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| import json | |
| from src.api_clients import openai_client | |
| last_eval_result = {} # Shared state | |
| def get_last_eval_data(): | |
| return last_eval_result if last_eval_result else None | |
| def run_comparison(human_scores, human_comments, model_scores, model_comments): | |
| prompt = f"""Compare human and model summary evaluations. | |
| Human Scores: {human_scores} | |
| Model Scores: {model_scores} | |
| Human Comments: {human_comments} | |
| Model Comments: {model_comments} | |
| Output key differences, strengths, and any mismatches.""" | |
| res = openai_client.chat.completions.create( | |
| model="gpt-4o-mini", | |
| messages=[{"role": "user", "content": prompt}], | |
| max_tokens=800 | |
| ) | |
| return res.choices[0].message.content | |
| def import_model_metrics(): | |
| data = get_last_eval_data() | |
| if not data or "scores" not in data: | |
| return ["" ] * 6 | |
| s = data["scores"] | |
| return ( | |
| str(s.get("coverage", "")), | |
| str(s.get("alignment", "")), | |
| str(s.get("hallucination", "")), | |
| str(s.get("relevance", "")), | |
| str(s.get("bias_toxicity", "")), | |
| json.dumps(data.get("comments", ""), indent=2) | |
| ) |