mirror of
https://ghfast.top/https://github.com/aeroxw/tick-stock-panel.git
synced 2026-09-12 23:44:16 +08:00
wshyandshy3130
773cd2fe12
* fix(ai): 兼容 reasoning 模型 temperature 限制 + 透出上游真实错误 Kimi kimi-k2.7-code 等 reasoning 模型拒绝非约定 temperature (Moonshot 报 "only 1 is allowed for this model"), 之前无条件下发导致 400 配置失败。 - 捕获 temperature 相关 400 后自动去掉 temperature 重试一次 (非流式 + 流式), 不再依赖模型名猜测, 对任意 reasoning 模型稳健 - _format_openai_error 优先透出上游真实 detail, 仅无可读 detail 时回落到 状态码通用文案, 避免吞掉 "model not found" 等排障关键信息 - 前端 Kimi 预设 model 更正为 kimi-k2.7-code * chore(polling): 调整各档位轮询间隔范围 实时行情 (quote_service): - pro 最小间隔 2s → 3s, starter 3s → 6s (expert/free 不变) - DEFAULT_INTERVAL 10s → 6s 五档盘口 (depth_service): - expert 区间上限 300s → 120s - 默认值 20s → 10s 前端兜底默认值同步 (Data/Monitoring/DepthConfigCard): - quote interval fallback 10→6, min 5→6 - depth interval fallback 20→10, expert hi 300→120 --------- Co-authored-by: shy3130 <shy3130@users.noreply.github.com>
143 lines
5.5 KiB
Python
143 lines
5.5 KiB
Python
from __future__ import annotations
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import httpx
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import openai
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from app.services.ai_provider import (
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_format_openai_error,
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_is_temperature_rejected,
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normalize_openai_base_url,
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)
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def test_normalize_openai_base_url_adds_v1_for_root_gateway():
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assert normalize_openai_base_url("http://ai.zedbox.cn:8080") == "http://ai.zedbox.cn:8080/v1"
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def test_normalize_openai_base_url_preserves_v1_base():
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assert normalize_openai_base_url("http://ai.zedbox.cn:8080/v1") == "http://ai.zedbox.cn:8080/v1"
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def test_normalize_openai_base_url_strips_chat_completions_path():
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assert normalize_openai_base_url("http://ai.zedbox.cn:8080/v1/chat/completions") == "http://ai.zedbox.cn:8080/v1"
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def test_normalize_openai_base_url_preserves_glm_v4():
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"""智谱 GLM 用 /api/paas/v4, 不能强制补成 /v4/v1 (会 404)。"""
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assert normalize_openai_base_url("https://open.bigmodel.cn/api/paas/v4") == "https://open.bigmodel.cn/api/paas/v4"
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def test_normalize_openai_base_url_strips_chat_completions_from_glm_v4():
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"""用户填完整 /v4/chat/completions 时, 去掉后缀归一化为 /v4。"""
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assert normalize_openai_base_url("https://open.bigmodel.cn/api/paas/v4/chat/completions") == "https://open.bigmodel.cn/api/paas/v4"
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def test_normalize_openai_base_url_preserves_other_version_segments():
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"""其它非 v1 版本号 (/v2 等) 也应保持原样。"""
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assert normalize_openai_base_url("https://example.com/api/v2") == "https://example.com/api/v2"
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def test_normalize_openai_base_url_strips_trailing_slash():
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assert normalize_openai_base_url("https://open.bigmodel.cn/api/paas/v4/") == "https://open.bigmodel.cn/api/paas/v4"
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def test_format_openai_error_hides_html_gateway_body():
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response = httpx.Response(
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504,
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headers={"content-type": "text/html; charset=utf-8"},
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text="<!DOCTYPE html><html><body><h1>Gateway Timeout</h1></body></html>",
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request=httpx.Request("POST", "https://example.com/v1/chat/completions"),
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)
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exc = openai.InternalServerError("gateway timeout", response=response, body=response.text)
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message = _format_openai_error(exc)
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assert message == "AI 服务请求失败(504): AI 上游服务超时, 请稍后重试或检查 AI Base URL / 网络"
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assert "html" not in message.lower()
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assert "Gateway Timeout" not in message
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def test_format_openai_error_prefers_upstream_detail_when_available():
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"""有可读的上游 detail 时优先透出, 而不是用 400 通用文案吞掉。"""
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response = httpx.Response(
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400,
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json={"error": {"message": "model context length exceeded"}},
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request=httpx.Request("POST", "https://example.com/v1/chat/completions"),
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)
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exc = openai.BadRequestError(
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"bad request",
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response=response,
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body={"error": {"message": "model context length exceeded"}},
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)
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message = _format_openai_error(exc)
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assert message == "AI 服务请求失败(400): model context length exceeded"
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def test_format_openai_error_falls_back_to_status_message_without_detail():
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"""上游无可读 detail (如 HTML 网关页) 时, 才回落到 400 通用文案。"""
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response = httpx.Response(
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400,
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headers={"content-type": "text/html; charset=utf-8"},
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text="<!DOCTYPE html><html></html>",
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request=httpx.Request("POST", "https://example.com/v1/chat/completions"),
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)
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exc = openai.BadRequestError("bad request", response=response, body=None)
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message = _format_openai_error(exc)
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assert message == "AI 服务请求失败(400): 请求参数无效, 请检查模型名称和上下文长度"
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def test_is_temperature_rejected_matches_moonshot_message():
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"""Moonshot 对 reasoning 模型报 'only 1 is allowed for this model'。"""
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response = httpx.Response(
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400,
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json={"error": {"message": "invalid temperature: only 1 is allowed for this model"}},
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request=httpx.Request("POST", "https://api.moonshot.cn/v1/chat/completions"),
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)
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exc = openai.BadRequestError(
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"bad request",
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response=response,
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body={"error": {"message": "invalid temperature: only 1 is allowed for this model"}},
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)
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assert _is_temperature_rejected(exc) is True
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def test_is_temperature_rejected_matches_generic_temperature_hint():
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response = httpx.Response(
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400,
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json={"error": {"message": "unsupported parameter: temperature"}},
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request=httpx.Request("POST", "https://example.com/v1/chat/completions"),
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)
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exc = openai.BadRequestError(
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"bad request", response=response,
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body={"error": {"message": "unsupported parameter: temperature"}},
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)
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assert _is_temperature_rejected(exc) is True
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def test_is_temperature_rejected_false_for_other_400():
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"""非 temperature 相关的 400 (如 model not found) 不应触发去 temperature 重试。"""
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response = httpx.Response(
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400,
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json={"error": {"message": "model not found"}},
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request=httpx.Request("POST", "https://example.com/v1/chat/completions"),
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)
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exc = openai.BadRequestError(
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"bad request", response=response,
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body={"error": {"message": "model not found"}},
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)
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assert _is_temperature_rejected(exc) is False
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def test_is_temperature_rejected_false_for_non_400():
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response = httpx.Response(
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401,
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json={"error": {"message": "invalid api key"}},
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request=httpx.Request("POST", "https://example.com/v1/chat/completions"),
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)
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exc = openai.AuthenticationError("unauthorized", response=response, body=None)
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assert _is_temperature_rejected(exc) is False
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