Optimize tablet load: defer health check, lighten service worker, drop Google Fonts.

Co-authored-by: Cursor <cursoragent@cursor.com>
This commit is contained in:
dekun
2026-06-12 14:49:58 +08:00
parent f0bb40c605
commit 7e65349878
4 changed files with 338 additions and 285 deletions
+90 -85
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@@ -1,85 +1,90 @@
"""
Trading Studio 全局配置模块
统一存放局域网节点、模型名称、固定 Prompt 及本地路径。
"""
from pathlib import Path
# ---------------------------------------------------------------------------
# 网络与服务
# ---------------------------------------------------------------------------
# 远程 Ollama 节点(局域网大模型审查润色)
OLLAMA_HOST = "192.168.8.64"
OLLAMA_PORT = 11434
OLLAMA_URL = f"http://{OLLAMA_HOST}:{OLLAMA_PORT}/api/chat"
# 指定无限制版 Gemma4 模型
MODEL_NAME = "huihui_ai/gemma-4-abliterated:e4b"
# Gradio 中控固定端口(硬性死规则)
HOST = "0.0.0.0"
PORT = 5683
# HTTP 请求超时(秒)
OLLAMA_TIMEOUT = 60
# ---------------------------------------------------------------------------
# LLM 系统 Prompt
# ---------------------------------------------------------------------------
SYSTEM_PROMPT = (
"你是一个冷静、极其严格的数字资产量化交易员。"
"请把下面这段口语化、包含结巴和逻辑混乱的交易复盘录音转写,"
"润色成一段逻辑清晰、行文通顺的 B 站长视频反思配音稿。"
"语气要内向、克制、严谨。"
"如果原视频中有由于心态不好、违背交易纪律(如手贱乱开仓、提前平仓)"
"导致少赚或亏损的部分,请用冷酷、严厉的语气狠狠地自我吐槽、反思该点"
"去掉所有无意义的口头禅,字数不做删减。"
)
# ---------------------------------------------------------------------------
# Faster-Whisper 配置
# ---------------------------------------------------------------------------
WHISPER_MODEL_SIZE = "small"
WHISPER_DEVICE = "cuda"
WHISPER_COMPUTE_TYPE = "float16"
WHISPER_LANGUAGE = "zh"
# ---------------------------------------------------------------------------
# ChatTTS 配置
# ---------------------------------------------------------------------------
# 标准生产安装路径(/opt,root 部署)
INSTALL_DIR = Path("/opt/Trading_Studio")
# 项目根目录(开发/生产均自适应,以实际 app.py 所在目录为准)
BASE_DIR = Path(__file__).resolve().parent
# 固定音色 Embedding 存储路径
SPEAKER_EMB_PATH = BASE_DIR / "speaker_emb.pt"
# 合成音频输出目录
OUTPUT_DIR = BASE_DIR / "outputs"
OUTPUT_DIR.mkdir(parents=True, exist_ok=True)
# ChatTTS 采样率(Hz
TTS_SAMPLE_RATE = 24000
# 音色样本时长建议(秒)
SPEAKER_SAMPLE_MIN_SEC = 10
SPEAKER_SAMPLE_MAX_SEC = 30
# TTS 推理默认参数(低 temperature 有助于音色稳定)
TTS_TEMPERATURE = 0.3
TTS_TOP_P = 0.7
TTS_TOP_K = 20
TTS_SPEED_PROMPT = "[speed_5]"
# ---------------------------------------------------------------------------
# 上传临时文件目录
# ---------------------------------------------------------------------------
UPLOAD_DIR = BASE_DIR / "uploads"
UPLOAD_DIR.mkdir(parents=True, exist_ok=True)
# ---------------------------------------------------------------------------
# Git 仓库(文档引用)
# ---------------------------------------------------------------------------
GIT_REPO_URL = "https://git.bz121.com/dekun/Trading_Studio.git"
"""
Trading Studio 全局配置模块
统一存放局域网节点、模型名称、固定 Prompt 及本地路径。
"""
from pathlib import Path
# ---------------------------------------------------------------------------
# 网络与服务
# ---------------------------------------------------------------------------
# 远程 Ollama 节点(局域网大模型审查润色)
OLLAMA_HOST = "192.168.8.64"
OLLAMA_PORT = 11434
OLLAMA_URL = f"http://{OLLAMA_HOST}:{OLLAMA_PORT}/api/chat"
# 指定无限制版 Gemma4 模型
MODEL_NAME = "huihui_ai/gemma-4-abliterated:e4b"
# Gradio 中控固定端口(硬性死规则)
HOST = "0.0.0.0"
PORT = 5683
# HTTP 请求超时(秒)
OLLAMA_TIMEOUT = 60
# 健康检查快速超时(秒)— 避免平板首屏被长时间阻塞
HEALTH_CHECK_CONNECT_TIMEOUT = 2
HEALTH_CHECK_READ_TIMEOUT = 3
HEALTH_CHECK_CACHE_SECONDS = 30
# ---------------------------------------------------------------------------
# LLM 系统 Prompt
# ---------------------------------------------------------------------------
SYSTEM_PROMPT = (
"你是一个冷静、极其严格的数字资产量化交易员"
"请把下面这段口语化、包含结巴和逻辑混乱的交易复盘录音转写,"
"润色成一段逻辑清晰、行文通顺的 B 站长视频反思配音稿。"
"语气要内向、克制、严谨。"
"如果原视频中有由于心态不好、违背交易纪律(如手贱乱开仓、提前平仓)"
"导致少赚或亏损的部分,请用冷酷、严厉的语气狠狠地自我吐槽、反思该点。"
"去掉所有无意义的口头禅,字数不做删减。"
)
# ---------------------------------------------------------------------------
# Faster-Whisper 配置
# ---------------------------------------------------------------------------
WHISPER_MODEL_SIZE = "small"
WHISPER_DEVICE = "cuda"
WHISPER_COMPUTE_TYPE = "float16"
WHISPER_LANGUAGE = "zh"
# ---------------------------------------------------------------------------
# ChatTTS 配置
# ---------------------------------------------------------------------------
# 标准生产安装路径(/opt,root 部署)
INSTALL_DIR = Path("/opt/Trading_Studio")
# 项目根目录(开发/生产均自适应,以实际 app.py 所在目录为准)
BASE_DIR = Path(__file__).resolve().parent
# 固定音色 Embedding 存储路径
SPEAKER_EMB_PATH = BASE_DIR / "speaker_emb.pt"
# 合成音频输出目录
OUTPUT_DIR = BASE_DIR / "outputs"
OUTPUT_DIR.mkdir(parents=True, exist_ok=True)
# ChatTTS 采样率(Hz
TTS_SAMPLE_RATE = 24000
# 音色样本时长建议(秒)
SPEAKER_SAMPLE_MIN_SEC = 10
SPEAKER_SAMPLE_MAX_SEC = 30
# TTS 推理默认参数(低 temperature 有助于音色稳定)
TTS_TEMPERATURE = 0.3
TTS_TOP_P = 0.7
TTS_TOP_K = 20
TTS_SPEED_PROMPT = "[speed_5]"
# ---------------------------------------------------------------------------
# 上传临时文件目录
# ---------------------------------------------------------------------------
UPLOAD_DIR = BASE_DIR / "uploads"
UPLOAD_DIR.mkdir(parents=True, exist_ok=True)
# ---------------------------------------------------------------------------
# Git 仓库(文档引用)
# ---------------------------------------------------------------------------
GIT_REPO_URL = "https://git.bz121.com/dekun/Trading_Studio.git"