@Marvin While using the Gemini Model randomly “Call LLM”’ results in the following error:

raise ChatGoogleGEnerativeAIError(langchain_google_genai.chat_models.ChatGoogleGenerativeAIError: Invalid argument provided to Gemini: 400 Unable to submit request because it has an empty text parameter. Add a value to the parameter and try again. Learn more: <https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/gemini>')

Successive runs of the same code may result in successful completion without modification, are they any known issues? The same code does not display this behavior when using OpenAI models. or LLM.

The error message you're encountering suggests that the Gemini model is receiving an empty text parameter, which is causing the request to fail. This can happen if the input text is not properly passed to the model or if there's an intermittent issue with the data being sent. Here are a few potential reasons and solutions for this behavior: 1. Intermittent Empty Input: Ensure that the input text is consistently non-empty. There might be a conditional logic or data fetching issue in your code that sometimes results in an empty string being passed. 2. API Rate Limits or Quotas: Sometimes, API rate limits or quotas can cause intermittent failures. Ensure that you're not exceeding any limits set by the Gemini model's API. 3. Network Issues: Intermittent network issues could cause requests to fail. Ensure that your network connection is stable. 4. Library or SDK Bugs: There might be a bug in the library or SDK you're using to interact with the Gemini model. Check for updates or patches to the library. 5. Logging and Debugging: Add logging to your code to capture the input being sent to the Gemini model. This will help you identify if the input is indeed empty when the error occurs. 6. Known Issues: Check the official documentation or support channels for any known issues related to the Gemini model. The link provided in the error message might have more information. Since this error doesn't occur with OpenAI models, it could be specific to how the Gemini model processes requests. If the problem persists, consider reaching out to the support team of the service you're using for more detailed assistance.