# 成本归因封装：每次LLM调用时附加业务标签
async def tracked_llm_call(messages, feature: str, user_id: str, user_tier: str = "free"):
    response = await async_client.chat.completions.create(
        model="deepseek-chat",
        max_tokens=500,
        messages=messages,
    )
    # 记录到成本数据库，附带归因标签
    cost_tracker.record(
        feature=feature,          # "rag_search" / "content_gen" / "chat_support"
        user_id=user_id,
        user_tier=user_tier,      # "free" / "pro" / "enterprise"
        input_tokens=response.usage.prompt_tokens,
        output_tokens=response.usage.completion_tokens,
        model=response.model,
        timestamp=time.time(),
    )
    return response

# cost_tracker.py — 成本追踪模块
import sqlite3
from datetime import datetime
from contextlib import contextmanager

DB_PATH = "costs.db"

def init_db():
    """初始化成本追踪数据库"""
    with sqlite3.connect(DB_PATH) as conn:
        conn.execute("""
            CREATE TABLE IF NOT EXISTS llm_costs (
                id INTEGER PRIMARY KEY AUTOINCREMENT,
                timestamp TEXT NOT NULL,
                feature TEXT NOT NULL,
                user_id TEXT,
                model TEXT NOT NULL,
                input_tokens INTEGER NOT NULL,
                output_tokens INTEGER NOT NULL,
                cost_usd REAL NOT NULL
            )
        """)

# ⚠️ 注意：以下价格为写作时的参考值，实际价格以官方文档为准
# 生产环境建议从配置文件或环境变量读取，避免价格变动时需要改代码
# 参考：https://api-docs.deepseek.com/quick_start/pricing  https://openai.com/pricing
MODEL_PRICES = {
    "deepseek-chat": {"input": 0.00027, "output": 0.0011},
    "deepseek-reasoner": {"input": 0.00055, "output": 0.00219},
    "gpt-4o": {"input": 0.0025, "output": 0.01},
    "gpt-4o-mini": {"input": 0.00015, "output": 0.0006},
}

# 生产环境推荐：从配置文件读取价格，方便更新
# 例如在 .env 文件中设置：
# DEEPSEEK_CHAT_INPUT_PRICE=0.00027
# DEEPSEEK_CHAT_OUTPUT_PRICE=0.0011
# 然后用 os.getenv("DEEPSEEK_CHAT_INPUT_PRICE", "0.00027") 读取

def record_cost(feature: str, user_id: str, model: str,
                input_tokens: int, output_tokens: int):
    """记录一次LLM调用的成本"""
    price = MODEL_PRICES.get(model, {"input": 0.01, "output": 0.03})
    cost = (input_tokens * price["input"] + output_tokens * price["output"]) / 1000

    with sqlite3.connect(DB_PATH) as conn:
        conn.execute(
            "INSERT INTO llm_costs VALUES (NULL,?,?,?,?,?,?,?)",
            (datetime.now().isoformat(), feature, user_id,
             model, input_tokens, output_tokens, cost)
        )
    return cost

def get_daily_cost_by_feature(date: str = None) -> dict:
    """按功能统计当日成本，用于仪表盘"""
    if date is None:
        date = datetime.now().strftime("%Y-%m-%d")
    with sqlite3.connect(DB_PATH) as conn:
        rows = conn.execute("""
            SELECT feature, SUM(cost_usd) as total, COUNT(*) as calls
            FROM llm_costs
            WHERE timestamp LIKE ?
            GROUP BY feature
            ORDER BY total DESC
        """, (f"{date}%",)).fetchall()
    return {row[0]: {"cost_usd": round(row[1], 4), "calls": row[2]} for row in rows}

# main.py — FastAPI 应用集成示例
import os
from fastapi import FastAPI, Depends
from pydantic import BaseModel
from openai import OpenAI
from cost_tracker import init_db, record_cost, get_daily_cost_by_feature

app = FastAPI()
client = OpenAI(
    api_key=os.getenv("DEEPSEEK_API_KEY"),
    base_url="https://api.deepseek.com",
)

@app.on_event("startup")
async def startup():
    init_db()  # 应用启动时初始化数据库

class ChatRequest(BaseModel):
    message: str
    user_id: str = "anonymous"

@app.post("/chat")
async def chat(req: ChatRequest):
    """带成本追踪的聊天接口"""
    response = client.chat.completions.create(
        model="deepseek-chat",  # 聊天用便宜模型
        max_tokens=1024,
        messages=[{"role": "user", "content": req.message}]
    )

    # 记录成本（异步不阻塞响应）
    record_cost(
        feature="chat",
        user_id=req.user_id,
        model=response.model,
        input_tokens=response.usage.prompt_tokens,
        output_tokens=response.usage.completion_tokens,
    )

    return {"reply": response.choices[0].message.content}

@app.get("/admin/costs/today")
async def today_costs():
    """查看今日各功能成本分布（管理员接口）"""
    return get_daily_cost_by_feature()

{
  "chat": {"cost_usd": 0.0234, "calls": 156},
  "rag_search": {"cost_usd": 0.1823, "calls": 89},
  "report_gen": {"cost_usd": 0.9156, "calls": 12}
}