feat: AI 분석 결과 이미지 저장 + 교사 대시보드 학생별 분석 뷰어

- 학생/교사 화면에 AI 배움 분석 PNG 이미지 다운로드 버튼 추가
- Dockerfile.base에 NanumGothic 한글 폰트 설치 추가
- 교사 대시보드에 학생별 분석 결과 조회 기능 추가 (드롭다운 선택)
- fetch_all_opinion_changes() DB 함수 추가

https://claude.ai/code/session_016DE3uHLsVmA5Uv7gZGGaKT

Dockerfile.base

@@ -1,4 +1,6 @@
 FROM python:3.11-slim
 WORKDIR /app
 COPY requirements.txt .
+RUN apt-get update && apt-get install -y --no-install-recommends fonts-nanum \
+    && rm -rf /var/lib/apt/lists/*
 RUN pip install --no-cache-dir -r requirements.txt

components/opinion_change.py

@@ -1,6 +1,7 @@
 import streamlit as st
 
 from config import AI_MODEL_NAME, LIVE_BOARD_FETCH_LIMIT
+from utils import create_analysis_image, get_kst_now
 from db import (
     fetch_debate_status,
     fetch_live_messages,
@@ -77,6 +78,20 @@ def render_post_opinion_section(supabase, room_name, student_name, act_type, cur
         if ai_analysis:
             st.info("🤖 **AI 배움 분석**")
             st.markdown(ai_analysis.replace("\n", "\n\n"))
+            try:
+                img_bytes = create_analysis_image(
+                    student_name, current_topic, pre_opinion, post_opinion, ai_analysis
+                )
+                filename = f"배움분석_{student_name}_{get_kst_now().strftime('%Y%m%d_%H%M')}.png"
+                st.download_button(
+                    "🖼️ 분석 결과 이미지로 저장",
+                    data=img_bytes,
+                    file_name=filename,
+                    mime="image/png",
+                    use_container_width=True,
+                )
+            except Exception:
+                pass
         else:
             if st.button("🤖 AI 배움 분석 받기", use_container_width=True):
                 _trigger_analysis(supabase, room_name, student_name, act_type, current_topic, pre_opinion, post_opinion)

components/teacher_dashboard.py

@@ -3,7 +3,8 @@ import logging
 import plotly.express as px
 import streamlit as st
 
-from db import destroy_room_data, fetch_debate_status, fetch_live_messages, session_control_available, set_debate_status
+from db import destroy_room_data, fetch_all_opinion_changes, fetch_debate_status, fetch_live_messages, opinion_changes_available, session_control_available, set_debate_status
+from utils import create_analysis_image, get_kst_now
 from validators import with_fallback_author_role
 from utils import log_audit
 from config import DASHBOARD_FETCH_LIMIT, ROOM_DESTROY_ENABLED, UI_FONT_FAMILY
@@ -47,6 +48,43 @@ def render_teacher_dashboard(supabase, room_name, user_role, student_name, curre
     else:
         st.info(f"{act_type} 데이터가 없습니다.")
 
+    if opinion_changes_available():
+        df_oc = fetch_all_opinion_changes(supabase, room_name)
+        if not df_oc.empty:
+            st.divider()
+            st.subheader("🔍 학생별 배움 분석")
+            students = df_oc["student_name"].tolist()
+            selected = st.selectbox("학생 선택", students, key="oc_student_select")
+            row = df_oc[df_oc["student_name"] == selected].iloc[0]
+            pre  = row.get("pre_opinion")  or "(없음)"
+            post = row.get("post_opinion") or "(없음)"
+            ai   = row.get("ai_analysis")  or ""
+            col_pre, col_post = st.columns(2)
+            with col_pre:
+                st.caption("📌 토론 전 생각")
+                st.info(pre)
+            with col_post:
+                st.caption("🔄 토론 후 생각")
+                st.info(post)
+            if ai:
+                st.caption("🤖 AI 배움 분석")
+                st.markdown(ai.replace("\n", "\n\n"))
+                try:
+                    img_bytes = create_analysis_image(selected, current_topic, pre, post, ai)
+                    filename = f"배움분석_{selected}_{get_kst_now().strftime('%Y%m%d_%H%M')}.png"
+                    st.download_button(
+                        "🖼️ 분석 결과 이미지로 저장",
+                        data=img_bytes,
+                        file_name=filename,
+                        mime="image/png",
+                        use_container_width=True,
+                        key="oc_img_download",
+                    )
+                except Exception:
+                    pass
+            else:
+                st.caption("AI 분석이 아직 없습니다.")
+
     if session_control_available():
         st.divider()
         st.subheader("🎛️ 토론 진행 제어")

db.py

@@ -429,6 +429,21 @@ def upsert_post_opinion(supabase: Client, room_name: str, student_name: str, pos
     )
 
 
+def fetch_all_opinion_changes(supabase: Client, room_name: str):
+    if not opinion_changes_available():
+        return pd.DataFrame()
+    res = execute_query(
+        supabase.table("opinion_changes")
+        .select("student_name, pre_opinion, post_opinion, ai_analysis")
+        .eq("room_name", room_name)
+        .order("student_name"),
+        fail_message="학생별 생각 변화 조회 실패",
+    )
+    if not res or not res.data:
+        return pd.DataFrame()
+    return pd.DataFrame(res.data)
+
+
 def save_opinion_analysis(supabase: Client, room_name: str, student_name: str, ai_analysis: str):
     if not opinion_changes_available():
         return None

utils.py

@@ -1,3 +1,4 @@
+import io
 import logging
 import re
 from datetime import datetime, timedelta, timezone
@@ -81,6 +82,160 @@ def to_bool_flag(value):
     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",
+]
+
+
+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 _strip_non_renderable(text: str) -> str:
+    """이미지 렌더링 시 깨질 수 있는 이모지/심볼 제거."""
+    result = []
+    for ch in (text or ""):
+        code = ord(ch)
+        if code > 0xFFFF or 0xD800 <= code <= 0xDFFF:
+            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,
+) -> 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_body  = _get_pil_font(17)
+    f_small = _get_pil_font(13)
+
+    LH_BODY    = 27   # body line height px
+    LH_LABEL   = 22
+    SEC_GAP    = 16
+    HEADER_H   = 74
+    FOOTER_H   = 38
+    DIV_H      = 20
+
+    # ── 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
+
+    total_h = (
+        HEADER_H + 18
+        + LH_LABEL + 14      # info line
+        + DIV_H
+        + section_h(pre_opinion)
+        + section_h(post_opinion)
+        + DIV_H
+        + section_h(ai_analysis)
+        + 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
+
+    divider()
+    section("토론 전 생각", pre_opinion or "(없음)")
+    section("토론 후 생각", post_opinion or "(없음)")
+    divider()
+    section("AI 배움 분석", ai_analysis or "(분석 없음)")
+
+    # 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("#")]