How can I force GPT-4-0125-preview to automatically call tools without explicit instructions?

Below is some guidance based on the documentation for tool usage with the OpenAI API:

Forcing the Model to Use a Tool

To force the model to call a tool rather than choosing between generating a message or calling the tool, you can explicitly specify the tool in your API request. For example, setting the parameter like this:

JSONCopied
{
  "tool_choice": {"type": "function", "function": {"name": "my_function"}}
}

This tells the model it must use the specified function rather than making a choice. The documentation notes that when you specify a tool, it forces the model to call that tool.

Comparing GPT-4 vs. GPT-4 Turbo

Your observation that the normal GPT-4-turbo uses the tool as intended while your current implementation does not might be due to differences in how parameters are interpreted across versions. The default behavior for both GPT-4 and GPT-4-turbo is auto, meaning the model decides whether to generate a message or call a tool. When not using auto and forcing the tool, the model should consistently use the tool without waiting for explicit instructions in the response.

Recommendations

• Double-Check Parameters: Ensure that your API call is correctly structured with the tool specification. Even a small formatting mistake can cause the model to fall back to auto behavior.
• Model Compatibility: Confirm that you’re using a compatible model version (such as GPT-4 Turbo) that supports explicit tool calls as described in the documentation.
• Test in Isolation: Create isolated test calls with the tool-specific configuration to determine if the issue is with the parameters or with the broader application context.
• Report if Persisting: If you continue to experience this behavior despite following recommendations, it might be a good idea to reach out to OpenAI support or consult community channels to see if others are encountering similar issues.

This guidance is directly in line with our API reference documentation, which outlines the proper use of the tool_choice parameter. Hopefully, this helps ensure that your customer-facing application behaves as expected.