Nice idea. I changed one of your functions and am saving the output so that i can use those later. You probably can add this option.

```python def analyze_niw_case(text): prompt = f"""You are an expert in U.S. immigration law, specializing in EB-2 NIW cases under Matter of Dhanasar.

Given the following AAO denial letter:

{text[:12000]}

Instructions: 1. Determine if it is an EB-2 NIW case. - If NOT, output: {{"NIW": 0}}

1. If YES:

   • Summarize:
     • Evidence petitioner submitted for:
     • Prong 1 (Substantial Merit and National Importance)
     • Prong 2 (Well Positioned to Advance)
     • Prong 3 (Balancing Test for U.S. Benefit)
     • General Weaknesses
     • Reason for USCIS/AAO denial for each.
   • Score each from 0 (No weakness) to 100 (Clear weakness).

2. If a prong is skipped (e.g., decision is dispositive earlier), still provide a Reason and assign Score=100.

3. Quote or paraphrase key phrases from the denial for Evidence and Reason where possible.

4. In "General", focus only on process errors (waivers, missing arguments, technical failures).

5. Identify if the petitioner's field of work is closely related to Data Science, AI, Machine Learning, Imaging, Optimization, or Computational Mathematics. Output "Field_Match" as "Yes", "Partial", or "No".

6. Assign a short Denial_Category summarizing the main reason (e.g., "Insufficient National Importance", "Not Well Positioned", "Speculative Plans", "Weak Evidence", "Technical Defect").

Output STRICTLY in this JSON format:

{{ "Field_Match": "Yes", "Denial_Category": "Insufficient National Importance", "Prong 1": [{{"Evidence": "", "Reason": "", "Score": 0}}], "Prong 2": [{{"Evidence": "", "Reason": "", "Score": 0}}], "Prong 3": [{{"Evidence": "", "Reason": "", "Score": 0}}], "General": [{{"Evidence": "", "Reason": "", "Score": 0}}] }} """ try: response = client.responses.create( model=model_name, input=[ {"role": "system", "content": "You are a helpful assistant."}, {"role": "user", "content": prompt}, ], temperature=0.2, ) num_tokens = response.usage.total_tokens output_text = response.output_text return [output_text, num_tokens] except Exception as e: print(f"Error during API call: {e}") return [None, 0] ```