Files
shaguabijia-app-server/tests/test_llm_cost.py
T
guke 5c6840dd71 feat(compare): 比价记录 LLM token 成本落库与展示(按当时价冻结) (#133)
- comparison_record 加 llm_cost_yuan(元/float)+ llm_price_snapshot(JSON)两列
- _backfill_llm_calls 回填时按 app_config 当时单价逐模型算成本、冻结成本+快照到记录
- app_config 新增 llm_token_price 配置(per_model + default 兜底,运营在系统配置页可改)
- services/llm_cost.py:compute_llm_cost 纯函数(按 model 分桶、error/无 usage 跳过、
  脏价格当 unpriced 不抛异常以免连累 token 回填)+ get_llm_prices reader
- admin schema 暴露成本:列表项带 llm_cost_yuan,详情另带价格快照
- tests/test_llm_cost.py(10 测试);scripts/seed_mock_llm_cost.py(mock seeder)

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

---------

Co-authored-by: guke <guke@autohome.com.cn>
Reviewed-on: #133
2026-07-13 17:46:11 +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
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(compare_record, "fetch_llm_calls", lambda trace_id: sample)
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