初始化提交

docs/GPU_DOCKER_DEPLOYMENT.md

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+# GPU Docker Deployment Guide
+
+本文档介绍如何使用 GPU 加速 `faster-whisper` 字幕生成，大幅提升处理速度。
+
+## 为什么要 GPU 加速
+
+MoneyPrinterTurbo 中唯一的深度学习环节是 **faster-whisper 语音识别**（将音频转为带时间戳的字幕）。
+
+- **CPU 模式**（默认）：`large-v3` 模型生成字幕较慢
+- **GPU 模式**：利用 NVIDIA GPU + CUDA 加速，速度提升 **5-10 倍**
+
+> 注意：项目的其他环节（脚本生成、音频合成、视频剪辑）不涉及深度学习，GPU 只加速字幕生成。
+
+## 部署方式
+
+本项目提供两种 Docker 部署方式，**默认 CPU 部署不受任何影响**：
+
+### CPU 部署（默认，零变化）
+
+```bash
+docker compose up -d
+```
+
+使用原有的 `Dockerfile`（`python:3.11-slim-bullseye`），无需 GPU。
+
+### GPU 部署（有 NVIDIA GPU 的用户）
+
+```bash
+docker compose -f docker-compose.yml -f docker-compose.gpu.yml up -d
+```
+
+使用 `Dockerfile.gpu`（`nvidia/cuda:12.1.1-cudnn8-runtime-ubuntu22.04`）并为 api 服务挂载 GPU。
+
+## GPU 部署前提条件
+
+### 1. 硬件要求
+
+- NVIDIA GPU（建议 6GB 以上显存）
+- `large-v3` 模型在 GPU 上 `float16` 精度约占用 1.5GB 显存
+
+### 2. 软件要求
+
+- **NVIDIA 驱动**：最新版即可，运行 `nvidia-smi` 确认
+- **Docker Desktop**
+- **NVIDIA Container Toolkit**：运行 `docker info` 查看 Runtimes 列表中是否有 `nvidia`
+
+### 3. 环境验证
+
+```bash
+# 确认 NVIDIA 驱动正常
+nvidia-smi
+
+# 确认 Docker 支持 GPU（Runtimes 中应包含 nvidia）
+docker info | findstr nvidia
+```
+
+如果没有 `nvidia` runtime，需要先安装 [NVIDIA Container Toolkit](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html)。
+
+## 配置 Whisper 使用 GPU
+
+在 `config.toml` 中设置：
+
+```toml
+subtitle_provider = "whisper"
+
+[whisper]
+model_size = "large-v3"
+device = "cuda"           # 使用 GPU（CPU 用户设为 "cpu"）
+compute_type = "float16"  # GPU 推荐 float16（CPU 用户设为 "int8"）
+```
+
+## 文件说明
+
+| 文件 | 用途 |
+|---|---|
+| `Dockerfile` | 默认 CPU 镜像（原有，未修改） |
+| `Dockerfile.gpu` | GPU 镜像（新增，基于 NVIDIA CUDA） |
+| `docker-compose.yml` | 默认 CPU 部署配置（原有，未修改） |
+| `docker-compose.gpu.yml` | GPU 部署覆盖配置（新增） |
+
+## GPU 部署步骤
+
+### 第 1 步：拉取 CUDA 基础镜像
+
+```bash
+docker pull nvidia/cuda:12.1.1-cudnn8-runtime-ubuntu22.04
+```
+
+> 如果使用了阿里云等镜像加速源，可能对 `nvidia/cuda` 返回 403。请确保能从 Docker Hub 直接拉取。
+
+### 第 2 步：修改 config.toml
+
+按上文说明设置 `subtitle_provider = "whisper"` 和 `device = "cuda"`。
+
+### 第 3 步：构建并启动
+
+```bash
+docker compose -f docker-compose.yml -f docker-compose.gpu.yml up -d --build
+```
+
+### 第 4 步：验证 GPU 是否生效
+
+```bash
+docker exec -it moneyprinterturbo-api nvidia-smi
+```
+
+如果能看到 GPU 信息，说明 GPU 挂载成功。
+
+## 显存与并发建议
+
+| GPU 显存 | 建议最大并发任务数 |
+|---|---|
+| 4GB | 1-2 |
+| 6GB | 2-3 |
+| 8GB | 3-4 |
+| 12GB+ | 5 |
+
+可通过 `config.toml` 中的 `max_concurrent_tasks` 控制并发数。
+
+## 故障排查
+
+### 问题 1：镜像拉取失败（403 Forbidden）
+
+阿里云镜像加速对 `nvidia/cuda` 返回 403。解决方法：
+- 配置其他可用的镜像加速源
+- 或直接 `docker pull nvidia/cuda:12.1.1-cudnn8-runtime-ubuntu22.04`
+
+### 问题 2：pip 安装报 `Cannot uninstall blinker`
+
+Ubuntu 22.04 系统自带的 `blinker` 通过 `distutils` 安装，pip 无法卸载。`Dockerfile.gpu` 已通过 `apt-get remove -y python3-blinker` 处理。
+
+### 问题 3：容器内 `nvidia-smi` 找不到 GPU
+
+- 确认宿主机已安装 NVIDIA Container Toolkit
+- 确认 `docker info` 中 Runtimes 包含 `nvidia`
+- 确认使用了 GPU 部署命令：`docker compose -f docker-compose.yml -f docker-compose.gpu.yml up -d`
+
+### 问题 4：Whisper 报 CUDA 错误
+
+- 确认 `config.toml` 中 `device = "cuda"`（大小写敏感，不是 `"CPU"`）
+- 确认 `compute_type = "float16"`
+- 确认 `subtitle_provider = "whisper"`

docs/MoneyPrinterTurbo.ipynb

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+{
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "# MoneyPrinterTurbo Setup Guide\n",
+        "\n",
+        "This notebook will guide you through the process of setting up [MoneyPrinterTurbo](https://github.com/harry0703/MoneyPrinterTurbo)."
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## 1. Clone Repository and Install Dependencies\n",
+        "\n",
+        "First, we'll clone the repository from GitHub and install all required packages:"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "S8Eu-aQarY_B"
+      },
+      "outputs": [],
+      "source": [
+        "!git clone https://github.com/harry0703/MoneyPrinterTurbo.git\n",
+        "%cd MoneyPrinterTurbo\n",
+        "!pip install -q uv pyngrok\n",
+        "!uv python install 3.11\n",
+        "# Colab 预装了 google-colab / google-genai / google-adk 等包，直接 pip install -r requirements.txt\n",
+        "# 会覆盖全局依赖并触发版本冲突。这里使用 uv 为项目创建独立 .venv，避免影响 Colab 运行时。\n",
+        "!uv sync --frozen --python 3.11"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## 2. Configure ngrok for Remote Access\n",
+        "\n",
+        "We'll use ngrok to create a secure tunnel to expose our local Streamlit server to the internet.\n",
+        "\n",
+        "**Important**: You need to get your authentication token from the [ngrok dashboard](https://dashboard.ngrok.com/get-started/your-authtoken) to use this service."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "from pyngrok import ngrok\n",
+        "\n",
+        "# Terminate any existing ngrok tunnels\n",
+        "ngrok.kill()\n",
+        "\n",
+        "# Set your authentication token\n",
+        "# Replace \"your_ngrok_auth_token\" with your actual token\n",
+        "ngrok.set_auth_token(\"your_ngrok_auth_token\")"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## 3. Launch Application and Generate Public URL\n",
+        "\n",
+        "Now we'll start the Streamlit server and create an ngrok tunnel to make it accessible online:"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "collapsed": true,
+        "id": "oahsIOXmwjl9",
+        "outputId": "ee23a96c-af21-4207-deb7-9fab69e0c05e"
+      },
+      "outputs": [],
+      "source": [
+        "import subprocess\n",
+        "import time\n",
+        "\n",
+        "print(\"🚀 Starting MoneyPrinterTurbo...\")\n",
+        "# 通过 uv run 进入项目 .venv，确保 Streamlit 使用上一步锁定的依赖版本。\n",
+        "streamlit_proc = subprocess.Popen([\n",
+        "    \"uv\", \"run\", \"streamlit\", \"run\", \"./webui/Main.py\", \"--server.port=8501\", \"--server.address=0.0.0.0\"\n",
+        "])\n",
+        "\n",
+        "# Wait for the server to initialize\n",
+        "time.sleep(5)\n",
+        "\n",
+        "print(\"🌐 Creating ngrok tunnel to expose the MoneyPrinterTurbo...\")\n",
+        "public_url = ngrok.connect(8501, bind_tls=True)\n",
+        "\n",
+        "print(\"✅ Deployment complete! Access your MoneyPrinterTurbo at:\")\n",
+        "print(public_url)"
+      ]
+    }
+  ],
+  "metadata": {
+    "colab": {
+      "provenance": []
+    },
+    "kernelspec": {
+      "display_name": "Python 3",
+      "name": "python3"
+    },
+    "language_info": {
+      "name": "python"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}

docs/PR_MERGE_RECORD_2026-04-02.md

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+# 2026-04-02 PR 合并与验证记录
+
+## 本次已合并并推送的 PR
+
+- `#837` `fix: update google-generativeai version for response_modalities support`
+- `#835` `fix: add missing pydub dependency to requirements.txt`
+- `#850` `feat: support reading subtitle position from config file`
+- `#838` `feat: add MiniMax as LLM provider`
+- `#811` `refactor: optimize codebase for better performance and reliability`
+- `#848` `feat: support GPU acceleration for faster-whisper in Docker`
+- `#843` `feat: Add Upload-Post integration for cross-posting to TikTok/Instagram`
+
+## 合并后的主线提交
+
+- TTS 与字幕修复基线提交：`953a6c0` `fix: restore edge tts synthesis and readable subtitles`
+- 当前主线提交：`1f8a746`
+
+## 合并时的验证结论
+
+### 已通过
+
+- `#837`
+  - 依赖升级后可正常导入
+  - `google-generativeai==0.8.6` 已生效
+- `#835`
+  - `pydub==0.25.1` 已生效
+- `#850`
+  - `subtitle_position` 与 `custom_position` 可从配置文件读取
+- `#838`
+  - MiniMax provider 接线正常
+  - 使用 mock 调用验证 `_generate_response` 通过
+- `#811`
+  - 主线导入正常
+  - 抽样单测通过
+- `#848`
+  - `docker compose -f docker-compose.yml -f docker-compose.gpu.yml config` 可正常解析
+- `#843`
+  - Upload-Post 服务导入和 mock 上传调用通过
+  - 与前面 PR 叠加时仅在 `config.example.toml` 存在配置段落冲突，已手工保留两边内容
+
+### 已拒绝并关闭
+
+- `#852`
+  - 能恢复音频，但会破坏字幕链路，并删除仍被 WebUI 调用的 Gemini 逻辑
+- `#787`
+  - 不能解决当前 `403` 场景
+- `#841`
+  - 与当前主线 TTS/字幕修复冲突，且收益已被更小 PR 覆盖
+- `#824`
+  - ModelsLab 路径能出音频，但字幕链路失败，无法产出可用 SRT
+- `#840`
+  - 后端加入 `video_source="ai"`，但 WebUI 仍不支持该值，端到端不可用
+- `#826`
+  - 与当前主线 `voice.py` 和依赖变更冲突，未通过合并验证
+- `#751`
+- `#749`
+- `#742`
+- `#705`
+  - 以上 4 个 PR 在当前主线下均为 `DIRTY`，未通过合并验证
+
+## 冒烟测试记录
+
+### 服务重启
+
+- API：`http://127.0.0.1:8080/docs`
+- WebUI：`http://127.0.0.1:8501`
+
+### 第一次完整视频任务
+
+- 任务号：`ced0b190-dd72-489c-b978-2761740933db`
+- 结果：失败
+- 结论：
+  - API 默认 `video_transition_mode=null`
+  - 视频拼接阶段在 `app/services/video.py` 中直接访问 `video_transition_mode.value`
+  - 导致任务线程异常退出，任务状态停留在 `state=4, progress=75`
+
+### 第二次完整视频任务
+
+- 任务号：`8b2a0e6e-b3e6-44ab-a1b4-1865a0b4788d`
+- 提交方式：
+  - `POST /api/v1/videos`
+  - 使用本地素材 `/Users/harry/Projects/Python/MoneyPrinterTurbo/test/resources/1.png`
+  - 显式指定 `video_transition_mode="FadeIn"`
+- 结果：成功
+- 任务状态：`state=1, progress=100`
+
+### 第二次任务产物
+
+- 音频：`/Users/harry/Projects/Python/MoneyPrinterTurbo/storage/tasks/8b2a0e6e-b3e6-44ab-a1b4-1865a0b4788d/audio.mp3`
+  - 时长：`8.952s`
+  - 大小：`53712 bytes`
+- 拼接视频：`/Users/harry/Projects/Python/MoneyPrinterTurbo/storage/tasks/8b2a0e6e-b3e6-44ab-a1b4-1865a0b4788d/combined-1.mp4`
+  - 时长：`9.000s`
+  - 大小：`177666 bytes`
+- 成片：`/Users/harry/Projects/Python/MoneyPrinterTurbo/storage/tasks/8b2a0e6e-b3e6-44ab-a1b4-1865a0b4788d/final-1.mp4`
+  - 时长：`9.000s`
+  - 大小：`352810 bytes`
+- 字幕：`/Users/harry/Projects/Python/MoneyPrinterTurbo/storage/tasks/8b2a0e6e-b3e6-44ab-a1b4-1865a0b4788d/subtitle.srt`
+
+### 第二次任务字幕样本
+
+```srt
+1
+00:00:00,100 --> 00:00:03,300
+这是一次主线合并后的完整冒烟测试
+
+2
+00:00:03,875 --> 00:00:05,350
+我们要确认语音
+
+3
+00:00:05,575 --> 00:00:08,375
+字幕和视频成片都能正常生成
+```
+
+## 当前仍需关注的风险
+
+- `#843` 仅做了 mock 验证，尚未使用真实 Upload-Post 密钥联调
+- `#848` 仅验证了 Docker GPU 配置解析，尚未在真实 GPU 环境运行
+- 当前 API 默认 `video_transition_mode=null` 时，完整视频任务仍存在回归风险

docs/voice-list.txt

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+Name: af-ZA-AdriNeural
+Gender: Female
+
+Name: af-ZA-WillemNeural
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+
+Name: am-ET-AmehaNeural
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+Name: am-ET-MekdesNeural
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+Name: ar-BH-LailaNeural
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+Name: ar-DZ-IsmaelNeural
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+Name: ar-EG-ShakirNeural
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+Name: ar-IQ-BasselNeural
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+Name: ar-IQ-RanaNeural
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+Name: ar-JO-SanaNeural
+Gender: Female
+
+Name: ar-JO-TaimNeural
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+Name: ar-KW-FahedNeural
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+Name: ar-KW-NouraNeural
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+Name: ar-LB-LaylaNeural
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+Name: ar-LB-RamiNeural
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+Name: ar-SY-LaithNeural
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+Name: ar-TN-HediNeural
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+Name: ar-TN-ReemNeural
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+Name: ar-YE-MaryamNeural
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+Name: ar-YE-SalehNeural
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+Name: az-AZ-BabekNeural
+Gender: Male
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+Name: bg-BG-BorislavNeural
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+Name: bg-BG-KalinaNeural
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+Name: bn-BD-NabanitaNeural
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+Name: bn-BD-PradeepNeural
+Gender: Male
+
+Name: bn-IN-BashkarNeural
+Gender: Male
+
+Name: bn-IN-TanishaaNeural
+Gender: Female
+
+Name: bs-BA-GoranNeural
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+
+Name: bs-BA-VesnaNeural
+Gender: Female
+
+Name: ca-ES-EnricNeural
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+
+Name: ca-ES-JoanaNeural
+Gender: Female
+
+Name: cs-CZ-AntoninNeural
+Gender: Male
+
+Name: cs-CZ-VlastaNeural
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+
+Name: cy-GB-AledNeural
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+
+Name: cy-GB-NiaNeural
+Gender: Female
+
+Name: da-DK-ChristelNeural
+Gender: Female
+
+Name: da-DK-JeppeNeural
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+
+Name: de-AT-IngridNeural
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+Name: de-AT-JonasNeural
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+Name: de-CH-JanNeural
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+
+Name: de-CH-LeniNeural
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+
+Name: de-DE-AmalaNeural
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+
+Name: de-DE-ConradNeural
+Gender: Male
+
+Name: de-DE-FlorianMultilingualNeural
+Gender: Male
+
+Name: de-DE-KatjaNeural
+Gender: Female
+
+Name: de-DE-KillianNeural
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+
+Name: de-DE-SeraphinaMultilingualNeural
+Gender: Female
+
+Name: el-GR-AthinaNeural
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+Name: el-GR-NestorasNeural
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+Name: en-CA-LiamNeural
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+Name: en-IE-EmilyNeural
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+Name: en-IN-NeerjaExpressiveNeural
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+Name: en-IN-NeerjaNeural
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+Name: en-IN-PrabhatNeural
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+Name: en-KE-AsiliaNeural
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+Name: en-KE-ChilembaNeural
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+Name: en-NG-AbeoNeural
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+
+Name: en-NG-EzinneNeural
+Gender: Female
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+Name: en-NZ-MitchellNeural
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+Name: en-NZ-MollyNeural
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+Name: en-PH-JamesNeural
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+Name: en-PH-RosaNeural
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+Name: en-SG-WayneNeural
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+Name: en-TZ-ImaniNeural
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+Name: en-US-BrianNeural
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