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56a6725 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 | """Evidence ranking, deduplication, and truncation."""
SOURCE_PRIORITY = {
"DMD_ExonSkip_Lookup": -2,
"Variant_Therapy_Lookup": -2,
"Supportive_Care_Lookup": -2,
"ACMG_SF": -1,
"ACMG_Guideline": -1,
"CPIC": -1,
"N1C_Eligibility": -1,
"FDA": 0,
"DailyMed": 0,
"GeneReviews": 1,
"ClinGen": 1,
"ClinGen_Validity": 1,
"ClinVar": 2,
"Orphanet": 2,
"GenCC": 2,
"PharmGKB": 2,
"HPO_MONDO": 2,
"ClinicalTrials.gov": 3,
"Ensembl": 4,
"Ensembl_VEP": 4,
"UniProt": 4,
"ChEMBL": 5,
"PubMed": 5,
"PHAROS": 5,
"DGIdb": 5,
"Open Targets": 6,
"OMIM": 7,
"gnomAD": 8,
}
def _estimate_tokens(text: str) -> int:
return len(text) // 4
def truncate_evidence(evidence: list[dict], max_tokens: int = 3000) -> list[dict]:
"""Rank, deduplicate, and truncate evidence to fit within token budget."""
# Deduplicate by URL, keeping the first occurrence — but merge the
# strongest `_disease_relevance` across duplicates. The same trial can be
# retrieved by several queries (broad gene search vs. targeted condition
# search) that score disease-relevance differently; keeping only the first
# (often a low-relevance gene-query hit) would let a 0.0 duplicate mask a
# 1.0 hit and wrongly disqualify the right trial (-> spurious "None").
seen_urls: dict[str, dict] = {}
unique = []
for e in evidence:
url = e["url"]
if url not in seen_urls:
seen_urls[url] = e
unique.append(e)
elif e.get("_disease_relevance", 0) > seen_urls[url].get("_disease_relevance", 0):
seen_urls[url]["_disease_relevance"] = e.get("_disease_relevance")
def sort_key(e):
base = SOURCE_PRIORITY.get(e["source_name"], 99)
snippet = e.get("snippet", "")
if "maps to exon" in snippet or "DOMAIN MATCH" in snippet:
return (-1, base)
return (0, base)
unique.sort(key=sort_key)
selected = []
total_tokens = 0
for e in unique:
snippet_tokens = _estimate_tokens(e["snippet"])
if total_tokens + snippet_tokens > max_tokens:
break
selected.append(e)
total_tokens += snippet_tokens
return selected
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