Pieces OS: Reverse Pieces-OS GRPC Conversion to OpenAI Interface (Failed)

General Introduction

Pieces-OS is an open source project that aims to reverse and convert the GRPC streams of Pieces-OS into a standard OpenAI API interface. The project is developed by Nekohy and is open source under GPL-3.0 for learning and communication, not for commercial use. The project provides a variety of model compatibility and support for Vercel one-click deployment.

reverse direction pieces , one minute free deployment of API interfaces supporting Claude, GPT, Gemini models. Providego versionThe

Function List

• GRPC flow reversal: Converts GRPC streams from Pieces-OS to the standard OpenAI interface.
• Multi-model support: Compatible Claude series, GPT series, Gemini series and many other models.
• One-Click Deployment: Support One-click deployment of the Vercel platform, easy for users to build quickly.
• Cloud Model Configuration: Provide profiles of cloud models so that users can extract and use different models as needed.
• API Request Management: Manage prefix paths, keys, retries, etc. for API requests by configuring environment variables.

Using Help

Installation process

1. cloning project: Use git clone command to clone the project locally.

   git clone https://github.com/Nekohy/pieces-os.git
   

2. Installation of dependencies: Go to the project directory and install package.json Dependency libraries defined in the

   cd pieces-os
   npm install
   

3. triggering program: Implementation node index.js Start the program.

   node index.js
   

Usage Process

1. Getting a list of models: Get the list of available models with the following command.

   curl --request GET 'http://127.0.0.1:8787/v1/models' --header 'Content-Type: application/json'

2. Send Request: Use the following command to send a chat request.

   curl --request POST 'http://127.0.0.1:8787/v1/chat/completions' --header 'Content-Type: application/json' --data '{
   "messages": [
   {
   "role": "user",
   "content": "你好！"
   }
   ],
   "model": "gpt-4o",
   "stream": true
   }'

Environment variable configuration

• API_PREFIX: Prefix path for API requests, default value is '/'The
• API_KEY: The key for the API request, defaults to an empty string.
• MAX_RETRY_COUNT: Maximum number of retries, defaults to 3The
• RETRY_DELAY: retry delay time in milliseconds, default value is 5000(5 seconds).
• PORT: The port on which the service listens, the default value is 8787The

Model Configuration

The project provides profiles for multiple models cloud_model.json, users can extract and use different models as needed. For example:

• Claude Series::claude-3-5-sonnet@20240620,claude-3-haiku@20240307 etc.
• GPT Series::gpt-3.5-turbo,gpt-4,gpt-4-turbo etc.
• Gemini Series::gemini-1.5-flash,gemini-1.5-pro etc.

How to use it after deployment

Configuration in nextchat:

Fill in the domain name directly, do not add after the URL/v1/models , /v1/chat/completions

API_KEY is not configured in Vercel, then no input is required.

Configuration in immersive translation: (not recommended due to concurrency issues)

https://你的域名/v1/chat/completions

If apikey is not set, fill in the blanks.