ai-engineer-expert

What problem does it solve?

This Skill provides expert guidance and code examples for implementing, integrating, and deploying AI and LLM-powered applications into production environments.

Core Features & Use Cases

• LLM Integration: Connect and utilize various LLMs (OpenAI, Anthropic) with unified clients and streaming capabilities.
• RAG Implementation: Set up Retrieval-Augmented Generation systems using vector databases like Chroma.
• Prompt Engineering: Craft effective prompts using patterns like Chain-of-Thought and Few-Shot learning.
• AI Agent Systems: Develop agents capable of using tools and managing conversation history.
• Production Deployment: Implement APIs with rate limiting, circuit breakers, and streaming responses.
• Use Case: Develop a customer support chatbot that can access a knowledge base using RAG, understand user queries, and respond intelligently using a chosen LLM, while being deployed as a scalable API.

Quick Start

Use the ai-engineer-expert skill to create a RAG system by ingesting documents from a specified directory.