统一的AI服务网关SDK,支持硅基流动、OpenAI等多种AI厂商
Project description
AI Service Gateway SDK
统一的 AI 服务网关 SDK,支持硅基流动、OpenAI 等多种 AI 厂商,一次接入,随处使用。
特性
- 🚀 简单易用 - 统一的客户端接口,几行代码即可接入
- 🔌 插件化架构 - 支持多种 AI 厂商,可轻松扩展
- 🛡️ 完善错误处理 - 清晰的异常体系,易于调试
- 📦 类型提示完整 - 完整的 Type Hints 支持 IDE 自动补全
- 🔄 自动重试 - 内置请求重试机制,提高稳定性
支持的 AI 厂商
| 厂商 | 文本生成 | 图像生成 | 语音识别 | 语音合成 |
|---|---|---|---|---|
| 硅基流动 | ✅ | ✅ | ✅ | ✅ |
| OpenAI | 🚧 | 🚧 | 🚧 | 🚧 |
安装
pip install aiservice-gateway-sdk
快速开始
文本生成
from aiservice_gateway_sdk import AIServiceGatewayClient
# 初始化客户端
client = AIServiceGatewayClient(
provider="silicon", # AI服务厂商
api_key="your-api-key" # 你的API Key
)
# 文本生成
result = client.text.generate(
prompt="你好,请介绍一下你自己",
model="Qwen/Qwen2.5-7B-Instruct",
max_tokens=1000,
temperature=0.7
)
print(result.text)
print(f"使用模型: {result.model}")
print(f"消耗Token: {result.usage.total_tokens}")
图像生成
# 图像生成
result = client.image.generate(
prompt="一只可爱的橘猫在阳光下打盹",
model="dall-e-3",
size="1024x1024",
n=1
)
for img in result.image_urls:
print(f"图像URL: {img.url}")
语音识别
# 读取音频文件
with open("audio.wav", "rb") as f:
audio_data = f.read()
# 语音识别
result = client.audio.recognize(
audio=audio_data,
model="whisper-1",
language="zh"
)
print(f"识别结果: {result.text}")
语音合成
# 语音合成
result = client.audio.synthesize(
text="你好,欢迎使用AI服务网关SDK",
model="tts-1",
voice="alloy"
)
# 保存音频文件
with open("output.mp3", "wb") as f:
f.write(result.audio)
配置选项
| 参数 | 类型 | 默认值 | 说明 |
|---|---|---|---|
| provider | str | "silicon" | AI 服务厂商 |
| api_key | str | None | API 密钥 |
| base_url | str | None | 自定义 API 地址 |
| timeout | int | 30 | 请求超时时间(秒) |
| max_retries | int | 3 | 最大重试次数 |
错误处理
from aiservice_gateway_sdk import (
AIServiceGatewayClient,
AuthenticationError,
RateLimitError,
APIError,
)
client = AIServiceGatewayClient(
provider="silicon",
api_key="your-api-key"
)
try:
result = client.text.generate("你好")
except AuthenticationError:
print("认证失败,请检查API Key")
except RateLimitError:
print("请求频率超限,请稍后重试")
except APIError as e:
print(f"API错误: {e.message}")
支持的模型
硅基流动
文本生成模型:
Qwen/Qwen2.5-7B-InstructQwen/Qwen2.5-14B-InstructQwen/Qwen2.5-72B-Instructdeepseek-ai/DeepSeek-V2.5THUDM/GLM-4-9B-Chat
图像生成模型:
dall-e-3
语音识别模型:
whisper-1
语音合成模型:
tts-1
从源码安装
git clone https://github.com/your-repo/aiservice-gateway-sdk.git
cd aiservice-gateway-sdk
pip install -e .
开发
# 克隆项目
git clone https://github.com/your-repo/aiservice-gateway-sdk.git
# 创建虚拟环境
python -m venv venv
source venv/bin/activate # Linux/Mac
# 或
.\venv\Scripts\activate # Windows
# 安装开发依赖
pip install -e ".[dev]"
# 运行测试
pytest tests/
# 代码格式化
black src/
isort src/
发布到 PyPI
# 构建包
python -m build
# 上传到 PyPI
twine upload dist/*
License
MIT License - 详见 LICENSE 文件
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