pytest for AI agents — trace, debug and catch regressions in LLM swarms
Project description
SwarmTrace 🐝
Pytest framework for AI Multi-Agents — trace, debug, and catch regressions in LLM swarms.
Built for the AMD Hackathon, SwarmTrace brings software engineering rigor to agentic AI systems. Test your multi-agent workflows like you test your code.
🎯 Why SwarmTrace?
LLM agents are unpredictable. SwarmTrace gives you:
- ✅ Trace agent reasoning — see every decision, tool call, and output
- ✅ Catch regressions — when agent behavior changes unexpectedly
- ✅ Debug failures — pinpoint exactly where the swarm broke
- ✅ CI/CD ready — integrates with any pytest pipeline
📦 Installation
git clone https://github.com/ravi3594444/swarmtrace.git
cd swarmtrace
pip install -r requirements.txt
🚀 Quick Start
from swarmtrace import SwarmTest, Agent
# Define your agent
agent = Agent(name="researcher", model="gpt-4")
# Write a test
def test_research_accuracy():
result = agent.run("What is the capital of France?")
assert "Paris" in result.output
assert result.latency < 5.0 # seconds
🛠️ Tech Stack
- Python 3.10+
- pytest — test framework
- LangChain / custom agent orchestration
- OpenAI / Anthropic / Local LLM APIs
📝 License
MIT — built by Ravi Kumar
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