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A library that wraps multiple LLM providers into a consistent API while using each provider's native SDK internally, supporting multimodal I/O, file processing, and stream output.

Project description

LLM Bridge

LLM Bridge is a Python library that wraps multiple LLM providers into a consistent API while using each provider's native SDK internally, supporting multimodal I/O, file processing, and stream output.

GitHub: https://github.com/windsnow1025/LLM-Bridge

PyPI: https://pypi.org/project/LLM-Bridge/

Workflow and Features

  1. Chat Client Factory: creates a client for the specific LLM API with model parameters
    1. Model Message Converter: converts general messages to model messages
      1. Media Processor: converts general media to model compatible formats.
  2. Chat Client: generate stream or non-stream responses

Supported Features for API Types

The features listed represent the maximum capabilities of each API type supported by LLM Bridge.

API Type Input Format Capabilities Output Format
OpenAI Completion API Text, Image, PDF Thinking, Structured Output Text
OpenAI Responses API Text, Image, PDF Thinking, Web Search, Code Execution, Structured Output Text, Image
Google GenAI Text, Image, PDF, Audio, Video Thinking, Web Search, Code Execution, Structured Output Text, Image, File
Anthropic Text, Image, PDF Thinking, Web Search, Code Execution, Structured Output Text, File
xAI Text, Image, PDF, Audio, Video, docx, xlsx, pptx Thinking, Web Search, Code Execution, Structured Output Text

Development

Python uv

  1. Install uv: powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
  2. Install Python in uv: uv python install 3.12; upgrade Python in uv: uv python upgrade 3.12
  3. Configure requirements:
uv sync --refresh

PyCharm

Add New Interpreter >> Add Local Interpreter

  • Environment: Select existing
  • Type: uv

Usage

Copy ./usage/.env.example and rename it to ./usage/.env, then fill in the environment variables.

Build

uv build

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