first commit
24
.dockerignore
Normal file
@ -0,0 +1,24 @@
|
||||
# Exclude common Python files and directories
|
||||
venv/
|
||||
__pycache__/
|
||||
*.pyc
|
||||
*.pyo
|
||||
*.pyd
|
||||
*.pyz
|
||||
*.pyw
|
||||
*.pyi
|
||||
*.egg-info/
|
||||
|
||||
# Exclude development and local files
|
||||
.env
|
||||
.env.*
|
||||
*.log
|
||||
*.db
|
||||
|
||||
# Exclude version control system files
|
||||
.git/
|
||||
.gitignore
|
||||
.svn/
|
||||
|
||||
storage/
|
||||
config.toml
|
||||
24
.github/workflows/codeReview.yml
vendored
Normal file
@ -0,0 +1,24 @@
|
||||
name: Code Review
|
||||
|
||||
permissions:
|
||||
contents: read
|
||||
pull-requests: write
|
||||
|
||||
on:
|
||||
# 在提合并请求的时候触发
|
||||
pull_request:
|
||||
types: [opened, reopened]
|
||||
workflow_dispatch:
|
||||
|
||||
jobs:
|
||||
codeReview:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- name: GPT代码逻辑检查
|
||||
uses: anc95/ChatGPT-CodeReview@main
|
||||
env:
|
||||
GITHUB_TOKEN: ${{ secrets.GIT_TOKEN }}
|
||||
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
|
||||
OPENAI_API_ENDPOINT: https://api.groq.com/openai/v1
|
||||
MODEL: llama-3.1-70b-versatile
|
||||
LANGUAGE: Chinese
|
||||
35
.github/workflows/dockerImageBuild.yml.bak
vendored
Normal file
@ -0,0 +1,35 @@
|
||||
name: build_docker
|
||||
|
||||
on:
|
||||
release:
|
||||
types: [created] # 表示在创建新的 Release 时触发
|
||||
|
||||
jobs:
|
||||
build_docker:
|
||||
name: Build docker
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- name: Checkout
|
||||
uses: actions/checkout@v3
|
||||
|
||||
- name: Set up QEMU
|
||||
uses: docker/setup-qemu-action@v3
|
||||
- name: Set up Docker Buildx
|
||||
uses: docker/setup-buildx-action@v3
|
||||
- name: Login to DockerHub
|
||||
uses: docker/login-action@v3
|
||||
with:
|
||||
username: ${{ secrets.DOCKERHUB_USERNAME }}
|
||||
password: ${{ secrets.DOCKERHUB_TOKEN }}
|
||||
|
||||
- name: Build and push
|
||||
id: docker_build
|
||||
uses: docker/build-push-action@v6
|
||||
with:
|
||||
context: .
|
||||
file: ./Dockerfile
|
||||
push: true
|
||||
platforms: linux/amd64,linux/arm64
|
||||
tags: |
|
||||
${{ secrets.DOCKERHUB_USERNAME }}/${{ GITHUB_REPOSITORY_NAME_PART }}:${{ github.ref_name }}
|
||||
${{ secrets.DOCKERHUB_USERNAME }}/${{ GITHUB_REPOSITORY_NAME_PART }}:latest
|
||||
29
.gitignore
vendored
Normal file
@ -0,0 +1,29 @@
|
||||
.DS_Store
|
||||
/config.toml
|
||||
/storage/
|
||||
/.idea/
|
||||
/app/services/__pycache__
|
||||
/app/__pycache__/
|
||||
/app/config/__pycache__/
|
||||
/app/models/__pycache__/
|
||||
/app/utils/__pycache__/
|
||||
/*/__pycache__/*
|
||||
.vscode
|
||||
/**/.streamlit
|
||||
__pycache__
|
||||
logs/
|
||||
|
||||
node_modules
|
||||
# VuePress 默认临时文件目录
|
||||
/sites/docs/.vuepress/.temp
|
||||
# VuePress 默认缓存目录
|
||||
/sites/docs/.vuepress/.cache
|
||||
# VuePress 默认构建生成的静态文件目录
|
||||
/sites/docs/.vuepress/dist
|
||||
# 模型目录
|
||||
/models/
|
||||
./models/*
|
||||
resource/scripts/*
|
||||
resource/videos/*
|
||||
resource/songs/*
|
||||
resource/fonts/*
|
||||
45
Dockerfile
Normal file
@ -0,0 +1,45 @@
|
||||
# Use an official Python runtime as a parent image
|
||||
FROM python:3.10-slim-bullseye
|
||||
|
||||
# Set the working directory in the container
|
||||
WORKDIR /NarratoAI
|
||||
|
||||
# 设置/NarratoAI目录权限为777
|
||||
RUN chmod 777 /NarratoAI
|
||||
|
||||
ENV PYTHONPATH="/NarratoAI"
|
||||
|
||||
# Install system dependencies
|
||||
RUN apt-get update && apt-get install -y \
|
||||
git \
|
||||
imagemagick \
|
||||
ffmpeg \
|
||||
wget \
|
||||
&& 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
|
||||
|
||||
# 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
|
||||
|
||||
# Now copy the rest of the codebase into the image
|
||||
COPY . .
|
||||
|
||||
# Expose the port the app runs on
|
||||
EXPOSE 8501
|
||||
|
||||
# Command to run the application
|
||||
CMD ["streamlit", "run", "./webui/Main.py","--browser.serverAddress=127.0.0.1","--server.enableCORS=True","--browser.gatherUsageStats=False"]
|
||||
|
||||
# 1. Build the Docker image using the following command
|
||||
# docker build -t moneyprinterturbo .
|
||||
|
||||
# 2. Run the Docker container using the following command
|
||||
## For Linux or MacOS:
|
||||
# docker run -v $(pwd)/config.toml:/NarratoAI/config.toml -v $(pwd)/storage:/NarratoAI/storage -p 8501:8501 moneyprinterturbo
|
||||
## For Windows:
|
||||
# docker run -v %cd%/config.toml:/NarratoAI/config.toml -v %cd%/storage:/NarratoAI/storage -p 8501:8501 moneyprinterturbo
|
||||
21
LICENSE
Normal file
@ -0,0 +1,21 @@
|
||||
MIT License
|
||||
|
||||
Copyright (c) 2024 linyq
|
||||
|
||||
Permission is hereby granted, free of charge, to any person obtaining a copy
|
||||
of this software and associated documentation files (the "Software"), to deal
|
||||
in the Software without restriction, including without limitation the rights
|
||||
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
|
||||
copies of the Software, and to permit persons to whom the Software is
|
||||
furnished to do so, subject to the following conditions:
|
||||
|
||||
The above copyright notice and this permission notice shall be included in all
|
||||
copies or substantial portions of the Software.
|
||||
|
||||
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
|
||||
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
|
||||
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
|
||||
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
|
||||
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
|
||||
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
|
||||
SOFTWARE.
|
||||
170
README-en.md
Normal file
@ -0,0 +1,170 @@
|
||||
<div align="center">
|
||||
<h1 align="center" style="font-size: 2cm;"> NarratoAI 😎 </h1>
|
||||
<h3 align="center">All-in-One AI-Powered Video Narration + Automated Editing Tool🎬</h3>
|
||||
|
||||
<h3> 📖 <a href="README.md">Simplified Chinese</a> | English </h3>
|
||||
<div align="center">
|
||||
<a href="https://trendshift.io/repositories/8731" target="_blank"><img src="https://trendshift.io/api/badge/repositories/8731" alt="harry0703%2FNarratoAI | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
|
||||
</div>
|
||||
<br>
|
||||
NarratoAI is an automated video narration tool that provides an all-in-one solution for script writing, automated video editing, voice-over, and subtitle generation, powered by LLM to enhance efficient content creation.
|
||||
<br>
|
||||
|
||||
[](https://github.com/linyqh/NarratoAI)
|
||||
[](https://github.com/linyqh/NarratoAI/blob/main/LICENSE)
|
||||
[](https://github.com/linyqh/NarratoAI/issues)
|
||||
[](https://github.com/linyqh/NarratoAI/stargazers)
|
||||
[](https://dsc.gg/fuji-community)
|
||||
|
||||
<h3>Home</h3>
|
||||
|
||||

|
||||
|
||||
<h3>Video Review Interface</h3>
|
||||
|
||||

|
||||
|
||||
</div>
|
||||
|
||||
## System Requirements 📦
|
||||
|
||||
- Recommended minimum: CPU with 4 cores or more, 8GB RAM or more, GPU is not required
|
||||
- Windows 10 or MacOS 11.0 or above
|
||||
|
||||
## Quick Start 🚀
|
||||
### Apply for Google AI Studio Account
|
||||
1. Visit https://aistudio.google.com/app/prompts/new_chat to apply for an account.
|
||||
2. Click `Get API Key` to request an API Key.
|
||||
3. Enter the obtained API Key into the `gemini_api_key` setting in the `config.example.toml` file.
|
||||
|
||||
### Configure Proxy VPN
|
||||
> The method to configure VPN is not restricted, as long as you can access Google's network. Here, `clash` is used as an example.
|
||||
1. Note the port of the clash service, usually `http://127.0.0.1:7890`.
|
||||
2. If the port is not `7890`, modify the `VPN_PROXY_URL` in the `docker-compose.yml` file to your proxy address.
|
||||
```yaml
|
||||
environment:
|
||||
- "VPN_PROXY_URL=http://host.docker.internal:7890" # Change to your proxy port; host.docker.internal represents the IP of the physical machine.
|
||||
```
|
||||
|
||||
3. (Optional) Or modify the `proxy` settings in the `config.example.toml` file.
|
||||
```toml
|
||||
[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
|
||||
|
||||
http = "http://xx.xx.xx.xx:7890"
|
||||
https = "http://xx.xx.xx.xx:7890"
|
||||
```
|
||||
|
||||
### Docker Deployment 🐳
|
||||
#### ① Start Docker
|
||||
```shell
|
||||
cd NarratoAI
|
||||
docker-compose up
|
||||
```
|
||||
#### ② Access the Web Interface
|
||||
|
||||
Open your browser and go to http://127.0.0.1:8501
|
||||
|
||||
#### ③ Access the API Documentation
|
||||
|
||||
Open your browser and go to http://127.0.0.1:8080/docs or http://127.0.0.1:8080/redoc
|
||||
|
||||
## Usage
|
||||
#### 1. Basic Configuration, Select Model, Enter API Key, and Choose Model
|
||||
> Currently, only the `Gemini` model is supported. Other modes will be added in future updates. Contributions are welcome via [PR](https://github.com/linyqh/NarratoAI/pulls) to join in the development 🎉🎉🎉
|
||||
<div align="center">
|
||||
<img src="docs/img001.png" alt="001" width="1000"/>
|
||||
</div>
|
||||
|
||||
#### 2. Select the Video for Narration and Click to Generate Video Script
|
||||
> A demo video is included in the platform. To use your own video, place the mp4 file in the `resource/videos` directory and refresh your browser.
|
||||
> Note: The filename can be anything, but it must not contain Chinese characters, special characters, spaces, backslashes, etc.
|
||||
<div align="center">
|
||||
<img src="docs/img002.png" alt="002" width="400"/>
|
||||
</div>
|
||||
|
||||
#### 3. Save the Script and Start Editing
|
||||
> After saving the script, refresh the browser, and the newly generated `.json` script file will appear in the script file dropdown. Select the json file and video to start editing.
|
||||
<div align="center">
|
||||
<img src="docs/img003.png" alt="003" width="400"/>
|
||||
</div>
|
||||
|
||||
#### 4. Review the Video; if there are segments that don't meet the rules, click to regenerate or manually edit them.
|
||||
<div align="center">
|
||||
<img src="docs/img004.png" alt="003" width="1000"/>
|
||||
</div>
|
||||
|
||||
#### 5. Configure Basic Video Parameters
|
||||
<div align="center">
|
||||
<img src="docs/img005.png" alt="003" width="700"/>
|
||||
</div>
|
||||
|
||||
#### 6. Start Generating
|
||||
<div align="center">
|
||||
<img src="docs/img006.png" alt="003" width="1000"/>
|
||||
</div>
|
||||
|
||||
#### 7. Video Generation Complete
|
||||
<div align="center">
|
||||
<img src="docs/img007.png" alt="003" width="1000"/>
|
||||
</div>
|
||||
|
||||
## Development 💻
|
||||
1. Install Dependencies
|
||||
```shell
|
||||
conda create -n narratoai python=3.10
|
||||
conda activate narratoai
|
||||
cd narratoai
|
||||
pip install -r requirements.txt
|
||||
```
|
||||
2. Install ImageMagick
|
||||
###### Windows:
|
||||
|
||||
- Download https://imagemagick.org/archive/binaries/ImageMagick-7.1.1-36-Q16-x64-static.exe
|
||||
- Install the downloaded ImageMagick, ensuring you do not change the installation path
|
||||
- Update `imagemagick_path` in the `config.toml` file to your actual installation path (typically `C:\Program Files\ImageMagick-7.1.1-Q16\magick.exe`)
|
||||
|
||||
###### MacOS:
|
||||
|
||||
```shell
|
||||
brew install imagemagick
|
||||
````
|
||||
|
||||
###### Ubuntu
|
||||
|
||||
```shell
|
||||
sudo apt-get install imagemagick
|
||||
```
|
||||
|
||||
###### CentOS
|
||||
|
||||
```shell
|
||||
sudo yum install ImageMagick
|
||||
```
|
||||
|
||||
3. initiate webui
|
||||
```shell
|
||||
streamlit run ./webui/Main.py --browser.serverAddress=127.0.0.1 --server.enableCORS=True --browser.gatherUsageStats=False
|
||||
```
|
||||
4. Access http://127.0.0.1:8501
|
||||
|
||||
## Feedback & Suggestions 📢
|
||||
|
||||
### 👏👏👏 You can submit [issues](https://github.com/linyqh/NarratoAI/issues) or [pull requests](https://github.com/linyqh/NarratoAI/pulls) 🎉🎉🎉
|
||||
|
||||
## Reference Projects 📚
|
||||
- https://github.com/FujiwaraChoki/MoneyPrinter
|
||||
- https://github.com/harry0703/MoneyPrinterTurbo
|
||||
|
||||
This project was refactored based on the above projects with the addition of video narration features. Thanks to the original authors for their open-source spirit 🥳🥳🥳
|
||||
|
||||
## License 📝
|
||||
|
||||
Click to view the [`LICENSE`](LICENSE) file
|
||||
|
||||
## Star History
|
||||
|
||||
[](https://star-history.com/#linyqh/NarratoAI&Date)
|
||||
175
README.md
Normal file
@ -0,0 +1,175 @@
|
||||
|
||||
<div align="center">
|
||||
<h1 align="center" style="font-size: 2cm;"> NarratoAI 😎📽️ </h1>
|
||||
<h3 align="center">一站式 AI 影视解说+自动化剪辑工具🎬🎞️ </h3>
|
||||
|
||||
|
||||
<h3>📖 简体中文 | <a href="README-en.md">English</a></h3>
|
||||
<div align="center">
|
||||
|
||||
[//]: # ( <a href="https://trendshift.io/repositories/8731" target="_blank"><img src="https://trendshift.io/api/badge/repositories/8731" alt="harry0703%2FNarratoAI | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>)
|
||||
</div>
|
||||
<br>
|
||||
NarratoAI 是一个自动化影视解说工具,基于LLM实现文案撰写、自动化视频剪辑、配音和字幕生成的一站式流程,助力高效内容创作。
|
||||
<br>
|
||||
|
||||
[](https://github.com/linyqh/NarratoAI)
|
||||
[](https://github.com/linyqh/NarratoAI/blob/main/LICENSE)
|
||||
[](https://github.com/linyqh/NarratoAI/issues)
|
||||
[](https://github.com/linyqh/NarratoAI/stargazers)
|
||||
[](https://discord.gg/WBKChhmZ)
|
||||
|
||||
|
||||
<h3>首页</h3>
|
||||
|
||||

|
||||
|
||||
<h3>视频审查界面</h3>
|
||||
|
||||

|
||||
|
||||
</div>
|
||||
|
||||
## 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
|
||||
|
||||
## 快速开始 🚀
|
||||
### 申请 Google AI studio 账号
|
||||
1. 访问 https://aistudio.google.com/app/prompts/new_chat 申请账号
|
||||
2. 点击 `Get API Key` 申请 API Key
|
||||
3. 申请的 API Key 填入 `config.example.toml` 文件中的 `gemini_api_key` 配置
|
||||
|
||||
### 配置 proxy VPN
|
||||
> 配置vpn的方法不限,只要能正常访问 Google 网络即可,本文采用的是 chash
|
||||
1. 记住 clash 服务的端口,一般为 `http://127.0.0.1:7890`
|
||||
2. 若端口不为 `7890`,请修改 `docker-compose.yml` 文件中的 `VPN_PROXY_URL` 为你的代理地址
|
||||
```yaml
|
||||
environment:
|
||||
- "VPN_PROXY_URL=http://host.docker.internal:7890" # 修改为你的代理端口;host.docker.internal表示物理机的IP
|
||||
```
|
||||
3. (可选)或者修改 `config.example.toml` 文件中的 `proxy` 配置
|
||||
```toml
|
||||
[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
|
||||
|
||||
http = "http://xx.xx.xx.xx:7890"
|
||||
https = "http://xx.xx.xx.xx:7890"
|
||||
```
|
||||
### docker部署🐳
|
||||
#### ① 垃取项目,启动Docker
|
||||
```shell
|
||||
git clone https://github.com/linyqh/NarratoAI.git
|
||||
cd NarratoAI
|
||||
docker-compose up
|
||||
```
|
||||
#### ② 访问Web界面
|
||||
|
||||
打开浏览器,访问 http://127.0.0.1:8501
|
||||
|
||||
#### ③ 访问API文档
|
||||
|
||||
打开浏览器,访问 http://127.0.0.1:8080/docs 或者 http://127.0.0.1:8080/redoc
|
||||
|
||||
## 使用方法
|
||||
#### 1. 基础配置,选择模型,填入APIKey,选择模型
|
||||
> 目前暂时只支持 `Gemini` 模型,其他模式待后续更新,欢迎大家提交 [PR](https://github.com/linyqh/NarratoAI/pulls),参与开发 🎉🎉🎉
|
||||
<div align="center">
|
||||
<img src="docs/img001.png" alt="001" width="1000"/>
|
||||
</div>
|
||||
|
||||
#### 2. 选择需要解说的视频,点击生成视频脚本
|
||||
> 平台内置了一个演示视频,若要使用自己的视频,将mp4文件放在 `resource/videos` 目录下,刷新浏览器即可,
|
||||
> 注意:文件名随意,但文件名不能包含中文,特殊字符,空格,反斜杠等
|
||||
<div align="center">
|
||||
<img src="docs/img002.png" alt="002" width="400"/>
|
||||
</div>
|
||||
|
||||
#### 3. 保存脚本,开始剪辑
|
||||
> 保存脚本后,刷新浏览器,在脚本文件的下拉框就会有新生成的 `.json` 脚本文件,选择json文件和视频就可以开始剪辑了。
|
||||
<div align="center">
|
||||
<img src="docs/img003.png" alt="003" width="400"/>
|
||||
</div>
|
||||
|
||||
#### 4. 检查视频,若视频存在不符合规则的片段,可以点击重新生成或者手动编辑
|
||||
<div align="center">
|
||||
<img src="docs/img004.png" alt="003" width="1000"/>
|
||||
</div>
|
||||
|
||||
#### 5. 配置视频基本参数
|
||||
<div align="center">
|
||||
<img src="docs/img005.png" alt="003" width="700"/>
|
||||
</div>
|
||||
|
||||
#### 6. 开始生成
|
||||
<div align="center">
|
||||
<img src="docs/img006.png" alt="003" width="1000"/>
|
||||
</div>
|
||||
|
||||
#### 7. 视频生成完成
|
||||
<div align="center">
|
||||
<img src="docs/img007.png" alt="003" width="1000"/>
|
||||
</div>
|
||||
|
||||
## 开发 💻
|
||||
1. 安装依赖
|
||||
```shell
|
||||
conda create -n narratoai python=3.10
|
||||
conda activate narratoai
|
||||
cd narratoai
|
||||
pip install -r requirements.txt
|
||||
```
|
||||
|
||||
2. 安装 ImageMagick
|
||||
###### Windows:
|
||||
|
||||
- 下载 https://imagemagick.org/archive/binaries/ImageMagick-7.1.1-36-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(一般在 `C:\Program Files\ImageMagick-7.1.1-Q16\magick.exe`)
|
||||
|
||||
###### MacOS:
|
||||
|
||||
```shell
|
||||
brew install imagemagick
|
||||
````
|
||||
|
||||
###### Ubuntu
|
||||
|
||||
```shell
|
||||
sudo apt-get install imagemagick
|
||||
```
|
||||
|
||||
###### CentOS
|
||||
|
||||
```shell
|
||||
sudo yum install ImageMagick
|
||||
```
|
||||
3. 启动 webui
|
||||
```shell
|
||||
streamlit run ./webui/Main.py --browser.serverAddress=127.0.0.1 --server.enableCORS=True --browser.gatherUsageStats=False
|
||||
```
|
||||
4. 访问 http://127.0.0.1:8501
|
||||
|
||||
|
||||
## 反馈建议 📢
|
||||
|
||||
### 👏👏👏 可以提交 [issue](https://github.com/linyqh/NarratoAI/issues)或者 [pull request](https://github.com/linyqh/NarratoAI/pulls) 🎉🎉🎉
|
||||
|
||||
## 参考项目 📚
|
||||
- https://github.com/FujiwaraChoki/MoneyPrinter
|
||||
- https://github.com/harry0703/MoneyPrinterTurbo
|
||||
|
||||
该项目基于以上项目重构而来,增加了影视解说功能,感谢大佬的开源精神 🥳🥳🥳
|
||||
|
||||
## 许可证 📝
|
||||
|
||||
点击查看 [`LICENSE`](LICENSE) 文件
|
||||
|
||||
## Star History
|
||||
|
||||
[](https://star-history.com/#linyqh/NarratoAI&Date)
|
||||
|
||||
0
app/__init__.py
Normal file
82
app/asgi.py
Normal file
@ -0,0 +1,82 @@
|
||||
"""Application implementation - ASGI."""
|
||||
|
||||
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 app.config import config
|
||||
from app.models.exception import HttpException
|
||||
from app.router import root_api_router
|
||||
from app.utils import utils
|
||||
|
||||
|
||||
def exception_handler(request: Request, e: HttpException):
|
||||
return JSONResponse(
|
||||
status_code=e.status_code,
|
||||
content=utils.get_response(e.status_code, e.data, e.message),
|
||||
)
|
||||
|
||||
|
||||
def validation_exception_handler(request: Request, e: RequestValidationError):
|
||||
return JSONResponse(
|
||||
status_code=400,
|
||||
content=utils.get_response(
|
||||
status=400, data=e.errors(), message="field required"
|
||||
),
|
||||
)
|
||||
|
||||
|
||||
def get_application() -> FastAPI:
|
||||
"""Initialize FastAPI application.
|
||||
|
||||
Returns:
|
||||
FastAPI: Application object instance.
|
||||
|
||||
"""
|
||||
instance = FastAPI(
|
||||
title=config.project_name,
|
||||
description=config.project_description,
|
||||
version=config.project_version,
|
||||
debug=False,
|
||||
)
|
||||
instance.include_router(root_api_router)
|
||||
instance.add_exception_handler(HttpException, exception_handler)
|
||||
instance.add_exception_handler(RequestValidationError, validation_exception_handler)
|
||||
return instance
|
||||
|
||||
|
||||
app = get_application()
|
||||
|
||||
# Configures the CORS middleware for the FastAPI app
|
||||
cors_allowed_origins_str = os.getenv("CORS_ALLOWED_ORIGINS", "")
|
||||
origins = cors_allowed_origins_str.split(",") if cors_allowed_origins_str else ["*"]
|
||||
app.add_middleware(
|
||||
CORSMiddleware,
|
||||
allow_origins=origins,
|
||||
allow_credentials=True,
|
||||
allow_methods=["*"],
|
||||
allow_headers=["*"],
|
||||
)
|
||||
|
||||
task_dir = utils.task_dir()
|
||||
app.mount(
|
||||
"/tasks", StaticFiles(directory=task_dir, html=True, follow_symlink=True), name=""
|
||||
)
|
||||
|
||||
public_dir = utils.public_dir()
|
||||
app.mount("/", StaticFiles(directory=public_dir, html=True), name="")
|
||||
|
||||
|
||||
@app.on_event("shutdown")
|
||||
def shutdown_event():
|
||||
logger.info("shutdown event")
|
||||
|
||||
|
||||
@app.on_event("startup")
|
||||
def startup_event():
|
||||
logger.info("startup event")
|
||||
56
app/config/__init__.py
Normal file
@ -0,0 +1,56 @@
|
||||
import os
|
||||
import sys
|
||||
|
||||
from loguru import logger
|
||||
|
||||
from app.config import config
|
||||
from app.utils import utils
|
||||
|
||||
|
||||
def __init_logger():
|
||||
# _log_file = utils.storage_dir("logs/server.log")
|
||||
_lvl = config.log_level
|
||||
root_dir = os.path.dirname(
|
||||
os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
|
||||
)
|
||||
|
||||
def format_record(record):
|
||||
# 获取日志记录中的文件全路径
|
||||
file_path = record["file"].path
|
||||
# 将绝对路径转换为相对于项目根目录的路径
|
||||
relative_path = os.path.relpath(file_path, root_dir)
|
||||
# 更新记录中的文件路径
|
||||
record["file"].path = f"./{relative_path}"
|
||||
# 返回修改后的格式字符串
|
||||
# 您可以根据需要调整这里的格式
|
||||
_format = (
|
||||
"<green>{time:%Y-%m-%d %H:%M:%S}</> | "
|
||||
+ "<level>{level}</> | "
|
||||
+ '"{file.path}:{line}":<blue> {function}</> '
|
||||
+ "- <level>{message}</>"
|
||||
+ "\n"
|
||||
)
|
||||
return _format
|
||||
|
||||
logger.remove()
|
||||
|
||||
logger.add(
|
||||
sys.stdout,
|
||||
level=_lvl,
|
||||
format=format_record,
|
||||
colorize=True,
|
||||
)
|
||||
|
||||
# logger.add(
|
||||
# _log_file,
|
||||
# level=_lvl,
|
||||
# format=format_record,
|
||||
# rotation="00:00",
|
||||
# retention="3 days",
|
||||
# backtrace=True,
|
||||
# diagnose=True,
|
||||
# enqueue=True,
|
||||
# )
|
||||
|
||||
|
||||
__init_logger()
|
||||
70
app/config/config.py
Normal file
@ -0,0 +1,70 @@
|
||||
import os
|
||||
import socket
|
||||
import toml
|
||||
import shutil
|
||||
from loguru import logger
|
||||
|
||||
root_dir = os.path.dirname(os.path.dirname(os.path.dirname(os.path.realpath(__file__))))
|
||||
config_file = f"{root_dir}/config.toml"
|
||||
|
||||
|
||||
def load_config():
|
||||
# fix: IsADirectoryError: [Errno 21] Is a directory: '/NarratoAI/config.toml'
|
||||
if os.path.isdir(config_file):
|
||||
shutil.rmtree(config_file)
|
||||
|
||||
if not os.path.isfile(config_file):
|
||||
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(f"load config from file: {config_file}")
|
||||
|
||||
try:
|
||||
_config_ = toml.load(config_file)
|
||||
except Exception as e:
|
||||
logger.warning(f"load config failed: {str(e)}, try to load as utf-8-sig")
|
||||
with open(config_file, mode="r", encoding="utf-8-sig") as fp:
|
||||
_cfg_content = fp.read()
|
||||
_config_ = toml.loads(_cfg_content)
|
||||
return _config_
|
||||
|
||||
|
||||
def save_config():
|
||||
with open(config_file, "w", encoding="utf-8") as f:
|
||||
_cfg["app"] = app
|
||||
_cfg["azure"] = azure
|
||||
_cfg["ui"] = ui
|
||||
f.write(toml.dumps(_cfg))
|
||||
|
||||
|
||||
_cfg = load_config()
|
||||
app = _cfg.get("app", {})
|
||||
whisper = _cfg.get("whisper", {})
|
||||
proxy = _cfg.get("proxy", {})
|
||||
azure = _cfg.get("azure", {})
|
||||
ui = _cfg.get("ui", {})
|
||||
|
||||
hostname = socket.gethostname()
|
||||
|
||||
log_level = _cfg.get("log_level", "DEBUG")
|
||||
listen_host = _cfg.get("listen_host", "0.0.0.0")
|
||||
listen_port = _cfg.get("listen_port", 8080)
|
||||
project_name = _cfg.get("project_name", "NarratoAI")
|
||||
project_description = _cfg.get(
|
||||
"project_description",
|
||||
"<a href='https://github.com/linyqh/NarratoAI'>https://github.com/linyqh/NarratoAI</a>",
|
||||
)
|
||||
project_version = _cfg.get("app", {}).get("project_version")
|
||||
reload_debug = False
|
||||
|
||||
imagemagick_path = app.get("imagemagick_path", "")
|
||||
if imagemagick_path and os.path.isfile(imagemagick_path):
|
||||
os.environ["IMAGEMAGICK_BINARY"] = imagemagick_path
|
||||
|
||||
ffmpeg_path = app.get("ffmpeg_path", "")
|
||||
if ffmpeg_path and os.path.isfile(ffmpeg_path):
|
||||
os.environ["IMAGEIO_FFMPEG_EXE"] = ffmpeg_path
|
||||
|
||||
logger.info(f"{project_name} v{project_version}")
|
||||
31
app/controllers/base.py
Normal file
@ -0,0 +1,31 @@
|
||||
from uuid import uuid4
|
||||
|
||||
from fastapi import Request
|
||||
|
||||
from app.config import config
|
||||
from app.models.exception import HttpException
|
||||
|
||||
|
||||
def get_task_id(request: Request):
|
||||
task_id = request.headers.get("x-task-id")
|
||||
if not task_id:
|
||||
task_id = uuid4()
|
||||
return str(task_id)
|
||||
|
||||
|
||||
def get_api_key(request: Request):
|
||||
api_key = request.headers.get("x-api-key")
|
||||
return api_key
|
||||
|
||||
|
||||
def verify_token(request: Request):
|
||||
token = get_api_key(request)
|
||||
if token != config.app.get("api_key", ""):
|
||||
request_id = get_task_id(request)
|
||||
request_url = request.url
|
||||
user_agent = request.headers.get("user-agent")
|
||||
raise HttpException(
|
||||
task_id=request_id,
|
||||
status_code=401,
|
||||
message=f"invalid token: {request_url}, {user_agent}",
|
||||
)
|
||||
64
app/controllers/manager/base_manager.py
Normal file
@ -0,0 +1,64 @@
|
||||
import threading
|
||||
from typing import Callable, Any, Dict
|
||||
|
||||
|
||||
class TaskManager:
|
||||
def __init__(self, max_concurrent_tasks: int):
|
||||
self.max_concurrent_tasks = max_concurrent_tasks
|
||||
self.current_tasks = 0
|
||||
self.lock = threading.Lock()
|
||||
self.queue = self.create_queue()
|
||||
|
||||
def create_queue(self):
|
||||
raise NotImplementedError()
|
||||
|
||||
def add_task(self, func: Callable, *args: Any, **kwargs: Any):
|
||||
with self.lock:
|
||||
if self.current_tasks < self.max_concurrent_tasks:
|
||||
print(f"add task: {func.__name__}, current_tasks: {self.current_tasks}")
|
||||
self.execute_task(func, *args, **kwargs)
|
||||
else:
|
||||
print(
|
||||
f"enqueue task: {func.__name__}, current_tasks: {self.current_tasks}"
|
||||
)
|
||||
self.enqueue({"func": func, "args": args, "kwargs": kwargs})
|
||||
|
||||
def execute_task(self, func: Callable, *args: Any, **kwargs: Any):
|
||||
thread = threading.Thread(
|
||||
target=self.run_task, args=(func, *args), kwargs=kwargs
|
||||
)
|
||||
thread.start()
|
||||
|
||||
def run_task(self, func: Callable, *args: Any, **kwargs: Any):
|
||||
try:
|
||||
with self.lock:
|
||||
self.current_tasks += 1
|
||||
func(*args, **kwargs) # 在这里调用函数,传递*args和**kwargs
|
||||
finally:
|
||||
self.task_done()
|
||||
|
||||
def check_queue(self):
|
||||
with self.lock:
|
||||
if (
|
||||
self.current_tasks < self.max_concurrent_tasks
|
||||
and not self.is_queue_empty()
|
||||
):
|
||||
task_info = self.dequeue()
|
||||
func = task_info["func"]
|
||||
args = task_info.get("args", ())
|
||||
kwargs = task_info.get("kwargs", {})
|
||||
self.execute_task(func, *args, **kwargs)
|
||||
|
||||
def task_done(self):
|
||||
with self.lock:
|
||||
self.current_tasks -= 1
|
||||
self.check_queue()
|
||||
|
||||
def enqueue(self, task: Dict):
|
||||
raise NotImplementedError()
|
||||
|
||||
def dequeue(self):
|
||||
raise NotImplementedError()
|
||||
|
||||
def is_queue_empty(self):
|
||||
raise NotImplementedError()
|
||||
18
app/controllers/manager/memory_manager.py
Normal file
@ -0,0 +1,18 @@
|
||||
from queue import Queue
|
||||
from typing import Dict
|
||||
|
||||
from app.controllers.manager.base_manager import TaskManager
|
||||
|
||||
|
||||
class InMemoryTaskManager(TaskManager):
|
||||
def create_queue(self):
|
||||
return Queue()
|
||||
|
||||
def enqueue(self, task: Dict):
|
||||
self.queue.put(task)
|
||||
|
||||
def dequeue(self):
|
||||
return self.queue.get()
|
||||
|
||||
def is_queue_empty(self):
|
||||
return self.queue.empty()
|
||||
56
app/controllers/manager/redis_manager.py
Normal file
@ -0,0 +1,56 @@
|
||||
import json
|
||||
from typing import Dict
|
||||
|
||||
import redis
|
||||
|
||||
from app.controllers.manager.base_manager import TaskManager
|
||||
from app.models.schema import VideoParams
|
||||
from app.services import task as tm
|
||||
|
||||
FUNC_MAP = {
|
||||
"start": tm.start,
|
||||
# 'start_test': tm.start_test
|
||||
}
|
||||
|
||||
|
||||
class RedisTaskManager(TaskManager):
|
||||
def __init__(self, max_concurrent_tasks: int, redis_url: str):
|
||||
self.redis_client = redis.Redis.from_url(redis_url)
|
||||
super().__init__(max_concurrent_tasks)
|
||||
|
||||
def create_queue(self):
|
||||
return "task_queue"
|
||||
|
||||
def enqueue(self, task: Dict):
|
||||
task_with_serializable_params = task.copy()
|
||||
|
||||
if "params" in task["kwargs"] and isinstance(
|
||||
task["kwargs"]["params"], VideoParams
|
||||
):
|
||||
task_with_serializable_params["kwargs"]["params"] = task["kwargs"][
|
||||
"params"
|
||||
].dict()
|
||||
|
||||
# 将函数对象转换为其名称
|
||||
task_with_serializable_params["func"] = task["func"].__name__
|
||||
self.redis_client.rpush(self.queue, json.dumps(task_with_serializable_params))
|
||||
|
||||
def dequeue(self):
|
||||
task_json = self.redis_client.lpop(self.queue)
|
||||
if task_json:
|
||||
task_info = json.loads(task_json)
|
||||
# 将函数名称转换回函数对象
|
||||
task_info["func"] = FUNC_MAP[task_info["func"]]
|
||||
|
||||
if "params" in task_info["kwargs"] and isinstance(
|
||||
task_info["kwargs"]["params"], dict
|
||||
):
|
||||
task_info["kwargs"]["params"] = VideoParams(
|
||||
**task_info["kwargs"]["params"]
|
||||
)
|
||||
|
||||
return task_info
|
||||
return None
|
||||
|
||||
def is_queue_empty(self):
|
||||
return self.redis_client.llen(self.queue) == 0
|
||||
14
app/controllers/ping.py
Normal file
@ -0,0 +1,14 @@
|
||||
from fastapi import APIRouter
|
||||
from fastapi import Request
|
||||
|
||||
router = APIRouter()
|
||||
|
||||
|
||||
@router.get(
|
||||
"/ping",
|
||||
tags=["Health Check"],
|
||||
description="检查服务可用性",
|
||||
response_description="pong",
|
||||
)
|
||||
def ping(request: Request) -> str:
|
||||
return "pong"
|
||||
11
app/controllers/v1/base.py
Normal file
@ -0,0 +1,11 @@
|
||||
from fastapi import APIRouter, Depends
|
||||
|
||||
|
||||
def new_router(dependencies=None):
|
||||
router = APIRouter()
|
||||
router.tags = ["V1"]
|
||||
router.prefix = "/api/v1"
|
||||
# 将认证依赖项应用于所有路由
|
||||
if dependencies:
|
||||
router.dependencies = dependencies
|
||||
return router
|
||||
44
app/controllers/v1/llm.py
Normal file
@ -0,0 +1,44 @@
|
||||
from fastapi import Request
|
||||
from app.controllers.v1.base import new_router
|
||||
from app.models.schema import (
|
||||
VideoScriptResponse,
|
||||
VideoScriptRequest,
|
||||
VideoTermsResponse,
|
||||
VideoTermsRequest,
|
||||
)
|
||||
from app.services import llm
|
||||
from app.utils import utils
|
||||
|
||||
# 认证依赖项
|
||||
# router = new_router(dependencies=[Depends(base.verify_token)])
|
||||
router = new_router()
|
||||
|
||||
|
||||
@router.post(
|
||||
"/scripts",
|
||||
response_model=VideoScriptResponse,
|
||||
summary="Create a script for the video",
|
||||
)
|
||||
def generate_video_script(request: Request, body: VideoScriptRequest):
|
||||
video_script = llm.generate_script(
|
||||
video_subject=body.video_subject,
|
||||
language=body.video_language,
|
||||
paragraph_number=body.paragraph_number,
|
||||
)
|
||||
response = {"video_script": video_script}
|
||||
return utils.get_response(200, response)
|
||||
|
||||
|
||||
@router.post(
|
||||
"/terms",
|
||||
response_model=VideoTermsResponse,
|
||||
summary="Generate video terms based on the video script",
|
||||
)
|
||||
def generate_video_terms(request: Request, body: VideoTermsRequest):
|
||||
video_terms = llm.generate_terms(
|
||||
video_subject=body.video_subject,
|
||||
video_script=body.video_script,
|
||||
amount=body.amount,
|
||||
)
|
||||
response = {"video_terms": video_terms}
|
||||
return utils.get_response(200, response)
|
||||
271
app/controllers/v1/video.py
Normal file
@ -0,0 +1,271 @@
|
||||
import glob
|
||||
import os
|
||||
import pathlib
|
||||
import shutil
|
||||
from typing import Union
|
||||
|
||||
from fastapi import BackgroundTasks, Depends, Path, Request, UploadFile
|
||||
from fastapi.params import File
|
||||
from fastapi.responses import FileResponse, StreamingResponse
|
||||
from loguru import logger
|
||||
|
||||
from app.config import config
|
||||
from app.controllers import base
|
||||
from app.controllers.manager.memory_manager import InMemoryTaskManager
|
||||
from app.controllers.manager.redis_manager import RedisTaskManager
|
||||
from app.controllers.v1.base import new_router
|
||||
from app.models.exception import HttpException
|
||||
from app.models.schema import (
|
||||
AudioRequest,
|
||||
BgmRetrieveResponse,
|
||||
BgmUploadResponse,
|
||||
SubtitleRequest,
|
||||
TaskDeletionResponse,
|
||||
TaskQueryRequest,
|
||||
TaskQueryResponse,
|
||||
TaskResponse,
|
||||
TaskVideoRequest,
|
||||
)
|
||||
from app.services import state as sm
|
||||
from app.services import task as tm
|
||||
from app.utils import utils
|
||||
|
||||
# 认证依赖项
|
||||
# router = new_router(dependencies=[Depends(base.verify_token)])
|
||||
router = new_router()
|
||||
|
||||
_enable_redis = config.app.get("enable_redis", False)
|
||||
_redis_host = config.app.get("redis_host", "localhost")
|
||||
_redis_port = config.app.get("redis_port", 6379)
|
||||
_redis_db = config.app.get("redis_db", 0)
|
||||
_redis_password = config.app.get("redis_password", None)
|
||||
_max_concurrent_tasks = config.app.get("max_concurrent_tasks", 5)
|
||||
|
||||
redis_url = f"redis://:{_redis_password}@{_redis_host}:{_redis_port}/{_redis_db}"
|
||||
# 根据配置选择合适的任务管理器
|
||||
if _enable_redis:
|
||||
task_manager = RedisTaskManager(
|
||||
max_concurrent_tasks=_max_concurrent_tasks, redis_url=redis_url
|
||||
)
|
||||
else:
|
||||
task_manager = InMemoryTaskManager(max_concurrent_tasks=_max_concurrent_tasks)
|
||||
|
||||
|
||||
@router.post("/videos", response_model=TaskResponse, summary="Generate a short video")
|
||||
def create_video(
|
||||
background_tasks: BackgroundTasks, request: Request, body: TaskVideoRequest
|
||||
):
|
||||
return create_task(request, body, stop_at="video")
|
||||
|
||||
|
||||
@router.post("/subtitle", response_model=TaskResponse, summary="Generate subtitle only")
|
||||
def create_subtitle(
|
||||
background_tasks: BackgroundTasks, request: Request, body: SubtitleRequest
|
||||
):
|
||||
return create_task(request, body, stop_at="subtitle")
|
||||
|
||||
|
||||
@router.post("/audio", response_model=TaskResponse, summary="Generate audio only")
|
||||
def create_audio(
|
||||
background_tasks: BackgroundTasks, request: Request, body: AudioRequest
|
||||
):
|
||||
return create_task(request, body, stop_at="audio")
|
||||
|
||||
|
||||
def create_task(
|
||||
request: Request,
|
||||
body: Union[TaskVideoRequest, SubtitleRequest, AudioRequest],
|
||||
stop_at: str,
|
||||
):
|
||||
task_id = utils.get_uuid()
|
||||
request_id = base.get_task_id(request)
|
||||
try:
|
||||
task = {
|
||||
"task_id": task_id,
|
||||
"request_id": request_id,
|
||||
"params": body.model_dump(),
|
||||
}
|
||||
sm.state.update_task(task_id)
|
||||
task_manager.add_task(tm.start, task_id=task_id, params=body, stop_at=stop_at)
|
||||
logger.success(f"Task created: {utils.to_json(task)}")
|
||||
return utils.get_response(200, task)
|
||||
except ValueError as e:
|
||||
raise HttpException(
|
||||
task_id=task_id, status_code=400, message=f"{request_id}: {str(e)}"
|
||||
)
|
||||
|
||||
|
||||
@router.get(
|
||||
"/tasks/{task_id}", response_model=TaskQueryResponse, summary="Query task status"
|
||||
)
|
||||
def get_task(
|
||||
request: Request,
|
||||
task_id: str = Path(..., description="Task ID"),
|
||||
query: TaskQueryRequest = Depends(),
|
||||
):
|
||||
endpoint = config.app.get("endpoint", "")
|
||||
if not endpoint:
|
||||
endpoint = str(request.base_url)
|
||||
endpoint = endpoint.rstrip("/")
|
||||
|
||||
request_id = base.get_task_id(request)
|
||||
task = sm.state.get_task(task_id)
|
||||
if task:
|
||||
task_dir = utils.task_dir()
|
||||
|
||||
def file_to_uri(file):
|
||||
if not file.startswith(endpoint):
|
||||
_uri_path = v.replace(task_dir, "tasks").replace("\\", "/")
|
||||
_uri_path = f"{endpoint}/{_uri_path}"
|
||||
else:
|
||||
_uri_path = file
|
||||
return _uri_path
|
||||
|
||||
if "videos" in task:
|
||||
videos = task["videos"]
|
||||
urls = []
|
||||
for v in videos:
|
||||
urls.append(file_to_uri(v))
|
||||
task["videos"] = urls
|
||||
if "combined_videos" in task:
|
||||
combined_videos = task["combined_videos"]
|
||||
urls = []
|
||||
for v in combined_videos:
|
||||
urls.append(file_to_uri(v))
|
||||
task["combined_videos"] = urls
|
||||
return utils.get_response(200, task)
|
||||
|
||||
raise HttpException(
|
||||
task_id=task_id, status_code=404, message=f"{request_id}: task not found"
|
||||
)
|
||||
|
||||
|
||||
@router.delete(
|
||||
"/tasks/{task_id}",
|
||||
response_model=TaskDeletionResponse,
|
||||
summary="Delete a generated short video task",
|
||||
)
|
||||
def delete_video(request: Request, task_id: str = Path(..., description="Task ID")):
|
||||
request_id = base.get_task_id(request)
|
||||
task = sm.state.get_task(task_id)
|
||||
if task:
|
||||
tasks_dir = utils.task_dir()
|
||||
current_task_dir = os.path.join(tasks_dir, task_id)
|
||||
if os.path.exists(current_task_dir):
|
||||
shutil.rmtree(current_task_dir)
|
||||
|
||||
sm.state.delete_task(task_id)
|
||||
logger.success(f"video deleted: {utils.to_json(task)}")
|
||||
return utils.get_response(200)
|
||||
|
||||
raise HttpException(
|
||||
task_id=task_id, status_code=404, message=f"{request_id}: task not found"
|
||||
)
|
||||
|
||||
|
||||
@router.get(
|
||||
"/musics", response_model=BgmRetrieveResponse, summary="Retrieve local BGM files"
|
||||
)
|
||||
def get_bgm_list(request: Request):
|
||||
suffix = "*.mp3"
|
||||
song_dir = utils.song_dir()
|
||||
files = glob.glob(os.path.join(song_dir, suffix))
|
||||
bgm_list = []
|
||||
for file in files:
|
||||
bgm_list.append(
|
||||
{
|
||||
"name": os.path.basename(file),
|
||||
"size": os.path.getsize(file),
|
||||
"file": file,
|
||||
}
|
||||
)
|
||||
response = {"files": bgm_list}
|
||||
return utils.get_response(200, response)
|
||||
|
||||
|
||||
@router.post(
|
||||
"/musics",
|
||||
response_model=BgmUploadResponse,
|
||||
summary="Upload the BGM file to the songs directory",
|
||||
)
|
||||
def upload_bgm_file(request: Request, file: UploadFile = File(...)):
|
||||
request_id = base.get_task_id(request)
|
||||
# check file ext
|
||||
if file.filename.endswith("mp3"):
|
||||
song_dir = utils.song_dir()
|
||||
save_path = os.path.join(song_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 *.mp3 files can be uploaded"
|
||||
)
|
||||
|
||||
|
||||
@router.get("/stream/{file_path:path}")
|
||||
async def stream_video(request: Request, file_path: str):
|
||||
tasks_dir = utils.task_dir()
|
||||
video_path = os.path.join(tasks_dir, file_path)
|
||||
range_header = request.headers.get("Range")
|
||||
video_size = os.path.getsize(video_path)
|
||||
start, end = 0, video_size - 1
|
||||
|
||||
length = video_size
|
||||
if range_header:
|
||||
range_ = range_header.split("bytes=")[1]
|
||||
start, end = [int(part) if part else None for part in range_.split("-")]
|
||||
if start is None:
|
||||
start = video_size - end
|
||||
end = video_size - 1
|
||||
if end is None:
|
||||
end = video_size - 1
|
||||
length = end - start + 1
|
||||
|
||||
def file_iterator(file_path, offset=0, bytes_to_read=None):
|
||||
with open(file_path, "rb") as f:
|
||||
f.seek(offset, os.SEEK_SET)
|
||||
remaining = bytes_to_read or video_size
|
||||
while remaining > 0:
|
||||
bytes_to_read = min(4096, remaining)
|
||||
data = f.read(bytes_to_read)
|
||||
if not data:
|
||||
break
|
||||
remaining -= len(data)
|
||||
yield data
|
||||
|
||||
response = StreamingResponse(
|
||||
file_iterator(video_path, start, length), media_type="video/mp4"
|
||||
)
|
||||
response.headers["Content-Range"] = f"bytes {start}-{end}/{video_size}"
|
||||
response.headers["Accept-Ranges"] = "bytes"
|
||||
response.headers["Content-Length"] = str(length)
|
||||
response.status_code = 206 # Partial Content
|
||||
|
||||
return response
|
||||
|
||||
|
||||
@router.get("/download/{file_path:path}")
|
||||
async def download_video(_: Request, file_path: str):
|
||||
"""
|
||||
download video
|
||||
:param _: Request request
|
||||
:param file_path: video file path, eg: /cd1727ed-3473-42a2-a7da-4faafafec72b/final-1.mp4
|
||||
:return: video file
|
||||
"""
|
||||
tasks_dir = utils.task_dir()
|
||||
video_path = os.path.join(tasks_dir, file_path)
|
||||
file_path = pathlib.Path(video_path)
|
||||
filename = file_path.stem
|
||||
extension = file_path.suffix
|
||||
headers = {"Content-Disposition": f"attachment; filename={filename}{extension}"}
|
||||
return FileResponse(
|
||||
path=video_path,
|
||||
headers=headers,
|
||||
filename=f"{filename}{extension}",
|
||||
media_type=f"video/{extension[1:]}",
|
||||
)
|
||||
0
app/models/__init__.py
Normal file
25
app/models/const.py
Normal file
@ -0,0 +1,25 @@
|
||||
PUNCTUATIONS = [
|
||||
"?",
|
||||
",",
|
||||
".",
|
||||
"、",
|
||||
";",
|
||||
":",
|
||||
"!",
|
||||
"…",
|
||||
"?",
|
||||
",",
|
||||
"。",
|
||||
"、",
|
||||
";",
|
||||
":",
|
||||
"!",
|
||||
"...",
|
||||
]
|
||||
|
||||
TASK_STATE_FAILED = -1
|
||||
TASK_STATE_COMPLETE = 1
|
||||
TASK_STATE_PROCESSING = 4
|
||||
|
||||
FILE_TYPE_VIDEOS = ["mp4", "mov", "mkv", "webm"]
|
||||
FILE_TYPE_IMAGES = ["jpg", "jpeg", "png", "bmp"]
|
||||
28
app/models/exception.py
Normal file
@ -0,0 +1,28 @@
|
||||
import traceback
|
||||
from typing import Any
|
||||
|
||||
from loguru import logger
|
||||
|
||||
|
||||
class HttpException(Exception):
|
||||
def __init__(
|
||||
self, task_id: str, status_code: int, message: str = "", data: Any = None
|
||||
):
|
||||
self.message = message
|
||||
self.status_code = status_code
|
||||
self.data = data
|
||||
# 获取异常堆栈信息
|
||||
tb_str = traceback.format_exc().strip()
|
||||
if not tb_str or tb_str == "NoneType: None":
|
||||
msg = f"HttpException: {status_code}, {task_id}, {message}"
|
||||
else:
|
||||
msg = f"HttpException: {status_code}, {task_id}, {message}\n{tb_str}"
|
||||
|
||||
if status_code == 400:
|
||||
logger.warning(msg)
|
||||
else:
|
||||
logger.error(msg)
|
||||
|
||||
|
||||
class FileNotFoundException(Exception):
|
||||
pass
|
||||
370
app/models/schema.py
Normal file
@ -0,0 +1,370 @@
|
||||
import warnings
|
||||
from enum import Enum
|
||||
from typing import Any, List, Optional
|
||||
|
||||
import pydantic
|
||||
from pydantic import BaseModel
|
||||
|
||||
# 忽略 Pydantic 的特定警告
|
||||
warnings.filterwarnings(
|
||||
"ignore",
|
||||
category=UserWarning,
|
||||
message="Field name.*shadows an attribute in parent.*",
|
||||
)
|
||||
|
||||
|
||||
class VideoConcatMode(str, Enum):
|
||||
random = "random"
|
||||
sequential = "sequential"
|
||||
|
||||
|
||||
class VideoAspect(str, Enum):
|
||||
landscape = "16:9"
|
||||
portrait = "9:16"
|
||||
square = "1:1"
|
||||
|
||||
def to_resolution(self):
|
||||
if self == VideoAspect.landscape.value:
|
||||
return 1920, 1080
|
||||
elif self == VideoAspect.portrait.value:
|
||||
return 1080, 1920
|
||||
elif self == VideoAspect.square.value:
|
||||
return 1080, 1080
|
||||
return 1080, 1920
|
||||
|
||||
|
||||
class _Config:
|
||||
arbitrary_types_allowed = True
|
||||
|
||||
|
||||
@pydantic.dataclasses.dataclass(config=_Config)
|
||||
class MaterialInfo:
|
||||
provider: str = "pexels"
|
||||
url: str = ""
|
||||
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):
|
||||
"""
|
||||
{
|
||||
"video_subject": "",
|
||||
"video_aspect": "横屏 16:9(西瓜视频)",
|
||||
"voice_name": "女生-晓晓",
|
||||
"bgm_name": "random",
|
||||
"font_name": "STHeitiMedium 黑体-中",
|
||||
"text_color": "#FFFFFF",
|
||||
"font_size": 60,
|
||||
"stroke_color": "#000000",
|
||||
"stroke_width": 1.5
|
||||
}
|
||||
"""
|
||||
|
||||
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_aspect: Optional[VideoAspect] = VideoAspect.portrait.value
|
||||
video_concat_mode: Optional[VideoConcatMode] = VideoConcatMode.random.value
|
||||
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_language: Optional[str] = "" # auto detect
|
||||
|
||||
voice_name: Optional[str] = ""
|
||||
voice_volume: Optional[float] = 1.0
|
||||
voice_rate: Optional[float] = 1.0
|
||||
bgm_type: Optional[str] = "random"
|
||||
bgm_file: Optional[str] = ""
|
||||
bgm_volume: Optional[float] = 0.2
|
||||
|
||||
subtitle_enabled: Optional[bool] = True
|
||||
subtitle_position: Optional[str] = "bottom" # top, bottom, center
|
||||
custom_position: float = 70.0
|
||||
font_name: Optional[str] = "STHeitiMedium.ttc"
|
||||
text_fore_color: Optional[str] = "#FFFFFF"
|
||||
text_background_color: Optional[str] = "transparent"
|
||||
|
||||
font_size: int = 60
|
||||
stroke_color: Optional[str] = "#000000"
|
||||
stroke_width: float = 1.5
|
||||
n_threads: Optional[int] = 2
|
||||
paragraph_number: Optional[int] = 1
|
||||
|
||||
|
||||
class SubtitleRequest(BaseModel):
|
||||
video_script: str
|
||||
video_language: Optional[str] = ""
|
||||
voice_name: Optional[str] = "zh-CN-XiaoxiaoNeural-Female"
|
||||
voice_volume: Optional[float] = 1.0
|
||||
voice_rate: Optional[float] = 1.2
|
||||
bgm_type: Optional[str] = "random"
|
||||
bgm_file: Optional[str] = ""
|
||||
bgm_volume: Optional[float] = 0.2
|
||||
subtitle_position: Optional[str] = "bottom"
|
||||
font_name: Optional[str] = "STHeitiMedium.ttc"
|
||||
text_fore_color: Optional[str] = "#FFFFFF"
|
||||
text_background_color: Optional[str] = "transparent"
|
||||
font_size: int = 60
|
||||
stroke_color: Optional[str] = "#000000"
|
||||
stroke_width: float = 1.5
|
||||
video_source: Optional[str] = "local"
|
||||
subtitle_enabled: Optional[str] = "true"
|
||||
|
||||
|
||||
class AudioRequest(BaseModel):
|
||||
video_script: str
|
||||
video_language: Optional[str] = ""
|
||||
voice_name: Optional[str] = "zh-CN-XiaoxiaoNeural-Female"
|
||||
voice_volume: Optional[float] = 1.0
|
||||
voice_rate: Optional[float] = 1.2
|
||||
bgm_type: Optional[str] = "random"
|
||||
bgm_file: Optional[str] = ""
|
||||
bgm_volume: Optional[float] = 0.2
|
||||
video_source: Optional[str] = "local"
|
||||
|
||||
|
||||
class VideoScriptParams:
|
||||
"""
|
||||
{
|
||||
"video_subject": "春天的花海",
|
||||
"video_language": "",
|
||||
"paragraph_number": 1
|
||||
}
|
||||
"""
|
||||
|
||||
video_subject: Optional[str] = "春天的花海"
|
||||
video_language: Optional[str] = ""
|
||||
paragraph_number: Optional[int] = 1
|
||||
|
||||
|
||||
class VideoTermsParams:
|
||||
"""
|
||||
{
|
||||
"video_subject": "",
|
||||
"video_script": "",
|
||||
"amount": 5
|
||||
}
|
||||
"""
|
||||
|
||||
video_subject: Optional[str] = "春天的花海"
|
||||
video_script: Optional[str] = (
|
||||
"春天的花海,如诗如画般展现在眼前。万物复苏的季节里,大地披上了一袭绚丽多彩的盛装。金黄的迎春、粉嫩的樱花、洁白的梨花、艳丽的郁金香……"
|
||||
)
|
||||
amount: Optional[int] = 5
|
||||
|
||||
|
||||
class BaseResponse(BaseModel):
|
||||
status: int = 200
|
||||
message: Optional[str] = "success"
|
||||
data: Any = None
|
||||
|
||||
|
||||
class TaskVideoRequest(VideoParams, BaseModel):
|
||||
pass
|
||||
|
||||
|
||||
class TaskQueryRequest(BaseModel):
|
||||
pass
|
||||
|
||||
|
||||
class VideoScriptRequest(VideoScriptParams, BaseModel):
|
||||
pass
|
||||
|
||||
|
||||
class VideoTermsRequest(VideoTermsParams, BaseModel):
|
||||
pass
|
||||
|
||||
|
||||
######################################################################################################
|
||||
######################################################################################################
|
||||
######################################################################################################
|
||||
######################################################################################################
|
||||
class TaskResponse(BaseResponse):
|
||||
class TaskResponseData(BaseModel):
|
||||
task_id: str
|
||||
|
||||
data: TaskResponseData
|
||||
|
||||
class Config:
|
||||
json_schema_extra = {
|
||||
"example": {
|
||||
"status": 200,
|
||||
"message": "success",
|
||||
"data": {"task_id": "6c85c8cc-a77a-42b9-bc30-947815aa0558"},
|
||||
},
|
||||
}
|
||||
|
||||
|
||||
class TaskQueryResponse(BaseResponse):
|
||||
class Config:
|
||||
json_schema_extra = {
|
||||
"example": {
|
||||
"status": 200,
|
||||
"message": "success",
|
||||
"data": {
|
||||
"state": 1,
|
||||
"progress": 100,
|
||||
"videos": [
|
||||
"http://127.0.0.1:8080/tasks/6c85c8cc-a77a-42b9-bc30-947815aa0558/final-1.mp4"
|
||||
],
|
||||
"combined_videos": [
|
||||
"http://127.0.0.1:8080/tasks/6c85c8cc-a77a-42b9-bc30-947815aa0558/combined-1.mp4"
|
||||
],
|
||||
},
|
||||
},
|
||||
}
|
||||
|
||||
|
||||
class TaskDeletionResponse(BaseResponse):
|
||||
class Config:
|
||||
json_schema_extra = {
|
||||
"example": {
|
||||
"status": 200,
|
||||
"message": "success",
|
||||
"data": {
|
||||
"state": 1,
|
||||
"progress": 100,
|
||||
"videos": [
|
||||
"http://127.0.0.1:8080/tasks/6c85c8cc-a77a-42b9-bc30-947815aa0558/final-1.mp4"
|
||||
],
|
||||
"combined_videos": [
|
||||
"http://127.0.0.1:8080/tasks/6c85c8cc-a77a-42b9-bc30-947815aa0558/combined-1.mp4"
|
||||
],
|
||||
},
|
||||
},
|
||||
}
|
||||
|
||||
|
||||
class VideoScriptResponse(BaseResponse):
|
||||
class Config:
|
||||
json_schema_extra = {
|
||||
"example": {
|
||||
"status": 200,
|
||||
"message": "success",
|
||||
"data": {
|
||||
"video_script": "春天的花海,是大自然的一幅美丽画卷。在这个季节里,大地复苏,万物生长,花朵争相绽放,形成了一片五彩斑斓的花海..."
|
||||
},
|
||||
},
|
||||
}
|
||||
|
||||
|
||||
class VideoTermsResponse(BaseResponse):
|
||||
class Config:
|
||||
json_schema_extra = {
|
||||
"example": {
|
||||
"status": 200,
|
||||
"message": "success",
|
||||
"data": {"video_terms": ["sky", "tree"]},
|
||||
},
|
||||
}
|
||||
|
||||
|
||||
class BgmRetrieveResponse(BaseResponse):
|
||||
class Config:
|
||||
json_schema_extra = {
|
||||
"example": {
|
||||
"status": 200,
|
||||
"message": "success",
|
||||
"data": {
|
||||
"files": [
|
||||
{
|
||||
"name": "output013.mp3",
|
||||
"size": 1891269,
|
||||
"file": "/NarratoAI/resource/songs/output013.mp3",
|
||||
}
|
||||
]
|
||||
},
|
||||
},
|
||||
}
|
||||
|
||||
|
||||
class BgmUploadResponse(BaseResponse):
|
||||
class Config:
|
||||
json_schema_extra = {
|
||||
"example": {
|
||||
"status": 200,
|
||||
"message": "success",
|
||||
"data": {"file": "/NarratoAI/resource/songs/example.mp3"},
|
||||
},
|
||||
}
|
||||
|
||||
|
||||
class VideoClipParams(BaseModel):
|
||||
video_subject: Optional[str] = "春天的花海让人心旷神怡"
|
||||
|
||||
video_clip_json: Optional[str] = "" # 视频剪辑脚本
|
||||
video_origin_path: Optional[str] = "" # 原视频路径
|
||||
video_aspect: Optional[VideoAspect] = VideoAspect.portrait.value # 视频比例
|
||||
video_clip_duration: Optional[int] = 5 # 视频片段时长
|
||||
video_count: Optional[int] = 1 # 视频片段数量
|
||||
video_source: Optional[str] = "local"
|
||||
video_language: Optional[str] = "" # 自动检测
|
||||
video_concat_mode: Optional[VideoConcatMode] = VideoConcatMode.random.value
|
||||
|
||||
# # 女性
|
||||
# "zh-CN-XiaoxiaoNeural",
|
||||
# "zh-CN-XiaoyiNeural",
|
||||
# # 男性
|
||||
# "zh-CN-YunjianNeural" 男声
|
||||
# "zh-CN-YunyangNeural",
|
||||
# "zh-CN-YunxiNeural",
|
||||
voice_name: Optional[str] = "zh-CN-YunjianNeural" # 语音名称 指定选择:
|
||||
voice_volume: Optional[float] = 1.0 # 语音音量
|
||||
voice_rate: Optional[float] = 1.0 # 语速
|
||||
|
||||
bgm_name: Optional[str] = "random" # 背景音乐名称
|
||||
bgm_type: Optional[str] = "random" # 背景音乐类型
|
||||
bgm_file: Optional[str] = "" # 背景音乐文件
|
||||
bgm_volume: Optional[float] = 0.2
|
||||
|
||||
subtitle_enabled: Optional[bool] = True # 是否启用字幕
|
||||
subtitle_position: Optional[str] = "bottom" # top, bottom, center
|
||||
font_name: Optional[str] = "STHeitiMedium.ttc" # 字体名称
|
||||
text_fore_color: Optional[str] = "#FFFFFF" # 文字前景色
|
||||
text_background_color: Optional[str] = "transparent" # 文字背景色
|
||||
|
||||
font_size: int = 60 # 文字大小
|
||||
stroke_color: Optional[str] = "#000000" # 文字描边颜色
|
||||
stroke_width: float = 1.5 # 文字描边宽度
|
||||
n_threads: Optional[int] = 2 # 线程数
|
||||
paragraph_number: Optional[int] = 1 # 段落数量
|
||||
17
app/router.py
Normal file
@ -0,0 +1,17 @@
|
||||
"""Application configuration - root APIRouter.
|
||||
|
||||
Defines all FastAPI application endpoints.
|
||||
|
||||
Resources:
|
||||
1. https://fastapi.tiangolo.com/tutorial/bigger-applications
|
||||
|
||||
"""
|
||||
|
||||
from fastapi import APIRouter
|
||||
|
||||
from app.controllers.v1 import llm, video
|
||||
|
||||
root_api_router = APIRouter()
|
||||
# v1
|
||||
root_api_router.include_router(video.router)
|
||||
root_api_router.include_router(llm.router)
|
||||
0
app/services/__init__.py
Normal file
477
app/services/llm.py
Normal file
@ -0,0 +1,477 @@
|
||||
import logging
|
||||
import re
|
||||
import os
|
||||
import json
|
||||
from typing import List
|
||||
from loguru import logger
|
||||
from openai import OpenAI
|
||||
from openai import AzureOpenAI
|
||||
from openai.types.chat import ChatCompletion
|
||||
import google.generativeai as gemini
|
||||
|
||||
from app.config import config
|
||||
|
||||
_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."
|
||||
)
|
||||
else:
|
||||
raise ValueError(
|
||||
"llm_provider is not set, please set it in the config.toml file."
|
||||
)
|
||||
|
||||
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
|
||||
|
||||
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
|
||||
|
||||
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."
|
||||
)
|
||||
else:
|
||||
raise Exception(
|
||||
f"[{llm_provider}] returned an empty response, please check your network connection and try again."
|
||||
)
|
||||
|
||||
return content.replace("\n", "")
|
||||
|
||||
|
||||
def generate_script(
|
||||
video_subject: str, language: str = "", paragraph_number: int = 1
|
||||
) -> str:
|
||||
prompt = f"""
|
||||
# Role: Video Script Generator
|
||||
|
||||
## Goals:
|
||||
Generate a script for a video, depending on the subject of the video.
|
||||
|
||||
## Constrains:
|
||||
1. the script is to be returned as a string with the specified number of paragraphs.
|
||||
2. do not under any circumstance reference this prompt in your response.
|
||||
3. get straight to the point, don't start with unnecessary things like, "welcome to this video".
|
||||
4. you must not include any type of markdown or formatting in the script, never use a title.
|
||||
5. only return the raw content of the script.
|
||||
6. do not include "voiceover", "narrator" or similar indicators of what should be spoken at the beginning of each paragraph or line.
|
||||
7. you must not mention the prompt, or anything about the script itself. also, never talk about the amount of paragraphs or lines. just write the script.
|
||||
8. respond in the same language as the video subject.
|
||||
|
||||
# Initialization:
|
||||
- video subject: {video_subject}
|
||||
- number of paragraphs: {paragraph_number}
|
||||
""".strip()
|
||||
if language:
|
||||
prompt += f"\n- language: {language}"
|
||||
|
||||
final_script = ""
|
||||
logger.info(f"subject: {video_subject}")
|
||||
|
||||
def format_response(response):
|
||||
# Clean the script
|
||||
# Remove asterisks, hashes
|
||||
response = response.replace("*", "")
|
||||
response = response.replace("#", "")
|
||||
|
||||
# Remove markdown syntax
|
||||
response = re.sub(r"\[.*\]", "", response)
|
||||
response = re.sub(r"\(.*\)", "", response)
|
||||
|
||||
# Split the script into paragraphs
|
||||
paragraphs = response.split("\n\n")
|
||||
|
||||
# Select the specified number of paragraphs
|
||||
selected_paragraphs = paragraphs[:paragraph_number]
|
||||
|
||||
# Join the selected paragraphs into a single string
|
||||
return "\n\n".join(paragraphs)
|
||||
|
||||
for i in range(_max_retries):
|
||||
try:
|
||||
response = _generate_response(prompt=prompt)
|
||||
if response:
|
||||
final_script = format_response(response)
|
||||
else:
|
||||
logging.error("gpt returned an empty response")
|
||||
|
||||
# g4f may return an error message
|
||||
if final_script and "当日额度已消耗完" in final_script:
|
||||
raise ValueError(final_script)
|
||||
|
||||
if final_script:
|
||||
break
|
||||
except Exception as e:
|
||||
logger.error(f"failed to generate script: {e}")
|
||||
|
||||
if i < _max_retries:
|
||||
logger.warning(f"failed to generate video script, trying again... {i + 1}")
|
||||
|
||||
logger.success(f"completed: \n{final_script}")
|
||||
return final_script.strip()
|
||||
|
||||
|
||||
def generate_terms(video_subject: str, video_script: str, amount: int = 5) -> List[str]:
|
||||
prompt = f"""
|
||||
# Role: Video Search Terms Generator
|
||||
|
||||
## Goals:
|
||||
Generate {amount} search terms for stock videos, depending on the subject of a video.
|
||||
|
||||
## Constrains:
|
||||
1. the search terms are to be returned as a json-array of strings.
|
||||
2. each search term should consist of 1-3 words, always add the main subject of the video.
|
||||
3. you must only return the json-array of strings. you must not return anything else. you must not return the script.
|
||||
4. the search terms must be related to the subject of the video.
|
||||
5. reply with english search terms only.
|
||||
|
||||
## Output Example:
|
||||
["search term 1", "search term 2", "search term 3","search term 4","search term 5"]
|
||||
|
||||
## Context:
|
||||
### Video Subject
|
||||
{video_subject}
|
||||
|
||||
### Video Script
|
||||
{video_script}
|
||||
|
||||
Please note that you must use English for generating video search terms; Chinese is not accepted.
|
||||
""".strip()
|
||||
|
||||
logger.info(f"subject: {video_subject}")
|
||||
|
||||
search_terms = []
|
||||
response = ""
|
||||
for i in range(_max_retries):
|
||||
try:
|
||||
response = _generate_response(prompt)
|
||||
search_terms = json.loads(response)
|
||||
if not isinstance(search_terms, list) or not all(
|
||||
isinstance(term, str) for term in search_terms
|
||||
):
|
||||
logger.error("response is not a list of strings.")
|
||||
continue
|
||||
|
||||
except Exception as e:
|
||||
logger.warning(f"failed to generate video terms: {str(e)}")
|
||||
if response:
|
||||
match = re.search(r"\[.*]", response)
|
||||
if match:
|
||||
try:
|
||||
search_terms = json.loads(match.group())
|
||||
except Exception as e:
|
||||
logger.warning(f"failed to generate video terms: {str(e)}")
|
||||
pass
|
||||
|
||||
if search_terms and len(search_terms) > 0:
|
||||
break
|
||||
if i < _max_retries:
|
||||
logger.warning(f"failed to generate video terms, trying again... {i + 1}")
|
||||
|
||||
logger.success(f"completed: \n{search_terms}")
|
||||
return search_terms
|
||||
|
||||
|
||||
def gemini_video2json(video_origin_name: str, video_origin_path: str, video_plot: str) -> str:
|
||||
'''
|
||||
使用 gemini-1.5-pro 进行影视解析
|
||||
Args:
|
||||
video_origin_name: str - 影视作品的原始名称
|
||||
video_origin_path: str - 影视作品的原始路径
|
||||
video_plot: str - 影视作品的简介或剧情概述
|
||||
|
||||
Return:
|
||||
str - 解析后的 JSON 格式字符串
|
||||
'''
|
||||
api_key = config.app.get("gemini_api_key")
|
||||
model_name = config.app.get("gemini_model_name")
|
||||
|
||||
gemini.configure(api_key=api_key)
|
||||
model = gemini.GenerativeModel(model_name=model_name)
|
||||
|
||||
prompt = """
|
||||
# Role: 影视解说专家
|
||||
|
||||
## Background:
|
||||
擅长根据剧情描述视频的画面和故事,能够生成一段非常有趣的解说文案。
|
||||
|
||||
## Goals:
|
||||
1. 根据剧情描述视频的画面和故事,并对重要的画面进行展开叙述
|
||||
2. 根据剧情内容,生成符合 tiktok/抖音 风格的影视解说文案
|
||||
3. 将结果直接以json格式输出给用户,需要包含字段: picture 画面描述, timestamp 时间戳, narration 解说文案
|
||||
4. 剧情内容如下:{%s}
|
||||
|
||||
## Skills
|
||||
- 精通 tiktok/抖音 等短视频影视解说文案撰写
|
||||
- 能够理解视频中的故事和画面表现
|
||||
- 能精准匹配视频中的画面和时间戳
|
||||
- 能精准把控旁白和时长
|
||||
- 精通中文
|
||||
- 精通JSON数据格式
|
||||
|
||||
## Constrains
|
||||
- 解说文案的时长要和时间戳的时长尽量匹配
|
||||
- 忽略视频中关于广告的内容
|
||||
- 忽略视频中片头和片尾
|
||||
- 不得在脚本中包含任何类型的 Markdown 或格式
|
||||
|
||||
## Format
|
||||
- 对应JSON的key为:picture, timestamp, narration
|
||||
""" % video_plot
|
||||
logger.debug(f"视频名称: {video_origin_name}")
|
||||
try:
|
||||
gemini_video_file = gemini.upload_file(video_origin_path)
|
||||
logger.debug(f"上传视频至 Google cloud 成功: {gemini_video_file.name}")
|
||||
while gemini_video_file.state.name == "PROCESSING":
|
||||
import time
|
||||
time.sleep(1)
|
||||
gemini_video_file = gemini.get_file(gemini_video_file.name)
|
||||
logger.debug(f"视频当前状态(ACTIVE才可用): {gemini_video_file.state.name}")
|
||||
if gemini_video_file.state.name == "FAILED":
|
||||
raise ValueError(gemini_video_file.state.name)
|
||||
except:
|
||||
logger.error("上传视频至 Google cloud 失败, 请检查 VPN 配置和 APIKey 是否正确")
|
||||
raise TimeoutError("上传视频至 Google cloud 失败, 请检查 VPN 配置和 APIKey 是否正确")
|
||||
|
||||
streams = model.generate_content([prompt, gemini_video_file], stream=True)
|
||||
response = []
|
||||
for chunk in streams:
|
||||
response.append(chunk.text)
|
||||
|
||||
response = "".join(response)
|
||||
logger.success(f"llm response: \n{response}")
|
||||
|
||||
return response
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
juqin = ""
|
||||
res = gemini_video2json("test", "/NarratoAI/resource/videos/test.mp4", juqin)
|
||||
print(res)
|
||||
|
||||
# video_subject = "生命的意义是什么"
|
||||
# script = generate_script(
|
||||
# video_subject=video_subject, language="zh-CN", paragraph_number=1
|
||||
# )
|
||||
# print("######################")
|
||||
# print(script)
|
||||
# search_terms = generate_terms(
|
||||
# video_subject=video_subject, video_script=script, amount=5
|
||||
# )
|
||||
# print("######################")
|
||||
# print(search_terms)
|
||||
335
app/services/material.py
Normal file
@ -0,0 +1,335 @@
|
||||
import os
|
||||
import random
|
||||
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.utils import utils
|
||||
|
||||
requested_count = 0
|
||||
|
||||
|
||||
def get_api_key(cfg_key: str):
|
||||
api_keys = config.app.get(cfg_key)
|
||||
if not api_keys:
|
||||
raise ValueError(
|
||||
f"\n\n##### {cfg_key} is not set #####\n\nPlease set it in the config.toml file: {config.config_file}\n\n"
|
||||
f"{utils.to_json(config.app)}"
|
||||
)
|
||||
|
||||
# if only one key is provided, return it
|
||||
if isinstance(api_keys, str):
|
||||
return api_keys
|
||||
|
||||
global requested_count
|
||||
requested_count += 1
|
||||
return api_keys[requested_count % len(api_keys)]
|
||||
|
||||
|
||||
def search_videos_pexels(
|
||||
search_term: str,
|
||||
minimum_duration: int,
|
||||
video_aspect: VideoAspect = VideoAspect.portrait,
|
||||
) -> List[MaterialInfo]:
|
||||
aspect = VideoAspect(video_aspect)
|
||||
video_orientation = aspect.name
|
||||
video_width, video_height = aspect.to_resolution()
|
||||
api_key = get_api_key("pexels_api_keys")
|
||||
headers = {"Authorization": api_key}
|
||||
# Build URL
|
||||
params = {"query": search_term, "per_page": 20, "orientation": video_orientation}
|
||||
query_url = f"https://api.pexels.com/videos/search?{urlencode(params)}"
|
||||
logger.info(f"searching videos: {query_url}, with proxies: {config.proxy}")
|
||||
|
||||
try:
|
||||
r = requests.get(
|
||||
query_url,
|
||||
headers=headers,
|
||||
proxies=config.proxy,
|
||||
verify=False,
|
||||
timeout=(30, 60),
|
||||
)
|
||||
response = r.json()
|
||||
video_items = []
|
||||
if "videos" not in response:
|
||||
logger.error(f"search videos failed: {response}")
|
||||
return video_items
|
||||
videos = response["videos"]
|
||||
# loop through each video in the result
|
||||
for v in videos:
|
||||
duration = v["duration"]
|
||||
# check if video has desired minimum duration
|
||||
if duration < minimum_duration:
|
||||
continue
|
||||
video_files = v["video_files"]
|
||||
# loop through each url to determine the best quality
|
||||
for video in video_files:
|
||||
w = int(video["width"])
|
||||
h = int(video["height"])
|
||||
if w == video_width and h == video_height:
|
||||
item = MaterialInfo()
|
||||
item.provider = "pexels"
|
||||
item.url = video["link"]
|
||||
item.duration = duration
|
||||
video_items.append(item)
|
||||
break
|
||||
return video_items
|
||||
except Exception as e:
|
||||
logger.error(f"search videos failed: {str(e)}")
|
||||
|
||||
return []
|
||||
|
||||
|
||||
def search_videos_pixabay(
|
||||
search_term: str,
|
||||
minimum_duration: int,
|
||||
video_aspect: VideoAspect = VideoAspect.portrait,
|
||||
) -> List[MaterialInfo]:
|
||||
aspect = VideoAspect(video_aspect)
|
||||
|
||||
video_width, video_height = aspect.to_resolution()
|
||||
|
||||
api_key = get_api_key("pixabay_api_keys")
|
||||
# Build URL
|
||||
params = {
|
||||
"q": search_term,
|
||||
"video_type": "all", # Accepted values: "all", "film", "animation"
|
||||
"per_page": 50,
|
||||
"key": api_key,
|
||||
}
|
||||
query_url = f"https://pixabay.com/api/videos/?{urlencode(params)}"
|
||||
logger.info(f"searching videos: {query_url}, with proxies: {config.proxy}")
|
||||
|
||||
try:
|
||||
r = requests.get(
|
||||
query_url, proxies=config.proxy, verify=False, timeout=(30, 60)
|
||||
)
|
||||
response = r.json()
|
||||
video_items = []
|
||||
if "hits" not in response:
|
||||
logger.error(f"search videos failed: {response}")
|
||||
return video_items
|
||||
videos = response["hits"]
|
||||
# loop through each video in the result
|
||||
for v in videos:
|
||||
duration = v["duration"]
|
||||
# check if video has desired minimum duration
|
||||
if duration < minimum_duration:
|
||||
continue
|
||||
video_files = v["videos"]
|
||||
# loop through each url to determine the best quality
|
||||
for video_type in video_files:
|
||||
video = video_files[video_type]
|
||||
w = int(video["width"])
|
||||
h = int(video["height"])
|
||||
if w >= video_width:
|
||||
item = MaterialInfo()
|
||||
item.provider = "pixabay"
|
||||
item.url = video["url"]
|
||||
item.duration = duration
|
||||
video_items.append(item)
|
||||
break
|
||||
return video_items
|
||||
except Exception as e:
|
||||
logger.error(f"search videos failed: {str(e)}")
|
||||
|
||||
return []
|
||||
|
||||
|
||||
def save_video(video_url: str, save_dir: str = "") -> str:
|
||||
if not save_dir:
|
||||
save_dir = utils.storage_dir("cache_videos")
|
||||
|
||||
if not os.path.exists(save_dir):
|
||||
os.makedirs(save_dir)
|
||||
|
||||
url_without_query = video_url.split("?")[0]
|
||||
url_hash = utils.md5(url_without_query)
|
||||
video_id = f"vid-{url_hash}"
|
||||
video_path = f"{save_dir}/{video_id}.mp4"
|
||||
|
||||
# if video already exists, return the path
|
||||
if os.path.exists(video_path) and os.path.getsize(video_path) > 0:
|
||||
logger.info(f"video already exists: {video_path}")
|
||||
return video_path
|
||||
|
||||
# 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)
|
||||
).content
|
||||
)
|
||||
|
||||
if os.path.exists(video_path) and os.path.getsize(video_path) > 0:
|
||||
try:
|
||||
clip = VideoFileClip(video_path)
|
||||
duration = clip.duration
|
||||
fps = clip.fps
|
||||
clip.close()
|
||||
if duration > 0 and fps > 0:
|
||||
return video_path
|
||||
except Exception as e:
|
||||
try:
|
||||
os.remove(video_path)
|
||||
except Exception as e:
|
||||
logger.warning(f"无效的视频文件: {video_path} => {str(e)}")
|
||||
return ""
|
||||
|
||||
|
||||
def download_videos(
|
||||
task_id: str,
|
||||
search_terms: List[str],
|
||||
source: str = "pexels",
|
||||
video_aspect: VideoAspect = VideoAspect.portrait,
|
||||
video_contact_mode: VideoConcatMode = VideoConcatMode.random,
|
||||
audio_duration: float = 0.0,
|
||||
max_clip_duration: int = 5,
|
||||
) -> List[str]:
|
||||
valid_video_items = []
|
||||
valid_video_urls = []
|
||||
found_duration = 0.0
|
||||
search_videos = search_videos_pexels
|
||||
if source == "pixabay":
|
||||
search_videos = search_videos_pixabay
|
||||
|
||||
for search_term in search_terms:
|
||||
video_items = search_videos(
|
||||
search_term=search_term,
|
||||
minimum_duration=max_clip_duration,
|
||||
video_aspect=video_aspect,
|
||||
)
|
||||
logger.info(f"found {len(video_items)} videos for '{search_term}'")
|
||||
|
||||
for item in video_items:
|
||||
if item.url not in valid_video_urls:
|
||||
valid_video_items.append(item)
|
||||
valid_video_urls.append(item.url)
|
||||
found_duration += item.duration
|
||||
|
||||
logger.info(
|
||||
f"found total videos: {len(valid_video_items)}, required duration: {audio_duration} seconds, found duration: {found_duration} seconds"
|
||||
)
|
||||
video_paths = []
|
||||
|
||||
material_directory = config.app.get("material_directory", "").strip()
|
||||
if material_directory == "task":
|
||||
material_directory = utils.task_dir(task_id)
|
||||
elif material_directory and not os.path.isdir(material_directory):
|
||||
material_directory = ""
|
||||
|
||||
if video_contact_mode.value == VideoConcatMode.random.value:
|
||||
random.shuffle(valid_video_items)
|
||||
|
||||
total_duration = 0.0
|
||||
for item in valid_video_items:
|
||||
try:
|
||||
logger.info(f"downloading video: {item.url}")
|
||||
saved_video_path = save_video(
|
||||
video_url=item.url, save_dir=material_directory
|
||||
)
|
||||
if saved_video_path:
|
||||
logger.info(f"video saved: {saved_video_path}")
|
||||
video_paths.append(saved_video_path)
|
||||
seconds = min(max_clip_duration, item.duration)
|
||||
total_duration += seconds
|
||||
if total_duration > audio_duration:
|
||||
logger.info(
|
||||
f"total duration of downloaded videos: {total_duration} seconds, skip downloading more"
|
||||
)
|
||||
break
|
||||
except Exception as e:
|
||||
logger.error(f"failed to download video: {utils.to_json(item)} => {str(e)}")
|
||||
logger.success(f"downloaded {len(video_paths)} videos")
|
||||
return video_paths
|
||||
|
||||
|
||||
def save_clip_video(timestamp: str, origin_video: str, save_dir: str = "") -> dict:
|
||||
"""
|
||||
保存剪辑后的视频
|
||||
Args:
|
||||
timestamp: 需要裁剪的单个时间戳,如:'00:36-00:40'
|
||||
origin_video: 原视频路径
|
||||
save_dir: 存储目录
|
||||
|
||||
Returns:
|
||||
裁剪后的视频路径
|
||||
"""
|
||||
if not save_dir:
|
||||
save_dir = utils.storage_dir("cache_videos")
|
||||
|
||||
if not os.path.exists(save_dir):
|
||||
os.makedirs(save_dir)
|
||||
|
||||
# url_hash = utils.md5(str(uuid.uuid4()))
|
||||
video_id = f"vid-{timestamp.replace(':', '_')}"
|
||||
video_path = f"{save_dir}/{video_id}.mp4"
|
||||
|
||||
if os.path.exists(video_path) and os.path.getsize(video_path) > 0:
|
||||
logger.info(f"video already exists: {video_path}")
|
||||
return {timestamp: video_path}
|
||||
|
||||
# 剪辑视频
|
||||
start, end = utils.split_timestamp(timestamp)
|
||||
video = VideoFileClip(origin_video).subclip(start, end)
|
||||
video.write_videofile(video_path)
|
||||
|
||||
if os.path.getsize(video_path) > 0 and os.path.exists(video_path):
|
||||
try:
|
||||
clip = VideoFileClip(video_path)
|
||||
duration = clip.duration
|
||||
fps = clip.fps
|
||||
clip.close()
|
||||
if duration > 0 and fps > 0:
|
||||
return {timestamp: video_path}
|
||||
except Exception as e:
|
||||
try:
|
||||
os.remove(video_path)
|
||||
except Exception as e:
|
||||
logger.warning(str(e))
|
||||
logger.warning(f"无效的视频文件: {video_path}")
|
||||
return {}
|
||||
|
||||
|
||||
def clip_videos(task_id: str, timestamp_terms: List[str], origin_video: str, ) -> dict:
|
||||
"""
|
||||
剪辑视频
|
||||
Args:
|
||||
task_id: 任务id
|
||||
timestamp_terms: 需要剪辑的时间戳列表,如:['00:00-00:20', '00:36-00:40', '07:07-07:22']
|
||||
origin_video: 原视频路径
|
||||
|
||||
Returns:
|
||||
剪辑后的视频路径
|
||||
"""
|
||||
video_paths = {}
|
||||
for item in timestamp_terms:
|
||||
logger.info(f"需要裁剪 '{origin_video}' 为 {len(timestamp_terms)} 个视频")
|
||||
material_directory = config.app.get("material_directory", "").strip()
|
||||
if material_directory == "task":
|
||||
material_directory = utils.task_dir(task_id)
|
||||
elif material_directory and not os.path.isdir(material_directory):
|
||||
material_directory = ""
|
||||
|
||||
try:
|
||||
logger.info(f"clip video: {item}")
|
||||
saved_video_path = save_clip_video(timestamp=item, origin_video=origin_video, save_dir=material_directory)
|
||||
if saved_video_path:
|
||||
logger.info(f"video saved: {saved_video_path}")
|
||||
video_paths.update(saved_video_path)
|
||||
except Exception as e:
|
||||
logger.error(f"视频裁剪失败: {utils.to_json(item)} => {str(e)}")
|
||||
return {}
|
||||
logger.success(f"裁剪 {len(video_paths)} videos")
|
||||
return video_paths
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
download_videos(
|
||||
"test123", ["Money Exchange Medium"], audio_duration=100, source="pixabay"
|
||||
)
|
||||
122
app/services/state.py
Normal file
@ -0,0 +1,122 @@
|
||||
import ast
|
||||
from abc import ABC, abstractmethod
|
||||
from app.config import config
|
||||
from app.models import const
|
||||
|
||||
|
||||
# Base class for state management
|
||||
class BaseState(ABC):
|
||||
@abstractmethod
|
||||
def update_task(self, task_id: str, state: int, progress: int = 0, **kwargs):
|
||||
pass
|
||||
|
||||
@abstractmethod
|
||||
def get_task(self, task_id: str):
|
||||
pass
|
||||
|
||||
|
||||
# Memory state management
|
||||
class MemoryState(BaseState):
|
||||
def __init__(self):
|
||||
self._tasks = {}
|
||||
|
||||
def update_task(
|
||||
self,
|
||||
task_id: str,
|
||||
state: int = const.TASK_STATE_PROCESSING,
|
||||
progress: int = 0,
|
||||
**kwargs,
|
||||
):
|
||||
progress = int(progress)
|
||||
if progress > 100:
|
||||
progress = 100
|
||||
|
||||
self._tasks[task_id] = {
|
||||
"state": state,
|
||||
"progress": progress,
|
||||
**kwargs,
|
||||
}
|
||||
|
||||
def get_task(self, task_id: str):
|
||||
return self._tasks.get(task_id, None)
|
||||
|
||||
def delete_task(self, task_id: str):
|
||||
if task_id in self._tasks:
|
||||
del self._tasks[task_id]
|
||||
|
||||
|
||||
# Redis state management
|
||||
class RedisState(BaseState):
|
||||
def __init__(self, host="localhost", port=6379, db=0, password=None):
|
||||
import redis
|
||||
|
||||
self._redis = redis.StrictRedis(host=host, port=port, db=db, password=password)
|
||||
|
||||
def update_task(
|
||||
self,
|
||||
task_id: str,
|
||||
state: int = const.TASK_STATE_PROCESSING,
|
||||
progress: int = 0,
|
||||
**kwargs,
|
||||
):
|
||||
progress = int(progress)
|
||||
if progress > 100:
|
||||
progress = 100
|
||||
|
||||
fields = {
|
||||
"state": state,
|
||||
"progress": progress,
|
||||
**kwargs,
|
||||
}
|
||||
|
||||
for field, value in fields.items():
|
||||
self._redis.hset(task_id, field, str(value))
|
||||
|
||||
def get_task(self, task_id: str):
|
||||
task_data = self._redis.hgetall(task_id)
|
||||
if not task_data:
|
||||
return None
|
||||
|
||||
task = {
|
||||
key.decode("utf-8"): self._convert_to_original_type(value)
|
||||
for key, value in task_data.items()
|
||||
}
|
||||
return task
|
||||
|
||||
def delete_task(self, task_id: str):
|
||||
self._redis.delete(task_id)
|
||||
|
||||
@staticmethod
|
||||
def _convert_to_original_type(value):
|
||||
"""
|
||||
Convert the value from byte string to its original data type.
|
||||
You can extend this method to handle other data types as needed.
|
||||
"""
|
||||
value_str = value.decode("utf-8")
|
||||
|
||||
try:
|
||||
# try to convert byte string array to list
|
||||
return ast.literal_eval(value_str)
|
||||
except (ValueError, SyntaxError):
|
||||
pass
|
||||
|
||||
if value_str.isdigit():
|
||||
return int(value_str)
|
||||
# Add more conversions here if needed
|
||||
return value_str
|
||||
|
||||
|
||||
# Global state
|
||||
_enable_redis = config.app.get("enable_redis", False)
|
||||
_redis_host = config.app.get("redis_host", "localhost")
|
||||
_redis_port = config.app.get("redis_port", 6379)
|
||||
_redis_db = config.app.get("redis_db", 0)
|
||||
_redis_password = config.app.get("redis_password", None)
|
||||
|
||||
state = (
|
||||
RedisState(
|
||||
host=_redis_host, port=_redis_port, db=_redis_db, password=_redis_password
|
||||
)
|
||||
if _enable_redis
|
||||
else MemoryState()
|
||||
)
|
||||
299
app/services/subtitle.py
Normal file
@ -0,0 +1,299 @@
|
||||
import json
|
||||
import os.path
|
||||
import re
|
||||
|
||||
from faster_whisper import WhisperModel
|
||||
from timeit import default_timer as timer
|
||||
from loguru import logger
|
||||
|
||||
from app.config import config
|
||||
from app.utils import utils
|
||||
|
||||
model_size = config.whisper.get("model_size", "large-v3")
|
||||
device = config.whisper.get("device", "cpu")
|
||||
compute_type = config.whisper.get("compute_type", "int8")
|
||||
model = None
|
||||
|
||||
|
||||
def create(audio_file, subtitle_file: str = ""):
|
||||
global model
|
||||
if not model:
|
||||
model_path = f"{utils.root_dir()}/models/whisper-{model_size}"
|
||||
model_bin_file = f"{model_path}/model.bin"
|
||||
if not os.path.isdir(model_path) or not os.path.isfile(model_bin_file):
|
||||
model_path = model_size
|
||||
|
||||
logger.info(
|
||||
f"loading model: {model_path}, device: {device}, compute_type: {compute_type}"
|
||||
)
|
||||
try:
|
||||
model = WhisperModel(
|
||||
model_size_or_path=model_path, device=device, compute_type=compute_type
|
||||
)
|
||||
except Exception as e:
|
||||
logger.error(
|
||||
f"failed to load model: {e} \n\n"
|
||||
f"********************************************\n"
|
||||
f"this may be caused by network issue. \n"
|
||||
f"please download the model manually and put it in the 'models' folder. \n"
|
||||
f"see [README.md FAQ](https://github.com/harry0703/NarratoAI) for more details.\n"
|
||||
f"********************************************\n\n"
|
||||
)
|
||||
return None
|
||||
|
||||
logger.info(f"start, output file: {subtitle_file}")
|
||||
if not subtitle_file:
|
||||
subtitle_file = f"{audio_file}.srt"
|
||||
|
||||
segments, info = model.transcribe(
|
||||
audio_file,
|
||||
beam_size=5,
|
||||
word_timestamps=True,
|
||||
vad_filter=True,
|
||||
vad_parameters=dict(min_silence_duration_ms=500),
|
||||
)
|
||||
|
||||
logger.info(
|
||||
f"detected language: '{info.language}', probability: {info.language_probability:.2f}"
|
||||
)
|
||||
|
||||
start = timer()
|
||||
subtitles = []
|
||||
|
||||
def recognized(seg_text, seg_start, seg_end):
|
||||
seg_text = seg_text.strip()
|
||||
if not seg_text:
|
||||
return
|
||||
|
||||
msg = "[%.2fs -> %.2fs] %s" % (seg_start, seg_end, seg_text)
|
||||
logger.debug(msg)
|
||||
|
||||
subtitles.append(
|
||||
{"msg": seg_text, "start_time": seg_start, "end_time": seg_end}
|
||||
)
|
||||
|
||||
for segment in segments:
|
||||
words_idx = 0
|
||||
words_len = len(segment.words)
|
||||
|
||||
seg_start = 0
|
||||
seg_end = 0
|
||||
seg_text = ""
|
||||
|
||||
if segment.words:
|
||||
is_segmented = False
|
||||
for word in segment.words:
|
||||
if not is_segmented:
|
||||
seg_start = word.start
|
||||
is_segmented = True
|
||||
|
||||
seg_end = word.end
|
||||
# 如果包含标点,则断句
|
||||
seg_text += word.word
|
||||
|
||||
if utils.str_contains_punctuation(word.word):
|
||||
# remove last char
|
||||
seg_text = seg_text[:-1]
|
||||
if not seg_text:
|
||||
continue
|
||||
|
||||
recognized(seg_text, seg_start, seg_end)
|
||||
|
||||
is_segmented = False
|
||||
seg_text = ""
|
||||
|
||||
if words_idx == 0 and segment.start < word.start:
|
||||
seg_start = word.start
|
||||
if words_idx == (words_len - 1) and segment.end > word.end:
|
||||
seg_end = word.end
|
||||
words_idx += 1
|
||||
|
||||
if not seg_text:
|
||||
continue
|
||||
|
||||
recognized(seg_text, seg_start, seg_end)
|
||||
|
||||
end = timer()
|
||||
|
||||
diff = end - start
|
||||
logger.info(f"complete, elapsed: {diff:.2f} s")
|
||||
|
||||
idx = 1
|
||||
lines = []
|
||||
for subtitle in subtitles:
|
||||
text = subtitle.get("msg")
|
||||
if text:
|
||||
lines.append(
|
||||
utils.text_to_srt(
|
||||
idx, text, subtitle.get("start_time"), subtitle.get("end_time")
|
||||
)
|
||||
)
|
||||
idx += 1
|
||||
|
||||
sub = "\n".join(lines) + "\n"
|
||||
with open(subtitle_file, "w", encoding="utf-8") as f:
|
||||
f.write(sub)
|
||||
logger.info(f"subtitle file created: {subtitle_file}")
|
||||
|
||||
|
||||
def file_to_subtitles(filename):
|
||||
if not filename or not os.path.isfile(filename):
|
||||
return []
|
||||
|
||||
times_texts = []
|
||||
current_times = None
|
||||
current_text = ""
|
||||
index = 0
|
||||
with open(filename, "r", encoding="utf-8") as f:
|
||||
for line in f:
|
||||
times = re.findall("([0-9]*:[0-9]*:[0-9]*,[0-9]*)", line)
|
||||
if times:
|
||||
current_times = line
|
||||
elif line.strip() == "" and current_times:
|
||||
index += 1
|
||||
times_texts.append((index, current_times.strip(), current_text.strip()))
|
||||
current_times, current_text = None, ""
|
||||
elif current_times:
|
||||
current_text += line
|
||||
return times_texts
|
||||
|
||||
|
||||
def levenshtein_distance(s1, s2):
|
||||
if len(s1) < len(s2):
|
||||
return levenshtein_distance(s2, s1)
|
||||
|
||||
if len(s2) == 0:
|
||||
return len(s1)
|
||||
|
||||
previous_row = range(len(s2) + 1)
|
||||
for i, c1 in enumerate(s1):
|
||||
current_row = [i + 1]
|
||||
for j, c2 in enumerate(s2):
|
||||
insertions = previous_row[j + 1] + 1
|
||||
deletions = current_row[j] + 1
|
||||
substitutions = previous_row[j] + (c1 != c2)
|
||||
current_row.append(min(insertions, deletions, substitutions))
|
||||
previous_row = current_row
|
||||
|
||||
return previous_row[-1]
|
||||
|
||||
|
||||
def similarity(a, b):
|
||||
distance = levenshtein_distance(a.lower(), b.lower())
|
||||
max_length = max(len(a), len(b))
|
||||
return 1 - (distance / max_length)
|
||||
|
||||
|
||||
def correct(subtitle_file, video_script):
|
||||
subtitle_items = file_to_subtitles(subtitle_file)
|
||||
script_lines = utils.split_string_by_punctuations(video_script)
|
||||
|
||||
corrected = False
|
||||
new_subtitle_items = []
|
||||
script_index = 0
|
||||
subtitle_index = 0
|
||||
|
||||
while script_index < len(script_lines) and subtitle_index < len(subtitle_items):
|
||||
script_line = script_lines[script_index].strip()
|
||||
subtitle_line = subtitle_items[subtitle_index][2].strip()
|
||||
|
||||
if script_line == subtitle_line:
|
||||
new_subtitle_items.append(subtitle_items[subtitle_index])
|
||||
script_index += 1
|
||||
subtitle_index += 1
|
||||
else:
|
||||
combined_subtitle = subtitle_line
|
||||
start_time = subtitle_items[subtitle_index][1].split(" --> ")[0]
|
||||
end_time = subtitle_items[subtitle_index][1].split(" --> ")[1]
|
||||
next_subtitle_index = subtitle_index + 1
|
||||
|
||||
while next_subtitle_index < len(subtitle_items):
|
||||
next_subtitle = subtitle_items[next_subtitle_index][2].strip()
|
||||
if similarity(
|
||||
script_line, combined_subtitle + " " + next_subtitle
|
||||
) > similarity(script_line, combined_subtitle):
|
||||
combined_subtitle += " " + next_subtitle
|
||||
end_time = subtitle_items[next_subtitle_index][1].split(" --> ")[1]
|
||||
next_subtitle_index += 1
|
||||
else:
|
||||
break
|
||||
|
||||
if similarity(script_line, combined_subtitle) > 0.8:
|
||||
logger.warning(
|
||||
f"Merged/Corrected - Script: {script_line}, Subtitle: {combined_subtitle}"
|
||||
)
|
||||
new_subtitle_items.append(
|
||||
(
|
||||
len(new_subtitle_items) + 1,
|
||||
f"{start_time} --> {end_time}",
|
||||
script_line,
|
||||
)
|
||||
)
|
||||
corrected = True
|
||||
else:
|
||||
logger.warning(
|
||||
f"Mismatch - Script: {script_line}, Subtitle: {combined_subtitle}"
|
||||
)
|
||||
new_subtitle_items.append(
|
||||
(
|
||||
len(new_subtitle_items) + 1,
|
||||
f"{start_time} --> {end_time}",
|
||||
script_line,
|
||||
)
|
||||
)
|
||||
corrected = True
|
||||
|
||||
script_index += 1
|
||||
subtitle_index = next_subtitle_index
|
||||
|
||||
# 处理剩余的脚本行
|
||||
while script_index < len(script_lines):
|
||||
logger.warning(f"Extra script line: {script_lines[script_index]}")
|
||||
if subtitle_index < len(subtitle_items):
|
||||
new_subtitle_items.append(
|
||||
(
|
||||
len(new_subtitle_items) + 1,
|
||||
subtitle_items[subtitle_index][1],
|
||||
script_lines[script_index],
|
||||
)
|
||||
)
|
||||
subtitle_index += 1
|
||||
else:
|
||||
new_subtitle_items.append(
|
||||
(
|
||||
len(new_subtitle_items) + 1,
|
||||
"00:00:00,000 --> 00:00:00,000",
|
||||
script_lines[script_index],
|
||||
)
|
||||
)
|
||||
script_index += 1
|
||||
corrected = True
|
||||
|
||||
if corrected:
|
||||
with open(subtitle_file, "w", encoding="utf-8") as fd:
|
||||
for i, item in enumerate(new_subtitle_items):
|
||||
fd.write(f"{i + 1}\n{item[1]}\n{item[2]}\n\n")
|
||||
logger.info("Subtitle corrected")
|
||||
else:
|
||||
logger.success("Subtitle is correct")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
task_id = "c12fd1e6-4b0a-4d65-a075-c87abe35a072"
|
||||
task_dir = utils.task_dir(task_id)
|
||||
subtitle_file = f"{task_dir}/subtitle.srt"
|
||||
audio_file = f"{task_dir}/audio.mp3"
|
||||
|
||||
subtitles = file_to_subtitles(subtitle_file)
|
||||
print(subtitles)
|
||||
|
||||
script_file = f"{task_dir}/script.json"
|
||||
with open(script_file, "r") as f:
|
||||
script_content = f.read()
|
||||
s = json.loads(script_content)
|
||||
script = s.get("script")
|
||||
|
||||
correct(subtitle_file, script)
|
||||
|
||||
subtitle_file = f"{task_dir}/subtitle-test.srt"
|
||||
create(audio_file, subtitle_file)
|
||||
473
app/services/task.py
Normal file
@ -0,0 +1,473 @@
|
||||
import math
|
||||
import json
|
||||
import os.path
|
||||
import re
|
||||
from os import path
|
||||
|
||||
from edge_tts import SubMaker
|
||||
from loguru import logger
|
||||
|
||||
from app.config import config
|
||||
from app.models import const
|
||||
from app.models.schema import VideoConcatMode, VideoParams, VideoClipParams
|
||||
from app.services import llm, material, subtitle, video, voice
|
||||
from app.services import state as sm
|
||||
from app.utils import utils
|
||||
|
||||
|
||||
def generate_script(task_id, params):
|
||||
logger.info("\n\n## generating video script")
|
||||
video_script = params.video_script.strip()
|
||||
if not video_script:
|
||||
video_script = llm.generate_script(
|
||||
video_subject=params.video_subject,
|
||||
language=params.video_language,
|
||||
paragraph_number=params.paragraph_number,
|
||||
)
|
||||
else:
|
||||
logger.debug(f"video script: \n{video_script}")
|
||||
|
||||
if not video_script:
|
||||
sm.state.update_task(task_id, state=const.TASK_STATE_FAILED)
|
||||
logger.error("failed to generate video script.")
|
||||
return None
|
||||
|
||||
return video_script
|
||||
|
||||
|
||||
def generate_terms(task_id, params, video_script):
|
||||
logger.info("\n\n## generating video terms")
|
||||
video_terms = params.video_terms
|
||||
if not video_terms:
|
||||
video_terms = llm.generate_terms(
|
||||
video_subject=params.video_subject, video_script=video_script, amount=5
|
||||
)
|
||||
else:
|
||||
if isinstance(video_terms, str):
|
||||
video_terms = [term.strip() for term in re.split(r"[,,]", video_terms)]
|
||||
elif isinstance(video_terms, list):
|
||||
video_terms = [term.strip() for term in video_terms]
|
||||
else:
|
||||
raise ValueError("video_terms must be a string or a list of strings.")
|
||||
|
||||
logger.debug(f"video terms: {utils.to_json(video_terms)}")
|
||||
|
||||
if not video_terms:
|
||||
sm.state.update_task(task_id, state=const.TASK_STATE_FAILED)
|
||||
logger.error("failed to generate video terms.")
|
||||
return None
|
||||
|
||||
return video_terms
|
||||
|
||||
|
||||
def save_script_data(task_id, video_script, video_terms, params):
|
||||
script_file = path.join(utils.task_dir(task_id), "script.json")
|
||||
script_data = {
|
||||
"script": video_script,
|
||||
"search_terms": video_terms,
|
||||
"params": params,
|
||||
}
|
||||
|
||||
with open(script_file, "w", encoding="utf-8") as f:
|
||||
f.write(utils.to_json(script_data))
|
||||
|
||||
|
||||
def generate_audio(task_id, params, video_script):
|
||||
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:
|
||||
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, None
|
||||
|
||||
audio_duration = math.ceil(voice.get_audio_duration(sub_maker))
|
||||
return audio_file, audio_duration, sub_maker
|
||||
|
||||
|
||||
def generate_subtitle(task_id, params, video_script, sub_maker, audio_file):
|
||||
if not params.subtitle_enabled:
|
||||
return ""
|
||||
|
||||
subtitle_path = path.join(utils.task_dir(task_id), "subtitle.srt")
|
||||
subtitle_provider = config.app.get("subtitle_provider", "").strip().lower()
|
||||
logger.info(f"\n\n## generating subtitle, provider: {subtitle_provider}")
|
||||
|
||||
subtitle_fallback = False
|
||||
if subtitle_provider == "edge":
|
||||
voice.create_subtitle(
|
||||
text=video_script, sub_maker=sub_maker, subtitle_file=subtitle_path
|
||||
)
|
||||
if not os.path.exists(subtitle_path):
|
||||
subtitle_fallback = True
|
||||
logger.warning("subtitle file not found, fallback to whisper")
|
||||
|
||||
if subtitle_provider == "whisper" or subtitle_fallback:
|
||||
subtitle.create(audio_file=audio_file, subtitle_file=subtitle_path)
|
||||
logger.info("\n\n## correcting subtitle")
|
||||
subtitle.correct(subtitle_file=subtitle_path, video_script=video_script)
|
||||
|
||||
subtitle_lines = subtitle.file_to_subtitles(subtitle_path)
|
||||
if not subtitle_lines:
|
||||
logger.warning(f"subtitle file is invalid: {subtitle_path}")
|
||||
return ""
|
||||
|
||||
return subtitle_path
|
||||
|
||||
|
||||
def get_video_materials(task_id, params, video_terms, audio_duration):
|
||||
if params.video_source == "local":
|
||||
logger.info("\n\n## preprocess local materials")
|
||||
materials = video.preprocess_video(
|
||||
materials=params.video_materials, clip_duration=params.video_clip_duration
|
||||
)
|
||||
if not materials:
|
||||
sm.state.update_task(task_id, state=const.TASK_STATE_FAILED)
|
||||
logger.error(
|
||||
"no valid materials found, please check the materials and try again."
|
||||
)
|
||||
return None
|
||||
return [material_info.url for material_info in materials]
|
||||
else:
|
||||
logger.info(f"\n\n## downloading videos from {params.video_source}")
|
||||
downloaded_videos = material.download_videos(
|
||||
task_id=task_id,
|
||||
search_terms=video_terms,
|
||||
source=params.video_source,
|
||||
video_aspect=params.video_aspect,
|
||||
video_contact_mode=params.video_concat_mode,
|
||||
audio_duration=audio_duration * params.video_count,
|
||||
max_clip_duration=params.video_clip_duration,
|
||||
)
|
||||
if not downloaded_videos:
|
||||
sm.state.update_task(task_id, state=const.TASK_STATE_FAILED)
|
||||
logger.error(
|
||||
"failed to download videos, maybe the network is not available. if you are in China, please use a VPN."
|
||||
)
|
||||
return None
|
||||
return downloaded_videos
|
||||
|
||||
|
||||
def generate_final_videos(
|
||||
task_id, params, downloaded_videos, audio_file, subtitle_path
|
||||
):
|
||||
final_video_paths = []
|
||||
combined_video_paths = []
|
||||
video_concat_mode = (
|
||||
params.video_concat_mode if params.video_count == 1 else VideoConcatMode.random
|
||||
)
|
||||
|
||||
_progress = 50
|
||||
for i in range(params.video_count):
|
||||
index = i + 1
|
||||
combined_video_path = path.join(
|
||||
utils.task_dir(task_id), f"combined-{index}.mp4"
|
||||
)
|
||||
logger.info(f"\n\n## combining video: {index} => {combined_video_path}")
|
||||
video.combine_videos(
|
||||
combined_video_path=combined_video_path,
|
||||
video_paths=downloaded_videos,
|
||||
audio_file=audio_file,
|
||||
video_aspect=params.video_aspect,
|
||||
video_concat_mode=video_concat_mode,
|
||||
max_clip_duration=params.video_clip_duration,
|
||||
threads=params.n_threads,
|
||||
)
|
||||
|
||||
_progress += 50 / params.video_count / 2
|
||||
sm.state.update_task(task_id, progress=_progress)
|
||||
|
||||
final_video_path = path.join(utils.task_dir(task_id), f"final-{index}.mp4")
|
||||
|
||||
logger.info(f"\n\n## generating video: {index} => {final_video_path}")
|
||||
video.generate_video(
|
||||
video_path=combined_video_path,
|
||||
audio_path=audio_file,
|
||||
subtitle_path=subtitle_path,
|
||||
output_file=final_video_path,
|
||||
params=params,
|
||||
)
|
||||
|
||||
_progress += 50 / params.video_count / 2
|
||||
sm.state.update_task(task_id, progress=_progress)
|
||||
|
||||
final_video_paths.append(final_video_path)
|
||||
combined_video_paths.append(combined_video_path)
|
||||
|
||||
return final_video_paths, combined_video_paths
|
||||
|
||||
|
||||
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:
|
||||
sm.state.update_task(task_id, state=const.TASK_STATE_FAILED)
|
||||
return
|
||||
|
||||
sm.state.update_task(task_id, state=const.TASK_STATE_PROCESSING, progress=10)
|
||||
|
||||
if stop_at == "script":
|
||||
sm.state.update_task(
|
||||
task_id, state=const.TASK_STATE_COMPLETE, progress=100, script=video_script
|
||||
)
|
||||
return {"script": video_script}
|
||||
|
||||
# 2. Generate terms
|
||||
video_terms = ""
|
||||
if params.video_source != "local":
|
||||
video_terms = generate_terms(task_id, params, video_script)
|
||||
if not video_terms:
|
||||
sm.state.update_task(task_id, state=const.TASK_STATE_FAILED)
|
||||
return
|
||||
|
||||
save_script_data(task_id, video_script, video_terms, params)
|
||||
|
||||
if stop_at == "terms":
|
||||
sm.state.update_task(
|
||||
task_id, state=const.TASK_STATE_COMPLETE, progress=100, terms=video_terms
|
||||
)
|
||||
return {"script": video_script, "terms": video_terms}
|
||||
|
||||
sm.state.update_task(task_id, state=const.TASK_STATE_PROCESSING, progress=20)
|
||||
|
||||
# 3. Generate audio
|
||||
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
|
||||
|
||||
sm.state.update_task(task_id, state=const.TASK_STATE_PROCESSING, progress=30)
|
||||
|
||||
if stop_at == "audio":
|
||||
sm.state.update_task(
|
||||
task_id,
|
||||
state=const.TASK_STATE_COMPLETE,
|
||||
progress=100,
|
||||
audio_file=audio_file,
|
||||
)
|
||||
return {"audio_file": audio_file, "audio_duration": audio_duration}
|
||||
|
||||
# 4. Generate subtitle
|
||||
subtitle_path = generate_subtitle(task_id, params, video_script, sub_maker, audio_file)
|
||||
|
||||
if stop_at == "subtitle":
|
||||
sm.state.update_task(
|
||||
task_id,
|
||||
state=const.TASK_STATE_COMPLETE,
|
||||
progress=100,
|
||||
subtitle_path=subtitle_path,
|
||||
)
|
||||
return {"subtitle_path": subtitle_path}
|
||||
|
||||
sm.state.update_task(task_id, state=const.TASK_STATE_PROCESSING, progress=40)
|
||||
|
||||
# 5. Get video materials
|
||||
downloaded_videos = get_video_materials(
|
||||
task_id, params, video_terms, audio_duration
|
||||
)
|
||||
if not downloaded_videos:
|
||||
sm.state.update_task(task_id, state=const.TASK_STATE_FAILED)
|
||||
return
|
||||
|
||||
if stop_at == "materials":
|
||||
sm.state.update_task(
|
||||
task_id,
|
||||
state=const.TASK_STATE_COMPLETE,
|
||||
progress=100,
|
||||
materials=downloaded_videos,
|
||||
)
|
||||
return {"materials": downloaded_videos}
|
||||
|
||||
sm.state.update_task(task_id, state=const.TASK_STATE_PROCESSING, progress=50)
|
||||
|
||||
# 6. Generate final videos
|
||||
final_video_paths, combined_video_paths = generate_final_videos(
|
||||
task_id, params, downloaded_videos, audio_file, subtitle_path
|
||||
)
|
||||
|
||||
if not final_video_paths:
|
||||
sm.state.update_task(task_id, state=const.TASK_STATE_FAILED)
|
||||
return
|
||||
|
||||
logger.success(
|
||||
f"task {task_id} finished, generated {len(final_video_paths)} videos."
|
||||
)
|
||||
|
||||
kwargs = {
|
||||
"videos": final_video_paths,
|
||||
"combined_videos": combined_video_paths,
|
||||
"script": video_script,
|
||||
"terms": video_terms,
|
||||
"audio_file": audio_file,
|
||||
"audio_duration": audio_duration,
|
||||
"subtitle_path": subtitle_path,
|
||||
"materials": downloaded_videos,
|
||||
}
|
||||
sm.state.update_task(
|
||||
task_id, state=const.TASK_STATE_COMPLETE, progress=100, **kwargs
|
||||
)
|
||||
return kwargs
|
||||
|
||||
|
||||
def start_subclip(task_id, params: VideoClipParams, subclip_path_videos):
|
||||
"""
|
||||
后台任务(自动剪辑视频进行剪辑)
|
||||
"""
|
||||
logger.info(f"\n\n## 开始任务: {task_id}")
|
||||
sm.state.update_task(task_id, state=const.TASK_STATE_PROCESSING, progress=5)
|
||||
|
||||
voice_name = voice.parse_voice_name(params.voice_name)
|
||||
# voice_name = 'zh-CN-XiaoyiNeural'
|
||||
paragraph_number = params.paragraph_number
|
||||
n_threads = params.n_threads
|
||||
max_clip_duration = params.video_clip_duration
|
||||
|
||||
logger.info("\n\n## 1. 读取json")
|
||||
# video_script = params.video_script.strip()
|
||||
# 搜索 ../storage 目录下 名称为 video_subject 的docx文件,并读出所有字符串
|
||||
# video_script_path = path.join('E:\\Projects\\linyq\\MoneyPrinterLin\\txt.txt\\txt2.json')
|
||||
video_script_path = path.join(params.video_clip_json)
|
||||
# 判断json文件是否存在
|
||||
if path.exists(video_script_path):
|
||||
# 读取json文件内容,并转为dict
|
||||
with open(video_script_path, "r", encoding="utf-8") as f:
|
||||
list_script = json.load(f)
|
||||
video_list = [i['narration'] for i in list_script]
|
||||
time_list = [i['timestamp'] for i in list_script]
|
||||
|
||||
video_script = " ".join(video_list)
|
||||
logger.debug(f"原json脚本: \n{video_script}")
|
||||
logger.debug(f"原json时间戳: \n{time_list}")
|
||||
|
||||
else:
|
||||
print("#@#@#@", params.video_clip_json)
|
||||
raise ValueError("解说文案不存在!检查文案名称是否正确。")
|
||||
|
||||
# video_script = llm.text_polishing(context=video_script, language=params.video_language)
|
||||
# logger.debug(f"润色后的视频脚本: \n{video_script}")
|
||||
# sm.state.update_task(task_id, state=const.TASK_STATE_PROCESSING, progress=10)
|
||||
|
||||
logger.info("\n\n## 2. 生成音频")
|
||||
audio_file = path.join(utils.task_dir(task_id), f"audio.mp3")
|
||||
sub_maker = voice.tts(text=video_script, voice_name=voice_name, voice_file=audio_file, voice_rate=params.voice_rate)
|
||||
if sub_maker is None:
|
||||
sm.state.update_task(task_id, state=const.TASK_STATE_FAILED)
|
||||
logger.error(
|
||||
"无法生成音频,可能是网络不可用。如果您在中国,请使用VPN。或者手动选择 zh-CN-Yunjian-男性 音频")
|
||||
return
|
||||
|
||||
audio_duration = voice.get_audio_duration(sub_maker)
|
||||
audio_duration = math.ceil(audio_duration)
|
||||
|
||||
sm.state.update_task(task_id, state=const.TASK_STATE_PROCESSING, progress=30)
|
||||
|
||||
subtitle_path = ""
|
||||
if params.subtitle_enabled:
|
||||
subtitle_path = path.join(utils.task_dir(task_id), f"subtitle.srt")
|
||||
subtitle_provider = config.app.get("subtitle_provider", "").strip().lower()
|
||||
logger.info(f"\n\n## 3. 生成字幕、提供程序是: {subtitle_provider}")
|
||||
subtitle_fallback = False
|
||||
if subtitle_provider == "edge":
|
||||
voice.create_subtitle(text=video_script, sub_maker=sub_maker, subtitle_file=subtitle_path)
|
||||
if not os.path.exists(subtitle_path):
|
||||
subtitle_fallback = True
|
||||
logger.warning("找不到字幕文件,回退到whisper")
|
||||
|
||||
if subtitle_provider == "whisper" or subtitle_fallback:
|
||||
subtitle.create(audio_file=audio_file, subtitle_file=subtitle_path)
|
||||
logger.info("\n\n## 更正字幕")
|
||||
subtitle.correct(subtitle_file=subtitle_path, video_script=video_script)
|
||||
|
||||
subtitle_lines = subtitle.file_to_subtitles(subtitle_path)
|
||||
if not subtitle_lines:
|
||||
logger.warning(f"字幕文件无效: {subtitle_path}")
|
||||
subtitle_path = ""
|
||||
|
||||
sm.state.update_task(task_id, state=const.TASK_STATE_PROCESSING, progress=40)
|
||||
|
||||
logger.info("\n\n## 4. 裁剪视频")
|
||||
subclip_videos = [x for x in subclip_path_videos.values()]
|
||||
# subclip_videos = material.clip_videos(task_id=task_id,
|
||||
# timestamp_terms=time_list,
|
||||
# origin_video=params.video_origin_path
|
||||
# )
|
||||
logger.debug(f"\n\n## 裁剪后的视频文件列表: \n{subclip_videos}")
|
||||
|
||||
if not subclip_videos:
|
||||
sm.state.update_task(task_id, state=const.TASK_STATE_FAILED)
|
||||
logger.error(
|
||||
"裁剪视频失败,可能是 ImageMagick 不可用")
|
||||
return
|
||||
|
||||
sm.state.update_task(task_id, state=const.TASK_STATE_PROCESSING, progress=50)
|
||||
|
||||
final_video_paths = []
|
||||
combined_video_paths = []
|
||||
|
||||
_progress = 50
|
||||
for i in range(params.video_count):
|
||||
index = i + 1
|
||||
combined_video_path = path.join(utils.task_dir(task_id), f"combined-{index}.mp4")
|
||||
logger.info(f"\n\n## 5. 合并视频: {index} => {combined_video_path}")
|
||||
video.combine_clip_videos(combined_video_path=combined_video_path,
|
||||
video_paths=subclip_videos,
|
||||
video_script_list=video_list,
|
||||
audio_file=audio_file,
|
||||
video_aspect=params.video_aspect,
|
||||
threads=n_threads)
|
||||
|
||||
_progress += 50 / params.video_count / 2
|
||||
sm.state.update_task(task_id, progress=_progress)
|
||||
|
||||
final_video_path = path.join(utils.task_dir(task_id), f"final-{index}.mp4")
|
||||
|
||||
logger.info(f"\n\n## 6. 生成视频: {index} => {final_video_path}")
|
||||
# 把所有东西合到在一起
|
||||
video.generate_video(video_path=combined_video_path,
|
||||
audio_path=audio_file,
|
||||
subtitle_path=subtitle_path,
|
||||
output_file=final_video_path,
|
||||
params=params,
|
||||
)
|
||||
|
||||
_progress += 50 / params.video_count / 2
|
||||
sm.state.update_task(task_id, progress=_progress)
|
||||
|
||||
final_video_paths.append(final_video_path)
|
||||
combined_video_paths.append(combined_video_path)
|
||||
|
||||
logger.success(f"任务 {task_id} 已完成, 生成 {len(final_video_paths)} 个视频.")
|
||||
|
||||
kwargs = {
|
||||
"videos": final_video_paths,
|
||||
"combined_videos": combined_video_paths
|
||||
}
|
||||
sm.state.update_task(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")
|
||||
520
app/services/video.py
Normal file
@ -0,0 +1,520 @@
|
||||
import glob
|
||||
import random
|
||||
from typing import List
|
||||
from typing import Union
|
||||
|
||||
from loguru import logger
|
||||
from moviepy.editor import *
|
||||
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, VideoClipParams
|
||||
from app.utils import utils
|
||||
|
||||
|
||||
def get_bgm_file(bgm_type: str = "random", bgm_file: str = ""):
|
||||
if not bgm_type:
|
||||
return ""
|
||||
|
||||
if bgm_file and os.path.exists(bgm_file):
|
||||
return bgm_file
|
||||
|
||||
if bgm_type == "random":
|
||||
suffix = "*.mp3"
|
||||
song_dir = utils.song_dir()
|
||||
files = glob.glob(os.path.join(song_dir, suffix))
|
||||
return random.choice(files)
|
||||
|
||||
return ""
|
||||
|
||||
|
||||
def combine_videos(
|
||||
combined_video_path: str,
|
||||
video_paths: List[str],
|
||||
audio_file: str,
|
||||
video_aspect: VideoAspect = VideoAspect.portrait,
|
||||
video_concat_mode: VideoConcatMode = VideoConcatMode.random,
|
||||
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")
|
||||
# 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")
|
||||
output_dir = os.path.dirname(combined_video_path)
|
||||
|
||||
aspect = VideoAspect(video_aspect)
|
||||
video_width, video_height = aspect.to_resolution()
|
||||
|
||||
clips = []
|
||||
video_duration = 0
|
||||
|
||||
raw_clips = []
|
||||
for video_path in video_paths:
|
||||
clip = VideoFileClip(video_path).without_audio()
|
||||
clip_duration = clip.duration
|
||||
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
|
||||
if video_concat_mode.value == VideoConcatMode.sequential.value:
|
||||
break
|
||||
|
||||
# random video_paths order
|
||||
if video_concat_mode.value == VideoConcatMode.random.value:
|
||||
random.shuffle(raw_clips)
|
||||
|
||||
# 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)
|
||||
|
||||
# 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
|
||||
|
||||
if clip_ratio == video_ratio:
|
||||
# 等比例缩放
|
||||
clip = clip.resize((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}"
|
||||
)
|
||||
|
||||
if clip.duration > max_clip_duration:
|
||||
clip = clip.subclip(0, max_clip_duration)
|
||||
|
||||
clips.append(clip)
|
||||
video_duration += clip.duration
|
||||
|
||||
video_clip = concatenate_videoclips(clips)
|
||||
video_clip = video_clip.set_fps(30)
|
||||
logger.info("writing")
|
||||
# https://github.com/harry0703/NarratoAI/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")
|
||||
return combined_video_path
|
||||
|
||||
|
||||
def wrap_text(text, max_width, font="Arial", fontsize=60):
|
||||
# 创建字体对象
|
||||
font = ImageFont.truetype(font, fontsize)
|
||||
|
||||
def get_text_size(inner_text):
|
||||
inner_text = inner_text.strip()
|
||||
left, top, right, bottom = font.getbbox(inner_text)
|
||||
return right - left, bottom - top
|
||||
|
||||
width, height = get_text_size(text)
|
||||
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_ = []
|
||||
words = text.split(" ")
|
||||
_txt_ = ""
|
||||
for word in words:
|
||||
_before = _txt_
|
||||
_txt_ += f"{word} "
|
||||
_width, _height = get_text_size(_txt_)
|
||||
if _width <= max_width:
|
||||
continue
|
||||
else:
|
||||
if _txt_.strip() == word.strip():
|
||||
processed = False
|
||||
break
|
||||
_wrapped_lines_.append(_before)
|
||||
_txt_ = f"{word} "
|
||||
_wrapped_lines_.append(_txt_)
|
||||
if processed:
|
||||
_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_ = []
|
||||
chars = list(text)
|
||||
_txt_ = ""
|
||||
for word in chars:
|
||||
_txt_ += word
|
||||
_width, _height = get_text_size(_txt_)
|
||||
if _width <= max_width:
|
||||
continue
|
||||
else:
|
||||
_wrapped_lines_.append(_txt_)
|
||||
_txt_ = ""
|
||||
_wrapped_lines_.append(_txt_)
|
||||
result = "\n".join(_wrapped_lines_).strip()
|
||||
height = len(_wrapped_lines_) * height
|
||||
# logger.warning(f"wrapped text: {result}")
|
||||
return result, height
|
||||
|
||||
|
||||
def generate_video(
|
||||
video_path: str,
|
||||
audio_path: str,
|
||||
subtitle_path: str,
|
||||
output_file: str,
|
||||
params: Union[VideoParams, VideoClipParams],
|
||||
):
|
||||
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" ① video: {video_path}")
|
||||
logger.info(f" ② audio: {audio_path}")
|
||||
logger.info(f" ③ subtitle: {subtitle_path}")
|
||||
logger.info(f" ④ output: {output_file}")
|
||||
|
||||
# https://github.com/harry0703/NarratoAI/issues/217
|
||||
# PermissionError: [WinError 32] The process cannot access the file because it is being used by another process: 'final-1.mp4.tempTEMP_MPY_wvf_snd.mp3'
|
||||
# write into the same directory as the output file
|
||||
output_dir = os.path.dirname(output_file)
|
||||
|
||||
font_path = ""
|
||||
if params.subtitle_enabled:
|
||||
if not params.font_name:
|
||||
params.font_name = "STHeitiMedium.ttc"
|
||||
font_path = os.path.join(utils.font_dir(), params.font_name)
|
||||
if os.name == "nt":
|
||||
font_path = font_path.replace("\\", "/")
|
||||
|
||||
logger.info(f"using font: {font_path}")
|
||||
|
||||
def create_text_clip(subtitle_item):
|
||||
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
|
||||
)
|
||||
_clip = TextClip(
|
||||
wrapped_txt,
|
||||
font=font_path,
|
||||
fontsize=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,
|
||||
)
|
||||
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)
|
||||
if params.subtitle_position == "bottom":
|
||||
_clip = _clip.set_position(("center", video_height * 0.95 - _clip.h))
|
||||
elif params.subtitle_position == "top":
|
||||
_clip = _clip.set_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
|
||||
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))
|
||||
else: # center
|
||||
_clip = _clip.set_position(("center", "center"))
|
||||
return _clip
|
||||
|
||||
video_clip = VideoFileClip(video_path)
|
||||
audio_clip = AudioFileClip(audio_path).volumex(params.voice_volume)
|
||||
|
||||
if subtitle_path and os.path.exists(subtitle_path):
|
||||
sub = SubtitlesClip(subtitles=subtitle_path, encoding="utf-8")
|
||||
text_clips = []
|
||||
for item in sub.subtitles:
|
||||
clip = create_text_clip(subtitle_item=item)
|
||||
text_clips.append(clip)
|
||||
video_clip = CompositeVideoClip([video_clip, *text_clips])
|
||||
|
||||
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 = 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.write_videofile(
|
||||
output_file,
|
||||
audio_codec="aac",
|
||||
temp_audiofile_path=output_dir,
|
||||
threads=params.n_threads or 2,
|
||||
logger=None,
|
||||
fps=30,
|
||||
)
|
||||
video_clip.close()
|
||||
del video_clip
|
||||
logger.success("completed")
|
||||
|
||||
|
||||
def preprocess_video(materials: List[MaterialInfo], clip_duration=4):
|
||||
for material in materials:
|
||||
if not material.url:
|
||||
continue
|
||||
|
||||
ext = utils.parse_extension(material.url)
|
||||
try:
|
||||
clip = VideoFileClip(material.url)
|
||||
except Exception:
|
||||
clip = ImageClip(material.url)
|
||||
|
||||
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}")
|
||||
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
|
||||
clip = (
|
||||
ImageClip(material.url)
|
||||
.set_duration(clip_duration)
|
||||
.set_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(
|
||||
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)
|
||||
final_clip = CompositeVideoClip([zoom_clip])
|
||||
|
||||
# 输出视频
|
||||
video_file = f"{material.url}.mp4"
|
||||
final_clip.write_videofile(video_file, fps=30, logger=None)
|
||||
final_clip.close()
|
||||
del final_clip
|
||||
material.url = video_file
|
||||
logger.success(f"completed: {video_file}")
|
||||
return materials
|
||||
|
||||
|
||||
def combine_clip_videos(combined_video_path: str,
|
||||
video_paths: List[str],
|
||||
video_script_list: List[str],
|
||||
audio_file: str,
|
||||
video_aspect: VideoAspect = VideoAspect.portrait,
|
||||
threads: int = 2,
|
||||
) -> str:
|
||||
"""
|
||||
合并子视频
|
||||
Args:
|
||||
combined_video_path: 合并后的存储路径
|
||||
video_paths: 子视频路径列表
|
||||
audio_file: mp3旁白
|
||||
video_aspect: 屏幕比例
|
||||
threads: 线程数
|
||||
|
||||
Returns:
|
||||
|
||||
"""
|
||||
audio_clip = AudioFileClip(audio_file)
|
||||
audio_duration = audio_clip.duration
|
||||
logger.info(f"音频的最大持续时间: {audio_duration} s")
|
||||
# 每个剪辑所需的持续时间
|
||||
req_dur = audio_duration / len(video_paths)
|
||||
# req_dur = max_clip_duration
|
||||
# logger.info(f"每个剪辑的最大长度为 {req_dur} s")
|
||||
output_dir = os.path.dirname(combined_video_path)
|
||||
|
||||
aspect = VideoAspect(video_aspect)
|
||||
video_width, video_height = aspect.to_resolution()
|
||||
|
||||
clips = []
|
||||
video_duration = 0
|
||||
# 一遍又一遍地添加下载的剪辑,直到达到音频的持续时间 (max_duration)
|
||||
while video_duration < audio_duration:
|
||||
for video_path, video_script in zip(video_paths, video_script_list):
|
||||
clip = VideoFileClip(video_path).without_audio()
|
||||
# 检查剪辑是否比剩余音频长
|
||||
if (audio_duration - video_duration) < clip.duration:
|
||||
clip = clip.subclip(0, (audio_duration - video_duration))
|
||||
# 仅当计算出的剪辑长度 (req_dur) 短于实际剪辑时,才缩短剪辑以防止静止图像
|
||||
elif req_dur < clip.duration:
|
||||
clip = clip.subclip(0, req_dur)
|
||||
clip = clip.set_fps(30)
|
||||
|
||||
# 并非所有视频的大小都相同,因此我们需要调整它们的大小
|
||||
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
|
||||
|
||||
if clip_ratio == video_ratio:
|
||||
# 等比例缩放
|
||||
clip = clip.resize((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"将视频 {video_path} 大小调整为 {video_width} x {video_height}, 剪辑尺寸: {clip_w} x {clip_h}")
|
||||
|
||||
# TODO: 片段时长过长时,需要缩短,但暂时没有好的解决方案
|
||||
# if clip.duration > 5:
|
||||
# ctime = utils.reduce_video_time(txt=video_script)
|
||||
# if clip.duration > (2 * ctime):
|
||||
# clip = clip.subclip(ctime, 2*ctime)
|
||||
# else:
|
||||
# clip = clip.subclip(0, ctime)
|
||||
# logger.info(f"视频 {video_path} 片段时长较长,将剪辑时长缩短至 {ctime} 秒")
|
||||
|
||||
clips.append(clip)
|
||||
video_duration += clip.duration
|
||||
|
||||
video_clip = concatenate_videoclips(clips)
|
||||
video_clip = video_clip.set_fps(30)
|
||||
logger.info(f"合并中...")
|
||||
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(f"completed")
|
||||
return combined_video_path
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
from app.utils import utils
|
||||
|
||||
suffix = "*.mp4"
|
||||
song_dir = utils.video_dir()
|
||||
files = glob.glob(os.path.join(song_dir, suffix))
|
||||
|
||||
print(files)
|
||||
|
||||
# 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
|
||||
# )
|
||||
1354
app/services/voice.py
Normal file
271
app/utils/utils.py
Normal file
@ -0,0 +1,271 @@
|
||||
import locale
|
||||
import os
|
||||
import platform
|
||||
import threading
|
||||
from typing import Any
|
||||
from loguru import logger
|
||||
import json
|
||||
from uuid import uuid4
|
||||
import urllib3
|
||||
|
||||
from app.models import const
|
||||
|
||||
urllib3.disable_warnings()
|
||||
|
||||
|
||||
def get_response(status: int, data: Any = None, message: str = ""):
|
||||
obj = {
|
||||
"status": status,
|
||||
}
|
||||
if data:
|
||||
obj["data"] = data
|
||||
if message:
|
||||
obj["message"] = message
|
||||
return obj
|
||||
|
||||
|
||||
def to_json(obj):
|
||||
try:
|
||||
# 定义一个辅助函数来处理不同类型的对象
|
||||
def serialize(o):
|
||||
# 如果对象是可序列化类型,直接返回
|
||||
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
|
||||
elif isinstance(o, bytes):
|
||||
return "*** binary data ***"
|
||||
# 如果对象是字典,递归处理每个键值对
|
||||
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
|
||||
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
|
||||
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)
|
||||
else:
|
||||
return None
|
||||
|
||||
# 使用serialize函数处理输入对象
|
||||
serialized_obj = serialize(obj)
|
||||
|
||||
# 序列化处理后的对象为JSON字符串
|
||||
return json.dumps(serialized_obj, ensure_ascii=False, indent=4)
|
||||
except Exception as e:
|
||||
return None
|
||||
|
||||
|
||||
def get_uuid(remove_hyphen: bool = False):
|
||||
u = str(uuid4())
|
||||
if remove_hyphen:
|
||||
u = u.replace("-", "")
|
||||
return u
|
||||
|
||||
|
||||
def root_dir():
|
||||
return os.path.dirname(os.path.dirname(os.path.dirname(os.path.realpath(__file__))))
|
||||
|
||||
|
||||
def storage_dir(sub_dir: str = "", create: bool = False):
|
||||
d = os.path.join(root_dir(), "storage")
|
||||
if sub_dir:
|
||||
d = os.path.join(d, sub_dir)
|
||||
if create and not os.path.exists(d):
|
||||
os.makedirs(d)
|
||||
|
||||
return d
|
||||
|
||||
|
||||
def resource_dir(sub_dir: str = ""):
|
||||
d = os.path.join(root_dir(), "resource")
|
||||
if sub_dir:
|
||||
d = os.path.join(d, sub_dir)
|
||||
return d
|
||||
|
||||
|
||||
def task_dir(sub_dir: str = ""):
|
||||
d = os.path.join(storage_dir(), "tasks")
|
||||
if sub_dir:
|
||||
d = os.path.join(d, sub_dir)
|
||||
if not os.path.exists(d):
|
||||
os.makedirs(d)
|
||||
return d
|
||||
|
||||
|
||||
def font_dir(sub_dir: str = ""):
|
||||
d = resource_dir(f"fonts")
|
||||
if sub_dir:
|
||||
d = os.path.join(d, sub_dir)
|
||||
if not os.path.exists(d):
|
||||
os.makedirs(d)
|
||||
return d
|
||||
|
||||
|
||||
def song_dir(sub_dir: str = ""):
|
||||
d = resource_dir(f"songs")
|
||||
if sub_dir:
|
||||
d = os.path.join(d, sub_dir)
|
||||
if not os.path.exists(d):
|
||||
os.makedirs(d)
|
||||
return d
|
||||
|
||||
|
||||
def public_dir(sub_dir: str = ""):
|
||||
d = resource_dir(f"public")
|
||||
if sub_dir:
|
||||
d = os.path.join(d, sub_dir)
|
||||
if not os.path.exists(d):
|
||||
os.makedirs(d)
|
||||
return d
|
||||
|
||||
|
||||
def run_in_background(func, *args, **kwargs):
|
||||
def run():
|
||||
try:
|
||||
func(*args, **kwargs)
|
||||
except Exception as e:
|
||||
logger.error(f"run_in_background error: {e}")
|
||||
|
||||
thread = threading.Thread(target=run)
|
||||
thread.start()
|
||||
return thread
|
||||
|
||||
|
||||
def time_convert_seconds_to_hmsm(seconds) -> str:
|
||||
hours = int(seconds // 3600)
|
||||
seconds = seconds % 3600
|
||||
minutes = int(seconds // 60)
|
||||
milliseconds = int(seconds * 1000) % 1000
|
||||
seconds = int(seconds % 60)
|
||||
return "{:02d}:{:02d}:{:02d},{:03d}".format(hours, minutes, seconds, milliseconds)
|
||||
|
||||
|
||||
def text_to_srt(idx: int, msg: str, start_time: float, end_time: float) -> str:
|
||||
start_time = time_convert_seconds_to_hmsm(start_time)
|
||||
end_time = time_convert_seconds_to_hmsm(end_time)
|
||||
srt = """%d
|
||||
%s --> %s
|
||||
%s
|
||||
""" % (
|
||||
idx,
|
||||
start_time,
|
||||
end_time,
|
||||
msg,
|
||||
)
|
||||
return srt
|
||||
|
||||
|
||||
def str_contains_punctuation(word):
|
||||
for p in const.PUNCTUATIONS:
|
||||
if p in word:
|
||||
return True
|
||||
return False
|
||||
|
||||
|
||||
def split_string_by_punctuations(s):
|
||||
result = []
|
||||
txt = ""
|
||||
|
||||
previous_char = ""
|
||||
next_char = ""
|
||||
for i in range(len(s)):
|
||||
char = s[i]
|
||||
if char == "\n":
|
||||
result.append(txt.strip())
|
||||
txt = ""
|
||||
continue
|
||||
|
||||
if i > 0:
|
||||
previous_char = s[i - 1]
|
||||
if i < len(s) - 1:
|
||||
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
|
||||
txt += char
|
||||
continue
|
||||
|
||||
if char not in const.PUNCTUATIONS:
|
||||
txt += char
|
||||
else:
|
||||
result.append(txt.strip())
|
||||
txt = ""
|
||||
result.append(txt.strip())
|
||||
# filter empty string
|
||||
result = list(filter(None, result))
|
||||
return result
|
||||
|
||||
|
||||
def md5(text):
|
||||
import hashlib
|
||||
|
||||
return hashlib.md5(text.encode("utf-8")).hexdigest()
|
||||
|
||||
|
||||
def get_system_locale():
|
||||
try:
|
||||
loc = locale.getdefaultlocale()
|
||||
# zh_CN, zh_TW return zh
|
||||
# en_US, en_GB return en
|
||||
language_code = loc[0].split("_")[0]
|
||||
return language_code
|
||||
except Exception as e:
|
||||
return "en"
|
||||
|
||||
|
||||
def load_locales(i18n_dir):
|
||||
_locales = {}
|
||||
for root, dirs, files in os.walk(i18n_dir):
|
||||
for file in files:
|
||||
if file.endswith(".json"):
|
||||
lang = file.split(".")[0]
|
||||
with open(os.path.join(root, file), "r", encoding="utf-8") as f:
|
||||
_locales[lang] = json.loads(f.read())
|
||||
return _locales
|
||||
|
||||
|
||||
def parse_extension(filename):
|
||||
return os.path.splitext(filename)[1].strip().lower().replace(".", "")
|
||||
|
||||
|
||||
def script_dir(sub_dir: str = ""):
|
||||
d = resource_dir(f"scripts")
|
||||
if sub_dir:
|
||||
d = os.path.join(d, sub_dir)
|
||||
if not os.path.exists(d):
|
||||
os.makedirs(d)
|
||||
return d
|
||||
|
||||
|
||||
def video_dir(sub_dir: str = ""):
|
||||
d = resource_dir(f"videos")
|
||||
if sub_dir:
|
||||
d = os.path.join(d, sub_dir)
|
||||
if not os.path.exists(d):
|
||||
os.makedirs(d)
|
||||
return d
|
||||
|
||||
|
||||
def split_timestamp(timestamp):
|
||||
"""
|
||||
拆分时间戳
|
||||
"""
|
||||
start, end = timestamp.split('-')
|
||||
start_hour, start_minute = map(int, start.split(':'))
|
||||
end_hour, end_minute = map(int, end.split(':'))
|
||||
|
||||
start_time = '00:{:02d}:{:02d}'.format(start_hour, start_minute)
|
||||
end_time = '00:{:02d}:{:02d}'.format(end_hour, end_minute)
|
||||
|
||||
return start_time, end_time
|
||||
|
||||
|
||||
def reduce_video_time(txt: str, duration: float = 0.21531):
|
||||
"""
|
||||
按照字数缩减视频时长,一个字耗时约 0.21531 s,
|
||||
Returns:
|
||||
"""
|
||||
# 返回结果四舍五入为整数
|
||||
duration = len(txt) * duration
|
||||
return int(duration)
|
||||
17
changelog.py
Normal file
@ -0,0 +1,17 @@
|
||||
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,
|
||||
)
|
||||
194
config.example.toml
Normal file
@ -0,0 +1,194 @@
|
||||
[app]
|
||||
project_version="0.1.2"
|
||||
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 = []
|
||||
|
||||
# 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 = []
|
||||
|
||||
# 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
|
||||
|
||||
# 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"
|
||||
|
||||
########## 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 = ""
|
||||
|
||||
########## 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"
|
||||
|
||||
########## 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"
|
||||
|
||||
########## OneAPI API Key
|
||||
# Visit https://github.com/songquanpeng/one-api to get your API key
|
||||
oneapi_api_key=""
|
||||
oneapi_base_url=""
|
||||
oneapi_model_name=""
|
||||
|
||||
########## 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"
|
||||
|
||||
########## 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"
|
||||
|
||||
########## Gemini API Key
|
||||
gemini_api_key=""
|
||||
gemini_model_name = "gemini-1.5-flash"
|
||||
|
||||
########## 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"
|
||||
|
||||
|
||||
#
|
||||
# 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/
|
||||
|
||||
# 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/
|
||||
|
||||
# ffmpeg_path = "C:\\Users\\harry\\Downloads\\ffmpeg.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=""
|
||||
|
||||
|
||||
# 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
|
||||
|
||||
# webui界面是否显示配置项
|
||||
# webui hide baisc config panel
|
||||
hide_config = false
|
||||
|
||||
|
||||
[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 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")
|
||||
|
||||
# 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
|
||||
|
||||
# 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=""
|
||||
26
docker-compose.yml
Normal file
@ -0,0 +1,26 @@
|
||||
x-common-volumes: &common-volumes
|
||||
- ./:/NarratoAI
|
||||
|
||||
services:
|
||||
webui:
|
||||
build:
|
||||
context: .
|
||||
dockerfile: Dockerfile
|
||||
container_name: "webui"
|
||||
ports:
|
||||
- "8501:8501"
|
||||
command: [ "bash", "webui.sh" ]
|
||||
volumes: *common-volumes
|
||||
environment:
|
||||
- "VPN_PROXY_URL=http://host.docker.internal:7890"
|
||||
restart: always
|
||||
api:
|
||||
build:
|
||||
context: .
|
||||
dockerfile: Dockerfile
|
||||
container_name: "api"
|
||||
ports:
|
||||
- "8080:8080"
|
||||
command: [ "python3", "main.py" ]
|
||||
volumes: *common-volumes
|
||||
restart: always
|
||||
BIN
docs/check.png
Normal file
|
After Width: | Height: | Size: 434 KiB |
BIN
docs/img001.png
Normal file
|
After Width: | Height: | Size: 132 KiB |
BIN
docs/img002.png
Normal file
|
After Width: | Height: | Size: 54 KiB |
BIN
docs/img003.png
Normal file
|
After Width: | Height: | Size: 54 KiB |
BIN
docs/img004.png
Normal file
|
After Width: | Height: | Size: 696 KiB |
BIN
docs/img005.png
Normal file
|
After Width: | Height: | Size: 144 KiB |
BIN
docs/img006.png
Normal file
|
After Width: | Height: | Size: 143 KiB |
BIN
docs/img007.png
Normal file
|
After Width: | Height: | Size: 300 KiB |
BIN
docs/index.png
Normal file
|
After Width: | Height: | Size: 95 KiB |
941
docs/voice-list.txt
Normal file
@ -0,0 +1,941 @@
|
||||
Name: af-ZA-AdriNeural
|
||||
Gender: Female
|
||||
|
||||
Name: af-ZA-WillemNeural
|
||||
Gender: Male
|
||||
|
||||
Name: am-ET-AmehaNeural
|
||||
Gender: Male
|
||||
|
||||
Name: am-ET-MekdesNeural
|
||||
Gender: Female
|
||||
|
||||
Name: ar-AE-FatimaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: ar-AE-HamdanNeural
|
||||
Gender: Male
|
||||
|
||||
Name: ar-BH-AliNeural
|
||||
Gender: Male
|
||||
|
||||
Name: ar-BH-LailaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: ar-DZ-AminaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: ar-DZ-IsmaelNeural
|
||||
Gender: Male
|
||||
|
||||
Name: ar-EG-SalmaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: ar-EG-ShakirNeural
|
||||
Gender: Male
|
||||
|
||||
Name: ar-IQ-BasselNeural
|
||||
Gender: Male
|
||||
|
||||
Name: ar-IQ-RanaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: ar-JO-SanaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: ar-JO-TaimNeural
|
||||
Gender: Male
|
||||
|
||||
Name: ar-KW-FahedNeural
|
||||
Gender: Male
|
||||
|
||||
Name: ar-KW-NouraNeural
|
||||
Gender: Female
|
||||
|
||||
Name: ar-LB-LaylaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: ar-LB-RamiNeural
|
||||
Gender: Male
|
||||
|
||||
Name: ar-LY-ImanNeural
|
||||
Gender: Female
|
||||
|
||||
Name: ar-LY-OmarNeural
|
||||
Gender: Male
|
||||
|
||||
Name: ar-MA-JamalNeural
|
||||
Gender: Male
|
||||
|
||||
Name: ar-MA-MounaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: ar-OM-AbdullahNeural
|
||||
Gender: Male
|
||||
|
||||
Name: ar-OM-AyshaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: ar-QA-AmalNeural
|
||||
Gender: Female
|
||||
|
||||
Name: ar-QA-MoazNeural
|
||||
Gender: Male
|
||||
|
||||
Name: ar-SA-HamedNeural
|
||||
Gender: Male
|
||||
|
||||
Name: ar-SA-ZariyahNeural
|
||||
Gender: Female
|
||||
|
||||
Name: ar-SY-AmanyNeural
|
||||
Gender: Female
|
||||
|
||||
Name: ar-SY-LaithNeural
|
||||
Gender: Male
|
||||
|
||||
Name: ar-TN-HediNeural
|
||||
Gender: Male
|
||||
|
||||
Name: ar-TN-ReemNeural
|
||||
Gender: Female
|
||||
|
||||
Name: ar-YE-MaryamNeural
|
||||
Gender: Female
|
||||
|
||||
Name: ar-YE-SalehNeural
|
||||
Gender: Male
|
||||
|
||||
Name: az-AZ-BabekNeural
|
||||
Gender: Male
|
||||
|
||||
Name: az-AZ-BanuNeural
|
||||
Gender: Female
|
||||
|
||||
Name: bg-BG-BorislavNeural
|
||||
Gender: Male
|
||||
|
||||
Name: bg-BG-KalinaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: bn-BD-NabanitaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: bn-BD-PradeepNeural
|
||||
Gender: Male
|
||||
|
||||
Name: bn-IN-BashkarNeural
|
||||
Gender: Male
|
||||
|
||||
Name: bn-IN-TanishaaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: bs-BA-GoranNeural
|
||||
Gender: Male
|
||||
|
||||
Name: bs-BA-VesnaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: ca-ES-EnricNeural
|
||||
Gender: Male
|
||||
|
||||
Name: ca-ES-JoanaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: cs-CZ-AntoninNeural
|
||||
Gender: Male
|
||||
|
||||
Name: cs-CZ-VlastaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: cy-GB-AledNeural
|
||||
Gender: Male
|
||||
|
||||
Name: cy-GB-NiaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: da-DK-ChristelNeural
|
||||
Gender: Female
|
||||
|
||||
Name: da-DK-JeppeNeural
|
||||
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|
||||
|
||||
Name: de-AT-IngridNeural
|
||||
Gender: Female
|
||||
|
||||
Name: de-AT-JonasNeural
|
||||
Gender: Male
|
||||
|
||||
Name: de-CH-JanNeural
|
||||
Gender: Male
|
||||
|
||||
Name: de-CH-LeniNeural
|
||||
Gender: Female
|
||||
|
||||
Name: de-DE-AmalaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: de-DE-ConradNeural
|
||||
Gender: Male
|
||||
|
||||
Name: de-DE-FlorianMultilingualNeural
|
||||
Gender: Male
|
||||
|
||||
Name: de-DE-KatjaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: de-DE-KillianNeural
|
||||
Gender: Male
|
||||
|
||||
Name: de-DE-SeraphinaMultilingualNeural
|
||||
Gender: Female
|
||||
|
||||
Name: el-GR-AthinaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: el-GR-NestorasNeural
|
||||
Gender: Male
|
||||
|
||||
Name: en-AU-NatashaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: en-AU-WilliamNeural
|
||||
Gender: Male
|
||||
|
||||
Name: en-CA-ClaraNeural
|
||||
Gender: Female
|
||||
|
||||
Name: en-CA-LiamNeural
|
||||
Gender: Male
|
||||
|
||||
Name: en-GB-LibbyNeural
|
||||
Gender: Female
|
||||
|
||||
Name: en-GB-MaisieNeural
|
||||
Gender: Female
|
||||
|
||||
Name: en-GB-RyanNeural
|
||||
Gender: Male
|
||||
|
||||
Name: en-GB-SoniaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: en-GB-ThomasNeural
|
||||
Gender: Male
|
||||
|
||||
Name: en-HK-SamNeural
|
||||
Gender: Male
|
||||
|
||||
Name: en-HK-YanNeural
|
||||
Gender: Female
|
||||
|
||||
Name: en-IE-ConnorNeural
|
||||
Gender: Male
|
||||
|
||||
Name: en-IE-EmilyNeural
|
||||
Gender: Female
|
||||
|
||||
Name: en-IN-NeerjaExpressiveNeural
|
||||
Gender: Female
|
||||
|
||||
Name: en-IN-NeerjaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: en-IN-PrabhatNeural
|
||||
Gender: Male
|
||||
|
||||
Name: en-KE-AsiliaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: en-KE-ChilembaNeural
|
||||
Gender: Male
|
||||
|
||||
Name: en-NG-AbeoNeural
|
||||
Gender: Male
|
||||
|
||||
Name: en-NG-EzinneNeural
|
||||
Gender: Female
|
||||
|
||||
Name: en-NZ-MitchellNeural
|
||||
Gender: Male
|
||||
|
||||
Name: en-NZ-MollyNeural
|
||||
Gender: Female
|
||||
|
||||
Name: en-PH-JamesNeural
|
||||
Gender: Male
|
||||
|
||||
Name: en-PH-RosaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: en-SG-LunaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: en-SG-WayneNeural
|
||||
Gender: Male
|
||||
|
||||
Name: en-TZ-ElimuNeural
|
||||
Gender: Male
|
||||
|
||||
Name: en-TZ-ImaniNeural
|
||||
Gender: Female
|
||||
|
||||
Name: en-US-AnaNeural
|
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Gender: Female
|
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|
||||
Name: en-US-AndrewNeural
|
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Gender: Male
|
||||
|
||||
Name: en-US-AriaNeural
|
||||
Gender: Female
|
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|
||||
Name: en-US-AvaNeural
|
||||
Gender: Female
|
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|
||||
Name: en-US-BrianNeural
|
||||
Gender: Male
|
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|
||||
Name: en-US-ChristopherNeural
|
||||
Gender: Male
|
||||
|
||||
Name: en-US-EmmaNeural
|
||||
Gender: Female
|
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|
||||
Name: en-US-EricNeural
|
||||
Gender: Male
|
||||
|
||||
Name: en-US-GuyNeural
|
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Gender: Male
|
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|
||||
Name: en-US-JennyNeural
|
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Gender: Female
|
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|
||||
Name: en-US-MichelleNeural
|
||||
Gender: Female
|
||||
|
||||
Name: en-US-RogerNeural
|
||||
Gender: Male
|
||||
|
||||
Name: en-US-SteffanNeural
|
||||
Gender: Male
|
||||
|
||||
Name: en-ZA-LeahNeural
|
||||
Gender: Female
|
||||
|
||||
Name: en-ZA-LukeNeural
|
||||
Gender: Male
|
||||
|
||||
Name: es-AR-ElenaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: es-AR-TomasNeural
|
||||
Gender: Male
|
||||
|
||||
Name: es-BO-MarceloNeural
|
||||
Gender: Male
|
||||
|
||||
Name: es-BO-SofiaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: es-CL-CatalinaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: es-CL-LorenzoNeural
|
||||
Gender: Male
|
||||
|
||||
Name: es-CO-GonzaloNeural
|
||||
Gender: Male
|
||||
|
||||
Name: es-CO-SalomeNeural
|
||||
Gender: Female
|
||||
|
||||
Name: es-CR-JuanNeural
|
||||
Gender: Male
|
||||
|
||||
Name: es-CR-MariaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: es-CU-BelkysNeural
|
||||
Gender: Female
|
||||
|
||||
Name: es-CU-ManuelNeural
|
||||
Gender: Male
|
||||
|
||||
Name: es-DO-EmilioNeural
|
||||
Gender: Male
|
||||
|
||||
Name: es-DO-RamonaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: es-EC-AndreaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: es-EC-LuisNeural
|
||||
Gender: Male
|
||||
|
||||
Name: es-ES-AlvaroNeural
|
||||
Gender: Male
|
||||
|
||||
Name: es-ES-ElviraNeural
|
||||
Gender: Female
|
||||
|
||||
Name: es-ES-XimenaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: es-GQ-JavierNeural
|
||||
Gender: Male
|
||||
|
||||
Name: es-GQ-TeresaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: es-GT-AndresNeural
|
||||
Gender: Male
|
||||
|
||||
Name: es-GT-MartaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: es-HN-CarlosNeural
|
||||
Gender: Male
|
||||
|
||||
Name: es-HN-KarlaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: es-MX-DaliaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: es-MX-JorgeNeural
|
||||
Gender: Male
|
||||
|
||||
Name: es-NI-FedericoNeural
|
||||
Gender: Male
|
||||
|
||||
Name: es-NI-YolandaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: es-PA-MargaritaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: es-PA-RobertoNeural
|
||||
Gender: Male
|
||||
|
||||
Name: es-PE-AlexNeural
|
||||
Gender: Male
|
||||
|
||||
Name: es-PE-CamilaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: es-PR-KarinaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: es-PR-VictorNeural
|
||||
Gender: Male
|
||||
|
||||
Name: es-PY-MarioNeural
|
||||
Gender: Male
|
||||
|
||||
Name: es-PY-TaniaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: es-SV-LorenaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: es-SV-RodrigoNeural
|
||||
Gender: Male
|
||||
|
||||
Name: es-US-AlonsoNeural
|
||||
Gender: Male
|
||||
|
||||
Name: es-US-PalomaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: es-UY-MateoNeural
|
||||
Gender: Male
|
||||
|
||||
Name: es-UY-ValentinaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: es-VE-PaolaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: es-VE-SebastianNeural
|
||||
Gender: Male
|
||||
|
||||
Name: et-EE-AnuNeural
|
||||
Gender: Female
|
||||
|
||||
Name: et-EE-KertNeural
|
||||
Gender: Male
|
||||
|
||||
Name: fa-IR-DilaraNeural
|
||||
Gender: Female
|
||||
|
||||
Name: fa-IR-FaridNeural
|
||||
Gender: Male
|
||||
|
||||
Name: fi-FI-HarriNeural
|
||||
Gender: Male
|
||||
|
||||
Name: fi-FI-NooraNeural
|
||||
Gender: Female
|
||||
|
||||
Name: fil-PH-AngeloNeural
|
||||
Gender: Male
|
||||
|
||||
Name: fil-PH-BlessicaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: fr-BE-CharlineNeural
|
||||
Gender: Female
|
||||
|
||||
Name: fr-BE-GerardNeural
|
||||
Gender: Male
|
||||
|
||||
Name: fr-CA-AntoineNeural
|
||||
Gender: Male
|
||||
|
||||
Name: fr-CA-JeanNeural
|
||||
Gender: Male
|
||||
|
||||
Name: fr-CA-SylvieNeural
|
||||
Gender: Female
|
||||
|
||||
Name: fr-CA-ThierryNeural
|
||||
Gender: Male
|
||||
|
||||
Name: fr-CH-ArianeNeural
|
||||
Gender: Female
|
||||
|
||||
Name: fr-CH-FabriceNeural
|
||||
Gender: Male
|
||||
|
||||
Name: fr-FR-DeniseNeural
|
||||
Gender: Female
|
||||
|
||||
Name: fr-FR-EloiseNeural
|
||||
Gender: Female
|
||||
|
||||
Name: fr-FR-HenriNeural
|
||||
Gender: Male
|
||||
|
||||
Name: fr-FR-RemyMultilingualNeural
|
||||
Gender: Male
|
||||
|
||||
Name: fr-FR-VivienneMultilingualNeural
|
||||
Gender: Female
|
||||
|
||||
Name: ga-IE-ColmNeural
|
||||
Gender: Male
|
||||
|
||||
Name: ga-IE-OrlaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: gl-ES-RoiNeural
|
||||
Gender: Male
|
||||
|
||||
Name: gl-ES-SabelaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: gu-IN-DhwaniNeural
|
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Gender: Female
|
||||
|
||||
Name: gu-IN-NiranjanNeural
|
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Gender: Male
|
||||
|
||||
Name: he-IL-AvriNeural
|
||||
Gender: Male
|
||||
|
||||
Name: he-IL-HilaNeural
|
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Gender: Female
|
||||
|
||||
Name: hi-IN-MadhurNeural
|
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Gender: Male
|
||||
|
||||
Name: hi-IN-SwaraNeural
|
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Gender: Female
|
||||
|
||||
Name: hr-HR-GabrijelaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: hr-HR-SreckoNeural
|
||||
Gender: Male
|
||||
|
||||
Name: hu-HU-NoemiNeural
|
||||
Gender: Female
|
||||
|
||||
Name: hu-HU-TamasNeural
|
||||
Gender: Male
|
||||
|
||||
Name: id-ID-ArdiNeural
|
||||
Gender: Male
|
||||
|
||||
Name: id-ID-GadisNeural
|
||||
Gender: Female
|
||||
|
||||
Name: is-IS-GudrunNeural
|
||||
Gender: Female
|
||||
|
||||
Name: is-IS-GunnarNeural
|
||||
Gender: Male
|
||||
|
||||
Name: it-IT-DiegoNeural
|
||||
Gender: Male
|
||||
|
||||
Name: it-IT-ElsaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: it-IT-GiuseppeNeural
|
||||
Gender: Male
|
||||
|
||||
Name: it-IT-IsabellaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: ja-JP-KeitaNeural
|
||||
Gender: Male
|
||||
|
||||
Name: ja-JP-NanamiNeural
|
||||
Gender: Female
|
||||
|
||||
Name: jv-ID-DimasNeural
|
||||
Gender: Male
|
||||
|
||||
Name: jv-ID-SitiNeural
|
||||
Gender: Female
|
||||
|
||||
Name: ka-GE-EkaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: ka-GE-GiorgiNeural
|
||||
Gender: Male
|
||||
|
||||
Name: kk-KZ-AigulNeural
|
||||
Gender: Female
|
||||
|
||||
Name: kk-KZ-DauletNeural
|
||||
Gender: Male
|
||||
|
||||
Name: km-KH-PisethNeural
|
||||
Gender: Male
|
||||
|
||||
Name: km-KH-SreymomNeural
|
||||
Gender: Female
|
||||
|
||||
Name: kn-IN-GaganNeural
|
||||
Gender: Male
|
||||
|
||||
Name: kn-IN-SapnaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: ko-KR-HyunsuNeural
|
||||
Gender: Male
|
||||
|
||||
Name: ko-KR-InJoonNeural
|
||||
Gender: Male
|
||||
|
||||
Name: ko-KR-SunHiNeural
|
||||
Gender: Female
|
||||
|
||||
Name: lo-LA-ChanthavongNeural
|
||||
Gender: Male
|
||||
|
||||
Name: lo-LA-KeomanyNeural
|
||||
Gender: Female
|
||||
|
||||
Name: lt-LT-LeonasNeural
|
||||
Gender: Male
|
||||
|
||||
Name: lt-LT-OnaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: lv-LV-EveritaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: lv-LV-NilsNeural
|
||||
Gender: Male
|
||||
|
||||
Name: mk-MK-AleksandarNeural
|
||||
Gender: Male
|
||||
|
||||
Name: mk-MK-MarijaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: ml-IN-MidhunNeural
|
||||
Gender: Male
|
||||
|
||||
Name: ml-IN-SobhanaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: mn-MN-BataaNeural
|
||||
Gender: Male
|
||||
|
||||
Name: mn-MN-YesuiNeural
|
||||
Gender: Female
|
||||
|
||||
Name: mr-IN-AarohiNeural
|
||||
Gender: Female
|
||||
|
||||
Name: mr-IN-ManoharNeural
|
||||
Gender: Male
|
||||
|
||||
Name: ms-MY-OsmanNeural
|
||||
Gender: Male
|
||||
|
||||
Name: ms-MY-YasminNeural
|
||||
Gender: Female
|
||||
|
||||
Name: mt-MT-GraceNeural
|
||||
Gender: Female
|
||||
|
||||
Name: mt-MT-JosephNeural
|
||||
Gender: Male
|
||||
|
||||
Name: my-MM-NilarNeural
|
||||
Gender: Female
|
||||
|
||||
Name: my-MM-ThihaNeural
|
||||
Gender: Male
|
||||
|
||||
Name: nb-NO-FinnNeural
|
||||
Gender: Male
|
||||
|
||||
Name: nb-NO-PernilleNeural
|
||||
Gender: Female
|
||||
|
||||
Name: ne-NP-HemkalaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: ne-NP-SagarNeural
|
||||
Gender: Male
|
||||
|
||||
Name: nl-BE-ArnaudNeural
|
||||
Gender: Male
|
||||
|
||||
Name: nl-BE-DenaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: nl-NL-ColetteNeural
|
||||
Gender: Female
|
||||
|
||||
Name: nl-NL-FennaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: nl-NL-MaartenNeural
|
||||
Gender: Male
|
||||
|
||||
Name: pl-PL-MarekNeural
|
||||
Gender: Male
|
||||
|
||||
Name: pl-PL-ZofiaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: ps-AF-GulNawazNeural
|
||||
Gender: Male
|
||||
|
||||
Name: ps-AF-LatifaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: pt-BR-AntonioNeural
|
||||
Gender: Male
|
||||
|
||||
Name: pt-BR-FranciscaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: pt-BR-ThalitaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: pt-PT-DuarteNeural
|
||||
Gender: Male
|
||||
|
||||
Name: pt-PT-RaquelNeural
|
||||
Gender: Female
|
||||
|
||||
Name: ro-RO-AlinaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: ro-RO-EmilNeural
|
||||
Gender: Male
|
||||
|
||||
Name: ru-RU-DmitryNeural
|
||||
Gender: Male
|
||||
|
||||
Name: ru-RU-SvetlanaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: si-LK-SameeraNeural
|
||||
Gender: Male
|
||||
|
||||
Name: si-LK-ThiliniNeural
|
||||
Gender: Female
|
||||
|
||||
Name: sk-SK-LukasNeural
|
||||
Gender: Male
|
||||
|
||||
Name: sk-SK-ViktoriaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: sl-SI-PetraNeural
|
||||
Gender: Female
|
||||
|
||||
Name: sl-SI-RokNeural
|
||||
Gender: Male
|
||||
|
||||
Name: so-SO-MuuseNeural
|
||||
Gender: Male
|
||||
|
||||
Name: so-SO-UbaxNeural
|
||||
Gender: Female
|
||||
|
||||
Name: sq-AL-AnilaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: sq-AL-IlirNeural
|
||||
Gender: Male
|
||||
|
||||
Name: sr-RS-NicholasNeural
|
||||
Gender: Male
|
||||
|
||||
Name: sr-RS-SophieNeural
|
||||
Gender: Female
|
||||
|
||||
Name: su-ID-JajangNeural
|
||||
Gender: Male
|
||||
|
||||
Name: su-ID-TutiNeural
|
||||
Gender: Female
|
||||
|
||||
Name: sv-SE-MattiasNeural
|
||||
Gender: Male
|
||||
|
||||
Name: sv-SE-SofieNeural
|
||||
Gender: Female
|
||||
|
||||
Name: sw-KE-RafikiNeural
|
||||
Gender: Male
|
||||
|
||||
Name: sw-KE-ZuriNeural
|
||||
Gender: Female
|
||||
|
||||
Name: sw-TZ-DaudiNeural
|
||||
Gender: Male
|
||||
|
||||
Name: sw-TZ-RehemaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: ta-IN-PallaviNeural
|
||||
Gender: Female
|
||||
|
||||
Name: ta-IN-ValluvarNeural
|
||||
Gender: Male
|
||||
|
||||
Name: ta-LK-KumarNeural
|
||||
Gender: Male
|
||||
|
||||
Name: ta-LK-SaranyaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: ta-MY-KaniNeural
|
||||
Gender: Female
|
||||
|
||||
Name: ta-MY-SuryaNeural
|
||||
Gender: Male
|
||||
|
||||
Name: ta-SG-AnbuNeural
|
||||
Gender: Male
|
||||
|
||||
Name: ta-SG-VenbaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: te-IN-MohanNeural
|
||||
Gender: Male
|
||||
|
||||
Name: te-IN-ShrutiNeural
|
||||
Gender: Female
|
||||
|
||||
Name: th-TH-NiwatNeural
|
||||
Gender: Male
|
||||
|
||||
Name: th-TH-PremwadeeNeural
|
||||
Gender: Female
|
||||
|
||||
Name: tr-TR-AhmetNeural
|
||||
Gender: Male
|
||||
|
||||
Name: tr-TR-EmelNeural
|
||||
Gender: Female
|
||||
|
||||
Name: uk-UA-OstapNeural
|
||||
Gender: Male
|
||||
|
||||
Name: uk-UA-PolinaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: ur-IN-GulNeural
|
||||
Gender: Female
|
||||
|
||||
Name: ur-IN-SalmanNeural
|
||||
Gender: Male
|
||||
|
||||
Name: ur-PK-AsadNeural
|
||||
Gender: Male
|
||||
|
||||
Name: ur-PK-UzmaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: uz-UZ-MadinaNeural
|
||||
Gender: Female
|
||||
|
||||
Name: uz-UZ-SardorNeural
|
||||
Gender: Male
|
||||
|
||||
Name: vi-VN-HoaiMyNeural
|
||||
Gender: Female
|
||||
|
||||
Name: vi-VN-NamMinhNeural
|
||||
Gender: Male
|
||||
|
||||
Name: zh-CN-XiaoxiaoNeural
|
||||
Gender: Female
|
||||
|
||||
Name: zh-CN-XiaoyiNeural
|
||||
Gender: Female
|
||||
|
||||
Name: zh-CN-YunjianNeural
|
||||
Gender: Male
|
||||
|
||||
Name: zh-CN-YunxiNeural
|
||||
Gender: Male
|
||||
|
||||
Name: zh-CN-YunxiaNeural
|
||||
Gender: Male
|
||||
|
||||
Name: zh-CN-YunyangNeural
|
||||
Gender: Male
|
||||
|
||||
Name: zh-CN-liaoning-XiaobeiNeural
|
||||
Gender: Female
|
||||
|
||||
Name: zh-CN-shaanxi-XiaoniNeural
|
||||
Gender: Female
|
||||
|
||||
Name: zh-HK-HiuGaaiNeural
|
||||
Gender: Female
|
||||
|
||||
Name: zh-HK-HiuMaanNeural
|
||||
Gender: Female
|
||||
|
||||
Name: zh-HK-WanLungNeural
|
||||
Gender: Male
|
||||
|
||||
Name: zh-TW-HsiaoChenNeural
|
||||
Gender: Female
|
||||
|
||||
Name: zh-TW-HsiaoYuNeural
|
||||
Gender: Female
|
||||
|
||||
Name: zh-TW-YunJheNeural
|
||||
Gender: Male
|
||||
|
||||
Name: zu-ZA-ThandoNeural
|
||||
Gender: Female
|
||||
|
||||
Name: zu-ZA-ThembaNeural
|
||||
Gender: Male
|
||||
16
main.py
Normal file
@ -0,0 +1,16 @@
|
||||
import uvicorn
|
||||
from loguru import logger
|
||||
|
||||
from app.config import config
|
||||
|
||||
if __name__ == "__main__":
|
||||
logger.info(
|
||||
"start server, docs: http://127.0.0.1:" + str(config.listen_port) + "/docs"
|
||||
)
|
||||
uvicorn.run(
|
||||
app="app.asgi:app",
|
||||
host=config.listen_host,
|
||||
port=config.listen_port,
|
||||
reload=config.reload_debug,
|
||||
log_level="warning",
|
||||
)
|
||||
26
requirements.txt
Normal file
@ -0,0 +1,26 @@
|
||||
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>=0.7.2
|
||||
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
|
||||
19
resource/public/index.html
Normal file
@ -0,0 +1,19 @@
|
||||
<!DOCTYPE html>
|
||||
<html lang="en">
|
||||
<head>
|
||||
<meta charset="UTF-8">
|
||||
<title>NarratoAI</title>
|
||||
</head>
|
||||
<body>
|
||||
<h1>NarratoAI</h1>
|
||||
<a href="https://github.com/harry0703/NarratoAI">https://github.com/harry0703/NarratoAI</a>
|
||||
<p>
|
||||
只需提供一个视频 主题 或 关键词 ,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。
|
||||
</p>
|
||||
|
||||
<p>
|
||||
Simply provide a topic or keyword 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.
|
||||
</p>
|
||||
</body>
|
||||
</html>
|
||||
43
webui.bat
Normal file
@ -0,0 +1,43 @@
|
||||
@echo off
|
||||
set CURRENT_DIR=%CD%
|
||||
echo ***** Current directory: %CURRENT_DIR% *****
|
||||
set PYTHONPATH=%CURRENT_DIR%
|
||||
|
||||
@echo off
|
||||
setlocal enabledelayedexpansion
|
||||
|
||||
rem 创建链接和路径的数组
|
||||
set "urls_paths[0]=https://zenodo.org/records/13293144/files/MicrosoftYaHeiBold.ttc|.\resource\fonts"
|
||||
set "urls_paths[1]=https://zenodo.org/records/13293144/files/MicrosoftYaHeiNormal.ttc|.\resource\fonts"
|
||||
set "urls_paths[2]=https://zenodo.org/records/13293144/files/STHeitiLight.ttc|.\resource\fonts"
|
||||
set "urls_paths[3]=https://zenodo.org/records/13293144/files/STHeitiMedium.ttc|.\resource\fonts"
|
||||
set "urls_paths[4]=https://zenodo.org/records/13293144/files/UTM%20Kabel%20KT.ttf|.\resource\fonts"
|
||||
set "urls_paths[5]=https://zenodo.org/records/13293129/files/demo.mp4|.\resource\videos"
|
||||
set "urls_paths[6]=https://zenodo.org/records/13293150/files/output000.mp3|.\resource\songs"
|
||||
set "urls_paths[7]=https://zenodo.org/records/13293150/files/output001.mp3|.\resource\songs"
|
||||
set "urls_paths[8]=https://zenodo.org/records/13293150/files/output002.mp3|.\resource\songs"
|
||||
set "urls_paths[9]=https://zenodo.org/records/13293150/files/output003.mp3|.\resource\songs"
|
||||
set "urls_paths[10]=https://zenodo.org/records/13293150/files/output004.mp3|.\resource\songs"
|
||||
set "urls_paths[11]=https://zenodo.org/records/13293150/files/output005.mp3|.\resource\songs"
|
||||
set "urls_paths[12]=https://zenodo.org/records/13293150/files/output006.mp3|.\resource\songs"
|
||||
set "urls_paths[13]=https://zenodo.org/records/13293150/files/output007.mp3|.\resource\songs"
|
||||
set "urls_paths[14]=https://zenodo.org/records/13293150/files/output008.mp3|.\resource\songs"
|
||||
set "urls_paths[15]=https://zenodo.org/records/13293150/files/output009.mp3|.\resource\songs"
|
||||
set "urls_paths[16]=https://zenodo.org/records/13293150/files/output010.mp3|.\resource\songs"
|
||||
|
||||
rem 循环下载所有文件并保存到指定路径
|
||||
for /L %%i in (0,1,16) do (
|
||||
for /f "tokens=1,2 delims=|" %%a in ("!urls_paths[%%i]!") do (
|
||||
if not exist "%%b" mkdir "%%b"
|
||||
echo 正在下载 %%a 到 %%b
|
||||
curl -o "%%b\%%~nxa" %%a
|
||||
)
|
||||
)
|
||||
|
||||
echo 所有文件已成功下载到指定目录
|
||||
endlocal
|
||||
pause
|
||||
|
||||
|
||||
rem set HF_ENDPOINT=https://hf-mirror.com
|
||||
streamlit run .\webui\Main.py --browser.gatherUsageStats=False --server.enableCORS=True
|
||||
58
webui.sh
Normal file
@ -0,0 +1,58 @@
|
||||
#!/bin/bash
|
||||
|
||||
# 从环境变量中加载VPN代理的配置URL
|
||||
vpn_proxy_url="$VPN_PROXY_URL"
|
||||
# 检查是否成功加载
|
||||
if [ -z "$vpn_proxy_url" ]; then
|
||||
echo "VPN代理配置URL未设置,请检查环境变量VPN_PROXY_URL"
|
||||
exit 1
|
||||
fi
|
||||
# 使用VPN代理进行一些操作,比如通过代理下载文件
|
||||
export http_proxy="$vpn_proxy_url"
|
||||
export https_proxy="$vpn_proxy_url"
|
||||
|
||||
# 创建链接和路径的数组
|
||||
declare -A urls_paths=(
|
||||
["https://zenodo.org/records/13293144/files/MicrosoftYaHeiBold.ttc"]="./resource/fonts"
|
||||
["https://zenodo.org/records/13293144/files/MicrosoftYaHeiNormal.ttc"]="./resource/fonts"
|
||||
["https://zenodo.org/records/13293144/files/STHeitiLight.ttc"]="./resource/fonts"
|
||||
["https://zenodo.org/records/13293144/files/STHeitiMedium.ttc"]="./resource/fonts"
|
||||
["https://zenodo.org/records/13293144/files/UTM%20Kabel%20KT.ttf"]="./resource/fonts"
|
||||
["https://zenodo.org/records/13293129/files/demo.mp4"]="./resource/videos"
|
||||
["https://zenodo.org/records/13293150/files/output000.mp3"]="./resource/songs"
|
||||
["https://zenodo.org/records/13293150/files/output001.mp3"]="./resource/songs"
|
||||
["https://zenodo.org/records/13293150/files/output002.mp3"]="./resource/songs"
|
||||
["https://zenodo.org/records/13293150/files/output003.mp3"]="./resource/songs"
|
||||
["https://zenodo.org/records/13293150/files/output004.mp3"]="./resource/songs"
|
||||
["https://zenodo.org/records/13293150/files/output005.mp3"]="./resource/songs"
|
||||
["https://zenodo.org/records/13293150/files/output006.mp3"]="./resource/songs"
|
||||
["https://zenodo.org/records/13293150/files/output007.mp3"]="./resource/songs"
|
||||
["https://zenodo.org/records/13293150/files/output008.mp3"]="./resource/songs"
|
||||
["https://zenodo.org/records/13293150/files/output009.mp3"]="./resource/songs"
|
||||
["https://zenodo.org/records/13293150/files/output010.mp3"]="./resource/songs"
|
||||
# 添加更多链接及其对应的路径
|
||||
)
|
||||
|
||||
# 循环下载所有文件并保存到指定路径
|
||||
for url in "${!urls_paths[@]}"; do
|
||||
output_dir="${urls_paths[$url]}"
|
||||
mkdir -p "$output_dir" # 创建目录(如果不存在)
|
||||
|
||||
# 提取文件名
|
||||
filename=$(basename "$url")
|
||||
|
||||
# 检查文件是否已经存在
|
||||
if [ -f "$output_dir/$filename" ]; then
|
||||
echo "文件 $filename 已经存在,跳过下载"
|
||||
else
|
||||
wget -P "$output_dir" "$url" &
|
||||
fi
|
||||
done
|
||||
|
||||
# 等待所有下载完成
|
||||
wait
|
||||
|
||||
echo "所有文件已成功下载到指定目录"
|
||||
|
||||
|
||||
streamlit run ./webui/Main.py --browser.serverAddress="0.0.0.0" --server.enableCORS=True --browser.gatherUsageStats=False
|
||||
746
webui/Main.py
Normal file
@ -0,0 +1,746 @@
|
||||
import sys
|
||||
import os
|
||||
import glob
|
||||
import json
|
||||
import datetime
|
||||
|
||||
# 将项目的根目录添加到系统路径中,以允许从项目导入模块
|
||||
root_dir = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
|
||||
if root_dir not in sys.path:
|
||||
sys.path.append(root_dir)
|
||||
print("******** sys.path ********")
|
||||
print(sys.path)
|
||||
print("")
|
||||
|
||||
import streamlit as st
|
||||
|
||||
import os
|
||||
from uuid import uuid4
|
||||
import platform
|
||||
import streamlit.components.v1 as components
|
||||
from loguru import logger
|
||||
from app.config import config
|
||||
|
||||
st.set_page_config(
|
||||
page_title="NarratoAI",
|
||||
page_icon="📽️",
|
||||
layout="wide",
|
||||
initial_sidebar_state="auto",
|
||||
menu_items={
|
||||
"Report a bug": "https://github.com/linyqh/NarratoAI/issues",
|
||||
'About': f"# NarratoAI:sunglasses: 📽️ \n #### Version: v{config.project_version} \n "
|
||||
f"自动化影视解说视频详情请移步:https://github.com/linyqh/NarratoAI"
|
||||
},
|
||||
)
|
||||
|
||||
from app.models.const import FILE_TYPE_IMAGES, FILE_TYPE_VIDEOS
|
||||
from app.models.schema import VideoClipParams, VideoAspect, VideoConcatMode
|
||||
from app.services import task as tm, llm, voice, material
|
||||
from app.utils import utils
|
||||
|
||||
os.environ["HTTP_PROXY"] = config.proxy.get("http", "") or os.getenv("VPN_PROXY_URL", "")
|
||||
os.environ["HTTPS_PROXY"] = config.proxy.get("https", "") or os.getenv("VPN_PROXY_URL", "")
|
||||
|
||||
hide_streamlit_style = """
|
||||
<style>#root > div:nth-child(1) > div > div > div > div > section > div {padding-top: 6px; padding-bottom: 10px; padding-left: 20px; padding-right: 20px;}</style>
|
||||
"""
|
||||
st.markdown(hide_streamlit_style, unsafe_allow_html=True)
|
||||
st.title(f"NarratoAI :sunglasses:📽️")
|
||||
support_locales = [
|
||||
"zh-CN",
|
||||
"zh-HK",
|
||||
"zh-TW",
|
||||
"de-DE",
|
||||
"en-US",
|
||||
"fr-FR",
|
||||
"vi-VN",
|
||||
"th-TH",
|
||||
]
|
||||
font_dir = os.path.join(root_dir, "resource", "fonts")
|
||||
song_dir = os.path.join(root_dir, "resource", "songs")
|
||||
i18n_dir = os.path.join(root_dir, "webui", "i18n")
|
||||
config_file = os.path.join(root_dir, "webui", ".streamlit", "webui.toml")
|
||||
system_locale = utils.get_system_locale()
|
||||
|
||||
if 'video_subject' not in st.session_state:
|
||||
st.session_state['video_subject'] = ''
|
||||
if 'video_clip_json' not in st.session_state:
|
||||
st.session_state['video_clip_json'] = ''
|
||||
if 'video_plot' not in st.session_state:
|
||||
st.session_state['video_plot'] = ''
|
||||
if 'ui_language' not in st.session_state:
|
||||
st.session_state['ui_language'] = config.ui.get("language", system_locale)
|
||||
|
||||
|
||||
def get_all_fonts():
|
||||
fonts = []
|
||||
for root, dirs, files in os.walk(font_dir):
|
||||
for file in files:
|
||||
if file.endswith(".ttf") or file.endswith(".ttc"):
|
||||
fonts.append(file)
|
||||
fonts.sort()
|
||||
return fonts
|
||||
|
||||
|
||||
def get_all_songs():
|
||||
songs = []
|
||||
for root, dirs, files in os.walk(song_dir):
|
||||
for file in files:
|
||||
if file.endswith(".mp3"):
|
||||
songs.append(file)
|
||||
return songs
|
||||
|
||||
|
||||
def open_task_folder(task_id):
|
||||
try:
|
||||
sys = platform.system()
|
||||
path = os.path.join(root_dir, "storage", "tasks", task_id)
|
||||
if os.path.exists(path):
|
||||
if sys == 'Windows':
|
||||
os.system(f"start {path}")
|
||||
if sys == 'Darwin':
|
||||
os.system(f"open {path}")
|
||||
except Exception as e:
|
||||
logger.error(e)
|
||||
|
||||
|
||||
def scroll_to_bottom():
|
||||
js = f"""
|
||||
<script>
|
||||
console.log("scroll_to_bottom");
|
||||
function scroll(dummy_var_to_force_repeat_execution){{
|
||||
var sections = parent.document.querySelectorAll('section.main');
|
||||
console.log(sections);
|
||||
for(let index = 0; index<sections.length; index++) {{
|
||||
sections[index].scrollTop = sections[index].scrollHeight;
|
||||
}}
|
||||
}}
|
||||
scroll(1);
|
||||
</script>
|
||||
"""
|
||||
st.components.v1.html(js, height=0, width=0)
|
||||
|
||||
|
||||
def init_log():
|
||||
logger.remove()
|
||||
_lvl = "DEBUG"
|
||||
|
||||
def format_record(record):
|
||||
# 获取日志记录中的文件全路径
|
||||
file_path = record["file"].path
|
||||
# 将绝对路径转换为相对于项目根目录的路径
|
||||
relative_path = os.path.relpath(file_path, root_dir)
|
||||
# 更新记录中的文件路径
|
||||
record["file"].path = f"./{relative_path}"
|
||||
# 返回修改后的格式字符串
|
||||
# 您可以根据需要调整这里的格式
|
||||
record['message'] = record['message'].replace(root_dir, ".")
|
||||
|
||||
_format = '<green>{time:%Y-%m-%d %H:%M:%S}</> | ' + \
|
||||
'<level>{level}</> | ' + \
|
||||
'"{file.path}:{line}":<blue> {function}</> ' + \
|
||||
'- <level>{message}</>' + "\n"
|
||||
return _format
|
||||
|
||||
logger.add(
|
||||
sys.stdout,
|
||||
level=_lvl,
|
||||
format=format_record,
|
||||
colorize=True,
|
||||
)
|
||||
|
||||
|
||||
init_log()
|
||||
|
||||
locales = utils.load_locales(i18n_dir)
|
||||
|
||||
|
||||
def tr(key):
|
||||
loc = locales.get(st.session_state['ui_language'], {})
|
||||
return loc.get("Translation", {}).get(key, key)
|
||||
|
||||
|
||||
st.write(tr("Get Help"))
|
||||
|
||||
# 基础设置
|
||||
with st.expander(tr("Basic Settings"), expanded=False):
|
||||
config_panels = st.columns(3)
|
||||
left_config_panel = config_panels[0]
|
||||
middle_config_panel = config_panels[1]
|
||||
right_config_panel = config_panels[2]
|
||||
with left_config_panel:
|
||||
display_languages = []
|
||||
selected_index = 0
|
||||
for i, code in enumerate(locales.keys()):
|
||||
display_languages.append(f"{code} - {locales[code].get('Language')}")
|
||||
if code == st.session_state['ui_language']:
|
||||
selected_index = i
|
||||
|
||||
selected_language = st.selectbox(tr("Language"), options=display_languages,
|
||||
index=selected_index)
|
||||
if selected_language:
|
||||
code = selected_language.split(" - ")[0].strip()
|
||||
st.session_state['ui_language'] = code
|
||||
config.ui['language'] = code
|
||||
|
||||
with middle_config_panel:
|
||||
# openai
|
||||
# moonshot (月之暗面)
|
||||
# oneapi
|
||||
# g4f
|
||||
# azure
|
||||
# qwen (通义千问)
|
||||
# gemini
|
||||
# ollama
|
||||
llm_providers = ['OpenAI', 'Moonshot', 'Azure', 'Qwen', 'Gemini', 'Ollama', 'G4f', 'OneAPI', "Cloudflare"]
|
||||
saved_llm_provider = config.app.get("llm_provider", "OpenAI").lower()
|
||||
saved_llm_provider_index = 0
|
||||
for i, provider in enumerate(llm_providers):
|
||||
if provider.lower() == saved_llm_provider:
|
||||
saved_llm_provider_index = i
|
||||
break
|
||||
|
||||
llm_provider = st.selectbox(tr("LLM Provider"), options=llm_providers, index=saved_llm_provider_index)
|
||||
llm_provider = llm_provider.lower()
|
||||
config.app["llm_provider"] = llm_provider
|
||||
|
||||
llm_api_key = config.app.get(f"{llm_provider}_api_key", "")
|
||||
llm_base_url = config.app.get(f"{llm_provider}_base_url", "")
|
||||
llm_model_name = config.app.get(f"{llm_provider}_model_name", "")
|
||||
llm_account_id = config.app.get(f"{llm_provider}_account_id", "")
|
||||
st_llm_api_key = st.text_input(tr("API Key"), value=llm_api_key, type="password")
|
||||
st_llm_base_url = st.text_input(tr("Base Url"), value=llm_base_url)
|
||||
st_llm_model_name = st.text_input(tr("Model Name"), value=llm_model_name)
|
||||
if st_llm_api_key:
|
||||
config.app[f"{llm_provider}_api_key"] = st_llm_api_key
|
||||
if st_llm_base_url:
|
||||
config.app[f"{llm_provider}_base_url"] = st_llm_base_url
|
||||
if st_llm_model_name:
|
||||
config.app[f"{llm_provider}_model_name"] = st_llm_model_name
|
||||
|
||||
if llm_provider == 'cloudflare':
|
||||
st_llm_account_id = st.text_input(tr("Account ID"), value=llm_account_id)
|
||||
if st_llm_account_id:
|
||||
config.app[f"{llm_provider}_account_id"] = st_llm_account_id
|
||||
|
||||
with right_config_panel:
|
||||
pexels_api_keys = config.app.get("pexels_api_keys", [])
|
||||
if isinstance(pexels_api_keys, str):
|
||||
pexels_api_keys = [pexels_api_keys]
|
||||
pexels_api_key = ", ".join(pexels_api_keys)
|
||||
|
||||
pexels_api_key = st.text_input(tr("Pexels API Key"), value=pexels_api_key, type="password")
|
||||
pexels_api_key = pexels_api_key.replace(" ", "")
|
||||
if pexels_api_key:
|
||||
config.app["pexels_api_keys"] = pexels_api_key.split(",")
|
||||
|
||||
panel = st.columns(3)
|
||||
left_panel = panel[0]
|
||||
middle_panel = panel[1]
|
||||
right_panel = panel[2]
|
||||
|
||||
params = VideoClipParams()
|
||||
|
||||
# 左侧面板
|
||||
with left_panel:
|
||||
with st.container(border=True):
|
||||
st.write(tr("Video Script Configuration"))
|
||||
# 脚本语言
|
||||
video_languages = [
|
||||
(tr("Auto Detect"), ""),
|
||||
]
|
||||
for code in ["zh-CN", "zh-TW", "de-DE", "en-US", "vi-VN"]:
|
||||
video_languages.append((code, code))
|
||||
|
||||
selected_index = st.selectbox(tr("Script Language"),
|
||||
index=0,
|
||||
options=range(len(video_languages)), # 使用索引作为内部选项值
|
||||
format_func=lambda x: video_languages[x][0] # 显示给用户的是标签
|
||||
)
|
||||
params.video_language = video_languages[selected_index][1]
|
||||
|
||||
# 脚本路径
|
||||
suffix = "*.json"
|
||||
song_dir = utils.script_dir()
|
||||
files = glob.glob(os.path.join(song_dir, suffix))
|
||||
script_list = []
|
||||
for file in files:
|
||||
script_list.append({
|
||||
"name": os.path.basename(file),
|
||||
"size": os.path.getsize(file),
|
||||
"file": file,
|
||||
})
|
||||
|
||||
script_path = [(tr("Auto Generate"), ""), ]
|
||||
for code in [file['file'] for file in script_list]:
|
||||
script_path.append((code, code))
|
||||
|
||||
selected_json2 = st.selectbox(tr("Script Files"),
|
||||
index=0,
|
||||
options=range(len(script_path)), # 使用索引作为内部选项值
|
||||
format_func=lambda x: script_path[x][0] # 显示给用户的是标签
|
||||
)
|
||||
params.video_clip_json = script_path[selected_json2][1]
|
||||
video_json_file = params.video_clip_json
|
||||
|
||||
# 视频文件
|
||||
suffix = "*.mp4"
|
||||
song_dir = utils.video_dir()
|
||||
files = glob.glob(os.path.join(song_dir, suffix))
|
||||
video_list = []
|
||||
for file in files:
|
||||
video_list.append({
|
||||
"name": os.path.basename(file),
|
||||
"size": os.path.getsize(file),
|
||||
"file": file,
|
||||
})
|
||||
|
||||
video_path = [(tr("None"), ""), ]
|
||||
for code in [file['file'] for file in video_list]:
|
||||
video_path.append((code, code))
|
||||
|
||||
selected_index2 = st.selectbox(tr("Video File"),
|
||||
index=0,
|
||||
options=range(len(video_path)), # 使用索引作为内部选项值
|
||||
format_func=lambda x: video_path[x][0] # 显示给用户的是标签
|
||||
)
|
||||
params.video_origin_path = video_path[selected_index2][1]
|
||||
|
||||
# 剧情内容
|
||||
video_plot = st.text_area(
|
||||
tr("Plot Description"),
|
||||
value=st.session_state['video_plot'],
|
||||
height=180
|
||||
)
|
||||
|
||||
if st.button(tr("Video Script Generate"), key="auto_generate_script"):
|
||||
with st.spinner(tr("Video Script Generate")):
|
||||
if video_json_file == "" and params.video_origin_path != "":
|
||||
script = llm.gemini_video2json(
|
||||
video_origin_name=params.video_origin_path.split("\\")[-1],
|
||||
video_origin_path=params.video_origin_path,
|
||||
video_plot=video_plot
|
||||
)
|
||||
st.session_state['video_clip_json'] = script
|
||||
cleaned_string = script.strip("```json").strip("```")
|
||||
st.session_state['video_script_list'] = json.loads(cleaned_string)
|
||||
else:
|
||||
with open(video_json_file, 'r', encoding='utf-8') as f:
|
||||
script = f.read()
|
||||
st.session_state['video_clip_json'] = script
|
||||
cleaned_string = script.strip("```json").strip("```")
|
||||
st.session_state['video_script_list'] = json.loads(cleaned_string)
|
||||
|
||||
video_clip_json_details = st.text_area(
|
||||
tr("Video Script"),
|
||||
value=st.session_state['video_clip_json'],
|
||||
height=180
|
||||
)
|
||||
|
||||
button_columns = st.columns(2)
|
||||
with button_columns[0]:
|
||||
if st.button(tr("Save Script"), key="auto_generate_terms", use_container_width=True):
|
||||
if not video_clip_json_details:
|
||||
st.error(tr("请输入视频脚本"))
|
||||
st.stop()
|
||||
|
||||
with st.spinner(tr("保存脚本")):
|
||||
script_dir = utils.script_dir()
|
||||
# 获取当前时间戳,形如 2024-0618-171820
|
||||
timestamp = datetime.datetime.now().strftime("%Y-%m%d-%H%M%S")
|
||||
save_path = os.path.join(script_dir, f"{timestamp}.json")
|
||||
|
||||
# 尝试解析输入的 JSON 数据
|
||||
input_json = str(video_clip_json_details).replace("'", '"')
|
||||
input_json = input_json.strip('```json').strip('```')
|
||||
try:
|
||||
data = json.loads(input_json)
|
||||
except:
|
||||
raise ValueError("视频脚本格式错误,请检查脚本是否符合 JSON 格式")
|
||||
|
||||
# 检查是否是一个列表
|
||||
if not isinstance(data, list):
|
||||
raise ValueError("JSON is not a list")
|
||||
|
||||
# 检查列表中的每个元素是否包含所需的键
|
||||
required_keys = {"picture", "timestamp", "narration"}
|
||||
for item in data:
|
||||
if not isinstance(item, dict):
|
||||
raise ValueError("List 元素不是字典")
|
||||
if not required_keys.issubset(item.keys()):
|
||||
raise ValueError("Dict 元素不包含必需的键")
|
||||
|
||||
# 存储为新的 JSON 文件
|
||||
with open(save_path, 'w', encoding='utf-8') as file:
|
||||
json.dump(data, file, ensure_ascii=False, indent=4)
|
||||
# 将data的值存储到 session_state 中,类似缓存
|
||||
st.session_state['video_script_list'] = data
|
||||
|
||||
logger.debug(f"脚本内容已成功保存到 {save_path}")
|
||||
|
||||
with button_columns[1]:
|
||||
if st.button(tr("Crop Video"), key="auto_crop_video", use_container_width=True):
|
||||
with st.spinner(tr("裁剪视频中...")):
|
||||
st.session_state['task_id'] = str(uuid4())
|
||||
|
||||
if st.session_state.get('video_script_list', None) is not None:
|
||||
video_script_list = st.session_state.video_script_list
|
||||
time_list = [i['timestamp'] for i in video_script_list]
|
||||
subclip_videos = material.clip_videos(
|
||||
task_id=st.session_state['task_id'],
|
||||
timestamp_terms=time_list,
|
||||
origin_video=params.video_origin_path
|
||||
)
|
||||
if subclip_videos is None:
|
||||
st.error(tr("裁剪视频失败"))
|
||||
st.stop()
|
||||
st.session_state['subclip_videos'] = subclip_videos
|
||||
for video_script in video_script_list:
|
||||
try:
|
||||
video_script['path'] = subclip_videos[video_script['timestamp']]
|
||||
except KeyError as e:
|
||||
st.error(f"裁剪视频失败")
|
||||
# logger.debug(f"当前的脚本为:{st.session_state.video_script_list}")
|
||||
else:
|
||||
st.error(tr("请先生成视频脚本"))
|
||||
|
||||
# 新中间面板
|
||||
with middle_panel:
|
||||
with st.container(border=True):
|
||||
st.write(tr("Video Settings"))
|
||||
video_concat_modes = [
|
||||
(tr("Sequential"), "sequential"),
|
||||
(tr("Random"), "random"),
|
||||
]
|
||||
# video_sources = [
|
||||
# (tr("Pexels"), "pexels"),
|
||||
# (tr("Pixabay"), "pixabay"),
|
||||
# (tr("Local file"), "local"),
|
||||
# (tr("TikTok"), "douyin"),
|
||||
# (tr("Bilibili"), "bilibili"),
|
||||
# (tr("Xiaohongshu"), "xiaohongshu"),
|
||||
# ]
|
||||
#
|
||||
# saved_video_source_name = config.app.get("video_source", "pexels")
|
||||
# saved_video_source_index = [v[1] for v in video_sources].index(
|
||||
# saved_video_source_name
|
||||
# )
|
||||
#
|
||||
# selected_index = st.selectbox(
|
||||
# tr("Video Source"),
|
||||
# options=range(len(video_sources)),
|
||||
# format_func=lambda x: video_sources[x][0],
|
||||
# index=saved_video_source_index,
|
||||
# )
|
||||
# params.video_source = video_sources[selected_index][1]
|
||||
# config.app["video_source"] = params.video_source
|
||||
#
|
||||
# if params.video_source == "local":
|
||||
# _supported_types = FILE_TYPE_VIDEOS + FILE_TYPE_IMAGES
|
||||
# uploaded_files = st.file_uploader(
|
||||
# "Upload Local Files",
|
||||
# type=["mp4", "mov", "avi", "flv", "mkv", "jpg", "jpeg", "png"],
|
||||
# accept_multiple_files=True,
|
||||
# )
|
||||
|
||||
selected_index = st.selectbox(
|
||||
tr("Video Concat Mode"),
|
||||
index=1,
|
||||
options=range(len(video_concat_modes)), # 使用索引作为内部选项值
|
||||
format_func=lambda x: video_concat_modes[x][0], # 显示给用户的是标签
|
||||
)
|
||||
params.video_concat_mode = VideoConcatMode(
|
||||
video_concat_modes[selected_index][1]
|
||||
)
|
||||
|
||||
video_aspect_ratios = [
|
||||
(tr("Portrait"), VideoAspect.portrait.value),
|
||||
(tr("Landscape"), VideoAspect.landscape.value),
|
||||
]
|
||||
selected_index = st.selectbox(
|
||||
tr("Video Ratio"),
|
||||
options=range(len(video_aspect_ratios)), # 使用索引作为内部选项值
|
||||
format_func=lambda x: video_aspect_ratios[x][0], # 显示给用户的是标签
|
||||
)
|
||||
params.video_aspect = VideoAspect(video_aspect_ratios[selected_index][1])
|
||||
|
||||
params.video_clip_duration = st.selectbox(
|
||||
tr("Clip Duration"), options=[2, 3, 4, 5, 6, 7, 8, 9, 10], index=1
|
||||
)
|
||||
params.video_count = st.selectbox(
|
||||
tr("Number of Videos Generated Simultaneously"),
|
||||
options=[1, 2, 3, 4, 5],
|
||||
index=0,
|
||||
)
|
||||
with st.container(border=True):
|
||||
st.write(tr("Audio Settings"))
|
||||
|
||||
# tts_providers = ['edge', 'azure']
|
||||
# tts_provider = st.selectbox(tr("TTS Provider"), tts_providers)
|
||||
|
||||
voices = voice.get_all_azure_voices(filter_locals=support_locales)
|
||||
friendly_names = {
|
||||
v: v.replace("Female", tr("Female"))
|
||||
.replace("Male", tr("Male"))
|
||||
.replace("Neural", "")
|
||||
for v in voices
|
||||
}
|
||||
saved_voice_name = config.ui.get("voice_name", "")
|
||||
saved_voice_name_index = 0
|
||||
if saved_voice_name in friendly_names:
|
||||
saved_voice_name_index = list(friendly_names.keys()).index(saved_voice_name)
|
||||
else:
|
||||
for i, v in enumerate(voices):
|
||||
if (
|
||||
v.lower().startswith(st.session_state["ui_language"].lower())
|
||||
and "V2" not in v
|
||||
):
|
||||
saved_voice_name_index = i
|
||||
break
|
||||
|
||||
selected_friendly_name = st.selectbox(
|
||||
tr("Speech Synthesis"),
|
||||
options=list(friendly_names.values()),
|
||||
index=saved_voice_name_index,
|
||||
)
|
||||
|
||||
voice_name = list(friendly_names.keys())[
|
||||
list(friendly_names.values()).index(selected_friendly_name)
|
||||
]
|
||||
params.voice_name = voice_name
|
||||
config.ui["voice_name"] = voice_name
|
||||
|
||||
if st.button(tr("Play Voice")):
|
||||
play_content = params.video_subject
|
||||
if not play_content:
|
||||
play_content = params.video_script
|
||||
if not play_content:
|
||||
play_content = tr("Voice Example")
|
||||
with st.spinner(tr("Synthesizing Voice")):
|
||||
temp_dir = utils.storage_dir("temp", create=True)
|
||||
audio_file = os.path.join(temp_dir, f"tmp-voice-{str(uuid4())}.mp3")
|
||||
sub_maker = voice.tts(
|
||||
text=play_content,
|
||||
voice_name=voice_name,
|
||||
voice_rate=params.voice_rate,
|
||||
voice_file=audio_file,
|
||||
)
|
||||
# if the voice file generation failed, try again with a default content.
|
||||
if not sub_maker:
|
||||
play_content = "This is a example voice. if you hear this, the voice synthesis failed with the original content."
|
||||
sub_maker = voice.tts(
|
||||
text=play_content,
|
||||
voice_name=voice_name,
|
||||
voice_rate=params.voice_rate,
|
||||
voice_file=audio_file,
|
||||
)
|
||||
|
||||
if sub_maker and os.path.exists(audio_file):
|
||||
st.audio(audio_file, format="audio/mp3")
|
||||
if os.path.exists(audio_file):
|
||||
os.remove(audio_file)
|
||||
|
||||
if voice.is_azure_v2_voice(voice_name):
|
||||
saved_azure_speech_region = config.azure.get("speech_region", "")
|
||||
saved_azure_speech_key = config.azure.get("speech_key", "")
|
||||
azure_speech_region = st.text_input(
|
||||
tr("Speech Region"), value=saved_azure_speech_region
|
||||
)
|
||||
azure_speech_key = st.text_input(
|
||||
tr("Speech Key"), value=saved_azure_speech_key, type="password"
|
||||
)
|
||||
config.azure["speech_region"] = azure_speech_region
|
||||
config.azure["speech_key"] = azure_speech_key
|
||||
|
||||
params.voice_volume = st.selectbox(
|
||||
tr("Speech Volume"),
|
||||
options=[0.6, 0.8, 1.0, 1.2, 1.5, 2.0, 3.0, 4.0, 5.0],
|
||||
index=2,
|
||||
)
|
||||
|
||||
params.voice_rate = st.selectbox(
|
||||
tr("Speech Rate"),
|
||||
options=[0.8, 0.9, 1.0, 1.1, 1.2, 1.3, 1.5, 1.8, 2.0],
|
||||
index=2,
|
||||
)
|
||||
|
||||
bgm_options = [
|
||||
(tr("No Background Music"), ""),
|
||||
(tr("Random Background Music"), "random"),
|
||||
(tr("Custom Background Music"), "custom"),
|
||||
]
|
||||
selected_index = st.selectbox(
|
||||
tr("Background Music"),
|
||||
index=1,
|
||||
options=range(len(bgm_options)), # 使用索引作为内部选项值
|
||||
format_func=lambda x: bgm_options[x][0], # 显示给用户的是标签
|
||||
)
|
||||
# 获取选择的背景音乐类型
|
||||
params.bgm_type = bgm_options[selected_index][1]
|
||||
|
||||
# 根据选择显示或隐藏组件
|
||||
if params.bgm_type == "custom":
|
||||
custom_bgm_file = st.text_input(tr("Custom Background Music File"))
|
||||
if custom_bgm_file and os.path.exists(custom_bgm_file):
|
||||
params.bgm_file = custom_bgm_file
|
||||
# st.write(f":red[已选择自定义背景音乐]:**{custom_bgm_file}**")
|
||||
params.bgm_volume = st.selectbox(
|
||||
tr("Background Music Volume"),
|
||||
options=[0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0],
|
||||
index=2,
|
||||
)
|
||||
|
||||
# 新右侧面板
|
||||
with right_panel:
|
||||
with st.container(border=True):
|
||||
st.write(tr("Subtitle Settings"))
|
||||
params.subtitle_enabled = st.checkbox(tr("Enable Subtitles"), value=True)
|
||||
font_names = get_all_fonts()
|
||||
saved_font_name = config.ui.get("font_name", "")
|
||||
saved_font_name_index = 0
|
||||
if saved_font_name in font_names:
|
||||
saved_font_name_index = font_names.index(saved_font_name)
|
||||
params.font_name = st.selectbox(
|
||||
tr("Font"), font_names, index=saved_font_name_index
|
||||
)
|
||||
config.ui["font_name"] = params.font_name
|
||||
|
||||
subtitle_positions = [
|
||||
(tr("Top"), "top"),
|
||||
(tr("Center"), "center"),
|
||||
(tr("Bottom"), "bottom"),
|
||||
(tr("Custom"), "custom"),
|
||||
]
|
||||
selected_index = st.selectbox(
|
||||
tr("Position"),
|
||||
index=2,
|
||||
options=range(len(subtitle_positions)),
|
||||
format_func=lambda x: subtitle_positions[x][0],
|
||||
)
|
||||
params.subtitle_position = subtitle_positions[selected_index][1]
|
||||
|
||||
if params.subtitle_position == "custom":
|
||||
custom_position = st.text_input(
|
||||
tr("Custom Position (% from top)"), value="70.0"
|
||||
)
|
||||
try:
|
||||
params.custom_position = float(custom_position)
|
||||
if params.custom_position < 0 or params.custom_position > 100:
|
||||
st.error(tr("Please enter a value between 0 and 100"))
|
||||
except ValueError:
|
||||
st.error(tr("Please enter a valid number"))
|
||||
|
||||
font_cols = st.columns([0.3, 0.7])
|
||||
with font_cols[0]:
|
||||
saved_text_fore_color = config.ui.get("text_fore_color", "#FFFFFF")
|
||||
params.text_fore_color = st.color_picker(
|
||||
tr("Font Color"), saved_text_fore_color
|
||||
)
|
||||
config.ui["text_fore_color"] = params.text_fore_color
|
||||
|
||||
with font_cols[1]:
|
||||
saved_font_size = config.ui.get("font_size", 60)
|
||||
params.font_size = st.slider(tr("Font Size"), 30, 100, saved_font_size)
|
||||
config.ui["font_size"] = params.font_size
|
||||
|
||||
stroke_cols = st.columns([0.3, 0.7])
|
||||
with stroke_cols[0]:
|
||||
params.stroke_color = st.color_picker(tr("Stroke Color"), "#000000")
|
||||
with stroke_cols[1]:
|
||||
params.stroke_width = st.slider(tr("Stroke Width"), 0.0, 10.0, 1.5)
|
||||
|
||||
# 视频编辑面板
|
||||
with st.expander(tr("视频审查"), expanded=False):
|
||||
try:
|
||||
video_list = st.session_state['video_script_list']
|
||||
except KeyError as e:
|
||||
video_list = []
|
||||
|
||||
# 计算列数和行数
|
||||
num_videos = len(video_list)
|
||||
cols_per_row = 3
|
||||
rows = (num_videos + cols_per_row - 1) // cols_per_row # 向上取整计算行数
|
||||
|
||||
# 使用容器展示视频
|
||||
for row in range(rows):
|
||||
cols = st.columns(cols_per_row)
|
||||
for col in range(cols_per_row):
|
||||
index = row * cols_per_row + col
|
||||
if index < num_videos:
|
||||
with cols[col]:
|
||||
video_info = video_list[index]
|
||||
video_path = video_info.get('path')
|
||||
if video_path is not None:
|
||||
initial_narration = video_info['narration']
|
||||
initial_picture = video_info['picture']
|
||||
initial_timestamp = video_info['timestamp']
|
||||
|
||||
with open(video_path, 'rb') as video_file:
|
||||
video_bytes = video_file.read()
|
||||
st.video(video_bytes)
|
||||
|
||||
# 可编辑的输入框
|
||||
text_panels = st.columns(2)
|
||||
with text_panels[0]:
|
||||
text1 = st.text_area("时间戳", value=initial_timestamp, height=20)
|
||||
with text_panels[1]:
|
||||
text2 = st.text_area("画面描述", value=initial_picture, height=20)
|
||||
text3 = st.text_area("解说旁白", value=initial_narration, height=100)
|
||||
|
||||
# 清空文本框按钮
|
||||
if st.button("重新生成", key=f"button_{index}"):
|
||||
print(123123)
|
||||
# with st.spinner(tr("大模型生成中...")):
|
||||
|
||||
start_button = st.button(tr("Generate Video"), use_container_width=True, type="primary")
|
||||
if start_button:
|
||||
config.save_config()
|
||||
task_id = st.session_state['task_id']
|
||||
if not params.video_clip_json:
|
||||
st.error(tr("脚本文件不能为空"))
|
||||
scroll_to_bottom()
|
||||
st.stop()
|
||||
if not params.video_origin_path:
|
||||
st.error(tr("视频文件不能为空"))
|
||||
scroll_to_bottom()
|
||||
st.stop()
|
||||
if llm_provider != 'g4f' and not config.app.get(f"{llm_provider}_api_key", ""):
|
||||
st.error(tr("请输入 LLM API 密钥"))
|
||||
scroll_to_bottom()
|
||||
st.stop()
|
||||
|
||||
log_container = st.empty()
|
||||
log_records = []
|
||||
|
||||
|
||||
def log_received(msg):
|
||||
with log_container:
|
||||
log_records.append(msg)
|
||||
st.code("\n".join(log_records))
|
||||
|
||||
|
||||
logger.add(log_received)
|
||||
|
||||
st.toast(tr("生成视频"))
|
||||
logger.info(tr("开始生成视频"))
|
||||
logger.info(utils.to_json(params))
|
||||
scroll_to_bottom()
|
||||
|
||||
result = tm.start_subclip(task_id=task_id, params=params, subclip_path_videos=st.session_state.subclip_videos)
|
||||
|
||||
video_files = result.get("videos", [])
|
||||
st.success(tr("视频生成完成"))
|
||||
try:
|
||||
if video_files:
|
||||
# 将视频播放器居中
|
||||
player_cols = st.columns(len(video_files) * 2 + 1)
|
||||
for i, url in enumerate(video_files):
|
||||
player_cols[i * 2 + 1].video(url)
|
||||
except Exception as e:
|
||||
pass
|
||||
|
||||
open_task_folder(task_id)
|
||||
logger.info(tr("视频生成完成"))
|
||||
scroll_to_bottom()
|
||||
|
||||
config.save_config()
|
||||
79
webui/i18n/de.json
Normal file
@ -0,0 +1,79 @@
|
||||
{
|
||||
"Language": "German",
|
||||
"Translation": {
|
||||
"Video Script Settings": "**Drehbuch / Topic des Videos**",
|
||||
"Video Subject": "Worum soll es in dem Video gehen? (Geben Sie ein Keyword an, :red[Dank KI wird automatisch ein Drehbuch generieren])",
|
||||
"Script Language": "Welche Sprache soll zum Generieren von Drehbüchern verwendet werden? :red[KI generiert anhand dieses Begriffs das Drehbuch]",
|
||||
"Generate Video Script and Keywords": "Klicken Sie hier, um mithilfe von KI ein [Video Drehbuch] und [Video Keywords] basierend auf dem **Keyword** zu generieren.",
|
||||
"Auto Detect": "Automatisch erkennen",
|
||||
"Video Script": "Drehbuch (Storybook) (:blue[① Optional, KI generiert ② Die richtige Zeichensetzung hilft bei der Erstellung von Untertiteln])",
|
||||
"Generate Video Keywords": "Klicken Sie, um KI zum Generieren zu verwenden [Video Keywords] basierend auf dem **Drehbuch**",
|
||||
"Please Enter the Video Subject": "Bitte geben Sie zuerst das Drehbuch an",
|
||||
"Generating Video Script and Keywords": "KI generiert ein Drehbuch und Schlüsselwörter...",
|
||||
"Generating Video Keywords": "AI is generating video keywords...",
|
||||
"Video Keywords": "Video Schlüsselwörter (:blue[① Optional, KI generiert ② Verwende **, (Kommas)** zur Trennung der Wörter, in englischer Sprache])",
|
||||
"Video Settings": "**Video Einstellungen**",
|
||||
"Video Concat Mode": "Videoverkettungsmodus",
|
||||
"Random": "Zufällige Verkettung (empfohlen)",
|
||||
"Sequential": "Sequentielle Verkettung",
|
||||
"Video Ratio": "Video-Seitenverhältnis",
|
||||
"Portrait": "Portrait 9:16",
|
||||
"Landscape": "Landschaft 16:9",
|
||||
"Clip Duration": "Maximale Dauer einzelner Videoclips in sekunden",
|
||||
"Number of Videos Generated Simultaneously": "Anzahl der parallel generierten Videos",
|
||||
"Audio Settings": "**Audio Einstellungen**",
|
||||
"Speech Synthesis": "Sprachausgabe",
|
||||
"Speech Region": "Region(:red[Required,[Get Region](https://portal.azure.com/#view/Microsoft_Azure_ProjectOxford/CognitiveServicesHub/~/SpeechServices)])",
|
||||
"Speech Key": "API Key(:red[Required,[Get API Key](https://portal.azure.com/#view/Microsoft_Azure_ProjectOxford/CognitiveServicesHub/~/SpeechServices)])",
|
||||
"Speech Volume": "Lautstärke der Sprachausgabe",
|
||||
"Speech Rate": "Lesegeschwindigkeit (1,0 bedeutet 1x)",
|
||||
"Male": "Männlich",
|
||||
"Female": "Weiblich",
|
||||
"Background Music": "Hintergrundmusik",
|
||||
"No Background Music": "Ohne Hintergrundmusik",
|
||||
"Random Background Music": "Zufällig erzeugte Hintergrundmusik",
|
||||
"Custom Background Music": "Benutzerdefinierte Hintergrundmusik",
|
||||
"Custom Background Music File": "Bitte gib den Pfad zur Musikdatei an:",
|
||||
"Background Music Volume": "Lautstärke: (0.2 entspricht 20%, sollte nicht zu laut sein)",
|
||||
"Subtitle Settings": "**Untertitel-Einstellungen**",
|
||||
"Enable Subtitles": "Untertitel aktivieren (Wenn diese Option deaktiviert ist, werden die Einstellungen nicht genutzt)",
|
||||
"Font": "Schriftart des Untertitels",
|
||||
"Position": "Ausrichtung des Untertitels",
|
||||
"Top": "Oben",
|
||||
"Center": "Mittig",
|
||||
"Bottom": "Unten (empfohlen)",
|
||||
"Custom": "Benutzerdefinierte Position (70, was 70% von oben bedeutet)",
|
||||
"Font Size": "Schriftgröße für Untertitel",
|
||||
"Font Color": "Schriftfarbe",
|
||||
"Stroke Color": "Kontur",
|
||||
"Stroke Width": "Breite der Untertitelkontur",
|
||||
"Generate Video": "Generiere Videos durch KI",
|
||||
"Video Script and Subject Cannot Both Be Empty": "Das Video-Thema und Drehbuch dürfen nicht beide leer sein",
|
||||
"Generating Video": "Video wird erstellt, bitte warten...",
|
||||
"Start Generating Video": "Beginne mit der Generierung",
|
||||
"Video Generation Completed": "Video erfolgreich generiert",
|
||||
"Video Generation Failed": "Video Generierung fehlgeschlagen",
|
||||
"You can download the generated video from the following links": "Sie können das generierte Video über die folgenden Links herunterladen",
|
||||
"Basic Settings": "**Grunde Instellungen**",
|
||||
"Pexels API Key": "Pexels API Key ([Get API Key](https://www.pexels.com/api/))",
|
||||
"Pixabay API Key": "Pixabay API Key ([Get API Key](https://pixabay.com/api/docs/#api_search_videos))",
|
||||
"Language": "Language",
|
||||
"LLM Provider": "LLM Provider",
|
||||
"API Key": "API Key (:red[Required])",
|
||||
"Base Url": "Base Url",
|
||||
"Model Name": "Model Name",
|
||||
"Please Enter the LLM API Key": "Please Enter the **LLM API Key**",
|
||||
"Please Enter the Pexels API Key": "Please Enter the **Pexels API Key**",
|
||||
"Please Enter the Pixabay API Key": "Please Enter the **Pixabay API Key**",
|
||||
"Get Help": "If you need help, or have any questions, you can join discord for help ",
|
||||
"Video Source": "Video Source",
|
||||
"TikTok": "TikTok (TikTok support is coming soon)",
|
||||
"Bilibili": "Bilibili (Bilibili support is coming soon)",
|
||||
"Xiaohongshu": "Xiaohongshu (Xiaohongshu support is coming soon)",
|
||||
"Local file": "Local file",
|
||||
"Play Voice": "Play Voice",
|
||||
"Voice Example": "This is an example text for testing speech synthesis",
|
||||
"Synthesizing Voice": "Synthesizing voice, please wait...",
|
||||
"TTS Provider": "Select the voice synthesis provider"
|
||||
}
|
||||
}
|
||||
81
webui/i18n/en.json
Normal file
@ -0,0 +1,81 @@
|
||||
{
|
||||
"Language": "English",
|
||||
"Translation": {
|
||||
"Video Script Settings": "**Video Script Settings**",
|
||||
"Video Subject": "Video Subject (Provide a keyword, :red[AI will automatically generate] video script)",
|
||||
"Script Language": "Language for Generating Video Script (AI will automatically output based on the language of your subject)",
|
||||
"Generate Video Script and Keywords": "Click to use AI to generate [Video Script] and [Video Keywords] based on **subject**",
|
||||
"Auto Detect": "Auto Detect",
|
||||
"Video Script": "Video Script (:blue[① Optional, AI generated ② Proper punctuation helps with subtitle generation])",
|
||||
"Generate Video Keywords": "Click to use AI to generate [Video Keywords] based on **script**",
|
||||
"Please Enter the Video Subject": "Please Enter the Video Script First",
|
||||
"Generating Video Script and Keywords": "AI is generating video script and keywords...",
|
||||
"Generating Video Keywords": "AI is generating video keywords...",
|
||||
"Video Keywords": "Video Keywords (:blue[① Optional, AI generated ② Use **English commas** for separation, English only])",
|
||||
"Video Settings": "**Video Settings**",
|
||||
"Video Concat Mode": "Video Concatenation Mode",
|
||||
"Random": "Random Concatenation (Recommended)",
|
||||
"Sequential": "Sequential Concatenation",
|
||||
"Video Ratio": "Video Aspect Ratio",
|
||||
"Portrait": "Portrait 9:16",
|
||||
"Landscape": "Landscape 16:9",
|
||||
"Clip Duration": "Maximum Duration of Video Clips (seconds)",
|
||||
"Number of Videos Generated Simultaneously": "Number of Videos Generated Simultaneously",
|
||||
"Audio Settings": "**Audio Settings**",
|
||||
"Speech Synthesis": "Speech Synthesis Voice",
|
||||
"Speech Region": "Region(:red[Required,[Get Region](https://portal.azure.com/#view/Microsoft_Azure_ProjectOxford/CognitiveServicesHub/~/SpeechServices)])",
|
||||
"Speech Key": "API Key(:red[Required,[Get API Key](https://portal.azure.com/#view/Microsoft_Azure_ProjectOxford/CognitiveServicesHub/~/SpeechServices)])",
|
||||
"Speech Volume": "Speech Volume (1.0 represents 100%)",
|
||||
"Speech Rate": "Speech Rate (1.0 means 1x speed)",
|
||||
"Male": "Male",
|
||||
"Female": "Female",
|
||||
"Background Music": "Background Music",
|
||||
"No Background Music": "No Background Music",
|
||||
"Random Background Music": "Random Background Music",
|
||||
"Custom Background Music": "Custom Background Music",
|
||||
"Custom Background Music File": "Please enter the file path for custom background music:",
|
||||
"Background Music Volume": "Background Music Volume (0.2 represents 20%, background music should not be too loud)",
|
||||
"Subtitle Settings": "**Subtitle Settings**",
|
||||
"Enable Subtitles": "Enable Subtitles (If unchecked, the settings below will not take effect)",
|
||||
"Font": "Subtitle Font",
|
||||
"Position": "Subtitle Position",
|
||||
"Top": "Top",
|
||||
"Center": "Center",
|
||||
"Bottom": "Bottom (Recommended)",
|
||||
"Custom": "Custom position (70, indicating 70% down from the top)",
|
||||
"Font Size": "Subtitle Font Size",
|
||||
"Font Color": "Subtitle Font Color",
|
||||
"Stroke Color": "Subtitle Outline Color",
|
||||
"Stroke Width": "Subtitle Outline Width",
|
||||
"Generate Video": "Generate Video",
|
||||
"Video Script and Subject Cannot Both Be Empty": "Video Subject and Video Script cannot both be empty",
|
||||
"Generating Video": "Generating video, please wait...",
|
||||
"Start Generating Video": "Start Generating Video",
|
||||
"Video Generation Completed": "Video Generation Completed",
|
||||
"Video Generation Failed": "Video Generation Failed",
|
||||
"You can download the generated video from the following links": "You can download the generated video from the following links",
|
||||
"Pexels API Key": "Pexels API Key ([Get API Key](https://www.pexels.com/api/))",
|
||||
"Pixabay API Key": "Pixabay API Key ([Get API Key](https://pixabay.com/api/docs/#api_search_videos))",
|
||||
"Basic Settings": "**Basic Settings** (:blue[Click to expand])",
|
||||
"Language": "Language",
|
||||
"LLM Provider": "LLM Provider",
|
||||
"API Key": "API Key (:red[Required])",
|
||||
"Base Url": "Base Url",
|
||||
"Account ID": "Account ID (Get from Cloudflare dashboard)",
|
||||
"Model Name": "Model Name",
|
||||
"Please Enter the LLM API Key": "Please Enter the **LLM API Key**",
|
||||
"Please Enter the Pexels API Key": "Please Enter the **Pexels API Key**",
|
||||
"Please Enter the Pixabay API Key": "Please Enter the **Pixabay API Key**",
|
||||
"Get Help": "If you need help, or have any questions, you can join discord for help ",
|
||||
"Video Source": "Video Source",
|
||||
"TikTok": "TikTok (TikTok support is coming soon)",
|
||||
"Bilibili": "Bilibili (Bilibili support is coming soon)",
|
||||
"Xiaohongshu": "Xiaohongshu (Xiaohongshu support is coming soon)",
|
||||
"Local file": "Local file",
|
||||
"Play Voice": "Play Voice",
|
||||
"Voice Example": "This is an example text for testing speech synthesis",
|
||||
"Synthesizing Voice": "Synthesizing voice, please wait...",
|
||||
"TTS Provider": "Select the voice synthesis provider",
|
||||
"Hide Log": "Hide Log"
|
||||
}
|
||||
}
|
||||
80
webui/i18n/vi.json
Normal file
@ -0,0 +1,80 @@
|
||||
{
|
||||
"Language": "Tiếng Việt",
|
||||
"Translation": {
|
||||
"Video Script Settings": "**Cài Đặt Kịch Bản Video**",
|
||||
"Video Subject": "Chủ Đề Video (Cung cấp một từ khóa, :red[AI sẽ tự động tạo ra] kịch bản video)",
|
||||
"Script Language": "Ngôn Ngữ cho Việc Tạo Kịch Bản Video (AI sẽ tự động xuất ra dựa trên ngôn ngữ của chủ đề của bạn)",
|
||||
"Generate Video Script and Keywords": "Nhấn để sử dụng AI để tạo [Kịch Bản Video] và [Từ Khóa Video] dựa trên **chủ đề**",
|
||||
"Auto Detect": "Tự Động Phát Hiện",
|
||||
"Video Script": "Kịch Bản Video (:blue[① Tùy chọn, AI tạo ra ② Dấu câu chính xác giúp việc tạo phụ đề)",
|
||||
"Generate Video Keywords": "Nhấn để sử dụng AI để tạo [Từ Khóa Video] dựa trên **kịch bản**",
|
||||
"Please Enter the Video Subject": "Vui lòng Nhập Kịch Bản Video Trước",
|
||||
"Generating Video Script and Keywords": "AI đang tạo kịch bản video và từ khóa...",
|
||||
"Generating Video Keywords": "AI đang tạo từ khóa video...",
|
||||
"Video Keywords": "Từ Khóa Video (:blue[① Tùy chọn, AI tạo ra ② Sử dụng dấu phẩy **Tiếng Anh** để phân tách, chỉ sử dụng Tiếng Anh])",
|
||||
"Video Settings": "**Cài Đặt Video**",
|
||||
"Video Concat Mode": "Chế Độ Nối Video",
|
||||
"Random": "Nối Ngẫu Nhiên (Được Khuyến Nghị)",
|
||||
"Sequential": "Nối Theo Thứ Tự",
|
||||
"Video Ratio": "Tỷ Lệ Khung Hình Video",
|
||||
"Portrait": "Dọc 9:16",
|
||||
"Landscape": "Ngang 16:9",
|
||||
"Clip Duration": "Thời Lượng Tối Đa Của Đoạn Video (giây)",
|
||||
"Number of Videos Generated Simultaneously": "Số Video Được Tạo Ra Đồng Thời",
|
||||
"Audio Settings": "**Cài Đặt Âm Thanh**",
|
||||
"Speech Synthesis": "Giọng Đọc Văn Bản",
|
||||
"Speech Region": "Vùng(:red[Bắt Buộc,[Lấy Vùng](https://portal.azure.com/#view/Microsoft_Azure_ProjectOxford/CognitiveServicesHub/~/SpeechServices)])",
|
||||
"Speech Key": "Khóa API(:red[Bắt Buộc,[Lấy Khóa API](https://portal.azure.com/#view/Microsoft_Azure_ProjectOxford/CognitiveServicesHub/~/SpeechServices)])",
|
||||
"Speech Volume": "Âm Lượng Giọng Đọc (1.0 đại diện cho 100%)",
|
||||
"Speech Rate": "Tốc độ đọc (1.0 biểu thị tốc độ gốc)",
|
||||
"Male": "Nam",
|
||||
"Female": "Nữ",
|
||||
"Background Music": "Âm Nhạc Nền",
|
||||
"No Background Music": "Không Có Âm Nhạc Nền",
|
||||
"Random Background Music": "Âm Nhạc Nền Ngẫu Nhiên",
|
||||
"Custom Background Music": "Âm Nhạc Nền Tùy Chỉnh",
|
||||
"Custom Background Music File": "Vui lòng nhập đường dẫn tệp cho âm nhạc nền tùy chỉnh:",
|
||||
"Background Music Volume": "Âm Lượng Âm Nhạc Nền (0.2 đại diện cho 20%, âm nhạc nền không nên quá to)",
|
||||
"Subtitle Settings": "**Cài Đặt Phụ Đề**",
|
||||
"Enable Subtitles": "Bật Phụ Đề (Nếu không chọn, các cài đặt dưới đây sẽ không có hiệu lực)",
|
||||
"Font": "Phông Chữ Phụ Đề",
|
||||
"Position": "Vị Trí Phụ Đề",
|
||||
"Top": "Trên",
|
||||
"Center": "Giữa",
|
||||
"Bottom": "Dưới (Được Khuyến Nghị)",
|
||||
"Custom": "Vị trí tùy chỉnh (70, chỉ ra là cách đầu trang 70%)",
|
||||
"Font Size": "Cỡ Chữ Phụ Đề",
|
||||
"Font Color": "Màu Chữ Phụ Đề",
|
||||
"Stroke Color": "Màu Viền Phụ Đề",
|
||||
"Stroke Width": "Độ Rộng Viền Phụ Đề",
|
||||
"Generate Video": "Tạo Video",
|
||||
"Video Script and Subject Cannot Both Be Empty": "Chủ Đề Video và Kịch Bản Video không thể cùng trống",
|
||||
"Generating Video": "Đang tạo video, vui lòng đợi...",
|
||||
"Start Generating Video": "Bắt Đầu Tạo Video",
|
||||
"Video Generation Completed": "Hoàn Tất Tạo Video",
|
||||
"Video Generation Failed": "Tạo Video Thất Bại",
|
||||
"You can download the generated video from the following links": "Bạn có thể tải video được tạo ra từ các liên kết sau",
|
||||
"Pexels API Key": "Khóa API Pexels ([Lấy Khóa API](https://www.pexels.com/api/))",
|
||||
"Pixabay API Key": "Pixabay API Key ([Get API Key](https://pixabay.com/api/docs/#api_search_videos))",
|
||||
"Basic Settings": "**Cài Đặt Cơ Bản** (:blue[Nhấp để mở rộng])",
|
||||
"Language": "Ngôn Ngữ",
|
||||
"LLM Provider": "Nhà Cung Cấp LLM",
|
||||
"API Key": "Khóa API (:red[Bắt Buộc])",
|
||||
"Base Url": "Url Cơ Bản",
|
||||
"Account ID": "ID Tài Khoản (Lấy từ bảng điều khiển Cloudflare)",
|
||||
"Model Name": "Tên Mô Hình",
|
||||
"Please Enter the LLM API Key": "Vui lòng Nhập **Khóa API LLM**",
|
||||
"Please Enter the Pexels API Key": "Vui lòng Nhập **Khóa API Pexels**",
|
||||
"Please Enter the Pixabay API Key": "Vui lòng Nhập **Pixabay API Key**",
|
||||
"Get Help": "Nếu bạn cần giúp đỡ hoặc có bất kỳ câu hỏi nào, bạn có thể tham gia discord để được giúp đỡ ",
|
||||
"Video Source": "Video Source",
|
||||
"TikTok": "TikTok (TikTok support is coming soon)",
|
||||
"Bilibili": "Bilibili (Bilibili support is coming soon)",
|
||||
"Xiaohongshu": "Xiaohongshu (Xiaohongshu support is coming soon)",
|
||||
"Local file": "Local file",
|
||||
"Play Voice": "Play Voice",
|
||||
"Voice Example": "This is an example text for testing speech synthesis",
|
||||
"Synthesizing Voice": "Synthesizing voice, please wait...",
|
||||
"TTS Provider": "Select the voice synthesis provider"
|
||||
}
|
||||
}
|
||||
88
webui/i18n/zh.json
Normal file
@ -0,0 +1,88 @@
|
||||
{
|
||||
"Language": "简体中文",
|
||||
"Translation": {
|
||||
"Video Script Configuration": "**视频脚本配置**",
|
||||
"Video Script Generate": "生成视频脚本",
|
||||
"Video Subject": "视频主题(给定一个关键词,:red[AI自动生成]视频文案)",
|
||||
"Script Language": "生成视频脚本的语言(一般情况AI会自动根据你输入的主题语言输出)",
|
||||
"Script Files": "脚本文件",
|
||||
"Generate Video Script and Keywords": "点击使用AI根据**主题**生成 【视频文案】 和 【视频关键词】",
|
||||
"Auto Detect": "自动检测",
|
||||
"Auto Generate": "自动生成",
|
||||
"Video Script": "视频脚本(:blue[①可不填,使用AI生成 ②合理使用标点断句,有助于生成字幕])",
|
||||
"Save Script": "保存脚本",
|
||||
"Crop Video": "裁剪视频",
|
||||
"Video File": "视频文件(:blue)",
|
||||
"Plot Description": "剧情描述 (:blue[可从 https://www.tvmao.com/ 获取])",
|
||||
"Generate Video Keywords": "点击使用AI根据**文案**生成【视频关键词】",
|
||||
"Please Enter the Video Subject": "请先填写视频文案",
|
||||
"Generating Video Script and Keywords": "AI正在生成视频文案和关键词...",
|
||||
"Generating Video Keywords": "AI正在生成视频关键词...",
|
||||
"Video Keywords": "视频关键词(:blue[①可不填,使用AI生成 ②用**英文逗号**分隔,只支持英文])",
|
||||
"Video Settings": "**视频设置**",
|
||||
"Video Concat Mode": "视频拼接模式",
|
||||
"Random": "随机拼接(推荐)",
|
||||
"Sequential": "顺序拼接",
|
||||
"Video Ratio": "视频比例",
|
||||
"Portrait": "竖屏 9:16(抖音视频)",
|
||||
"Landscape": "横屏 16:9(西瓜视频)",
|
||||
"Clip Duration": "视频片段最大时长(秒)(**不是视频总长度**,是指每个**合成片段**的长度)",
|
||||
"Number of Videos Generated Simultaneously": "同时生成视频数量",
|
||||
"Audio Settings": "**音频设置**",
|
||||
"Speech Synthesis": "朗读声音(:red[**与文案语言保持一致**。注意:V2版效果更好,但是需要API KEY])",
|
||||
"Speech Region": "服务区域 (:red[必填,[点击获取](https://portal.azure.com/#view/Microsoft_Azure_ProjectOxford/CognitiveServicesHub/~/SpeechServices)])",
|
||||
"Speech Key": "API Key (:red[必填,密钥1 或 密钥2 均可 [点击获取](https://portal.azure.com/#view/Microsoft_Azure_ProjectOxford/CognitiveServicesHub/~/SpeechServices)])",
|
||||
"Speech Volume": "朗读音量(1.0表示100%)",
|
||||
"Speech Rate": "朗读速度(1.0表示1倍速)",
|
||||
"Male": "男性",
|
||||
"Female": "女性",
|
||||
"Background Music": "背景音乐",
|
||||
"No Background Music": "无背景音乐",
|
||||
"Random Background Music": "随机背景音乐",
|
||||
"Custom Background Music": "自定义背景音乐",
|
||||
"Custom Background Music File": "请输入自定义背景音乐的文件路径",
|
||||
"Background Music Volume": "背景音乐音量(0.2表示20%,背景声音不宜过高)",
|
||||
"Subtitle Settings": "**字幕设置**",
|
||||
"Enable Subtitles": "启用字幕(若取消勾选,下面的设置都将不生效)",
|
||||
"Font": "字幕字体",
|
||||
"Position": "字幕位置",
|
||||
"Top": "顶部",
|
||||
"Center": "中间",
|
||||
"Bottom": "底部(推荐)",
|
||||
"Custom": "自定义位置(70,表示离顶部70%的位置)",
|
||||
"Font Size": "字幕大小",
|
||||
"Font Color": "字幕颜色",
|
||||
"Stroke Color": "描边颜色",
|
||||
"Stroke Width": "描边粗细",
|
||||
"Generate Video": "生成视频",
|
||||
"Video Script and Subject Cannot Both Be Empty": "视频主题 和 视频文案,不能同时为空",
|
||||
"Generating Video": "正在生成视频,请稍候...",
|
||||
"Start Generating Video": "开始生成视频",
|
||||
"Video Generation Completed": "视频生成完成",
|
||||
"Video Generation Failed": "视频生成失败",
|
||||
"You can download the generated video from the following links": "你可以从以下链接下载生成的视频",
|
||||
"Basic Settings": "**基础设置** (:blue[点击展开])",
|
||||
"Language": "界面语言",
|
||||
"Pexels API Key": "Pexels API Key ([点击获取](https://www.pexels.com/api/)) :red[推荐使用]",
|
||||
"Pixabay API Key": "Pixabay API Key ([点击获取](https://pixabay.com/api/docs/#api_search_videos)) :red[可以不用配置,如果 Pexels 无法使用,再选择Pixabay]",
|
||||
"LLM Provider": "大模型提供商",
|
||||
"API Key": "API Key (:red[必填,需要到大模型提供商的后台申请])",
|
||||
"Base Url": "Base Url (可选)",
|
||||
"Account ID": "账户ID (Cloudflare的dash面板url中获取)",
|
||||
"Model Name": "模型名称 (:blue[需要到大模型提供商的后台确认被授权的模型名称])",
|
||||
"Please Enter the LLM API Key": "请先填写大模型 **API Key**",
|
||||
"Please Enter the Pexels API Key": "请先填写 **Pexels API Key**",
|
||||
"Please Enter the Pixabay API Key": "请先填写 **Pixabay API Key**",
|
||||
"Get Help": "一站式 AI 影视解说+自动化剪辑工具\uD83C\uDF89\uD83C\uDF89\uD83C\uDF89\n\n有任何问题或建议,可以加入 **社区频道** 求助或讨论:https://discord.gg/WBKChhmZ",
|
||||
"Video Source": "视频来源",
|
||||
"TikTok": "抖音 (TikTok 支持中,敬请期待)",
|
||||
"Bilibili": "哔哩哔哩 (Bilibili 支持中,敬请期待)",
|
||||
"Xiaohongshu": "小红书 (Xiaohongshu 支持中,敬请期待)",
|
||||
"Local file": "本地文件",
|
||||
"Play Voice": "试听语音合成",
|
||||
"Voice Example": "这是一段测试语音合成的示例文本",
|
||||
"Synthesizing Voice": "语音合成中,请稍候...",
|
||||
"TTS Provider": "语音合成提供商",
|
||||
"Hide Log": "隐藏日志"
|
||||
}
|
||||
}
|
||||