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Measurement & Control for LLM Automations

Supported Python versions

PyPI Downloads License

Root Signals streamlines the evaluation of your LLM and agentic pipelines. We provide a holistic approach to GenAI measurability & observability with carefully-crafted ready-to-use evaluators based on cutting-edge LLM research as well as a framework for systematically adding your own custom evaluators.

With Root Signals you can develop your LLM application reliably, deploy them in confidence, and ensure optimal performance with continuous monitoring.

📦 Install

pip install root-signals

⚡ Quickstart

🔑 Get Your API Key

Sign up & create a key or generate a temporary key

Setup Option 1: Environment Variable

export ROOTSIGNALS_API_KEY=your-Root-API-key

Setup Option 2: .env File

echo ROOTSIGNALS_API_KEY=your-Root-API-key >> .env

Root Evaluators

from root import RootSignals

# Connect to Root Signals API
client = RootSignals()

# Run any of our ready-made evaluators
result = client.evaluators.Politeness(
    response="You can find the instructions from our Careers page."
)
# Example result:
#   {
#     "score": 0.7, --> a normalized score between [0, 1]
#     "justification": "The response is st...",
#     "execution_log_id": "..."
#   }

Check the full list of Root evaluators from the Root evaluators documentation. You can also add your own custom evaluators.

📖 Documentation

Resource Link
🐍 Python SDK View Documentation
📘 Product Docs View Documentation
📑 API Docs View Documentation
🔌 MCP View Repo
Tutorial Link
Quickstart Quickstart in Colab
Tuning a Custom Judge Tuning a Custom Judge in Colab
RAG Hallucination Detection with Root Judge RAG Hallucination Detection in Colab

🌍 Community

💬 Welcome to our Discord Server! It's a great place to ask questions, get help, and discuss ideas.

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Release files for root-signals 1.6.5

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