simple-one-api
S
Simple One Api
Overview :
simple-one-api is a program that adapts to various large model interfaces, supporting OpenAI interfaces, allowing users to call different large model services through a unified API format, simplifying the complexity brought by differences in different platform interfaces. It supports multiple platforms, including Qianfan Large Model Platform, Xfyun Xinghuo Large Model, and Tencent HunYuan Large Model, and provides the convenience of one-click deployment and out-of-the-box usability.
Target Users :
This product is aimed at developers and enterprise users who need to integrate large model API services. It is suitable for them because it provides a fast and easy way to integrate and call various large models, without having to worry about the differences in the underlying platforms, allowing them to focus more on the development of business logic.
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Use Cases
Developers use simple-one-api to quickly integrate Baidu Qianfan large model into their projects.
Enterprise users use this API adapter to call Xfyun Xinghuo and Tencent HunYuan large models at different times to perform AI-related business processing.
Educational institutions utilize the unified interface provided by simple-one-api to teach students how to use different AI large models.
Features
Supports multiple large models, including Baidu Smart Cloud Qianfan, Xfyun Xinghuo, Tencent HunYuan, etc.
Unified OpenAI interface format, simplifying the use of APIs from different platforms.
One-click deployment, fast service startup.
Simple configuration through the config.json file to configure model services and credentials.
Supports load balancing strategies, including 'first' and 'random' modes.
Provides detailed documentation and update logs to help users understand product updates and usage.
How to Use
Clone the simple-one-api repository to your local machine.
Modify the config.json file as needed to configure model service and credential information.
Execute the compilation script to generate the executable file.
Start the simple-one-api service and call the large model services through OpenAI-compatible interfaces.
Check service logs to ensure the service is running properly.
Adjust the load balancing strategy and model configuration as needed.
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