effect-ai-provider

Configure and compose AI provider layers using @effect/ai packages.

68|13|Updated Aug 9, 2025

Search Tags:#integration #ai #configuration #provider #effect #language model

Ready to run

npx skills add https://github.com/kriegcloud/beep-effect --skill effect-ai-provider-kriegcloud

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: effect-ai-provider
Source: https://github.com/kriegcloud/beep-effect/tree/main/.repos/beep-effect/.claude/skills/effect-ai-provider
Command: npx skills add https://github.com/kriegcloud/beep-effect --skill effect-ai-provider-kriegcloud

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill simplifies the integration of various AI language model providers into Effect applications, abstracting away complex configurations and enabling seamless switching between services.

Core Features & Use Cases

Multi-Provider Support: Integrates with Anthropic, OpenAI, OpenRouter, Google, and Amazon Bedrock.
Configuration Management: Handles API keys and provider-specific settings securely using Effect's configuration system.
Model Abstraction: Provides a unified interface for different language models.
Stateful Conversations: Enables chat functionalities with context management.
Embedding Generation: Supports creating vector embeddings for semantic search.

Quick Start

Use the effect-ai-provider skill to configure the Anthropic AI provider with your API key.

Frequently Asked Questions about effect-ai-provider

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I configure AI provider layers in Effect applications?▼

Configure AI provider layers in Effect applications by using @effect/ai packages to manage API keys and provider-specific settings. This approach abstracts complex configurations and enables seamless switching between supported language model services.

Does the Effect AI integration support Anthropic and OpenAI providers?▼

Yes, the Effect AI integration supports Anthropic, OpenAI, OpenRouter, Google, and Amazon Bedrock providers. It provides a unified model abstraction interface and handles configuration management for each specific language model service.

How do I manage stateful chat conversations with language models in Effect?▼

Manage stateful chat conversations with language models in Effect by utilizing the provider layers to maintain context. This enables continuous chat functionalities alongside token management for efficient language model interaction.

Can I generate vector embeddings using @effect/ai packages?▼

Yes, you can generate vector embeddings using @effect/ai packages for semantic search. The configuration management system handles embedding generation alongside chat conversations and token management.

How do I securely handle API keys for language model integration in Effect?▼

Securely handle API keys for language model integration in Effect by leveraging the configuration management system. This allows runtime overrides and secure settings handling for supported providers like Anthropic and OpenAI.

What is the best way to switch between different language model providers in an Effect application?▼

The best way to switch between different language model providers in an Effect application is using model abstraction. This unified interface abstracts provider-specific settings, enabling seamless switching across Anthropic, OpenAI, and other supported services.