feat: 复盘四周期手动上传，移除 AI 识别预填

固定 5m/15m/1h/4h 四槽截图上传与详情四宫格展示；自动 K 线默认关闭且与手动上传互斥。

Co-authored-by: Cursor <cursoragent@cursor.com>

lib/instance/journal_images_lib.py

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+"""复盘记录：多周期截图上传、存储与读取（三所共用）。"""
+from __future__ import annotations
+
+import json
+import os
+from typing import Any, Callable, Dict, List, Mapping, Optional, Sequence
+
+JOURNAL_UPLOAD_TFS: tuple[str, ...] = ("5m", "15m", "1h", "4h")
+JOURNAL_UPLOAD_ALLOWED_EXT = frozenset({".png", ".jpg", ".jpeg", ".webp", ".gif", ".bmp"})
+
+
+def journal_upload_field_name(tf: str) -> str:
+    return f"screenshot_{tf}"
+
+
+def _safe_ext(filename: str) -> str:
+    ext = os.path.splitext(str(filename or ""))[1].lower()
+    return ext if ext in JOURNAL_UPLOAD_ALLOWED_EXT else ".png"
+
+
+def save_journal_slot_uploads(
+    files,
+    entry_id: str,
+    upload_folder: str,
+    *,
+    secure_filename_fn: Callable[[str], str],
+) -> List[Dict[str, str]]:
+    """保存四槽位手动截图，返回 [{"tf":"5m","file":"journal_xxx_5m.png"}, ...]。"""
+    saved: List[Dict[str, str]] = []
+    if not entry_id or not upload_folder:
+        return saved
+    os.makedirs(upload_folder, exist_ok=True)
+    for tf in JOURNAL_UPLOAD_TFS:
+        f = files.get(journal_upload_field_name(tf)) if files else None
+        if not f or not getattr(f, "filename", None):
+            continue
+        ext = _safe_ext(f.filename)
+        fname = secure_filename_fn(f"journal_{entry_id}_{tf}{ext}")
+        if not fname:
+            continue
+        path = os.path.join(upload_folder, fname)
+        f.save(path)
+        saved.append({"tf": tf, "file": fname})
+    return saved
+
+
+def images_json_dumps(items: Sequence[Mapping[str, str]]) -> Optional[str]:
+    if not items:
+        return None
+    return json.dumps(list(items), ensure_ascii=False, separators=(",", ":"))
+
+
+def parse_images_json(raw: Any) -> List[Dict[str, str]]:
+    if not raw:
+        return []
+    if isinstance(raw, list):
+        data = raw
+    else:
+        try:
+            data = json.loads(str(raw))
+        except (TypeError, ValueError, json.JSONDecodeError):
+            return []
+    if not isinstance(data, list):
+        return []
+    out: List[Dict[str, str]] = []
+    for item in data:
+        if not isinstance(item, dict):
+            continue
+        tf = str(item.get("tf") or "").strip()
+        file = str(item.get("file") or "").strip()
+        if file:
+            out.append({"tf": tf, "file": file})
+    return out
+
+
+def primary_journal_image(
+    manual_images: Sequence[Mapping[str, str]],
+    *,
+    fallback: Optional[str] = None,
+) -> Optional[str]:
+    if manual_images:
+        return str(manual_images[0].get("file") or "").strip() or None
+    return fallback
+
+
+def enrich_journal_api_item(item: Dict[str, Any]) -> Dict[str, Any]:
+    """API 输出：解析 images_json，兼容旧单图 image 字段。"""
+    images = parse_images_json(item.get("images_json"))
+    if not images and item.get("image"):
+        images = [{"tf": "", "file": str(item["image"]).strip()}]
+    item["images"] = images
+    return item
+
+
+def journal_image_paths(row: Any, upload_folder: str) -> List[str]:
+    """删除 / AI 附图：收集本条复盘所有本地图片路径（去重）。"""
+    upload_folder = os.path.abspath(upload_folder or "")
+    paths: List[str] = []
+    seen = set()
+
+    def _add(name: Optional[str]) -> None:
+        if not name:
+            return
+        p = os.path.abspath(os.path.join(upload_folder, str(name).strip()))
+        if os.path.isfile(p) and p not in seen:
+            seen.add(p)
+            paths.append(p)
+
+    try:
+        keys = row.keys() if hasattr(row, "keys") else ()
+    except Exception:
+        keys = ()
+
+    if "images_json" in keys and row["images_json"]:
+        for img in parse_images_json(row["images_json"]):
+            _add(img.get("file"))
+    if "image" in keys:
+        _add(row["image"])
+    return paths