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| from backend import run_llm, generate_variants | |
| from evaluator import final_score | |
| def optimize_prompt(base_prompt: str, reference_answer: str = ""): | |
| variants = generate_variants(base_prompt) | |
| batch_prompt = """ | |
| You are a helpful AI assistant. | |
| Answer each prompt separately. | |
| Format strictly: | |
| 1. <answer> | |
| 2. <answer> | |
| 3. <answer> | |
| 4. <answer> | |
| 5. <answer> | |
| Prompts: | |
| """ | |
| for i, p in enumerate(variants, 1): | |
| batch_prompt += f"{i}. {p}\n" | |
| combined_output = run_llm(batch_prompt) | |
| answers = [] | |
| for i in range(1, len(variants) + 1): | |
| parts = combined_output.split(f"{i}.") | |
| if len(parts) > 1: | |
| answers.append(parts[1].strip()) | |
| results = [] | |
| for p, out in zip(variants, answers): | |
| score = final_score(out, reference_answer) | |
| results.append({ | |
| "prompt": p, | |
| "output": out, | |
| "score": score | |
| }) | |
| results.sort(key=lambda x: x["score"], reverse=True) | |
| return results |