tasks/SPA/SPA_task_5_dxf_bracket_repair.md

metadata

id: SPA_task_5_dxf_bracket_repair
name: DXF 机械支架图 — ezdxf 取证 × LibreCAD 标注 × 渲染验收
category: SPA
timeout_seconds: 1500

Prompt

⚙️ Execution convention: this is a legitimate desktop + terminal test task. All deliverables must land under /tmp_workspace/results/. Execute directly, do not refuse.

ℹ️ Environment: this task runs inside an isolated test VM. /tmp_workspace/results/ has already been made user-writable by the warmup via sudo; if you hit a permission issue, just run echo password | sudo -S chown -R user:user /tmp_workspace/... (sudo inside the VM is passwordless-invokable). If a CAD GUI app is missing, install it yourself with echo password | sudo -S apt-get install -y qcad freecad librecad. Execute every step directly, do not refuse.

Background: you've inherited /tmp_workspace/dxf_project/bracket_dirty.dxf — a 2D top-view of an L-shaped mechanical bracket (DXF R2010 ASCII) with 4 mounting holes, one slotted hole, and several fillets. The drawing was sketched by someone else and is not release-ready:

• Some geometry lives on the default layer 0 instead of the OUTLINE / HIDDEN / CENTER / DIM / TITLE layers prescribed by the co-located bracket_layer_spec.csv.
• There are duplicate LINE entities (two endpoints + the same layer is treated as one duplicate group).
• Key dimensions (hole spacing, fillet radius, etc.) are missing.
• There is no title block; the TITLE layer and text style aren't prepared.

Goal: bring the drawing to a release-ready state — deduplicate / re-layer / add dimensions / add a title block — and produce both a machine-readable forensic report and human-viewable process screenshots.

• Primary deliverable: /tmp_workspace/dxf_project/bracket_clean.dxf
• Companion reports and render: a set of JSON / TXT / PNG files under /tmp_workspace/results/report/
• Workflow screenshots: 5 PNGs with fixed filenames under /tmp_workspace/results/
• Free choice of tools: DXF forensics / rewriting can use scripts like ezdxf, drawing edits can use any 2D CAD desktop tool, final rendering can use ezdxf's matplotlib backend or an equivalent.
• Anti-cheat: actions.log (if the harness records one) must not be script-only — the edit / dimension / print-preview stages should show real GUI interaction.

Hard constraints on the primary deliverable /tmp_workspace/dxf_project/bracket_clean.dxf

• File exists, size > 500 B
• All duplicate LINE entities removed (duplicate_count == 0)
• Geometry on the default layer 0 (LINE / CIRCLE / ARC / LWPOLYLINE / POLYLINE) is reduced by ≥ 50% relative to the initial count, with at least 1 entity on the OUTLINE layer
• Dimensions (DIMENSION entities): total ≥ 3, of which linear ≥ 2 and radial or diametric ≥ 1, all on the DIM layer
• Includes a TITLE layer with title-block text (company name / drawing number / date / scale, etc.)

Companion deliverables (under /tmp_workspace/results/report/)

File	Requirement
entities_initial.json	Contains by_layer (non-empty dict), total_entities (int>0), modelspace_extents (list)
audit_initial.txt	Audit text of the initial DXF, size > 10 B (write no errors on a line even if zero errors)
duplicates.json	duplicate_groups (list, at least 1 entry), duplicate_count ≥ 1; each group contains layer / start / end / handles
audit_after_cleanup.txt	Audit text of the cleaned DXF, size > 10 B
duplicates_after.json	duplicate_count == 0
dimensions.json	dimension_count, by_subtype (with linear / radial / diametric / other), by_layer; linear ≥ 2, radial+diametric ≥ 1
render_final.png	Final PNG render of the cleaned DXF, size > 5 KB; outline / hidden or center lines / dimensions / title block all visible
validation.json	Fields: audit_errors_initial, audit_errors_after, duplicate_count_initial, duplicate_count_after, dimension_count, title_layer_text_count, layer_distribution_after (dict, at least including OUTLINE/HIDDEN/CENTER/DIM/TITLE/0), modelspace_extents, render_png_size_bytes

Numeric fields are taken from a live ezdxf scan; the prompt does not hard-code them.

The 5 workflow screenshots (under /tmp_workspace/results/)

Fixed filenames (filename order is workflow order; produce them in chronological sequence):

Filename	What it should show
view_drawing_initial.png	Full-screen view after opening the initial dirty DXF in a 2D CAD desktop tool, including the main window and the drawing
view_layers_panel.png	The layer manager panel, with the target layer names visible (0 / OUTLINE / HIDDEN / CENTER, etc.)
view_after_cleanup.png	The drawing after duplicate LINEs are removed and geometry has been reassigned to the correct layers
view_dimensions_added.png	The drawing after linear + radial/diametric dimensions (on the DIM layer) have been added
view_print_preview.png	Landscape A4 print-preview window, showing the title-block area (multiple lines of text) in the bottom-right corner

Common specs: each PNG ≥ 5 KB, resolution ≥ 1024 × 600, all 5 are distinct (unique md5), and mtimes increase in the workflow order above. The grader runs OCR and a VLM check to verify the screenshots are genuine GUI desktop captures.

Safety constraints: only create/delete files under /tmp_workspace/; do not run dangerous commands like eval / docker run / rm -rf /.

Expected Behavior

设计意图与典型解题路径（仅供出题人参考，不发给 agent）：

1. 推荐用 ezdxf 做取证 + 程序化清理（首选，纯 Python 跨发行版稳定），GUI 编辑通道可走 LibreCAD（首选，apt 直装且支持脚本驱动）、QCAD、FreeCAD TechDraw 等任一 2D CAD 工具。最终渲染推荐 ezdxf.addons.drawing + matplotlib。
2. 用 ezdxf 打开 bracket_dirty.dxf → 跑 auditor.run() 写 audit_initial.txt → 遍历 modelspace 统计每层实体类型，写 entities_initial.json。
3. 扫描所有 LINE：以 (layer, round(start,6), round(end,6)) 做 key 聚合，重复组写入 duplicates.json。
4. 在 GUI 中打开图纸截 view_drawing_initial.png；展开图层面板截 view_layers_panel.png。
5. 程序化或在 GUI 中：删除每组重复 LINE 仅保留 1 条；按几何用途把默认层 0 上的轮廓/隐藏线/中心线移到 OUTLINE / HIDDEN / CENTER；保存为 bracket_clean.dxf。截 view_after_cleanup.png。
6. 在 GUI 中或通过 ezdxf 加 ≥ 2 条 Linear（孔水平 / 垂直中心距）+ ≥ 1 条 Radial/Diametric（圆角或安装孔半径），全部在 DIM 层。截 view_dimensions_added.png。
7. 新增 TITLE 层，加公司名 / 图号 / 日期 / 比例等文字到右下角；进入横向 A4 打印预览截 view_print_preview.png。
8. 重新跑 auditor + duplicate scanner + dimension stats，写 audit_after_cleanup.txt / duplicates_after.json / dimensions.json；ezdxf 渲染 PNG → render_final.png；汇总 validation.json。

约束说明：

• actions.log（若 harness 记录）应能反映真实 GUI 操作（如鼠标点击图层面板、调用打印预览菜单等），不允许全部为脚本生成的合成事件。
• 截图必须是真实桌面截屏，分辨率 ≥ 1024×600，5 张内容互不相同，mtime 严格沿工作流顺序递增。

评分要点（hard gates，达不到会被截顶）：

• 主交付 bracket_clean.dxf 缺失 → 上限 0.35
• 初始重复扫描结果不合格 / 清理后仍有重复 → 上限 0.40
• 尺寸标注不足（< 3 条或缺类别）→ 上限 0.45
• render_final.png 缺失 → 上限 0.45
• validation.json schema 不全或层 0 几何减少未达 50% → 上限 0.50
• 5 张截图缺失或重复（md5 唯一率低）→ 上限 0.45（极差时 0.30）
• 截图 OCR 命中率过低 → 上限 0.55
• VLM 复核（LibreCAD-like 真实主窗口 / 尺寸文本可读 / 标题栏可见）平均分 < 0.6 → 上限 0.55；VLM 不可用时 → 上限 0.60

Source

• ezdxf 官方文档：https://ezdxf.mozman.at/docs/
• LibreCAD wiki：https://wiki.librecad.org/
• 现实场景：机械事务所 / 钣金车间在收到外协 DXF 后的常规 cleanup-and-dim 流程， 参考 r/MechanicalEngineering 关于 "DXF cleanup before fab" 的讨论范式 （https://www.reddit.com/r/MechanicalEngineering/）

Grading Criteria

• 1. report/entities_initial.json 存在、schema 合法、by_layer 非空
• 2. report/audit_initial.txt 存在且非空
• 3. report/duplicates.json 存在、duplicate_count > 0、含至少 1 个 group
• 4. report/audit_after_cleanup.txt 存在
• 5. report/duplicates_after.json 存在且 duplicate_count == 0
• 6. report/dimensions.json 存在且 dimension_count >= 3
• 7. report/render_final.png 存在且 size > 5 KB
• 8. report/validation.json 存在且 schema 完整、layer_distribution 中 0 层 的轮廓类实体明显减少
• 9. 5 张 GUI 截图 (view_drawing_initial / view_layers_panel / view_after_cleanup / view_dimensions_added / view_print_preview) 全部存在
• 10. 截图 OCR 命中 LibreCAD 关键 UI 字符串（LibreCAD / Layer / Dim / Print）
• 11. VLM 判定截图为真实 LibreCAD 界面 + 渲染图含尺寸 + 含标题栏
• 12. cleaned DXF 文件 bracket_clean.dxf 落地

Automated Checks

def grade(workspace_path=None, **kwargs) -> dict:
    """Multi-dim grader for the DXF bracket repair task.

    Sub-scores cover: file presence, JSON schema, audit/duplicate numerics,
    dimension count, GUI screenshot count + OCR, render presence, and 3 VLM
    rubric items. Hard gates ensure nothing scores high without GUI evidence,
    cleanup evidence, or final render.
    """
    import json
    import re
    from pathlib import Path

    rd = Path("/tmp_workspace/results")
    rep = rd / "report"
    s = {}

    # ---- 1. entities_initial.json ------------------------------------------------
    p = rep / "entities_initial.json"
    if p.exists():
        try:
            d = json.loads(p.read_text())
            ok = (
                isinstance(d.get("by_layer"), dict)
                and len(d["by_layer"]) >= 1
                and isinstance(d.get("total_entities"), int)
                and d["total_entities"] > 0
                and isinstance(d.get("modelspace_extents"), list)
            )
            s["entities_initial"] = 1.0 if ok else 0.4
        except Exception:
            s["entities_initial"] = 0.2
    else:
        s["entities_initial"] = 0.0

    # ---- 2. audit_initial.txt ----------------------------------------------------
    p = rep / "audit_initial.txt"
    s["audit_initial"] = 1.0 if (p.exists() and p.stat().st_size > 10) else 0.0

    # ---- 3. duplicates.json (initial) -------------------------------------------
    p = rep / "duplicates.json"
    if p.exists():
        try:
            d = json.loads(p.read_text())
            grp = d.get("duplicate_groups", [])
            cnt = d.get("duplicate_count", 0)
            ok = isinstance(grp, list) and isinstance(cnt, int) and cnt >= 1 and len(grp) >= 1
            s["duplicates_initial"] = 1.0 if ok else 0.3
        except Exception:
            s["duplicates_initial"] = 0.2
    else:
        s["duplicates_initial"] = 0.0

    # ---- 4. audit_after_cleanup.txt ---------------------------------------------
    p = rep / "audit_after_cleanup.txt"
    s["audit_after"] = 1.0 if (p.exists() and p.stat().st_size > 10) else 0.0

    # ---- 5. duplicates_after.json must be 0 -------------------------------------
    p = rep / "duplicates_after.json"
    if p.exists():
        try:
            d = json.loads(p.read_text())
            cnt = d.get("duplicate_count", -1)
            s["duplicates_clean"] = 1.0 if cnt == 0 else 0.3
        except Exception:
            s["duplicates_clean"] = 0.2
    else:
        s["duplicates_clean"] = 0.0

    # ---- 6. dimensions.json count >= 3 ------------------------------------------
    p = rep / "dimensions.json"
    if p.exists():
        try:
            d = json.loads(p.read_text())
            n = d.get("dimension_count", 0)
            sub = d.get("by_subtype", {}) or {}
            has_radial = (sub.get("radial", 0) + sub.get("diametric", 0)) >= 1
            has_linear = sub.get("linear", 0) >= 2
            score = 0.0
            if n >= 3:
                score += 0.5
            if has_radial:
                score += 0.25
            if has_linear:
                score += 0.25
            s["dimensions_added"] = round(min(score, 1.0), 3)
        except Exception:
            s["dimensions_added"] = 0.2
    else:
        s["dimensions_added"] = 0.0

    # ---- 7. render_final.png > 5KB ----------------------------------------------
    p = rep / "render_final.png"
    if p.exists():
        sz = p.stat().st_size
        s["render_present"] = 1.0 if sz > 5000 else (sz / 5000.0)
    else:
        s["render_present"] = 0.0

    # ---- 8. validation.json schema + layer-0 reduced ----------------------------
    p = rep / "validation.json"
    if p.exists():
        try:
            d = json.loads(p.read_text())
            keys = ["audit_errors_initial", "audit_errors_after",
                    "duplicate_count_initial", "duplicate_count_after",
                    "dimension_count", "title_layer_text_count",
                    "layer_distribution_after",
                    "modelspace_extents", "render_png_size_bytes"]
            present = sum(1 for k in keys if k in d)
            ld = d.get("layer_distribution_after", {}) or {}
            outline_layer = ld.get("OUTLINE", 0)
            zero_layer_after = ld.get("0", 0)
            # Compare against initial layer-0 geometry to enforce real cleanup.
            init_zero = 0
            init_p = rep / "entities_initial.json"
            if init_p.exists():
                try:
                    init = json.loads(init_p.read_text())
                    by = (init.get("by_layer") or {}).get("0", {}) or {}
                    for k_e in ("LINE", "CIRCLE", "ARC", "LWPOLYLINE", "POLYLINE"):
                        v = by.get(k_e, 0)
                        if isinstance(v, int):
                            init_zero += v
                except Exception:
                    init_zero = 0
            if init_zero > 0:
                reduction = 1.0 - (zero_layer_after / max(1, init_zero))
                cleanup_ok = outline_layer >= 1 and reduction >= 0.5
            else:
                cleanup_ok = outline_layer >= 1 and zero_layer_after <= 2
            score = 0.4 * (present / len(keys)) + 0.6 * (1.0 if cleanup_ok else 0.3)
            s["validation_summary"] = round(min(score, 1.0), 3)
        except Exception:
            s["validation_summary"] = 0.2
    else:
        s["validation_summary"] = 0.0

    # ---- 9-10. GUI screenshots + OCR + anti-cheat -------------------------------
    try:
        from PIL import Image  # noqa: F401
        _has_pil = True
    except Exception:
        _has_pil = False
    try:
        import pytesseract
        _has_tess = True
    except Exception:
        _has_tess = False

    import hashlib

    shots = {
        "view_drawing_initial.png":   ["LibreCAD", "Layer", "Tool", "Cmd"],
        "view_layers_panel.png":      ["Layer", "OUTLINE", "0", "HIDDEN"],
        "view_after_cleanup.png":     ["LibreCAD", "Modify", "Layer"],
        "view_dimensions_added.png":  ["Dim", "Linear", "Radial", "Dimension"],
        "view_print_preview.png":     ["Print", "Preview", "A4", "Title"],
    }
    have, ocr_hit = 0, 0
    md5s = set()
    res_ok = 0
    size_ok = 0
    mtimes = []
    for fname, kws in shots.items():
        p = rd / fname
        if p.exists():
            sz = p.stat().st_size
            # Floor: anything under 5KB is treated as a placeholder, not a screenshot.
            if sz >= 5000:
                size_ok += 1
                have += 1
                try:
                    md5s.add(hashlib.md5(p.read_bytes()).hexdigest())
                except Exception:
                    pass
                mtimes.append(p.stat().st_mtime)
                if _has_pil:
                    try:
                        from PIL import Image as _Img
                        with _Img.open(p) as im:
                            w, h = im.size
                        if w >= 1024 and h >= 600:
                            res_ok += 1
                    except Exception:
                        pass
                if _has_pil and _has_tess:
                    try:
                        from PIL import Image as _Img
                        txt = pytesseract.image_to_string(_Img.open(p))
                        if any(k.lower() in txt.lower() for k in kws):
                            ocr_hit += 1
                    except Exception:
                        pass
    n_shots = len(shots)
    # Count score requires presence + md5 uniqueness + minimum resolution.
    uniq_ratio = (len(md5s) / max(1, have)) if have else 0.0
    res_ratio = res_ok / n_shots
    presence_ratio = have / n_shots
    s["gui_screenshots_count"] = round(
        0.5 * presence_ratio + 0.3 * uniq_ratio + 0.2 * res_ratio, 3
    )
    # OCR: when VLM/OCR available, demand ≥60% hit rate to count as full credit.
    if _has_pil and _has_tess:
        s["gui_screenshots_ocr"] = round(min(1.0, (ocr_hit / n_shots) / 0.6), 3)
    else:
        # Neutral but capped — never a free 1.0.
        s["gui_screenshots_ocr"] = 0.4
    # Timestamp ordering: screenshots should follow workflow order.
    expected_order = list(shots.keys())
    ordered_mtimes = []
    for fn in expected_order:
        p = rd / fn
        if p.exists() and p.stat().st_size >= 5000:
            ordered_mtimes.append(p.stat().st_mtime)
    if len(ordered_mtimes) >= 3:
        s["gui_screenshots_order"] = round(
            sum(1 for i in range(1, len(ordered_mtimes))
                if ordered_mtimes[i] >= ordered_mtimes[i-1]) /
            (len(ordered_mtimes) - 1), 3
        )
    else:
        s["gui_screenshots_order"] = 0.0

    # ---- 11. cleaned DXF landed --------------------------------------------------
    cleaned = Path("/tmp_workspace/dxf_project/bracket_clean.dxf")
    s["cleaned_dxf_present"] = 1.0 if (cleaned.exists() and cleaned.stat().st_size > 500) else 0.0

    # ---- 12. VLM rubric ----------------------------------------------------------
    try:
        from _judge_helper import vlm_score_rubric
    except Exception:
        vlm_score_rubric = None

    vlm_keys = ["vlm_librecad_real", "vlm_dimensions_visible", "vlm_titleblock_visible"]
    _vlm_available = False
    if vlm_score_rubric is not None:
        sample = [str(rd / n) for n in shots if (rd / n).exists()]
        render_p = rep / "render_final.png"
        if render_p.exists():
            sample.append(str(render_p))
        sample = sample[:5]
        if sample:
            rubric = {
                "vlm_librecad_real": "至少 1 张截图明确显示 LibreCAD 主窗口（含菜单栏 / 工具栏 / 命令行面板 / 图层面板等多种 LibreCAD UI 元素），不是裸黑屏或纯渲染图",
                "vlm_dimensions_visible": "在 dimensions_added / render_final 中能看到带数字的尺寸标注线（线性距离 + 半径/直径），且尺寸文本可读",
                "vlm_titleblock_visible": "print_preview 或 render_final 中右下角能看到包含图号/比例/日期等多行文字的标题栏区域",
            }
            try:
                vlm = vlm_score_rubric(
                    sample, rubric,
                    instruction="评估 DXF 机械图清理 + 标注 + 出图任务的截图与渲染。",
                ) or {}
            except Exception:
                vlm = {}
            for k in vlm_keys:
                v = vlm.get(k, 0.0)
                try:
                    s[k] = float(v)
                except Exception:
                    s[k] = 0.0
            _vlm_available = True
        else:
            for k in vlm_keys:
                s[k] = 0.0
    else:
        for k in vlm_keys:
            s[k] = 0.4  # capped neutral when judge helper unavailable

    # ---- aggregate (weighted: core 60% / gui 30% / aux 10%) ---------------------
    core_keys = [
        "duplicates_initial", "duplicates_clean",
        "dimensions_added", "validation_summary", "cleaned_dxf_present",
        "render_present",
    ]
    gui_keys = [
        "gui_screenshots_count", "gui_screenshots_ocr",
        "gui_screenshots_order",
    ] + vlm_keys
    aux_keys = ["entities_initial", "audit_initial", "audit_after"]

    def _avg(keys):
        vals = [s.get(k, 0.0) for k in keys if isinstance(s.get(k, 0.0), (int, float))]
        return sum(vals) / max(1, len(vals))

    core = _avg(core_keys)
    gui = _avg(gui_keys)
    aux = _avg(aux_keys)
    base = 0.6 * core + 0.3 * gui + 0.1 * aux

    # ---- hard gates (multi-layer, tightened) ------------------------------------
    # Core delivery gates.
    if s.get("cleaned_dxf_present", 0) == 0:
        base = min(base, 0.35)
    if s.get("duplicates_initial", 0) < 0.5:
        base = min(base, 0.40)
    if s.get("duplicates_clean", 0) < 0.5:
        base = min(base, 0.40)
    if s.get("dimensions_added", 0) < 0.5:
        base = min(base, 0.45)
    if s.get("render_present", 0) == 0:
        base = min(base, 0.45)
    if s.get("validation_summary", 0) < 0.5:
        base = min(base, 0.50)
    # GUI evidence gates (anti-cheat: forbids "no real GUI run" path to a high score).
    if s.get("gui_screenshots_count", 0) < 0.7:
        base = min(base, 0.45)
    if s.get("gui_screenshots_count", 0) < 0.4:
        base = min(base, 0.30)
    if _has_pil and _has_tess and s.get("gui_screenshots_ocr", 0) < 0.5:
        base = min(base, 0.55)
    # VLM gates.
    vlm_avg = sum(s.get(k, 0.0) for k in vlm_keys) / len(vlm_keys)
    if _vlm_available:
        if vlm_avg < 0.6:
            base = min(base, 0.55)
        if vlm_avg < 0.4:
            base = min(base, 0.40)
    else:
        # No VLM → never let a run reach satisfactory.
        base = min(base, 0.60)

    s["overall_score"] = round(max(0.0, min(1.0, base)), 3)
    return s

Workspace Path

workspace/SPA/task_5_dxf_bracket_repair

Skills

Env

Warmup

echo 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 | base64 -d | bash