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352ddf6 4b0d992 44ebedd 4b0d992 44ebedd 4b0d992 44ebedd 4b0d992 a03076c 4b0d992 a03076c 4b0d992 02c069f 009a807 02c069f 009a807 02c069f 4b0d992 352ddf6 0c7f47b 352ddf6 0c7f47b c2dd7cd 352ddf6 c2dd7cd 352ddf6 ab347bd 352ddf6 ab347bd 352ddf6 32b1d82 352ddf6 0c7f47b 352ddf6 0c7f47b 352ddf6 0c7f47b 352ddf6 0c7f47b 352ddf6 0c7f47b 352ddf6 0c7f47b 32b1d82 352ddf6 0c7f47b 352ddf6 0c7f47b 32b1d82 352ddf6 4b0d992 44ebedd 4b0d992 | 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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 | import io
import logging
import re
from datetime import datetime, timedelta, timezone
import streamlit as st
logger = logging.getLogger("talk_trace_ai")
DATETIME_FMT = "%Y-%m-%d %H:%M:%S"
DISPLAY_DATETIME_FMT = "%Y-%m-%d %p %I:%M:%S"
KST = timezone(timedelta(hours=9))
def get_kst_now():
return datetime.now(tz=KST)
def get_kst_now_str():
return get_kst_now().strftime(DATETIME_FMT)
def format_kst_datetime(value):
if value is None:
return "-"
kst_tz = timezone(timedelta(hours=9))
parsed_dt = None
should_assume_utc = False
if isinstance(value, datetime):
parsed_dt = value
else:
raw = str(value).strip()
if not raw:
return "-"
if "T" in raw and "+" not in raw and "Z" not in raw:
should_assume_utc = True
iso_candidate = raw.replace("Z", "+00:00")
try:
parsed_dt = datetime.fromisoformat(iso_candidate)
except ValueError:
for fmt in ("%Y-%m-%d %H:%M:%S.%f", DATETIME_FMT):
try:
parsed_dt = datetime.strptime(raw, fmt)
break
except ValueError:
continue
if parsed_dt is None:
return str(value)
if parsed_dt.tzinfo is not None:
parsed_dt = parsed_dt.astimezone(kst_tz)
elif should_assume_utc:
parsed_dt = parsed_dt.replace(tzinfo=timezone.utc).astimezone(kst_tz)
return parsed_dt.strftime(DISPLAY_DATETIME_FMT)
def get_client_ip():
try:
headers = st.context.headers
except Exception:
return ""
if not headers:
return ""
for key in ["x-forwarded-for", "x-real-ip", "cf-connecting-ip", "fly-client-ip",
"X-Forwarded-For", "X-Real-Ip", "CF-Connecting-IP", "True-Client-Ip",
"true-client-ip"]:
raw_ip = headers.get(key)
if raw_ip:
return str(raw_ip).split(",")[0].strip()
try:
all_keys = list(headers.keys()) if headers else []
logger.info("get_client_ip: IP 헤더 없음. 수신된 헤더 키: %s", all_keys)
except Exception:
pass
return ""
def anonymize_ip(raw_ip: str) -> str | None:
"""IP를 익명화하여 반환합니다. 저장 불가 시 None 반환.
IPv4: 첫 번째·마지막 옥텟 유지, 중간 0으로 대체 (예: 165.0.0.41)
IPv6: 앞 4그룹·마지막 그룹 유지, 중간 :: 처리 (예: 2406:5900:117c:424b::4444)
→ 같은 Wi-Fi라도 기기별 구분 가능
"""
ip = str(raw_ip or "").strip()
if not ip:
return None
if ":" in ip: # IPv6
groups = [g for g in ip.split(":") if g] # 빈 그룹 제거
if len(groups) >= 5:
return ":".join(groups[:4]) + "::" + groups[-1]
if len(groups) >= 4:
return ":".join(groups[:4]) + "::"
return None
parts = ip.split(".") # IPv4
if len(parts) == 4:
return f"{parts[0]}.0.0.{parts[3]}"
return None
def log_audit(event, room_name="", actor_name="", role="", **extra):
logger.info(
"AUDIT event=%s room=%s actor=%s role=%s extra=%s",
event, room_name, actor_name, role, extra,
)
def to_bool_flag(value):
if isinstance(value, bool):
return value
if value is None:
return False
return str(value).strip().lower() in {"true", "t", "1", "yes", "y", "on"}
_FONT_CANDIDATES = [
"/usr/share/fonts/truetype/nanum/NanumGothic.ttf",
"/usr/share/fonts/truetype/fonts-japanese-gothic.ttf",
"/usr/share/fonts/opentype/noto/NotoSansCJK-Regular.ttc",
]
_FONT_BOLD_CANDIDATES = [
"/usr/share/fonts/truetype/nanum/NanumGothicBold.ttf",
"/usr/share/fonts/truetype/nanum/NanumGothic.ttf",
"/usr/share/fonts/truetype/fonts-japanese-gothic.ttf",
]
_AI_SUBSECTION_LABELS = ("배움의 변화:", "성장한 점:", "한 줄 요약:")
def _get_pil_font(size: int):
from PIL import ImageFont
for path in _FONT_CANDIDATES:
try:
return ImageFont.truetype(path, size)
except Exception:
continue
return ImageFont.load_default()
def _get_pil_font_bold(size: int):
from PIL import ImageFont
for path in _FONT_BOLD_CANDIDATES:
try:
return ImageFont.truetype(path, size)
except Exception:
continue
return _get_pil_font(size)
_EMOJI_TEXT_SUBS = [
# AI 피드백 카드 레이블
("✅", "[완료]"),
("🌱", "[성장]"),
# 섹션 마커
("📌", ">>"),
("🔄", ">>"),
("🤖", "[AI]"),
("👨🏫", "[교사]"),
# 기타 자주 쓰이는 이모지
("💡", "[아이디어]"),
("➕", "[보충]"),
("❓", "[질문]"),
("🔵", "[찬성]"),
("🔴", "[반대]"),
("👍", "[좋아요]"),
("🎉", ""),
("⚠️", "[주의]"),
]
def _strip_non_renderable(text: str) -> str:
"""이미지 렌더링 시 깨질 수 있는 이모지/심볼을 텍스트로 대체하거나 제거."""
# 1단계: 알려진 이모지를 텍스트 레이블로 치환
for emoji, replacement in _EMOJI_TEXT_SUBS:
text = (text or "").replace(emoji, replacement)
# 2단계: 나머지 렌더링 불가 문자 제거
result = []
for ch in (text or ""):
code = ord(ch)
# 4바이트 유니코드 (이모지 대부분)
if code > 0xFFFF or 0xD800 <= code <= 0xDFFF:
continue
# BMP 내 이모지/기호 블록
if 0x2190 <= code <= 0x27FF: # 화살표, 기술기호, 딩뱃(✅ 등)
continue
if 0x2B00 <= code <= 0x2BFF: # 기타 기호·화살표
continue
if 0xFE00 <= code <= 0xFEFF: # 변형 선택자 등
continue
result.append(ch)
return "".join(result)
def _wrap_to_width(draw, text: str, font, max_width: int) -> list:
lines = []
for para in _strip_non_renderable(text).split("\n"):
if not para.strip():
lines.append("")
continue
words = para.split()
line: list = []
for word in words:
test = " ".join(line + [word])
try:
w = draw.textbbox((0, 0), test, font=font)[2]
except Exception:
w = len(test) * (font.size // 2 if hasattr(font, "size") else 9)
if w <= max_width:
line.append(word)
else:
if line:
lines.append(" ".join(line))
line = [word]
else:
lines.append(word)
if line:
lines.append(" ".join(line))
return lines or [""]
def create_analysis_image(
student_name: str,
topic: str,
pre_opinion: str,
post_opinion: str,
ai_analysis: str,
ai_feedback: str = "",
) -> bytes:
"""AI 배움 분석 결과를 PNG 이미지 bytes로 반환합니다."""
from PIL import Image, ImageDraw
W, PAD = 800, 40
CONTENT_W = W - PAD * 2
C_BG = (255, 255, 255)
C_HDR_BG = (25, 80, 160)
C_HDR_FG = (255, 255, 255)
C_HDR_SUB = (170, 200, 240)
C_ACCENT = (25, 80, 160)
C_TEXT = (30, 30, 30)
C_MUTED = (110, 110, 110)
C_DIVIDER = (220, 220, 220)
C_FTR_BG = (245, 245, 248)
f_title = _get_pil_font(22)
f_label = _get_pil_font(15)
f_sublabel = _get_pil_font_bold(16)
f_body = _get_pil_font(17)
f_small = _get_pil_font(13)
LH_BODY = 27 # body line height px
LH_LABEL = 22
LH_SUBLBL = 24
SEC_GAP = 16
SUBSEC_GAP = 14 # extra gap between AI subsections
HEADER_H = 74
FOOTER_H = 38
DIV_H = 20
def _ai_paragraphs(text):
"""AI 분석 텍스트를 (is_label, label_str, body_str) 튜플 리스트로 파싱."""
result = []
for para in _strip_non_renderable(text or "").split("\n"):
para = para.strip()
if not para:
continue
matched = next((lbl for lbl in _AI_SUBSECTION_LABELS if para.startswith(lbl)), None)
if matched:
result.append((True, matched, para[len(matched):].strip()))
else:
result.append((False, "", para))
return result or [(False, "", "(분석 없음)")]
# ── measure total height with dummy canvas ──────────────────────────
dummy = Image.new("RGB", (W, 10))
d = ImageDraw.Draw(dummy)
def section_h(text):
return LH_LABEL + 10 + len(_wrap_to_width(d, text, f_body, CONTENT_W)) * LH_BODY + SEC_GAP
def ai_section_h(text):
h = LH_LABEL + 10 # "AI 배움 분석" 헤더
paras = _ai_paragraphs(text)
for i, (is_lbl, lbl, body) in enumerate(paras):
if is_lbl and i > 0:
h += SUBSEC_GAP
if is_lbl:
h += LH_SUBLBL + 6
h += len(_wrap_to_width(d, body if is_lbl else lbl + body, f_body, CONTENT_W)) * LH_BODY
return h + SEC_GAP
total_h = (
HEADER_H + 18
+ LH_LABEL + 14 # info line
+ DIV_H
+ section_h(pre_opinion)
+ section_h(post_opinion)
+ DIV_H
+ ai_section_h(ai_analysis)
+ (DIV_H + section_h(ai_feedback) if ai_feedback else 0)
+ FOOTER_H
)
# ── render ──────────────────────────────────────────────────────────
img = Image.new("RGB", (W, total_h), C_BG)
draw = ImageDraw.Draw(img)
# Header
draw.rectangle([0, 0, W, HEADER_H], fill=C_HDR_BG)
draw.text((PAD, 14), "말자취 Talk-Trace AI", font=f_small, fill=C_HDR_SUB)
draw.text((PAD, 34), "AI 배움 분석 결과", font=f_title, fill=C_HDR_FG)
y = HEADER_H + 18
# Student / topic info line
info = f"학생: {_strip_non_renderable(student_name)} | 주제: {_strip_non_renderable(topic)}"
draw.text((PAD, y), info, font=f_label, fill=C_MUTED)
y += LH_LABEL + 14
def divider():
nonlocal y
draw.line([PAD, y, W - PAD, y], fill=C_DIVIDER, width=1)
y += DIV_H
def section(label, text):
nonlocal y
draw.text((PAD, y), label, font=f_label, fill=C_ACCENT)
y += LH_LABEL + 10
for line in _wrap_to_width(draw, text, f_body, CONTENT_W):
draw.text((PAD, y), line, font=f_body, fill=C_TEXT)
y += LH_BODY
y += SEC_GAP
def ai_section(text):
nonlocal y
draw.text((PAD, y), "AI 배움 분석", font=f_label, fill=C_ACCENT)
y += LH_LABEL + 10
for i, (is_lbl, lbl, body) in enumerate(_ai_paragraphs(text)):
if is_lbl and i > 0:
y += SUBSEC_GAP
if is_lbl:
# 소제목: 굵은 강조색
draw.text((PAD, y), lbl, font=f_sublabel, fill=C_ACCENT)
y += LH_SUBLBL + 6
for line in _wrap_to_width(draw, body, f_body, CONTENT_W):
draw.text((PAD + 8, y), line, font=f_body, fill=C_TEXT)
y += LH_BODY
else:
full = (lbl + body).strip()
for line in _wrap_to_width(draw, full, f_body, CONTENT_W):
draw.text((PAD, y), line, font=f_body, fill=C_TEXT)
y += LH_BODY
y += SEC_GAP
divider()
section("토론 전 생각", pre_opinion or "(없음)")
section("토론 후 생각", post_opinion or "(없음)")
divider()
ai_section(ai_analysis)
if ai_feedback:
divider()
section("AI 피드백 카드 (잘한 점 / 발전할 점)", ai_feedback)
# Footer
draw.rectangle([0, total_h - FOOTER_H, W, total_h], fill=C_FTR_BG)
now_str = datetime.now(tz=KST).strftime("%Y-%m-%d %H:%M")
draw.text((PAD, total_h - FOOTER_H + 13), f"생성: {now_str}", font=f_small, fill=C_MUTED)
buf = io.BytesIO()
img.save(buf, format="PNG", optimize=True)
return buf.getvalue()
def compact_ai_report_output(text):
raw_lines = [str(line).strip() for line in str(text or "").splitlines()]
cleaned = [line for line in raw_lines if line and not line.startswith("#")]
if not cleaned:
return ""
normalized_text = " ".join(cleaned)
normalized_text = re.sub(r"\s*(핵심요약 [123]:|베스트 학생:|선정 이유:)", r"\n\1", normalized_text)
normalized_lines = [line.strip() for line in normalized_text.splitlines() if line.strip()]
return "\n".join(normalized_lines[:5])
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