Troubleshooting Azure OpenAI Integration with NVIDIA’s Nemo Guardrails 0.14.0

Recently, I’ve encountered an issue while integrating Azure OpenAI with the latest version of NVIDIA’s Nemo Guardrails, specifically version 0.14.0. Previously, when I was using Nemo Guardrails version 0.11.0, everything worked smoothly without any complications. However, after upgrading to the new version, I’ve run into an error that has stumped me.

Upon debugging, I confirmed that the model configuration in my setup is correctly specified and being passed from the config folder as intended. Thus, I am at a loss as to what might have changed in the latest release of Nemo that could cause this issue. Unfortunately, the official documentation does not seem to provide insights into any alterations in model configuration.

Here’s the specific error message I’m encountering:

Traceback (most recent call last):
File ".venv\Lib\site-packages\nemoguardrails\Ilm\models\langchain_initializer.py", line 193, in init_langchain_model
raise ModellnitializationError(base) from last_exception
nemoguardrails.Ilm.models.langchain_initializer.ModellnitializationError: Failed to initialize model 'gpt-40-mini' with provider 'azure' in 'chat' mode: ValueError encountered in initializer_init_text_completion_model(modes=['text', 'chat']) for model: gpt-40-mini and provider: azure: 1 validation error for OpenAIChat Value error, Did not find openai_api_key, please add an environment variable OPENAI_API_KEY which contains it, or pass openai_api_key as a named parameter. [type=value_error, input_value={'api_key': '9DUJj5JczBLw...

The error indicates that the integration is failing due to a missing API key, specifically acknowledging that the environment variable OPENAI_API_KEY has not been set. Hence, it’s prompting me to ensure that this key is either included as an environment variable or provided directly as a named parameter in the configuration.

For anyone else who might be facing similar challenges with the transition to Nemo Guardrails 0.14.0, I recommend verifying your environment setup carefully. If you’re running into the same validation error, double-check to ensure your API keys are correctly defined in your environment or specified in your configuration.

I would also appreciate any insights or documentation updates regarding changes