mirror of
https://github.com/snailyp/gemini-balance.git
synced 2026-09-06 08:06:37 +08:00
feat: 添加TTS相关配置和功能
- 在.env.example中添加TTS模型、语音名称和语速的配置选项 - 更新README文件，增加TTS相关配置的说明 - 在配置类中添加TTS相关设置 - 新增TTS请求模型以支持文本转语音功能 - 更新智能路由中间件以支持音频请求 - 在路由中添加处理TTS请求的API接口 - 更新前端配置编辑器以支持TTS配置选项
This commit is contained in:
snaily
@@ -11,7 +11,7 @@
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[](https://www.uvicorn.org/)
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[](https://t.me/+soaHax5lyI0wZDVl)
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> Telegram Group: https://t.me/+soaHax5lyI0wZDVl
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> Telegram Group: <https://t.me/+soaHax5lyI0wZDVl>
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## Project Introduction
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@@ -40,39 +40,39 @@ app/
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## ✨ Feature Highlights
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* **Multi-Key Load Balancing**: Supports configuring multiple Gemini API Keys (`API_KEYS`) for automatic sequential polling, improving availability and concurrency.
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* **Visual Configuration Takes Effect Immediately**: Configurations modified through the admin backend take effect without restarting the service. Remember to click save for changes to apply.
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* **Multi-Key Load Balancing**: Supports configuring multiple Gemini API Keys (`API_KEYS`) for automatic sequential polling, improving availability and concurrency.
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* **Visual Configuration Takes Effect Immediately**: Configurations modified through the admin backend take effect without restarting the service. Remember to click save for changes to apply.
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* **Dual Protocol API Compatibility**: Supports forwarding CHAT API requests in both Gemini and OpenAI formats.
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* **Dual Protocol API Compatibility**: Supports forwarding CHAT API requests in both Gemini and OpenAI formats.
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```plaintext
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openai baseurl `http://localhost:8000(/hf)/v1`
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gemini baseurl `http://localhost:8000(/gemini)/v1beta`
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```
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* **Supports Image-Text Chat and Image Modification**: `IMAGE_MODELS` configures which models can perform image-text chat and image editing. When actually calling, use the `configured_model-image` model name to use this feature.
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* **Supports Image-Text Chat and Image Modification**: `IMAGE_MODELS` configures which models can perform image-text chat and image editing. When actually calling, use the `configured_model-image` model name to use this feature.
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* **Supports Web Search**: Supports web search. `SEARCH_MODELS` configures which models can perform web searches. When actually calling, use the `configured_model-search` model name to use this feature.
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* **Supports Web Search**: Supports web search. `SEARCH_MODELS` configures which models can perform web searches. When actually calling, use the `configured_model-search` model name to use this feature.
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* **Key Status Monitoring**: Provides a `/keys_status` page (requires authentication) to view the status and usage of each Key in real-time.
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* **Key Status Monitoring**: Provides a `/keys_status` page (requires authentication) to view the status and usage of each Key in real-time.
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* **Detailed Logging**: Provides detailed error logs for easy troubleshooting.
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* **Detailed Logging**: Provides detailed error logs for easy troubleshooting.
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* **Support for Custom Gemini Proxy**: Supports custom Gemini proxies, such as those built on Deno or Cloudflare.
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* **OpenAI Image Generation API Compatibility**: Adapts the `imagen-3.0-generate-002` model interface to be compatible with the OpenAI image generation API, supporting client calls.
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* **Flexible Key Addition**: Flexible way to add keys using regex matching for `gemini_key`, with key deduplication.
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* **Support for Custom Gemini Proxy**: Supports custom Gemini proxies, such as those built on Deno or Cloudflare.
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* **OpenAI Image Generation API Compatibility**: Adapts the `imagen-3.0-generate-002` model interface to be compatible with the OpenAI image generation API, supporting client calls.
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* **Flexible Key Addition**: Flexible way to add keys using regex matching for `gemini_key`, with key deduplication.
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* **OpenAI Format Embeddings API Compatibility**: Perfectly adapts to the OpenAI format `embeddings` interface, usable for local document vectorization.
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* **Streamlined Response Optimization**: Optional stream output optimizer (`STREAM_OPTIMIZER_ENABLED`) to improve the experience of long-text stream responses.
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* **Failure Retry and Key Management**: Automatically handles API request failures, retries (`MAX_RETRIES`), automatically disables Keys after too many failures (`MAX_FAILURES`), and periodically checks for recovery (`CHECK_INTERVAL_HOURS`).
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* **Docker Support**: Supports AMD and ARM architecture Docker deployments. You can also build your own Docker image.
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* **OpenAI Format Embeddings API Compatibility**: Perfectly adapts to the OpenAI format `embeddings` interface, usable for local document vectorization.
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* **Streamlined Response Optimization**: Optional stream output optimizer (`STREAM_OPTIMIZER_ENABLED`) to improve the experience of long-text stream responses.
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* **Failure Retry and Key Management**: Automatically handles API request failures, retries (`MAX_RETRIES`), automatically disables Keys after too many failures (`MAX_FAILURES`), and periodically checks for recovery (`CHECK_INTERVAL_HOURS`).
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* **Docker Support**: Supports AMD and ARM architecture Docker deployments. You can also build your own Docker image.
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> Image address: docker pull ghcr.io/snailyp/gemini-balance:latest
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* **Automatic Model List Maintenance**: Supports fetching OpenAI and Gemini model lists, perfectly compatible with NewAPI's automatic model list fetching, no manual entry required.
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* **Support for Removing Unused Models**: Too many default models are provided, many of which are not used. You can filter them out using `FILTERED_MODELS`.
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* **Proxy Support**: Supports configuring HTTP/SOCKS5 proxy servers (`PROXIES`) for accessing the Gemini API, convenient for use in special network environments. Supports batch adding proxies.
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* **Automatic Model List Maintenance**: Supports fetching OpenAI and Gemini model lists, perfectly compatible with NewAPI's automatic model list fetching, no manual entry required.
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* **Support for Removing Unused Models**: Too many default models are provided, many of which are not used. You can filter them out using `FILTERED_MODELS`.
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* **Proxy Support**: Supports configuring HTTP/SOCKS5 proxy servers (`PROXIES`) for accessing the Gemini API, convenient for use in special network environments. Supports batch adding proxies.
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## 🚀 Quick Start
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#### a) Build with Dockerfile
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1. **Build Image**:
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1. **Build Image**:
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```bash
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docker build -t gemini-balance .
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```
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2. **Run Container**:
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2. **Run Container**:
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```bash
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docker run -d -p 8000:8000 --env-file .env gemini-balance
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```
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* `-d`: Run in detached mode.
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* `-p 8000:8000`: Map port 8000 of the container to port 8000 of the host.
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* `--env-file .env`: Use the `.env` file to set environment variables.
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* `-d`: Run in detached mode.
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* `-p 8000:8000`: Map port 8000 of the container to port 8000 of the host.
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* `--env-file .env`: Use the `.env` file to set environment variables.
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> Note: If using an SQLite database, you need to mount a data volume to persist
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> Note: If using an SQLite database, you need to mount a data volume to persist
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>
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> ```bash
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> docker run -d -p 8000:8000 --env-file .env -v /path/to/data:/app/data gemini-balance
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> ```
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>
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> Where `/path/to/data` is the data storage path on the host, and `/app/data` is the data directory inside the container.
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#### b) Deploy with an Existing Docker Image
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1. **Pull Image**:
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1. **Pull Image**:
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```bash
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docker pull ghcr.io/snailyp/gemini-balance:latest
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```
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2. **Run Container**:
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2. **Run Container**:
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```bash
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docker run -d -p 8000:8000 --env-file .env ghcr.io/snailyp/gemini-balance:latest
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```
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* `-d`: Run in detached mode.
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* `-p 8000:8000`: Map port 8000 of the container to port 8000 of the host (adjust as needed).
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* `--env-file .env`: Use the `.env` file to set environment variables (ensure the `.env` file exists in the directory where the command is executed).
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* `-d`: Run in detached mode.
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* `-p 8000:8000`: Map port 8000 of the container to port 8000 of the host (adjust as needed).
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* `--env-file .env`: Use the `.env` file to set environment variables (ensure the `.env` file exists in the directory where the command is executed).
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> Note: If using an SQLite database, you need to mount a data volume to persist
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> Note: If using an SQLite database, you need to mount a data volume to persist
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>
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> ```bash
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> docker run -d -p 8000:8000 --env-file .env -v /path/to/data:/app/data ghcr.io/snailyp/gemini-balance:latest
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> ```
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>
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> Where `/path/to/data` is the data storage path on the host, and `/app/data` is the data directory inside the container.
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### Run Locally (Suitable for Development and Testing)
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If you want to run the source code directly locally for development or testing, follow these steps:
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1. **Ensure Prerequisites are Met**:
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* Clone the repository locally.
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* Install Python 3.9 or higher.
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* Create and configure the `.env` file in the project root directory (refer to the "Configure Environment Variables" section above).
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* Install project dependencies:
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1. **Ensure Prerequisites are Met**:
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* Clone the repository locally.
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* Install Python 3.9 or higher.
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* Create and configure the `.env` file in the project root directory (refer to the "Configure Environment Variables" section above).
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* Install project dependencies:
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```bash
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pip install -r requirements.txt
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```
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2. **Start Application**:
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2. **Start Application**:
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Run the following command in the project root directory:
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```bash
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uvicorn app.main:app --host 0.0.0.0 --port 8000 --reload
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```
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* `app.main:app`: Specifies the location of the FastAPI application instance (the `app` object in the `main.py` file within the `app` module).
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* `--host 0.0.0.0`: Makes the application accessible from any IP address on the local network.
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* `--port 8000`: Specifies the port number the application listens on (you can change this as needed).
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* `--reload`: Enables automatic reloading. When you modify the code, the service will automatically restart, which is very suitable for development environments (remove this option in production environments).
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* `app.main:app`: Specifies the location of the FastAPI application instance (the `app` object in the `main.py` file within the `app` module).
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* `--host 0.0.0.0`: Makes the application accessible from any IP address on the local network.
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* `--port 8000`: Specifies the port number the application listens on (you can change this as needed).
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* `--reload`: Enables automatic reloading. When you modify the code, the service will automatically restart, which is very suitable for development environments (remove this option in production environments).
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3. **Access Application**:
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3. **Access Application**:
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After the application starts, you can access `http://localhost:8000` (or the host and port you specified) through a browser or API tool.
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### Complete Configuration List
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@@ -181,6 +185,7 @@ If you want to run the source code directly locally for development or testing,
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| `SHOW_THINKING_PROCESS` | Optional, whether to display the model's thinking process | `true` |
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| `THINKING_MODELS` | Optional, list of models that support thinking functions | `[]` |
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| `THINKING_BUDGET_MAP` | Optional, thinking function budget mapping (model_name:budget_value) | `{}` |
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| `URL_NORMALIZATION_ENABLED` | Optional, whether to enable intelligent URL routing mapping | `false` |
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| `BASE_URL` | Optional, Gemini API base URL, no modification needed by default | `https://generativelanguage.googleapis.com/v1beta` |
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| `MAX_FAILURES` | Optional, number of times a single key is allowed to fail | `3` |
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| `MAX_RETRIES` | Optional, maximum number of retries for failed API requests | `3` |
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| `AUTO_DELETE_REQUEST_LOGS_ENABLED`| Optional, whether to enable automatic deletion of request logs | `false` |
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| `AUTO_DELETE_REQUEST_LOGS_DAYS` | Optional, automatically delete request logs older than this many days (e.g., 1, 7, 30) | `30` |
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| `SAFETY_SETTINGS` | Optional, safety settings (JSON string format), used to configure content safety thresholds. Example values may need adjustment based on actual model support. | `[{"category": "HARM_CATEGORY_HARASSMENT", "threshold": "OFF"}, {"category": "HARM_CATEGORY_HATE_SPEECH", "threshold": "OFF"}, {"category": "HARM_CATEGORY_SEXUALLY_EXPLICIT", "threshold": "OFF"}, {"category": "HARM_CATEGORY_DANGEROUS_CONTENT", "threshold": "OFF"}, {"category": "HARM_CATEGORY_CIVIC_INTEGRITY", "threshold": "BLOCK_NONE"}]` |
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| **TTS Related** | | |
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| `TTS_MODEL` | Optional, TTS model name | `gemini-2.5-flash-preview-tts` |
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| `TTS_VOICE_NAME` | Optional, TTS voice name | `Zephyr` |
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| `TTS_SPEED` | Optional, TTS speed | `normal` |
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| **Image Generation Related** | | |
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| `PAID_KEY` | Optional, paid API Key for advanced features like image generation | `your-paid-api-key` |
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| `CREATE_IMAGE_MODEL` | Optional, image generation model | `imagen-3.0-generate-002` |
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### Gemini API Related (`(/gemini)/v1beta`)
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* `GET /models`: List available Gemini models.
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* `POST /models/{model_name}:generateContent`: Generate content using the specified Gemini model.
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* `POST /models/{model_name}:streamGenerateContent`: Stream content generation using the specified Gemini model.
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* `GET /models`: List available Gemini models.
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* `POST /models/{model_name}:generateContent`: Generate content using the specified Gemini model.
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* `POST /models/{model_name}:streamGenerateContent`: Stream content generation using the specified Gemini model.
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### OpenAI API Related
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* `GET (/hf)/v1/models`: List available models (uses Gemini format underneath).
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* `POST (/hf)/v1/chat/completions`: Perform chat completion (uses Gemini format underneath, supports streaming).
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* `POST (/hf)/v1/embeddings`: Create text embeddings (uses Gemini format underneath).
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* `POST (/hf)/v1/images/generations`: Generate images (uses Gemini format underneath).
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* `GET /openai/v1/models`: List available models (uses OpenAI format underneath).
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* `POST /openai/v1/chat/completions`: Perform chat completion (uses OpenAI format underneath, supports streaming, can prevent truncation, and is faster).
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* `POST /openai/v1/embeddings`: Create text embeddings (uses OpenAI format underneath).
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* `POST /openai/v1/images/generations`: Generate images (uses OpenAI format underneath).
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* `GET (/hf)/v1/models`: List available models (uses Gemini format underneath).
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* `POST (/hf)/v1/chat/completions`: Perform chat completion (uses Gemini format underneath, supports streaming).
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* `POST (/hf)/v1/embeddings`: Create text embeddings (uses Gemini format underneath).
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* `POST (/hf)/v1/images/generations`: Generate images (uses Gemini format underneath).
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* `GET /openai/v1/models`: List available models (uses OpenAI format underneath).
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* `POST /openai/v1/chat/completions`: Perform chat completion (uses OpenAI format underneath, supports streaming, can prevent truncation, and is faster).
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* `POST /openai/v1/embeddings`: Create text embeddings (uses OpenAI format underneath).
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* `POST /openai/v1/images/generations`: Generate images (uses OpenAI format underneath).
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## 🤝 Contributing
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@@ -242,9 +251,9 @@ Pull Requests or Issues are welcome.
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Special thanks to the following projects and platforms for providing image hosting services for this project:
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* [PicGo](https://www.picgo.net/)
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* [SM.MS](https://smms.app/)
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* [CloudFlare-ImgBed](https://github.com/MarSeventh/CloudFlare-ImgBed) open source project
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* [PicGo](https://www.picgo.net/)
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* [SM.MS](https://smms.app/)
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* [CloudFlare-ImgBed](https://github.com/MarSeventh/CloudFlare-ImgBed) open source project
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## 🙏 Thanks to Contributors
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@@ -266,7 +275,7 @@ CDN acceleration and security protection for this project are sponsored by Tence
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## 💖 Friendly Projects
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* **[OneLine](https://github.com/chengtx809/OneLine)** by [chengtx809](https://github.com/chengtx809) - OneLine: AI-driven hot event timeline generation tool
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* **[OneLine](https://github.com/chengtx809/OneLine)** by [chengtx809](https://github.com/chengtx809) - OneLine: AI-driven hot event timeline generation tool
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## 🎁 Project Support
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