Calibrate
Core engine powering Calibrate, a framework for evaluating AI agents which let you move from slow, manual testing to a fast, automated, and repeatable testing process for your entire agent stack:
Text to Text (LLMs): Evaluate the response quality and tool calling of your LLMs for multi-turn conversations and find the find LLM for your agentHuman alignment: Create LLM judges to make your evaluations scalable and reliable with human in the loop.Speech to Text (STT): Benchmark multiple providers (Google, Sarvam, ElevenLabs and more) on your dataset across 10+ indic languages using metrics optimised for agentic use casesText to Speech (TTS): Benchmark generated speech by multiple providers automatically using an Audio LLM Judge across 10+ indic languagesSimulations: Simulate realistic conversations using realistic user personas and scenarios to test failure modes for your agent (including interruptions for voice agents)
Installation
pip install calibrate-agent
Usage
calibrate-agent # Interactive main menu
calibrate-agent stt # Benchmark STT providers
calibrate-agent tts # Benchmark TTS providers
calibrate-agent llm # Interactive LLM evaluation
calibrate-agent simulations # Interactive text or voice simulations
Contributing
For the web version, see the frontend and backend repositories.
Install development dependencies once (requires uv):
uv sync --extra dev
Running tests
Run the full test suite:
uv run pytest tests/
Pre-commit
Enable the project's git hooks so the pre-commit test
runner fires on commits to main:
git config core.hooksPath .githooks
Every contributor needs to run it once.
Citation
If you use Calibrate in your work, please cite it:
@software{calibrate2026,
author = {Dalmia, Aman and Doshi, Jigar},
title = {Calibrate: An open-source framework for evaluating AI agents},
year = {2026},
url = {https://calibrate.artpark.ai},
note = {Source code: \url{https://github.com/ARTPARK-SAHAI-ORG}}
}
License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Metadata
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