Llm App Patterns

What it does

This skill provides a collection of common patterns and techniques for building applications powered by Large Language Models (LLMs). It helps structure interactions, manage context, and guide LLM behavior to achieve specific goals. The patterns cover areas like tool use, conversation management, and data retrieval. This allows developers to create more robust and predictable AI agent experiences.

When to use it

• Building a chatbot that needs to access external APIs: Use the skill’s tool-use patterns to enable the bot to fetch information or perform actions through API calls.
• Creating an agent for complex tasks requiring multiple steps: Leverage conversation management patterns to break down the task into smaller, manageable interactions.
• Developing a data extraction application from unstructured text: Apply data retrieval patterns to efficiently extract specific pieces of information.
• Designing agents that need to remember and reference previous interactions: Utilize context management techniques for maintaining conversational history and user preferences.

Key capabilities

• Tool Use Patterns
• Conversation Management Patterns
• Data Retrieval Patterns
• Context Management Techniques

Example prompts

• "Show me the pattern for using a calculator API in my agent."
• "How can I structure a multi-turn conversation to gather user requirements?"
• "What's the best way to extract dates from a block of text using an LLM?"

Tips & gotchas

This skill assumes some familiarity with LLMs and prompt engineering. Understanding basic concepts like context windows and token limits will help you effectively apply these patterns.