---

name: llm-integration description: Integrate LLMs into applications - APIs, prompting, fine-tuning, and context management sasmp_version: "1.3.0" bonded_agent: 02-llm-integration bond_type: PRIMARY_BOND version: "2.0.0"

LLM Integration

Integrate Large Language Models with production-grade reliability.

When to Use This Skill

Invoke this skill when:

• Connecting to Claude, OpenAI, or other LLM APIs
• Designing effective prompts and system messages
• Optimizing token usage and costs
• Implementing streaming responses

Parameter Schema

Quick Start

Copy# Anthropic Claude
from anthropic import Anthropic

client = Anthropic()
response = client.messages.create(
    model="claude-sonnet-4-20250514",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Hello!"}]
)

# OpenAI
from openai import OpenAI

client = OpenAI()
response = client.chat.completions.create(
    model="gpt-4-turbo",
    messages=[{"role": "user", "content": "Hello!"}]
)

Prompt Templates

System Prompt

CopySYSTEM = """You are {role}, an expert in {domain}.
Your task: {task}
Constraints: {constraints}
Output format: {format}"""

Chain-of-Thought

CopyCOT = """Think step by step:
1. Understand the problem
2. Break it down
3. Solve each part
4. Combine results"""

Cost Optimization

Troubleshooting

Best Practices

• Always implement retry with backoff
• Use streaming for better UX
• Cache repeated queries
• Monitor token usage

Related Skills

• ai-agent-basics - Agent architecture
• rag-systems - Retrieval augmentation
• tool-calling - Function calling

References

• Anthropic API
• OpenAI API