Llm App Patterns
ListedHelps with LLMs, patterns as part of building AI and machine learning applications workflows.
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jpropato
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Live repository
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About this skill
What it does
This skill provides a collection of application patterns designed to enhance Large Language Model (LLM) agent capabilities. It offers pre-built structures and approaches for common LLM application scenarios, streamlining development and improving performance. The patterns cover areas such as data retrieval, tool use, and complex task orchestration within an AI agent workflow.
When to use it
- Rapid prototyping: Quickly build and test LLM applications without starting from scratch.
- Complex workflows: Structure intricate tasks involving multiple tools or data sources.
- Improving agent reliability: Implement proven patterns for more predictable and consistent results.
- Standardizing development: Ensure consistency across different AI agent projects within a team.
Key capabilities
- Pre-built application patterns
- Data retrieval strategies
- Tool use integration
- Task orchestration frameworks
Example prompts
- "Implement the 'Document Q&A' pattern for my knowledge base."
- "Show me how to integrate the 'API Interaction' pattern with a weather API."
- "Can you adapt the 'Planning and Execution' pattern for a travel itinerary generator?"
Tips & gotchas
This skill assumes some familiarity with LLM agent architecture and concepts. While it provides pre-built patterns, customization may be required to fit specific application needs.