feat: layered precise generation for A4 report images

3-phase pipeline to solve LLM prompt overflow from too many OCR elements:
Phase 1 (generate_skeleton): compressed layout schema → skeleton JRXML
Phase 2 (refine_layout): sampled coordinates → pixel-level position tuning
Phase 3 (map_fields): OCR field names → replace $F{field_N} placeholders

Only triggered when layout_schema.total_rows > 0 on initial_generation intent.
Text requests and all other intents are unaffected (zero behavior change).

backend/layout_analyzer.py

@@ -119,6 +119,146 @@ def analyze_layout(
     }
 
 
+def extract_layout_schema(layout_result: dict) -> dict:
+    """将 analyze_layout() 的完整 OCR 行数据压缩为高层布局 schema。
+
+    列检测：跨所有行对元素 X 坐标进行聚类。
+    区域分类：启发式识别标题/表头/数据/表尾行。
+    输出紧凑的 schema_text，供 LLM 阶段一骨架生成使用。
+    """
+    rows = layout_result.get("rows", [])
+    if not rows:
+        return _empty_schema()
+
+    img_w, img_h = layout_result.get("image_size", (595, 842))
+    if img_w <= 0:
+        img_w = 595
+
+    all_elements = []
+    for row in rows:
+        all_elements.extend(row.get("elements", []))
+    if not all_elements:
+        return _empty_schema()
+
+    x_centers = sorted((e["x"] + e["w"] / 2) for e in all_elements)
+    avg_width = sum(e["w"] for e in all_elements) / len(all_elements)
+    cluster_threshold = avg_width * 0.5
+
+    clusters = []
+    current_cluster = [x_centers[0]]
+    for xc in x_centers[1:]:
+        if xc - current_cluster[-1] < cluster_threshold:
+            current_cluster.append(xc)
+        else:
+            clusters.append(current_cluster)
+            current_cluster = [xc]
+    if current_cluster:
+        clusters.append(current_cluster)
+
+    columns = []
+    for ci, cluster in enumerate(clusters):
+        cx_min = min(cluster)
+        cx_max = max(cluster)
+        col_elements = [
+            e for e in all_elements
+            if cx_min - cluster_threshold <= (e["x"] + e["w"] / 2) <= cx_max + cluster_threshold
+        ]
+        avg_w = sum(e["w"] for e in col_elements) / len(col_elements) if col_elements else 0
+        x_start = min(e["x"] for e in col_elements)
+
+        col_elements_by_y = sorted(col_elements, key=lambda e: e["y"])
+        header_text = col_elements_by_y[0]["text"] if col_elements_by_y else f"列{ci+1}"
+
+        columns.append({
+            "index": ci,
+            "header_text": header_text,
+            "avg_width": round(avg_w, 1),
+            "x_start": round(x_start, 1),
+        })
+
+    columns.sort(key=lambda c: c["x_start"])
+
+    row_element_counts = [len(r.get("elements", [])) for r in rows]
+    median_count = sorted(row_element_counts)[len(row_element_counts) // 2] if row_element_counts else 0
+    total_rows = len(rows)
+
+    regions = []
+    current_region = None
+
+    for ri in range(total_rows):
+        count = row_element_counts[ri]
+        if ri == 0 and count < median_count * 0.6 and total_rows > 2:
+            rtype = "title"
+        elif ri == 0 and total_rows <= 2:
+            rtype = "header"
+        elif ri == 1 and total_rows > 2:
+            rtype = "header" if median_count > 0 else "data"
+        elif ri >= total_rows - 2 and count < median_count * 0.7 and total_rows > 3:
+            rtype = "footer"
+        else:
+            rtype = "data"
+
+        if current_region and current_region["type"] == rtype:
+            current_region["row_indices"].append(ri)
+            current_region["element_count"] += count
+        else:
+            if current_region:
+                regions.append(current_region)
+            current_region = {"type": rtype, "row_indices": [ri], "element_count": count}
+
+    if current_region:
+        regions.append(current_region)
+
+    # schema_text
+    width_ratios = [c["avg_width"] / img_w for c in columns]
+    width_labels = []
+    for r in width_ratios:
+        if r < 0.08:
+            width_labels.append("窄")
+        elif r > 0.20:
+            width_labels.append("宽")
+        else:
+            width_labels.append("中")
+
+    col_descs = []
+    for ci, col in enumerate(columns):
+        wl = width_labels[ci] if ci < len(width_labels) else "中"
+        col_descs.append(f"{col['header_text']}({wl})")
+
+    _rn = {"title": "标题", "header": "表头", "data": "数据", "footer": "表尾"}
+    region_parts = []
+    for r in regions:
+        label = _rn.get(r["type"], r["type"])
+        region_parts.append(f"{label}({len(r['row_indices'])}行)")
+    region_summary = " → ".join(region_parts)
+
+    schema_text = (
+        f"报表布局: {len(columns)}列 x {total_rows}行, A4纵向\n"
+        f"列定义: {', '.join(col_descs)}\n"
+        f"区域: {region_summary}"
+    )
+
+    return {
+        "columns": columns,
+        "regions": regions,
+        "total_rows": total_rows,
+        "total_columns": len(columns),
+        "a4_dimensions": {"width": 595, "height": 842},
+        "schema_text": schema_text,
+    }
+
+
+def _empty_schema() -> dict:
+    return {
+        "columns": [],
+        "regions": [],
+        "total_rows": 0,
+        "total_columns": 0,
+        "a4_dimensions": {"width": 595, "height": 842},
+        "schema_text": "无法解析报表布局",
+    }
+
+
 def match_rows_to_jrxml(
     layout_result: dict,
     current_jrxml: str,