Merge pull request #715 from michaeltmk/feat/custom_audio

feat: add custom audio file support

.github/ISSUE_TEMPLATE/bug_report.yml

@@ -0,0 +1,87 @@
+name: 🐛 Bug | Bug Report
+description: 报告错误或异常问题 | Report an error or unexpected behavior
+title: "[Bug]: "
+labels:
+  - bug
+
+body:
+  - type: markdown
+    attributes:
+      value: |
+        **提交问题前，请确保您已阅读以下文档：[Getting Started (English)](https://github.com/harry0703/MoneyPrinterTurbo/blob/main/README-en.md#system-requirements-) 或 [快速开始 (中文)](https://github.com/harry0703/MoneyPrinterTurbo/blob/main/README.md#%E5%BF%AB%E9%80%9F%E5%BC%80%E5%A7%8B-)。**
+        
+        **Before submitting an issue, please make sure you've read the following documentation: [Getting Started (English)](https://github.com/harry0703/MoneyPrinterTurbo/blob/main/README-en.md#system-requirements-) or [快速开始 (Chinese)](https://github.com/harry0703/MoneyPrinterTurbo/blob/main/README.md#%E5%BF%AB%E9%80%9F%E5%BC%80%E5%A7%8B-).**
+        
+  - type: textarea
+    attributes:
+      label: 问题描述 | Current Behavior
+      description: |
+        描述您遇到的问题
+        Describe the issue you're experiencing
+      placeholder: |
+        当我执行...操作时，程序出现了...问题
+        When I perform..., the program shows...
+    validations:
+      required: true
+  - type: textarea
+    attributes:
+      label: 重现步骤 | Steps to Reproduce
+      description: |
+        详细描述如何重现此问题
+        Describe in detail how to reproduce this issue
+      placeholder: |
+        1. 打开...
+        2. 点击...
+        3. 出现错误...
+        
+        1. Open...
+        2. Click on...
+        3. Error occurs...
+    validations:
+      required: true
+  - type: textarea
+    attributes:
+      label: 错误日志 | Error Logs
+      description: |
+        请提供相关错误信息或日志（注意不要包含敏感信息）
+        Please provide any error messages or logs (be careful not to include sensitive information)
+      placeholder: |
+        错误信息、日志或截图...
+        Error messages, logs, or screenshots...
+    validations:
+      required: true
+  - type: input
+    attributes:
+      label: Python 版本 | Python Version
+      description: |
+        您使用的 Python 版本
+        The Python version you're using
+      placeholder: v3.13.0, v3.10.0, etc.
+    validations:
+      required: true
+  - type: input
+    attributes:
+      label: 操作系统 | Operating System
+      description: |
+        您的操作系统信息
+        Your operating system information
+      placeholder: macOS 14.1, Windows 11, Ubuntu 22.04, etc.
+    validations:
+      required: true
+  - type: input
+    attributes:
+      label: MoneyPrinterTurbo 版本 | Version
+      description: |
+        您使用的 MoneyPrinterTurbo 版本
+        The version of MoneyPrinterTurbo you're using
+      placeholder: v1.2.2, etc.
+    validations:
+      required: true
+  - type: textarea
+    attributes:
+      label: 补充信息 | Additional Information
+      description: |
+        其他对解决问题有帮助的信息（如截图、视频等）
+        Any other information that might help solve the issue (screenshots, videos, etc.)
+    validations:
+      required: false

.github/ISSUE_TEMPLATE/config.yml

@@ -0,0 +1 @@
+blank_issues_enabled: false

.github/ISSUE_TEMPLATE/feature_request.yml

@@ -0,0 +1,29 @@
+name: ✨ 增加功能 | Feature Request
+description: 为此项目提出一个新想法或建议 | Suggest a new idea for this project
+title: "[Feature]: "
+labels:
+  - enhancement
+
+body:
+  - type: textarea
+    attributes:
+      label: 需求描述 | Problem Statement
+      description: |
+        请描述您希望解决的问题或需求 
+        Please describe the problem you want to solve
+      placeholder: |
+        我在使用过程中遇到了...
+        I encountered... when using this project
+    validations:
+      required: true
+  - type: textarea
+    attributes:
+      label: 建议的解决方案 | Proposed Solution
+      description: |
+        请描述您认为可行的解决方案或实现方式
+        Please describe your suggested solution or implementation
+      placeholder: |
+        可以考虑添加...功能来解决这个问题
+        Consider adding... feature to address this issue
+    validations:
+      required: true

.github/workflows/gh-pages.yml

@@ -1,33 +0,0 @@
-name: gp-pages
-on:
-  push:
-    branches:
-      - main
-    paths:
-      - 'sites/**'
-
-jobs:
-  build-deploy:
-    runs-on: ubuntu-latest
-    steps:
-      - name: Checkout
-        uses: actions/checkout@v2
-      - name: Set-up Node
-        uses: actions/setup-node@v1
-        with:
-          node-version: "18.15.0"
-      - name: Install pnpm
-        run: npm install -g pnpm
-      - name: Install dependencies
-        run: pnpm i
-        working-directory: ./sites
-      - name: Build gh-pages
-        run: pnpm docs:build
-        working-directory: ./sites
-      - name: Deploy to gh-pages
-        uses: crazy-max/ghaction-github-pages@v1
-        with:
-          target_branch: gh-pages
-          build_dir: sites/docs/.vuepress/dist
-        env:
-          GITHUB_TOKEN: ${{ secrets.MY_TOKEN }}

.gitignore

@@ -22,4 +22,14 @@ node_modules
 /sites/docs/.vuepress/dist
 # 模型目录
 /models/
-./models/*
+./models/*
+
+venv/
+.venv
+
+# Debug and test files
+CLAUDE.md
+debug/
+debug_*.py
+test_*.py
+streamlit.log

CHANGELOG.md

@@ -1,22 +0,0 @@
-<!-- insertion marker -->
-## [1.1.2](https://github.com/KevinZhang19870314/MoneyPrinterTurbo/releases/tag/1.1.2) - 2024-04-18
-
-<small>[Compare with first commit](https://github.com/KevinZhang19870314/MoneyPrinterTurbo/compare/d4f7b53b841e65da658e3d77822f9923286ddab6...1.1.2)</small>
-
-### Features
-
-- add support for maximum concurrency of /api/v1/videos ([abe12ab](https://github.com/KevinZhang19870314/MoneyPrinterTurbo/commit/abe12abd7b78997651468ad5dd656985066f8bd9) by kevin.zhang).
-- add task deletion endpoint ([d57434e](https://github.com/KevinZhang19870314/MoneyPrinterTurbo/commit/d57434e0d31c8195dbcd3c86ff2763af96736cdf) by kevin.zhang).
-- add redis support for task state management ([3d45348](https://github.com/KevinZhang19870314/MoneyPrinterTurbo/commit/3d453486627234937c7bfe6f176890360074696b) by kevin.zhang).
-- enable cors to allow play video through mounted videos url ([3b1871d](https://github.com/KevinZhang19870314/MoneyPrinterTurbo/commit/3b1871d591873594bb4aa8dc17a1253b3a7563a3) by kevin.zhang).
-- add /api/v1/get_bgm_list and /api/v1/upload_bgm_file ([6d8911f](https://github.com/KevinZhang19870314/MoneyPrinterTurbo/commit/6d8911f5bf496e7c5dd718309a302df88d11817b) by cathy).
-- return combined videos in /api/v1/tasks response ([28199c9](https://github.com/KevinZhang19870314/MoneyPrinterTurbo/commit/28199c93b78f67e9a6bf50f290f1591078f63da8) by cathy).
-- add Dockerfile ([f3b3c7f](https://github.com/KevinZhang19870314/MoneyPrinterTurbo/commit/f3b3c7fb47b01ed4ecba44eaebf29f5d6d2cb7b5) by kevin.zhang).
-
-### Bug Fixes
-
-- response parsing bug for gemini ([ee7306d](https://github.com/KevinZhang19870314/MoneyPrinterTurbo/commit/ee7306d216ea41e40855bbca396cacb094d572db) by elf-mouse).
-
-### Code Refactoring
-
-- Streaming MP4 files in the browser using video html element instead of waiting for the entire file to download before playing ([d13a3cf](https://github.com/KevinZhang19870314/MoneyPrinterTurbo/commit/d13a3cf6e911d1573c62b1f6459c3c0b7a1bc18d) by kevin.zhang).

Dockerfile

@@ -1,5 +1,5 @@
 # Use an official Python runtime as a parent image
-FROM python:3.10-slim-bullseye
+FROM python:3.11-slim-bullseye
 
 # Set the working directory in the container
 WORKDIR /MoneyPrinterTurbo
@@ -9,12 +9,40 @@ RUN chmod 777 /MoneyPrinterTurbo
 
 ENV PYTHONPATH="/MoneyPrinterTurbo"
 
-# Install system dependencies
-RUN apt-get update && apt-get install -y \
-    git \
-    imagemagick \
-    ffmpeg \
-    && rm -rf /var/lib/apt/lists/*
+# Install system dependencies with domestic mirrors first for stability
+RUN echo "deb http://mirrors.aliyun.com/debian bullseye main" > /etc/apt/sources.list && \
+    echo "deb http://mirrors.aliyun.com/debian-security bullseye-security main" >> /etc/apt/sources.list && \
+    ( \
+        for i in 1 2 3; do \
+            echo "Attempt $i: Using Aliyun mirror"; \
+            apt-get update && apt-get install -y --no-install-recommends \
+                git \
+                imagemagick \
+                ffmpeg && break || \
+            echo "Attempt $i failed, retrying..."; \
+            if [ $i -eq 3 ]; then \
+                echo "Aliyun mirror failed, switching to Tsinghua mirror"; \
+                sed -i 's/mirrors.aliyun.com/mirrors.tuna.tsinghua.edu.cn/g' /etc/apt/sources.list && \
+                sed -i 's/mirrors.aliyun.com\/debian-security/mirrors.tuna.tsinghua.edu.cn\/debian-security/g' /etc/apt/sources.list && \
+                ( \
+                    apt-get update && apt-get install -y --no-install-recommends \
+                        git \
+                        imagemagick \
+                        ffmpeg || \
+                    ( \
+                        echo "Tsinghua mirror failed, switching to default Debian mirror"; \
+                        sed -i 's/mirrors.tuna.tsinghua.edu.cn/deb.debian.org/g' /etc/apt/sources.list && \
+                        sed -i 's/mirrors.tuna.tsinghua.edu.cn\/debian-security/security.debian.org/g' /etc/apt/sources.list; \
+                        apt-get update && apt-get install -y --no-install-recommends \
+                            git \
+                            imagemagick \
+                            ffmpeg; \
+                    ); \
+                ); \
+            fi; \
+            sleep 5; \
+        done \
+    ) && rm -rf /var/lib/apt/lists/*
 
 # Fix security policy for ImageMagick
 RUN sed -i '/<policy domain="path" rights="none" pattern="@\*"/d' /etc/ImageMagick-6/policy.xml
@@ -22,8 +50,10 @@ RUN sed -i '/<policy domain="path" rights="none" pattern="@\*"/d' /etc/ImageMagi
 # Copy only the requirements.txt first to leverage Docker cache
 COPY requirements.txt ./
 
-# Install Python dependencies
-RUN pip install --no-cache-dir -r requirements.txt
+# Install Python dependencies with domestic mirrors first and retry logic
+RUN pip install --no-cache-dir -i https://mirrors.aliyun.com/pypi/simple/ --trusted-host mirrors.aliyun.com --retries 3 --timeout 60 -r requirements.txt || \
+    pip install --no-cache-dir -i https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple/ --trusted-host mirrors.tuna.tsinghua.edu.cn --retries 3 --timeout 60 -r requirements.txt || \
+    pip install --no-cache-dir --retries 3 --timeout 60 -r requirements.txt
 
 # Now copy the rest of the codebase into the image
 COPY . .
@@ -41,4 +71,4 @@ CMD ["streamlit", "run", "./webui/Main.py","--browser.serverAddress=127.0.0.1","
 ## For Linux or MacOS:
 # docker run -v $(pwd)/config.toml:/MoneyPrinterTurbo/config.toml -v $(pwd)/storage:/MoneyPrinterTurbo/storage -p 8501:8501 moneyprinterturbo
 ## For Windows:
-# docker run -v %cd%/config.toml:/MoneyPrinterTurbo/config.toml -v %cd%/storage:/MoneyPrinterTurbo/storage -p 8501:8501 moneyprinterturbo
+# docker run -v ${PWD}/config.toml:/MoneyPrinterTurbo/config.toml -v ${PWD}/storage:/MoneyPrinterTurbo/storage -p 8501:8501 moneyprinterturbo

README-en.md

@@ -35,10 +35,19 @@ like to express our special thanks to
 **RecCloud (AI-Powered Multimedia Service Platform)** for providing a free `AI Video Generator` service based on this
 project. It allows for online use without deployment, which is very convenient.
 
-https://reccloud.com
+- Chinese version: https://reccloud.cn
+- English version: https://reccloud.com
 
 ![](docs/reccloud.com.jpg)
 
+## Thanks for Sponsorship 🙏
+
+Thanks to Picwish https://picwish.com for supporting and sponsoring this project, enabling continuous updates and maintenance.
+
+Picwish focuses on the **image processing field**, providing a rich set of **image processing tools** that extremely simplify complex operations, truly making image processing easier.
+
+![picwish.jpg](docs/picwish.com.jpg)
+
 ## Features 🎯
 
 - [x] Complete **MVC architecture**, **clearly structured** code, easy to maintain, supports both `API`
@@ -51,28 +60,22 @@ https://reccloud.com
   satisfactory one
 - [x] Supports setting the **duration of video clips**, facilitating adjustments to material switching frequency
 - [x] Supports video copy in both **Chinese** and **English**
-- [x] Supports **multiple voice** synthesis
+- [x] Supports **multiple voice** synthesis, with **real-time preview** of effects
 - [x] Supports **subtitle generation**, with adjustable `font`, `position`, `color`, `size`, and also
   supports `subtitle outlining`
 - [x] Supports **background music**, either random or specified music files, with adjustable `background music volume`
-- [x] Video material sources are **high-definition** and **royalty-free**
-- [x] Supports integration with various models such as **OpenAI**, **moonshot**, **Azure**, **gpt4free**, **one-api**,
-  **qianwen**, **Google Gemini**, **Ollama** and more
-
-❓[How to Use the Free OpenAI GPT-3.5 Model?](https://github.com/harry0703/MoneyPrinterTurbo/blob/main/README-en.md#common-questions-)
+- [x] Video material sources are **high-definition** and **royalty-free**, and you can also use your own **local materials**
+- [x] Supports integration with various models such as **OpenAI**, **Moonshot**, **Azure**, **gpt4free**, **one-api**, **Qwen**, **Google Gemini**, **Ollama**, **DeepSeek**, **ERNIE**, **Pollinations**, **ModelScope** and more
 
 ### Future Plans 📅
 
-- [ ] Introduce support for GPT-SoVITS dubbing
-- [ ] Enhance voice synthesis with large models for a more natural and emotionally resonant voice output
-- [ ] Incorporate video transition effects to ensure a smoother viewing experience
-- [ ] Improve the relevance of video content
-- [ ] Add options for video length: short, medium, long
-- [ ] Package the application into a one-click launch bundle for Windows and macOS for ease of use
-- [ ] Enable the use of custom materials
-- [ ] Offer voiceover and background music options with real-time preview
-- [ ] Support a wider range of voice synthesis providers, such as OpenAI TTS, Azure TTS
-- [ ] Automate the upload process to the YouTube platform
+- [ ] GPT-SoVITS dubbing support
+- [ ] Optimize voice synthesis using large models for more natural and emotionally rich voice output
+- [ ] Add video transition effects for a smoother viewing experience
+- [ ] Add more video material sources, improve the matching between video materials and script
+- [ ] Add video length options: short, medium, long
+- [ ] Support more voice synthesis providers, such as OpenAI TTS
+- [ ] Automate upload to YouTube platform
 
 ## Video Demos 📺
 
@@ -112,13 +115,32 @@ https://reccloud.com
 
 ## System Requirements 📦
 
-- Recommended minimum 4 CPU cores or more, 8G of memory or more, GPU is not required
+- Recommended minimum 4 CPU cores or more, 4G of memory or more, GPU is not required
 - Windows 10 or MacOS 11.0, and their later versions
 
+## Quick Start 🚀
+
+### Run in Google Colab 
+Want to try MoneyPrinterTurbo without setting up a local environment? Run it directly in Google Colab!
+
+[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/harry0703/MoneyPrinterTurbo/blob/main/docs/MoneyPrinterTurbo.ipynb)
+
+
+### Windows
+
+Google Drive (v1.2.6): https://drive.google.com/file/d/1HsbzfT7XunkrCrHw5ncUjFX8XX4zAuUh/view?usp=sharing
+
+After downloading, it is recommended to **double-click** `update.bat` first to update to the **latest code**, then double-click `start.bat` to launch
+
+After launching, the browser will open automatically (if it opens blank, it is recommended to use **Chrome** or **Edge**)
+
+### Other Systems
+
+One-click startup packages have not been created yet. See the **Installation & Deployment** section below. It is recommended to use **docker** for deployment, which is more convenient.
+
 ## Installation & Deployment 📥
 
-- Try to avoid using **Chinese paths** to prevent unpredictable issues
-- Ensure your **network** is stable, meaning you can access foreign websites normally
+### Prerequisites
 
 #### ① Clone the Project
 
@@ -132,11 +154,6 @@ git clone https://github.com/harry0703/MoneyPrinterTurbo.git
 - Follow the instructions in the `config.toml` file to configure `pexels_api_keys` and `llm_provider`, and according to
   the llm_provider's service provider, set up the corresponding API Key
 
-#### ③ Configure Large Language Models (LLM)
-
-- To use `GPT-4.0` or `GPT-3.5`, you need an `API Key` from `OpenAI`. If you don't have one, you can set `llm_provider`
-  to `g4f` (a free-to-use GPT library https://github.com/xtekky/gpt4free)
-
 ### Docker Deployment 🐳
 
 #### ① Launch the Docker Container
@@ -152,6 +169,8 @@ cd MoneyPrinterTurbo
 docker-compose up
 ```
 
+> Note：The latest version of docker will automatically install docker compose in the form of a plug-in, and the start command is adjusted to `docker compose up `
+
 #### ② Access the Web Interface
 
 Open your browser and visit http://0.0.0.0:8501
@@ -164,13 +183,12 @@ Open your browser and visit http://0.0.0.0:8080/docs Or http://0.0.0.0:8080/redo
 
 #### ① Create a Python Virtual Environment
 
-It is recommended to create a Python virtual environment
-using [conda](https://conda.io/projects/conda/en/latest/user-guide/install/index.html)
+It is recommended to create a Python virtual environment using [conda](https://conda.io/projects/conda/en/latest/user-guide/install/index.html)
 
 ```shell
 git clone https://github.com/harry0703/MoneyPrinterTurbo.git
 cd MoneyPrinterTurbo
-conda create -n MoneyPrinterTurbo python=3.10
+conda create -n MoneyPrinterTurbo python=3.11
 conda activate MoneyPrinterTurbo
 pip install -r requirements.txt
 ```
@@ -179,10 +197,9 @@ pip install -r requirements.txt
 
 ###### Windows:
 
-- Download https://imagemagick.org/archive/binaries/ImageMagick-7.1.1-29-Q16-x64-static.exe
+- Download https://imagemagick.org/script/download.php Choose the Windows version, make sure to select the **static library** version, such as ImageMagick-7.1.1-32-Q16-x64-**static**.exe
 - Install the downloaded ImageMagick, **do not change the installation path**
-- Modify the `config.toml` configuration file, set `imagemagick_path` to your actual installation path (if you didn't
-  change the path during installation, just uncomment it)
+- Modify the `config.toml` configuration file, set `imagemagick_path` to your actual installation path
 
 ###### MacOS:
 
@@ -209,14 +226,12 @@ Note that you need to execute the following commands in the `root directory` of
 ###### Windows
 
 ```bat
-conda activate MoneyPrinterTurbo
 webui.bat
 ```
 
 ###### MacOS or Linux
 
 ```shell
-conda activate MoneyPrinterTurbo
 sh webui.sh
 ```
 
@@ -235,13 +250,15 @@ online for a quick experience.
 
 A list of all supported voices can be viewed here: [Voice List](./docs/voice-list.txt)
 
+2024-04-16 v1.1.2 Added 9 new Azure voice synthesis voices that require API KEY configuration. These voices sound more realistic.
+
 ## Subtitle Generation 📜
 
 Currently, there are 2 ways to generate subtitles:
 
-- edge: Faster generation speed, better performance, no specific requirements for computer configuration, but the
+- **edge**: Faster generation speed, better performance, no specific requirements for computer configuration, but the
   quality may be unstable
-- whisper: Slower generation speed, poorer performance, specific requirements for computer configuration, but more
+- **whisper**: Slower generation speed, poorer performance, specific requirements for computer configuration, but more
   reliable quality
 
 You can switch between them by modifying the `subtitle_provider` in the `config.toml` configuration file
@@ -250,18 +267,22 @@ It is recommended to use `edge` mode, and switch to `whisper` mode if the qualit
 satisfactory.
 
 > Note:
-> If left blank, it means no subtitles will be generated.
+>
+> 1. In whisper mode, you need to download a model file from HuggingFace, about 3GB in size, please ensure good internet connectivity
+> 2. If left blank, it means no subtitles will be generated.
 
-**Download whisper**
-- Please ensure a good internet connectivity
-- `whisper` model can be downloaded from HuggingFace: https://huggingface.co/openai/whisper-large-v3/tree/main
+> Since HuggingFace is not accessible in China, you can use the following methods to download the `whisper-large-v3` model file
 
-After downloading the model to local machine, copy the whole folder and put it into the following path: `.\MoneyPrinterTurbo\models`
+Download links:
 
-This is what the final path should look like: `.\MoneyPrinterTurbo\models\whisper-large-v3`
+- Baidu Netdisk: https://pan.baidu.com/s/11h3Q6tsDtjQKTjUu3sc5cA?pwd=xjs9
+- Quark Netdisk: https://pan.quark.cn/s/3ee3d991d64b
+
+After downloading the model, extract it and place the entire directory in `.\MoneyPrinterTurbo\models`,
+The final file path should look like this: `.\MoneyPrinterTurbo\models\whisper-large-v3`
 
 ```
-MoneyPrinterTurbo  
+MoneyPrinterTurbo
   ├─models
   │   └─whisper-large-v3
   │          config.json
@@ -284,24 +305,6 @@ own fonts.
 
 ## Common Questions 🤔
 
-### ❓How to Use the Free OpenAI GPT-3.5 Model?
-
-[OpenAI has announced that ChatGPT with 3.5 is now free](https://openai.com/blog/start-using-chatgpt-instantly), and
-developers have wrapped it into an API for direct usage.
-
-**Ensure you have Docker installed and running**. Execute the following command to start the Docker service:
-
-```shell
-docker run -p 3040:3040 missuo/freegpt35
-```
-
-Once successfully started, modify the `config.toml` configuration as follows:
-
-- Set `llm_provider` to `openai`
-- Fill in `openai_api_key` with any value, for example, '123456'
-- Change `openai_base_url` to `http://localhost:3040/v1/`
-- Set `openai_model_name` to `gpt-3.5-turbo`
-
 ### ❓RuntimeError: No ffmpeg exe could be found
 
 Normally, ffmpeg will be automatically downloaded and detected.
@@ -321,24 +324,6 @@ actual installation path.
 ffmpeg_path = "C:\\Users\\harry\\Downloads\\ffmpeg.exe"
 ```
 
-### ❓Error generating audio or downloading videos
-
-[issue 56](https://github.com/harry0703/MoneyPrinterTurbo/issues/56)
-
-```
-failed to generate audio, maybe the network is not available. 
-if you are in China, please use a VPN.
-```
-
-[issue 44](https://github.com/harry0703/MoneyPrinterTurbo/issues/44)
-
-```
-failed to download videos, maybe the network is not available. 
-if you are in China, please use a VPN.
-```
-
-This is likely due to network issues preventing access to foreign services. Please use a VPN to resolve this.
-
 ### ❓ImageMagick is not installed on your computer
 
 [issue 33](https://github.com/harry0703/MoneyPrinterTurbo/issues/33)
@@ -353,16 +338,48 @@ For Linux systems, you can manually install it, refer to https://cn.linux-consol
 
 Thanks to [@wangwenqiao666](https://github.com/wangwenqiao666) for their research and exploration
 
+### ❓ImageMagick's security policy prevents operations related to temporary file @/tmp/tmpur5hyyto.txt
+
+You can find these policies in ImageMagick's configuration file policy.xml.
+This file is usually located in /etc/ImageMagick-`X`/ or a similar location in the ImageMagick installation directory.
+Modify the entry containing `pattern="@"`, change `rights="none"` to `rights="read|write"` to allow read and write operations on files.
+
+### ❓OSError: [Errno 24] Too many open files
+
+This issue is caused by the system's limit on the number of open files. You can solve it by modifying the system's file open limit.
+
+Check the current limit:
+
+```shell
+ulimit -n
+```
+
+If it's too low, you can increase it, for example:
+
+```shell
+ulimit -n 10240
+```
+
+### ❓Whisper model download failed, with the following error
+
+LocalEntryNotfoundEror: Cannot find an appropriate cached snapshotfolderfor the specified revision on the local disk and
+outgoing trafic has been disabled.
+To enablerepo look-ups and downloads online, pass 'local files only=False' as input.
+
+or
+
+An error occured while synchronizing the model Systran/faster-whisper-large-v3 from the Hugging Face Hub:
+An error happened while trying to locate the files on the Hub and we cannot find the appropriate snapshot folder for the
+specified revision on the local disk. Please check your internet connection and try again.
+Trying to load the model directly from the local cache, if it exists.
+
+Solution: [Click to see how to manually download the model from netdisk](#subtitle-generation-)
+
 ## Feedback & Suggestions 📢
 
 - You can submit an [issue](https://github.com/harry0703/MoneyPrinterTurbo/issues) or
   a [pull request](https://github.com/harry0703/MoneyPrinterTurbo/pulls).
 
-## Reference Projects 📚
-
-This project is based on https://github.com/FujiwaraChoki/MoneyPrinter and has been refactored with a lot of
-optimizations and added functionalities. Thanks to the original author for their spirit of open source.
-
 ## License 📝
 
 Click to view the [`LICENSE`](LICENSE) file

README.md

@@ -58,10 +58,10 @@
 - [x] 支持 **字幕生成**，可以调整 `字体`、`位置`、`颜色`、`大小`，同时支持`字幕描边`设置
 - [x] 支持 **背景音乐**，随机或者指定音乐文件，可设置`背景音乐音量`
 - [x] 视频素材来源 **高清**，而且 **无版权**，也可以使用自己的 **本地素材**
-- [x] 支持 **OpenAI**、**Moonshot**、**Azure**、**gpt4free**、**one-api**、**通义千问**、**Google Gemini**、**Ollama**、
-  **DeepSeek**、 **文心一言** 等多种模型接入
+- [x] 支持 **OpenAI**、**Moonshot**、**Azure**、**gpt4free**、**one-api**、**通义千问**、**Google Gemini**、**Ollama**、**DeepSeek**、 **文心一言**, **Pollinations**、**ModelScope** 等多种模型接入
     - 中国用户建议使用 **DeepSeek** 或 **Moonshot** 作为大模型提供商（国内可直接访问，不需要VPN。注册就送额度，基本够用）
 
+
 ### 后期计划 📅
 
 - [ ] GPT-SoVITS 配音支持
@@ -72,10 +72,6 @@
 - [ ] 支持更多的语音合成服务商，比如 OpenAI TTS
 - [ ] 自动上传到YouTube平台
 
-## 交流讨论 💬
-
-<img src="docs/wechat-group.jpg" width="250">
-
 ## 视频演示 📺
 
 ### 竖屏 9:16
@@ -116,25 +112,29 @@
 
 ## 配置要求 📦
 
-- 建议最低 CPU 4核或以上，内存 8G 或以上，显卡非必须
+- 建议最低 CPU **4核** 或以上，内存 **4G** 或以上，显卡非必须
 - Windows 10 或 MacOS 11.0 以上系统
 
+
 ## 快速开始 🚀
 
-下载一键启动包，解压直接使用（路径不要有 **中文** 和 **空格**）
+### 在 Google Colab 中运行
+免去本地环境配置，点击直接在 Google Colab 中快速体验 MoneyPrinterTurbo
 
-### Windows
+[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/harry0703/MoneyPrinterTurbo/blob/main/docs/MoneyPrinterTurbo.ipynb)
 
-- 百度网盘: https://pan.baidu.com/s/1MzBmcLTmVWohPEp9ohvvzA?pwd=pdcu 提取码: pdcu
+
+### Windows一键启动包
+
+下载一键启动包，解压直接使用（路径不要有 **中文**、**特殊字符**、**空格**）
+
+- 百度网盘（v1.2.6）: https://pan.baidu.com/s/1wg0UaIyXpO3SqIpaq790SQ?pwd=sbqx 提取码: sbqx
+- Google Drive (v1.2.6): https://drive.google.com/file/d/1HsbzfT7XunkrCrHw5ncUjFX8XX4zAuUh/view?usp=sharing
 
 下载后，建议先**双击执行** `update.bat` 更新到**最新代码**，然后双击 `start.bat` 启动
 
 启动后，会自动打开浏览器（如果打开是空白，建议换成 **Chrome** 或者 **Edge** 打开）
 
-### 其他系统
-
-还没有制作一键启动包，看下面的 **安装部署** 部分，建议使用 **docker** 部署，更加方便。
-
 ## 安装部署 📥
 
 ### 前提条件
@@ -148,7 +148,7 @@
 git clone https://github.com/harry0703/MoneyPrinterTurbo.git
 ```
 
-#### ② 修改配置文件
+#### ② 修改配置文件（可选，建议启动后也可以在 WebUI 里面配置）
 
 - 将 `config.example.toml` 文件复制一份，命名为 `config.toml`
 - 按照 `config.toml` 文件中的说明，配置好 `pexels_api_keys` 和 `llm_provider`，并根据 llm_provider 对应的服务商，配置相关的
@@ -170,6 +170,8 @@ cd MoneyPrinterTurbo
 docker-compose up
 ```
 
+> 注意：最新版的docker安装时会自动以插件的形式安装docker compose，启动命令调整为docker compose up
+
 #### ② 访问Web界面
 
 打开浏览器，访问 http://0.0.0.0:8501
@@ -192,7 +194,7 @@ docker-compose up
 ```shell
 git clone https://github.com/harry0703/MoneyPrinterTurbo.git
 cd MoneyPrinterTurbo
-conda create -n MoneyPrinterTurbo python=3.10
+conda create -n MoneyPrinterTurbo python=3.11
 conda activate MoneyPrinterTurbo
 pip install -r requirements.txt
 ```
@@ -225,14 +227,12 @@ pip install -r requirements.txt
 ###### Windows
 
 ```bat
-conda activate MoneyPrinterTurbo
 webui.bat
 ```
 
 ###### MacOS or Linux
 
 ```shell
-conda activate MoneyPrinterTurbo
 sh webui.sh
 ```
 
@@ -300,33 +300,6 @@ MoneyPrinterTurbo
 
 ## 常见问题 🤔
 
-### ❓如何使用免费的OpenAI GPT-3.5模型?
-
-[OpenAI宣布ChatGPT里面3.5已经免费了](https://openai.com/blog/start-using-chatgpt-instantly)，有开发者将其封装成了API，可以直接调用
-
-**确保你安装和启动了docker服务**，执行以下命令启动docker服务
-
-```shell
-docker run -p 3040:3040 missuo/freegpt35
-```
-
-启动成功后，修改 `config.toml` 中的配置
-
-- `llm_provider` 设置为 `openai`
-- `openai_api_key` 随便填写一个即可，比如 '123456'
-- `openai_base_url` 改为 `http://localhost:3040/v1/`
-- `openai_model_name` 改为 `gpt-3.5-turbo`
-
-> 注意：该方式稳定性较差
-
-### ❓AttributeError: 'str' object has no attribute 'choices'`
-
-这个问题是由于大模型没有返回正确的回复导致的。
-
-大概率是网络原因， 使用 **VPN**，或者设置 `openai_base_url` 为你的代理 ，应该就可以解决了。
-
-同时建议使用 **Moonshot** 或 **DeepSeek** 作为大模型提供商，这两个服务商在国内访问速度更快，更加稳定。
-
 ### ❓RuntimeError: No ffmpeg exe could be found
 
 通常情况下，ffmpeg 会被自动下载，并且会被自动检测到。
@@ -387,11 +360,6 @@ Trying to load the model directly from the local cache, if it exists.
 - 可以提交 [issue](https://github.com/harry0703/MoneyPrinterTurbo/issues)
   或者 [pull request](https://github.com/harry0703/MoneyPrinterTurbo/pulls)。
 
-## 参考项目 📚
-
-该项目基于 https://github.com/FujiwaraChoki/MoneyPrinter 重构而来，做了大量的优化，增加了更多的功能。
-感谢原作者的开源精神。
-
 ## 许可证 📝
 
 点击查看 [`LICENSE`](LICENSE) 文件

app/asgi.py

@@ -4,10 +4,10 @@ import os
 
 from fastapi import FastAPI, Request
 from fastapi.exceptions import RequestValidationError
-from fastapi.responses import JSONResponse
-from loguru import logger
-from fastapi.staticfiles import StaticFiles
 from fastapi.middleware.cors import CORSMiddleware
+from fastapi.responses import JSONResponse
+from fastapi.staticfiles import StaticFiles
+from loguru import logger
 
 from app.config import config
 from app.models.exception import HttpException

app/config/config.py

@@ -1,7 +1,8 @@
 import os
-import socket
-import toml
 import shutil
+import socket
+
+import toml
 from loguru import logger
 
 root_dir = os.path.dirname(os.path.dirname(os.path.dirname(os.path.realpath(__file__))))
@@ -17,7 +18,7 @@ def load_config():
         example_file = f"{root_dir}/config.example.toml"
         if os.path.isfile(example_file):
             shutil.copyfile(example_file, config_file)
-            logger.info(f"copy config.example.toml to config.toml")
+            logger.info("copy config.example.toml to config.toml")
 
     logger.info(f"load config from file: {config_file}")
 
@@ -35,6 +36,7 @@ def save_config():
     with open(config_file, "w", encoding="utf-8") as f:
         _cfg["app"] = app
         _cfg["azure"] = azure
+        _cfg["siliconflow"] = siliconflow
         _cfg["ui"] = ui
         f.write(toml.dumps(_cfg))
 
@@ -44,7 +46,13 @@ app = _cfg.get("app", {})
 whisper = _cfg.get("whisper", {})
 proxy = _cfg.get("proxy", {})
 azure = _cfg.get("azure", {})
-ui = _cfg.get("ui", {})
+siliconflow = _cfg.get("siliconflow", {})
+ui = _cfg.get(
+    "ui",
+    {
+        "hide_log": False,
+    },
+)
 
 hostname = socket.gethostname()
 
@@ -56,7 +64,7 @@ project_description = _cfg.get(
     "project_description",
     "<a href='https://github.com/harry0703/MoneyPrinterTurbo'>https://github.com/harry0703/MoneyPrinterTurbo</a>",
 )
-project_version = _cfg.get("project_version", "1.2.0")
+project_version = _cfg.get("project_version", "1.2.6")
 reload_debug = False
 
 imagemagick_path = app.get("imagemagick_path", "")

app/controllers/manager/base_manager.py

@@ -1,5 +1,5 @@
 import threading
-from typing import Callable, Any, Dict
+from typing import Any, Callable, Dict
 
 
 class TaskManager:
@@ -33,7 +33,7 @@ class TaskManager:
         try:
             with self.lock:
                 self.current_tasks += 1
-            func(*args, **kwargs)  # 在这里调用函数，传递*args和**kwargs
+            func(*args, **kwargs)  # call the function here, passing *args and **kwargs.
         finally:
             self.task_done()
 

app/controllers/ping.py

@@ -1,5 +1,4 @@
-from fastapi import APIRouter
-from fastapi import Request
+from fastapi import APIRouter, Request
 
 router = APIRouter()
 

app/controllers/v1/base.py

@@ -1,4 +1,4 @@
-from fastapi import APIRouter, Depends
+from fastapi import APIRouter
 
 
 def new_router(dependencies=None):

app/controllers/v1/llm.py

@@ -1,15 +1,16 @@
 from fastapi import Request
+
 from app.controllers.v1.base import new_router
 from app.models.schema import (
-    VideoScriptResponse,
     VideoScriptRequest,
-    VideoTermsResponse,
+    VideoScriptResponse,
     VideoTermsRequest,
+    VideoTermsResponse,
 )
 from app.services import llm
 from app.utils import utils
 
-# 认证依赖项
+# authentication dependency
 # router = new_router(dependencies=[Depends(base.verify_token)])
 router = new_router()
 

app/controllers/v1/video.py

@@ -25,6 +25,8 @@ from app.models.schema import (
     TaskQueryResponse,
     TaskResponse,
     TaskVideoRequest,
+    VideoMaterialUploadResponse,
+    VideoMaterialRetrieveResponse
 )
 from app.services import state as sm
 from app.services import task as tm
@@ -94,6 +96,22 @@ def create_task(
             task_id=task_id, status_code=400, message=f"{request_id}: {str(e)}"
         )
 
+from fastapi import Query
+
+@router.get("/tasks", response_model=TaskQueryResponse, summary="Get all tasks")
+def get_all_tasks(request: Request, page: int = Query(1, ge=1), page_size: int = Query(10, ge=1)):
+    request_id = base.get_task_id(request)
+    tasks, total = sm.state.get_all_tasks(page, page_size)
+
+    response = {
+        "tasks": tasks,
+        "total": total,
+        "page": page,
+        "page_size": page_size,
+    }
+    return utils.get_response(200, response)
+
+
 
 @router.get(
     "/tasks/{task_id}", response_model=TaskQueryResponse, summary="Query task status"
@@ -206,6 +224,51 @@ def upload_bgm_file(request: Request, file: UploadFile = File(...)):
         "", status_code=400, message=f"{request_id}: Only *.mp3 files can be uploaded"
     )
 
+@router.get(
+    "/video_materials", response_model=VideoMaterialRetrieveResponse, summary="Retrieve local video materials"
+)
+def get_video_materials_list(request: Request):
+    allowed_suffixes = ("mp4", "mov", "avi", "flv", "mkv", "jpg", "jpeg", "png")
+    local_videos_dir = utils.storage_dir("local_videos", create=True)
+    files = []
+    for suffix in allowed_suffixes:
+        files.extend(glob.glob(os.path.join(local_videos_dir, f"*.{suffix}")))
+    video_materials_list = []
+    for file in files:
+        video_materials_list.append(
+            {
+                "name": os.path.basename(file),
+                "size": os.path.getsize(file),
+                "file": file,
+            }
+        )
+    response = {"files": video_materials_list}
+    return utils.get_response(200, response)
+
+
+@router.post(
+    "/video_materials",
+    response_model=VideoMaterialUploadResponse,
+    summary="Upload the video material file to the local videos directory",
+)
+def upload_video_material_file(request: Request, file: UploadFile = File(...)):
+    request_id = base.get_task_id(request)
+    # check file ext
+    allowed_suffixes = ("mp4", "mov", "avi", "flv", "mkv", "jpg", "jpeg", "png")
+    if file.filename.endswith(allowed_suffixes):
+        local_videos_dir = utils.storage_dir("local_videos", create=True)
+        save_path = os.path.join(local_videos_dir, file.filename)
+        # save file
+        with open(save_path, "wb+") as buffer:
+            # If the file already exists, it will be overwritten
+            file.file.seek(0)
+            buffer.write(file.file.read())
+        response = {"file": save_path}
+        return utils.get_response(200, response)
+
+    raise HttpException(
+        "", status_code=400, message=f"{request_id}: Only files with extensions {', '.join(allowed_suffixes)} can be uploaded"
+    )
 
 @router.get("/stream/{file_path:path}")
 async def stream_video(request: Request, file_path: str):

app/models/exception.py

@@ -11,7 +11,7 @@ class HttpException(Exception):
         self.message = message
         self.status_code = status_code
         self.data = data
-        # 获取异常堆栈信息
+        # Retrieve the exception stack trace information.
         tb_str = traceback.format_exc().strip()
         if not tb_str or tb_str == "NoneType: None":
             msg = f"HttpException: {status_code}, {task_id}, {message}"

app/models/schema.py

@@ -1,6 +1,6 @@
 import warnings
 from enum import Enum
-from typing import Any, List, Optional
+from typing import Any, List, Optional, Union
 
 import pydantic
 from pydantic import BaseModel
@@ -18,6 +18,15 @@ class VideoConcatMode(str, Enum):
     sequential = "sequential"
 
 
+class VideoTransitionMode(str, Enum):
+    none = None
+    shuffle = "Shuffle"
+    fade_in = "FadeIn"
+    fade_out = "FadeOut"
+    slide_in = "SlideIn"
+    slide_out = "SlideOut"
+
+
 class VideoAspect(str, Enum):
     landscape = "16:9"
     portrait = "9:16"
@@ -44,44 +53,6 @@ class MaterialInfo:
     duration: int = 0
 
 
-# VoiceNames = [
-#     # zh-CN
-#     "female-zh-CN-XiaoxiaoNeural",
-#     "female-zh-CN-XiaoyiNeural",
-#     "female-zh-CN-liaoning-XiaobeiNeural",
-#     "female-zh-CN-shaanxi-XiaoniNeural",
-#
-#     "male-zh-CN-YunjianNeural",
-#     "male-zh-CN-YunxiNeural",
-#     "male-zh-CN-YunxiaNeural",
-#     "male-zh-CN-YunyangNeural",
-#
-#     # "female-zh-HK-HiuGaaiNeural",
-#     # "female-zh-HK-HiuMaanNeural",
-#     # "male-zh-HK-WanLungNeural",
-#     #
-#     # "female-zh-TW-HsiaoChenNeural",
-#     # "female-zh-TW-HsiaoYuNeural",
-#     # "male-zh-TW-YunJheNeural",
-#
-#     # en-US
-#     "female-en-US-AnaNeural",
-#     "female-en-US-AriaNeural",
-#     "female-en-US-AvaNeural",
-#     "female-en-US-EmmaNeural",
-#     "female-en-US-JennyNeural",
-#     "female-en-US-MichelleNeural",
-#
-#     "male-en-US-AndrewNeural",
-#     "male-en-US-BrianNeural",
-#     "male-en-US-ChristopherNeural",
-#     "male-en-US-EricNeural",
-#     "male-en-US-GuyNeural",
-#     "male-en-US-RogerNeural",
-#     "male-en-US-SteffanNeural",
-# ]
-
-
 class VideoParams(BaseModel):
     """
     {
@@ -98,16 +69,20 @@ class VideoParams(BaseModel):
     """
 
     video_subject: str
-    video_script: str = ""  # 用于生成视频的脚本
-    video_terms: Optional[str | list] = None  # 用于生成视频的关键词
+    video_script: str = ""  # Script used to generate the video
+    video_terms: Optional[str | list] = None  # Keywords used to generate the video
     video_aspect: Optional[VideoAspect] = VideoAspect.portrait.value
     video_concat_mode: Optional[VideoConcatMode] = VideoConcatMode.random.value
+    video_transition_mode: Optional[VideoTransitionMode] = None
     video_clip_duration: Optional[int] = 5
     video_count: Optional[int] = 1
 
     video_source: Optional[str] = "pexels"
-    video_materials: Optional[List[MaterialInfo]] = None  # 用于生成视频的素材
-
+    video_materials: Optional[List[MaterialInfo]] = (
+        None  # Materials used to generate the video
+    )
+    
+    custom_audio_file: Optional[str] = None  # Custom audio file path, will ignore video_script and disable subtitle
     video_language: Optional[str] = ""  # auto detect
 
     voice_name: Optional[str] = ""
@@ -122,7 +97,7 @@ class VideoParams(BaseModel):
     custom_position: float = 70.0
     font_name: Optional[str] = "STHeitiMedium.ttc"
     text_fore_color: Optional[str] = "#FFFFFF"
-    text_background_color: Optional[str] = "transparent"
+    text_background_color: Union[bool, str] = True
 
     font_size: int = 60
     stroke_color: Optional[str] = "#000000"
@@ -143,7 +118,7 @@ class SubtitleRequest(BaseModel):
     subtitle_position: Optional[str] = "bottom"
     font_name: Optional[str] = "STHeitiMedium.ttc"
     text_fore_color: Optional[str] = "#FFFFFF"
-    text_background_color: Optional[str] = "transparent"
+    text_background_color: Union[bool, str] = True
     font_size: int = 60
     stroke_color: Optional[str] = "#000000"
     stroke_width: float = 1.5
@@ -327,3 +302,33 @@ class BgmUploadResponse(BaseResponse):
                 "data": {"file": "/MoneyPrinterTurbo/resource/songs/example.mp3"},
             },
         }
+
+class VideoMaterialRetrieveResponse(BaseResponse):
+    class Config:
+        json_schema_extra = {
+            "example": {
+                "status": 200,
+                "message": "success",
+                "data": {
+                    "files": [
+                        {
+                            "name": "example.mp4",
+                            "size": 12345678,
+                            "file": "/MoneyPrinterTurbo/resource/videos/example.mp4",
+                        }
+                    ]
+                },
+            },
+        }
+
+class VideoMaterialUploadResponse(BaseResponse):
+    class Config:
+        json_schema_extra = {
+            "example": {
+                "status": 200,
+                "message": "success",
+                "data": {
+                    "file": "/MoneyPrinterTurbo/resource/videos/example.mp4",
+                },
+            },
+        }

app/services/llm.py

@@ -1,10 +1,12 @@
+import json
 import logging
 import re
-import json
+import requests
 from typing import List
+
+import g4f
 from loguru import logger
-from openai import OpenAI
-from openai import AzureOpenAI
+from openai import AzureOpenAI, OpenAI
 from openai.types.chat import ChatCompletion
 
 from app.config import config
@@ -13,243 +15,317 @@ _max_retries = 5
 
 
 def _generate_response(prompt: str) -> str:
-    content = ""
-    llm_provider = config.app.get("llm_provider", "openai")
-    logger.info(f"llm provider: {llm_provider}")
-    if llm_provider == "g4f":
-        model_name = config.app.get("g4f_model_name", "")
-        if not model_name:
-            model_name = "gpt-3.5-turbo-16k-0613"
-        import g4f
-
-        content = g4f.ChatCompletion.create(
-            model=model_name,
-            messages=[{"role": "user", "content": prompt}],
-        )
-    else:
-        api_version = ""  # for azure
-        if llm_provider == "moonshot":
-            api_key = config.app.get("moonshot_api_key")
-            model_name = config.app.get("moonshot_model_name")
-            base_url = "https://api.moonshot.cn/v1"
-        elif llm_provider == "ollama":
-            # api_key = config.app.get("openai_api_key")
-            api_key = "ollama"  # any string works but you are required to have one
-            model_name = config.app.get("ollama_model_name")
-            base_url = config.app.get("ollama_base_url", "")
-            if not base_url:
-                base_url = "http://localhost:11434/v1"
-        elif llm_provider == "openai":
-            api_key = config.app.get("openai_api_key")
-            model_name = config.app.get("openai_model_name")
-            base_url = config.app.get("openai_base_url", "")
-            if not base_url:
-                base_url = "https://api.openai.com/v1"
-        elif llm_provider == "oneapi":
-            api_key = config.app.get("oneapi_api_key")
-            model_name = config.app.get("oneapi_model_name")
-            base_url = config.app.get("oneapi_base_url", "")
-        elif llm_provider == "azure":
-            api_key = config.app.get("azure_api_key")
-            model_name = config.app.get("azure_model_name")
-            base_url = config.app.get("azure_base_url", "")
-            api_version = config.app.get("azure_api_version", "2024-02-15-preview")
-        elif llm_provider == "gemini":
-            api_key = config.app.get("gemini_api_key")
-            model_name = config.app.get("gemini_model_name")
-            base_url = "***"
-        elif llm_provider == "qwen":
-            api_key = config.app.get("qwen_api_key")
-            model_name = config.app.get("qwen_model_name")
-            base_url = "***"
-        elif llm_provider == "cloudflare":
-            api_key = config.app.get("cloudflare_api_key")
-            model_name = config.app.get("cloudflare_model_name")
-            account_id = config.app.get("cloudflare_account_id")
-            base_url = "***"
-        elif llm_provider == "deepseek":
-            api_key = config.app.get("deepseek_api_key")
-            model_name = config.app.get("deepseek_model_name")
-            base_url = config.app.get("deepseek_base_url")
-            if not base_url:
-                base_url = "https://api.deepseek.com"
-        elif llm_provider == "ernie":
-            api_key = config.app.get("ernie_api_key")
-            secret_key = config.app.get("ernie_secret_key")
-            base_url = config.app.get("ernie_base_url")
-            model_name = "***"
-            if not secret_key:
-                raise ValueError(
-                    f"{llm_provider}: secret_key is not set, please set it in the config.toml file."
-                )
+    try:
+        content = ""
+        llm_provider = config.app.get("llm_provider", "openai")
+        logger.info(f"llm provider: {llm_provider}")
+        if llm_provider == "g4f":
+            model_name = config.app.get("g4f_model_name", "")
+            if not model_name:
+                model_name = "gpt-3.5-turbo-16k-0613"
+            content = g4f.ChatCompletion.create(
+                model=model_name,
+                messages=[{"role": "user", "content": prompt}],
+            )
         else:
-            raise ValueError(
-                "llm_provider is not set, please set it in the config.toml file."
-            )
+            api_version = ""  # for azure
+            if llm_provider == "moonshot":
+                api_key = config.app.get("moonshot_api_key")
+                model_name = config.app.get("moonshot_model_name")
+                base_url = "https://api.moonshot.cn/v1"
+            elif llm_provider == "ollama":
+                # api_key = config.app.get("openai_api_key")
+                api_key = "ollama"  # any string works but you are required to have one
+                model_name = config.app.get("ollama_model_name")
+                base_url = config.app.get("ollama_base_url", "")
+                if not base_url:
+                    base_url = "http://localhost:11434/v1"
+            elif llm_provider == "openai":
+                api_key = config.app.get("openai_api_key")
+                model_name = config.app.get("openai_model_name")
+                base_url = config.app.get("openai_base_url", "")
+                if not base_url:
+                    base_url = "https://api.openai.com/v1"
+            elif llm_provider == "oneapi":
+                api_key = config.app.get("oneapi_api_key")
+                model_name = config.app.get("oneapi_model_name")
+                base_url = config.app.get("oneapi_base_url", "")
+            elif llm_provider == "azure":
+                api_key = config.app.get("azure_api_key")
+                model_name = config.app.get("azure_model_name")
+                base_url = config.app.get("azure_base_url", "")
+                api_version = config.app.get("azure_api_version", "2024-02-15-preview")
+            elif llm_provider == "gemini":
+                api_key = config.app.get("gemini_api_key")
+                model_name = config.app.get("gemini_model_name")
+                base_url = config.app.get("gemini_base_url", "")
+            elif llm_provider == "qwen":
+                api_key = config.app.get("qwen_api_key")
+                model_name = config.app.get("qwen_model_name")
+                base_url = "***"
+            elif llm_provider == "cloudflare":
+                api_key = config.app.get("cloudflare_api_key")
+                model_name = config.app.get("cloudflare_model_name")
+                account_id = config.app.get("cloudflare_account_id")
+                base_url = "***"
+            elif llm_provider == "deepseek":
+                api_key = config.app.get("deepseek_api_key")
+                model_name = config.app.get("deepseek_model_name")
+                base_url = config.app.get("deepseek_base_url")
+                if not base_url:
+                    base_url = "https://api.deepseek.com"
+            elif llm_provider == "modelscope":
+                api_key = config.app.get("modelscope_api_key")
+                model_name = config.app.get("modelscope_model_name")
+                base_url = config.app.get("modelscope_base_url")
+                if not base_url:
+                    base_url = "https://api-inference.modelscope.cn/v1/"
+            elif llm_provider == "ernie":
+                api_key = config.app.get("ernie_api_key")
+                secret_key = config.app.get("ernie_secret_key")
+                base_url = config.app.get("ernie_base_url")
+                model_name = "***"
+                if not secret_key:
+                    raise ValueError(
+                        f"{llm_provider}: secret_key is not set, please set it in the config.toml file."
+                    )
+            elif llm_provider == "pollinations":
+                try:
+                    base_url = config.app.get("pollinations_base_url", "")
+                    if not base_url:
+                        base_url = "https://text.pollinations.ai/openai"
+                    model_name = config.app.get("pollinations_model_name", "openai-fast")
+                   
+                    # Prepare the payload
+                    payload = {
+                        "model": model_name,
+                        "messages": [
+                            {"role": "user", "content": prompt}
+                        ],
+                        "seed": 101  # Optional but helps with reproducibility
+                    }
+                    
+                    # Optional parameters if configured
+                    if config.app.get("pollinations_private"):
+                        payload["private"] = True
+                    if config.app.get("pollinations_referrer"):
+                        payload["referrer"] = config.app.get("pollinations_referrer")
+                    
+                    headers = {
+                        "Content-Type": "application/json"
+                    }
+                    
+                    # Make the API request
+                    response = requests.post(base_url, headers=headers, json=payload)
+                    response.raise_for_status()
+                    result = response.json()
+                    
+                    if result and "choices" in result and len(result["choices"]) > 0:
+                        content = result["choices"][0]["message"]["content"]
+                        return content.replace("\n", "")
+                    else:
+                        raise Exception(f"[{llm_provider}] returned an invalid response format")
+                        
+                except requests.exceptions.RequestException as e:
+                    raise Exception(f"[{llm_provider}] request failed: {str(e)}")
+                except Exception as e:
+                    raise Exception(f"[{llm_provider}] error: {str(e)}")
 
-        if not api_key:
-            raise ValueError(
-                f"{llm_provider}: api_key is not set, please set it in the config.toml file."
-            )
-        if not model_name:
-            raise ValueError(
-                f"{llm_provider}: model_name is not set, please set it in the config.toml file."
-            )
-        if not base_url:
-            raise ValueError(
-                f"{llm_provider}: base_url is not set, please set it in the config.toml file."
-            )
+            if llm_provider not in ["pollinations", "ollama"]:  # Skip validation for providers that don't require API key
+                if not api_key:
+                    raise ValueError(
+                        f"{llm_provider}: api_key is not set, please set it in the config.toml file."
+                    )
+                if not model_name:
+                    raise ValueError(
+                        f"{llm_provider}: model_name is not set, please set it in the config.toml file."
+                    )
+                if not base_url:
+                    raise ValueError(
+                        f"{llm_provider}: base_url is not set, please set it in the config.toml file."
+                    )
 
-        if llm_provider == "qwen":
-            import dashscope
-            from dashscope.api_entities.dashscope_response import GenerationResponse
+            if llm_provider == "qwen":
+                import dashscope
+                from dashscope.api_entities.dashscope_response import GenerationResponse
 
-            dashscope.api_key = api_key
-            response = dashscope.Generation.call(
+                dashscope.api_key = api_key
+                response = dashscope.Generation.call(
+                    model=model_name, messages=[{"role": "user", "content": prompt}]
+                )
+                if response:
+                    if isinstance(response, GenerationResponse):
+                        status_code = response.status_code
+                        if status_code != 200:
+                            raise Exception(
+                                f'[{llm_provider}] returned an error response: "{response}"'
+                            )
+
+                        content = response["output"]["text"]
+                        return content.replace("\n", "")
+                    else:
+                        raise Exception(
+                            f'[{llm_provider}] returned an invalid response: "{response}"'
+                        )
+                else:
+                    raise Exception(f"[{llm_provider}] returned an empty response")
+
+            if llm_provider == "gemini":
+                import google.generativeai as genai
+
+                if not base_url:
+                    genai.configure(api_key=api_key, transport="rest")
+                else:
+                    genai.configure(api_key=api_key, transport="rest", client_options={'api_endpoint': base_url})
+
+                generation_config = {
+                    "temperature": 0.5,
+                    "top_p": 1,
+                    "top_k": 1,
+                    "max_output_tokens": 2048,
+                }
+
+                safety_settings = [
+                    {
+                        "category": "HARM_CATEGORY_HARASSMENT",
+                        "threshold": "BLOCK_ONLY_HIGH",
+                    },
+                    {
+                        "category": "HARM_CATEGORY_HATE_SPEECH",
+                        "threshold": "BLOCK_ONLY_HIGH",
+                    },
+                    {
+                        "category": "HARM_CATEGORY_SEXUALLY_EXPLICIT",
+                        "threshold": "BLOCK_ONLY_HIGH",
+                    },
+                    {
+                        "category": "HARM_CATEGORY_DANGEROUS_CONTENT",
+                        "threshold": "BLOCK_ONLY_HIGH",
+                    },
+                ]
+
+                model = genai.GenerativeModel(
+                    model_name=model_name,
+                    generation_config=generation_config,
+                    safety_settings=safety_settings,
+                )
+
+                try:
+                    response = model.generate_content(prompt)
+                    candidates = response.candidates
+                    generated_text = candidates[0].content.parts[0].text
+                except (AttributeError, IndexError) as e:
+                    print("Gemini Error:", e)
+
+                return generated_text
+
+            if llm_provider == "cloudflare":
+                response = requests.post(
+                    f"https://api.cloudflare.com/client/v4/accounts/{account_id}/ai/run/{model_name}",
+                    headers={"Authorization": f"Bearer {api_key}"},
+                    json={
+                        "messages": [
+                            {
+                                "role": "system",
+                                "content": "You are a friendly assistant",
+                            },
+                            {"role": "user", "content": prompt},
+                        ]
+                    },
+                )
+                result = response.json()
+                logger.info(result)
+                return result["result"]["response"]
+
+            if llm_provider == "ernie":
+                response = requests.post(
+                    "https://aip.baidubce.com/oauth/2.0/token", 
+                    params={
+                        "grant_type": "client_credentials",
+                        "client_id": api_key,
+                        "client_secret": secret_key,
+                    }
+                )
+                access_token = response.json().get("access_token")
+                url = f"{base_url}?access_token={access_token}"
+
+                payload = json.dumps(
+                    {
+                        "messages": [{"role": "user", "content": prompt}],
+                        "temperature": 0.5,
+                        "top_p": 0.8,
+                        "penalty_score": 1,
+                        "disable_search": False,
+                        "enable_citation": False,
+                        "response_format": "text",
+                    }
+                )
+                headers = {"Content-Type": "application/json"}
+
+                response = requests.request(
+                    "POST", url, headers=headers, data=payload
+                ).json()
+                return response.get("result")
+
+            if llm_provider == "azure":
+                client = AzureOpenAI(
+                    api_key=api_key,
+                    api_version=api_version,
+                    azure_endpoint=base_url,
+                )
+
+            if llm_provider == "modelscope":
+                content = ''
+                client = OpenAI(
+                    api_key=api_key,
+                    base_url=base_url,
+                )
+                response = client.chat.completions.create(
+                    model=model_name,
+                    messages=[{"role": "user", "content": prompt}],
+                    extra_body={"enable_thinking": False},
+                    stream=True
+                )
+                if response:
+                    for chunk in response:
+                        if not chunk.choices:
+                            continue
+                        delta = chunk.choices[0].delta
+                        if delta and delta.content:
+                            content += delta.content
+                    
+                    if not content.strip():
+                        raise ValueError("Empty content in stream response")
+                    
+                    return content.replace("\n", "")
+                else:
+                    raise Exception(f"[{llm_provider}] returned an empty response")
+
+            else:
+                client = OpenAI(
+                    api_key=api_key,
+                    base_url=base_url,
+                )
+
+            response = client.chat.completions.create(
                 model=model_name, messages=[{"role": "user", "content": prompt}]
             )
             if response:
-                if isinstance(response, GenerationResponse):
-                    status_code = response.status_code
-                    if status_code != 200:
-                        raise Exception(
-                            f'[{llm_provider}] returned an error response: "{response}"'
-                        )
-
-                    content = response["output"]["text"]
-                    return content.replace("\n", "")
+                if isinstance(response, ChatCompletion):
+                    content = response.choices[0].message.content
                 else:
                     raise Exception(
-                        f'[{llm_provider}] returned an invalid response: "{response}"'
+                        f'[{llm_provider}] returned an invalid response: "{response}", please check your network '
+                        f"connection and try again."
                     )
-            else:
-                raise Exception(f"[{llm_provider}] returned an empty response")
-
-        if llm_provider == "gemini":
-            import google.generativeai as genai
-
-            genai.configure(api_key=api_key, transport="rest")
-
-            generation_config = {
-                "temperature": 0.5,
-                "top_p": 1,
-                "top_k": 1,
-                "max_output_tokens": 2048,
-            }
-
-            safety_settings = [
-                {
-                    "category": "HARM_CATEGORY_HARASSMENT",
-                    "threshold": "BLOCK_ONLY_HIGH",
-                },
-                {
-                    "category": "HARM_CATEGORY_HATE_SPEECH",
-                    "threshold": "BLOCK_ONLY_HIGH",
-                },
-                {
-                    "category": "HARM_CATEGORY_SEXUALLY_EXPLICIT",
-                    "threshold": "BLOCK_ONLY_HIGH",
-                },
-                {
-                    "category": "HARM_CATEGORY_DANGEROUS_CONTENT",
-                    "threshold": "BLOCK_ONLY_HIGH",
-                },
-            ]
-
-            model = genai.GenerativeModel(
-                model_name=model_name,
-                generation_config=generation_config,
-                safety_settings=safety_settings,
-            )
-
-            try:
-                response = model.generate_content(prompt)
-                candidates = response.candidates
-                generated_text = candidates[0].content.parts[0].text
-            except (AttributeError, IndexError) as e:
-                print("Gemini Error:", e)
-
-            return generated_text
-
-        if llm_provider == "cloudflare":
-            import requests
-
-            response = requests.post(
-                f"https://api.cloudflare.com/client/v4/accounts/{account_id}/ai/run/{model_name}",
-                headers={"Authorization": f"Bearer {api_key}"},
-                json={
-                    "messages": [
-                        {"role": "system", "content": "You are a friendly assistant"},
-                        {"role": "user", "content": prompt},
-                    ]
-                },
-            )
-            result = response.json()
-            logger.info(result)
-            return result["result"]["response"]
-
-        if llm_provider == "ernie":
-            import requests
-
-            params = {
-                "grant_type": "client_credentials",
-                "client_id": api_key,
-                "client_secret": secret_key,
-            }
-            access_token = (
-                requests.post("https://aip.baidubce.com/oauth/2.0/token", params=params)
-                .json()
-                .get("access_token")
-            )
-            url = f"{base_url}?access_token={access_token}"
-
-            payload = json.dumps(
-                {
-                    "messages": [{"role": "user", "content": prompt}],
-                    "temperature": 0.5,
-                    "top_p": 0.8,
-                    "penalty_score": 1,
-                    "disable_search": False,
-                    "enable_citation": False,
-                    "response_format": "text",
-                }
-            )
-            headers = {"Content-Type": "application/json"}
-
-            response = requests.request(
-                "POST", url, headers=headers, data=payload
-            ).json()
-            return response.get("result")
-
-        if llm_provider == "azure":
-            client = AzureOpenAI(
-                api_key=api_key,
-                api_version=api_version,
-                azure_endpoint=base_url,
-            )
-        else:
-            client = OpenAI(
-                api_key=api_key,
-                base_url=base_url,
-            )
-
-        response = client.chat.completions.create(
-            model=model_name, messages=[{"role": "user", "content": prompt}]
-        )
-        if response:
-            if isinstance(response, ChatCompletion):
-                content = response.choices[0].message.content
             else:
                 raise Exception(
-                    f'[{llm_provider}] returned an invalid response: "{response}", please check your network '
-                    f"connection and try again."
+                    f"[{llm_provider}] returned an empty response, please check your network connection and try again."
                 )
-        else:
-            raise Exception(
-                f"[{llm_provider}] returned an empty response, please check your network connection and try again."
-            )
 
-    return content.replace("\n", "")
+        return content.replace("\n", "")
+    except Exception as e:
+        return f"Error: {str(e)}"
 
 
 def generate_script(
@@ -295,7 +371,7 @@ Generate a script for a video, depending on the subject of the video.
         paragraphs = response.split("\n\n")
 
         # Select the specified number of paragraphs
-        selected_paragraphs = paragraphs[:paragraph_number]
+        # selected_paragraphs = paragraphs[:paragraph_number]
 
         # Join the selected paragraphs into a single string
         return "\n\n".join(paragraphs)
@@ -319,8 +395,10 @@ Generate a script for a video, depending on the subject of the video.
 
         if i < _max_retries:
             logger.warning(f"failed to generate video script, trying again... {i + 1}")
-
-    logger.success(f"completed: \n{final_script}")
+    if "Error: " in final_script:
+        logger.error(f"failed to generate video script: {final_script}")
+    else:
+        logger.success(f"completed: \n{final_script}")
     return final_script.strip()
 
 
@@ -358,6 +436,9 @@ Please note that you must use English for generating video search terms; Chinese
     for i in range(_max_retries):
         try:
             response = _generate_response(prompt)
+            if "Error: " in response:
+                logger.error(f"failed to generate video script: {response}")
+                return response
             search_terms = json.loads(response)
             if not isinstance(search_terms, list) or not all(
                 isinstance(term, str) for term in search_terms
@@ -397,3 +478,4 @@ if __name__ == "__main__":
     )
     print("######################")
     print(search_terms)
+    

app/services/material.py

@@ -1,14 +1,14 @@
 import os
 import random
+from typing import List
 from urllib.parse import urlencode
 
 import requests
-from typing import List
 from loguru import logger
 from moviepy.video.io.VideoFileClip import VideoFileClip
 
 from app.config import config
-from app.models.schema import VideoAspect, VideoConcatMode, MaterialInfo
+from app.models.schema import MaterialInfo, VideoAspect, VideoConcatMode
 from app.utils import utils
 
 requested_count = 0
@@ -40,7 +40,10 @@ def search_videos_pexels(
     video_orientation = aspect.name
     video_width, video_height = aspect.to_resolution()
     api_key = get_api_key("pexels_api_keys")
-    headers = {"Authorization": api_key}
+    headers = {
+        "Authorization": api_key,
+        "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/115.0.0.0 Safari/537.36",
+    }
     # Build URL
     params = {"query": search_term, "per_page": 20, "orientation": video_orientation}
     query_url = f"https://api.pexels.com/videos/search?{urlencode(params)}"
@@ -126,7 +129,7 @@ def search_videos_pixabay(
             for video_type in video_files:
                 video = video_files[video_type]
                 w = int(video["width"])
-                h = int(video["height"])
+                # h = int(video["height"])
                 if w >= video_width:
                     item = MaterialInfo()
                     item.provider = "pixabay"
@@ -158,11 +161,19 @@ def save_video(video_url: str, save_dir: str = "") -> str:
         logger.info(f"video already exists: {video_path}")
         return video_path
 
+    headers = {
+        "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/115.0.0.0 Safari/537.36"
+    }
+
     # if video does not exist, download it
     with open(video_path, "wb") as f:
         f.write(
             requests.get(
-                video_url, proxies=config.proxy, verify=False, timeout=(60, 240)
+                video_url,
+                headers=headers,
+                proxies=config.proxy,
+                verify=False,
+                timeout=(60, 240),
             ).content
         )
 
@@ -177,7 +188,7 @@ def save_video(video_url: str, save_dir: str = "") -> str:
         except Exception as e:
             try:
                 os.remove(video_path)
-            except Exception as e:
+            except Exception:
                 pass
             logger.warning(f"invalid video file: {video_path} => {str(e)}")
     return ""

app/services/state.py

@@ -1,5 +1,6 @@
 import ast
 from abc import ABC, abstractmethod
+
 from app.config import config
 from app.models import const
 
@@ -14,12 +15,23 @@ class BaseState(ABC):
     def get_task(self, task_id: str):
         pass
 
+    @abstractmethod
+    def get_all_tasks(self, page: int, page_size: int):
+        pass
+
 
 # Memory state management
 class MemoryState(BaseState):
     def __init__(self):
         self._tasks = {}
 
+    def get_all_tasks(self, page: int, page_size: int):
+        start = (page - 1) * page_size
+        end = start + page_size
+        tasks = list(self._tasks.values())
+        total = len(tasks)
+        return tasks[start:end], total
+
     def update_task(
         self,
         task_id: str,
@@ -32,6 +44,7 @@ class MemoryState(BaseState):
             progress = 100
 
         self._tasks[task_id] = {
+            "task_id": task_id,
             "state": state,
             "progress": progress,
             **kwargs,
@@ -52,6 +65,28 @@ class RedisState(BaseState):
 
         self._redis = redis.StrictRedis(host=host, port=port, db=db, password=password)
 
+    def get_all_tasks(self, page: int, page_size: int):
+        start = (page - 1) * page_size
+        end = start + page_size
+        tasks = []
+        cursor = 0
+        total = 0
+        while True:
+            cursor, keys = self._redis.scan(cursor, count=page_size)
+            total += len(keys)
+            if total > start:
+                for key in keys[max(0, start - total):end - total]:
+                    task_data = self._redis.hgetall(key)
+                    task = {
+                        k.decode("utf-8"): self._convert_to_original_type(v) for k, v in task_data.items()
+                    }
+                    tasks.append(task)
+                    if len(tasks) >= page_size:
+                        break
+            if cursor == 0 or len(tasks) >= page_size:
+                break
+        return tasks, total
+
     def update_task(
         self,
         task_id: str,
@@ -64,6 +99,7 @@ class RedisState(BaseState):
             progress = 100
 
         fields = {
+            "task_id": task_id,
             "state": state,
             "progress": progress,
             **kwargs,

app/services/subtitle.py

@@ -1,9 +1,12 @@
 import json
 import os.path
 import re
-
-from faster_whisper import WhisperModel
 from timeit import default_timer as timer
+
+try:
+    from faster_whisper import WhisperModel
+except ImportError:
+    WhisperModel = None
 from loguru import logger
 
 from app.config import config
@@ -17,6 +20,9 @@ model = None
 
 def create(audio_file, subtitle_file: str = ""):
     global model
+    if WhisperModel is None:
+        logger.warning("faster_whisper not available, skipping whisper subtitle generation")
+        return ""
     if not model:
         model_path = f"{utils.root_dir()}/models/whisper-{model_size}"
         model_bin_file = f"{model_path}/model.bin"
@@ -88,7 +94,7 @@ def create(audio_file, subtitle_file: str = ""):
                     is_segmented = True
 
                 seg_end = word.end
-                # 如果包含标点,则断句
+                # If it contains punctuation, then break the sentence.
                 seg_text += word.word
 
                 if utils.str_contains_punctuation(word.word):
@@ -246,7 +252,7 @@ def correct(subtitle_file, video_script):
             script_index += 1
             subtitle_index = next_subtitle_index
 
-    # 处理剩余的脚本行
+    # Process the remaining lines of the script.
     while script_index < len(script_lines):
         logger.warning(f"Extra script line: {script_lines[script_index]}")
         if subtitle_index < len(subtitle_items):

app/services/task.py

@@ -71,34 +71,70 @@ def save_script_data(task_id, video_script, video_terms, params):
 
 
 def generate_audio(task_id, params, video_script):
+    '''
+    Generate audio for the video script.
+    If a custom audio file is provided, it will be used directly.
+    There will be no subtitle maker object returned in this case.
+    Otherwise, TTS will be used to generate the audio.
+    Returns:
+        - audio_file: path to the generated or provided audio file
+        - audio_duration: duration of the audio in seconds
+        - sub_maker: subtitle maker object if TTS is used, None otherwise
+    '''
     logger.info("\n\n## generating audio")
-    audio_file = path.join(utils.task_dir(task_id), "audio.mp3")
-    sub_maker = voice.tts(
-        text=video_script,
-        voice_name=voice.parse_voice_name(params.voice_name),
-        voice_rate=params.voice_rate,
-        voice_file=audio_file,
-    )
-    if sub_maker is None:
-        sm.state.update_task(task_id, state=const.TASK_STATE_FAILED)
-        logger.error(
-            """failed to generate audio:
+    custom_audio_file = params.custom_audio_file
+    if not custom_audio_file or not os.path.exists(custom_audio_file):
+        if custom_audio_file:
+            logger.warning(
+                f"custom audio file not found: {custom_audio_file}, using TTS to generate audio."
+            )
+        else:
+            logger.info("no custom audio file provided, using TTS to generate audio.")
+        audio_file = path.join(utils.task_dir(task_id), "audio.mp3")
+        sub_maker = voice.tts(
+            text=video_script,
+            voice_name=voice.parse_voice_name(params.voice_name),
+            voice_rate=params.voice_rate,
+            voice_file=audio_file,
+        )
+        if sub_maker is None:
+            sm.state.update_task(task_id, state=const.TASK_STATE_FAILED)
+            logger.error(
+                """failed to generate audio:
 1. check if the language of the voice matches the language of the video script.
 2. check if the network is available. If you are in China, it is recommended to use a VPN and enable the global traffic mode.
-        """.strip()
-        )
-        return None, None
-
-    audio_duration = math.ceil(voice.get_audio_duration(sub_maker))
-    return audio_file, audio_duration
-
+            """.strip()
+            )
+            return None, None, None
+        audio_duration = math.ceil(voice.get_audio_duration(sub_maker))
+        if audio_duration == 0:
+            sm.state.update_task(task_id, state=const.TASK_STATE_FAILED)
+            logger.error("failed to get audio duration.")
+            return None, None, None
+        return audio_file, audio_duration, sub_maker
+    else:
+        logger.info(f"using custom audio file: {custom_audio_file}")
+        audio_duration = voice.get_audio_duration(custom_audio_file)
+        if audio_duration == 0:
+            sm.state.update_task(task_id, state=const.TASK_STATE_FAILED)
+            logger.error("failed to get audio duration from custom audio file.")
+            return None, None, None
+        return custom_audio_file, audio_duration, None
 
 def generate_subtitle(task_id, params, video_script, sub_maker, audio_file):
-    if not params.subtitle_enabled:
+    '''
+    Generate subtitle for the video script.
+    If subtitle generation is disabled or no subtitle maker is provided, it will return an empty string.
+    Otherwise, it will generate the subtitle using the specified provider.
+    Returns:
+        - subtitle_path: path to the generated subtitle file
+    '''
+    logger.info("\n\n## generating subtitle")
+    if not params.subtitle_enabled or sub_maker is None:
         return ""
 
     subtitle_path = path.join(utils.task_dir(task_id), "subtitle.srt")
-    subtitle_provider = config.app.get("subtitle_provider", "").strip().lower()
+    subtitle_provider = config.app.get("subtitle_provider", "edge").strip().lower()
     logger.info(f"\n\n## generating subtitle, provider: {subtitle_provider}")
 
     subtitle_fallback = False
@@ -164,6 +200,7 @@ def generate_final_videos(
     video_concat_mode = (
         params.video_concat_mode if params.video_count == 1 else VideoConcatMode.random
     )
+    video_transition_mode = params.video_transition_mode
 
     _progress = 50
     for i in range(params.video_count):
@@ -178,6 +215,7 @@ def generate_final_videos(
             audio_file=audio_file,
             video_aspect=params.video_aspect,
             video_concat_mode=video_concat_mode,
+            video_transition_mode=video_transition_mode,
             max_clip_duration=params.video_clip_duration,
             threads=params.n_threads,
         )
@@ -209,9 +247,12 @@ def start(task_id, params: VideoParams, stop_at: str = "video"):
     logger.info(f"start task: {task_id}, stop_at: {stop_at}")
     sm.state.update_task(task_id, state=const.TASK_STATE_PROCESSING, progress=5)
 
+    if type(params.video_concat_mode) is str:
+        params.video_concat_mode = VideoConcatMode(params.video_concat_mode)
+
     # 1. Generate script
     video_script = generate_script(task_id, params)
-    if not video_script:
+    if not video_script or "Error: " in video_script:
         sm.state.update_task(task_id, state=const.TASK_STATE_FAILED)
         return
 
@@ -242,7 +283,9 @@ def start(task_id, params: VideoParams, stop_at: str = "video"):
     sm.state.update_task(task_id, state=const.TASK_STATE_PROCESSING, progress=20)
 
     # 3. Generate audio
-    audio_file, audio_duration = generate_audio(task_id, params, video_script)
+    audio_file, audio_duration, sub_maker = generate_audio(
+        task_id, params, video_script
+    )
     if not audio_file:
         sm.state.update_task(task_id, state=const.TASK_STATE_FAILED)
         return
@@ -259,7 +302,9 @@ def start(task_id, params: VideoParams, stop_at: str = "video"):
         return {"audio_file": audio_file, "audio_duration": audio_duration}
 
     # 4. Generate subtitle
-    subtitle_path = generate_subtitle(task_id, params, video_script, None, audio_file)
+    subtitle_path = generate_subtitle(
+        task_id, params, video_script, sub_maker, audio_file
+    )
 
     if stop_at == "subtitle":
         sm.state.update_task(
@@ -318,3 +363,13 @@ def start(task_id, params: VideoParams, stop_at: str = "video"):
         task_id, state=const.TASK_STATE_COMPLETE, progress=100, **kwargs
     )
     return kwargs
+
+
+if __name__ == "__main__":
+    task_id = "task_id"
+    params = VideoParams(
+        video_subject="金钱的作用",
+        voice_name="zh-CN-XiaoyiNeural-Female",
+        voice_rate=1.0,
+    )
+    start(task_id, params, stop_at="video")

app/services/utils/video_effects.py

@@ -0,0 +1,21 @@
+from moviepy import Clip, vfx
+
+
+# FadeIn
+def fadein_transition(clip: Clip, t: float) -> Clip:
+    return clip.with_effects([vfx.FadeIn(t)])
+
+
+# FadeOut
+def fadeout_transition(clip: Clip, t: float) -> Clip:
+    return clip.with_effects([vfx.FadeOut(t)])
+
+
+# SlideIn
+def slidein_transition(clip: Clip, t: float, side: str) -> Clip:
+    return clip.with_effects([vfx.SlideIn(t, side)])
+
+
+# SlideOut
+def slideout_transition(clip: Clip, t: float, side: str) -> Clip:
+    return clip.with_effects([vfx.SlideOut(t, side)])

app/services/video.py

@@ -1,16 +1,102 @@
 import glob
+import itertools
+import os
 import random
+import gc
+import shutil
 from typing import List
-
 from loguru import logger
-from moviepy.editor import *
+from moviepy import (
+    AudioFileClip,
+    ColorClip,
+    CompositeAudioClip,
+    CompositeVideoClip,
+    ImageClip,
+    TextClip,
+    VideoFileClip,
+    afx,
+    concatenate_videoclips,
+)
 from moviepy.video.tools.subtitles import SubtitlesClip
 from PIL import ImageFont
 
 from app.models import const
-from app.models.schema import MaterialInfo, VideoAspect, VideoConcatMode, VideoParams
+from app.models.schema import (
+    MaterialInfo,
+    VideoAspect,
+    VideoConcatMode,
+    VideoParams,
+    VideoTransitionMode,
+)
+from app.services.utils import video_effects
 from app.utils import utils
 
+class SubClippedVideoClip:
+    def __init__(self, file_path, start_time=None, end_time=None, width=None, height=None, duration=None):
+        self.file_path = file_path
+        self.start_time = start_time
+        self.end_time = end_time
+        self.width = width
+        self.height = height
+        if duration is None:
+            self.duration = end_time - start_time
+        else:
+            self.duration = duration
+
+    def __str__(self):
+        return f"SubClippedVideoClip(file_path={self.file_path}, start_time={self.start_time}, end_time={self.end_time}, duration={self.duration}, width={self.width}, height={self.height})"
+
+
+audio_codec = "aac"
+video_codec = "libx264"
+fps = 30
+
+def close_clip(clip):
+    if clip is None:
+        return
+        
+    try:
+        # close main resources
+        if hasattr(clip, 'reader') and clip.reader is not None:
+            clip.reader.close()
+            
+        # close audio resources
+        if hasattr(clip, 'audio') and clip.audio is not None:
+            if hasattr(clip.audio, 'reader') and clip.audio.reader is not None:
+                clip.audio.reader.close()
+            del clip.audio
+            
+        # close mask resources
+        if hasattr(clip, 'mask') and clip.mask is not None:
+            if hasattr(clip.mask, 'reader') and clip.mask.reader is not None:
+                clip.mask.reader.close()
+            del clip.mask
+            
+        # handle child clips in composite clips
+        if hasattr(clip, 'clips') and clip.clips:
+            for child_clip in clip.clips:
+                if child_clip is not clip:  # avoid possible circular references
+                    close_clip(child_clip)
+            
+        # clear clip list
+        if hasattr(clip, 'clips'):
+            clip.clips = []
+            
+    except Exception as e:
+        logger.error(f"failed to close clip: {str(e)}")
+    
+    del clip
+    gc.collect()
+
+def delete_files(files: List[str] | str):
+    if isinstance(files, str):
+        files = [files]
+        
+    for file in files:
+        try:
+            os.remove(file)
+        except:
+            pass
 
 def get_bgm_file(bgm_type: str = "random", bgm_file: str = ""):
     if not bgm_type:
@@ -34,115 +120,194 @@ def combine_videos(
     audio_file: str,
     video_aspect: VideoAspect = VideoAspect.portrait,
     video_concat_mode: VideoConcatMode = VideoConcatMode.random,
+    video_transition_mode: VideoTransitionMode = None,
     max_clip_duration: int = 5,
     threads: int = 2,
 ) -> str:
     audio_clip = AudioFileClip(audio_file)
     audio_duration = audio_clip.duration
-    logger.info(f"max duration of audio: {audio_duration} seconds")
+    logger.info(f"audio duration: {audio_duration} seconds")
     # Required duration of each clip
     req_dur = audio_duration / len(video_paths)
     req_dur = max_clip_duration
-    logger.info(f"each clip will be maximum {req_dur} seconds long")
+    logger.info(f"maximum clip duration: {req_dur} seconds")
     output_dir = os.path.dirname(combined_video_path)
 
     aspect = VideoAspect(video_aspect)
     video_width, video_height = aspect.to_resolution()
 
-    clips = []
+    processed_clips = []
+    subclipped_items = []
     video_duration = 0
-
-    raw_clips = []
     for video_path in video_paths:
-        clip = VideoFileClip(video_path).without_audio()
+        clip = VideoFileClip(video_path)
         clip_duration = clip.duration
+        clip_w, clip_h = clip.size
+        close_clip(clip)
+        
         start_time = 0
 
         while start_time < clip_duration:
-            end_time = min(start_time + max_clip_duration, clip_duration)
-            split_clip = clip.subclip(start_time, end_time)
-            raw_clips.append(split_clip)
-            # logger.info(f"splitting from {start_time:.2f} to {end_time:.2f}, clip duration {clip_duration:.2f}, split_clip duration {split_clip.duration:.2f}")
-            start_time = end_time
+            end_time = min(start_time + max_clip_duration, clip_duration)            
+            if clip_duration - start_time >= max_clip_duration:
+                subclipped_items.append(SubClippedVideoClip(file_path= video_path, start_time=start_time, end_time=end_time, width=clip_w, height=clip_h))
+            start_time = end_time    
             if video_concat_mode.value == VideoConcatMode.sequential.value:
                 break
 
-    # random video_paths order
+    # random subclipped_items order
     if video_concat_mode.value == VideoConcatMode.random.value:
-        random.shuffle(raw_clips)
-
+        random.shuffle(subclipped_items)
+        
+    logger.debug(f"total subclipped items: {len(subclipped_items)}")
+    
     # Add downloaded clips over and over until the duration of the audio (max_duration) has been reached
-    while video_duration < audio_duration:
-        for clip in raw_clips:
-            # Check if clip is longer than the remaining audio
-            if (audio_duration - video_duration) < clip.duration:
-                clip = clip.subclip(0, (audio_duration - video_duration))
-            # Only shorten clips if the calculated clip length (req_dur) is shorter than the actual clip to prevent still image
-            elif req_dur < clip.duration:
-                clip = clip.subclip(0, req_dur)
-            clip = clip.set_fps(30)
-
+    for i, subclipped_item in enumerate(subclipped_items):
+        if video_duration > audio_duration:
+            break
+        
+        logger.debug(f"processing clip {i+1}: {subclipped_item.width}x{subclipped_item.height}, current duration: {video_duration:.2f}s, remaining: {audio_duration - video_duration:.2f}s")
+        
+        try:
+            clip = VideoFileClip(subclipped_item.file_path).subclipped(subclipped_item.start_time, subclipped_item.end_time)
+            clip_duration = clip.duration
             # Not all videos are same size, so we need to resize them
             clip_w, clip_h = clip.size
             if clip_w != video_width or clip_h != video_height:
                 clip_ratio = clip.w / clip.h
                 video_ratio = video_width / video_height
-
+                logger.debug(f"resizing clip, source: {clip_w}x{clip_h}, ratio: {clip_ratio:.2f}, target: {video_width}x{video_height}, ratio: {video_ratio:.2f}")
+                
                 if clip_ratio == video_ratio:
-                    # 等比例缩放
-                    clip = clip.resize((video_width, video_height))
+                    clip = clip.resized(new_size=(video_width, video_height))
                 else:
-                    # 等比缩放视频
                     if clip_ratio > video_ratio:
-                        # 按照目标宽度等比缩放
                         scale_factor = video_width / clip_w
                     else:
-                        # 按照目标高度等比缩放
                         scale_factor = video_height / clip_h
 
                     new_width = int(clip_w * scale_factor)
                     new_height = int(clip_h * scale_factor)
-                    clip_resized = clip.resize(newsize=(new_width, new_height))
 
-                    background = ColorClip(
-                        size=(video_width, video_height), color=(0, 0, 0)
-                    )
-                    clip = CompositeVideoClip(
-                        [
-                            background.set_duration(clip.duration),
-                            clip_resized.set_position("center"),
-                        ]
-                    )
-
-                logger.info(
-                    f"resizing video to {video_width} x {video_height}, clip size: {clip_w} x {clip_h}"
-                )
+                    background = ColorClip(size=(video_width, video_height), color=(0, 0, 0)).with_duration(clip_duration)
+                    clip_resized = clip.resized(new_size=(new_width, new_height)).with_position("center")
+                    clip = CompositeVideoClip([background, clip_resized])
+                    
+            shuffle_side = random.choice(["left", "right", "top", "bottom"])
+            if video_transition_mode.value == VideoTransitionMode.none.value:
+                clip = clip
+            elif video_transition_mode.value == VideoTransitionMode.fade_in.value:
+                clip = video_effects.fadein_transition(clip, 1)
+            elif video_transition_mode.value == VideoTransitionMode.fade_out.value:
+                clip = video_effects.fadeout_transition(clip, 1)
+            elif video_transition_mode.value == VideoTransitionMode.slide_in.value:
+                clip = video_effects.slidein_transition(clip, 1, shuffle_side)
+            elif video_transition_mode.value == VideoTransitionMode.slide_out.value:
+                clip = video_effects.slideout_transition(clip, 1, shuffle_side)
+            elif video_transition_mode.value == VideoTransitionMode.shuffle.value:
+                transition_funcs = [
+                    lambda c: video_effects.fadein_transition(c, 1),
+                    lambda c: video_effects.fadeout_transition(c, 1),
+                    lambda c: video_effects.slidein_transition(c, 1, shuffle_side),
+                    lambda c: video_effects.slideout_transition(c, 1, shuffle_side),
+                ]
+                shuffle_transition = random.choice(transition_funcs)
+                clip = shuffle_transition(clip)
 
             if clip.duration > max_clip_duration:
-                clip = clip.subclip(0, max_clip_duration)
-
-            clips.append(clip)
+                clip = clip.subclipped(0, max_clip_duration)
+                
+            # wirte clip to temp file
+            clip_file = f"{output_dir}/temp-clip-{i+1}.mp4"
+            clip.write_videofile(clip_file, logger=None, fps=fps, codec=video_codec)
+            
+            close_clip(clip)
+        
+            processed_clips.append(SubClippedVideoClip(file_path=clip_file, duration=clip.duration, width=clip_w, height=clip_h))
             video_duration += clip.duration
+            
+        except Exception as e:
+            logger.error(f"failed to process clip: {str(e)}")
+    
+    # loop processed clips until the video duration matches or exceeds the audio duration.
+    if video_duration < audio_duration:
+        logger.warning(f"video duration ({video_duration:.2f}s) is shorter than audio duration ({audio_duration:.2f}s), looping clips to match audio length.")
+        base_clips = processed_clips.copy()
+        for clip in itertools.cycle(base_clips):
+            if video_duration >= audio_duration:
+                break
+            processed_clips.append(clip)
+            video_duration += clip.duration
+        logger.info(f"video duration: {video_duration:.2f}s, audio duration: {audio_duration:.2f}s, looped {len(processed_clips)-len(base_clips)} clips")
+     
+    # merge video clips progressively, avoid loading all videos at once to avoid memory overflow
+    logger.info("starting clip merging process")
+    if not processed_clips:
+        logger.warning("no clips available for merging")
+        return combined_video_path
+    
+    # if there is only one clip, use it directly
+    if len(processed_clips) == 1:
+        logger.info("using single clip directly")
+        shutil.copy(processed_clips[0].file_path, combined_video_path)
+        delete_files(processed_clips)
+        logger.info("video combining completed")
+        return combined_video_path
+    
+    # create initial video file as base
+    base_clip_path = processed_clips[0].file_path
+    temp_merged_video = f"{output_dir}/temp-merged-video.mp4"
+    temp_merged_next = f"{output_dir}/temp-merged-next.mp4"
+    
+    # copy first clip as initial merged video
+    shutil.copy(base_clip_path, temp_merged_video)
+    
+    # merge remaining video clips one by one
+    for i, clip in enumerate(processed_clips[1:], 1):
+        logger.info(f"merging clip {i}/{len(processed_clips)-1}, duration: {clip.duration:.2f}s")
+        
+        try:
+            # load current base video and next clip to merge
+            base_clip = VideoFileClip(temp_merged_video)
+            next_clip = VideoFileClip(clip.file_path)
+            
+            # merge these two clips
+            merged_clip = concatenate_videoclips([base_clip, next_clip])
 
-    video_clip = concatenate_videoclips(clips)
-    video_clip = video_clip.set_fps(30)
-    logger.info("writing")
-    # https://github.com/harry0703/MoneyPrinterTurbo/issues/111#issuecomment-2032354030
-    video_clip.write_videofile(
-        filename=combined_video_path,
-        threads=threads,
-        logger=None,
-        temp_audiofile_path=output_dir,
-        audio_codec="aac",
-        fps=30,
-    )
-    video_clip.close()
-    logger.success("completed")
+            # save merged result to temp file
+            merged_clip.write_videofile(
+                filename=temp_merged_next,
+                threads=threads,
+                logger=None,
+                temp_audiofile_path=output_dir,
+                audio_codec=audio_codec,
+                fps=fps,
+            )
+            close_clip(base_clip)
+            close_clip(next_clip)
+            close_clip(merged_clip)
+            
+            # replace base file with new merged file
+            delete_files(temp_merged_video)
+            os.rename(temp_merged_next, temp_merged_video)
+            
+        except Exception as e:
+            logger.error(f"failed to merge clip: {str(e)}")
+            continue
+    
+    # after merging, rename final result to target file name
+    os.rename(temp_merged_video, combined_video_path)
+    
+    # clean temp files
+    clip_files = [clip.file_path for clip in processed_clips]
+    delete_files(clip_files)
+            
+    logger.info("video combining completed")
     return combined_video_path
 
 
 def wrap_text(text, max_width, font="Arial", fontsize=60):
-    # 创建字体对象
+    # Create ImageFont
     font = ImageFont.truetype(font, fontsize)
 
     def get_text_size(inner_text):
@@ -154,8 +319,6 @@ def wrap_text(text, max_width, font="Arial", fontsize=60):
     if width <= max_width:
         return text, height
 
-    # logger.warning(f"wrapping text, max_width: {max_width}, text_width: {width}, text: {text}")
-
     processed = True
 
     _wrapped_lines_ = []
@@ -178,7 +341,6 @@ def wrap_text(text, max_width, font="Arial", fontsize=60):
         _wrapped_lines_ = [line.strip() for line in _wrapped_lines_]
         result = "\n".join(_wrapped_lines_).strip()
         height = len(_wrapped_lines_) * height
-        # logger.warning(f"wrapped text: {result}")
         return result, height
 
     _wrapped_lines_ = []
@@ -195,7 +357,6 @@ def wrap_text(text, max_width, font="Arial", fontsize=60):
     _wrapped_lines_.append(_txt_)
     result = "\n".join(_wrapped_lines_).strip()
     height = len(_wrapped_lines_) * height
-    # logger.warning(f"wrapped text: {result}")
     return result, height
 
 
@@ -209,7 +370,7 @@ def generate_video(
     aspect = VideoAspect(params.video_aspect)
     video_width, video_height = aspect.to_resolution()
 
-    logger.info(f"start, video size: {video_width} x {video_height}")
+    logger.info(f"generating video: {video_width} x {video_height}")
     logger.info(f"  ① video: {video_path}")
     logger.info(f"  ② audio: {audio_path}")
     logger.info(f"  ③ subtitle: {subtitle_path}")
@@ -228,49 +389,68 @@ def generate_video(
         if os.name == "nt":
             font_path = font_path.replace("\\", "/")
 
-        logger.info(f"using font: {font_path}")
+        logger.info(f"  ⑤ font: {font_path}")
 
     def create_text_clip(subtitle_item):
+        params.font_size = int(params.font_size)
+        params.stroke_width = int(params.stroke_width)
         phrase = subtitle_item[1]
         max_width = video_width * 0.9
         wrapped_txt, txt_height = wrap_text(
             phrase, max_width=max_width, font=font_path, fontsize=params.font_size
         )
+        interline = int(params.font_size * 0.25)
+        size=(int(max_width), int(txt_height + params.font_size * 0.25 + (interline * (wrapped_txt.count("\n") + 1))))
+
         _clip = TextClip(
-            wrapped_txt,
+            text=wrapped_txt,
             font=font_path,
-            fontsize=params.font_size,
+            font_size=params.font_size,
             color=params.text_fore_color,
             bg_color=params.text_background_color,
             stroke_color=params.stroke_color,
             stroke_width=params.stroke_width,
-            print_cmd=False,
+            # interline=interline,
+            # size=size,
         )
         duration = subtitle_item[0][1] - subtitle_item[0][0]
-        _clip = _clip.set_start(subtitle_item[0][0])
-        _clip = _clip.set_end(subtitle_item[0][1])
-        _clip = _clip.set_duration(duration)
+        _clip = _clip.with_start(subtitle_item[0][0])
+        _clip = _clip.with_end(subtitle_item[0][1])
+        _clip = _clip.with_duration(duration)
         if params.subtitle_position == "bottom":
-            _clip = _clip.set_position(("center", video_height * 0.95 - _clip.h))
+            _clip = _clip.with_position(("center", video_height * 0.95 - _clip.h))
         elif params.subtitle_position == "top":
-            _clip = _clip.set_position(("center", video_height * 0.05))
+            _clip = _clip.with_position(("center", video_height * 0.05))
         elif params.subtitle_position == "custom":
-            # 确保字幕完全在屏幕内
-            margin = 10  # 额外的边距，单位为像素
+            # Ensure the subtitle is fully within the screen bounds
+            margin = 10  # Additional margin, in pixels
             max_y = video_height - _clip.h - margin
             min_y = margin
             custom_y = (video_height - _clip.h) * (params.custom_position / 100)
-            custom_y = max(min_y, min(custom_y, max_y))  # 限制 y 值在有效范围内
-            _clip = _clip.set_position(("center", custom_y))
+            custom_y = max(
+                min_y, min(custom_y, max_y)
+            )  # Constrain the y value within the valid range
+            _clip = _clip.with_position(("center", custom_y))
         else:  # center
-            _clip = _clip.set_position(("center", "center"))
+            _clip = _clip.with_position(("center", "center"))
         return _clip
 
-    video_clip = VideoFileClip(video_path)
-    audio_clip = AudioFileClip(audio_path).volumex(params.voice_volume)
+    video_clip = VideoFileClip(video_path).without_audio()
+    audio_clip = AudioFileClip(audio_path).with_effects(
+        [afx.MultiplyVolume(params.voice_volume)]
+    )
+
+    def make_textclip(text):
+        return TextClip(
+            text=text,
+            font=font_path,
+            font_size=params.font_size,
+        )
 
     if subtitle_path and os.path.exists(subtitle_path):
-        sub = SubtitlesClip(subtitles=subtitle_path, encoding="utf-8")
+        sub = SubtitlesClip(
+            subtitles=subtitle_path, encoding="utf-8", make_textclip=make_textclip
+        )
         text_clips = []
         for item in sub.subtitles:
             clip = create_text_clip(subtitle_item=item)
@@ -280,26 +460,28 @@ def generate_video(
     bgm_file = get_bgm_file(bgm_type=params.bgm_type, bgm_file=params.bgm_file)
     if bgm_file:
         try:
-            bgm_clip = (
-                AudioFileClip(bgm_file).volumex(params.bgm_volume).audio_fadeout(3)
+            bgm_clip = AudioFileClip(bgm_file).with_effects(
+                [
+                    afx.MultiplyVolume(params.bgm_volume),
+                    afx.AudioFadeOut(3),
+                    afx.AudioLoop(duration=video_clip.duration),
+                ]
             )
-            bgm_clip = afx.audio_loop(bgm_clip, duration=video_clip.duration)
             audio_clip = CompositeAudioClip([audio_clip, bgm_clip])
         except Exception as e:
             logger.error(f"failed to add bgm: {str(e)}")
 
-    video_clip = video_clip.set_audio(audio_clip)
+    video_clip = video_clip.with_audio(audio_clip)
     video_clip.write_videofile(
         output_file,
-        audio_codec="aac",
+        audio_codec=audio_codec,
         temp_audiofile_path=output_dir,
         threads=params.n_threads or 2,
         logger=None,
-        fps=30,
+        fps=fps,
     )
     video_clip.close()
     del video_clip
-    logger.success("completed")
 
 
 def preprocess_video(materials: List[MaterialInfo], clip_duration=4):
@@ -316,94 +498,34 @@ def preprocess_video(materials: List[MaterialInfo], clip_duration=4):
         width = clip.size[0]
         height = clip.size[1]
         if width < 480 or height < 480:
-            logger.warning(f"video is too small, width: {width}, height: {height}")
+            logger.warning(f"low resolution material: {width}x{height}, minimum 480x480 required")
             continue
 
         if ext in const.FILE_TYPE_IMAGES:
             logger.info(f"processing image: {material.url}")
-            # 创建一个图片剪辑，并设置持续时间为3秒钟
+            # Create an image clip and set its duration to 3 seconds
             clip = (
                 ImageClip(material.url)
-                .set_duration(clip_duration)
-                .set_position("center")
+                .with_duration(clip_duration)
+                .with_position("center")
             )
-            # 使用resize方法来添加缩放效果。这里使用了lambda函数来使得缩放效果随时间变化。
-            # 假设我们想要从原始大小逐渐放大到120%的大小。
-            # t代表当前时间，clip.duration为视频总时长，这里是3秒。
-            # 注意：1 表示100%的大小，所以1.2表示120%的大小
-            zoom_clip = clip.resize(
+            # Apply a zoom effect using the resize method.
+            # A lambda function is used to make the zoom effect dynamic over time.
+            # The zoom effect starts from the original size and gradually scales up to 120%.
+            # t represents the current time, and clip.duration is the total duration of the clip (3 seconds).
+            # Note: 1 represents 100% size, so 1.2 represents 120% size.
+            zoom_clip = clip.resized(
                 lambda t: 1 + (clip_duration * 0.03) * (t / clip.duration)
             )
 
-            # 如果需要，可以创建一个包含缩放剪辑的复合视频剪辑
-            # （这在您想要在视频中添加其他元素时非常有用）
+            # Optionally, create a composite video clip containing the zoomed clip.
+            # This is useful when you want to add other elements to the video.
             final_clip = CompositeVideoClip([zoom_clip])
 
-            # 输出视频
+            # Output the video to a file.
             video_file = f"{material.url}.mp4"
             final_clip.write_videofile(video_file, fps=30, logger=None)
-            final_clip.close()
-            del final_clip
+            close_clip(clip)
             material.url = video_file
-            logger.success(f"completed: {video_file}")
-    return materials
-
-
-if __name__ == "__main__":
-    m = MaterialInfo()
-    m.url = "/Users/harry/Downloads/IMG_2915.JPG"
-    m.provider = "local"
-    materials = preprocess_video([m], clip_duration=4)
-    print(materials)
-
-    # txt_en = "Here's your guide to travel hacks for budget-friendly adventures"
-    # txt_zh = "测试长字段这是您的旅行技巧指南帮助您进行预算友好的冒险"
-    # font = utils.resource_dir() + "/fonts/STHeitiMedium.ttc"
-    # for txt in [txt_en, txt_zh]:
-    #     t, h = wrap_text(text=txt, max_width=1000, font=font, fontsize=60)
-    #     print(t)
-    #
-    # task_id = "aa563149-a7ea-49c2-b39f-8c32cc225baf"
-    # task_dir = utils.task_dir(task_id)
-    # video_file = f"{task_dir}/combined-1.mp4"
-    # audio_file = f"{task_dir}/audio.mp3"
-    # subtitle_file = f"{task_dir}/subtitle.srt"
-    # output_file = f"{task_dir}/final.mp4"
-    #
-    # # video_paths = []
-    # # for file in os.listdir(utils.storage_dir("test")):
-    # #     if file.endswith(".mp4"):
-    # #         video_paths.append(os.path.join(utils.storage_dir("test"), file))
-    # #
-    # # combine_videos(combined_video_path=video_file,
-    # #                audio_file=audio_file,
-    # #                video_paths=video_paths,
-    # #                video_aspect=VideoAspect.portrait,
-    # #                video_concat_mode=VideoConcatMode.random,
-    # #                max_clip_duration=5,
-    # #                threads=2)
-    #
-    # cfg = VideoParams()
-    # cfg.video_aspect = VideoAspect.portrait
-    # cfg.font_name = "STHeitiMedium.ttc"
-    # cfg.font_size = 60
-    # cfg.stroke_color = "#000000"
-    # cfg.stroke_width = 1.5
-    # cfg.text_fore_color = "#FFFFFF"
-    # cfg.text_background_color = "transparent"
-    # cfg.bgm_type = "random"
-    # cfg.bgm_file = ""
-    # cfg.bgm_volume = 1.0
-    # cfg.subtitle_enabled = True
-    # cfg.subtitle_position = "bottom"
-    # cfg.n_threads = 2
-    # cfg.paragraph_number = 1
-    #
-    # cfg.voice_volume = 1.0
-    #
-    # generate_video(video_path=video_file,
-    #                audio_path=audio_file,
-    #                subtitle_path=subtitle_file,
-    #                output_file=output_file,
-    #                params=cfg
-    #                )
+            logger.success(f"image processed: {video_file}")
+    return materials

app/services/voice.py

@@ -2,21 +2,82 @@ import asyncio
 import os
 import re
 from datetime import datetime
+from typing import Union
 from xml.sax.saxutils import unescape
+
+import edge_tts
+import requests
+from edge_tts import SubMaker, submaker
 from edge_tts.submaker import mktimestamp
 from loguru import logger
-from edge_tts import submaker, SubMaker
-import edge_tts
 from moviepy.video.tools import subtitles
+from moviepy.audio.io.AudioFileClip import AudioFileClip
 
 from app.config import config
 from app.utils import utils
 
 
+def get_siliconflow_voices() -> list[str]:
+    """
+    获取硅基流动的声音列表
+
+    Returns:
+        声音列表，格式为 ["siliconflow:FunAudioLLM/CosyVoice2-0.5B:alex", ...]
+    """
+    # 硅基流动的声音列表和对应的性别（用于显示）
+    voices_with_gender = [
+        ("FunAudioLLM/CosyVoice2-0.5B", "alex", "Male"),
+        ("FunAudioLLM/CosyVoice2-0.5B", "anna", "Female"),
+        ("FunAudioLLM/CosyVoice2-0.5B", "bella", "Female"),
+        ("FunAudioLLM/CosyVoice2-0.5B", "benjamin", "Male"),
+        ("FunAudioLLM/CosyVoice2-0.5B", "charles", "Male"),
+        ("FunAudioLLM/CosyVoice2-0.5B", "claire", "Female"),
+        ("FunAudioLLM/CosyVoice2-0.5B", "david", "Male"),
+        ("FunAudioLLM/CosyVoice2-0.5B", "diana", "Female"),
+    ]
+
+    # 添加siliconflow:前缀，并格式化为显示名称
+    return [
+        f"siliconflow:{model}:{voice}-{gender}"
+        for model, voice, gender in voices_with_gender
+    ]
+
+
+def get_gemini_voices() -> list[str]:
+    """
+    获取Gemini TTS的声音列表
+    
+    Returns:
+        声音列表，格式为 ["gemini:Zephyr-Female", "gemini:Puck-Male", ...]
+    """
+    # Gemini TTS支持的语音列表
+    voices_with_gender = [
+        ("Zephyr", "Female"),
+        ("Puck", "Male"), 
+        ("Charon", "Male"),
+        ("Kore", "Female"),
+        ("Fenrir", "Male"),
+        ("Aoede", "Female"),
+        ("Thalia", "Female"),
+        ("Sage", "Male"),
+        ("Echo", "Female"),
+        ("Harmony", "Female"),
+        ("Lux", "Female"),
+        ("Nova", "Female"),
+        ("Vale", "Male"),
+        ("Orion", "Male"),
+        ("Atlas", "Male"),
+    ]
+    
+    # 添加gemini:前缀，并格式化为显示名称
+    return [
+        f"gemini:{voice}-{gender}"
+        for voice, gender in voices_with_gender
+    ]
+
+
 def get_all_azure_voices(filter_locals=None) -> list[str]:
-    if filter_locals is None:
-        filter_locals = ["zh-CN", "en-US", "zh-HK", "zh-TW", "vi-VN"]
-    voices_str = """
+    azure_voices_str = """
 Name: af-ZA-AdriNeural
 Gender: Female
 
@@ -302,21 +363,33 @@ Gender: Female
 Name: en-US-AnaNeural
 Gender: Female
 
+Name: en-US-AndrewMultilingualNeural
+Gender: Male
+
 Name: en-US-AndrewNeural
 Gender: Male
 
 Name: en-US-AriaNeural
 Gender: Female
 
+Name: en-US-AvaMultilingualNeural
+Gender: Female
+
 Name: en-US-AvaNeural
 Gender: Female
 
+Name: en-US-BrianMultilingualNeural
+Gender: Male
+
 Name: en-US-BrianNeural
 Gender: Male
 
 Name: en-US-ChristopherNeural
 Gender: Male
 
+Name: en-US-EmmaMultilingualNeural
+Gender: Female
+
 Name: en-US-EmmaNeural
 Gender: Female
 
@@ -602,12 +675,24 @@ Gender: Male
 Name: it-IT-ElsaNeural
 Gender: Female
 
-Name: it-IT-GiuseppeNeural
+Name: it-IT-GiuseppeMultilingualNeural
 Gender: Male
 
 Name: it-IT-IsabellaNeural
 Gender: Female
 
+Name: iu-Cans-CA-SiqiniqNeural
+Gender: Female
+
+Name: iu-Cans-CA-TaqqiqNeural
+Gender: Male
+
+Name: iu-Latn-CA-SiqiniqNeural
+Gender: Female
+
+Name: iu-Latn-CA-TaqqiqNeural
+Gender: Male
+
 Name: ja-JP-KeitaNeural
 Gender: Male
 
@@ -644,7 +729,7 @@ Gender: Male
 Name: kn-IN-SapnaNeural
 Gender: Female
 
-Name: ko-KR-HyunsuNeural
+Name: ko-KR-HyunsuMultilingualNeural
 Gender: Male
 
 Name: ko-KR-InJoonNeural
@@ -758,7 +843,7 @@ Gender: Male
 Name: pt-BR-FranciscaNeural
 Gender: Female
 
-Name: pt-BR-ThalitaNeural
+Name: pt-BR-ThalitaMultilingualNeural
 Gender: Female
 
 Name: pt-PT-DuarteNeural
@@ -988,27 +1073,20 @@ Name: zh-CN-XiaoxiaoMultilingualNeural-V2
 Gender: Female
     """.strip()
     voices = []
-    name = ""
-    for line in voices_str.split("\n"):
-        line = line.strip()
-        if not line:
-            continue
-        if line.startswith("Name: "):
-            name = line[6:].strip()
-        if line.startswith("Gender: "):
-            gender = line[8:].strip()
-            if name and gender:
-                # voices.append({
-                #     "name": name,
-                #     "gender": gender,
-                # })
-                if filter_locals:
-                    for filter_local in filter_locals:
-                        if name.lower().startswith(filter_local.lower()):
-                            voices.append(f"{name}-{gender}")
-                else:
-                    voices.append(f"{name}-{gender}")
-                name = ""
+    # 定义正则表达式模式，用于匹配 Name 和 Gender 行
+    pattern = re.compile(r"Name:\s*(.+)\s*Gender:\s*(.+)\s*", re.MULTILINE)
+    # 使用正则表达式查找所有匹配项
+    matches = pattern.findall(azure_voices_str)
+
+    for name, gender in matches:
+        # 应用过滤条件
+        if filter_locals and any(
+            name.lower().startswith(fl.lower()) for fl in filter_locals
+        ):
+            voices.append(f"{name}-{gender}")
+        elif not filter_locals:
+            voices.append(f"{name}-{gender}")
+
     voices.sort()
     return voices
 
@@ -1028,11 +1106,54 @@ def is_azure_v2_voice(voice_name: str):
     return ""
 
 
+def is_siliconflow_voice(voice_name: str):
+    """检查是否是硅基流动的声音"""
+    return voice_name.startswith("siliconflow:")
+
+
+def is_gemini_voice(voice_name: str):
+    """检查是否是Gemini TTS的声音"""
+    return voice_name.startswith("gemini:")
+
+
 def tts(
-    text: str, voice_name: str, voice_rate: float, voice_file: str
-) -> [SubMaker, None]:
+    text: str,
+    voice_name: str,
+    voice_rate: float,
+    voice_file: str,
+    voice_volume: float = 1.0,
+) -> Union[SubMaker, None]:
     if is_azure_v2_voice(voice_name):
         return azure_tts_v2(text, voice_name, voice_file)
+    elif is_siliconflow_voice(voice_name):
+        # 从voice_name中提取模型和声音
+        # 格式: siliconflow:model:voice-Gender
+        parts = voice_name.split(":")
+        if len(parts) >= 3:
+            model = parts[1]
+            # 移除性别后缀，例如 "alex-Male" -> "alex"
+            voice_with_gender = parts[2]
+            voice = voice_with_gender.split("-")[0]
+            # 构建完整的voice参数，格式为 "model:voice"
+            full_voice = f"{model}:{voice}"
+            return siliconflow_tts(
+                text, model, full_voice, voice_rate, voice_file, voice_volume
+            )
+        else:
+            logger.error(f"Invalid siliconflow voice name format: {voice_name}")
+            return None
+    elif is_gemini_voice(voice_name):
+        # 从voice_name中提取声音名称
+        # 格式: gemini:voice-Gender
+        parts = voice_name.split(":")
+        if len(parts) >= 2:
+            # 移除性别后缀，例如 "Zephyr-Female" -> "Zephyr"
+            voice_with_gender = parts[1]
+            voice = voice_with_gender.split("-")[0]
+            return gemini_tts(text, voice, voice_rate, voice_file, voice_volume)
+        else:
+            logger.error(f"Invalid gemini voice name format: {voice_name}")
+            return None
     return azure_tts_v1(text, voice_name, voice_rate, voice_file)
 
 
@@ -1048,7 +1169,7 @@ def convert_rate_to_percent(rate: float) -> str:
 
 def azure_tts_v1(
     text: str, voice_name: str, voice_rate: float, voice_file: str
-) -> [SubMaker, None]:
+) -> Union[SubMaker, None]:
     voice_name = parse_voice_name(voice_name)
     text = text.strip()
     rate_str = convert_rate_to_percent(voice_rate)
@@ -1071,7 +1192,7 @@ def azure_tts_v1(
 
             sub_maker = asyncio.run(_do())
             if not sub_maker or not sub_maker.subs:
-                logger.warning(f"failed, sub_maker is None or sub_maker.subs is None")
+                logger.warning("failed, sub_maker is None or sub_maker.subs is None")
                 continue
 
             logger.info(f"completed, output file: {voice_file}")
@@ -1081,7 +1202,145 @@ def azure_tts_v1(
     return None
 
 
-def azure_tts_v2(text: str, voice_name: str, voice_file: str) -> [SubMaker, None]:
+def siliconflow_tts(
+    text: str,
+    model: str,
+    voice: str,
+    voice_rate: float,
+    voice_file: str,
+    voice_volume: float = 1.0,
+) -> Union[SubMaker, None]:
+    """
+    使用硅基流动的API生成语音
+
+    Args:
+        text: 要转换为语音的文本
+        model: 模型名称，如 "FunAudioLLM/CosyVoice2-0.5B"
+        voice: 声音名称，如 "FunAudioLLM/CosyVoice2-0.5B:alex"
+        voice_rate: 语音速度，范围[0.25, 4.0]
+        voice_file: 输出的音频文件路径
+        voice_volume: 语音音量，范围[0.6, 5.0]，需要转换为硅基流动的增益范围[-10, 10]
+
+    Returns:
+        SubMaker对象或None
+    """
+    text = text.strip()
+    api_key = config.siliconflow.get("api_key", "")
+
+    if not api_key:
+        logger.error("SiliconFlow API key is not set")
+        return None
+
+    # 将voice_volume转换为硅基流动的增益范围
+    # 默认voice_volume为1.0，对应gain为0
+    gain = voice_volume - 1.0
+    # 确保gain在[-10, 10]范围内
+    gain = max(-10, min(10, gain))
+
+    url = "https://api.siliconflow.cn/v1/audio/speech"
+
+    payload = {
+        "model": model,
+        "input": text,
+        "voice": voice,
+        "response_format": "mp3",
+        "sample_rate": 32000,
+        "stream": False,
+        "speed": voice_rate,
+        "gain": gain,
+    }
+
+    headers = {"Authorization": f"Bearer {api_key}", "Content-Type": "application/json"}
+
+    for i in range(3):  # 尝试3次
+        try:
+            logger.info(
+                f"start siliconflow tts, model: {model}, voice: {voice}, try: {i + 1}"
+            )
+
+            response = requests.post(url, json=payload, headers=headers)
+
+            if response.status_code == 200:
+                # 保存音频文件
+                with open(voice_file, "wb") as f:
+                    f.write(response.content)
+
+                # 创建一个空的SubMaker对象
+                sub_maker = SubMaker()
+
+                # 获取音频文件的实际长度
+                try:
+                    # 尝试使用moviepy获取音频长度
+                    from moviepy import AudioFileClip
+
+                    audio_clip = AudioFileClip(voice_file)
+                    audio_duration = audio_clip.duration
+                    audio_clip.close()
+
+                    # 将音频长度转换为100纳秒单位（与edge_tts兼容）
+                    audio_duration_100ns = int(audio_duration * 10000000)
+
+                    # 使用文本分割来创建更准确的字幕
+                    # 将文本按标点符号分割成句子
+                    sentences = utils.split_string_by_punctuations(text)
+
+                    if sentences:
+                        # 计算每个句子的大致时长（按字符数比例分配）
+                        total_chars = sum(len(s) for s in sentences)
+                        char_duration = (
+                            audio_duration_100ns / total_chars if total_chars > 0 else 0
+                        )
+
+                        current_offset = 0
+                        for sentence in sentences:
+                            if not sentence.strip():
+                                continue
+
+                            # 计算当前句子的时长
+                            sentence_chars = len(sentence)
+                            sentence_duration = int(sentence_chars * char_duration)
+
+                            # 添加到SubMaker
+                            sub_maker.subs.append(sentence)
+                            sub_maker.offset.append(
+                                (current_offset, current_offset + sentence_duration)
+                            )
+
+                            # 更新偏移量
+                            current_offset += sentence_duration
+                    else:
+                        # 如果无法分割，则使用整个文本作为一个字幕
+                        sub_maker.subs = [text]
+                        sub_maker.offset = [(0, audio_duration_100ns)]
+
+                except Exception as e:
+                    logger.warning(f"Failed to create accurate subtitles: {str(e)}")
+                    # 回退到简单的字幕
+                    sub_maker.subs = [text]
+                    # 使用音频文件的实际长度，如果无法获取，则假设为10秒
+                    sub_maker.offset = [
+                        (
+                            0,
+                            audio_duration_100ns
+                            if "audio_duration_100ns" in locals()
+                            else 10000000,
+                        )
+                    ]
+
+                logger.success(f"siliconflow tts succeeded: {voice_file}")
+                print("s", sub_maker.subs, sub_maker.offset)
+                return sub_maker
+            else:
+                logger.error(
+                    f"siliconflow tts failed with status code {response.status_code}: {response.text}"
+                )
+        except Exception as e:
+            logger.error(f"siliconflow tts failed: {str(e)}")
+
+    return None
+
+
+def azure_tts_v2(text: str, voice_name: str, voice_file: str) -> Union[SubMaker, None]:
     voice_name = is_azure_v2_voice(voice_name)
     if not voice_name:
         logger.error(f"invalid voice name: {voice_name}")
@@ -1129,6 +1388,10 @@ def azure_tts_v2(text: str, voice_name: str, voice_file: str) -> [SubMaker, None
             # Creates an instance of a speech config with specified subscription key and service region.
             speech_key = config.azure.get("speech_key", "")
             service_region = config.azure.get("speech_region", "")
+            if not speech_key or not service_region:
+                logger.error("Azure speech key or region is not set")
+                return None
+
             audio_config = speechsdk.audio.AudioOutputConfig(
                 filename=voice_file, use_default_speaker=True
             )
@@ -1172,6 +1435,130 @@ def azure_tts_v2(text: str, voice_name: str, voice_file: str) -> [SubMaker, None
     return None
 
 
+def gemini_tts(
+    text: str,
+    voice_name: str,
+    voice_rate: float,
+    voice_file: str,
+    voice_volume: float = 1.0,
+) -> Union[SubMaker, None]:
+    """
+    使用Google Gemini TTS生成语音
+    
+    Args:
+        text: 要转换的文本
+        voice_name: 语音名称，如 "Zephyr", "Puck" 等
+        voice_rate: 语音速率（当前未使用）
+        voice_file: 输出音频文件路径
+        voice_volume: 音频音量（当前未使用）
+        
+    Returns:
+        SubMaker对象或None
+    """
+    import base64
+    import json
+    import io
+    from pydub import AudioSegment
+    import google.generativeai as genai
+    
+    try:
+        # 配置Gemini API
+        api_key = config.app.get("gemini_api_key", "")
+        if not api_key:
+            logger.error("Gemini API key is not set")
+            return None
+            
+        genai.configure(api_key=api_key)
+        
+        logger.info(f"start, voice name: {voice_name}, try: 1")
+        
+        # 使用Gemini TTS API
+        model = genai.GenerativeModel("gemini-2.5-flash-preview-tts")
+        
+        generation_config = {
+            "response_modalities": ["AUDIO"],
+            "speech_config": {
+                "voice_config": {
+                    "prebuilt_voice_config": {
+                        "voice_name": voice_name
+                    }
+                }
+            }
+        }
+        
+        response = model.generate_content(
+            contents=text,
+            generation_config=generation_config
+        )
+        
+        # 检查响应
+        if not response.candidates or not response.candidates[0].content:
+            logger.error("No audio content received from Gemini TTS")
+            return None
+            
+        # 获取音频数据
+        audio_data = None
+        for part in response.candidates[0].content.parts:
+            if hasattr(part, 'inline_data') and part.inline_data:
+                audio_data = part.inline_data.data
+                break
+                
+        if not audio_data:
+            logger.error("No audio data found in response")
+            return None
+            
+        # 音频数据已经是原始字节，不需要base64解码
+        if isinstance(audio_data, str):
+            # 如果是字符串，则需要base64解码
+            audio_bytes = base64.b64decode(audio_data)
+        else:
+            # 如果已经是字节，直接使用
+            audio_bytes = audio_data
+        
+        # 尝试不同的音频格式 - Gemini可能返回不同的格式
+        audio_segment = None
+        
+        # Gemini返回Linear PCM格式，按照文档参数解析
+        try:
+            audio_segment = AudioSegment.from_file(
+                io.BytesIO(audio_bytes), 
+                format="raw",
+                frame_rate=24000,  # Gemini TTS默认采样率
+                channels=1,        # 单声道
+                sample_width=2     # 16-bit
+            )
+        except Exception as e:
+            logger.error(f"Failed to load PCM audio: {e}")
+            return None
+        
+        # 导出为MP3格式
+        audio_segment.export(voice_file, format="mp3")
+        
+        logger.info(f"completed, output file: {voice_file}")
+        
+        # 创建SubMaker对象用于字幕
+        sub_maker = SubMaker()
+        audio_duration = len(audio_segment) / 1000.0  # 转换为秒
+        
+        # 将音频长度转换为100纳秒单位（与edge_tts兼容）
+        audio_duration_100ns = int(audio_duration * 10000000)
+        
+        # 使用create_sub方法正确创建字幕项
+        sub_maker.create_sub(
+            (0, audio_duration_100ns), 
+            text
+        )
+        
+        return sub_maker
+        
+    except ImportError as e:
+        logger.error(f"Missing required package for Gemini TTS: {str(e)}. Please install: pip install pydub")
+        return None
+    except Exception as e:
+        logger.error(f"Gemini TTS failed, error: {str(e)}")
+        return None
+
+
 def _format_text(text: str) -> str:
     # text = text.replace("\n", " ")
     text = text.replace("[", " ")
@@ -1202,7 +1589,7 @@ def create_subtitle(sub_maker: submaker.SubMaker, text: str, subtitle_file: str)
         """
         start_t = mktimestamp(start_time).replace(".", ",")
         end_t = mktimestamp(end_time).replace(".", ",")
-        return f"{idx}\n" f"{start_t} --> {end_t}\n" f"{sub_text}\n"
+        return f"{idx}\n{start_t} --> {end_t}\n{sub_text}\n"
 
     start_time = -1.0
     sub_items = []
@@ -1274,7 +1661,7 @@ def create_subtitle(sub_maker: submaker.SubMaker, text: str, subtitle_file: str)
         logger.error(f"failed, error: {str(e)}")
 
 
-def get_audio_duration(sub_maker: submaker.SubMaker):
+def _get_audio_duration_from_submaker(sub_maker: submaker.SubMaker):
     """
     获取音频时长
     """
@@ -1282,6 +1669,35 @@ def get_audio_duration(sub_maker: submaker.SubMaker):
         return 0.0
     return sub_maker.offset[-1][1] / 10000000
 
+def _get_audio_duration_from_mp3(mp3_file: str) -> float:
+    """
+    获取MP3音频时长
+    """
+    if not os.path.exists(mp3_file):
+        logger.error(f"MP3 file does not exist: {mp3_file}")
+        return 0.0
+
+    try:
+        # Use moviepy to get the duration of the MP3 file
+        with AudioFileClip(mp3_file) as audio:
+            return audio.duration  # Duration in seconds
+    except Exception as e:
+        logger.error(f"Failed to get audio duration from MP3: {str(e)}")
+        return 0.0
+
+def get_audio_duration( target: Union[str, submaker.SubMaker]) -> float:
+    """
+    获取音频时长
+    如果是SubMaker对象，则从SubMaker中获取时长
+    如果是MP3文件，则从MP3文件中获取时长
+    """
+    if isinstance(target, submaker.SubMaker):
+        return _get_audio_duration_from_submaker(target)
+    elif isinstance(target, str) and target.endswith(".mp3"):
+        return _get_audio_duration_from_mp3(target)
+    else:
+        logger.error(f"Invalid target type: {type(target)}")
+        return 0.0
 
 if __name__ == "__main__":
     voice_name = "zh-CN-XiaoxiaoMultilingualNeural-V2-Female"

app/utils/utils.py

@@ -1,12 +1,13 @@
+import json
 import locale
 import os
-import platform
+from pathlib import Path
 import threading
 from typing import Any
-from loguru import logger
-import json
 from uuid import uuid4
+
 import urllib3
+from loguru import logger
 
 from app.models import const
 
@@ -26,33 +27,33 @@ def get_response(status: int, data: Any = None, message: str = ""):
 
 def to_json(obj):
     try:
-        # 定义一个辅助函数来处理不同类型的对象
+        # Define a helper function to handle different types of objects
         def serialize(o):
-            # 如果对象是可序列化类型，直接返回
+            # If the object is a serializable type, return it directly
             if isinstance(o, (int, float, bool, str)) or o is None:
                 return o
-            # 如果对象是二进制数据，转换为base64编码的字符串
+            # If the object is binary data, convert it to a base64-encoded string
             elif isinstance(o, bytes):
                 return "*** binary data ***"
-            # 如果对象是字典，递归处理每个键值对
+            # If the object is a dictionary, recursively process each key-value pair
             elif isinstance(o, dict):
                 return {k: serialize(v) for k, v in o.items()}
-            # 如果对象是列表或元组，递归处理每个元素
+            # If the object is a list or tuple, recursively process each element
             elif isinstance(o, (list, tuple)):
                 return [serialize(item) for item in o]
-            # 如果对象是自定义类型，尝试返回其__dict__属性
+            # If the object is a custom type, attempt to return its __dict__ attribute
             elif hasattr(o, "__dict__"):
                 return serialize(o.__dict__)
-            # 其他情况返回None（或者可以选择抛出异常）
+            # Return None for other cases (or choose to raise an exception)
             else:
                 return None
 
-        # 使用serialize函数处理输入对象
+        # Use the serialize function to process the input object
         serialized_obj = serialize(obj)
 
-        # 序列化处理后的对象为JSON字符串
+        # Serialize the processed object into a JSON string
         return json.dumps(serialized_obj, ensure_ascii=False, indent=4)
-    except Exception as e:
+    except Exception:
         return None
 
 
@@ -94,7 +95,7 @@ def task_dir(sub_dir: str = ""):
 
 
 def font_dir(sub_dir: str = ""):
-    d = resource_dir(f"fonts")
+    d = resource_dir("fonts")
     if sub_dir:
         d = os.path.join(d, sub_dir)
     if not os.path.exists(d):
@@ -103,7 +104,7 @@ def font_dir(sub_dir: str = ""):
 
 
 def song_dir(sub_dir: str = ""):
-    d = resource_dir(f"songs")
+    d = resource_dir("songs")
     if sub_dir:
         d = os.path.join(d, sub_dir)
     if not os.path.exists(d):
@@ -112,7 +113,7 @@ def song_dir(sub_dir: str = ""):
 
 
 def public_dir(sub_dir: str = ""):
-    d = resource_dir(f"public")
+    d = resource_dir("public")
     if sub_dir:
         d = os.path.join(d, sub_dir)
     if not os.path.exists(d):
@@ -182,7 +183,7 @@ def split_string_by_punctuations(s):
             next_char = s[i + 1]
 
         if char == "." and previous_char.isdigit() and next_char.isdigit():
-            # 取现1万，按2.5%收取手续费, 2.5 中的 . 不能作为换行标记
+            # # In the case of "withdraw 10,000, charged at 2.5% fee", the dot in "2.5" should not be treated as a line break marker
             txt += char
             continue
 
@@ -210,7 +211,7 @@ def get_system_locale():
         # en_US, en_GB return en
         language_code = loc[0].split("_")[0]
         return language_code
-    except Exception as e:
+    except Exception:
         return "en"
 
 
@@ -226,4 +227,4 @@ def load_locales(i18n_dir):
 
 
 def parse_extension(filename):
-    return os.path.splitext(filename)[1].strip().lower().replace(".", "")
+    return Path(filename).suffix.lower().lstrip('.')

changelog.py

@@ -1,17 +0,0 @@
-from git_changelog.cli import build_and_render
-
-# 运行这段脚本自动生成CHANGELOG.md文件
-
-build_and_render(
-    repository=".",
-    output="CHANGELOG.md",
-    convention="angular",
-    provider="github",
-    template="keepachangelog",
-    parse_trailers=True,
-    parse_refs=False,
-    sections=["build", "deps", "feat", "fix", "refactor"],
-    versioning="pep440",
-    bump="1.1.2",  # 指定bump版本
-    in_place=True,
-)

config.example.toml

@@ -1,194 +1,223 @@
 [app]
+video_source = "pexels" # "pexels" or "pixabay"
 
-    video_source = "pexels"  # "pexels" or "pixabay"
-    # Pexels API Key
-    # Register at https://www.pexels.com/api/ to get your API key.
-    # You can use multiple keys to avoid rate limits.
-    # For example: pexels_api_keys = ["123adsf4567adf89","abd1321cd13efgfdfhi"]
-    # 特别注意格式，Key 用英文双引号括起来，多个Key用逗号隔开
-    pexels_api_keys = []
+# 是否隐藏配置面板
+hide_config = false
 
-    # Pixabay API Key
-    # Register at https://pixabay.com/api/docs/ to get your API key.
-    # You can use multiple keys to avoid rate limits.
-    # For example: pixabay_api_keys = ["123adsf4567adf89","abd1321cd13efgfdfhi"]
-    # 特别注意格式，Key 用英文双引号括起来，多个Key用逗号隔开
-    pixabay_api_keys = []
+# Pexels API Key
+# Register at https://www.pexels.com/api/ to get your API key.
+# You can use multiple keys to avoid rate limits.
+# For example: pexels_api_keys = ["123adsf4567adf89","abd1321cd13efgfdfhi"]
+# 特别注意格式，Key 用英文双引号括起来，多个Key用逗号隔开
+pexels_api_keys = []
 
-    # 如果你没有 OPENAI API Key，可以使用 g4f 代替，或者使用国内的 Moonshot API
-    # If you don't have an OPENAI API Key, you can use g4f instead
+# Pixabay API Key
+# Register at https://pixabay.com/api/docs/ to get your API key.
+# You can use multiple keys to avoid rate limits.
+# For example: pixabay_api_keys = ["123adsf4567adf89","abd1321cd13efgfdfhi"]
+# 特别注意格式，Key 用英文双引号括起来，多个Key用逗号隔开
+pixabay_api_keys = []
 
-    # 支持的提供商 (Supported providers):
-    #   openai
-    #   moonshot (月之暗面)
-    #   oneapi
-    #   g4f
-    #   azure
-    #   qwen (通义千问)
-    #   gemini
-    llm_provider="openai"
+# 支持的提供商 (Supported providers):
+#   openai
+#   moonshot    (月之暗面)
+#   azure
+#   qwen        (通义千问)
+#   deepseek
+#   gemini
+#   ollama
+#   g4f
+#   oneapi
+#   cloudflare
+#   ernie       (文心一言)
+#   modelscope  (魔搭社区)
+llm_provider = "openai"
 
-    ########## Ollama Settings
-    # No need to set it unless you want to use your own proxy
-    ollama_base_url = ""
-    # Check your available models at https://ollama.com/library
-    ollama_model_name = ""
+########## Pollinations AI Settings
+# Visit https://pollinations.ai/ to learn more
+# API Key is optional - leave empty for public access
+pollinations_api_key = ""
+# Default base URL for Pollinations API
+pollinations_base_url = "https://pollinations.ai/api/v1"
+# Default model for text generation
+pollinations_model_name = "openai-fast"
 
-    ########## OpenAI API Key
-    # Get your API key at https://platform.openai.com/api-keys
-    openai_api_key = ""
-    # No need to set it unless you want to use your own proxy
-    openai_base_url = ""
-    # Check your available models at https://platform.openai.com/account/limits
-    openai_model_name = "gpt-4-turbo"
+########## Ollama Settings
+# No need to set it unless you want to use your own proxy
+ollama_base_url = ""
+# Check your available models at https://ollama.com/library
+ollama_model_name = ""
 
-    ########## Moonshot API Key
-    # Visit https://platform.moonshot.cn/console/api-keys to get your API key.
-    moonshot_api_key=""
-    moonshot_base_url = "https://api.moonshot.cn/v1"
-    moonshot_model_name = "moonshot-v1-8k"
+########## OpenAI API Key
+# Get your API key at https://platform.openai.com/api-keys
+openai_api_key = ""
+# No need to set it unless you want to use your own proxy
+openai_base_url = ""
+# Check your available models at https://platform.openai.com/account/limits
+openai_model_name = "gpt-4o-mini"
 
-    ########## OneAPI API Key
-    # Visit https://github.com/songquanpeng/one-api to get your API key
-    oneapi_api_key=""
-    oneapi_base_url=""
-    oneapi_model_name=""
+########## Moonshot API Key
+# Visit https://platform.moonshot.cn/console/api-keys to get your API key.
+moonshot_api_key = ""
+moonshot_base_url = "https://api.moonshot.cn/v1"
+moonshot_model_name = "moonshot-v1-8k"
 
-    ########## G4F
-    # Visit https://github.com/xtekky/gpt4free to get more details
-    # Supported model list: https://github.com/xtekky/gpt4free/blob/main/g4f/models.py
-    g4f_model_name = "gpt-3.5-turbo"
+########## OneAPI API Key
+# Visit https://github.com/songquanpeng/one-api to get your API key
+oneapi_api_key = ""
+oneapi_base_url = ""
+oneapi_model_name = ""
 
-    ########## Azure API Key
-    # Visit https://learn.microsoft.com/zh-cn/azure/ai-services/openai/ to get more details
-    # API documentation: https://learn.microsoft.com/zh-cn/azure/ai-services/openai/reference
-    azure_api_key = ""
-    azure_base_url=""
-    azure_model_name="gpt-35-turbo" # replace with your model deployment name
-    azure_api_version = "2024-02-15-preview"
+########## G4F
+# Visit https://github.com/xtekky/gpt4free to get more details
+# Supported model list: https://github.com/xtekky/gpt4free/blob/main/g4f/models.py
+g4f_model_name = "gpt-3.5-turbo"
 
-    ########## Gemini API Key
-    gemini_api_key=""
-    gemini_model_name = "gemini-1.0-pro"
+########## Azure API Key
+# Visit https://learn.microsoft.com/zh-cn/azure/ai-services/openai/ to get more details
+# API documentation: https://learn.microsoft.com/zh-cn/azure/ai-services/openai/reference
+azure_api_key = ""
+azure_base_url = ""
+azure_model_name = "gpt-35-turbo"        # replace with your model deployment name
+azure_api_version = "2024-02-15-preview"
 
-    ########## Qwen API Key
-    # Visit https://dashscope.console.aliyun.com/apiKey to get your API key
-    # Visit below links to get more details
-    # https://tongyi.aliyun.com/qianwen/
-    # https://help.aliyun.com/zh/dashscope/developer-reference/model-introduction
-    qwen_api_key = ""
-    qwen_model_name = "qwen-max"
+########## Gemini API Key
+gemini_api_key = ""
+gemini_model_name = "gemini-1.0-pro"
+
+########## Qwen API Key
+# Visit https://dashscope.console.aliyun.com/apiKey to get your API key
+# Visit below links to get more details
+# https://tongyi.aliyun.com/qianwen/
+# https://help.aliyun.com/zh/dashscope/developer-reference/model-introduction
+qwen_api_key = ""
+qwen_model_name = "qwen-max"
 
 
-    ########## DeepSeek API Key
-    # Visit https://platform.deepseek.com/api_keys to get your API key
-    deepseek_api_key = ""
-    deepseek_base_url = "https://api.deepseek.com"
-    deepseek_model_name = "deepseek-chat"
-
-    # Subtitle Provider, "edge" or "whisper"
-    # If empty, the subtitle will not be generated
-    subtitle_provider = "edge"
-
-    #
-    # ImageMagick
-    #
-    # Once you have installed it, ImageMagick will be automatically detected, except on Windows!
-    # On Windows, for example "C:\Program Files (x86)\ImageMagick-7.1.1-Q16-HDRI\magick.exe"
-    # Download from https://imagemagick.org/archive/binaries/ImageMagick-7.1.1-29-Q16-x64-static.exe
-
-    # imagemagick_path = "C:\\Program Files (x86)\\ImageMagick-7.1.1-Q16\\magick.exe"
+########## DeepSeek API Key
+# Visit https://platform.deepseek.com/api_keys to get your API key
+deepseek_api_key = ""
+deepseek_base_url = "https://api.deepseek.com"
+deepseek_model_name = "deepseek-chat"
 
 
-    #
-    # FFMPEG
-    #
-    # 通常情况下，ffmpeg 会被自动下载，并且会被自动检测到。
-    # 但是如果你的环境有问题，无法自动下载，可能会遇到如下错误：
-    #   RuntimeError: No ffmpeg exe could be found.
-    #   Install ffmpeg on your system, or set the IMAGEIO_FFMPEG_EXE environment variable.
-    # 此时你可以手动下载 ffmpeg 并设置 ffmpeg_path，下载地址：https://www.gyan.dev/ffmpeg/builds/
+########## ModelScope API Key
+# Visit https://modelscope.cn/docs/model-service/API-Inference/intro to get your API key
+# And note that you need to bind your Alibaba Cloud account before using the API.
+modelscope_api_key = ""
+modelscope_base_url = "https://api-inference.modelscope.cn/v1/"
+modelscope_model_name = "Qwen/Qwen3-32B"
 
-    # Under normal circumstances, ffmpeg is downloaded automatically and detected automatically.
-    # However, if there is an issue with your environment that prevents automatic downloading, you might encounter the following error:
-    #   RuntimeError: No ffmpeg exe could be found.
-    #   Install ffmpeg on your system, or set the IMAGEIO_FFMPEG_EXE environment variable.
-    # In such cases, you can manually download ffmpeg and set the ffmpeg_path, download link: https://www.gyan.dev/ffmpeg/builds/
+# Subtitle Provider, "edge" or "whisper"
+# If empty, the subtitle will not be generated
+subtitle_provider = "edge"
 
-    # ffmpeg_path = "C:\\Users\\harry\\Downloads\\ffmpeg.exe"
-    #########################################################################################
+#
+# ImageMagick
+#
+# Once you have installed it, ImageMagick will be automatically detected, except on Windows!
+# On Windows, for example "C:\Program Files (x86)\ImageMagick-7.1.1-Q16-HDRI\magick.exe"
+# Download from https://imagemagick.org/archive/binaries/ImageMagick-7.1.1-29-Q16-x64-static.exe
 
-    # 当视频生成成功后，API服务提供的视频下载接入点，默认为当前服务的地址和监听端口
-    # 比如 http://127.0.0.1:8080/tasks/6357f542-a4e1-46a1-b4c9-bf3bd0df5285/final-1.mp4
-    # 如果你需要使用域名对外提供服务（一般会用nginx做代理），则可以设置为你的域名
-    # 比如 https://xxxx.com/tasks/6357f542-a4e1-46a1-b4c9-bf3bd0df5285/final-1.mp4
-    # endpoint="https://xxxx.com"
-
-    # When the video is successfully generated, the API service provides a download endpoint for the video, defaulting to the service's current address and listening port.
-    # For example, http://127.0.0.1:8080/tasks/6357f542-a4e1-46a1-b4c9-bf3bd0df5285/final-1.mp4
-    # If you need to provide the service externally using a domain name (usually done with nginx as a proxy), you can set it to your domain name.
-    # For example, https://xxxx.com/tasks/6357f542-a4e1-46a1-b4c9-bf3bd0df5285/final-1.mp4
-    # endpoint="https://xxxx.com"
-    endpoint=""
+# imagemagick_path = "C:\\Program Files (x86)\\ImageMagick-7.1.1-Q16\\magick.exe"
 
 
-    # Video material storage location
-    # material_directory = ""                    # Indicates that video materials will be downloaded to the default folder, the default folder is ./storage/cache_videos under the current project
-    # material_directory = "/user/harry/videos"  # Indicates that video materials will be downloaded to a specified folder
-    # material_directory = "task"                # Indicates that video materials will be downloaded to the current task's folder, this method does not allow sharing of already downloaded video materials
+#
+# FFMPEG
+#
+# 通常情况下，ffmpeg 会被自动下载，并且会被自动检测到。
+# 但是如果你的环境有问题，无法自动下载，可能会遇到如下错误：
+#   RuntimeError: No ffmpeg exe could be found.
+#   Install ffmpeg on your system, or set the IMAGEIO_FFMPEG_EXE environment variable.
+# 此时你可以手动下载 ffmpeg 并设置 ffmpeg_path，下载地址：https://www.gyan.dev/ffmpeg/builds/
 
-    # 视频素材存放位置
-    # material_directory = ""                    #表示将视频素材下载到默认的文件夹，默认文件夹为当前项目下的 ./storage/cache_videos
-    # material_directory = "/user/harry/videos"  #表示将视频素材下载到指定的文件夹中
-    # material_directory = "task"                #表示将视频素材下载到当前任务的文件夹中，这种方式无法共享已经下载的视频素材
+# Under normal circumstances, ffmpeg is downloaded automatically and detected automatically.
+# However, if there is an issue with your environment that prevents automatic downloading, you might encounter the following error:
+#   RuntimeError: No ffmpeg exe could be found.
+#   Install ffmpeg on your system, or set the IMAGEIO_FFMPEG_EXE environment variable.
+# In such cases, you can manually download ffmpeg and set the ffmpeg_path, download link: https://www.gyan.dev/ffmpeg/builds/
 
-    material_directory = ""
+# ffmpeg_path = "C:\\Users\\harry\\Downloads\\ffmpeg.exe"
+#########################################################################################
 
-    # Used for state management of the task
-    enable_redis = false
-    redis_host = "localhost"
-    redis_port = 6379
-    redis_db = 0
-    redis_password = ""
+# 当视频生成成功后，API服务提供的视频下载接入点，默认为当前服务的地址和监听端口
+# 比如 http://127.0.0.1:8080/tasks/6357f542-a4e1-46a1-b4c9-bf3bd0df5285/final-1.mp4
+# 如果你需要使用域名对外提供服务（一般会用nginx做代理），则可以设置为你的域名
+# 比如 https://xxxx.com/tasks/6357f542-a4e1-46a1-b4c9-bf3bd0df5285/final-1.mp4
+# endpoint="https://xxxx.com"
 
-    # 文生视频时的最大并发任务数
-    max_concurrent_tasks = 5
+# When the video is successfully generated, the API service provides a download endpoint for the video, defaulting to the service's current address and listening port.
+# For example, http://127.0.0.1:8080/tasks/6357f542-a4e1-46a1-b4c9-bf3bd0df5285/final-1.mp4
+# If you need to provide the service externally using a domain name (usually done with nginx as a proxy), you can set it to your domain name.
+# For example, https://xxxx.com/tasks/6357f542-a4e1-46a1-b4c9-bf3bd0df5285/final-1.mp4
+# endpoint="https://xxxx.com"
+endpoint = ""
 
-    # webui界面是否显示配置项
-    # webui hide baisc config panel
-    hide_config = false
+
+# Video material storage location
+# material_directory = ""                    # Indicates that video materials will be downloaded to the default folder, the default folder is ./storage/cache_videos under the current project
+# material_directory = "/user/harry/videos"  # Indicates that video materials will be downloaded to a specified folder
+# material_directory = "task"                # Indicates that video materials will be downloaded to the current task's folder, this method does not allow sharing of already downloaded video materials
+
+# 视频素材存放位置
+# material_directory = ""                    #表示将视频素材下载到默认的文件夹，默认文件夹为当前项目下的 ./storage/cache_videos
+# material_directory = "/user/harry/videos"  #表示将视频素材下载到指定的文件夹中
+# material_directory = "task"                #表示将视频素材下载到当前任务的文件夹中，这种方式无法共享已经下载的视频素材
+
+material_directory = ""
+
+# Used for state management of the task
+enable_redis = false
+redis_host = "localhost"
+redis_port = 6379
+redis_db = 0
+redis_password = ""
+
+# 文生视频时的最大并发任务数
+max_concurrent_tasks = 5
 
 
 [whisper]
-    # Only effective when subtitle_provider is "whisper"
+# Only effective when subtitle_provider is "whisper"
 
-    # Run on GPU with FP16
-    # model = WhisperModel(model_size, device="cuda", compute_type="float16")
+# Run on GPU with FP16
+# model = WhisperModel(model_size, device="cuda", compute_type="float16")
 
-    # Run on GPU with INT8
-    # model = WhisperModel(model_size, device="cuda", compute_type="int8_float16")
+# Run on GPU with INT8
+# model = WhisperModel(model_size, device="cuda", compute_type="int8_float16")
 
-    # Run on CPU with INT8
-    # model = WhisperModel(model_size, device="cpu", compute_type="int8")
+# Run on CPU with INT8
+# model = WhisperModel(model_size, device="cpu", compute_type="int8")
 
-    # recommended model_size: "large-v3"
-    model_size="large-v3"
-    # if you want to use GPU, set device="cuda"
-    device="CPU"
-    compute_type="int8"
+# recommended model_size: "large-v3"
+model_size = "large-v3"
+# if you want to use GPU, set device="cuda"
+device = "CPU"
+compute_type = "int8"
 
 
 [proxy]
-    ### Use a proxy to access the Pexels API
-    ### Format: "http://<username>:<password>@<proxy>:<port>"
-    ### Example: "http://user:pass@proxy:1234"
-    ### Doc: https://requests.readthedocs.io/en/latest/user/advanced/#proxies
+### Use a proxy to access the Pexels API
+### Format: "http://<username>:<password>@<proxy>:<port>"
+### Example: "http://user:pass@proxy:1234"
+### Doc: https://requests.readthedocs.io/en/latest/user/advanced/#proxies
 
-    # http = "http://10.10.1.10:3128"
-    # https = "http://10.10.1.10:1080"
+# http = "http://10.10.1.10:3128"
+# https = "http://10.10.1.10:1080"
 
 [azure]
-    # Azure Speech API Key
-    # Get your API key at https://portal.azure.com/#view/Microsoft_Azure_ProjectOxford/CognitiveServicesHub/~/SpeechServices
-    speech_key=""
-    speech_region=""
+# Azure Speech API Key
+# Get your API key at https://portal.azure.com/#view/Microsoft_Azure_ProjectOxford/CognitiveServicesHub/~/SpeechServices
+speech_key = ""
+speech_region = ""
+
+[siliconflow]
+# SiliconFlow API Key
+# Get your API key at https://siliconflow.cn
+api_key = ""
+
+[ui]
+# UI related settings
+# 是否隐藏日志信息
+# Whether to hide logs in the UI
+hide_log = false

docker-compose.yml

@@ -6,7 +6,7 @@ services:
     build:
       context: .
       dockerfile: Dockerfile
-    container_name: "webui"
+    container_name: "moneyprinterturbo-webui"
     ports:
       - "8501:8501"
     command: [ "streamlit", "run", "./webui/Main.py","--browser.serverAddress=127.0.0.1","--server.enableCORS=True","--browser.gatherUsageStats=False" ]
@@ -16,7 +16,7 @@ services:
     build:
       context: .
       dockerfile: Dockerfile
-    container_name: "api"
+    container_name: "moneyprinterturbo-api"
     ports:
       - "8080:8080"
     command: [ "python3", "main.py" ]

docs/MoneyPrinterTurbo.ipynb

@@ -0,0 +1,118 @@
+{
+  "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 -r requirements.txt\n",
+        "!pip install pyngrok --quiet"
+      ]
+    },
+    {
+      "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",
+        "# Start Streamlit server on port 8501\n",
+        "streamlit_proc = subprocess.Popen([\n",
+        "    \"streamlit\", \"run\", \"./webui/Main.py\", \"--server.port=8501\"\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
+}

requirements.txt

@@ -1,26 +1,16 @@
-requests~=2.31.0
-moviepy~=2.0.0.dev2
-openai~=1.13.3
-faster-whisper~=1.0.1
-edge_tts~=6.1.10
-uvicorn~=0.27.1
-fastapi~=0.110.0
-tomli~=2.0.1
-streamlit~=1.33.0
-loguru~=0.7.2
-aiohttp~=3.9.3
-urllib3~=2.2.1
-pillow~=10.3.0
-pydantic~=2.6.3
-g4f~=0.3.0.4
-dashscope~=1.15.0
-google.generativeai~=0.4.1
-python-multipart~=0.0.9
-redis==5.0.3
-# if you use pillow~=10.3.0, you will get "PIL.Image' has no attribute 'ANTIALIAS'" error when resize video
-# please install opencv-python to fix "PIL.Image' has no attribute 'ANTIALIAS'" error
-opencv-python~=4.9.0.80
-# for azure speech
-# https://techcommunity.microsoft.com/t5/ai-azure-ai-services-blog/9-more-realistic-ai-voices-for-conversations-now-generally/ba-p/4099471
-azure-cognitiveservices-speech~=1.37.0
-git-changelog~=2.5.2
+moviepy==2.1.2
+streamlit==1.45.0
+edge_tts==6.1.19
+fastapi==0.115.6
+uvicorn==0.32.1
+openai==1.56.1
+faster-whisper==1.1.0
+loguru==0.7.3
+google.generativeai==0.8.3
+dashscope==1.20.14
+g4f==0.5.2.2
+azure-cognitiveservices-speech==1.41.1
+redis==5.2.0
+python-multipart==0.0.19
+pyyaml
+requests>=2.31.0

sites/docs/.vuepress/config.ts

@@ -1,208 +0,0 @@
-import { viteBundler } from "@vuepress/bundler-vite";
-import { defaultTheme } from "@vuepress/theme-default";
-import { defineUserConfig } from "vuepress";
-
-const base = "MoneyPrinterTurbo";
-const isProd = process.env.NODE_ENV === "production";
-
-export default defineUserConfig({
-  lang: "zh-CN",
-  base: `/${base}/`,
-  bundler: viteBundler(),
-  theme: defaultTheme({
-    repo: "harry0703/MoneyPrinterTurbo",
-    docsDir: "sites/docs",
-    colorModeSwitch: true,
-    locales: {
-      "/": {
-        // navbar
-        navbar: [
-          { text: "Guide", link: "/guide/" },
-          // { text: "Components", link: "/components/" },
-        ],
-        selectLanguageText: "Languages",
-        selectLanguageName: "English",
-        selectLanguageAriaLabel: "Select language",
-        // sidebar
-        sidebar: {
-          "/guide/": [
-            {
-              text: "Guide",
-              children: [
-                { text: "Get Started", link: "/guide/README.md" }, 
-                { text: "Video Demonstration", link: "/guide/video-demonstration.md" },
-                { text: "Features", link: "/guide/features.md" },
-                { text: "Speech Synthesis", link: "/guide/speech-synthesis.md" },
-                { text: "Subtitle Generation", link: "/guide/subtitle-generation.md" },
-                { text: "Background Music", link: "/guide/background-music.md" },
-                { text: "Subtitle Font", link: "/guide/subtitle-font.md" },
-              ],
-            },
-            {
-              text: "Others",
-              children: [
-                { text: "FAQ", link: "/guide/faq.md" },
-                { text: "Feedback", link: "/guide/feedback.md" },
-                { text: "Reference Project", link: "/guide/reference-project.md" },
-              ],
-            },
-          ],
-          // "/components/": getComponentsSidebar("Components", "Advanced"),
-        },
-        // page meta
-        editLinkText: "Edit this page on GitHub",
-      },
-      "/zh/": {
-        // navbar
-        navbar: [
-          { text: "指南", link: "/zh/guide/" },
-          // { text: "组件", link: "/zh/components/" },
-        ],
-        selectLanguageText: "选择语言",
-        selectLanguageName: "简体中文",
-        selectLanguageAriaLabel: "选择语言",
-        // sidebar
-        sidebar: {
-          "/zh/guide/": [
-            {
-              text: "指南",
-              children: [
-                { text: "快速开始", link: "/zh/guide/README.md" }, 
-                { text: "配置要求", link: "/zh/guide/configuration-requirements.md" },
-                { text: "视频演示", link: "/zh/guide/video-demonstration.md" },
-                { text: "功能", link: "/zh/guide/features.md" },
-                { text: "语音合成", link: "/zh/guide/speech-synthesis.md" },
-                { text: "字幕生成", link: "/zh/guide/subtitle-generation.md" },
-                { text: "背景音乐", link: "/zh/guide/background-music.md" },
-                { text: "字幕字体", link: "/zh/guide/subtitle-font.md" },
-              ],
-            },
-            {
-              text: "其他",
-              children: [
-                { text: "常见问题", link: "/zh/guide/faq.md" },
-                { text: "反馈建议", link: "/zh/guide/feedback.md" },
-                { text: "参考项目", link: "/zh/guide/reference-project.md" },
-                { text: "特别感谢", link: "/zh/guide/special-thanks.md" }, 
-                { text: "感谢赞助", link: "/zh/guide/thanks-for-sponsoring" },
-              ],
-            },
-          ],
-          // "/zh/others/": getComponentsSidebar("组件", "高级"),
-        },
-        // page meta
-        editLinkText: "在 GitHub 上编辑此页",
-        lastUpdatedText: "上次更新",
-        contributorsText: "贡献者",
-        // custom containers
-        tip: "提示",
-        warning: "注意",
-        danger: "警告",
-        // 404 page
-        notFound: [
-          "这里什么都没有",
-          "我们怎么到这来了？",
-          "这是一个 404 页面",
-          "看起来我们进入了错误的链接",
-        ],
-        backToHome: "返回首页",
-      },
-    },
-    themePlugins: {
-      // only enable git plugin in production mode
-      git: isProd,
-    },
-  }),
-  locales: {
-    "/": {
-      lang: "en-US",
-      title: "MoneyPrinterTurbo",
-      description: "Generate short videos with one click using AI LLM.",
-    },
-    "/zh/": {
-      lang: "zh-CN",
-      title: "MoneyPrinterTurbo",
-      description: "利用AI大模型，一键生成高清短视频。",
-    },
-  },
-  head: [
-    [
-      "link",
-      {
-        rel: "icon",
-        type: "image/png",
-        sizes: "16x16",
-        href: `/${base}/icons/favicon-16x16.png`,
-      },
-    ],
-    [
-      "link",
-      {
-        rel: "icon",
-        type: "image/png",
-        sizes: "32x32",
-        href: `/${base}/icons/favicon-32x32.png`,
-      },
-    ],
-    ["meta", { name: "application-name", content: "MoneyPrinterTurbo" }],
-    [
-      "meta",
-      { name: "apple-mobile-web-app-title", content: "MoneyPrinterTurbo" },
-    ],
-    ["meta", { name: "apple-mobile-web-app-capable", content: "yes" }],
-    [
-      "meta",
-      { name: "apple-mobile-web-app-status-bar-style", content: "black" },
-    ],
-    [
-      "link",
-      {
-        rel: "apple-touch-icon",
-        href: `/${base}/icons/apple-touch-icon-152x152.png`,
-      },
-    ],
-    [
-      "link",
-      {
-        rel: "mask-icon",
-        href: "/${base}/icons/safari-pinned-tab.svg",
-        color: "#3eaf7c",
-      },
-    ],
-    [
-      "meta",
-      {
-        name: "msapplication-TileImage",
-        content: "/${base}/icons/msapplication-icon-144x144.png",
-      },
-    ],
-    ["meta", { name: "msapplication-TileColor", content: "#000000" }],
-    ["meta", { name: "theme-color", content: "#3eaf7c" }],
-  ],
-});
-
-function getGuideSidebar(groupA: string, groupB: string) {
-  return [
-    {
-      text: groupA,
-      children: ["README.md", { text: "特别感谢", link: "/zh/guide/special-thanks.md" }, "2.md"],
-    },
-    {
-      text: groupB,
-      children: ["custom-validator.md", "1.md", "2.md", "3.md"],
-    },
-  ];
-}
-
-function getComponentsSidebar(groupA: string, groupB: string) {
-  return [
-    {
-      text: groupA,
-      children: ["README.md", "1.md", "2.md"],
-    },
-    {
-      text: groupB,
-      children: ["custom-components.md"],
-    },
-  ];
-}

sites/docs/.vuepress/public/icons/safari-pinned-tab.svg

@@ -1,149 +0,0 @@
-<?xml version="1.0" standalone="no"?>
-<!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 20010904//EN"
- "http://www.w3.org/TR/2001/REC-SVG-20010904/DTD/svg10.dtd">
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sites/docs/README.md

@@ -1,16 +0,0 @@
----
-home: true
-heroImage: /hero.png
-actions:
-  - text: Get Started →
-    link: /guide/
-    type: primary
-features:
-  - title: Multilingual
-    details: Supports video scripts in both Chinese and English; offers multiple voice synthesis options.
-  - title: Maintainability
-    details: Complete MVC architecture with clear code structure, easy to maintain, supports both API and Web interface.
-  - title: Multi-Model Support
-    details: Supports integration with multiple models including OpenAI, moonshot, Azure, gpt4free, one-api, Tongyi Qianwen, Google Gemini, Ollama, and others.
-footer: MIT Licensed | Copyright © 2024-present MoneyPrinterTurbo
----

sites/docs/guide/README.md

@@ -1,134 +0,0 @@
-## Installation & Deployment 📥
-
-Simply provide a <b>topic</b> or <b>keyword</b> for a video, and it will automatically generate the video copy, video
-materials, video subtitles, and video background music before synthesizing a high-definition short video.
-
-### WebUI
-
-![](/webui-en.jpg)
-
-### API Interface
-
-![](/api.jpg)
-
-- Try to avoid using **Chinese paths** to prevent unpredictable issues
-- Ensure your **network** is stable, meaning you can access foreign websites normally
-
-#### ① Clone the Project
-
-```shell
-git clone https://github.com/harry0703/MoneyPrinterTurbo.git
-```
-
-#### ② Modify the Configuration File
-
-- Copy the `config.example.toml` file and rename it to `config.toml`
-- Follow the instructions in the `config.toml` file to configure `pexels_api_keys` and `llm_provider`, and according to
-  the llm_provider's service provider, set up the corresponding API Key
-
-#### ③ Configure Large Language Models (LLM)
-
-- To use `GPT-4.0` or `GPT-3.5`, you need an `API Key` from `OpenAI`. If you don't have one, you can set `llm_provider`
-  to `g4f` (a free-to-use GPT library https://github.com/xtekky/gpt4free)
-
-### Docker Deployment 🐳
-
-#### ① Launch the Docker Container
-
-If you haven't installed Docker, please install it first https://www.docker.com/products/docker-desktop/
-If you are using a Windows system, please refer to Microsoft's documentation:
-
-1. https://learn.microsoft.com/en-us/windows/wsl/install
-2. https://learn.microsoft.com/en-us/windows/wsl/tutorials/wsl-containers
-
-```shell
-cd MoneyPrinterTurbo
-docker-compose up
-```
-
-#### ② Access the Web Interface
-
-Open your browser and visit http://0.0.0.0:8501
-
-#### ③ Access the API Interface
-
-Open your browser and visit http://0.0.0.0:8080/docs Or http://0.0.0.0:8080/redoc
-
-### Manual Deployment 📦
-
-#### ① Create a Python Virtual Environment
-
-It is recommended to create a Python virtual environment
-using [conda](https://conda.io/projects/conda/en/latest/user-guide/install/index.html)
-
-```shell
-git clone https://github.com/harry0703/MoneyPrinterTurbo.git
-cd MoneyPrinterTurbo
-conda create -n MoneyPrinterTurbo python=3.10
-conda activate MoneyPrinterTurbo
-pip install -r requirements.txt
-```
-
-#### ② Install ImageMagick
-
-###### Windows:
-
-- Download https://imagemagick.org/archive/binaries/ImageMagick-7.1.1-29-Q16-x64-static.exe
-- Install the downloaded ImageMagick, **do not change the installation path**
-- Modify the `config.toml` configuration file, set `imagemagick_path` to your actual installation path (if you didn't
-  change the path during installation, just uncomment it)
-
-###### MacOS:
-
-```shell
-brew install imagemagick
-```
-
-###### Ubuntu
-
-```shell
-sudo apt-get install imagemagick
-```
-
-###### CentOS
-
-```shell
-sudo yum install ImageMagick
-```
-
-#### ③ Launch the Web Interface 🌐
-
-Note that you need to execute the following commands in the `root directory` of the MoneyPrinterTurbo project
-
-###### Windows
-
-```bat
-conda activate MoneyPrinterTurbo
-webui.bat
-```
-
-###### MacOS or Linux
-
-```shell
-conda activate MoneyPrinterTurbo
-sh webui.sh
-```
-
-After launching, the browser will open automatically
-
-#### ④ Launch the API Service 🚀
-
-```shell
-python main.py
-```
-
-After launching, you can view the `API documentation` at http://127.0.0.1:8080/docs and directly test the interface
-online for a quick experience.
-
-## License 📝
-
-Click to view the [`LICENSE`](LICENSE) file
-
-## Star History
-
-[![Star History Chart](https://api.star-history.com/svg?repos=harry0703/MoneyPrinterTurbo&type=Date)](https://star-history.com/#harry0703/MoneyPrinterTurbo&Date)

sites/docs/guide/background-music.md

@@ -1,5 +0,0 @@
-## Background Music 🎵
-
-Background music for videos is located in the project's `resource/songs` directory.
-> The current project includes some default music from YouTube videos. If there are copyright issues, please delete
-> them.

sites/docs/guide/faq.md

@@ -1,70 +0,0 @@
-## Common Questions 🤔
-
-### ❓How to Use the Free OpenAI GPT-3.5 Model?
-
-[OpenAI has announced that ChatGPT with 3.5 is now free](https://openai.com/blog/start-using-chatgpt-instantly), and
-developers have wrapped it into an API for direct usage.
-
-**Ensure you have Docker installed and running**. Execute the following command to start the Docker service:
-
-```shell
-docker run -p 3040:3040 missuo/freegpt35
-```
-
-Once successfully started, modify the `config.toml` configuration as follows:
-
-- Set `llm_provider` to `openai`
-- Fill in `openai_api_key` with any value, for example, '123456'
-- Change `openai_base_url` to `http://localhost:3040/v1/`
-- Set `openai_model_name` to `gpt-3.5-turbo`
-
-### ❓RuntimeError: No ffmpeg exe could be found
-
-Normally, ffmpeg will be automatically downloaded and detected.
-However, if your environment has issues preventing automatic downloads, you may encounter the following error:
-
-```
-RuntimeError: No ffmpeg exe could be found.
-Install ffmpeg on your system, or set the IMAGEIO_FFMPEG_EXE environment variable.
-```
-
-In this case, you can download ffmpeg from https://www.gyan.dev/ffmpeg/builds/, unzip it, and set `ffmpeg_path` to your
-actual installation path.
-
-```toml
-[app]
-# Please set according to your actual path, note that Windows path separators are \\
-ffmpeg_path = "C:\\Users\\harry\\Downloads\\ffmpeg.exe"
-```
-
-### ❓Error generating audio or downloading videos
-
-[issue 56](https://github.com/harry0703/MoneyPrinterTurbo/issues/56)
-
-```
-failed to generate audio, maybe the network is not available. 
-if you are in China, please use a VPN.
-```
-
-[issue 44](https://github.com/harry0703/MoneyPrinterTurbo/issues/44)
-
-```
-failed to download videos, maybe the network is not available. 
-if you are in China, please use a VPN.
-```
-
-This is likely due to network issues preventing access to foreign services. Please use a VPN to resolve this.
-
-### ❓ImageMagick is not installed on your computer
-
-[issue 33](https://github.com/harry0703/MoneyPrinterTurbo/issues/33)
-
-1. Follow the `example configuration` provided `download address` to
-   install https://imagemagick.org/archive/binaries/ImageMagick-7.1.1-30-Q16-x64-static.exe, using the static library
-2. Do not install in a path with Chinese characters to avoid unpredictable issues
-
-[issue 54](https://github.com/harry0703/MoneyPrinterTurbo/issues/54#issuecomment-2017842022)
-
-For Linux systems, you can manually install it, refer to https://cn.linux-console.net/?p=16978
-
-Thanks to [@wangwenqiao666](https://github.com/wangwenqiao666) for their research and exploration

sites/docs/guide/features.md

@@ -1,34 +0,0 @@
-## Features 🎯
-
-- [x] Complete **MVC architecture**, **clearly structured** code, easy to maintain, supports both `API`
-  and `Web interface`
-- [x] Supports **AI-generated** video copy, as well as **customized copy**
-- [x] Supports various **high-definition video** sizes
-    - [x] Portrait 9:16, `1080x1920`
-    - [x] Landscape 16:9, `1920x1080`
-- [x] Supports **batch video generation**, allowing the creation of multiple videos at once, then selecting the most
-  satisfactory one
-- [x] Supports setting the **duration of video clips**, facilitating adjustments to material switching frequency
-- [x] Supports video copy in both **Chinese** and **English**
-- [x] Supports **multiple voice** synthesis
-- [x] Supports **subtitle generation**, with adjustable `font`, `position`, `color`, `size`, and also
-  supports `subtitle outlining`
-- [x] Supports **background music**, either random or specified music files, with adjustable `background music volume`
-- [x] Video material sources are **high-definition** and **royalty-free**
-- [x] Supports integration with various models such as **OpenAI**, **moonshot**, **Azure**, **gpt4free**, **one-api**,
-  **qianwen**, **Google Gemini**, **Ollama** and more
-
-❓[How to Use the Free OpenAI GPT-3.5 Model?](https://github.com/harry0703/MoneyPrinterTurbo/blob/main/README-en.md#common-questions-)
-
-### Future Plans 📅
-
-- [ ] Introduce support for GPT-SoVITS dubbing
-- [ ] Enhance voice synthesis with large models for a more natural and emotionally resonant voice output
-- [ ] Incorporate video transition effects to ensure a smoother viewing experience
-- [ ] Improve the relevance of video content
-- [ ] Add options for video length: short, medium, long
-- [ ] Package the application into a one-click launch bundle for Windows and macOS for ease of use
-- [ ] Enable the use of custom materials
-- [ ] Offer voiceover and background music options with real-time preview
-- [ ] Support a wider range of voice synthesis providers, such as OpenAI TTS, Azure TTS
-- [ ] Automate the upload process to the YouTube platform

sites/docs/guide/feedback.md

@@ -1,4 +0,0 @@
-## Feedback & Suggestions 📢
-
-- You can submit an [issue](https://github.com/harry0703/MoneyPrinterTurbo/issues) or
-  a [pull request](https://github.com/harry0703/MoneyPrinterTurbo/pulls).

sites/docs/guide/reference-project.md

@@ -1,4 +0,0 @@
-## Reference Projects 📚
-
-This project is based on https://github.com/FujiwaraChoki/MoneyPrinter and has been refactored with a lot of
-optimizations and added functionalities. Thanks to the original author for their spirit of open source.

sites/docs/guide/speech-synthesis.md

@@ -1,3 +0,0 @@
-## Voice Synthesis 🗣
-
-A list of all supported voices can be viewed here: [Voice List](/voice-list.txt)

sites/docs/guide/subtitle-font.md

@@ -1,4 +0,0 @@
-## Subtitle Fonts 🅰
-
-Fonts for rendering video subtitles are located in the project's `resource/fonts` directory, and you can also add your
-own fonts.

sites/docs/guide/subtitle-generation.md

@@ -1,15 +0,0 @@
-## Subtitle Generation 📜
-
-Currently, there are 2 ways to generate subtitles:
-
-- edge: Faster generation speed, better performance, no specific requirements for computer configuration, but the
-  quality may be unstable
-- whisper: Slower generation speed, poorer performance, specific requirements for computer configuration, but more
-  reliable quality
-
-You can switch between them by modifying the `subtitle_provider` in the `config.toml` configuration file
-
-It is recommended to use `edge` mode, and switch to `whisper` mode if the quality of the subtitles generated is not
-satisfactory.
-
-> If left blank, it means no subtitles will be generated.

sites/docs/guide/video-demonstration.md

@@ -1,35 +0,0 @@
-## Video Demos 📺
-
-### Portrait 9:16
-
-<table>
-<thead>
-<tr>
-<th align="center"><g-emoji class="g-emoji" alias="arrow_forward">▶️</g-emoji> How to Add Fun to Your Life </th>
-<th align="center"><g-emoji class="g-emoji" alias="arrow_forward">▶️</g-emoji> What is the Meaning of Life</th>
-</tr>
-</thead>
-<tbody>
-<tr>
-<td align="center"><video src="https://github.com/harry0703/MoneyPrinterTurbo/assets/4928832/a84d33d5-27a2-4aba-8fd0-9fb2bd91c6a6"></video></td>
-<td align="center"><video src="https://github.com/harry0703/MoneyPrinterTurbo/assets/4928832/112c9564-d52b-4472-99ad-970b75f66476"></video></td>
-</tr>
-</tbody>
-</table>
-
-### Landscape 16:9
-
-<table>
-<thead>
-<tr>
-<th align="center"><g-emoji class="g-emoji" alias="arrow_forward">▶️</g-emoji> What is the Meaning of Life</th>
-<th align="center"><g-emoji class="g-emoji" alias="arrow_forward">▶️</g-emoji> Why Exercise</th>
-</tr>
-</thead>
-<tbody>
-<tr>
-<td align="center"><video src="https://github.com/harry0703/MoneyPrinterTurbo/assets/4928832/346ebb15-c55f-47a9-a653-114f08bb8073"></video></td>
-<td align="center"><video src="https://github.com/harry0703/MoneyPrinterTurbo/assets/4928832/271f2fae-8283-44a0-8aa0-0ed8f9a6fa87"></video></td>
-</tr>
-</tbody>
-</table>

sites/docs/zh/README.md

@@ -1,16 +0,0 @@
----
-home: true
-heroImage: /hero.png
-actions:
-  - text: 快速上手 →
-    link: /zh/guide/
-    type: primary
-features:
-  - title: 多语言
-    details: 支持 中文 和 英文 视频文案；支持 多种语音 合成。
-  - title: 可维护性
-    details: 完整的 MVC架构，代码 结构清晰，易于维护，支持 API 和 Web界面。
-  - title: 多模型支持
-    details: 支持 OpenAI、moonshot、Azure、gpt4free、one-api、通义千问、Google Gemini、Ollama 等多种模型接入。
-footer: MIT Licensed | Copyright © 2024-present MoneyPrinterTurbo
----

sites/docs/zh/guide/README.md

@@ -1,157 +0,0 @@
-## 快速开始 🚀
-
-<br>
-只需提供一个视频 <b>主题</b> 或 <b>关键词</b> ，就可以全自动生成视频文案、视频素材、视频字幕、视频背景音乐，然后合成一个高清的短视频。
-<br>
-
-<h4>Web界面</h4>
-
-![](/webui.jpg)
-
-<h4>API界面</h4>
-
-![](/api.jpg)
-
-下载一键启动包，解压直接使用
-
-### Windows
-
-- 百度网盘: https://pan.baidu.com/s/1bpGjgQVE5sADZRn3A6F87w?pwd=xt16 提取码: xt16
-
-下载后，建议先**双击执行** `update.bat` 更新到**最新代码**，然后双击 `start.bat` 启动 Web 界面
-
-### 其他系统
-
-还没有制作一键启动包，看下面的 **安装部署** 部分，建议使用 **docker** 部署，更加方便。
-
-## 安装部署 📥
-
-### 前提条件
-
-- 尽量不要使用 **中文路径**，避免出现一些无法预料的问题
-- 请确保你的 **网络** 是正常的，VPN 需要打开`全局流量`模式
-
-#### ① 克隆代码
-
-```shell
-git clone https://github.com/harry0703/MoneyPrinterTurbo.git
-```
-
-#### ② 修改配置文件
-
-- 将 `config.example.toml` 文件复制一份，命名为 `config.toml`
-- 按照 `config.toml` 文件中的说明，配置好 `pexels_api_keys` 和 `llm_provider`，并根据 llm_provider 对应的服务商，配置相关的
-  API Key
-
-#### ③ 配置大模型(LLM)
-
-- 如果要使用 `GPT-4.0` 或 `GPT-3.5`，需要有 `OpenAI` 的 `API Key`，如果没有，可以将 `llm_provider` 设置为 `g4f` (
-  一个免费使用 GPT 的开源库 https://github.com/xtekky/gpt4free ，但是该免费的服务，稳定性较差，有时候可以用，有时候用不了)
-- 或者可以使用到 [月之暗面](https://platform.moonshot.cn/console/api-keys) 申请。注册就送
-  15 元体验金，可以对话 1500 次左右。然后设置 `llm_provider="moonshot"` 和 `moonshot_api_key`
-- 也可以使用 通义千问，具体请看配置文件里面的注释说明
-
-### Docker 部署 🐳
-
-#### ① 启动 Docker
-
-如果未安装 Docker，请先安装 https://www.docker.com/products/docker-desktop/
-
-如果是 Windows 系统，请参考微软的文档：
-
-1. https://learn.microsoft.com/zh-cn/windows/wsl/install
-2. https://learn.microsoft.com/zh-cn/windows/wsl/tutorials/wsl-containers
-
-```shell
-cd MoneyPrinterTurbo
-docker-compose up
-```
-
-#### ② 访问 Web 界面
-
-打开浏览器，访问 http://0.0.0.0:8501
-
-#### ③ 访问 API 文档
-
-打开浏览器，访问 http://0.0.0.0:8080/docs 或者 http://0.0.0.0:8080/redoc
-
-### 手动部署 📦
-
-> 视频教程
-
-- 完整的使用演示：https://v.douyin.com/iFhnwsKY/
-- 如何在 Windows 上部署：https://v.douyin.com/iFyjoW3M
-
-#### ① 创建虚拟环境
-
-建议使用 [conda](https://conda.io/projects/conda/en/latest/user-guide/install/index.html) 创建 python 虚拟环境
-
-```shell
-git clone https://github.com/harry0703/MoneyPrinterTurbo.git
-cd MoneyPrinterTurbo
-conda create -n MoneyPrinterTurbo python=3.10
-conda activate MoneyPrinterTurbo
-pip install -r requirements.txt
-```
-
-#### ② 安装好 ImageMagick
-
-###### Windows:
-
-- 下载 https://imagemagick.org/archive/binaries/ImageMagick-7.1.1-30-Q16-x64-static.exe
-- 安装下载好的 ImageMagick，注意不要修改安装路径
-- 修改 `配置文件 config.toml` 中的 `imagemagick_path` 为你的实际安装路径（如果安装的时候没有修改路径，直接取消注释即可）
-
-###### MacOS:
-
-```shell
-brew install imagemagick
-```
-
-###### Ubuntu
-
-```shell
-sudo apt-get install imagemagick
-```
-
-###### CentOS
-
-```shell
-sudo yum install ImageMagick
-```
-
-#### ③ 启动 Web 界面 🌐
-
-注意需要到 MoneyPrinterTurbo 项目 `根目录` 下执行以下命令
-
-###### Windows
-
-```bat
-conda activate MoneyPrinterTurbo
-webui.bat
-```
-
-###### MacOS or Linux
-
-```shell
-conda activate MoneyPrinterTurbo
-sh webui.sh
-```
-
-启动后，会自动打开浏览器
-
-#### ④ 启动 API 服务 🚀
-
-```shell
-python main.py
-```
-
-启动后，可以查看 `API文档` http://127.0.0.1:8080/docs 或者 http://127.0.0.1:8080/redoc 直接在线调试接口，快速体验。
-
-## 许可证 📝
-
-点击查看 [`LICENSE`](LICENSE) 文件
-
-## Star History
-
-[![Star History Chart](https://api.star-history.com/svg?repos=harry0703/MoneyPrinterTurbo&type=Date)](https://star-history.com/#harry0703/MoneyPrinterTurbo&Date)

sites/docs/zh/guide/background-music.md

@@ -1,4 +0,0 @@
-## 背景音乐 🎵
-
-用于视频的背景音乐，位于项目的 `resource/songs` 目录下。
-> 当前项目里面放了一些默认的音乐，来自于 YouTube 视频，如有侵权，请删除。

sites/docs/zh/guide/configuration-requirements.md

@@ -1,4 +0,0 @@
-## 配置要求 📦
-
-- 建议最低 CPU 4核或以上，内存 8G 或以上，显卡非必须
-- Windows 10 或 MacOS 11.0 以上系统

sites/docs/zh/guide/faq.md

@@ -1,123 +0,0 @@
-## 常见问题 🤔
-
-### ❓如何使用免费的OpenAI GPT-3.5模型?
-
-[OpenAI宣布ChatGPT里面3.5已经免费了](https://openai.com/blog/start-using-chatgpt-instantly)，有开发者将其封装成了API，可以直接调用
-
-**确保你安装和启动了docker服务**，执行以下命令启动docker服务
-
-```shell
-docker run -p 3040:3040 missuo/freegpt35
-```
-
-启动成功后，修改 `config.toml` 中的配置
-
-- `llm_provider` 设置为 `openai`
-- `openai_api_key` 随便填写一个即可，比如 '123456'
-- `openai_base_url` 改为 `http://localhost:3040/v1/`
-- `openai_model_name` 改为 `gpt-3.5-turbo`
-
-### ❓AttributeError: 'str' object has no attribute 'choices'`
-
-这个问题是由于 OpenAI 或者其他 LLM，没有返回正确的回复导致的。
-
-大概率是网络原因， 使用 **VPN**，或者设置 `openai_base_url` 为你的代理 ，应该就可以解决了。
-
-### ❓RuntimeError: No ffmpeg exe could be found
-
-通常情况下，ffmpeg 会被自动下载，并且会被自动检测到。
-但是如果你的环境有问题，无法自动下载，可能会遇到如下错误：
-
-```
-RuntimeError: No ffmpeg exe could be found.
-Install ffmpeg on your system, or set the IMAGEIO_FFMPEG_EXE environment variable.
-```
-
-此时你可以从 https://www.gyan.dev/ffmpeg/builds/ 下载ffmpeg，解压后，设置 `ffmpeg_path` 为你的实际安装路径即可。
-
-```toml
-[app]
-# 请根据你的实际路径设置，注意 Windows 路径分隔符为 \\
-ffmpeg_path = "C:\\Users\\harry\\Downloads\\ffmpeg.exe"
-```
-
-### ❓生成音频时报错或下载视频报错
-
-[issue 56](https://github.com/harry0703/MoneyPrinterTurbo/issues/56)
-
-```
-failed to generate audio, maybe the network is not available. 
-if you are in China, please use a VPN.
-```
-
-[issue 44](https://github.com/harry0703/MoneyPrinterTurbo/issues/44)
-
-```
-failed to download videos, maybe the network is not available. 
-if you are in China, please use a VPN.
-```
-
-这个大概率是网络原因，无法访问境外的服务，请使用VPN解决。
-
-### ❓ImageMagick is not installed on your computer
-
-[issue 33](https://github.com/harry0703/MoneyPrinterTurbo/issues/33)
-
-1. 按照 `示例配置` 里面提供的 `下载地址`
-   ，安装 https://imagemagick.org/archive/binaries/ImageMagick-7.1.1-29-Q16-x64-static.exe, 用静态库
-2. 不要安装在中文路径里面，避免出现一些无法预料的问题
-
-[issue 54](https://github.com/harry0703/MoneyPrinterTurbo/issues/54#issuecomment-2017842022)
-
-如果是linux系统，可以手动安装，参考 https://cn.linux-console.net/?p=16978
-
-感谢 [@wangwenqiao666](https://github.com/wangwenqiao666)的研究探索
-
-### ❓ImageMagick的安全策略阻止了与临时文件@/tmp/tmpur5hyyto.txt相关的操作
-
-[issue 92](https://github.com/harry0703/MoneyPrinterTurbo/issues/92)
-
-可以在ImageMagick的配置文件policy.xml中找到这些策略。
-这个文件通常位于 /etc/ImageMagick-`X`/ 或 ImageMagick 安装目录的类似位置。
-修改包含`pattern="@"`的条目，将`rights="none"`更改为`rights="read|write"`以允许对文件的读写操作。
-
-感谢 [@chenhengzh](https://github.com/chenhengzh)的研究探索
-
-### ❓OSError: [Errno 24] Too many open files
-
-[issue 100](https://github.com/harry0703/MoneyPrinterTurbo/issues/100)
-
-这个问题是由于系统打开文件数限制导致的，可以通过修改系统的文件打开数限制来解决。
-
-查看当前限制
-
-```shell
-ulimit -n
-```
-
-如果过低，可以调高一些，比如
-
-```shell
-ulimit -n 10240
-```
-
-### ❓AttributeError: module 'PIL.Image' has no attribute 'ANTIALIAS'
-
-[issue 101](https://github.com/harry0703/MoneyPrinterTurbo/issues/101),
-[issue 83](https://github.com/harry0703/MoneyPrinterTurbo/issues/83),
-[issue 70](https://github.com/harry0703/MoneyPrinterTurbo/issues/70)
-
-先看下当前的 Pillow 版本是多少
-
-```shell
-pip list |grep Pillow
-```
-
-如果是 10.x 的版本，可以尝试下降级看看，有用户反馈降级后正常
-
-```shell
-pip uninstall Pillow
-pip install Pillow==9.5.0
-# 或者降级到 8.4.0
-pip install Pillow==8.4.0
-```

sites/docs/zh/guide/features.md

@@ -1,31 +0,0 @@
-## 功能特性 🎯
-
-- [x] 完整的 **MVC架构**，代码 **结构清晰**，易于维护，支持 `API` 和 `Web界面`
-- [x] 支持视频文案 **AI自动生成**，也可以**自定义文案**
-- [x] 支持多种 **高清视频** 尺寸
-    - [x] 竖屏 9:16，`1080x1920`
-    - [x] 横屏 16:9，`1920x1080`
-- [x] 支持 **批量视频生成**，可以一次生成多个视频，然后选择一个最满意的
-- [x] 支持 **视频片段时长**设置，方便调节素材切换频率
-- [x] 支持 **中文** 和 **英文** 视频文案
-- [x] 支持 **多种语音** 合成
-- [x] 支持 **字幕生成**，可以调整 `字体`、`位置`、`颜色`、`大小`，同时支持`字幕描边`设置
-- [x] 支持 **背景音乐**，随机或者指定音乐文件，可设置`背景音乐音量`
-- [x] 视频素材来源 **高清**，而且 **无版权**
-- [x] 支持 **OpenAI**、**moonshot**、**Azure**、**gpt4free**、**one-api**、**通义千问**、**Google Gemini**、**Ollama** 等多种模型接入
-
-  ❓[如何使用免费的 **OpenAI GPT-3.5
-  ** 模型?](https://github.com/harry0703/MoneyPrinterTurbo?tab=readme-ov-file#%E5%B8%B8%E8%A7%81%E9%97%AE%E9%A2%98-)
-
-  ### 后期计划 📅
-
-- [ ] GPT-SoVITS 配音支持
-- [ ] 优化语音合成，利用大模型，使其合成的声音，更加自然，情绪更加丰富
-- [ ] 增加视频转场效果，使其看起来更加的流畅
-- [ ] 增加更多视频素材来源，优化视频素材和文案的匹配度
-- [ ] 增加视频长度选项：短、中、长
-- [ ] 增加免费网络代理，让访问OpenAI和素材下载不再受限
-- [ ] 可以使用自己的素材
-- [ ] 朗读声音和背景音乐，提供实时试听
-- [ ] 支持更多的语音合成服务商，比如 OpenAI TTS
-- [ ] 自动上传到YouTube平台

sites/docs/zh/guide/feedback.md

@@ -1,4 +0,0 @@
-## 反馈建议 📢
-
-- 可以提交 [issue](https://github.com/harry0703/MoneyPrinterTurbo/issues)
-  或者 [pull request](https://github.com/harry0703/MoneyPrinterTurbo/pulls)。

sites/docs/zh/guide/reference-project.md

@@ -1,4 +0,0 @@
-## 参考项目 📚
-
-该项目基于 https://github.com/FujiwaraChoki/MoneyPrinter 重构而来，做了大量的优化，增加了更多的功能。
-感谢原作者的开源精神。

sites/docs/zh/guide/special-thanks.md

@@ -1,9 +0,0 @@
-## 特别感谢 🙏
-
-由于该项目的 **部署** 和 **使用**，对于一些小白用户来说，还是 **有一定的门槛**，在此特别感谢
-**录咖（AI智能 多媒体服务平台）** 网站基于该项目，提供的免费`AI视频生成器`服务，可以不用部署，直接在线使用，非常方便。
-
-- 中文版：https://reccloud.cn
-- 英文版：https://reccloud.com
-
-![](/reccloud.cn.jpg)

sites/docs/zh/guide/speech-synthesis.md

@@ -1,5 +0,0 @@
-## 语音合成 🗣
-
-所有支持的声音列表，可以查看：[声音列表](/voice-list.txt)
-
-2024-04-16 v1.1.2 新增了9种Azure的语音合成声音，需要配置API KEY，该声音合成的更加真实。

sites/docs/zh/guide/subtitle-font.md

@@ -1,3 +0,0 @@
-## 字幕字体 🅰
-
-用于视频字幕的渲染，位于项目的 `resource/fonts` 目录下，你也可以放进去自己的字体。

sites/docs/zh/guide/subtitle-generation.md

@@ -1,36 +0,0 @@
-## 字幕生成 📜
-
-当前支持2种字幕生成方式：
-
-- **edge**: 生成`速度快`，性能更好，对电脑配置没有要求，但是质量可能不稳定
-- **whisper**: 生成`速度慢`，性能较差，对电脑配置有一定要求，但是`质量更可靠`。
-
-可以修改 `config.toml` 配置文件中的 `subtitle_provider` 进行切换
-
-建议使用 `edge` 模式，如果生成的字幕质量不好，再切换到 `whisper` 模式
-
-> 注意：
-
-1. whisper 模式下需要到 HuggingFace 下载一个模型文件，大约 3GB 左右，请确保网络通畅
-2. 如果留空，表示不生成字幕。
-
-> 由于国内无法访问 HuggingFace，可以使用以下方法下载 `whisper-large-v3` 的模型文件
-
-下载地址：
-
-- 百度网盘: https://pan.baidu.com/s/11h3Q6tsDtjQKTjUu3sc5cA?pwd=xjs9
-- 夸克网盘：https://pan.quark.cn/s/3ee3d991d64b
-
-模型下载后解压，整个目录放到 `.\MoneyPrinterTurbo\models` 里面，
-最终的文件路径应该是这样: `.\MoneyPrinterTurbo\models\whisper-large-v3`
-
-```
-MoneyPrinterTurbo  
-  ├─models
-  │   └─whisper-large-v3
-  │          config.json
-  │          model.bin
-  │          preprocessor_config.json
-  │          tokenizer.json
-  │          vocabulary.json
-```

sites/docs/zh/guide/thanks-for-sponsoring.md

@@ -1,7 +0,0 @@
-## 感谢赞助 🙏
-
-感谢佐糖 https://picwish.cn 对该项目的支持和赞助，使得该项目能够持续的更新和维护。
-
-佐糖专注于**图像处理领域**，提供丰富的**图像处理工具**，将复杂操作极致简化，真正实现让图像处理更简单。
-
-![picwish.jpg](/picwish.jpg)

sites/docs/zh/guide/video-demonstration.md

@@ -1,37 +0,0 @@
-## 视频演示 📺
-
-### 竖屏 9:16
-
-<table>
-<thead>
-<tr>
-<th align="center"><g-emoji class="g-emoji" alias="arrow_forward">▶️</g-emoji> 《如何增加生活的乐趣》</th>
-<th align="center"><g-emoji class="g-emoji" alias="arrow_forward">▶️</g-emoji> 《金钱的作用》<br>更真实的合成声音</th>
-<th align="center"><g-emoji class="g-emoji" alias="arrow_forward">▶️</g-emoji> 《生命的意义是什么》</th>
-</tr>
-</thead>
-<tbody>
-<tr>
-<td align="center"><video src="https://github.com/harry0703/MoneyPrinterTurbo/assets/4928832/a84d33d5-27a2-4aba-8fd0-9fb2bd91c6a6"></video></td>
-<td align="center"><video src="https://github.com/harry0703/MoneyPrinterTurbo/assets/4928832/af2f3b0b-002e-49fe-b161-18ba91c055e8"></video></td>
-<td align="center"><video src="https://github.com/harry0703/MoneyPrinterTurbo/assets/4928832/112c9564-d52b-4472-99ad-970b75f66476"></video></td>
-</tr>
-</tbody>
-</table>
-
-### 横屏 16:9
-
-<table>
-<thead>
-<tr>
-<th align="center"><g-emoji class="g-emoji" alias="arrow_forward">▶️</g-emoji>《生命的意义是什么》</th>
-<th align="center"><g-emoji class="g-emoji" alias="arrow_forward">▶️</g-emoji>《为什么要运动》</th>
-</tr>
-</thead>
-<tbody>
-<tr>
-<td align="center"><video src="https://github.com/harry0703/MoneyPrinterTurbo/assets/4928832/346ebb15-c55f-47a9-a653-114f08bb8073"></video></td>
-<td align="center"><video src="https://github.com/harry0703/MoneyPrinterTurbo/assets/4928832/271f2fae-8283-44a0-8aa0-0ed8f9a6fa87"></video></td>
-</tr>
-</tbody>
-</table>

sites/package.json

@@ -1,24 +0,0 @@
-{
-  "name": "MoneyPrinterTurbo",
-  "version": "1.1.2",
-  "description": "利用AI大模型，一键生成高清短视频 Generate short videos with one click using AI LLM.",
-  "main": "index.js",
-  "repository": "https://github.com/harry0703/MoneyPrinterTurbo",
-  "author": "harry0703",
-  "license": "MIT",
-  "devDependencies": {
-    "@vue/tsconfig": "^0.1.3",
-    "@vuepress/bundler-vite": "2.0.0-rc.9",
-    "@vuepress/theme-default": "2.0.0-rc.25",
-    "gh-pages": "^6.1.1",
-    "vue": "^3.4.23",
-    "vue-router": "^4.3.1",
-    "vuepress": "2.0.0-rc.9"
-  },
-  "scripts": {
-    "docs:dev": "vuepress dev docs",
-    "docs:build": "vuepress build docs",
-    "predeploy": "pnpm docs:build",
-    "deploy": "gh-pages -d docs/.vuepress/dist"
-  }
-}

sites/tsconfig.config.json

@@ -1,14 +0,0 @@
-{
-    "extends": "@vue/tsconfig/tsconfig.node.json",
-    "include": [
-        "vite.config.*",
-        "vitest.config.*",
-        "cypress.config.*"
-    ],
-    "compilerOptions": {
-        "composite": true,
-        "types": [
-            "node"
-        ]
-    }
-}

sites/tsconfig.json

@@ -1,24 +0,0 @@
-{
-  "extends": "@vue/tsconfig/tsconfig.web.json",
-  "module": "esnext",
-  "include": [
-    "env.d.ts",
-    "src/**/*",
-    "src/**/*.vue",
-    "docs/.vuepress/*.ts"
-  ],
-  "compilerOptions": {
-    "baseUrl": ".",
-    "isolatedModules": true,
-    "paths": {
-      "@/*": [
-        "./src/*"
-      ]
-    }
-  },
-  "references": [
-    {
-      "path": "./tsconfig.config.json"
-    }
-  ]
-}

test/README.md

@@ -0,0 +1,40 @@
+# MoneyPrinterTurbo Test Directory
+
+This directory contains unit tests for the **MoneyPrinterTurbo** project.
+
+## Directory Structure
+
+- `services/`: Tests for components in the `app/services` directory  
+  - `test_video.py`: Tests for the video service  
+  - `test_task.py`: Tests for the task service  
+  - `test_voice.py`: Tests for the voice service  
+
+## Running Tests
+
+You can run the tests using Python’s built-in `unittest` framework:
+
+```bash
+# Run all tests
+python -m unittest discover -s test
+
+# Run a specific test file
+python -m unittest test/services/test_video.py
+
+# Run a specific test class
+python -m unittest test.services.test_video.TestVideoService
+
+# Run a specific test method
+python -m unittest test.services.test_video.TestVideoService.test_preprocess_video
+````
+
+## Adding New Tests
+
+To add tests for other components, follow these guidelines:
+
+1. Create test files prefixed with `test_` in the appropriate subdirectory
+2. Use `unittest.TestCase` as the base class for your test classes
+3. Name test methods with the `test_` prefix
+
+## Test Resources
+
+Place any resource files required for testing in the `test/resources` directory.

test/__init__.py

@@ -0,0 +1 @@
+# Unit test package for test