shaoyingchen_mcp_client_llm.git
by shaoyingchenEnables large language models to access any API type and demonstrates local application integration.
Local Application Integration for Large Language Models
Overview
This project provides a simple example of how to use the OpenAI API to create a local application that can access any API type. It supports large models and demonstrates how to open a local application seamlessly.
Tools
- Python: The project is entirely written in Python.
- OpenAI API: Used to interact with large language models.
- uv sync: A library required for installation.
Configuration
- Install Necessary Libraries:
bash uv sync - Modify
.envFile:
Add your OpenAI API key, endpoint, and model details.
env OPENAI_API_KEY=your_api_key OPENAI_ENDPOINT=your_endpoint OPENAI_MODEL=your_model - Modify
servers_config.json:
Configure your server settings in theservers_config.jsonfile.
Usage
- Set Up Environment: Ensure all configurations are correctly set up as described in the Configuration section.
- Run the Application: Execute the Python script to start the local application.
bash python src/main.py
Resources
Repository Details
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- Python: 100.0%
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Features & Capabilities
Categories
mcp_server
model_context_protocol
python
api_integration
openai
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Repository Info
shaoyingchen
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