Refer to the exhibit. A developer creates an agent in Azure AI Foundry with a code_interpreter tool. The agent is supposed to generate plots but returns errors. What is the most likely cause?
Exhibit
"Azure AI Foundry agent definition:\n{ \"name\": \"customer-support-agent\", \"instructions\": \"Respond to customer queries...\", \"tools\": [{\"type\": \"code_interpreter\"}]}"Trap 1: The instructions are too generic
While generic instructions can cause suboptimal behavior, they typically do not cause runtime errors when using a tool. The specific error with plotting indicates a more fundamental issue.
Trap 2: The code interpreter tool does not support visualization libraries
Incorrect. The code_interpreter tool in Azure AI Foundry does support visualization libraries such as Matplotlib and Seaborn, so lack of support is not the cause of the error.
Trap 3: The agent name is invalid
Invalid agent names would cause the agent to fail to be created or invoked entirely, not to return errors specifically when trying to generate plots.
- A
The instructions are too generic
Why wrong: While generic instructions can cause suboptimal behavior, they typically do not cause runtime errors when using a tool. The specific error with plotting indicates a more fundamental issue.
- B
The JSON syntax is incorrect
Correct. JSON syntax errors in the tool definition or the function call are common causes of tool execution failures. The code_interpreter tool requires correctly formatted JSON to parse the function arguments.
- C
The code interpreter tool does not support visualization libraries
Why wrong: Incorrect. The code_interpreter tool in Azure AI Foundry does support visualization libraries such as Matplotlib and Seaborn, so lack of support is not the cause of the error.
- D
The agent name is invalid
Why wrong: Invalid agent names would cause the agent to fail to be created or invoked entirely, not to return errors specifically when trying to generate plots.