Where does the skill store provider configurations?

Configurations and API keys are managed through a centralized environment file typically located at /opt/cloodle/tools/ai/multi_agent_rag_system/.env.

Is this skill compatible with LangChain?

Yes, it includes implementation patterns specifically designed to integrate with LangChain classes such ChatOllama, ChatAnthropic, and HuggingFaceEndpoint.

How does this skill help with AI cost management?

It provides a framework to easily switch between premium providers like Anthropic and cost-effective alternatives like local Ollama instances or HuggingFace endpoints based on the specific use case.

Which providers does the AI Gateway skill support?

The skill currently supports Anthropic, Ollama (for local models), and HuggingFace (for open-source models), including specific configurations for models like Claude 3.5 Sonnet and Llama 3.2.

AI Gateway Manager

Name: AI Gateway Manager
Author: astoeffer

byastoeffer

数据科学与机器学习

Manages and routes requests across multiple AI providers including Anthropic, Ollama, and HuggingFace.

关于

The AI Gateway skill enables developers to implement robust, multi-provider AI routing logic within the Cloodle platform. It simplifies the process of switching between local models like Ollama, cloud-based services like Anthropic, and open-source models via HuggingFace by providing standardized configuration patterns and environment variable management. This skill is essential for building resilient AI applications that require automated fallbacks, model-specific optimizations, or cost-balancing strategies across different LLM vendors.

主要功能

0 GitHub stars
Pre-configured model recommendations for development and production
Multi-provider configuration support for Ollama, Anthropic, and HuggingFace
Built-in testing commands for verifying local provider connectivity
Dynamic provider switching logic for Python-based AI services
Standardized environment variable management for API keys and base URLs

使用场景

Managing complex LLM configurations for multi-agent RAG systems
Switching between local development with Ollama and production deployments with Anthropic
Implementing a resilient AI proxy that falls back to open-source models during outages

关于

主要功能

0 GitHub stars
Pre-configured model recommendations for development and production
Multi-provider configuration support for Ollama, Anthropic, and HuggingFace
Built-in testing commands for verifying local provider connectivity
Dynamic provider switching logic for Python-based AI services
Standardized environment variable management for API keys and base URLs

使用场景

Managing complex LLM configurations for multi-agent RAG systems
Switching between local development with Ollama and production deployments with Anthropic
Implementing a resilient AI proxy that falls back to open-source models during outages