Skip to main content

An open-source evaluation framework for voice agents

Project description

Calibrate

WhatsApp codecov CC BY-SA 4.0

CLI for Calibrate: an AI evaluation platform for non-profits

With Calibrate, you can 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)

Calibrate is built on top of pipecat, a framework for building 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

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-0.0.46.tar.gz (17.8 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-0.0.46-py3-none-any.whl (701.4 kB view details)

Uploaded Python 3

File details

Details for the file calibrate_agent-0.0.46.tar.gz.

File metadata

  • Download URL: calibrate_agent-0.0.46.tar.gz
  • Upload date:
  • Size: 17.8 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for calibrate_agent-0.0.46.tar.gz
Algorithm Hash digest
SHA256 963a15eb6d5cd982e229be9edb71c3e3550db975237bb852a5b262b11d3a6c87
MD5 80b85f1c39f66370c582391830203be4
BLAKE2b-256 68e3c93bbd58ac7ce07e1573f9103d16459dbf0c916d30a5a1b457adda13f509

See more details on using hashes here.

Provenance

The following attestation bundles were made for calibrate_agent-0.0.46.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-0.0.46-py3-none-any.whl.

File metadata

File hashes

Hashes for calibrate_agent-0.0.46-py3-none-any.whl
Algorithm Hash digest
SHA256 df8cf13af3d3174d3a397c465ad619ca2824ce90792647332175ecb2fca37acb
MD5 1807d4ed5d6d9b68a3579f3efc4a37b6
BLAKE2b-256 b73e44095601938fb7b7d3773cc6a5b5286bbcae45b1fb52dea1c00bb6f05a58

See more details on using hashes here.

Provenance

The following attestation bundles were made for calibrate_agent-0.0.46-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