Datasets:
Formats:
parquet
Languages:
English
Size:
10M - 100M
Tags:
biology
chemistry
drug-discovery
clinical-trials
protein-protein-interaction
gene-essentiality
License:
| #!/usr/bin/env python3 | |
| """Export all LLM benchmark prompt templates to a reproducibility appendix. | |
| Reads templates from src/negbiodb/llm_prompts.py and the judge rubric from | |
| src/negbiodb/llm_eval.py, then writes docs/appendix_prompts.md. | |
| Usage: | |
| python scripts/export_prompt_appendix.py | |
| """ | |
| from pathlib import Path | |
| from negbiodb.llm_eval import L3_JUDGE_PROMPT | |
| from negbiodb.llm_prompts import ( | |
| L1_ANSWER_FORMAT, | |
| L1_FEW_SHOT, | |
| L1_ZERO_SHOT, | |
| L2_FEW_SHOT, | |
| L2_ZERO_SHOT, | |
| L3_FEW_SHOT, | |
| L3_ZERO_SHOT, | |
| L4_ANSWER_FORMAT, | |
| L4_FEW_SHOT, | |
| L4_ZERO_SHOT, | |
| SYSTEM_PROMPT, | |
| ) | |
| PROJECT_ROOT = Path(__file__).resolve().parent.parent | |
| OUTPUT = PROJECT_ROOT / "docs" / "appendix_prompts.md" | |
| def code_block(text: str, lang: str = "") -> str: | |
| """Wrap text in a fenced code block.""" | |
| return f"```{lang}\n{text}\n```" | |
| def main(): | |
| sections = [] | |
| sections.append("# Appendix A: LLM Benchmark Prompt Templates\n") | |
| sections.append( | |
| "This appendix documents all prompt templates used in the NegBioDB " | |
| "LLM benchmark (tasks L1--L4). Templates are reproduced verbatim " | |
| "from `src/negbiodb/llm_prompts.py` and `src/negbiodb/llm_eval.py`.\n" | |
| ) | |
| # A.1 System Prompt | |
| sections.append("## A.1 System Prompt (Shared Across All Tasks)\n") | |
| sections.append(code_block(SYSTEM_PROMPT)) | |
| sections.append("") | |
| # A.2 L1 | |
| sections.append("## A.2 L1: Activity Classification (Multiple Choice)\n") | |
| sections.append("### A.2.1 Zero-Shot Template\n") | |
| sections.append(code_block(L1_ZERO_SHOT)) | |
| sections.append("") | |
| sections.append("### A.2.2 Few-Shot Template\n") | |
| sections.append(code_block(L1_FEW_SHOT)) | |
| sections.append("") | |
| sections.append("### A.2.3 Answer Format Instruction\n") | |
| sections.append(code_block(L1_ANSWER_FORMAT)) | |
| sections.append( | |
| "\nThe answer format instruction is appended after both zero-shot " | |
| "and few-shot templates.\n" | |
| ) | |
| # A.3 L2 | |
| sections.append("## A.3 L2: Structured Extraction\n") | |
| sections.append("### A.3.1 Zero-Shot Template\n") | |
| sections.append(code_block(L2_ZERO_SHOT)) | |
| sections.append("") | |
| sections.append("### A.3.2 Few-Shot Template\n") | |
| sections.append(code_block(L2_FEW_SHOT)) | |
| sections.append( | |
| "\nFew-shot examples include the abstract text and the corresponding " | |
| "gold extraction in JSON format, separated by `---` delimiters.\n" | |
| ) | |
| # A.4 L3 | |
| sections.append("## A.4 L3: Scientific Reasoning\n") | |
| sections.append("### A.4.1 Zero-Shot Template\n") | |
| sections.append(code_block(L3_ZERO_SHOT)) | |
| sections.append("") | |
| sections.append("### A.4.2 Few-Shot Template\n") | |
| sections.append(code_block(L3_FEW_SHOT)) | |
| sections.append("") | |
| sections.append("### A.4.3 LLM-as-Judge Rubric\n") | |
| sections.append( | |
| "Responses are evaluated by a judge model (Gemini 2.5 Flash-Lite) " | |
| "using the following rubric:\n" | |
| ) | |
| sections.append(code_block(L3_JUDGE_PROMPT)) | |
| sections.append( | |
| "\nThe judge returns scores as JSON with four dimensions " | |
| "(accuracy, reasoning, completeness, specificity), each rated 1--5.\n" | |
| ) | |
| # A.5 L4 | |
| sections.append("## A.5 L4: Tested vs Untested Discrimination\n") | |
| sections.append("### A.5.1 Zero-Shot Template\n") | |
| sections.append(code_block(L4_ZERO_SHOT)) | |
| sections.append("") | |
| sections.append("### A.5.2 Few-Shot Template\n") | |
| sections.append(code_block(L4_FEW_SHOT)) | |
| sections.append("") | |
| sections.append("### A.5.3 Answer Format Instruction\n") | |
| sections.append(code_block(L4_ANSWER_FORMAT)) | |
| sections.append( | |
| "\nThe answer format instruction is appended after both zero-shot " | |
| "and few-shot templates.\n" | |
| ) | |
| # A.6 Model Configuration | |
| sections.append("## A.6 Model Configuration\n") | |
| sections.append("| Parameter | Value |") | |
| sections.append("|-----------|-------|") | |
| sections.append("| Temperature | 0.0 (deterministic) |") | |
| sections.append("| Max output tokens | 1024 (L1/L4), 2048 (L2/L3) |") | |
| sections.append("| Few-shot sets | 3 independent sets (fs0, fs1, fs2) |") | |
| sections.append("| Retry policy | Exponential backoff, max 8 retries |") | |
| sections.append("") | |
| sections.append("### Models\n") | |
| sections.append("| Model | Provider | Inference |") | |
| sections.append("|-------|----------|-----------|") | |
| sections.append("| Llama-3.3-70B-Instruct-AWQ | vLLM | Local (A100 GPU) |") | |
| sections.append("| Qwen2.5-32B-Instruct-AWQ | vLLM | Local (A100 GPU) |") | |
| sections.append("| Mistral-7B-Instruct-v0.3 | vLLM | Local (A100 GPU) |") | |
| sections.append("| GPT-4o-mini | OpenAI API | Cloud |") | |
| sections.append("| Gemini 2.5 Flash | Google Gemini API | Cloud |") | |
| sections.append("| Gemini 2.5 Flash-Lite | Google Gemini API | Cloud |") | |
| sections.append("") | |
| sections.append( | |
| "Gemini 2.5 Flash uses `thinkingConfig: {thinkingBudget: 0}` to " | |
| "disable internal reasoning tokens and ensure the full output budget " | |
| "is available for the response.\n" | |
| ) | |
| # Write output | |
| OUTPUT.parent.mkdir(parents=True, exist_ok=True) | |
| text = "\n".join(sections) | |
| OUTPUT.write_text(text) | |
| print(f"Written: {OUTPUT}") | |
| print(f" Lines: {len(text.splitlines())}") | |
| # Verify completeness: check that each template's content appears in output | |
| checks = { | |
| "SYSTEM_PROMPT": SYSTEM_PROMPT[:40], | |
| "L1_ZERO_SHOT": "{context}", | |
| "L1_FEW_SHOT": "examples of drug-target interaction classification", | |
| "L1_ANSWER_FORMAT": "Respond with ONLY the letter", | |
| "L2_ZERO_SHOT": "Extract all negative drug-target interaction", | |
| "L2_FEW_SHOT": "extract from this abstract", | |
| "L3_ZERO_SHOT": "Structural compatibility", | |
| "L3_FEW_SHOT": "examples of scientific reasoning", | |
| "L3_JUDGE_PROMPT": "Rate the following scientific explanation", | |
| "L4_ZERO_SHOT": "{context}", | |
| "L4_FEW_SHOT": "tested/untested compound-target pair", | |
| "L4_ANSWER_FORMAT": "tested' or 'untested'", | |
| } | |
| missing = [name for name, snippet in checks.items() if snippet not in text] | |
| if missing: | |
| print(f" WARNING: Missing templates: {missing}") | |
| else: | |
| print(" All 12 templates included.") | |
| if __name__ == "__main__": | |
| main() | |