageScenarios ?? "",
+    allowSummary: row.allowSummary ?? 1,
+    allowReport: row.allowReport ?? 1,
+    allowFixedInfo: row.allowFixedInfo ?? 1,
+    allowDeepChat: row.allowDeepChat ?? 1,
   });
 }
 
@@ -742,6 +770,14 @@ function resetModelForm() {
     extraParams: "",
     remark: "",
     timeoutSecond: 30,
+    inputPricePer1k: null,
+    outputPricePer1k: null,
+    currency: "CNY",
+    usageScenarios: "",
+    allowSummary: 1,
+    allowReport: 1,
+    allowFixedInfo: 1,
+    allowDeepChat: 1,
   });
 }
 
@@ -1001,6 +1037,7 @@ function formatRecordDateTime(value: string, boundary: "start" | "end") {
             <div class="stat"><span>输入 Token</span><strong>{{ stats?.inputToken ?? 0 }}</strong></div>
             <div class="stat"><span>输出 Token</span><strong>{{ stats?.outputToken ?? 0 }}</strong></div>
             <div class="stat"><span>总 Token</span><strong>{{ stats?.totalToken ?? 0 }}</strong></div>
+            <div class="stat"><span>估算成本</span><strong>{{ formatMoney(stats?.estimatedCost, stats?.costCurrency || 'CNY') }}</strong></div>
           </div>
           <section class="storage-panel" v-loading="storageLoading"><div class="storage-panel-head"><div><h3>项目存储占用</h3><p>数据库、Redis 与附件分别统计；无权限或不支持时显示“无法统计”。</p></div><el-button :loading="storageLoading" @click="refreshStorage">手动刷新</el-button></div><div class="storage-grid"><div><span>项目总量</span><strong>{{ formatBytes(storageStats?.totalBytes) }}</strong></div><div><span>数据库</span><strong>{{ formatBytes(storageStats?.detail?.database?.bytes) }}</strong></div><div><span>Redis</span><strong>{{ formatBytes(storageStats?.detail?.redis?.bytes) }}</strong></div><div><span>附件/文件</span><strong>{{ formatBytes(storageStats?.detail?.files?.bytes) }}</strong></div><div><span>近7天增长</span><strong>{{ formatBytes(storageStats?.growth7DaysBytes) }}</strong></div><div><span>近30天增长</span><strong>{{ formatBytes(storageStats?.growth30DaysBytes) }}</strong></div></div><small>最后统计：{{ storageStats?.createdAt || '尚未统计' }}</small></section>
         </template>
@@ -1292,7 +1329,27 @@ function formatRecordDateTime(value: string, boundary: "start" | "end") {
               <el-form-item label="超时秒数">
                 <el-input-number v-model="modelForm.timeoutSecond" :min="1" :max="300" />
               </el-form-item>
+              <el-form-item label="输入单价/千Token">
+                <el-input-number v-model="modelForm.inputPricePer1k" :min="0" :precision="6" :step="0.001" placeholder="不填则不估算成本" />
+              </el-form-item>
+              <el-form-item label="输出单价/千Token">
+                <el-input-number v-model="modelForm.outputPricePer1k" :min="0" :precision="6" :step="0.001" placeholder="不填则不估算成本" />
+              </el-form-item>
+              <el-form-item label="币种">
+                <el-input v-model="modelForm.currency" placeholder="CNY / USD" maxlength="10" />
+              </el-form-item>
             </div>
+            <el-form-item label="适用场景">
+              <el-input v-model="modelForm.usageScenarios" placeholder="例如：正式对话、摘要、固定信息、报告批处理" />
+            </el-form-item>
+            <el-form-item label="可用能力">
+              <div class="entitlement-capabilities">
+                <el-checkbox v-model="modelForm.allowFixedInfo" :true-value="1" :false-value="0">固定信息</el-checkbox>
+                <el-checkbox v-model="modelForm.allowDeepChat" :true-value="1" :false-value="0">深度对话</el-checkbox>
+                <el-checkbox v-model="modelForm.allowSummary" :true-value="1" :false-value="0">摘要沉淀</el-checkbox>
+                <el-checkbox v-model="modelForm.allowReport" :true-value="1" :false-value="0">周期报告</el-checkbox>
+              </div>
+            </el-form-item>
             <el-form-item label="备注">
               <el-input v-model="modelForm.remark" placeholder="用途、额度、注意事项等" />
             </el-form-item>
@@ -1306,6 +1363,10 @@ function formatRecordDateTime(value: string, boundary: "start" | "end") {
             <el-table-column prop="provider" label="Provider" />
             <el-table-column prop="apiType" label="协议" width="170" />
             <el-table-column prop="modelName" label="模型" />
+            <el-table-column label="估算单价" width="180">
+              <template #default="{ row }">{{ row.currency || 'CNY' }} {{ row.inputPricePer1k ?? '-' }}/{{ row.outputPricePer1k ?? '-' }}</template>
+            </el-table-column>
+            <el-table-column prop="usageScenarios" label="适用场景" min-width="160" show-overflow-tooltip />
             <el-table-column prop="baseUrl" label="Base URL" min-width="220" show-overflow-tooltip />
             <el-table-column prop="authType" label="鉴权" width="110" />
             <el-table-column prop="enabled" label="启用" width="90" />
@@ -1521,6 +1582,9 @@ function formatRecordDateTime(value: string, boundary: "start" | "end") {
                   </template>
                 </el-table-column>
                 <el-table-column prop="totalToken" label="Token" width="90" />
+                <el-table-column label="估算成本" width="130">
+                  <template #default="{ row }">{{ formatMoney(row.estimatedCost, row.currency || 'CNY') }}</template>
+                </el-table-column>
                 <el-table-column prop="costMs" label="耗时(ms)" width="100" />
                 <el-table-column prop="status" label="状态" width="100" />
                 <el-table-column prop="errorMessage" label="错误" min-width="220" show-overflow-tooltip />
@@ -1726,6 +1790,10 @@ function formatRecordDateTime(value: string, boundary: "start" | "end") {
           <span>输入 Token：{{ selectedAiLog.inputToken || '-' }}</span>
           <span>输出 Token：{{ selectedAiLog.outputToken || '-' }}</span>
           <span>总 Token：{{ selectedAiLog.totalToken || '-' }}</span>
+          <span>估算成本：{{ formatMoney(selectedAiLog.estimatedCost, selectedAiLog.currency || 'CNY') }}</span>
+          <span>问题类型：{{ selectedAiLog.questionType || '-' }}</span>
+          <span>知识命中：{{ selectedAiLog.knowledgeHit ? '是' : '否' }}</span>
+          <span>路由原因：{{ selectedAiLog.routeReason || '-' }}</span>
           <span>耗时：{{ selectedAiLog.costMs || '-' }}ms</span>
           <span>时间：{{ selectedAiLog.createdAt }}</span>
         </section>

ai_knowledge_base_v2/apps/admin-web/src/types/api.ts

@@ -27,6 +27,8 @@ export interface DashboardStats {
   inputToken: number;
   outputToken: number;
   totalToken: number;
+  estimatedCost?: number | null;
+  costCurrency?: string | null;
 }
 
 export interface PromptDetail {
@@ -164,6 +166,14 @@ export interface ModelItem {
   remark?: string | null;
   timeoutSecond: number;
   enabled: number;
+  inputPricePer1k?: number | null;
+  outputPricePer1k?: number | null;
+  currency: string;
+  usageScenarios?: string | null;
+  allowSummary: number;
+  allowReport: number;
+  allowFixedInfo: number;
+  allowDeepChat: number;
 }
 
 export interface AgentGenerationConfig {
@@ -376,6 +386,11 @@ export interface AiLogRecord {
   outputToken?: number | null;
   totalToken?: number | null;
   costMs?: number | null;
+  estimatedCost?: number | null;
+  currency?: string | null;
+  routeReason?: string | null;
+  questionType?: string | null;
+  knowledgeHit?: boolean;
   status: string;
   errorMessage?: string | null;
   prompt?: string | null;

ai_knowledge_base_v2/apps/backend/alembic/versions/0018_ai_cost_tracking.py

@@ -0,0 +1,66 @@
+"""add ai cost tracking fields
+
+Revision ID: 0018_ai_cost_tracking
+Revises: 0017_share_drafts
+"""
+
+from alembic import op
+import sqlalchemy as sa
+
+
+revision = "0018_ai_cost_tracking"
+down_revision = "0017_share_drafts"
+branch_labels = None
+depends_on = None
+
+
+def upgrade() -> None:
+    inspector = sa.inspect(op.get_bind())
+    model_columns = {column["name"] for column in inspector.get_columns("sys_model")}
+    _add_column_if_missing(model_columns, "sys_model", sa.Column("input_price_per_1k", sa.Numeric(12, 6), nullable=True))
+    _add_column_if_missing(model_columns, "sys_model", sa.Column("output_price_per_1k", sa.Numeric(12, 6), nullable=True))
+    _add_column_if_missing(model_columns, "sys_model", sa.Column("currency", sa.String(10), nullable=False, server_default="CNY"))
+    _add_column_if_missing(model_columns, "sys_model", sa.Column("usage_scenarios", sa.String(255), nullable=True))
+    _add_column_if_missing(model_columns, "sys_model", sa.Column("allow_summary", sa.Integer(), nullable=False, server_default="1"))
+    _add_column_if_missing(model_columns, "sys_model", sa.Column("allow_report", sa.Integer(), nullable=False, server_default="1"))
+    _add_column_if_missing(model_columns, "sys_model", sa.Column("allow_fixed_info", sa.Integer(), nullable=False, server_default="1"))
+    _add_column_if_missing(model_columns, "sys_model", sa.Column("allow_deep_chat", sa.Integer(), nullable=False, server_default="1"))
+
+    log_columns = {column["name"] for column in inspector.get_columns("sys_ai_request_log")}
+    _add_column_if_missing(log_columns, "sys_ai_request_log", sa.Column("model_id", sa.BigInteger(), nullable=True))
+    _add_column_if_missing(log_columns, "sys_ai_request_log", sa.Column("estimated_cost", sa.Numeric(18, 6), nullable=True))
+    _add_column_if_missing(log_columns, "sys_ai_request_log", sa.Column("currency", sa.String(10), nullable=True))
+    _add_column_if_missing(log_columns, "sys_ai_request_log", sa.Column("route_reason", sa.String(255), nullable=True))
+    _add_column_if_missing(log_columns, "sys_ai_request_log", sa.Column("question_type", sa.String(50), nullable=True))
+    _add_column_if_missing(log_columns, "sys_ai_request_log", sa.Column("knowledge_hit", sa.Integer(), nullable=False, server_default="0"))
+    if "model_id" not in log_columns:
+        op.create_index("ix_sys_ai_request_log_model_id", "sys_ai_request_log", ["model_id"])
+
+
+def downgrade() -> None:
+    inspector = sa.inspect(op.get_bind())
+    log_columns = {column["name"] for column in inspector.get_columns("sys_ai_request_log")}
+    if "model_id" in log_columns:
+        op.drop_index("ix_sys_ai_request_log_model_id", table_name="sys_ai_request_log")
+    for column in ["knowledge_hit", "question_type", "route_reason", "currency", "estimated_cost", "model_id"]:
+        if column in log_columns:
+            op.drop_column("sys_ai_request_log", column)
+
+    model_columns = {column["name"] for column in inspector.get_columns("sys_model")}
+    for column in [
+        "allow_deep_chat",
+        "allow_fixed_info",
+        "allow_report",
+        "allow_summary",
+        "usage_scenarios",
+        "currency",
+        "output_price_per_1k",
+        "input_price_per_1k",
+    ]:
+        if column in model_columns:
+            op.drop_column("sys_model", column)
+
+
+def _add_column_if_missing(columns: set[str], table: str, column: sa.Column) -> None:
+    if column.name not in columns:
+        op.add_column(table, column)

ai_knowledge_base_v2/apps/backend/app/api/admin_records.py

@@ -231,7 +231,9 @@ def ai_logs(
             AiRequestLog.id, AiRequestLog.session_id, AiRequestLog.message_id, AiRequestLog.user_id,
             AiRequestLog.model_name, AiRequestLog.knowledge_ids, AiRequestLog.retrieve_count,
             AiRequestLog.input_token, AiRequestLog.output_token, AiRequestLog.total_token,
-            AiRequestLog.cost_ms, AiRequestLog.status, AiRequestLog.error_message, AiRequestLog.created_at,
+            AiRequestLog.cost_ms, AiRequestLog.estimated_cost, AiRequestLog.currency,
+            AiRequestLog.route_reason, AiRequestLog.question_type, AiRequestLog.knowledge_hit,
+            AiRequestLog.status, AiRequestLog.error_message, AiRequestLog.created_at,
         )).order_by(AiRequestLog.created_at.desc()).offset((page - 1) * pageSize).limit(pageSize)
     ).all()
     return api_success(page_result([_ai_log_dict(item, include_chunks=False) for item in logs], total=total, page=page, page_size=pageSize))
@@ -373,6 +375,11 @@ def _ai_log_dict(log: AiRequestLog, *, include_prompt: bool = False, include_chu
         "outputToken": log.output_token,
         "totalToken": log.total_token,
         "costMs": log.cost_ms,
+        "estimatedCost": float(log.estimated_cost) if log.estimated_cost is not None else None,
+        "currency": log.currency,
+        "routeReason": log.route_reason,
+        "questionType": log.question_type,
+        "knowledgeHit": bool(log.knowledge_hit),
         "status": log.status,
         "errorMessage": log.error_message,
         "createdAt": log.created_at,

ai_knowledge_base_v2/apps/backend/app/api/admin_settings.py

@@ -280,6 +280,14 @@ def create_model(
         extra_params=payload.extraParams,
         remark=payload.remark,
         timeout_second=payload.timeoutSecond,
+        input_price_per_1k=payload.inputPricePer1k,
+        output_price_per_1k=payload.outputPricePer1k,
+        currency=payload.currency or "CNY",
+        usage_scenarios=payload.usageScenarios,
+        allow_summary=payload.allowSummary,
+        allow_report=payload.allowReport,
+        allow_fixed_info=payload.allowFixedInfo,
+        allow_deep_chat=payload.allowDeepChat,
         enabled=0,
     )
     db.add(model)
@@ -323,6 +331,14 @@ def update_model(
     model.extra_params = payload.extraParams
     model.remark = payload.remark
     model.timeout_second = payload.timeoutSecond
+    model.input_price_per_1k = payload.inputPricePer1k
+    model.output_price_per_1k = payload.outputPricePer1k
+    model.currency = payload.currency or "CNY"
+    model.usage_scenarios = payload.usageScenarios
+    model.allow_summary = payload.allowSummary
+    model.allow_report = payload.allowReport
+    model.allow_fixed_info = payload.allowFixedInfo
+    model.allow_deep_chat = payload.allowDeepChat
     db.add(model)
     OperationLogService.write(db, admin_id=current_admin.id, module="model", action="update", target_id=model.id)
     db.commit()
@@ -433,6 +449,14 @@ def _model_dict(model: ModelConfig) -> dict:
         "remark": model.remark,
         "timeoutSecond": model.timeout_second,
         "enabled": model.enabled,
+        "inputPricePer1k": float(model.input_price_per_1k) if model.input_price_per_1k is not None else None,
+        "outputPricePer1k": float(model.output_price_per_1k) if model.output_price_per_1k is not None else None,
+        "currency": model.currency,
+        "usageScenarios": model.usage_scenarios,
+        "allowSummary": model.allow_summary,
+        "allowReport": model.allow_report,
+        "allowFixedInfo": model.allow_fixed_info,
+        "allowDeepChat": model.allow_deep_chat,
     }
 
 

ai_knowledge_base_v2/apps/backend/app/models/ai_config.py

@@ -49,6 +49,14 @@ class ModelConfig(Base):
     remark: Mapped[str | None] = mapped_column(String(255), nullable=True)
     timeout_second: Mapped[int] = mapped_column(Integer, default=30, nullable=False)
     enabled: Mapped[int] = mapped_column(default=0, nullable=False)
+    input_price_per_1k: Mapped[Decimal | None] = mapped_column(Numeric(12, 6), nullable=True)
+    output_price_per_1k: Mapped[Decimal | None] = mapped_column(Numeric(12, 6), nullable=True)
+    currency: Mapped[str] = mapped_column(String(10), default="CNY", nullable=False)
+    usage_scenarios: Mapped[str | None] = mapped_column(String(255), nullable=True)
+    allow_summary: Mapped[int] = mapped_column(Integer, default=1, nullable=False)
+    allow_report: Mapped[int] = mapped_column(Integer, default=1, nullable=False)
+    allow_fixed_info: Mapped[int] = mapped_column(Integer, default=1, nullable=False)
+    allow_deep_chat: Mapped[int] = mapped_column(Integer, default=1, nullable=False)
 
 
 class SystemConfig(Base):

ai_knowledge_base_v2/apps/backend/app/models/logs.py

@@ -2,7 +2,9 @@ from __future__ import annotations
 
 from datetime import datetime
 
-from sqlalchemy import BigInteger, DateTime, Integer, String, Text, func
+from decimal import Decimal
+
+from sqlalchemy import BigInteger, DateTime, Integer, Numeric, String, Text, func
 from sqlalchemy.orm import Mapped, mapped_column
 
 from app.models.base import Base
@@ -17,6 +19,7 @@ class AiRequestLog(Base):
     session_id: Mapped[int | None] = mapped_column(BigInteger, index=True, nullable=True)
     message_id: Mapped[int | None] = mapped_column(BigInteger, index=True, nullable=True)
     user_id: Mapped[int | None] = mapped_column(BigInteger, index=True, nullable=True)
+    model_id: Mapped[int | None] = mapped_column(BigInteger, index=True, nullable=True)
     model_name: Mapped[str | None] = mapped_column(String(100), nullable=True)
     prompt: Mapped[str | None] = mapped_column(Text, nullable=True)
     knowledge_ids: Mapped[str | None] = mapped_column(String(500), nullable=True)
@@ -26,6 +29,11 @@ class AiRequestLog(Base):
     output_token: Mapped[int | None] = mapped_column(Integer, nullable=True)
     total_token: Mapped[int | None] = mapped_column(Integer, nullable=True)
     cost_ms: Mapped[int | None] = mapped_column(Integer, nullable=True)
+    estimated_cost: Mapped[Decimal | None] = mapped_column(Numeric(18, 6), nullable=True)
+    currency: Mapped[str | None] = mapped_column(String(10), nullable=True)
+    route_reason: Mapped[str | None] = mapped_column(String(255), nullable=True)
+    question_type: Mapped[str | None] = mapped_column(String(50), nullable=True)
+    knowledge_hit: Mapped[int] = mapped_column(Integer, default=0, nullable=False)
     status: Mapped[str] = mapped_column(String(20), nullable=False)
     error_message: Mapped[str | None] = mapped_column(Text, nullable=True)
     created_at: Mapped[datetime] = mapped_column(DateTime, server_default=func.now(), nullable=False)

ai_knowledge_base_v2/apps/backend/app/schemas/admin.py

@@ -35,6 +35,8 @@ class DashboardStats(BaseModel):
     inputToken: int
     outputToken: int
     totalToken: int
+    estimatedCost: float | None = None
+    costCurrency: str | None = None
 
 
 class AdminUserUpdateRequest(BaseModel):
@@ -161,6 +163,14 @@ class ModelSaveRequest(BaseModel):
     extraParams: str | None = None
     remark: str | None = Field(default=None, max_length=255)
     timeoutSecond: int = Field(default=30, ge=1, le=300)
+    inputPricePer1k: float | None = Field(default=None, ge=0, le=1000000)
+    outputPricePer1k: float | None = Field(default=None, ge=0, le=1000000)
+    currency: str = Field(default="CNY", max_length=10)
+    usageScenarios: str | None = Field(default=None, max_length=255)
+    allowSummary: int = Field(default=1, ge=0, le=1)
+    allowReport: int = Field(default=1, ge=0, le=1)
+    allowFixedInfo: int = Field(default=1, ge=0, le=1)
+    allowDeepChat: int = Field(default=1, ge=0, le=1)
 
 
 class EnableModelRequest(BaseModel):

ai_knowledge_base_v2/apps/backend/app/services/admin_service.py

@@ -133,6 +133,12 @@ class AdminDashboardService:
             msg_filter.append(ChatMessage.created_at <= end)
             ai_filter.append(AiRequestLog.created_at <= end)
 
+        cost_currency = db.scalar(
+            select(AiRequestLog.currency)
+            .where(and_(*ai_filter), AiRequestLog.currency.is_not(None))
+            .order_by(AiRequestLog.id.desc())
+            .limit(1)
+        )
         return {
             "userCount": db.scalar(select(func.count(User.id)).where(and_(*user_filter))) or 0,
             "sessionCount": db.scalar(select(func.count(ChatSession.id)).where(and_(*session_filter))) or 0,
@@ -142,6 +148,8 @@ class AdminDashboardService:
             "inputToken": db.scalar(select(func.coalesce(func.sum(AiRequestLog.input_token), 0)).where(and_(*ai_filter))) or 0,
             "outputToken": db.scalar(select(func.coalesce(func.sum(AiRequestLog.output_token), 0)).where(and_(*ai_filter))) or 0,
             "totalToken": db.scalar(select(func.coalesce(func.sum(AiRequestLog.total_token), 0)).where(and_(*ai_filter))) or 0,
+            "estimatedCost": float(db.scalar(select(func.coalesce(func.sum(AiRequestLog.estimated_cost), 0)).where(and_(*ai_filter))) or 0),
+            "costCurrency": cost_currency,
         }
 
 

ai_knowledge_base_v2/apps/backend/app/services/ai_request_log_service.py

@@ -2,9 +2,11 @@ from __future__ import annotations
 
 import json
 from collections.abc import Sequence
+from decimal import Decimal, ROUND_HALF_UP
 
 from sqlalchemy.orm import Session
 
+from app.models.ai_config import ModelConfig
 from app.models.logs import AiRequestLog
 from app.services.rag_service import RetrievedChunk
 
@@ -25,12 +27,18 @@ class AiRequestLogService:
         output_token: int,
         cost_ms: int,
         retrieved_chunks: Sequence[RetrievedChunk] | None = None,
+        model_id: int | None = None,
+        route_reason: str | None = None,
+        question_type: str | None = None,
     ) -> None:
+        model = db.get(ModelConfig, model_id) if model_id else None
+        estimated_cost, currency = _estimate_cost(model, input_token, output_token)
         db.add(
             AiRequestLog(
                 session_id=session_id,
                 message_id=message_id,
                 user_id=user_id,
+                model_id=model_id,
                 model_name=model_name,
                 prompt=prompt,
                 knowledge_ids=knowledge_ids,
@@ -40,6 +48,11 @@ class AiRequestLogService:
                 output_token=output_token,
                 total_token=input_token + output_token,
                 cost_ms=cost_ms,
+                estimated_cost=estimated_cost,
+                currency=currency,
+                route_reason=route_reason or _default_route_reason(retrieve_count),
+                question_type=question_type or _question_type(retrieve_count),
+                knowledge_hit=1 if retrieve_count > 0 else 0,
                 status="SUCCESS",
             )
         )
@@ -58,18 +71,25 @@ class AiRequestLogService:
         cost_ms: int,
         error_message: str,
         retrieved_chunks: Sequence[RetrievedChunk] | None = None,
+        model_id: int | None = None,
+        route_reason: str | None = None,
+        question_type: str | None = None,
     ) -> None:
         db.add(
             AiRequestLog(
                 session_id=session_id,
                 message_id=message_id,
                 user_id=user_id,
+                model_id=model_id,
                 model_name=model_name,
                 prompt=prompt,
                 knowledge_ids=knowledge_ids,
                 retrieve_count=retrieve_count,
                 retrieved_chunks=_dump_retrieved_chunks(retrieved_chunks),
                 cost_ms=cost_ms,
+                route_reason=route_reason or _default_route_reason(retrieve_count),
+                question_type=question_type or _question_type(retrieve_count),
+                knowledge_hit=1 if retrieve_count > 0 else 0,
                 status="FAILED",
                 error_message=error_message,
             )
@@ -91,3 +111,22 @@ def _dump_retrieved_chunks(chunks: Sequence[RetrievedChunk] | None) -> str | Non
         for index, chunk in enumerate(chunks, start=1)
     ]
     return json.dumps(payload, ensure_ascii=False)
+
+
+def _estimate_cost(model: ModelConfig | None, input_token: int, output_token: int) -> tuple[Decimal | None, str | None]:
+    if model is None:
+        return None, None
+    input_price = Decimal(model.input_price_per_1k or 0)
+    output_price = Decimal(model.output_price_per_1k or 0)
+    if input_price <= 0 and output_price <= 0:
+        return None, model.currency
+    value = (Decimal(input_token) / Decimal(1000) * input_price) + (Decimal(output_token) / Decimal(1000) * output_price)
+    return value.quantize(Decimal("0.000001"), rounding=ROUND_HALF_UP), model.currency
+
+
+def _default_route_reason(retrieve_count: int) -> str:
+    return "当前默认正式模型；本轮命中知识库" if retrieve_count > 0 else "当前默认正式模型；本轮未命中知识库"
+
+
+def _question_type(retrieve_count: int) -> str:
+    return "knowledge_grounded" if retrieve_count > 0 else "general_chat"

ai_knowledge_base_v2/apps/backend/app/services/chat_service.py

@@ -154,6 +154,7 @@ class ChatService:
                 cost_ms=cost_ms,
                 error_message=str(exc),
                 retrieved_chunks=rag_result.chunks if rag_result is not None else None,
+                model_id=None,
             )
             db.commit()
             raise HTTPException(
@@ -204,6 +205,7 @@ class ChatService:
             output_token=completion.output_token,
             cost_ms=cost_ms,
             retrieved_chunks=rag_result.chunks,
+            model_id=completion.model_id,
         )
         db.commit()
         return completion.answer

ai_knowledge_base_v2/apps/backend/app/services/chat_stream_service.py

@@ -117,6 +117,7 @@ class ChatStreamService:
                 cost_ms=cost_ms,
                 error_message=str(exc),
                 retrieved_chunks=rag_result.chunks if rag_result is not None else None,
+                model_id=model_response.model_id if model_response is not None else None,
             )
             _mark_retrieval_failed(db, rag_result, str(exc), cost_ms)
             db.commit()
@@ -137,6 +138,7 @@ class ChatStreamService:
                 cost_ms=cost_ms,
                 error_message="模型未返回有效内容",
                 retrieved_chunks=rag_result.chunks if rag_result is not None else None,
+                model_id=model_response.model_id if model_response is not None else None,
             )
             _mark_retrieval_failed(db, rag_result, "模型未返回有效内容", cost_ms)
             db.commit()
@@ -185,6 +187,7 @@ class ChatStreamService:
             output_token=_rough_token_count(answer),
             cost_ms=cost_ms,
             retrieved_chunks=rag_result.chunks if rag_result is not None else None,
+            model_id=model_response.model_id if model_response is not None else None,
         )
         db.commit()
 
@@ -279,6 +282,7 @@ class ChatStreamService:
                 cost_ms=cost_ms,
                 error_message=str(exc),
                 retrieved_chunks=rag_result.chunks if rag_result is not None else None,
+                model_id=model_response.model_id if model_response is not None else None,
             )
             db.commit()
             raise HTTPException(status_code=status.HTTP_502_BAD_GATEWAY, detail=str(exc)) from exc
@@ -298,6 +302,7 @@ class ChatStreamService:
                 cost_ms=cost_ms,
                 error_message="模型未返回有效内容",
                 retrieved_chunks=rag_result.chunks if rag_result is not None else None,
+                model_id=model_response.model_id if model_response is not None else None,
             )
             db.commit()
             raise HTTPException(status_code=status.HTTP_502_BAD_GATEWAY, detail="模型未返回有效内容")
@@ -381,6 +386,7 @@ def _write_success(
         output_token=_rough_token_count(answer),
         cost_ms=cost_ms,
         retrieved_chunks=rag_result.chunks if rag_result is not None else None,
+        model_id=model_response.model_id if model_response is not None else None,
     )
     if rag_result is not None and rag_result.retrieval_log_id:
         retrieval_log = db.get(KnowledgeRetrievalLog, rag_result.retrieval_log_id)

ai_knowledge_base_v2/apps/backend/tests/test_ai_cost_tracking.py

@@ -0,0 +1,60 @@
+from __future__ import annotations
+
+from decimal import Decimal
+
+from sqlalchemy import create_engine
+from sqlalchemy.orm import Session
+from sqlalchemy.pool import StaticPool
+
+from app.models import Base
+from app.models.ai_config import ModelConfig
+from app.models.logs import AiRequestLog
+from app.services.ai_request_log_service import AiRequestLogService
+
+
+def _db() -> Session:
+    engine = create_engine("sqlite:///:memory:", connect_args={"check_same_thread": False}, poolclass=StaticPool)
+    Base.metadata.create_all(engine)
+    return Session(engine)
+
+
+def test_ai_request_log_estimates_cost_from_model_price():
+    with _db() as db:
+        model = ModelConfig(
+            id=1,
+            provider="test",
+            api_type="openai_compatible",
+            model_name="test-model",
+            api_url="https://example.com",
+            api_key="secret",
+            input_price_per_1k=Decimal("0.002"),
+            output_price_per_1k=Decimal("0.006"),
+            currency="CNY",
+            timeout_second=30,
+        )
+        db.add(model)
+        db.commit()
+
+        AiRequestLogService.write_success(
+            db,
+            session_id=1,
+            message_id=2,
+            user_id=3,
+            model_id=1,
+            model_name="test-model",
+            prompt="hello",
+            knowledge_ids="1",
+            retrieve_count=2,
+            input_token=1000,
+            output_token=500,
+            cost_ms=120,
+        )
+        db.commit()
+
+        log = db.query(AiRequestLog).one()
+        assert log.estimated_cost == Decimal("0.005000")
+        assert log.currency == "CNY"
+        assert log.knowledge_hit == 1
+        assert log.question_type == "knowledge_grounded"
+        assert "命中知识库" in (log.route_reason or "")
+

ai_knowledge_base_v2/docs/qianwen_product_todo.md

@@ -649,6 +649,10 @@ AI 日志增加：
 - 不同问题类型可以走不同模型；
 - 日志能解释为什么选这个模型。
 
+#### 开发进度
+
+- 2026-07-31：一期已新增模型输入/输出千 Token 单价、币种、适用场景和可用能力字段；AI 请求日志记录模型 ID、估算成本、币种、问题类型、知识命中和路由原因；数据看板展示筛选范围内估算成本。暂未自动切换模型，避免影响正式回答稳定性，后续再基于这些字段做模型分流。
+
 ---
 
 ### 10. 用户端“我的实修档案”