Update ui/ui_app.py

ui/ui_app.py

@@ -1,15 +1,20 @@
 # ui/ui_app.py
 from __future__ import annotations
 import json
-import shutil
 import gradio as gr
+import plotly.graph_objects as go
 
-from core.extract import parse_pdf  # (fin, df, meta, log) を返す
+from core.extract import parse_pdf  # (fin, df, meta, log)
+from core.external_scoring import (
+    get_external_template_df,
+    fill_missing_with_external,
+    score_external_from_df,
+)
+from core.ai_judgement import suggest_external_fields, make_ai_memo
 
-APP_TITLE = "📊 企業スコアリング／PDF解析（Vision対応・単位自動推定）"
+APP_TITLE = "📊 企業スコアリング／PDF解析（Vision・単位自動推定）＋ 外部評価 & AI評価"
 
-
-# --------- ユーティリティ（UI用） ---------
+# --------- UI補助 ---------
 def _fmt_num(v):
     if v is None or v == "":
         return "—"
@@ -17,7 +22,6 @@ def _fmt_num(v):
         x = float(v)
     except Exception:
         return str(v)
-    # 大きな数は3桁区切り
     return f"{x:,.0f}"
 
 def _get(dct, path, default=None):
@@ -29,54 +33,39 @@ def _get(dct, path, default=None):
     return cur
 
 def render_summary(fin: dict, meta: dict) -> str:
-    """JSONをそのまま出さず、要点だけのカードをHTMLで描画"""
     unit_label = meta.get("unit_label", "（不明）")
     company = _get(fin, ["company", "name"], "—")
     period = f"{_get(fin, ['period','start_date'],'—')} 〜 {_get(fin, ['period','end_date'],'—')}"
-
     bs = fin.get("balance_sheet", {}) or {}
     is_ = fin.get("income_statement", {}) or {}
     cf = fin.get("cash_flows", {}) or {}
 
     def row(label, key, src):
-        return f"""
-        <div class="row">
-          <div class="k">{label}</div>
-          <div class="v">{_fmt_num(src.get(key))}</div>
-        </div>"""
+        return f"<div class='row'><div class='k'>{label}</div><div class='v'>{_fmt_num(src.get(key))}</div></div>"
 
-    html = f"""
+    return f"""
     <style>
     .cards {{ display:grid; grid-template-columns: repeat(3, minmax(0,1fr)); gap:12px; }}
     @media (max-width: 1024px) {{ .cards {{ grid-template-columns: 1fr; }} }}
-    .card {{
-        background:#fff; border-radius:14px; box-shadow:0 4px 14px rgba(0,0,0,0.06);
-        padding:16px 16px 10px; border:1px solid #eee;
-    }}
-    .hd {{ font-weight:700; font-size:14px; margin-bottom:6px; color:#334; letter-spacing: .02em; }}
+    .card {{ background:#fff; border-radius:14px; box-shadow:0 4px 14px rgba(0,0,0,0.06);
+             padding:16px 16px 10px; border:1px solid #eee; }}
+    .hd {{ font-weight:700; font-size:14px; margin-bottom:6px; color:#334; }}
     .sub {{ color:#667; font-size:12px; margin-bottom:10px; }}
     .row {{ display:flex; justify-content:space-between; padding:6px 0; border-bottom:1px dashed #eef; }}
     .row:last-child {{ border-bottom:none; }}
-    .k {{ color:#566; }}
-    .v {{ font-weight:600; color:#111; }}
-    .meta {{
-        margin: 8px 0 14px; color:#556; font-size:12px; display:flex; gap:18px; flex-wrap:wrap;
-    }}
-    .badge {{
-        background:#f6f7fb; border:1px solid #e7e9f2; padding:4px 8px; border-radius:999px; font-size:12px;
-    }}
+    .k {{ color:#566; }} .v {{ font-weight:600; color:#111; }}
+    .meta {{ margin:8px 0 14px; color:#556; font-size:12px; display:flex; gap:18px; flex-wrap:wrap; }}
+    .badge {{ background:#f6f7fb; border:1px solid #e7e9f2; padding:4px 8px; border-radius:999px; font-size:12px; }}
     </style>
-
     <div class="meta">
       <span class="badge">会社名: {company}</span>
       <span class="badge">期間: {period}</span>
       <span class="badge">推定単位: {unit_label}</span>
     </div>
-
     <div class="cards">
       <div class="card">
         <div class="hd">貸借対照表（主項目）</div>
-        <div class="sub">主要残高を表示しています</div>
+        <div class="sub">主要残高</div>
         {row("総資産", "total_assets", bs)}
         {row("負債合計", "total_liabilities", bs)}
         {row("純資産", "total_equity", bs)}
@@ -85,10 +74,9 @@ def render_summary(fin: dict, meta: dict) -> str:
         {row("流動負債", "current_liabilities", bs)}
         {row("固定負債", "long_term_liabilities", bs)}
       </div>
-
       <div class="card">
         <div class="hd">損益計算書（主項目）</div>
-        <div class="sub">売上と利益の概況</div>
+        <div class="sub">売上と利益</div>
         {row("売上高", "sales", is_)}
         {row("売上原価", "cost_of_sales", is_)}
         {row("売上総利益", "gross_profit", is_)}
@@ -97,31 +85,43 @@ def render_summary(fin: dict, meta: dict) -> str:
         {row("経常利益", "ordinary_income", is_)}
         {row("当期純利益", "net_income", is_)}
       </div>
-
       <div class="card">
         <div class="hd">キャッシュフロー（主項目）</div>
-        <div class="sub">各CFの方向性</div>
+        <div class="sub">方向性</div>
         {row("営業CF", "operating_cash_flow", cf)}
         {row("投資CF", "investing_cash_flow", cf)}
         {row("財務CF", "financing_cash_flow", cf)}
       </div>
     </div>
     """
-    return html
 
+def _radar_from_category_scores(cat_scores: dict) -> go.Figure:
+    if not cat_scores:
+        return go.Figure()
+    labels = list(cat_scores.keys())
+    values = [cat_scores[k] for k in labels]
+    fig = go.Figure()
+    fig.add_trace(go.Scatterpolar(r=values + values[:1], theta=labels + labels[:1], fill="toself"))
+    fig.update_layout(
+        polar=dict(radialaxis=dict(visible=True, range=[0, 100])),
+        margin=dict(l=20, r=20, t=30, b=20),
+        showlegend=False,
+        height=380,
+        title="カテゴリ別スコア（外部・定量）",
+    )
+    return fig
 
-# --------- クリックハンドラ ---------
+# --------- ハンドラ ---------
 def on_analyze(company: str, use_vision: bool, files):
     try:
         fin, df, meta, log = parse_pdf(files, company=company or "", use_vision=use_vision)
-
         summary_html = render_summary(fin, meta)
         fin_json = json.dumps(fin, ensure_ascii=False, indent=2)
-
-        unit_label = f"推定単位: {meta.get('unit_label','—')}（スケール: ×{int(meta.get('unit_scale',1)):,}）"
+        unit_text = f"推定単位: {meta.get('unit_label','—')}（スケール: ×{int(meta.get('unit_scale',1)):,}）"
         debug = f"[OK] 解析完了\n--- log ---\n{log}"
-
-        return summary_html, df, fin_json, unit_label, debug
+        # 外部評価テンプレ初期化
+        df_ext = get_external_template_df()
+        return summary_html, df, fin_json, unit_text, debug, fin, df_ext
     except Exception as e:
         msg = f"解析に失敗しました: {e}"
         return (
@@ -130,27 +130,46 @@ def on_analyze(company: str, use_vision: bool, files):
             "{}",
             "推定単位: —",
             msg,
+            {},  # fin_state
+            get_external_template_df(),
         )
 
 def on_health():
-    msgs = []
-    try:
-        import gradio
-        msgs.append(f"Gradio: {gradio.__version__}")
-    except Exception as e:
-        msgs.append(f"Gradio: 取得失敗 ({e})")
-
     import os
     from shutil import which
+    msgs = []
     for b in ("pdftoppm", "pdftocairo"):
         ok = bool(which(b))
         msgs.append(("✅" if ok else "❌") + f" {b}: " + ("検出" if ok else "見つからず（packages.txt に poppler-utils が必要）"))
-    if os.environ.get("OPENAI_API_KEY"):
-        msgs.append("✅ OPENAI_API_KEY: 検出")
-    else:
-        msgs.append("❌ OPENAI_API_KEY: 未設定（Spaceの「Variables and secrets」に設定）")
+    msgs.append(("✅" if os.environ.get("OPENAI_API_KEY") else "❌") + " OPENAI_API_KEY")
     return "\n".join(msgs)
 
+def on_ext_fill(company: str, fin_state: dict, df_ext_in):
+    try:
+        sugg = suggest_external_fields(company, fin_state or {})
+        df_filled = fill_missing_with_external(df_ext_in, sugg)
+        return df_filled, json.dumps(sugg, ensure_ascii=False, indent=2)
+    except Exception as e:
+        return df_ext_in, f"LLM推定に失敗: {e}"
+
+def on_ext_score(df_ext_in):
+    try:
+        ext = score_external_from_df(df_ext_in)
+        chart = _radar_from_category_scores(ext.get("category_scores", {}))
+        total_md = f"**外部評価（定量）合計:** {ext['external_total']:.1f} / 100"
+        return json.dumps(ext, ensure_ascii=False, indent=2), chart, total_md
+    except Exception as e:
+        return f"外部評価に失敗: {e}", go.Figure(), "—"
+
+def on_ai_eval(company: str, fin_state: dict, df_ext_in):
+    try:
+        ext = score_external_from_df(df_ext_in)  # 最新入力で算出
+        ai = make_ai_memo(company, fin_state or {}, ext)
+        memo = ai.get("memo_md", "")
+        score = ai.get("ai_score", 50)
+        return memo, float(score)
+    except Exception as e:
+        return f"AI評価の生成に失敗: {e}", 50.0
 
 # --------- UI本体 ---------
 def build_ui() -> gr.Blocks:
@@ -160,8 +179,9 @@ def build_ui() -> gr.Blocks:
         fill_height=True,
         analytics_enabled=False,
     ) as demo:
-        gr.Markdown(f"## {APP_TITLE}\nPDFから主要財務項目を抽出し、**単位を自動推定**してスケーリングします。Vision失敗時はテキスト抽出にフォールバックします。")
+        gr.Markdown(f"## {APP_TITLE}\n- PDFから主要財務項目を抽出し、**単位自動推定**で円換算します。\n- 外部評価（定量）は**ルールベース**、AI評価は**別基準**で中立に要約・採点します。")
 
+        fin_state = gr.State({})
         with gr.Row():
             with gr.Column(scale=1):
                 company = gr.Textbox(label="企業名（任意）", placeholder="例：株式会社〇〇")
@@ -176,25 +196,70 @@ def build_ui() -> gr.Blocks:
                 health_btn = gr.Button("🩺 環境チェック")
 
                 unit_text = gr.Markdown("推定単位: —")
-
-                gr.Markdown("※ Vision / 画像化に失敗した場合はテキスト抽出へ自動切替します。Poppler（`poppler-utils`）必須。")
+                debug_out = gr.Textbox(label="ログ", lines=6, interactive=False, show_copy_button=True)
 
             with gr.Column(scale=2):
                 summary = gr.HTML(label="サマリー（カード表示）")
                 with gr.Tabs():
-                    with gr.Tab("表（編集可）"):
+                    with gr.Tab("抽出テーブル（編集可）"):
                         df_out = gr.Dataframe(headers=["category", "item", "value"], interactive=True, wrap=True)
                     with gr.Tab("抽出JSON"):
                         fin_json = gr.Code(label="抽出JSON", language="json")
 
-                debug_out = gr.Textbox(label="ログ", lines=8, interactive=False, show_copy_button=True)
+        # --- 外部評価 ---
+        gr.Markdown("### 外部評価（定量・ルールベース）")
+        with gr.Row():
+            with gr.Column(scale=2):
+                df_ext = gr.Dataframe(
+                    label="外部入力テンプレ（不足は空欄でOK）",
+                    value=get_external_template_df(),
+                    interactive=True,
+                    wrap=True,
+                    headers=["カテゴリー", "入力項目", "値"],
+                )
+            with gr.Column(scale=1):
+                fill_btn = gr.Button("✨ LLMで不足項目を推定して下書き")
+                fill_json = gr.Code(label="推定値（JSON）", language="json")
+                score_btn = gr.Button("🧮 外部評価を計算", variant="primary")
+                total_md = gr.Markdown("—")
+        with gr.Row():
+            ext_json = gr.Code(label="外部評価の結果（JSON）", language="json")
+            ext_chart = gr.Plot(label="カテゴリ別レーダー")
 
+        # --- AI評価 ---
+        gr.Markdown("### AI評価（中立メモ＋別基準スコア）")
+        with gr.Row():
+            ai_btn = gr.Button("🤖 AI評価を生成")
+        with gr.Row():
+            ai_memo = gr.Markdown()
+            ai_score = gr.Number(label="AIスコア(0-100)", precision=1, interactive=False)
+
+        # --- ワイヤリング ---
         run_btn.click(
             on_analyze,
             inputs=[company, use_vision, files],
-            outputs=[summary, df_out, fin_json, unit_text, debug_out],
+            outputs=[summary, df_out, fin_json, unit_text, debug_out, fin_state, df_ext],
             concurrency_limit=1,
         )
         health_btn.click(on_health, outputs=debug_out, concurrency_limit=1)
 
+        fill_btn.click(
+            on_ext_fill,
+            inputs=[company, fin_state, df_ext],
+            outputs=[df_ext, fill_json],
+            concurrency_limit=1,
+        )
+        score_btn.click(
+            on_ext_score,
+            inputs=[df_ext],
+            outputs=[ext_json, ext_chart, total_md],
+            concurrency_limit=1,
+        )
+        ai_btn.click(
+            on_ai_eval,
+            inputs=[company, fin_state, df_ext],
+            outputs=[ai_memo, ai_score],
+            concurrency_limit=1,
+        )
+
     return demo