From a84650bb9e353c5a371b7d34fa36b3a2bf09fbad Mon Sep 17 00:00:00 2001 From: Nelson <1475262689@qq.com> Date: Fri, 31 Jul 2026 16:24:35 +0800 Subject: [PATCH] feat: add ai cost tracking foundation --- .../apps/admin-web/src/App.vue | 68 +++++++++++++++++++ .../apps/admin-web/src/types/api.ts | 15 ++++ .../alembic/versions/0018_ai_cost_tracking.py | 66 ++++++++++++++++++ .../apps/backend/app/api/admin_records.py | 9 ++- .../apps/backend/app/api/admin_settings.py | 24 +++++++ .../apps/backend/app/models/ai_config.py | 8 +++ .../apps/backend/app/models/logs.py | 10 ++- .../apps/backend/app/schemas/admin.py | 10 +++ .../backend/app/services/admin_service.py | 8 +++ .../app/services/ai_request_log_service.py | 39 +++++++++++ .../apps/backend/app/services/chat_service.py | 2 + .../app/services/chat_stream_service.py | 6 ++ .../backend/tests/test_ai_cost_tracking.py | 60 ++++++++++++++++ .../docs/qianwen_product_todo.md | 4 ++ 14 files changed, 327 insertions(+), 2 deletions(-) create mode 100644 ai_knowledge_base_v2/apps/backend/alembic/versions/0018_ai_cost_tracking.py create mode 100644 ai_knowledge_base_v2/apps/backend/tests/test_ai_cost_tracking.py diff --git a/ai_knowledge_base_v2/apps/admin-web/src/App.vue b/ai_knowledge_base_v2/apps/admin-web/src/App.vue index b908de5..dd1ad70 100644 --- a/ai_knowledge_base_v2/apps/admin-web/src/App.vue +++ b/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>({}); @@ -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") {
输入 Token{{ stats?.inputToken ?? 0 }}
输出 Token{{ stats?.outputToken ?? 0 }}
总 Token{{ stats?.totalToken ?? 0 }}
+
估算成本{{ formatMoney(stats?.estimatedCost, stats?.costCurrency || 'CNY') }}

项目存储占用

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”。

手动刷新
项目总量{{ formatBytes(storageStats?.totalBytes) }}
数据库{{ formatBytes(storageStats?.detail?.database?.bytes) }}
Redis{{ formatBytes(storageStats?.detail?.redis?.bytes) }}
附件/文件{{ formatBytes(storageStats?.detail?.files?.bytes) }}
近7天增长{{ formatBytes(storageStats?.growth7DaysBytes) }}
近30天增长{{ formatBytes(storageStats?.growth30DaysBytes) }}
最后统计：{{ storageStats?.createdAt || '尚未统计' }}
@@ -1292,7 +1329,27 @@ function formatRecordDateTime(value: string, boundary: "start" | "end") { + + + + + + + + + + + + + +
+ 固定信息 + 深度对话 + 摘要沉淀 + 周期报告 +
+ @@ -1306,6 +1363,10 @@ function formatRecordDateTime(value: string, boundary: "start" | "end") { + + + + @@ -1521,6 +1582,9 @@ function formatRecordDateTime(value: string, boundary: "start" | "end") { + + + @@ -1726,6 +1790,10 @@ function formatRecordDateTime(value: string, boundary: "start" | "end") { 输入 Token：{{ selectedAiLog.inputToken || '-' }} 输出 Token：{{ selectedAiLog.outputToken || '-' }} 总 Token：{{ selectedAiLog.totalToken || '-' }} + 估算成本：{{ formatMoney(selectedAiLog.estimatedCost, selectedAiLog.currency || 'CNY') }} + 问题类型：{{ selectedAiLog.questionType || '-' }} + 知识命中：{{ selectedAiLog.knowledgeHit ? '是' : '否' }} + 路由原因：{{ selectedAiLog.routeReason || '-' }} 耗时：{{ selectedAiLog.costMs || '-' }}ms 时间：{{ selectedAiLog.createdAt }} diff --git a/ai_knowledge_base_v2/apps/admin-web/src/types/api.ts b/ai_knowledge_base_v2/apps/admin-web/src/types/api.ts index 7d4a83e..86e1da2 100644 --- a/ai_knowledge_base_v2/apps/admin-web/src/types/api.ts +++ b/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; diff --git a/ai_knowledge_base_v2/apps/backend/alembic/versions/0018_ai_cost_tracking.py b/ai_knowledge_base_v2/apps/backend/alembic/versions/0018_ai_cost_tracking.py new file mode 100644 index 0000000..4874f8f --- /dev/null +++ b/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) diff --git a/ai_knowledge_base_v2/apps/backend/app/api/admin_records.py b/ai_knowledge_base_v2/apps/backend/app/api/admin_records.py index fdae8f0..fe2605d 100644 --- a/ai_knowledge_base_v2/apps/backend/app/api/admin_records.py +++ b/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, diff --git a/ai_knowledge_base_v2/apps/backend/app/api/admin_settings.py b/ai_knowledge_base_v2/apps/backend/app/api/admin_settings.py index 5c05ba8..a84c62f 100644 --- a/ai_knowledge_base_v2/apps/backend/app/api/admin_settings.py +++ b/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, } diff --git a/ai_knowledge_base_v2/apps/backend/app/models/ai_config.py b/ai_knowledge_base_v2/apps/backend/app/models/ai_config.py index ae1e5e3..95ab416 100644 --- a/ai_knowledge_base_v2/apps/backend/app/models/ai_config.py +++ b/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): diff --git a/ai_knowledge_base_v2/apps/backend/app/models/logs.py b/ai_knowledge_base_v2/apps/backend/app/models/logs.py index d2b401f..7932c5a 100644 --- a/ai_knowledge_base_v2/apps/backend/app/models/logs.py +++ b/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) diff --git a/ai_knowledge_base_v2/apps/backend/app/schemas/admin.py b/ai_knowledge_base_v2/apps/backend/app/schemas/admin.py index 3dc2ce6..dca5ce8 100644 --- a/ai_knowledge_base_v2/apps/backend/app/schemas/admin.py +++ b/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): diff --git a/ai_knowledge_base_v2/apps/backend/app/services/admin_service.py b/ai_knowledge_base_v2/apps/backend/app/services/admin_service.py index 94d46ba..4c1e667 100644 --- a/ai_knowledge_base_v2/apps/backend/app/services/admin_service.py +++ b/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, } diff --git a/ai_knowledge_base_v2/apps/backend/app/services/ai_request_log_service.py b/ai_knowledge_base_v2/apps/backend/app/services/ai_request_log_service.py index fd70f80..8d0731f 100644 --- a/ai_knowledge_base_v2/apps/backend/app/services/ai_request_log_service.py +++ b/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" diff --git a/ai_knowledge_base_v2/apps/backend/app/services/chat_service.py b/ai_knowledge_base_v2/apps/backend/app/services/chat_service.py index 7a320ba..b244eae 100644 --- a/ai_knowledge_base_v2/apps/backend/app/services/chat_service.py +++ b/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 diff --git a/ai_knowledge_base_v2/apps/backend/app/services/chat_stream_service.py b/ai_knowledge_base_v2/apps/backend/app/services/chat_stream_service.py index c72eb3a..48cb167 100644 --- a/ai_knowledge_base_v2/apps/backend/app/services/chat_stream_service.py +++ b/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) diff --git a/ai_knowledge_base_v2/apps/backend/tests/test_ai_cost_tracking.py b/ai_knowledge_base_v2/apps/backend/tests/test_ai_cost_tracking.py new file mode 100644 index 0000000..00dd9ae --- /dev/null +++ b/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 "") + diff --git a/ai_knowledge_base_v2/docs/qianwen_product_todo.md b/ai_knowledge_base_v2/docs/qianwen_product_todo.md index 47ec0fe..56762e7 100644 --- a/ai_knowledge_base_v2/docs/qianwen_product_todo.md +++ b/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”