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881aff7 | 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 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 | from __future__ import annotations
import os
import re
MAX_CHAT_PAPERS = int(os.getenv("MAX_CHAT_PAPERS", "4"))
CHAT_SUMMARY_MAX_CHARS = int(os.getenv("CHAT_SUMMARY_MAX_CHARS", "14000"))
_SECTION_HEADING = re.compile(r"^##\s+\d+\.", re.MULTILINE)
_QUESTION_STOPWORDS = frozenset(
{
"about",
"also",
"based",
"compare",
"could",
"does",
"first",
"from",
"have",
"paper",
"papers",
"please",
"provide",
"range",
"second",
"source",
"summarize",
"summary",
"that",
"the",
"their",
"these",
"third",
"this",
"those",
"was",
"were",
"what",
"when",
"which",
"would",
"your",
}
)
_ORDINAL_PAPER = re.compile(
r"\b(?P<ordinal>first|1st|second|2nd|third|3rd|fourth|4th)\s+paper\b",
re.I,
)
_ORDINAL_INDEX = {
"first": 0,
"1st": 0,
"second": 1,
"2nd": 1,
"third": 2,
"3rd": 2,
"fourth": 3,
"4th": 3,
}
def focus_document_ids_for_question(message: str, document_ids: list[str]) -> list[str]:
"""When the user names a specific paper, answer from that paper only."""
if len(document_ids) <= 1:
return document_ids
match = _ORDINAL_PAPER.search(message or "")
if not match:
return document_ids
index = _ORDINAL_INDEX.get(match.group("ordinal").lower())
if index is None or index >= len(document_ids):
return document_ids
return [document_ids[index]]
def enhance_ordinal_question(message: str, sources: list[dict]) -> str:
"""When the user says 'second paper', inject that paper's title into the prompt."""
if not _ORDINAL_PAPER.search(message or "") or len(sources) != 1:
return message
title = (sources[0].get("title") or "").strip()
if not title:
return message
return f"{message}\n\nAnswer specifically about the paper titled: {title}"
def _question_terms(question: str) -> list[str]:
terms: list[str] = []
lowered = (question or "").lower()
if "ph" in lowered:
terms.append("ph")
for token in re.findall(r"[a-z0-9]+", lowered):
if token in _QUESTION_STOPWORDS or len(token) < 3:
continue
terms.append(token)
return list(dict.fromkeys(terms))
def _extract_section(text: str, section_number: int, section_label: str) -> str:
pattern = re.compile(
rf"^##\s*{section_number}\.\s*{re.escape(section_label)}.*?(?=^##\s+\d+\.|\Z)",
re.MULTILINE | re.DOTALL | re.IGNORECASE,
)
match = pattern.search(text)
return match.group(0).strip() if match else ""
def _matching_lines(text: str, terms: list[str]) -> str:
if not terms:
return ""
lines: list[str] = []
for line in text.splitlines():
lowered = line.lower()
if any(term in lowered for term in terms):
lines.append(line.rstrip())
return "\n".join(lines).strip()
def _fit_blocks(blocks: list[str], budget: int) -> str:
selected: list[str] = []
used = 0
for block in blocks:
block = block.strip()
if not block:
continue
extra = len(block) + (2 if selected else 0)
if used + extra > budget:
remaining = budget - used - (2 if selected else 0)
if remaining > 120:
selected.append(block[:remaining].rstrip() + "…")
break
selected.append(block)
used += extra
return "\n\n".join(selected)
def excerpt_summary(text: str, *, question: str = "", n_papers: int = 1) -> str:
"""Prefer identity + key results (+ question matches) instead of blind head truncation."""
per_paper = max(2500, CHAT_SUMMARY_MAX_CHARS // max(n_papers, 1))
if len(text) <= per_paper:
return text
blocks: list[str] = []
identity = _extract_section(text, 1, "Paper Identity")
key_results = _extract_section(text, 5, "Key Results")
takeaway = _extract_section(text, 10, "Concise Takeaway")
terms = _question_terms(question)
matched = _matching_lines(text, terms)
if identity:
blocks.append(identity)
if key_results:
blocks.append(key_results)
elif matched:
blocks.append(matched)
if takeaway and takeaway not in blocks:
blocks.append(takeaway)
if matched and matched not in blocks:
blocks.append(matched)
excerpt = _fit_blocks(blocks, per_paper)
if excerpt:
return excerpt
return text[:per_paper] + "\n\n[Additional sections omitted for length.]"
def truncate_summary(text: str, *, n_papers: int = 1, question: str = "") -> str:
return excerpt_summary(text, question=question, n_papers=n_papers)
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