openai
#10101
input_validation_error
The provided input does not match the required type. Expected a "string" but received a different type. Please adjust the input format to meet the specified constraints.
This error has been identified and solved.
Reason
The 400 status error in the OpenAI API, indicated by a "Bad Request," can be caused by several factors:
Invalid Request Structure
The error message suggests that the request is not of the correct type. In this case, the API is expecting a "string" type for the prompt, but the provided input is in a different format, such as a JSON object or another data structure.
Incorrect API Request Parameters
The request parameters, such as input_variables and template, may not be formatted correctly or may not match the expected parameters for the API endpoint you are using. The API expects a clear and well-defined prompt, and any deviation from this can result in a 400 error.
Syntax or Configuration Issues
The request might contain invalid syntax or configuration, such as incorrect headers, misplaced or missing parameters, or an improperly formatted prompt. This can make the server unable to understand the request, leading to a 400 error.
Model-Specific Errors
Sometimes, the error can be model-specific. For example, specifying dimensions for a model that does not support it can result in a 400 error, as seen in cases where users try to specify dimensions for embedding models that do not allow this parameter.
Solution
To fix the 400 status error in the OpenAI API due to the provided input not matching the required type, you need to ensure the following:
Verify the input type: Make sure the input is a string as expected by the API.
Check request parameters: Ensure that all request parameters, such as
inputand any other required fields, are correctly formatted and match the expected parameters for the API endpoint.Inspect headers and configuration: Double-check the headers and configuration of your request to ensure they are valid and properly set.
Review model-specific constraints: If using embedding models, ensure you are not specifying parameters that the model does not support, such as dimensions for models that do not allow this.
By adjusting these aspects, you can align your request with the API's expectations and resolve the error.
