Add visualization recommender, UI controls and chart-job fallback

bitnet_tools/ui/app.js

@@ -5,6 +5,8 @@ const UI = {
   refreshSheetsBtn: document.getElementById('refreshSheetsBtn'),
   csvText: document.getElementById('csvText'),
   question: document.getElementById('question'),
+  showVizOptionsBtn: document.getElementById('showVizOptionsBtn'),
+  vizRecommendation: document.getElementById('vizRecommendation'),
   intent: document.getElementById('intent'),
   intentActions: document.getElementById('intentActions'),
   model: document.getElementById('model'),
@@ -85,6 +87,7 @@ const appState = {
   uploadedFile: null,
   detectedInputType: 'csv',
   candidateTables: [],
+  vizRecommendation: null,
 };
 
 const CONFIDENCE_THRESHOLD_DEFAULT = 0.7;
@@ -676,6 +679,32 @@ function setPreprocessStatusText(text) {
   if (UI.preprocessStatus) UI.preprocessStatus.textContent = text;
 }
 
+function renderVizRecommendation(rec) {
+  appState.vizRecommendation = rec || null;
+  if (!UI.vizRecommendation) return;
+  if (!rec) {
+    UI.vizRecommendation.textContent = '추천 시각화 옵션이 여기에 표시됩니다.';
+    return;
+  }
+  const charts = Array.isArray(rec.recommended_chart_types) ? rec.recommended_chart_types.join(', ') : '-';
+  UI.vizRecommendation.textContent = `의도: ${rec.intent || '-'}\n추천 차트: ${charts}\n추천 사유: ${rec.reason || '-'}`;
+}
+
+async function fetchVizRecommendation() {
+  clearError();
+  const question = (UI.question?.value || '').trim();
+  try {
+    const rec = await postJson('/api/viz/recommend', { question }, '시각화 추천');
+    renderVizRecommendation(rec);
+    setStatus('시각화 추천을 확인했습니다.');
+    return rec;
+  } catch (err) {
+    showError(err.userMessage || '시각화 추천 실패', err.detail || '');
+    setStatus('시각화 추천 실패');
+    return null;
+  }
+}
+
 function stopPreprocessPolling() {
   if (appState.preprocessJob.pollTimer) {
     clearInterval(appState.preprocessJob.pollTimer);
@@ -771,7 +800,13 @@ async function pollChartJobOnce() {
     if (result.status === 'done') {
       stopChartPolling();
       UI.retryChartsJobBtn.disabled = true;
-      setStatus('차트 작업 완료');
+      if (result.fallback) {
+        const fallbackText = JSON.stringify(result.fallback, null, 2);
+        setChartsJobStatusText(`job=${result.job_id} status=done (fallback)\nreason=${result.fallback_reason || 'chart_generation_failed'}\n${fallbackText}`);
+        setStatus('차트 생성 실패로 표/요약 fallback을 제공합니다.');
+      } else {
+        setStatus('차트 작업 완료');
+      }
     } else if (result.status === 'failed') {
       stopChartPolling();
       UI.retryChartsJobBtn.disabled = false;
@@ -812,7 +847,9 @@ async function startChartsJob() {
     const payloadFiles = await buildMultiPayloadFiles(files);
     appState.chartJob.files = payloadFiles;
 
-    const queued = await postJson('/api/charts/jobs', { files: payloadFiles }, '차트 작업 생성');
+    const rec = appState.vizRecommendation || await fetchVizRecommendation();
+    const selectedChartTypes = Array.isArray(rec?.recommended_chart_types) ? rec.recommended_chart_types : [];
+    const queued = await postJson('/api/charts/jobs', { files: payloadFiles, question: UI.question?.value || '', selected_chart_types: selectedChartTypes }, '차트 작업 생성');
     appState.chartJob.id = queued.job_id;
     appState.chartJob.status = queued.status;
     UI.retryChartsJobBtn.disabled = true;
@@ -836,7 +873,10 @@ async function retryChartsJob() {
   clearError();
   toggleBusy(true);
   try {
-    const queued = await postJson('/api/charts/jobs', { files: appState.chartJob.files }, '차트 작업 재시도');
+    const selectedChartTypes = Array.isArray(appState.vizRecommendation?.recommended_chart_types)
+      ? appState.vizRecommendation.recommended_chart_types
+      : [];
+    const queued = await postJson('/api/charts/jobs', { files: appState.chartJob.files, question: UI.question?.value || '', selected_chart_types: selectedChartTypes }, '차트 작업 재시도');
     appState.chartJob.id = queued.job_id;
     appState.chartJob.status = queued.status;
     UI.retryChartsJobBtn.disabled = true;
@@ -1120,6 +1160,7 @@ function bindEvents() {
 
   UI.analyzeBtn?.addEventListener('click', runByIntent);
   UI.quickAnalyzeBtn?.addEventListener('click', runByIntent);
+  UI.showVizOptionsBtn?.addEventListener('click', fetchVizRecommendation);
   UI.runBtn?.addEventListener('click', runModel);
   UI.multiAnalyzeBtn?.addEventListener('click', runMultiAnalyze);
   UI.startChartsJobBtn?.addEventListener('click', startChartsJob);
@@ -1195,6 +1236,7 @@ function init() {
   if (UI.retryPreprocessBtn) UI.retryPreprocessBtn.disabled = true;
   setChartsJobStatusText('차트 작업 대기 중');
   setPreprocessStatusText('입력 전처리 대기 중');
+  renderVizRecommendation(null);
 }
 
 init();

bitnet_tools/ui/index.html

@@ -49,6 +49,10 @@ <h2>2) 입력</h2>
           <button class="chip" data-q="실행 가능한 다음 액션 5개를 우선순위로 제안해줘">다음행동</button>
         </div>
         <textarea id="question" rows="3">핵심 인사이트 3개와 근거를 알려줘</textarea>
+        <div class="actions">
+          <button id="showVizOptionsBtn" type="button">시각화 옵션 보기</button>
+        </div>
+        <pre id="vizRecommendation" aria-live="polite">추천 시각화 옵션이 여기에 표시됩니다.</pre>
 
         <label>작업 요청(intent)</label>
         <textarea id="intent" rows="2" placeholder="예: 파일 먼저 분석하고 이상치만 보여줘"></textarea>

bitnet_tools/visualize.py

@@ -7,6 +7,9 @@
 from typing import Any
 
 
+SUPPORTED_CHART_TYPES = {"histogram", "boxplot", "missing", "bar", "scatter", "line"}
+
+
 SAMPLE_CAP = 20000
 TOP_K = 10
 
@@ -103,6 +106,7 @@ def create_file_charts(
     out_dir: Path,
     max_numeric: int = 3,
     max_categorical: int = 2,
+    selected_chart_types: list[str] | None = None,
 ) -> list[str]:
     plt = _ensure_matplotlib()
 
@@ -116,36 +120,41 @@ def create_file_charts(
 
     artifacts: list[str] = []
     stem = _safe_stem(csv_path)
+    selected = {c.strip().lower() for c in (selected_chart_types or []) if c}
+    if not selected:
+        selected = set(SUPPORTED_CHART_TYPES)
 
     for col in numeric_cols:
         values: list[float] = profiles[col]["values"]
         missing = profiles[col]["missing"]
         if not values:
             continue
 
-        fig = plt.figure(figsize=(7, 4))
-        plt.hist(values, bins=20)
-        plt.title(f"{stem} - {col} histogram(sample)")
-        plt.xlabel(col)
-        plt.ylabel("count")
-        plt.tight_layout()
-        out = out_dir / f"{stem}_{col}_hist.png"
-        fig.savefig(out)
-        plt.close(fig)
-        artifacts.append(str(out))
-
-        fig = plt.figure(figsize=(5, 4))
-        plt.boxplot(values, vert=True)
-        plt.title(f"{stem} - {col} boxplot(sample)")
-        plt.ylabel(col)
-        plt.tight_layout()
-        out = out_dir / f"{stem}_{col}_box.png"
-        fig.savefig(out)
-        plt.close(fig)
-        artifacts.append(str(out))
+        if "histogram" in selected:
+            fig = plt.figure(figsize=(7, 4))
+            plt.hist(values, bins=20)
+            plt.title(f"{stem} - {col} histogram(sample)")
+            plt.xlabel(col)
+            plt.ylabel("count")
+            plt.tight_layout()
+            out = out_dir / f"{stem}_{col}_hist.png"
+            fig.savefig(out)
+            plt.close(fig)
+            artifacts.append(str(out))
+
+        if "boxplot" in selected:
+            fig = plt.figure(figsize=(5, 4))
+            plt.boxplot(values, vert=True)
+            plt.title(f"{stem} - {col} boxplot(sample)")
+            plt.ylabel(col)
+            plt.tight_layout()
+            out = out_dir / f"{stem}_{col}_box.png"
+            fig.savefig(out)
+            plt.close(fig)
+            artifacts.append(str(out))
 
         total = profiles[col]["seen"] + missing
-        if total > 0:
+        if total > 0 and "missing" in selected:
             fig = plt.figure(figsize=(5, 3))
             plt.bar(["non_missing", "missing"], [profiles[col]["seen"], missing])
             plt.title(f"{stem} - {col} missing overview")
@@ -162,17 +171,18 @@ def create_file_charts(
 
         labels = [x[0] for x in items]
         counts = [x[1] for x in items]
-        fig = plt.figure(figsize=(8, 4))
-        plt.bar(range(len(labels)), counts)
-        plt.xticks(range(len(labels)), labels, rotation=30, ha="right")
-        plt.title(f"{stem} - {col} top values")
-        plt.tight_layout()
-        out = out_dir / f"{stem}_{col}_top.png"
-        fig.savefig(out)
-        plt.close(fig)
-        artifacts.append(str(out))
-
-    if len(numeric_cols) >= 2:
+        if "bar" in selected:
+            fig = plt.figure(figsize=(8, 4))
+            plt.bar(range(len(labels)), counts)
+            plt.xticks(range(len(labels)), labels, rotation=30, ha="right")
+            plt.title(f"{stem} - {col} top values")
+            plt.tight_layout()
+            out = out_dir / f"{stem}_{col}_top.png"
+            fig.savefig(out)
+            plt.close(fig)
+            artifacts.append(str(out))
+
+    if len(numeric_cols) >= 2 and ("scatter" in selected or "line" in selected):
         x_col, y_col = numeric_cols[0], numeric_cols[1]
         xs: list[float] = []
         ys: list[float] = []
@@ -192,7 +202,7 @@ def create_file_charts(
                     seen += 1
                     _reservoir_pair(xs, ys, x, y, seen, SAMPLE_CAP)
 
-        if xs and ys:
+        if xs and ys and "scatter" in selected:
             fig = plt.figure(figsize=(6, 5))
             plt.scatter(xs, ys, alpha=0.6, s=12)
             plt.title(f"{stem} - {x_col} vs {y_col} scatter(sample)")
@@ -204,11 +214,28 @@ def create_file_charts(
             plt.close(fig)
             artifacts.append(str(out))
 
+        if xs and ys and "line" in selected:
+            pairs = sorted(zip(xs, ys), key=lambda pair: pair[0])
+            fig = plt.figure(figsize=(6, 4))
+            plt.plot([p[0] for p in pairs], [p[1] for p in pairs], linewidth=1.3)
+            plt.title(f"{stem} - {x_col} vs {y_col} line(sample)")
+            plt.xlabel(x_col)
+            plt.ylabel(y_col)
+            plt.tight_layout()
+            out = out_dir / f"{stem}_{x_col}_{y_col}_line.png"
+            fig.savefig(out)
+            plt.close(fig)
+            artifacts.append(str(out))
+
     return artifacts
 
 
-def create_multi_charts(csv_paths: list[Path], out_dir: Path) -> dict[str, Any]:
+def create_multi_charts(
+    csv_paths: list[Path],
+    out_dir: Path,
+    selected_chart_types: list[str] | None = None,
+) -> dict[str, Any]:
     results: dict[str, Any] = {}
     for p in csv_paths:
-        results[str(p)] = create_file_charts(p, out_dir)
+        results[str(p)] = create_file_charts(p, out_dir, selected_chart_types=selected_chart_types)
     return results

bitnet_tools/viz_recommender.py

@@ -0,0 +1,74 @@
+from __future__ import annotations
+
+from dataclasses import dataclass
+
+
+@dataclass(frozen=True)
+class VizRecommendation:
+    intent: str
+    chart_types: list[str]
+    reason: str
+
+
+_INTENT_RULES: list[tuple[tuple[str, ...], VizRecommendation]] = [
+    (
+        ("추이", "트렌드", "변화", "시계열", "trend", "over time"),
+        VizRecommendation(
+            intent="trend",
+            chart_types=["line", "scatter"],
+            reason="시간/순서 기반 변화 파악에는 선형 추세와 분포 확인이 유리합니다.",
+        ),
+    ),
+    (
+        ("비교", "랭킹", "상위", "하위", "compare", "ranking"),
+        VizRecommendation(
+            intent="comparison",
+            chart_types=["bar", "boxplot"],
+            reason="그룹 간 크기 비교에는 막대, 분산 비교에는 박스플롯이 적합합니다.",
+        ),
+    ),
+    (
+        ("관계", "상관", "영향", "relationship", "correlation"),
+        VizRecommendation(
+            intent="relationship",
+            chart_types=["scatter", "histogram"],
+            reason="변수 간 관계는 산점도로, 단일 변수 분포는 히스토그램으로 확인합니다.",
+        ),
+    ),
+    (
+        ("비율", "구성", "점유", "composition", "ratio"),
+        VizRecommendation(
+            intent="composition",
+            chart_types=["bar"],
+            reason="구성 비교는 범주형 막대 차트로 읽기 쉽고 왜곡이 적습니다.",
+        ),
+    ),
+    (
+        ("결측", "누락", "품질", "이상치", "missing", "quality", "outlier"),
+        VizRecommendation(
+            intent="quality",
+            chart_types=["missing", "boxplot"],
+            reason="데이터 품질 확인에는 결측 막대와 이상치 확인용 박스플롯이 효과적입니다.",
+        ),
+    ),
+]
+
+_DEFAULT = VizRecommendation(
+    intent="overview",
+    chart_types=["histogram", "bar", "scatter"],
+    reason="일반 탐색 질문으로 판단되어 분포/범주/관계를 함께 확인하는 구성을 추천합니다.",
+)
+
+
+def recommend_chart_types(question: str) -> dict[str, object]:
+    text = (question or "").strip().lower()
+    if not text:
+        rec = _DEFAULT
+    else:
+        rec = next((rule for keywords, rule in _INTENT_RULES if any(k in text for k in keywords)), _DEFAULT)
+
+    return {
+        "intent": rec.intent,
+        "recommended_chart_types": rec.chart_types,
+        "reason": rec.reason,
+    }