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f46ecc5eb0
Two defects that only surface against the real DeepSeek API, both of which break the cost model rather than the code: deepseek-v4-flash enables thinking mode by default. The same single-turn question took 13.5s with it on and 1.8s with it off, and the thinking tokens are billed at the output rate. That misses NFR-PERF-02b (15s per turn) and inflates every conversational call. SceneConfig now carries an explicit `thinking` flag, all four V1 scenes set it to false, and the provider always sends the parameter rather than relying on the upstream default. Reasoning tokens are recorded separately in Usage.tokens_reasoning so the cost of ever turning it back on is visible. DeepSeek moves to peak/off-peak pricing on 2026-08-17, with peak (Beijing 09:00-12:00 and 14:00-18:00) at twice the off-peak rate. Reports are generated mostly during peak hours, so a single blended rate would leave ob_ai_call -- the only input to V2 pricing -- off by nearly a factor of two. PeakAwareRateTable resolves the rate at call time; cost is computed and stored then, never recomputed later at whatever the current rate happens to be. Also here: - Replace the live API key in the redaction test with a synthetic one. The test that proves we redact secrets was itself a secret leak waiting for its first commit. - Correct LLM_COST_RATES_JSON, which held placeholder rates. - Make ids.SnowflakeGenerator take an injectable clock so rollover and clock-rollback are testable without patching a slots class. - Rename exceptions to the -Error suffix (N818) and clear the remaining ruff, mypy and import-linter findings, including two dead lines: a duplicate pytestmark assignment and a no-op assert on a None return. Gates: ruff, mypy (96 files incl. tests), 4/4 import contracts, detect-secrets, 166 unit + 3 integration tests, migration up/down round-trip.
80 lines
3.1 KiB
Makefile
Executable File
80 lines
3.1 KiB
Makefile
Executable File
.PHONY: help install up down logs migrate downgrade revision run worker \
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test test-unit test-integration lint fmt typecheck imports secrets check smoke psql redis-cli
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COMPOSE := docker compose -f deploy/docker-compose.dev.yml
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help: ## 列出所有目标
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@grep -hE '^[a-zA-Z_-]+:.*?## .*$$' $(MAKEFILE_LIST) \
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| awk 'BEGIN {FS = ":.*?## "}; {printf " \033[36m%-18s\033[0m %s\n", $$1, $$2}'
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# ── 环境 ────────────────────────────────────────────────────────────────────
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install: ## 安装依赖（uv 管理，含开发依赖）
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uv sync --extra dev
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uv run pre-commit install
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up: ## 起 PostgreSQL(pgvector) + Redis
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$(COMPOSE) up -d postgres redis
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down: ## 停容器（保留数据卷）
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$(COMPOSE) down
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logs: ## 跟踪容器日志
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$(COMPOSE) logs -f --tail=100
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psql: ## 连进数据库
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$(COMPOSE) exec postgres psql -U meida -d meida
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redis-cli: ## 连进 Redis
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$(COMPOSE) exec redis redis-cli
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# ── 数据库 ──────────────────────────────────────────────────────────────────
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migrate: ## 迁移到最新版本
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uv run alembic upgrade head
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downgrade: ## 回退一个版本
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uv run alembic downgrade -1
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revision: ## 生成迁移脚本：make revision m="描述"
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uv run alembic revision --autogenerate -m "$(m)"
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# ── 运行 ────────────────────────────────────────────────────────────────────
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run: ## 本地起 API（热重载）
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uv run uvicorn apps.api.main:app --reload --host 0.0.0.0 --port 8000
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worker: ## 本地起 Celery worker
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uv run celery -A apps.worker.celery_app.celery_app worker -Q cpu,io -l INFO
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# ── 质量防线（与 CI 一致，见 .github/workflows/ci.yml）─────────────────────
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lint: ## ruff 检查 + 格式校验
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uv run ruff check .
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uv run ruff format --check .
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fmt: ## 自动修复与格式化
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uv run ruff check --fix .
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uv run ruff format .
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typecheck: ## mypy（domain 与 llm 为 strict）
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uv run mypy packages/domain packages/llm
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uv run mypy apps packages/shared packages/identity packages/billing packages/task \
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packages/agent packages/compliance
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imports: ## 分层依赖契约（架构文档 §4.2）
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uv run lint-imports
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secrets: ## 敏感信息扫描
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uv run detect-secrets scan --baseline .secrets.baseline
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test: test-unit ## 默认只跑单测（不连库、不发网络请求）
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test-unit:
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uv run pytest
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test-integration: ## 需要 make up && make migrate
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MEIDA_RUN_INTEGRATION=1 uv run pytest -m integration
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check: lint typecheck imports test secrets ## 提交前一把过
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# ── 真实链路验证（会花钱）──────────────────────────────────────────────────
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smoke: ## 真调 DeepSeek，打印 ob_ai_call 与 bl_ledger
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bash scripts/smoke.sh
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