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OpenAI

By default, DeepEval uses gpt-4o to power all of its evaluation metrics. To enable this, you’ll need to set up your OpenAI API key. DeepEval also supports all other OpenAI models, which can be configured directly in Python.

Setting Up Your API Key​

To use OpenAI for deepeval's LLM-Evals (metrics evaluated using an LLM), supply your OPENAI_API_KEY in the CLI:

export OPENAI_API_KEY=<your-openai-api-key>

Alternatively, if you're working in a notebook environment (Jupyter or Colab), set your OPENAI_API_KEY in a cell:

%env OPENAI_API_KEY=<your-openai-api-key>

Python​

You may use OpenAI models other than gpt-4o, which can be configured directly in python code through DeepEval's GPTModel.

info

You may want to use stronger reasoning models like gpt-4o for metrics that require a high level of reasoning — for example, a custom GEval for mathematical correctness.

from deepeval.models import GPTModel
from deepeval.metrics import AnswerRelevancyMetric

model = GPTModel(
    model="o1",
    temperature=0
)
answer_relevancy = AnswerRelevancyMetric(model=model)

There are ONE mandatory and ONE optional parameters when creating a GPTModel:

  • model: A string specifying the name of the GPT model to use. Defaulted to gpt-4o.
  • [Optional] temperature: A float specifying the model temperature. Defaulted to 0.

Available OpenAI Models​

note

This list only displays some of the available models. For a comprehensive list, refer to the OpenAI's official documentation.

Below is a list of commonly used OpenAI models:

  • gpt-4.5-preview
  • gpt-4o
  • gpt-4o-mini
  • o1
  • o1-pro
  • o1-mini
  • o3-mini
  • gpt-4-turbo
  • gpt-4
  • gpt-4-32k
  • gpt-3.5-turbo
  • gpt-3.5-turbo-instruct
  • gpt-3.5-turbo-16k-0613
  • davinci-002
  • babbage-002