Skip to main content

An open-source evaluation framework for voice agents

Project description

Calibrate

WhatsApp codecov CC BY-SA 4.0

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 agent
  • Human 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 cases
  • Text to Speech (TTS): Benchmark generated speech by multiple providers automatically using an Audio LLM Judge across 10+ indic languages
  • Simulations: 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              # Interactive main menu
calibrate stt          # Benchmark STT providers
calibrate tts          # Benchmark TTS providers
calibrate llm          # Interactive LLM evaluation
calibrate 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.

License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

CC BY-SA 4.0

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

calibrate_agent-0.0.56.tar.gz (18.6 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

calibrate_agent-0.0.56-py3-none-any.whl (752.0 kB view details)

Uploaded Python 3

File details

Details for the file calibrate_agent-0.0.56.tar.gz.

File metadata

  • Download URL: calibrate_agent-0.0.56.tar.gz
  • Upload date:
  • Size: 18.6 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for calibrate_agent-0.0.56.tar.gz
Algorithm Hash digest
SHA256 d8060e8e15b385361a5d19d246d3ba124087440234a84e4d9ba7e108f306ad09
MD5 7b5c70a66ce762921f9819b5a38e2c00
BLAKE2b-256 c7ba605bf9538fc5d3db172869920ab88521995da316f626576bc946ace8f456

See more details on using hashes here.

Provenance

The following attestation bundles were made for calibrate_agent-0.0.56.tar.gz:

Publisher: publish.yml on ARTPARK-SAHAI-ORG/calibrate

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file calibrate_agent-0.0.56-py3-none-any.whl.

File metadata

File hashes

Hashes for calibrate_agent-0.0.56-py3-none-any.whl
Algorithm Hash digest
SHA256 7f9e788194f0ce9e35afc7025c86d3578592ed72a001ec3469b8f4d3e4dbe1a3
MD5 f593567bbca915a8a2e8b240c2152fea
BLAKE2b-256 da27cb099a03086d7a1f759ce7ddb2be83c7200046449ba891d7e6959aa09be7

See more details on using hashes here.

Provenance

The following attestation bundles were made for calibrate_agent-0.0.56-py3-none-any.whl:

Publisher: publish.yml on ARTPARK-SAHAI-ORG/calibrate

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page