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| """Reusable prompt templates for LLM-assisted ranking and classification.""" | |
| from __future__ import annotations | |
| from src.data.loaders import EventDefinitionForm | |
| RANK_SYSTEM_PROMPT = ( | |
| "You are a clinical terminology expert supporting semantic harmonization for " | |
| "real-world evidence studies. You review candidate medical codes retrieved for " | |
| "a phenotype and re-rank them by clinical relevance, using the structured " | |
| "phenotype definition (Event Definition Form) provided by the user. " | |
| "You must respond only with valid JSON, no additional commentary." | |
| ) | |
| CLASSIFY_SYSTEM_PROMPT = ( | |
| "You are a clinical terminology expert supporting semantic harmonization for " | |
| "real-world evidence studies. You review candidate medical codes for a phenotype " | |
| "and classify each one as 'Narrow' (highly specific to the phenotype), " | |
| "'Possible' (related but insufficiently specific, or specific in some but not " | |
| "all contexts), or 'Exclude' (not relevant, or explicitly an exclusion " | |
| "criterion). Base your decision on the structured phenotype definition (Event " | |
| "Definition Form) provided by the user. For every code, provide a brief " | |
| "explanation followed by the label and a confidence score between 0 and 1. " | |
| "You must respond only with valid JSON, no additional commentary." | |
| ) | |
| def classify_system_prompt(use_possible_category: bool = False) -> str: | |
| """Return classification instructions for binary or three-way labeling.""" | |
| if use_possible_category: | |
| return CLASSIFY_SYSTEM_PROMPT | |
| return ( | |
| "You are a clinical terminology expert supporting semantic harmonization " | |
| "for real-world evidence studies. Classify every candidate as 'Narrow' " | |
| "when it is sufficiently specific to the phenotype, or 'Exclude' otherwise. " | |
| "Do not return a 'Possible' label. Any EDF rule describing a Possible, " | |
| "ambiguous, or insufficiently specific case must be treated as Exclude in " | |
| "this binary mode. Base decisions on the supplied Event Definition Form. " | |
| "For every code, request the output fields in this order: code, vocabulary, " | |
| "explanation, label, confidence. Confidence must be from 0 to 1. Respond " | |
| "only with valid JSON." | |
| ) | |
| def build_rank_prompt(edf: EventDefinitionForm, candidates: list[dict]) -> str: | |
| """Build the user prompt for LLM-based re-ranking of candidate codes.""" | |
| candidate_lines = "\n".join( | |
| f"- code: {c['code']} | vocabulary: {c['vocabulary']} | description: {c['description']}" | |
| for c in candidates | |
| ) | |
| return ( | |
| f"Phenotype definition:\n{edf.to_prompt_context()}\n\n" | |
| f"Candidate codes to rank by clinical relevance to this phenotype " | |
| f"(most relevant first):\n{candidate_lines}\n\n" | |
| "Return a JSON object with a single key 'ranked_codes', containing a list of " | |
| "objects with keys 'code', 'vocabulary', and 'relevance_score' (float 0-1, " | |
| "higher = more relevant), sorted descending by relevance_score." | |
| ) | |
| def build_classify_prompt( | |
| edf: EventDefinitionForm, | |
| candidates: list[dict], | |
| use_possible_category: bool = False, | |
| ) -> str: | |
| """Build the user prompt for LLM-based classification of candidate codes.""" | |
| candidate_lines = "\n".join( | |
| f"- code: {c['code']} | vocabulary: {c['vocabulary']} | description: {c['description']}" | |
| for c in candidates | |
| ) | |
| labels = "'Narrow', 'Possible', or 'Exclude'" if use_possible_category else "'Narrow' or 'Exclude'" | |
| return ( | |
| f"Phenotype definition:\n{edf.to_prompt_context(include_possible=use_possible_category)}\n\n" | |
| f"Classify each of the following candidate codes:\n{candidate_lines}\n\n" | |
| "Return a JSON object with a single key 'classifications', containing a " | |
| "list of objects using this requested key order: 'code', 'vocabulary', " | |
| "'explanation' (brief string), 'label' " | |
| f"(one of {labels}), and 'confidence' (float 0-1)." | |
| ) | |