Measurement & Control for LLM Automations
Scorable 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 Scorable you can develop your LLM application reliably, deploy them in confidence, and ensure optimal performance with continuous monitoring.
📦 Install
pip install scorable
⚡ Quickstart
🔑 Get Your API Key
Sign up & create a key or generate a temporary key
Setup Option 1: Environment Variable
export SCORABLE_API_KEY=your-scorable-api-key
Setup Option 2: .env File
echo SCORABLE_API_KEY=your-scorable-api-key >> .env
Root Evaluators
from scorable import Scorable
# Connect to Scorable API
client = Scorable()
# 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 |
|
| Tuning a Custom Judge |
|
1 maintainer
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