octopus

🥈Silver

Octopus is an LLM API aggregation and load balancing service that enables developers to access multiple AI models through a single interface. It supports Claude, OpenAI, and other LLMs, simplifying integration for applications requiring diverse AI capabilities.

1,9761450Updated Yesterday

Intermediate30min to implementautomation

Saves ~20 min per use

Quick InstallView Source

git clone https://github.com/bestruirui/octopus.git

Works with:

Claude

Overview

About This Skill

The Octopus skill is designed to simplify the management of multiple Large Language Model (LLM) APIs by providing a unified interface. This automation tool allows users to aggregate various LLM services, enabling developers and AI practitioners to manage requests and responses efficiently. With Octopus, you can seamlessly convert requests and responses between different API formats, ensuring that your workflow remains uninterrupted and productive. One of the key benefits of using Octopus is the optimization of response times through automatic balancing of requests across different AI models. This functionality not only enhances performance but also helps in synchronizing model pricing and availability from various LLM providers. While the exact time savings are currently unknown, the streamlined management and reduced complexity of handling multiple APIs can significantly enhance productivity for teams focused on AI automation and workflow automation. Octopus is particularly beneficial for developers, product managers, and AI practitioners who are looking to integrate multiple LLMs into their projects. By leveraging this skill, teams can reduce the friction of managing disparate APIs, allowing them to focus on building innovative solutions rather than getting bogged down by technical complexities. Use cases include aggregating APIs for chatbot development, enhancing natural language processing applications, or even creating a centralized dashboard for monitoring API usage and costs. With an intermediate implementation difficulty and an estimated time of 30 minutes to set up, Octopus is accessible for those with a foundational understanding of API management. It fits seamlessly into AI-first workflows by providing a robust solution for managing multiple AI agent skills, ultimately leading to more efficient and effective automation processes. Explore how Octopus can enhance your AI projects and streamline your workflow on Shyft.ai.

How to Use

["Sign up for an Octopus account and obtain your API key.","Install the Octopus SDK in your development environment.","Initialize the Octopus client in your code using your API key.","Define API calls to the specific models you need, such as Claude and OpenAI.","Handle the responses from both models and integrate them into your application logic.","Use Octopus's load balancing features to distribute requests efficiently and monitor performance metrics to ensure cost efficiency."]

Use Cases

Aggregate multiple LLM APIs into a single interface for easier management.

Automatically balance requests across different AI models to optimize response times.

Synchronize model pricing and availability from various LLM providers.

Convert requests and responses between different API formats seamlessly.

Setup & Installation

Quick Install

No install command available. Check the GitHub repository for manual installation instructions.

Alternative Install (Git Clone)

git clone https://github.com/bestruirui/octopus

Requirements

Claude Code or compatible AI agent
Works with: Claude

Quick Start Guide

Install the Skill

Copy the install command above and run it in your terminal.

Open Your AI Agent

Launch Claude Code, Cursor, or your preferred AI coding agent.

Try It Out

Use the prompt template or examples below to test the skill.

Customize

Adapt the skill to your specific use case and workflow.

Usage Examples

Prompt Template

I want to use Octopus to build an application that needs to access both Claude and OpenAI models. [DESCRIBE APPLICATION]. I need to know the best way to set up the API calls through Octopus to ensure optimal performance and cost efficiency. Provide a step-by-step guide, including any necessary code snippets.

Example Output

To build your application using Octopus to access both Claude and OpenAI models, follow these steps:

1. **Set Up Octopus Account**: Sign up for an Octopus account and obtain your API key. This key will be used to authenticate your API requests.

2. **Install Octopus SDK**: Install the Octopus SDK in your development environment. For Python, you can use pip:
   ```bash
   pip install octopus-sdk
   ```

3. **Initialize Octopus Client**: Initialize the Octopus client in your code using your API key:
   ```python
   from octopus import Octopus
   octopus = Octopus(api_key='your_api_key_here')
   ```

4. **Define API Calls**: Define the API calls to the specific models you need. For example, to call Claude and OpenAI:
   ```python
   response_claude = octopus.call_model(model='claude', prompt='Your prompt here')
   response_openai = octopus.call_model(model='openai', prompt='Your prompt here')
   ```

5. **Handle Responses**: Process the responses from both models and integrate them into your application logic.

6. **Optimize Performance**: Use Octopus's load balancing features to distribute requests efficiently. Monitor performance metrics to ensure cost efficiency.

By following these steps, you can seamlessly integrate multiple AI models into your application using Octopus.