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Moonshot

DeepEval's integration with Moonshot AI allows you to use any Moonshot models to power all of DeepEval's metrics.

Command Line​

To configure your Moonshot model through the CLI, run the following command:

deepeval set-moonshot \
    --model "kimi-k2-0711-preview" \
    --api-key "your-api-key" \
    --temperature=0
info

The CLI command above sets Moonshot as the default provider for all metrics, unless overridden in Python code. To use a different default model provider, you must first unset Moonshot:

deepeval unset-moonshot
Persisting settings

You can persist CLI settings with the optional --save flag. See Flags and Configs -> Persisting CLI settings.

Python​

Alternatively, you can define KimiModel directly in python code:

from deepeval.models import KimiModel
from deepeval.metrics import AnswerRelevancyMetric

model = KimiModel(
    model_name="kimi-k2-0711-preview",
    api_key="your-api-key",
    temperature=0
)

answer_relevancy = AnswerRelevancyMetric(model=model)

There are TWO mandatory and ONE optional parameters when creating an KimiModel:

  • model: A string specifying the name of the Kimi model to use.
  • api_key: A string specifying your Kimi API key for authentication.
  • [Optional] temperature: A float specifying the model temperature. Defaulted to 0.
  • [Optional] generation_kwargs: A dictionary of additional generation parameters supported by your model provider.
tip

Any **kwargs you would like to use for your model can be passed through the generation_kwargs parameter. However, we request you to double check the params supported by the model and your model provider in their official docs.

Available Moonshot Models​

Below is a comprehensive list of available Moonshot models:

  • kimi-k2-0711-preview
  • kimi-thinking-preview
  • moonshot-v1-8k
  • moonshot-v1-32k
  • moonshot-v1-128k
  • moonshot-v1-8k-vision-preview
  • moonshot-v1-32k-vision-preview
  • moonshot-v1-128k-vision-preview
  • kimi-latest-8k
  • kimi-latest-32k
  • kimi-latest-128k