anyscale
#10007
response_format_error
'messages' must include 'json' to use 'response_format' as 'json_object'.
This error has been identified and solved.
Reason
The 400 status error you are seeing in the Anyscale API, specifically the message "'messages' must contain the word 'json' in some form, to use 'response_format' of type 'json_object'," is occurring because the messages array in your request does not meet the required format for using the json_object response format.
In this context, the API expects the messages array to be structured in a way that includes specific keywords or formats, likely indicating that each message should be a dictionary with certain keys, and the presence of 'json' is required to validate this structure. If the messages array does not adhere to this expected format, the API returns a 400 Bad Request error.
Solution
To fix the 400 status error in the Anyscale API, you need to ensure the messages array is properly formatted. Here are the key actions to take:
Structure the
messagesarray as a list of dictionaries, where each dictionary represents a message.Ensure each message dictionary includes the necessary keys, such as
roleandcontent.Verify that the message format complies with the API's specifications, which likely require a specific structure indicating JSON format.
Key Actions:
Use a list of dictionaries for the
messagesarray.Include
roleandcontentkeys in each message dictionary.Ensure the format indicates JSON, possibly by including the word 'json' or using JSON-compatible structure.
Suggested Links
https://github.com/ray-project/ray/issues/31370
https://github.com/langchain-ai/langchain/issues/15125
https://docs.apigee.com/api-platform/troubleshoot/runtime/400-decompressionfailureatrequest
https://learn.microsoft.com/vi-vn/azure/ai-services/openai/how-to/json-mode
https://forum.bubble.io/t/how-to-catch-a-400-error-from-api-connector/27682
https://portkey.ai/error-library/input-length-error-10000
https://community.openai.com/t/managing-messages-array-for-multi-user-chat-with-gpt-3-5-turbo/85976
https://docs.anyscale.com/endpoints/fine-tuning/dataset-prep/
