Files
shaguabijia-app-server/tests/test_llm_cost.py
T
linkeyu 1226bc8365 修复比价记录平均 TOKEN 成本采集与回填 (#182)
## 问题原因

- 新版客户端通过服务端 harvest 落库,但完成路径没有触发 LLM 调用明细与 TOKEN 成本回填。
- 内部共享密钥不一致或 PriceBot 实例切换后,拉取失败只留下空值,后续没有自动补偿。

## 本次改动

- harvest 完成后立即异步回填 LLM 调用、TOKEN 数及成本快照。
- 抽取统一、幂等的成本回填服务,并增加定时补偿 worker。
- 增加 PriceBot 内部鉴权预检、错误日志和多实例查找兜底。
- 仅回填当前价格配置生效后的终态记录,避免用现价误算更早历史数据。
- 补充环境配置、部署说明和单元测试。

## 验证

- 相关测试:36 passed。
- 静态检查通过,diff check 通过。
- 本地页面显示 ¥0.0139,与数据库精确均值 0.013916 的四舍五入结果一致。

## 上线注意

部署时需确保 app-server 与 PriceBot 的 INTERNAL_API_SECRET 完全一致并重启两个服务;worker 启动后会自动补齐符合条件的历史空值。

---------

Co-authored-by: guke <guke@wonderable.ai>
Co-authored-by: unknown <798648091@qq.com>
Reviewed-on: #182
Co-authored-by: linkeyu <linkeyu@wonderable.ai>
Co-committed-by: linkeyu <linkeyu@wonderable.ai>
2026-07-27 15:51:19 +08:00

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"""LLM 调用成本计算 compute_llm_cost:按模型分桶累加 token × 单价;error/无 usage 跳过。"""
from __future__ import annotations
from app.services.llm_cost import compute_llm_cost
_PRICE = {
"per_model": {"qwen3.5-flash": {"input_per_1m": 0.8, "output_per_1m": 2.0}},
"default": {"input_per_1m": 3.0, "output_per_1m": 15.0},
}
def test_sums_per_model_single_model():
# 真实样本:4 次 qwen3.5-flash;Σprompt=6888、Σcompletion=337
calls = [
{"model": "qwen3.5-flash", "error": None, "usage": {"prompt_tokens": 1512, "completion_tokens": 22}},
{"model": "qwen3.5-flash", "error": None, "usage": {"prompt_tokens": 2111, "completion_tokens": 160}},
{"model": "qwen3.5-flash", "error": None, "usage": {"prompt_tokens": 1940, "completion_tokens": 142}},
{"model": "qwen3.5-flash", "error": None, "usage": {"prompt_tokens": 1325, "completion_tokens": 13}},
]
cost, snapshot = compute_llm_cost(calls, _PRICE)
# 6888/1e6*0.8 + 337/1e6*2.0 = 0.0055104 + 0.000674 = 0.0061844 → round(6)
assert cost == 0.006184
assert snapshot == {
"mode": "per_model",
"prices": {
"qwen3.5-flash": {"input_per_1m": 0.8, "output_per_1m": 2.0, "_source": "per_model"},
},
}
def test_multi_model_prices_each_bucket_separately():
calls = [
{"model": "qwen3.5-flash", "error": None, "usage": {"prompt_tokens": 1_000_000, "completion_tokens": 0}},
{"model": "gpt-x", "error": None, "usage": {"prompt_tokens": 0, "completion_tokens": 1_000_000}},
]
price = {
"per_model": {
"qwen3.5-flash": {"input_per_1m": 0.8, "output_per_1m": 2.0},
"gpt-x": {"input_per_1m": 10.0, "output_per_1m": 30.0},
},
"default": {"input_per_1m": 3.0, "output_per_1m": 15.0},
}
cost, snap = compute_llm_cost(calls, price)
assert cost == 30.8 # qwen 1M入×0.8=0.8 + gpt-x 1M出×30=30.0
assert set(snap["prices"]) == {"qwen3.5-flash", "gpt-x"}
def test_unknown_model_falls_back_to_default():
calls = [{"model": "mystery", "error": None, "usage": {"prompt_tokens": 1_000_000, "completion_tokens": 0}}]
price = {"per_model": {}, "default": {"input_per_1m": 3.0, "output_per_1m": 15.0}}
cost, snap = compute_llm_cost(calls, price)
assert cost == 3.0
assert snap["prices"]["mystery"]["_source"] == "default"
def test_unpriced_model_marked_and_zero_cost():
calls = [{"model": "mystery", "error": None, "usage": {"prompt_tokens": 1_000_000, "completion_tokens": 999}}]
cost, snap = compute_llm_cost(calls, {"per_model": {}}) # 无 default
assert cost == 0.0
assert snap["prices"]["mystery"]["unpriced"] is True
def test_error_and_missing_usage_calls_skipped():
calls = [
{"model": "qwen3.5-flash", "error": "boom", "usage": {"prompt_tokens": 9_999_999, "completion_tokens": 9_999_999}},
{"model": "qwen3.5-flash", "error": None, "usage": None}, # 无 usage
{"model": "qwen3.5-flash", "error": None, "usage": {"prompt_tokens": 1_000_000, "completion_tokens": 0}},
]
cost, _ = compute_llm_cost(calls, _PRICE)
assert cost == 0.8 # 只有第 3 条计入
def test_empty_or_all_error_returns_none():
assert compute_llm_cost([], _PRICE) == (None, None)
assert compute_llm_cost(None, _PRICE) == (None, None)
all_error = [{"model": "x", "error": "boom", "usage": {"prompt_tokens": 100, "completion_tokens": 100}}]
assert compute_llm_cost(all_error, _PRICE) == (None, None)
def test_malformed_price_entry_is_treated_as_unpriced_not_raised():
# 手改配置页可能存出残缺/非法单价(缺 output_per_1m、非 dict);不能抛异常连累 token 回填。
calls = [
{"model": "bad-a", "error": None, "usage": {"prompt_tokens": 1_000_000, "completion_tokens": 5}},
{"model": "bad-b", "error": None, "usage": {"prompt_tokens": 1_000_000, "completion_tokens": 5}},
{"model": "ok", "error": None, "usage": {"prompt_tokens": 1_000_000, "completion_tokens": 0}},
]
price = {
"per_model": {
"bad-a": {"input_per_1m": 0.8}, # 缺 output_per_1m
"bad-b": 5, # 非 dict
"ok": {"input_per_1m": 3.0, "output_per_1m": 15.0},
},
}
cost, snap = compute_llm_cost(calls, price) # 不得抛异常
assert cost == 3.0 # 只有 ok(1M 入 × 3.0)计入;两个残缺项按 unpriced
assert snap["prices"]["bad-a"].get("unpriced") is True
assert snap["prices"]["bad-b"].get("unpriced") is True
def test_get_llm_prices_falls_back_to_default_then_uses_override():
from app.db.session import SessionLocal
from app.models.app_config import AppConfig
from app.repositories import app_config
from app.services.llm_cost import get_llm_prices
db = SessionLocal()
try:
# 无 override → CONFIG_DEFS 默认(含 per_model / default)
prices = get_llm_prices(db)
assert "per_model" in prices and "default" in prices
# 有 override → 用 DB 值
app_config.set_value(
db, "llm_token_price",
{"per_model": {"m": {"input_per_1m": 1.0, "output_per_1m": 2.0}},
"default": {"input_per_1m": 0.0, "output_per_1m": 0.0}},
admin_id=1,
)
assert get_llm_prices(db)["per_model"]["m"]["input_per_1m"] == 1.0
finally:
row = db.get(AppConfig, "llm_token_price")
if row is not None:
db.delete(row)
db.commit()
db.close()
def test_backfill_llm_calls_stores_cost_and_snapshot(monkeypatch):
from datetime import UTC, datetime
from app.api.v1 import compare_record
from app.db.session import SessionLocal
from app.models.app_config import AppConfig
from app.models.comparison import ComparisonRecord
from app.repositories import app_config
from app.services import comparison_llm_backfill
sample = [
{"model": "qwen3.5-flash", "error": None, "usage": {"prompt_tokens": 1512, "completion_tokens": 22}},
{"model": "qwen3.5-flash", "error": None, "usage": {"prompt_tokens": 2111, "completion_tokens": 160}},
{"model": "qwen3.5-flash", "error": None, "usage": {"prompt_tokens": 1940, "completion_tokens": 142}},
{"model": "qwen3.5-flash", "error": None, "usage": {"prompt_tokens": 1325, "completion_tokens": 13}},
]
monkeypatch.setattr(
comparison_llm_backfill, "fetch_llm_calls", lambda trace_id: sample
)
monkeypatch.setattr(
comparison_llm_backfill.settings, "INTERNAL_API_SECRET", "test-secret"
)
db = SessionLocal()
try:
app_config.set_value(
db, "llm_token_price",
{"per_model": {"qwen3.5-flash": {"input_per_1m": 0.8, "output_per_1m": 2.0}},
"default": {"input_per_1m": 3.0, "output_per_1m": 15.0}},
admin_id=1,
)
rec = ComparisonRecord(
trace_id="llmcost-bf-1", status="success",
created_at=datetime.now(UTC).replace(tzinfo=None),
)
db.add(rec)
db.commit()
rid = rec.id
finally:
db.close()
compare_record._backfill_llm_calls(rid, "llmcost-bf-1") # 独立 session 内回填
db = SessionLocal()
try:
rec = db.get(ComparisonRecord, rid)
assert rec.llm_cost_yuan == 0.006184
assert rec.llm_price_snapshot["prices"]["qwen3.5-flash"]["input_per_1m"] == 0.8
assert rec.input_tokens == 6888 # 现有 token 派生仍在
finally:
db.delete(db.get(ComparisonRecord, rid))
row = db.get(AppConfig, "llm_token_price")
if row is not None:
db.delete(row)
db.commit()
db.close()
def test_admin_detail_schema_exposes_llm_cost_fields():
from app.admin.schemas.comparison import AdminComparisonDetail
fields = AdminComparisonDetail.model_fields
assert "llm_cost_yuan" in fields
assert "llm_price_snapshot" in fields