openrouter-manager 0.0.1

Wrapper library for using **DeepSeek** with **openrouter.ai**

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openrouter-manager

openrouter-manager is a wrapper library for using DeepSeek with openrouter.ai, facilitating integration with language models through a simple and efficient API.

Main Features

• Wrapper for DeepSeek using openrouter.ai.

• Easy-to-use singleton class AiAgent.

• Allows defining dynamic prompts with variables.

• Configuration via environment variables.

Installation

It is recommended to install openrouter-manager in a virtual environment to avoid dependency conflicts:

pip install openrouter-manager

Requirements

To use this library, the following environment variables must be set:

• AIAGENT_API_KEY: API Key for openrouter.ai.

• AIAGENT_PROMPT_FILE: Path to the text file containing the prompt to send to the LLM.

Example configuration in a .env file:

AIAGENT_API_KEY="your_api_key_here"
AIAGENT_PROMPT_FILE="path/to/prompt_file.txt"

Usage

To use openrouter-manager, first instantiate AiAgent and then call the resolve method, providing the necessary variables to populate the prompt:

from openrouter_manager import AiAgent

# Get the singleton instance of the agent
agent = AiAgent()

# Resolve the prompt with dynamic variables
response = agent.resolve({"name": "John", "age": 30})

print(response)  # Response generated by the LLM

Contributing

If you would like to contribute to this project, you can clone the repository and make modifications:

git clone https://github.com/your_username/openrouter-manager.git
cd openrouter-manager

Contributions are welcome. Make sure to follow best coding practices and document your changes.

License

This project is open-source, owned by Koral Advanced Technology, and developed by Lenin David Lozano. It is freely available for use and modification under the MIT License. See the LICENSE file for more details. .. pyscaffold-notes:

Note

This project has been set up using PyScaffold 4.6. For details and usage information on PyScaffold see https://pyscaffold.org/.