xsl
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.
99 lines
2.2 KiB
Python
Executable File
99 lines
2.2 KiB
Python
Executable File
"""Request/response schemas.
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NFR-MAINT-01 契约先行: schema 先定义，客户端类型由 OpenAPI 生成。
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Wire responses are wrapped by the unified envelope (架构文档 §9.2); these models
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describe the ``data`` payload only.
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"""
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from __future__ import annotations
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from datetime import datetime
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from pydantic import BaseModel, Field
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class DevTokenRequest(BaseModel):
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device_key: str = Field(
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default="local-dev",
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min_length=1,
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max_length=64,
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description="任意稳定字符串；同一 device_key 复用同一测试用户",
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)
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class DevTokenResponse(BaseModel):
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access_token: str
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token_type: str = "Bearer"
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expires_in: int
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user_id: str = Field(description="雪花 ID 以字符串返回，避免 JS 精度丢失")
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class ChatRequest(BaseModel):
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message: str = Field(min_length=1, max_length=2000)
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request_key: str | None = Field(
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default=None,
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max_length=128,
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description="幂等键；相同键不会重复扣配额 (架构文档 §9.1)",
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)
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class ChatUsage(BaseModel):
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tokens_in: int
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tokens_out: int
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tokens_cached: int
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latency_ms: int
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cost_cents: str
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class ChatResponse(BaseModel):
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reply: str
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provider: str
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model: str
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prompt_id: str | None
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prompt_version: str | None
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call_id: str
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usage: ChatUsage
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quota_remaining: int
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class QuotaResponse(BaseModel):
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quota_key: str
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period_key: str
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used: int
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limit_value: int
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bonus_value: int
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remaining: int
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reset_at: datetime | None
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class LedgerEntry(BaseModel):
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tx_id: str
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delta: int
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tx_type: str
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status: str
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reason: str | None
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quota_key: str | None
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period_key: str | None
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balance_after: int
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created_at: datetime
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class TaskSubmitRequest(BaseModel):
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echo: str = Field(default="ping", max_length=200)
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idempotency_key: str | None = Field(default=None, max_length=128)
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class TaskResponse(BaseModel):
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task_id: str
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task_type: str
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status: str
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progress: int
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stage_text: str | None
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result: dict[str, object] | None
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error_code: int | None
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error_message: str | None
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retry_count: int
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submitted_at: datetime
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started_at: datetime | None
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finished_at: datetime | None
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