Agensight SDK
A simple SDK for tracing and evaluating AI agent workflows.
Installation
pip install --upgrade agensight
Quick Start
from agensight import init, trace, span
# Initialize Agensight
init(name="my-agent")
# Add tracing to your functions
@trace("my_workflow")
def my_function():
@span()
def my_subtask():
# Your code here
pass
return my_subtask()
Key Features
1. Tracing
- Auto-instrumented tracing of LLM calls
- Function execution tracking
- Agent interaction monitoring
- Performance metrics and token usage analytics
2. Evaluation
from agensight.eval.metrics import GEvalEvaluator
# Create custom evaluator
accuracy = GEvalEvaluator(
name="Accuracy",
criteria="Evaluate response accuracy",
threshold=0.7
)
# Use in your code
@span(metrics=[accuracy])
def my_function():
# Your code here
pass
3. Local Storage
- All data stored locally in
.agensight - No external data uploads
- Complete privacy and control
Dashboard
Start the dashboard to view traces and metrics:
agensight view
Visit http://localhost:5001 in your browser
Documentation
For detailed documentation, visit our docs.
Support
Join our GitHub Discussions for support and feature requests.
License
MIT License • © 2025 agensight contributors
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