An Introduction to Simple-One-API
Overview
Simple-One-API is designed to address the increasing number of free domestic large language models available in the market. The project aims to simplify the process of integrating and using these models by providing a standardized OpenAI API. Despite claims from some vendors about OpenAI interface compatibility, there often remain slight inconsistencies, and this project aims to bridge those gaps and streamline the user experience.
Key Features
Simple-One-API enables seamless access to multiple language models, while presenting a unified OpenAI interface to ease integration for users. Its principal features include:
- Compatibility with various OpenAI interfaces, offering a consistent and unified API experience across different platforms.
- A wide variety of supported models, such as Baidu's Ernie, iFlyTek's Spark, Tencent's Hunyuan, Cloudflare Workers AI, and many more.
- Support for several language models compatible with OpenAI models like OpenAI's own ChatGPT series, Google's Gemini, Llama Family, and so on.
Supported Free Language Models
Simple-One-API provides access to a variety of free language models without the complications of tracking usage statistics, traffic, or billing. Here's a list of some notable free models:
- iFlyTek's Spark Model: Unlimited token usage, with a limit of 2 queries per second (QPS).
- Baidu's Qianfan Platform: Offers several models with varied limits, like RPM and TPM constraints.
- Tencent's Hunyuan Model: Up to 5 concurrent uses.
- Cloudflare Workers AI: Free usage allows up to 10,000 uses per day.
Each of these has its documentation and access points, provided through links to their respective official pages.
Installation and Setup
Users can opt to install Simple-One-API via cloning from its GitHub repository or by downloading it directly from the releases page:
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Clone via Git:
git clone https://github.com/fruitbars/simple-one-api.git -
For a straightforward compilation, ensure Go is installed (version 1.21 or above). Then execute platform-specific build scripts.
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Docker deployment and execution are supported, requiring minimal configuration changes for launching the service.
Once installed, system configuration is possible through a config.json file, allowing for setup of models, services, and API keys for access.
Configurations
Simple-One-API allows for extensive customization through its configuration file, which supports:
- Load balancing between models, enabling random selection for optimal performance.
- Defining custom server URLs and API limits for different models.
- Configurability for handling API keys for different models and services.
The setup can accommodate multiple entries for models and services, making it suitable for diverse operational requirements, as shown in their detailed configuration documentation.
Application and Use
Simple-One-API is engineered to be easy to use, compatible with existing OpenAI messaging protocols. It supports configurations whereby a model can be dynamically chosen or fallback supported through aliases and system-wide settings for redirecting tasks.
Additionally, it allows for integration within applications such as ChatX, Lobe Chat, and others via the v1 interface and global proxy support. These applications have confirmed compatibility and serve as validated clients for using the API to access large language models.
Support and Community
The project benefits from a supportive community, encouraging feedback for improvements and offering an open channel for communication and updates. Regular updates and changes are logged through a dedicated changelog for user awareness.
By leveraging Simple-One-API, developers and users alike can radically reduce the complexity and diversification complications presented by an ever-growing pool of language models, all while maintaining seamless interoperability through a widely recognized API standard.