Build an Intelligent Document Processing with Confidence Scores with GPT-4o

An Intelligent Document Processing (IDP) provides actionable insights through confidence scores, allowing you to evaluate process performance, identify areas for review, and automate document processing and data extraction with precision, minimizing the need for manual oversight. In this blog, we will build an IDP app with confidence scores using GPT-4o.

We will be using the logprobs parameter in the OpenAI Chat Completions API. The log probabilities returned by the API, when logprobs is enabled, indicate the likelihood of each token in a GPT response, allowing assessment of model confidence and hallucination detection, with higher values (closer to zero) signifying greater confidence. It can help and can be utilized to gauge the confidence (probability) of the model’s response.

Using Logprobs to Gauge GPT’s Confidence in OCR Result

Evaluating Response Confidence with Log Probabilities in OpenAI APIs

To assess the confidence score of an OpenAI API response using log probabilities, follow these steps:

• Enable logprobs in your API request to obtain token-level log probabilities.
• Interpret log probabilities: values closer to 0…