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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. Message Preprocessor: extracts text content from documents (Word, Excel, PPT, Code files, PDFs) which are not natively supported by the target model.
  2. 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 (Image, Audio, Video, PDF) to model compatible formats.
  3. Chat Client: generate stream or non-stream responses
    • Model Thoughts: captures the model's thinking process
    • Code Execution: generates and executes Python code
    • Web Search: generates response from search results
    • Token Counter: tracks and reports input and output token usage

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 Text, Image, PDF Thinking, Web Search, Code Execution, Structured Output Text, Image
Gemini Text, Image, Video, Audio, PDF Thinking, Web Search, Code Execution, Structured Output Text, Image, File
Claude Text, Image, PDF Thinking, Web Search, Code Execution, Structured Output Text, File
Grok Text, Image Text

Planned Features

  • More features for API Types
  • Native support for Grok

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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