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# 🎙️ Simple Podcast Generator
> Easily transform your ideas into lively and engaging multi-person dialogue podcasts with one click!
> [中文版本](README.md)
This is a powerful script tool that leverages the wisdom of **OpenAI API** to generate insightful podcast scripts, and through **TTS (Text-to-Speech)** API services, transforms cold text into warm audio. You just need to provide a topic, and leave the rest to it!
✨ The podcast script generation logic of this project is deeply inspired by the [SurfSense](https://github.com/MODSetter/SurfSense) project. We would like to express our heartfelt thanks to their open-source contributions!
---
## ✨ Core Highlights
* **🤖 AI-Driven Scripts**: Automatically create high-quality, in-depth podcast dialogue scripts with the power of OpenAI models.
* **👥 Multi-Character Support**: Freely define multiple podcast characters (such as host, guest), and assign unique TTS voices to each character.
* **🔌 Flexible TTS Integration**: Seamlessly connect to your self-hosted or third-party TTS services through simple API URL configuration.
* **🔊 Intelligent Audio Synthesis**: Automatically splice voice segments of each character accurately, and support **volume and speed adjustment** to synthesize a complete, smooth podcast audio file (`.wav` format).
* **⌨️ Convenient Command-Line Interface**: Provides clear command-line parameters, giving you full control over every aspect of the podcast generation process.
---
## 🛠️ Installation Guide
### 📝 Prerequisites
1. **Python 3.x**
* Please ensure Python 3 is installed on your system.
2. **FFmpeg**
* This project depends on FFmpeg for audio merging. Please visit the [FFmpeg official website](https://ffmpeg.org/download.html) to download and install.
* **Important Note**: After installation, please ensure the `ffmpeg` command has been added to your system's environment variables (PATH) so that the script can call it normally.
### 🐍 Python Dependencies
Open your terminal or command prompt and install the required Python libraries using pip:
```bash
pip install requests openai pydub msgpack
```
> **Dependency Explanation**:
> - `requests`: Used to send HTTP requests to TTS service APIs
> - `openai`: Used to interact with OpenAI API to generate podcast scripts
> - `pydub`: Used for audio processing, such as adjusting volume and speed
> - `msgpack`: Used for efficient data serialization with certain TTS services (such as Fish Audio)
---
## 🚀 Quick Start
### 1. Prepare Input Files
Before running, please ensure the following files are ready:
* `input.txt`: Enter your **podcast topic** or core idea in this file.
* `prompt/prompt-overview.txt`: System prompt used to guide AI in generating the podcast **overall outline**.
* `prompt/prompt-podscript.txt`: System prompt used to guide AI in generating **detailed dialogue scripts**. It contains dynamic placeholders (such as `{{numSpeakers}}`, `{{turnPattern}}`), which the script will automatically replace.
### 2. Configure TTS Services and Characters
* TTS configuration files (such as `edge-tts.json`) are stored in the `config/` directory. This file defines the TTS service API interface, podcast characters (`podUsers`) and their corresponding voices (`voices`).
### 3. Run the Script
Execute the following command in the project root directory:
```bash
python podcast_generator.py [optional parameters]
```
#### **Optional Parameters**
* `--api-key <YOUR_OPENAI_API_KEY>`: Your OpenAI API key. If not provided, it will be read from the configuration file or `OPENAI_API_KEY` environment variable.
* `--base-url <YOUR_OPENAI_BASE_URL>`: Proxy address of the OpenAI API. If not provided, it will be read from the configuration file or `OPENAI_BASE_URL` environment variable.
* `--model <OPENAI_MODEL_NAME>`: Specify the OpenAI model to use (such as `gpt-4o`, `gpt-4-turbo`). Default value is `gpt-3.5-turbo`.
* `--threads <NUMBER_OF_THREADS>`: Specify the number of parallel threads for audio generation (default is `1`) to improve processing speed.
* `--output-language <LANGUAGE_CODE>`: Specify the output language of the podcast script (default is `Chinese`).
* `--usetime <TIME_DURATION>`: Specify the time length of the podcast script (default is `10 minutes`).
#### **Running Example**
```bash
# Use gpt-4o model, edge-tts service and 4 threads to generate podcast
python podcast_generator.py --api-key sk-xxxxxx --model gpt-4o --tts-provider edge --threads 4
```
### 5. Using Web API (main.py)
This project also provides a FastAPI-based web service that allows you to generate podcasts through HTTP requests.
#### Start Web Service
```bash
python main.py
```
By default, the service will run on `http://localhost:8000`.
#### API Endpoints
1. **Generate Podcast** - `POST /generate-podcast`
- Parameters:
- `api_key`: OpenAI API key
- `base_url`: OpenAI API base URL (optional)
- `model`: OpenAI model name (optional)
- `input_txt_content`: Input text content
- `tts_providers_config_content`: TTS provider configuration content
- `podUsers_json_content`: Podcast user JSON configuration
- `threads`: Number of threads (optional, default is 1)
- `tts_provider`: TTS provider name (optional, default is "index-tts")
2. **Get Podcast Generation Status** - `GET /podcast-status`
- Requires `X-Auth-Id` header
3. **Download Podcast** - `GET /download-podcast/`
- Parameters:
- `file_name`: Name of the file to download
4. **Get Voice List** - `GET /get-voices`
- Parameters:
- `tts_provider`: TTS provider name (optional, default is "tts")
#### API Usage Example
```bash
# After starting the service, use curl to send a request to generate podcast
curl -X POST "http://localhost:8000/generate-podcast" \
-H "X-Auth-Id: your-auth-id" \
-F "api_key=sk-xxxxxx" \
-F "model=gpt-4o" \
-F "input_txt_content=The future development of artificial intelligence" \
-F "tts_providers_config_content={\"index\": {\"api_key\": \"your-api-key\"}}" \
-F "podUsers_json_content=[{\"code\":\"zh-CN-XiaoxiaoNeural\",\"role\":\"Host\"}],\"voices\":[{\"name\":\"Xiaoxiao\",\"code\":\"zh-CN-XiaoxiaoNeural\"}]" \
-F "threads=4" \
-F "tts_provider=index-tts"
```
### 4. Customizing AI Prompts (`custom` code block)
To provide more detailed AI instructions or add specific context, you can embed `custom` code blocks in the `input.txt` file. The content in this code block will be used as additional instructions, built into the core prompt for podcast script generation (`prompt-podscript.txt`), thereby influencing the AI's generation behavior.
**Usage**:
In the `input.txt` file, define your custom content anywhere using the following format:
```
```custom-begin
Additional instructions or context you want to provide to the AI, for example:
- "Please ensure the discussion includes an in-depth analysis of [specific concept]."
- "Please add some humor to the conversation, especially jokes about [a certain topic]."
- "All characters' speeches must be brief, with each sentence not exceeding two lines."
```custom-end
```
---
## 🌐 Web Application (Next.js)
In addition to the command-line script and FastAPI service, this project also provides a fully functional web user interface. This interface aims to provide a more intuitive and convenient podcast generation and management experience, exposing complex backend functions through friendly frontend operations to users.
### ✨ Core Features
* **Web Operation Interface**: Intuitive and friendly web interface that makes the podcast generation process clear at a glance.
* **Micro User System Integration**: Supports user login, registration, points and billing functions, building a complete user ecosystem.
* **Podcast Creation and Configuration**: Allows users to enter topics through forms and configure TTS characters, volume and speed parameters.
* **Real-time Progress Tracking**: Displays the status and progress of podcast generation.
* **Podcast Playback and Management**: Integrates an audio player for users to listen to generated podcasts and may provide functions for managing historical podcasts.
* **API Interaction**: Seamless communication with the backend Python service through APIs, including podcast generation, status queries, and audio streaming.
### 🚀 Quick Start (Web)
1. **Install Node.js**: Please ensure Node.js is installed on your system (LTS version recommended).
2. **Install Dependencies**: Enter the `web/` directory and install all frontend dependencies.
```bash
cd web/
npm install
# or yarn install
```
3. **Start Development Server**:
```bash
npm run dev
# or yarn dev
```
The web application will start at `http://localhost:3000` (default).
4. **Build Production Environment**:
```bash
npm run build
# or yarn build
npm run start
# or yarn start
```
### 🐳 Docker Deployment
This project supports deployment via Docker. For detailed information, please refer to [Docker Usage Guide](DOCKER_USAGE.md).
---
## 🌍 Internationalization (i18n) Support
This project supports multilingual interfaces, currently supporting English (en), Chinese (zh-CN), and Japanese (ja).
### 📁 Language File Structure
Language files are located in the `web/public/locales/` directory, grouped by language code:
- `web/public/locales/en/common.json` - English translation
- `web/public/locales/zh-CN/common.json` - Chinese translation
- `web/public/locales/ja/common.json` - Japanese translation
### 🛠️ Adding New Languages
1. Create a new language folder in the `web/public/locales/` directory, for example `fr/`
2. Copy the `common.json` file to the new folder
3. Translate all key-value pairs in the file
4. Update the `languages` variable in the `web/src/i18n/settings.ts` file
### 🌐 Language Switching
Users can automatically switch languages through the URL path or browser language settings:
- `http://localhost:3000/en/` - English interface
- `http://localhost:3000/zh-CN/` - Chinese interface
- `http://localhost:3000/ja/` - Japanese interface
---
## ⚙️ Configuration File Details
### `config/[tts-provider].json` (TTS Character and Voice Configuration)
This is your core TTS configuration file, with the filename corresponding to the provider specified by the `--tts-provider` parameter. It tells the script how to work with the TTS service.
```json
{
"podUsers": [
{
"code": "zh-CN-XiaoxiaoNeural",
"role": "Host"
},
{
"code": "zh-CN-YunxiNeural",
"role": "Tech Expert"
}
],
"voices": [
{
"name": "XiaoMin",
"code": "yue-CN-XiaoMinNeural",
"volume_adjustment": 1.0,
"speed_adjustment": 5.0
}
],
"apiUrl": "http://localhost:5000/api/tts?text={{text}}&voiceCode={{voiceCode}}",
"turnPattern": "random",
"tts_max_retries": 3
}
```
* `podUsers`: Defines the **characters** in the podcast. Each character's `code` must correspond to a valid voice in the `voices` list.
* `voices`: Defines all available TTS **voices**.
* `volume_adjustment` (optional): Volume adjustment (dB). For example, `6.0` increases volume by 6dB.
* `speed_adjustment` (optional): Speed adjustment (%). For example, `10.0` increases speed by 10%.
* `apiUrl`: Your TTS service API endpoint. `{{text}}` and `{{voiceCode}}` are placeholders.
* `turnPattern`: Defines the **turn-taking mode** for character dialogue, such as `random` (random) or `sequential` (sequential).
* `tts_max_retries` (optional): Maximum number of retries when TTS API calls fail (default is `3`).
### `config/tts_providers.json` (TTS Provider Authentication)
This file is used to centrally manage authentication information (such as API keys) for all TTS service providers.
```json
{
"index": { "api_key": null },
"edge": { "api_key": null },
"doubao": { "X-Api-App-Id": "null", "X-Api-Access-Key": "null" },
"fish": { "api_key": "null" },
"minimax": { "group_id": "null", "api_key": "null" },
"gemini": { "api_key": "null" }
}
```
**Note**: In actual use, please replace `"null"` with valid authentication information. You can create a `tts_providers-local.json` to store real keys, which has been ignored by `.gitignore`.
---
## 🔌 Supported TTS Services
This project is designed to be highly flexible and supports multiple TTS services.
| Provider | Type | Support Status |
| :--- | :--- | :---: |
| **Index-TTS** | Local | ✅ Supported |
| **Edge-TTS** | Local | ✅ Supported |
| **Doubao** | Network | ✅ Supported |
| **Minimax** | Network | ✅ Supported |
| **Fish Audio**| Network | ✅ Supported |
| **Gemini** | Network | ✅ Supported |
| **OpenAI TTS**| Network | Planned |
| **Azure TTS** | Network | Planned |
---
## 🎉 Output Results
All successfully generated podcast audio files will be automatically saved in the `output/` directory. The filename format is `podcast_` plus the timestamp when it was generated, for example `podcast_1678886400.wav`.
---
## 🎧 Sample Audio
You can find sample podcast audio generated using different TTS services in the `example/` folder.
| TTS Service | Listen Link |
| :--- | :--- |
| **Edge TTS** | [▶️ edgeTTS.wav](example/edgeTTS.wav) |
| **Index TTS** | [▶️ indexTTS.wav](example/indexTTS.wav) |
| **Doubao TTS** | [▶️ doubaoTTS.wav](example/doubaoTTS.wav) |
| **Minimax** | [▶️ minimax.wav](example/minimax.wav) |
| **Fish Audio**| [▶️ fish.wav](example/fish.wav) |
| **Gemini TTS**| [▶️ geminiTTS.wav](example/geminiTTS.wav) |
---
## 📂 File Structure
```
.
├── config/ # ⚙️ Configuration directory
│ ├── doubao-tts.json # ... (configuration for each TTS provider)
│ └── tts_providers.json # Unified TTS authentication file
├── server/ # 🐍 Backend service directory
│ ├── main.py # FastAPI Web API entry: Provides RESTful APIs for podcast generation, status query, audio download, manages task lifecycle, and performs data cleanup.
│ ├── podcast_generator.py # Core podcast generation logic: Responsible for interacting with OpenAI API to generate podcast scripts, calling TTS adapters to convert text to speech, and using FFmpeg to merge audio files.
│ ├── tts_adapters.py # TTS adapter: Encapsulates interaction logic with different TTS services (such as Index-TTS, Edge-TTS, Doubao, Minimax, Fish Audio, Gemini).
│ ├── openai_cli.py # OpenAI command-line tool
│ └── ... # Other backend files
├── web/ # 🌐 Frontend Web Application Directory (Next.js)
│ ├── public/ # Static resources
│ ├── src/ # Source code
│ │ ├── app/ # Next.js route pages
│ │ ├── components/ # React components
│ │ ├── hooks/ # React Hooks
│ │ ├── lib/ # Library files (authentication, database, API, etc.)
│ │ └── types/ # TypeScript type definitions
│ ├── package.json # Frontend dependencies
│ ├── next.config.js # Next.js configuration
│ └── ... # Other frontend files
├── prompt/ # 🧠 AI prompt directory
│ ├── prompt-overview.txt
│ └── prompt-podscript.txt
├── example/ # 🎧 Sample audio directory
├── output/ # 🎉 Output audio directory
├── input.txt # 🎙️ Podcast topic input file
├── README.md # 📄 Project documentation (Chinese)
└── README_EN.md # 📄 Project documentation (English)
```
---
## 📝 Disclaimer
* **License**: This project is licensed under [GPL-3.0](https://www.gnu.org/licenses/gpl-3.0.html).
* **No Warranty**: This software is provided "as is" without any express or implied warranties.
* **Liability Limitation**: Under no circumstances shall the authors or copyright holders be liable for any damages arising from the use of this software.
* **Third-Party Services**: Users bear the risks and responsibilities of using third-party services (such as OpenAI API, TTS services) on their own.
* **Usage Purpose**: This project is for learning and research purposes only. Please comply with all applicable laws and regulations.
* **Final Interpretation Rights**: We reserve the right to modify this disclaimer at any time.
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