Getting Started
Get up and running with Trace2 in minutes
Getting Started with Trace2
Welcome! This guide will help you install, configure, and start using Trace2.
What You'll Learn
In this section, you'll learn how to:
- ✅ Install Trace2 and its dependencies
- ✅ Configure LLM backends (OpenAI, Anthropic, etc.)
- ✅ Build your first optimizable function
- ✅ Run your first optimization
Quick Navigation
Installation
Install Trace2 via pip and set up your environment
Quick Start
Build your first optimizable AI agent in 5 minutes
Configuration
Configure LLM backends and API keys
Installation (30 seconds)
pip install trace-optThat's it! Trace2 is now installed.
Set Up Your API Key (1 minute)
import os
os.environ['OPENAI_API_KEY'] = 'your-api-key-here'Your First Example (2 minutes)
from opto.trace import node, bundle
from opto.optimizers import OptoPrime
@bundle(trainable=True)
def greet(name):
"""Greet the user."""
return f"Hey {name}"
optimizer = OptoPrime(greet.parameters())
# Optimize the greeting to be more professional
output = greet("Alice")
feedback = "Make it more professional and formal"
optimizer.zero_feedback()
optimizer.backward(output, feedback)
optimizer.step()
# Try again
print(greet("Alice")) # Should be more formal now!What's Next?
Choose your path:
🚀 Fast Track
Jump straight to the Quick Start and build something!
📚 Deep Dive
Learn the Core Concepts to understand how Trace2 works.
💡 Learn by Example
Browse Examples to see Trace2 in action.
Need Help?
- Join our Discord
- Check GitHub Issues
- Read the Paper
Prerequisites
You should be comfortable with:
- Python programming (3.10+)
- Basic machine learning concepts
- Using APIs (optional)
No prior experience with optimization or LLMs required!