Below errors can occur when “Conversation history” is not set correctly.
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Studio transformation prompt_completion input validation error: must be array {"type":"array"} /history
Provide values for the conversation or use the x to remove it
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Studio transformation prompt_completion input validation error: must be equal to one of the allowed values {"allowedValues":["user","ai","function"]} /history/0/role
429: {"message":"Rate limit reached for default-gpt-3.5-turbo-16k in organization org-JfRBhZhDGaEQPgWeVxj3OEGF on tokens per min. Limit: 180000 / min. Current: 1 / min. Contact us through our help center at help.openai.com if you continue to have issues.","type":"tokens","param":null,"code":"rate_limit_exceeded"}
This error happens when the used API key is set to a different rate limit compared to what Relevance uses by default.
Trying again with different intervals of pause helps with this issue.
This error occurs when the input to “Extract website content” receives an input parameter that is not of type string (e.g. a URL).
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Studio transformation browserless_scrape input validation error: must be string {"type":"string"} /website_url
A common situation where this happens is when the output of another step (e.g. Google search as shown below) is used as the input to “Extract website content”.
If the output is a list or an object similar to the example below, you need to access the URL field.In our example, we can access the string URLs in three ways:
If the above result is the output of a google search step, accessing the
first link is via google.organic[0].link
At Relevance, you can set up validators for your LLM component to ensure that the output
follows the desired format. The below error happens when the LLM’s output does not meet the criteria. Prompt engineering is the best way to
handle such as situation. Try rewording your prompt and providing examples.